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• Published: 16 November 2020

Exercise/physical activity and health outcomes: an overview of Cochrane systematic reviews

• Pawel Posadzki 1 , 2 ,
• Dawid Pieper   ORCID: orcid.org/0000-0002-0715-5182 3 ,
• Ram Bajpai 4 ,
• Hubert Makaruk 5 ,
• Nadja Könsgen 3 ,
• Annika Lena Neuhaus 3 &
• Monika Semwal 6  

BMC Public Health volume  20 , Article number:  1724 ( 2020 ) Cite this article

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Sedentary lifestyle is a major risk factor for noncommunicable diseases such as cardiovascular diseases, cancer and diabetes. It has been estimated that approximately 3.2 million deaths each year are attributable to insufficient levels of physical activity. We evaluated the available evidence from Cochrane systematic reviews (CSRs) on the effectiveness of exercise/physical activity for various health outcomes.

Overview and meta-analysis. The Cochrane Library was searched from 01.01.2000 to issue 1, 2019. No language restrictions were imposed. Only CSRs of randomised controlled trials (RCTs) were included. Both healthy individuals, those at risk of a disease, and medically compromised patients of any age and gender were eligible. We evaluated any type of exercise or physical activity interventions; against any types of controls; and measuring any type of health-related outcome measures. The AMSTAR-2 tool for assessing the methodological quality of the included studies was utilised.

Hundred and fifty CSRs met the inclusion criteria. There were 54 different conditions. Majority of CSRs were of high methodological quality. Hundred and thirty CSRs employed meta-analytic techniques and 20 did not. Limitations for studies were the most common reasons for downgrading the quality of the evidence. Based on 10 CSRs and 187 RCTs with 27,671 participants, there was a 13% reduction in mortality rates risk ratio (RR) 0.87 [95% confidence intervals (CI) 0.78 to 0.96]; I 2  = 26.6%, [prediction interval (PI) 0.70, 1.07], median effect size (MES) = 0.93 [interquartile range (IQR) 0.81, 1.00]. Data from 15 CSRs and 408 RCTs with 32,984 participants showed a small improvement in quality of life (QOL) standardised mean difference (SMD) 0.18 [95% CI 0.08, 0.28]; I 2  = 74.3%; PI -0.18, 0.53], MES = 0.20 [IQR 0.07, 0.39]. Subgroup analyses by the type of condition showed that the magnitude of effect size was the largest among patients with mental health conditions.

There is a plethora of CSRs evaluating the effectiveness of physical activity/exercise. The evidence suggests that physical activity/exercise reduces mortality rates and improves QOL with minimal or no safety concerns.

Trial registration

Registered in PROSPERO ( CRD42019120295 ) on 10th January 2019.

Peer Review reports

The World Health Organization (WHO) defines physical activity “as any bodily movement produced by skeletal muscles that requires energy expenditure” [ 1 ]. Therefore, physical activity is not only limited to sports but also includes walking, running, swimming, gymnastics, dance, ball games, and martial arts, for example. In the last years, several organizations have published or updated their guidelines on physical activity. For example, the Physical Activity Guidelines for Americans, 2nd edition, provides information and guidance on the types and amounts of physical activity that provide substantial health benefits [ 2 ]. The evidence about the health benefits of regular physical activity is well established and so are the risks of sedentary behaviour [ 2 ]. Exercise is dose dependent, meaning that people who achieve cumulative levels several times higher than the current recommended minimum level have a significant reduction in the risk of breast cancer, colon cancer, diabetes, ischemic heart disease, and ischemic stroke events [ 3 ]. Benefits of physical activity have been reported for numerous outcomes such as mortality [ 4 , 5 ], cognitive and physical decline [ 5 , 6 , 7 ], glycaemic control [ 8 , 9 ], pain and disability [ 10 , 11 ], muscle and bone strength [ 12 ], depressive symptoms [ 13 ], and functional mobility and well-being [ 14 , 15 ]. Overall benefits of exercise apply to all bodily systems including immunological [ 16 ], musculoskeletal [ 17 ], respiratory [ 18 ], and hormonal [ 19 ]. Specifically for the cardiovascular system, exercise increases fatty acid oxidation, cardiac output, vascular smooth muscle relaxation, endothelial nitric oxide synthase expression and nitric oxide availability, improves plasma lipid profiles [ 15 ] while at the same time reducing resting heart rate and blood pressure, aortic valve calcification, and vascular resistance [ 20 ].

However, the degree of all the above-highlighted benefits vary considerably depending on individual fitness levels, types of populations, age groups and the intensity of different physical activities/exercises [ 21 ]. The majority of guidelines in different countries recommend a goal of 150 min/week of moderate-intensity aerobic physical activity (or equivalent of 75 min of vigorous-intensity) [ 22 ] with differences for cardiovascular disease [ 23 ] or obesity prevention [ 24 ] or age groups [ 25 ].

There is a plethora of systematic reviews published by the Cochrane Library critically evaluating the effectiveness of physical activity/exercise for various health outcomes. Cochrane systematic reviews (CSRs) are known to be a source of high-quality evidence. Thus, it is not only timely but relevant to evaluate the current knowledge, and determine the quality of the evidence-base, and the magnitude of the effect sizes given the negative lifestyle changes and rising physical inactivity-related burden of diseases. This overview will identify the breadth and scope to which CSRs have appraised the evidence for exercise on health outcomes; and this will help in directing future guidelines and identifying current gaps in the literature.

The objectives of this research were to a. answer the following research questions: in children, adolescents and adults (both healthy and medically compromised) what are the effects (and adverse effects) of exercise/physical activity in improving various health outcomes (e.g., pain, function, quality of life) reported in CSRs; b. estimate the magnitude of the effects by pooling the results quantitatively; c. evaluate the strength and quality of the existing evidence; and d. create recommendations for future researchers, patients, and clinicians.

Our overview was registered with PROSPERO (CRD42019120295) on 10th January 2019. The Cochrane Handbook for Systematic Reviews of interventions and Preferred Reporting Items for Overviews of Reviews were adhered to while writing and reporting this overview [ 26 , 27 ].

Search strategy and selection criteria

We followed the practical guidance for conducting overviews of reviews of health care interventions [ 28 ] and searched the Cochrane Database of Systematic Reviews (CDSR), 2019, Issue 1, on the Cochrane Library for relevant papers using the search strategy: (health) and (exercise or activity or physical). The decision to seek CSRs only was based on three main aspects. First, high quality (CSRs are considered to be the ‘gold methodological standard’) [ 29 , 30 , 31 ]. Second, data saturation (enough high-quality evidence to reach meaningful conclusions based on CSRs only). Third, including non-CSRs would have heavily increased the issue of overlapping reviews (also affecting data robustness and credibility of conclusions). One reviewer carried out the searches. The study screening and selection process were performed independently by two reviewers. We imported all identified references into reference manager software EndNote (X8). Any disagreements were resolved by discussion between the authors with third overview author acting as an arbiter, if necessary.

We included CSRs of randomised controlled trials (RCTs) involving both healthy individuals and medically compromised patients of any age and gender. Only CSRs assessing exercise or physical activity as a stand-alone intervention were included. This included interventions that could initially be taught by a professional or involve ongoing supervision (the WHO definition). Complex interventions e.g., assessing both exercise/physical activity and behavioural changes were excluded if the health effects of the interventions could not have been attributed to exercise distinctly.

Any types of controls were admissible. Reviews evaluating any type of health-related outcome measures were deemed eligible. However, we excluded protocols or/and CSRs that have been withdrawn from the Cochrane Library as well as reviews with no included studies.

Data analysis

Three authors (HM, ALN, NK) independently extracted relevant information from all the included studies using a custom-made data collection form. The methodological quality of SRs included was independently evaluated by same reviewers using the AMSTAR-2 tool [ 32 ]. Any disagreements on data extraction or CSR quality were resolved by discussion. The entire dataset was validated by three authors (PP, MS, DP) and any discrepant opinions were settled through discussions.

The results of CSRs are presented in a narrative fashion using descriptive tables. Where feasible, we presented outcome measures across CSRs. Data from the subset of homogeneous outcomes were pooled quantitatively using the approach previously described by Bellou et al. and Posadzki et al. [ 33 , 34 ]. For mortality and quality of life (QOL) outcomes, the number of participants and RCTs involved in the meta-analysis, summary effect sizes [with 95% confidence intervals (CI)] using random-effects model were calculated. For binary outcomes, we considered relative risks (RRs) as surrogate measures of the corresponding odds ratio (OR) or risk ratio/hazard ratio (HR). To stabilise the variance and normalise the distributions, we transformed RRs into their natural logarithms before pooling the data (a variation was allowed, however, it did not change interpretation of results) [ 35 ]. The standard error (SE) of the natural logarithm of RR was derived from the corresponding CIs, which was either provided in the study or calculated with standard formulas [ 36 ]. Binary outcomes reported as risk difference (RD) were also meta-analysed if two more estimates were available. For continuous outcomes, we only meta-analysed estimates that were available as standardised mean difference (SMD), and estimates reported with mean differences (MD) for QOL were presented separately in a supplementary Table  9 . To estimate the overall effect size, each study was weighted by the reciprocal of its variance. Random-effects meta-analysis, using DerSimonian and Laird method [ 37 ] was applied to individual CSR estimates to obtain a pooled summary estimate for RR or SMD. The 95% prediction interval (PI) was also calculated (where ≥3 studies were available), which further accounts for between-study heterogeneity and estimates the uncertainty around the effect that would be anticipated in a new study evaluating that same association. I -squared statistic was used to measure between study heterogeneity; and its various thresholds (small, substantial and considerable) were interpreted considering the size and direction of effects and the p -value from Cochran’s Q test ( p  < 0.1 considered as significance) [ 38 ]. Wherever possible, we calculated the median effect size (with interquartile range [IQR]) of each CSR to interpret the direction and magnitude of the effect size. Sub-group analyses are planned for type and intensity of the intervention; age group; gender; type and/or severity of the condition, risk of bias in RCTs, and the overall quality of the evidence (Grading of Recommendations Assessment, Development and Evaluation (GRADE) criteria). To assess overlap we calculated the corrected covered area (CCA) [ 39 ]. All statistical analyses were conducted on Stata statistical software version 15.2 (StataCorp LLC, College Station, Texas, USA).

The searches generated 280 potentially relevant CRSs. After removing of duplicates and screening, a total of 150 CSRs met our eligibility criteria [ 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 , 75 , 76 , 77 , 78 , 79 , 80 , 81 , 82 , 83 , 84 , 85 , 86 , 87 , 88 , 89 , 90 , 91 , 92 , 93 , 94 , 95 , 96 , 97 , 98 , 99 , 100 , 101 , 102 , 103 , 104 , 105 , 106 , 107 , 108 , 109 , 110 , 111 , 112 , 113 , 114 , 115 , 116 , 117 , 118 , 119 , 120 , 121 , 122 , 123 , 124 , 125 , 126 , 127 , 128 , 129 , 130 , 131 , 132 , 133 , 134 , 135 , 136 , 137 , 138 , 139 , 140 , 141 , 142 , 143 , 144 , 145 , 146 , 147 , 148 , 149 , 150 , 151 , 152 , 153 , 154 , 155 , 156 , 157 , 158 , 159 , 160 , 161 , 162 , 163 , 164 , 165 , 166 , 167 , 168 , 169 , 170 , 171 , 172 , 173 , 174 , 175 , 176 , 177 , 178 , 179 , 180 , 181 , 182 , 183 , 184 , 185 , 186 , 187 , 188 , 189 ] (Fig.  1 ). Reviews were published between September 2002 and December 2018. A total of 130 CSRs employed meta-analytic techniques and 20 did not. The total number of RCTs in the CSRs amounted to 2888; with 485,110 participants (mean = 3234, SD = 13,272). The age ranged from 3 to 87 and gender distribution was inestimable. The main characteristics of included reviews are summarised in supplementary Table  1 . Supplementary Table  2 summarises the effects of physical activity/exercise on health outcomes. Conclusions from CSRs are listed in supplementary Table  3 . Adverse effects are listed in supplementary Table  4 . Supplementary Table  5 presents summary of withdrawals/non-adherence. The methodological quality of CSRs is presented in supplementary Table  6 . Supplementary Table  7 summarises studies assessed at low risk of bias (by the authors of CSRs). GRADE-ings of the review’s main comparison are listed in supplementary Table  8 .

Study selection process

There were 54 separate populations/conditions, considerable range of interventions and comparators, co-interventions, and outcome measures. For detailed description of interventions, please refer to the supplementary tables . Most commonly measured outcomes were - function 112 (75%), QOL 83 (55%), AEs 70 (47%), pain 41 (27%), mortality 28 (19%), strength 30 (20%), costs 47 (31%), disability 14 (9%), and mental health in 35 (23%) CSRs.

There was a 13% reduction in mortality rates risk ratio (RR) 0.87 [95% CI 0.78 to 0.96]; I 2  = 26.6%, [PI 0.70, 1.07], median effect size (MES) = 0.93 [interquartile range (IQR) 0.81, 1.00]; 10 CSRs, 187 RCTs, 27,671 participants) following exercise when compared with various controls (Table 1 ). This reduction was smaller in ‘other groups’ of patients when compared to cardiovascular diseases (CVD) patients - RR 0.97 [95% CI 0.65, 1.45] versus 0.85 [0.76, 0.96] respectively. The effects of exercise were not intensity or frequency dependent. Sessions more than 3 times per week exerted a smaller reduction in mortality as compared with sessions of less than 3 times per week RR 0.87 [95% CI 0.78, 0.98] versus 0.63 [0.39, 1.00]. Subgroup analyses by risk of bias (ROB) in RCTs showed that RCTs at low ROB exerted smaller reductions in mortality when compared to RCTs at an unclear or high ROB, RR 0.90 [95% CI 0.78, 1.02] versus 0.72 [0.42, 1.22] versus 0.86 [0.69, 1.06] respectively. CSRs with moderate quality of evidence (GRADE), showed slightly smaller reductions in mortality when compared with CSRs that relied on very low to low quality evidence RR 0.88 [95% CI 0.79, 0.98] versus 0.70 [0.47, 1.04].

Exercise also showed an improvement in QOL, standardised mean difference (SMD) 0.18 [95% CI 0.08, 0.28]; I 2  = 74.3%; PI -0.18, 0.53], MES = 0.20 [IQR 0.07, 0.39]; 15 CSRs, 408 RCTs, 32,984 participants) when compared with various controls (Table 2 ). These improvements were greater observed for health related QOL when compared to overall QOL SMD 0.30 [95% CI 0.21, 0.39] vs 0.06 [− 0.08, 0.20] respectively. Again, the effects of exercise were duration and frequency dependent. For instance, sessions of more than 90 mins exerted a greater improvement in QOL as compared with sessions up to 90 min SMD 0.24 [95% CI 0.11, 0.37] versus 0.22 [− 0.30, 0.74]. Subgroup analyses by the type of condition showed that the magnitude of effect was the largest among patients with mental health conditions, followed by CVD and cancer. Physical activity exerted negative effects on QOL in patients with respiratory conditions (2 CSRs, 20 RCTs with 601 patients; SMD -0.97 [95% CI -1.43, 0.57]; I 2  = 87.8%; MES = -0.46 [IQR-0.97, 0.05]). Subgroup analyses by risk of bias (ROB) in RCTs showed that RCTs at low or unclear ROB exerted greater improvements in QOL when compared to RCTs at a high ROB SMD 0.21 [95% CI 0.10, 0.31] versus 0.17 [0.03, 0.31]. Analogically, CSRs with moderate to high quality of evidence showed slightly greater improvements in QOL when compared with CSRs that relied on very low to low quality evidence SMD 0.19 [95% CI 0.05, 0.33] versus 0.15 [− 0.02, 0.32]. Please also see supplementary Table  9 more studies reporting QOL outcomes as mean difference (not quantitatively synthesised herein).

Adverse events (AEs) were reported in 100 (66.6%) CSRs; and not reported in 50 (33.3%). The number of AEs ranged from 0 to 84 in the CSRs. The number was inestimable in 83 (55.3%) CSRs. Ten (6.6%) reported no occurrence of AEs. Mild AEs were reported in 28 (18.6%) CSRs, moderate in 9 (6%) and serious/severe in 20 (13.3%). There were 10 deaths and in majority of instances, the causality was not attributed to exercise. For this outcome, we were unable to pool the data as effect sizes were too heterogeneous (Table 3 ).

In 38 CSRs, the total number of trials reporting withdrawals/non-adherence was inestimable. There were different ways of reporting it such as adherence or attrition (high in 23.3% of CSRs) as well as various effect estimates including %, range, total numbers, MD, RD, RR, OR, mean and SD. The overall pooled estimates are reported in Table 3 .

Of all 16 domains of the AMSTAR-2 tool, 1876 (78.1%) scored ‘yes’, 76 (3.1%) ‘partial yes’; 375 (15.6%) ‘no’, and ‘not applicable’ in 25 (1%) CSRs. Ninety-six CSRs (64%) were scored as ‘no’ on reporting sources of funding for the studies followed by 88 (58.6%) failing to explain the selection of study designs for inclusion. One CSR (0.6%) each were judged as ‘no’ for reporting any potential sources of conflict of interest, including any funding for conducting the review as well for performing study selection in duplicate.

In 102 (68%) CSRs, there was predominantly a high risk of bias in RCTs. In 9 (6%) studies, this was reported as a range, e.g., low or unclear or low to high. Two CSRs used different terminology i.e., moderate methodological quality; and the risk of bias was inestimable in one CSR. Sixteen (10.6%) CSRs did not identify any studies (RCTs) at low risk of random sequence generation, 28 (18.6%) allocation concealment, 28 (18.6%) performance bias, 84 (54%) detection bias, 35 (23.3%) attrition bias, 18 (12%) reporting bias, and 29 (19.3%) other bias.

In 114 (76%) CSRs, limitation of studies was the main reason for downgrading the quality of the evidence followed by imprecision in 98 (65.3%) and inconsistency in 68 (45.3%). Publication bias was the least frequent reason for downgrading in 26 (17.3%) CSRs. Ninety-one (60.7%) CSRs reached equivocal conclusions, 49 (32.7%) reviews reached positive conclusions and 10 (6.7%) reached negative conclusions (as judged by the authors of CSRs).

In this systematic review of CSRs, we found a large body of evidence on the beneficial effects of physical activity/exercise on health outcomes in a wide range of heterogeneous populations. Our data shows a 13% reduction in mortality rates among 27,671 participants, and a small improvement in QOL and health-related QOL following various modes of physical activity/exercises. This means that both healthy individuals and medically compromised patients can significantly improve function, physical and mental health; or reduce pain and disability by exercising more [ 190 ]. In line with previous findings [ 191 , 192 , 193 , 194 ], where a dose-specific reduction in mortality has been found, our data shows a greater reduction in mortality in studies with longer follow-up (> 12 months) as compared to those with shorter follow-up (< 12 months). Interestingly, we found a consistent pattern in the findings, the higher the quality of evidence and the lower the risk of bias in primary studies, the smaller reductions in mortality. This pattern is observational in nature and cannot be over-generalised; however this might mean less certainty in the estimates measured. Furthermore, we found that the magnitude of the effect size was the largest among patients with mental health conditions. A possible mechanism of action may involve elevated levels of brain-derived neurotrophic factor or beta-endorphins [ 195 ].

We found the issue of poor reporting or underreporting of adherence/withdrawals in over a quarter of CSRs (25.3%). This is crucial both for improving the accuracy of the estimates at the RCT level as well as maintaining high levels of physical activity and associated health benefits at the population level.

Even the most promising interventions are not entirely risk-free; and some minor AEs such as post-exercise pain and soreness or discomfort related to physical activity/exercise have been reported. These were typically transient; resolved within a few days; and comparable between exercise and various control groups. However worryingly, the issue of poor reporting or underreporting of AEs has been observed in one third of the CSRs. Transparent reporting of AEs is crucial for identifying patients at risk and mitigating any potential negative or unintended consequences of the interventions.

High risk of bias of the RCTs evaluated was evident in more than two thirds of the CSRs. For example, more than half of reviews identified high risk of detection bias as a major source of bias suggesting that lack of blinding is still an issue in trials of behavioural interventions. Other shortcomings included insufficiently described randomisation and allocation concealment methods and often poor outcome reporting. This highlights the methodological challenges in RCTs of exercise and the need to counterbalance those with the underlying aim of strengthening internal and external validity of these trials.

Overall, high risk of bias in the primary trials was the main reason for downgrading the quality of the evidence using the GRADE criteria. Imprecision was frequently an issue, meaning the effective sample size was often small; studies were underpowered to detect the between-group differences. Pooling too heterogeneous results often resulted in inconsistent findings and inability to draw any meaningful conclusions. Indirectness and publication bias were lesser common reasons for downgrading. However, with regards to the latter, the generally accepted minimum number of 10 studies needed for quantitatively estimate the funnel plot asymmetry was not present in 69 (46%) CSRs.

Strengths of this research are the inclusion of large number of ‘gold standard’ systematic reviews, robust screening, data extractions and critical methodological appraisal. Nevertheless, some weaknesses need to be highlighted when interpreting findings of this overview. For instance, some of these CSRs analysed the same primary studies (RCTs) but, arrived at slightly different conclusions. Using, the Pieper et al. [ 39 ] formula, the amount of overlap ranged from 0.01% for AEs to 0.2% for adherence, which indicates slight overlap. All CSRs are vulnerable to publication bias [ 196 ] - hence the conclusions generated by them may be false-positive. Also, exercise was sometimes part of a complex intervention; and the effects of physical activity could not be distinguished from co-interventions. Often there were confounding effects of diet, educational, behavioural or lifestyle interventions; selection, and measurement bias were inevitably inherited in this overview too. Also, including CSRs only might lead to selection bias; and excluding reviews published before 2000 might limit the overall completeness and applicability of the evidence. A future update should consider these limitations, and in particular also including non-CSRs.

Conclusions

Trialists must improve the quality of primary studies. At the same time, strict compliance with the reporting standards should be enforced. Authors of CSRs should better explain eligibility criteria and report sources of funding for the primary studies. There are still insufficient physical activity trends worldwide amongst all age groups; and scalable interventions aimed at increasing physical activity levels should be prioritized [ 197 ]. Hence, policymakers and practitioners need to design and implement comprehensive and coordinated strategies aimed at targeting physical activity programs/interventions, health promotion and disease prevention campaigns at local, regional, national, and international levels [ 198 ].

Availability of data and materials

Data sharing is not applicable to this article as no raw data were analysed during the current study. All information in this article is based on published systematic reviews.

Abbreviations

Adverse events

Cardiovascular diseases

Cochrane Database of Systematic Reviews

Cochrane systematic reviews

Confidence interval

Grading of Recommendations Assessment, Development and Evaluation

Hazard ratio

Interquartile range

Mean difference

Prediction interval

Quality of life

Randomised controlled trials

Relative risk

Risk difference

Risk of bias

Standard error

Standardised mean difference

World Health Organization

https://www.who.int/dietphysicalactivity/pa/en/ . (Accessed 8 June 2020).

Piercy KL, Troiano RP, Ballard RM, Carlson SA, Fulton JE, Galuska DA, George SM, Olson RD. The physical activity guidelines for AmericansPhysical activity guidelines for AmericansPhysical activity guidelines for Americans. Jama. 2018;320(19):2020–8.

PubMed   Google Scholar  

Kyu HH, Bachman VF, Alexander LT, Mumford JE, Afshin A, Estep K, Veerman JL, Delwiche K, Iannarone ML, Moyer ML, et al. Physical activity and risk of breast cancer, colon cancer, diabetes, ischemic heart disease, and ischemic stroke events: systematic review and dose-response meta-analysis for the global burden of disease study 2013. BMJ. 2016;354:i3857.

PubMed   PubMed Central   Google Scholar  

Abell B, Glasziou P, Hoffmann T. The contribution of individual exercise training components to clinical outcomes in randomised controlled trials of cardiac rehabilitation: a systematic review and meta-regression. Sports Med Open. 2017;3(1):19.

Anderson D, Seib C, Rasmussen L. Can physical activity prevent physical and cognitive decline in postmenopausal women? A systematic review of the literature. Maturitas. 2014;79(1):14–33.

Barbaric M, Brooks E, Moore L, Cheifetz O. Effects of physical activity on cancer survival: a systematic review. Physiother Can. 2010;62(1):25–34.

Barlow PA, Otahal P, Schultz MG, Shing CM, Sharman JE. Low exercise blood pressure and risk of cardiovascular events and all-cause mortality: systematic review and meta-analysis. Atherosclerosis. 2014;237(1):13–22.

CAS   PubMed   Google Scholar  

Aljawarneh YM, Wardell DW, Wood GL, Rozmus CL. A systematic review of physical activity and exercise on physiological and biochemical outcomes in children and adolescents with type 1 diabetes. J Nurs Scholarsh. 2019.

Chastin SFM, De Craemer M, De Cocker K, Powell L, Van Cauwenberg J, Dall P, Hamer M, Stamatakis E. How does light-intensity physical activity associate with adult cardiometabolic health and mortality? Systematic review with meta-analysis of experimental and observational studies. Br J Sports Med. 2019;53(6):370–6.

Abdulla SY, Southerst D, Cote P, Shearer HM, Sutton D, Randhawa K, Varatharajan S, Wong JJ, Yu H, Marchand AA, et al. Is exercise effective for the management of subacromial impingement syndrome and other soft tissue injuries of the shoulder? A systematic review by the Ontario protocol for traffic injury management (OPTIMa) collaboration. Man Ther. 2015;20(5):646–56.

Alanazi MH, Parent EC, Dennett E. Effect of stabilization exercise on back pain, disability and quality of life in adults with scoliosis: a systematic review. Eur J Phys Rehabil Med. 2018;54(5):647–53.

Adsett JA, Mudge AM, Morris N, Kuys S, Paratz JD. Aquatic exercise training and stable heart failure: a systematic review and meta-analysis. Int J Cardiol. 2015;186:22–8.

Adamson BC, Ensari I, Motl RW. Effect of exercise on depressive symptoms in adults with neurologic disorders: a systematic review and meta-analysis. Arch Phys Med Rehabil. 2015;96(7):1329–38.

Abdin S, Welch RK, Byron-Daniel J, Meyrick J. The effectiveness of physical activity interventions in improving well-being across office-based workplace settings: a systematic review. Public Health. 2018;160:70–6.

Albalawi H, Coulter E, Ghouri N, Paul L. The effectiveness of structured exercise in the south Asian population with type 2 diabetes: a systematic review. Phys Sportsmed. 2017;45(4):408–17.

Sellami M, Gasmi M, Denham J, Hayes LD, Stratton D, Padulo J, Bragazzi N. Effects of acute and chronic exercise on immunological parameters in the elderly aged: can physical activity counteract the effects of aging? Front Immunol. 2018;9:2187.

Hagen KB, Dagfinrud H, Moe RH, Østerås N, Kjeken I, Grotle M, Smedslund G. Exercise therapy for bone and muscle health: an overview of systematic reviews. BMC Med. 2012;10(1):167.

Burton DA, Stokes K, Hall GM. Physiological effects of exercise. Contin Educ Anaesth Crit Care Pain. 2004;4(6):185–8.

Google Scholar  

Kraemer WJ, Ratamess NA. Hormonal responses and adaptations to resistance exercise and training. Sports Med. 2005;35(4):339–61.

Nystoriak MA, Bhatnagar A. Cardiovascular effects and benefits of exercise. Front Cardiovasc Med. 2018;5:135.

CAS   PubMed   PubMed Central   Google Scholar  

Vina J, Sanchis-Gomar F, Martinez-Bello V, Gomez-Cabrera MC. Exercise acts as a drug; the pharmacological benefits of exercise. Br J Pharmacol. 2012;167(1):1–12.

Warburton DER, Bredin SSD. Health benefits of physical activity: a systematic review of current systematic reviews. Curr Opin Cardiol. 2017;32(5):541–56.

Excellence NIfHaC: Cardiovascular disease prevention public health guideline [PH25] Published date: June 2010. Available at: https://www.nice.org.uk/guidance/ph25/resources/cardiovascular-disease-prevention-pdf-1996238687173 .

Excellence NIfHaC: Obesity prevention clinical guideline [CG43] published date: December 2006 Last updated: March 2015. Available at: https://www.nice.org.uk/guidance/cg43/resources/obesity-prevention-pdf-975445344709 .

Excellence NIfHaC: Physical activity for children and young people public health guideline [PH17] Published date: January 2009. Available at: https://www.nice.org.uk/guidance/ph17/resources/physical-activity-for-children-and-young-people-pdf-1996181580229 .

Higgins J, Green S. Cochrane Handbook for Systematic Reviews of Interventions. Version 6 [updated September 2018] edition. Available from www.cochrane-handbook.org : The Cochrane Collaboration, 2011. 2011.

Bougioukas KI, Liakos A, Tsapas A, Ntzani E, Haidich A-B. Preferred reporting items for overviews of systematic reviews including harms checklist: a pilot tool to be used for balanced reporting of benefits and harms. J Clin Epidemiol. 2018;93:9–24.

Pollock M, Fernandes RM, Newton AS, Scott SD, Hartling L. The impact of different inclusion decisions on the comprehensiveness and complexity of overviews of reviews of healthcare interventions. Syst Rev. 2019;8(1):18.

Handoll H, Madhok R. Quality of Cochrane reviews. Another study found that most Cochrane reviews are of a good standard. BMJ. 2002;324(7336):545.

Petticrew M, Wilson P, Wright K, Song F. Quality of Cochrane reviews. Quality of Cochrane reviews is better than that of non-Cochrane reviews. BMJ. 2002;324(7336):545.

Shea B, Moher D, Graham I, Pham B, Tugwell P. A comparison of the quality of Cochrane reviews and systematic reviews published in paper-based journals. Eval Health Prof. 2002;25(1):116–29.

Shea BJ, Reeves BC, Wells G, Thuku M, Hamel C, Moran J, Moher D, Tugwell P, Welch V, Kristjansson E, et al. AMSTAR 2: a critical appraisal tool for systematic reviews that include randomised or non-randomised studies of healthcare interventions, or both. BMJ. 2017;358:j4008.

Posadzki PP, Bajpai R, Kyaw BM, Roberts NJ, Brzezinski A, Christopoulos GI, Divakar U, Bajpai S, Soljak M, Dunleavy G, et al. Melatonin and health: an umbrella review of health outcomes and biological mechanisms of action. BMC Med. 2018;16(1):18.

Bellou V, Belbasis L, Tzoulaki I, Evangelou E, Ioannidis JP. Environmental risk factors and Parkinson's disease: an umbrella review of meta-analyses. Parkinsonism Relat Disord. 2016;23:1–9.

Walter SD, Cook RJ. A comparison of several point estimators of the odds ratio in a single 2 x 2 contingency table. Biometrics. 1991;47(3):795–811.

Khan H, Sempos CT. Statistical methods in epidemiology. New York: Oxford University Press; 1989.

DerSimonian R, Laird N. Meta-analysis in clinical trials. Control Clin Trials. 1986;7(3):177–88.

CAS   Google Scholar  

Higgins J, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, Welch VA, editors. Cochrane Handbook for Systematic Reviews of Interventions version 6.0 (updated July 2019): Cochrane; 2019. Available from www.training.cochrane.org/handbook .

Pieper D, Antoine SL, Mathes T, Neugebauer EA, Eikermann M. Systematic review finds overlapping reviews were not mentioned in every other overview. J Clin Epidemiol. 2014;67(4):368–75.

Adeniyi FB, Young T. Weight loss interventions for chronic asthma. Cochrane Database Syst Rev. 2012;7.

Al-Khudairy L, Loveman E, Colquitt JL, Mead E, Johnson RE, Fraser H, Olajide J, Murphy M, Velho RM, O'Malley C, et al. Diet, physical activity and behavioural interventions for the treatment of overweight or obese adolescents aged 12 to 17 years. Cochrane Database Syst Rev. 2017;6.

Amorim Adegboye AR, Linne YM. Diet or exercise, or both, for weight reduction in women after childbirth. Cochrane Database Syst Rev. 2013;7.

Anderson L, Nguyen TT, Dall CH, Burgess L, Bridges C, Taylor RS. Exercise-based cardiac rehabilitation in heart transplant recipients. Cochrane Database Syst Rev. 2017;4.

Anderson L, Thompson DR, Oldridge N, Zwisler AD, Rees K, Martin N, Taylor RS. Exercise-based cardiac rehabilitation for coronary heart disease. Cochrane Database Syst Rev. 2016;1.

Andriolo RB, El Dib RP, Ramos L, Atallah Á, da Silva EMK. Aerobic exercise training programmes for improving physical and psychosocial health in adults with Down syndrome. Cochrane Database Syst Rev. 2010;5.

Araujo DN, Ribeiro CTD, Maciel ACC, Bruno SS, Fregonezi GAF, Dias FAL. Physical exercise for the treatment of non-ulcerated chronic venous insufficiency. Cochrane Database Syst Rev. 2016;12.

Ashworth NL, Chad KE, Harrison EL, Reeder BA, Marshall SC. Home versus center based physical activity programs in older adults. Cochrane Database Syst Rev. 2005;1.

Bartels EM, Juhl CB, Christensen R, Hagen KB, Danneskiold-Samsøe B, Dagfinrud H, Lund H. Aquatic exercise for the treatment of knee and hip osteoarthritis. Cochrane Database Syst Rev. 2016;3.

Beggs S, Foong YC, Le HCT, Noor D, Wood-Baker R, Walters JAE. Swimming training for asthma in children and adolescents aged 18 years and under. Cochrane Database Syst Rev. 2013;4.

Bergenthal N, Will A, Streckmann F, Wolkewitz KD, Monsef I, Engert A, Elter T, Skoetz N. Aerobic physical exercise for adult patients with haematological malignancies. Cochrane Database Syst Rev. 2014;11.

Bidonde J, Busch AJ, Schachter CL, Overend TJ, Kim SY, Góes SM, Boden C, Foulds HJA. Aerobic exercise training for adults with fibromyalgia. Cochrane Database Syst Rev. 2017;6.

Bidonde J, Busch AJ, van der Spuy I, Tupper S, Kim SY, Boden C. Whole body vibration exercise training for fibromyalgia. Cochrane Database Syst Rev. 2017;9.

Bidonde J, Busch AJ, Webber SC, Schachter CL, Danyliw A, Overend TJ, Richards RS, Rader T. Aquatic exercise training for fibromyalgia. Cochrane Database Syst Rev. 2014;10.

Braam KI, van der Torre P, Takken T, Veening MA, van Dulmen-den Broeder E, Kaspers GJL. Physical exercise training interventions for children and young adults during and after treatment for childhood cancer. Cochrane Database Syst Rev. 2016;3.

Bradt J, Shim M, Goodill SW. Dance/movement therapy for improving psychological and physical outcomes in cancer patients. Cochrane Database Syst Rev. 2015;1.

Broderick J, Crumlish N, Waugh A, Vancampfort D. Yoga versus non-standard care for schizophrenia. Cochrane Database Syst Rev. 2017;9.

Broderick J, Knowles A, Chadwick J, Vancampfort D. Yoga versus standard care for schizophrenia. Cochrane Database Syst Rev. 2015;10.

Broderick J, Vancampfort D. Yoga as part of a package of care versus standard care for schizophrenia. Cochrane Database Syst Rev. 2017;9.

Brown J, Ceysens G, Boulvain M. Exercise for pregnant women with gestational diabetes for improving maternal and fetal outcomes. Cochrane Database Syst Rev. 2017;6.

Busch AJ, Barber KA, Overend TJ, Peloso PMJ, Schachter CL. Exercise for treating fibromyalgia syndrome. Cochrane Database Syst Rev. 2007;4.

Busch AJ, Webber SC, Richards RS, Bidonde J, Schachter CL, Schafer LA, Danyliw A, Sawant A, Dal Bello-Haas V, Rader T, et al. Resistance exercise training for fibromyalgia. Cochrane Database Syst Rev. 2013;12.

Cameron ID, Dyer SM, Panagoda CE, Murray GR, Hill KD, Cumming RG, Kerse N. Interventions for preventing falls in older people in care facilities and hospitals. Cochrane Database Syst Rev. 2018;9.

Carson KV, Chandratilleke MG, Picot J, Brinn MP, Esterman AJ, Smith BJ. Physical training for asthma. Cochrane Database Syst Rev. 2013;9.

Carvalho APV, Vital FMR, Soares BGO. Exercise interventions for shoulder dysfunction in patients treated for head and neck cancer. Cochrane Database Syst Rev. 2012;4.

Cavalheri V, Granger C. Preoperative exercise training for patients with non-small cell lung cancer. Cochrane Database Syst Rev. 2017;6.

Cavalheri V, Tahirah F, Nonoyama ML, Jenkins S, Hill K. Exercise training undertaken by people within 12 months of lung resection for non-small cell lung cancer. Cochrane Database Syst Rev. 2013;7.

Ceysens G, Rouiller D, Boulvain M. Exercise for diabetic pregnant women. Cochrane Database Syst Rev. 2006;3.

Choi BKL, Verbeek JH, Tam WWS, Jiang JY. Exercises for prevention of recurrences of low-back pain. Cochrane Database Syst Rev. 2010;1.

Colquitt JL, Loveman E, O'Malley C, Azevedo LB, Mead E, Al-Khudairy L, Ells LJ, Metzendorf MI, Rees K. Diet, physical activity, and behavioural interventions for the treatment of overweight or obesity in preschool children up to the age of 6 years. Cochrane Database Syst Rev. 2016;3.

Connolly B, Salisbury L, O'Neill B, Geneen LJ, Douiri A, Grocott MPW, Hart N, Walsh TS, Blackwood B. Exercise rehabilitation following intensive care unit discharge for recovery from critical illness. Cochrane Database Syst Rev. 2015;6.

Cooney GM, Dwan K, Greig CA, Lawlor DA, Rimer J, Waugh FR, McMurdo M, Mead GE. Exercise for depression. Cochrane Database Syst Rev. 2013;9.

Corbetta D, Sirtori V, Castellini G, Moja L, Gatti R. Constraint-induced movement therapy for upper extremities in people with stroke. Cochrane Database Syst Rev. 2015;10.

Cramer H, Lauche R, Klose P, Lange S, Langhorst J, Dobos GJ. Yoga for improving health-related quality of life, mental health and cancer-related symptoms in women diagnosed with breast cancer. Cochrane Database Syst Rev. 2017;1.

Cramp F, Byron-Daniel J. Exercise for the management of cancer-related fatigue in adults. Cochrane Database Syst Rev. 2012;11.

Dal Bello-Haas V, Florence JM. Therapeutic exercise for people with amyotrophic lateral sclerosis or motor neuron disease. Cochrane Database Syst Rev. 2013;5.

Dale MT, McKeough ZJ, Troosters T, Bye P, Alison JA. Exercise training to improve exercise capacity and quality of life in people with non-malignant dust-related respiratory diseases. Cochrane Database Syst Rev. 2015;11.

Daley A, Stokes-Lampard H, Thomas A, MacArthur C. Exercise for vasomotor menopausal symptoms. Cochrane Database Syst Rev. 2014;11.

de Morton N, Keating JL, Jeffs K. Exercise for acutely hospitalised older medical patients. Cochrane Database Syst Rev. 2007;1.

Dobbins M, Husson H, DeCorby K, LaRocca RL. School-based physical activity programs for promoting physical activity and fitness in children and adolescents aged 6 to 18. Cochrane Database Syst Rev. 2013;2.

Doiron KA, Hoffmann TC, Beller EM. Early intervention (mobilization or active exercise) for critically ill adults in the intensive care unit. Cochrane Database Syst Rev. 2018;3.

Ekeland E, Heian F, Hagen KB, Abbott JM, Nordheim L. Exercise to improve self-esteem in children and young people. Cochrane Database Syst Rev. 2004;1.

Elbers RG, Verhoef J, van Wegen EEH, Berendse HW, Kwakkel G. Interventions for fatigue in Parkinson's disease. Cochrane Database Syst Rev. 2015;10.

Felbel S, Meerpohl JJ, Monsef I, Engert A, Skoetz N. Yoga in addition to standard care for patients with haematological malignancies. Cochrane Database Syst Rev. 2014;6.

Forbes D, Forbes SC, Blake CM, Thiessen EJ, Forbes S. Exercise programs for people with dementia. Cochrane Database Syst Rev. 2015;4.

Fransen M, McConnell S, Harmer AR, Van der Esch M, Simic M, Bennell KL. Exercise for osteoarthritis of the knee. Cochrane Database Syst Rev. 2015;1.

Fransen M, McConnell S, Hernandez-Molina G, Reichenbach S. Exercise for osteoarthritis of the hip. Cochrane Database Syst Rev. 2014;4.

Freitas DA, Holloway EA, Bruno SS, Chaves GSS, Fregonezi GAF, Mendonça K. Breathing exercises for adults with asthma. Cochrane Database Syst Rev. 2013;10.

Furmaniak AC, Menig M, Markes MH. Exercise for women receiving adjuvant therapy for breast cancer. Cochrane Database Syst Rev. 2016;9.

Giangregorio LM, MacIntyre NJ, Thabane L, Skidmore CJ, Papaioannou A. Exercise for improving outcomes after osteoporotic vertebral fracture. Cochrane Database Syst Rev. 2013;1.

Gillespie LD, Robertson MC, Gillespie WJ, Sherrington C, Gates S, Clemson LM, Lamb SE. Interventions for preventing falls in older people living in the community. Cochrane Database Syst Rev. 2012;9.

Gorczynski P, Faulkner G. Exercise therapy for schizophrenia. Cochrane Database Syst Rev. 2010;5.

Grande AJ, Keogh J, Hoffmann TC, Beller EM, Del Mar CB. Exercise versus no exercise for the occurrence, severity and duration of acute respiratory infections. Cochrane Database Syst Rev. 2015;6.

Grande AJ, Reid H, Thomas EE, Nunan D, Foster C. Exercise prior to influenza vaccination for limiting influenza incidence and its related complications in adults. Cochrane Database Syst Rev. 2016;8.

Grande AJ, Silva V, Andriolo BNG, Riera R, Parra SA, Peccin MS. Water-based exercise for adults with asthma. Cochrane Database Syst Rev. 2014;7.

Gross A, Kay TM, Paquin JP, Blanchette S, Lalonde P, Christie T, Dupont G, Graham N, Burnie SJ, Gelley G, et al. Exercises for mechanical neck disorders. Cochrane Database Syst Rev. 2015;1.

Hageman D, Fokkenrood HJP, Gommans LNM, van den Houten MML, Teijink JAW. Supervised exercise therapy versus home-based exercise therapy versus walking advice for intermittent claudication. Cochrane Database Syst Rev. 2018;4.

Han A, Judd M, Welch V, Wu T, Tugwell P, Wells GA. Tai chi for treating rheumatoid arthritis. Cochrane Database Syst Rev. 2004;3.

Han S, Middleton P, Crowther CA. Exercise for pregnant women for preventing gestational diabetes mellitus. Cochrane Database Syst Rev. 2012;7.

Hartley L, Dyakova M, Holmes J, Clarke A, Lee MS, Ernst E, Rees K. Yoga for the primary prevention of cardiovascular disease. Cochrane Database Syst Rev. 2014;5.

Hartley L, Flowers N, Lee MS, Ernst E, Rees K. Tai chi for primary prevention of cardiovascular disease. Cochrane Database Syst Rev. 2014;4.

Hartley L, Lee MS, Kwong JSW, Flowers N, Todkill D, Ernst E, Rees K. Qigong for the primary prevention of cardiovascular disease. Cochrane Database Syst Rev. 2015;6.

Hassett L, Moseley AM, Harmer AR. Fitness training for cardiorespiratory conditioning after traumatic brain injury. Cochrane Database Syst Rev. 2017;12.

Hayden J, van Tulder MW, Malmivaara A, Koes BW. Exercise therapy for treatment of non-specific low back pain. Cochrane Database Syst Rev. 2005;3.

Hay-Smith EJC, Herderschee R, Dumoulin C, Herbison GP. Comparisons of approaches to pelvic floor muscle training for urinary incontinence in women. Cochrane Database Syst Rev. 2011;12.

Heine M, van de Port I, Rietberg MB, van Wegen EEH, Kwakkel G. Exercise therapy for fatigue in multiple sclerosis. Cochrane Database Syst Rev. 2015;9.

Heiwe S, Jacobson SH. Exercise training for adults with chronic kidney disease. Cochrane Database Syst Rev. 2011;10.

Hemmingsen B, Gimenez-Perez G, Mauricio D, Roqué i Figuls M, Metzendorf MI, Richter B. Diet, physical activity or both for prevention or delay of type 2 diabetes mellitus and its associated complications in people at increased risk of developing type 2 diabetes mellitus. Cochrane Database Syst Rev. 2017;12.

Herbert RD, de Noronha M, Kamper SJ. Stretching to prevent or reduce muscle soreness after exercise. Cochrane Database Syst Rev. 2011;7.

Heymans MW, van Tulder MW, Esmail R, Bombardier C, Koes BW. Back schools for non-specific low-back pain. Cochrane Database Syst Rev. 2004;4.

Holland AE, Hill CJ, Jones AY, McDonald CF. Breathing exercises for chronic obstructive pulmonary disease. Cochrane Database Syst Rev. 2012;10.

Howe TE, Rochester L, Neil F, Skelton DA, Ballinger C. Exercise for improving balance in older people. Cochrane Database Syst Rev. 2011;11.

Howe TE, Shea B, Dawson LJ, Downie F, Murray A, Ross C, Harbour RT, Caldwell LM, Creed G. Exercise for preventing and treating osteoporosis in postmenopausal women. Cochrane Database Syst Rev. 2011;7.

Hurkmans E, van der Giesen FJ, Vliet Vlieland TPM, Schoones J, Van den Ende E. Dynamic exercise programs (aerobic capacity and/or muscle strength training) in patients with rheumatoid arthritis. Cochrane Database Syst Rev. 2009;4.

Hurley M, Dickson K, Hallett R, Grant R, Hauari H, Walsh N, Stansfield C, Oliver S. Exercise interventions and patient beliefs for people with hip, knee or hip and knee osteoarthritis: a mixed methods review. Cochrane Database Syst Rev. 2018;4.

Jones M, Harvey A, Marston L, O'Connell NE. Breathing exercises for dysfunctional breathing/hyperventilation syndrome in adults. Cochrane Database Syst Rev. 2013;5.

Katsura M, Kuriyama A, Takeshima T, Fukuhara S, Furukawa TA. Preoperative inspiratory muscle training for postoperative pulmonary complications in adults undergoing cardiac and major abdominal surgery. Cochrane Database Syst Rev. 2015;10.

Kendrick D, Kumar A, Carpenter H, Zijlstra GAR, Skelton DA, Cook JR, Stevens Z, Belcher CM, Haworth D, Gawler SJ, et al. Exercise for reducing fear of falling in older people living in the community. Cochrane Database Syst Rev. 2014;11.

Kramer MS, McDonald SW. Aerobic exercise for women during pregnancy. Cochrane Database Syst Rev. 2006;3.

Lahart IM, Metsios GS, Nevill AM, Carmichael AR. Physical activity for women with breast cancer after adjuvant therapy. Cochrane Database Syst Rev. 2018;1.

Lane R, Harwood A, Watson L, Leng GC. Exercise for intermittent claudication. Cochrane Database Syst Rev. 2017;12.

Larun L, Brurberg KG, Odgaard-Jensen J, Price JR. Exercise therapy for chronic fatigue syndrome. Cochrane Database Syst Rev. 2017;4.

Larun L, Nordheim LV, Ekeland E, Hagen KB, Heian F. Exercise in prevention and treatment of anxiety and depression among children and young people. Cochrane Database Syst Rev. 2006;3.

Lauret GJ, Fakhry F, Fokkenrood HJP, Hunink MGM, Teijink JAW, Spronk S. Modes of exercise training for intermittent claudication. Cochrane Database Syst Rev. 2014;7.

Lawrence M, Celestino Junior FT, Matozinho HHS, Govan L, Booth J, Beecher J. Yoga for stroke rehabilitation. Cochrane Database Syst Rev. 2017;12.

Lin CWC, Donkers NAJ, Refshauge KM, Beckenkamp PR, Khera K, Moseley AM. Rehabilitation for ankle fractures in adults. Cochrane Database Syst Rev. 2012;11.

Liu CJ, Latham NK. Progressive resistance strength training for improving physical function in older adults. Cochrane Database Syst Rev. 2009;3.

Long L, Anderson L, Dewhirst AM, He J, Bridges C, Gandhi M, Taylor RS. Exercise-based cardiac rehabilitation for adults with stable angina. Cochrane Database Syst Rev. 2018;2.

Loughney LA, West MA, Kemp GJ, Grocott MPW, Jack S. Exercise interventions for people undergoing multimodal cancer treatment that includes surgery. Cochrane Database Syst Rev. 2018;12.

Macedo LG, Saragiotto BT, Yamato TP, Costa LOP, Menezes Costa LC, Ostelo R, Maher CG. Motor control exercise for acute non-specific low back pain. Cochrane Database Syst Rev. 2016;2.

Macêdo TMF, Freitas DA, Chaves GSS, Holloway EA, Mendonça K. Breathing exercises for children with asthma. Cochrane Database Syst Rev. 2016;4.

Martin A, Booth JN, Laird Y, Sproule J, Reilly JJ, Saunders DH. Physical activity, diet and other behavioural interventions for improving cognition and school achievement in children and adolescents with obesity or overweight. Cochrane Database Syst Rev. 2018;3.

McKeough ZJ, Velloso M, Lima VP, Alison JA. Upper limb exercise training for COPD. Cochrane Database Syst Rev. 2016;11.

McNamara RJ, McKeough ZJ, McKenzie DK, Alison JA. Water-based exercise training for chronic obstructive pulmonary disease. Cochrane Database Syst Rev. 2013;12.

McNeely ML, Campbell K, Ospina M, Rowe BH, Dabbs K, Klassen TP, Mackey J, Courneya K. Exercise interventions for upper-limb dysfunction due to breast cancer treatment. Cochrane Database Syst Rev. 2010;6.

Mead E, Brown T, Rees K, Azevedo LB, Whittaker V, Jones D, Olajide J, Mainardi GM, Corpeleijn E, O'Malley C, et al. Diet, physical activity and behavioural interventions for the treatment of overweight or obese children from the age of 6 to 11 years. Cochrane Database Syst Rev. 2017;6.

Meekums B, Karkou V, Nelson EA. Dance movement therapy for depression. Cochrane Database Syst Rev. 2015;2.

Meher S, Duley L. Exercise or other physical activity for preventing pre-eclampsia and its complications. Cochrane Database Syst Rev. 2006;2.

Mehrholz J, Kugler J, Pohl M. Water-based exercises for improving activities of daily living after stroke. Cochrane Database Syst Rev. 2011;1.

Mehrholz J, Kugler J, Pohl M. Locomotor training for walking after spinal cord injury. Cochrane Database Syst Rev. 2012;11.

Mehrholz J, Thomas S, Elsner B. Treadmill training and body weight support for walking after stroke. Cochrane Database Syst Rev. 2017;8.

Mishra SI, Scherer RW, Geigle PM, Berlanstein DR, Topaloglu O, Gotay CC, Snyder C. Exercise interventions on health-related quality of life for cancer survivors. Cochrane Database Syst Rev. 2012;8.

Mishra SI, Scherer RW, Snyder C, Geigle PM, Berlanstein DR, Topaloglu O. Exercise interventions on health-related quality of life for people with cancer during active treatment. Cochrane Database Syst Rev. 2012;8.

Montgomery P, Dennis JA. Physical exercise for sleep problems in adults aged 60+. Cochrane Database Syst Rev. 2002;4.

Morris NR, Kermeen FD, Holland AE. Exercise-based rehabilitation programmes for pulmonary hypertension. Cochrane Database Syst Rev. 2017;1.

Muktabhant B, Lawrie TA, Lumbiganon P, Laopaiboon M. Diet or exercise, or both, for preventing excessive weight gain in pregnancy. Cochrane Database Syst Rev. 2015;6.

Ngai SPC, Jones AYM, Tam WWS. Tai chi for chronic obstructive pulmonary disease (COPD). Cochrane Database Syst Rev. 2016;6.

Norton C, Cody JD. Biofeedback and/or sphincter exercises for the treatment of faecal incontinence in adults. Cochrane Database Syst Rev. 2012;7.

O'Brien K, Nixon S, Glazier R, Tynan AM. Progressive resistive exercise interventions for adults living with HIV/AIDS. Cochrane Database Syst Rev. 2004;4.

O'Brien K, Nixon S, Tynan AM, Glazier R. Aerobic exercise interventions for adults living with HIV/AIDS. Cochrane Database Syst Rev. 2010;8.

Østerås N, Kjeken I, Smedslund G, Moe RH, Slatkowsky-Christensen B, Uhlig T, Hagen KB. Exercise for hand osteoarthritis. Cochrane Database Syst Rev. 2017;1.

Page MJ, Green S, Kramer S, Johnston RV, McBain B, Chau M, Buchbinder R. Manual therapy and exercise for adhesive capsulitis (frozen shoulder). Cochrane Database Syst Rev. 2014;8.

Page MJ, Green S, McBain B, Surace SJ, Deitch J, Lyttle N, Mrocki MA, Buchbinder R. Manual therapy and exercise for rotator cuff disease. Cochrane Database Syst Rev. 2016;6.

Page MJ, O'Connor D, Pitt V, Massy-Westropp N. Exercise and mobilisation interventions for carpal tunnel syndrome. Cochrane Database Syst Rev. 2012;6.

Panebianco M, Sridharan K, Ramaratnam S. Yoga for epilepsy. Cochrane Database Syst Rev. 2017;10.

Perry A, Lee SH, Cotton S, Kennedy C. Therapeutic exercises for affecting post-treatment swallowing in people treated for advanced-stage head and neck cancers. Cochrane Database Syst Rev. 2016;8.

Radtke T, Nevitt SJ, Hebestreit H, Kriemler S. Physical exercise training for cystic fibrosis. Cochrane Database Syst Rev. 2017;11.

Regnaux JP, Lefevre-Colau MM, Trinquart L, Nguyen C, Boutron I, Brosseau L, Ravaud P. High-intensity versus low-intensity physical activity or exercise in people with hip or knee osteoarthritis. Cochrane Database Syst Rev. 2015;10.

Ren J, Xia J. Dance therapy for schizophrenia. Cochrane Database Syst Rev. 2013;10.

Rietberg MB, Brooks D, Uitdehaag BMJ, Kwakkel G. Exercise therapy for multiple sclerosis. Cochrane Database Syst Rev. 2005;1.

Risom SS, Zwisler AD, Johansen PP, Sibilitz KL, Lindschou J, Gluud C, Taylor RS, Svendsen JH, Berg SK. Exercise-based cardiac rehabilitation for adults with atrial fibrillation. Cochrane Database Syst Rev. 2017;2.

Romano M, Minozzi S, Bettany-Saltikov J, Zaina F, Chockalingam N, Kotwicki T, Maier-Hennes A, Negrini S. Exercises for adolescent idiopathic scoliosis. Cochrane Database Syst Rev. 2012;8.

Ryan JM, Cassidy EE, Noorduyn SG, O'Connell NE. Exercise interventions for cerebral palsy. Cochrane Database Syst Rev. 2017;6.

Saragiotto BT, Maher CG, Yamato TP, Costa LOP, Menezes Costa LC, Ostelo R, Macedo LG. Motor control exercise for chronic non-specific low-back pain. Cochrane Database Syst Rev. 2016;1.

Saunders DH, Sanderson M, Hayes S, Kilrane M, Greig CA, Brazzelli M, Mead GE. Physical fitness training for stroke patients. Cochrane Database Syst Rev. 2016;3.

Schulzke SM, Kaempfen S, Trachsel D, Patole SK. Physical activity programs for promoting bone mineralization and growth in preterm infants. Cochrane Database Syst Rev. 2014;4.

Seron P, Lanas F, Pardo Hernandez H, Bonfill Cosp X. Exercise for people with high cardiovascular risk. Cochrane Database Syst Rev. 2014;8.

Shaw KA, Gennat HC, O'Rourke P, Del Mar C. Exercise for overweight or obesity. Cochrane Database Syst Rev. 2006;4.

Shepherd E, Gomersall JC, Tieu J, Han S, Crowther CA, Middleton P. Combined diet and exercise interventions for preventing gestational diabetes mellitus. Cochrane Database Syst Rev. 2017;11.

Sibilitz KL, Berg SK, Tang LH, Risom SS, Gluud C, Lindschou J, Kober L, Hassager C, Taylor RS, Zwisler AD. Exercise-based cardiac rehabilitation for adults after heart valve surgery. Cochrane Database Syst Rev. 2016;3.

Silva IS, Fregonezi GAF, Dias FAL, Ribeiro CTD, Guerra RO, Ferreira GMH. Inspiratory muscle training for asthma. Cochrane Database Syst Rev. 2013;9.

States RA, Pappas E, Salem Y. Overground physical therapy gait training for chronic stroke patients with mobility deficits. Cochrane Database Syst Rev. 2009;3.

Strike K, Mulder K, Michael R. Exercise for haemophilia. Cochrane Database Syst Rev. 2016;12.

Takken T, Van Brussel M, Engelbert RH, van der Net JJ, Kuis W, Helders P. Exercise therapy in juvenile idiopathic arthritis. Cochrane Database Syst Rev. 2008;2.

Taylor RS, Sagar VA, Davies EJ, Briscoe S, Coats AJS, Dalal H, Lough F, Rees K, Singh SJ, Mordi IR. Exercise-based rehabilitation for heart failure. Cochrane Database Syst Rev. 2014;4.

Thomas D, Elliott EJ, Naughton GA. Exercise for type 2 diabetes mellitus. Cochrane Database Syst Rev. 2006;3.

Ussher MH, Taylor AH, Faulkner GEJ. Exercise interventions for smoking cessation. Cochrane Database Syst Rev. 2014;8.

Valentín-Gudiol M, Mattern-Baxter K, Girabent-Farrés M, Bagur-Calafat C, Hadders-Algra M, Angulo-Barroso RM. Treadmill interventions in children under six years of age at risk of neuromotor delay. Cochrane Database Syst Rev. 2017;7.

van der Heijden RA, Lankhorst NE, van Linschoten R, Bierma-Zeinstra SMA, van Middelkoop M. Exercise for treating patellofemoral pain syndrome. Cochrane Database Syst Rev. 2015;1.

Vloothuis JDM, Mulder M, Veerbeek JM, Konijnenbelt M, Visser-Meily JMA, Ket JCF, Kwakkel G, van Wegen EEH. Caregiver-mediated exercises for improving outcomes after stroke. Cochrane Database Syst Rev. 2016;12.

Voet NBM, van der Kooi EL. Riphagen, II, Lindeman E, van Engelen BGM, Geurts ACH: strength training and aerobic exercise training for muscle disease. Cochrane Database Syst Rev. 2013;7.

White CM, Pritchard J, Turner-Stokes L. Exercise for people with peripheral neuropathy. Cochrane Database Syst Rev. 2004;4.

Wieland LS, Skoetz N, Pilkington K, Vempati R, D'Adamo CR, Berman BM. Yoga treatment for chronic non-specific low back pain. Cochrane Database Syst Rev. 2017;1.

Williams AD, Bird ML, Hardcastle SGK, Kirschbaum M, Ogden KJ, Walters JAE. Exercise for reducing falls in people living with and beyond cancer. Cochrane Database Syst Rev. 2018;10.

Williams MA, Srikesavan C, Heine PJ, Bruce J, Brosseau L, Hoxey-Thomas N, Lamb SE. Exercise for rheumatoid arthritis of the hand. Cochrane Database Syst Rev. 2018;7.

Yamamoto S, Hotta K, Ota E, Matsunaga A, Mori R. Exercise-based cardiac rehabilitation for people with implantable ventricular assist devices. Cochrane Database Syst Rev. 2018;9.

Yamato TP, Maher CG, Saragiotto BT, Hancock MJ, Ostelo R, Cabral CMN, Menezes Costa LC, Costa LOP. Pilates for low back pain. Cochrane Database Syst Rev. 2015;7.

Yang ZY, Zhong HB, Mao C, Yuan JQ, Huang YF, Wu XY, Gao YM, Tang JL. Yoga for asthma. Cochrane Database Syst Rev. 2016;4.

Young J, Angevaren M, Rusted J, Tabet N. Aerobic exercise to improve cognitive function in older people without known cognitive impairment. Cochrane Database Syst Rev. 2015;4.

Zainuldin R, Mackey MG, Alison JA. Optimal intensity and type of leg exercise training for people with chronic obstructive pulmonary disease. Cochrane Database Syst Rev. 2011;11.

Mok A, Khaw K-T, Luben R, Wareham N, Brage S. Physical activity trajectories and mortality: population based cohort study. Bmj. 2019;365:l2323.

Ekelund U, Brown WJ, Steene-Johannessen J, Fagerland MW, Owen N, Powell KE, Bauman AE, Lee IM. Do the associations of sedentary behaviour with cardiovascular disease mortality and cancer mortality differ by physical activity level? A systematic review and harmonised meta-analysis of data from 850 060 participants. Br J Sports Med. 2019;53(14):886–94. https://doi.org/10.1136/bjsports-2017-098963 . Epub 2018 Jul 10.

Article   PubMed   Google Scholar  

Ekelund U, Steene-Johannessen J, Brown WJ, Fagerland MW, Owen N, Powell KE, Bauman A, Lee IM. Does physical activity attenuate, or even eliminate, the detrimental association of sitting time with mortality? A harmonised meta-analysis of data from more than 1 million men and women. Lancet. 2016;388(10051):1302–10.

Lear SA, Hu W, Rangarajan S, Gasevic D, Leong D, Iqbal R, Casanova A, Swaminathan S, Anjana RM, Kumar R, et al. The effect of physical activity on mortality and cardiovascular disease in 130000 people from 17 high-income, middle-income, and low-income countries: the PURE study. Lancet. 2017;390(10113):2643–54.

Sattelmair J, Pertman J, Ding EL, Kohl HW 3rd, Haskell W, Lee IM. Dose response between physical activity and risk of coronary heart disease: a meta-analysis. Circulation. 2011;124(7):789–95.

Heyman E, Gamelin FX, Goekint M, Piscitelli F, Roelands B, Leclair E, Di Marzo V, Meeusen R. Intense exercise increases circulating endocannabinoid and BDNF levels in humans--possible implications for reward and depression. Psychoneuroendocrinology. 2012;37(6):844–51.

Horton R. Offline: the gravy train of systematic reviews. Lancet. 2019;394(10211):1790.

Guthold R, Stevens GA, Riley LM, Bull FC. Worldwide trends in insufficient physical activity from 2001 to 2016: a pooled analysis of 358 population-based surveys with 1.9 million participants. Lancet Glob Health. 2018;6(10):e1077–86.

Fletcher GF, Landolfo C, Niebauer J, Ozemek C, Arena R, Lavie CJ. Promoting physical activity and exercise: JACC health promotion series. J Am Coll Cardiol. 2018;72(14):1622–39.

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Supplementary Table 1. Main characteristics of included Cochrane systematic reviews evaluating the effects of physical activity/exercise on health outcomes ( n  = 150). Supplementary Table 2. Additional information from Cochrane systematic reviews of the effects of physical activity/exercise on health outcomes ( n  = 150). Supplementary Table 3. Conclusions from Cochrane systematic reviews “quote”. Supplementary Table 4 . AEs reported in Cochrane systematic reviews. Supplementary Table 5. Summary of withdrawals/non-adherence. Supplementary Table 6. Methodological quality assessment of the included Cochrane reviews with AMSTAR-2. Supplementary Table 7. Number of studies assessed as low risk of bias per domain. Supplementary Table 8. GRADE for the review’s main comparison. Supplementary Table 9. Studies reporting quality of life outcomes as mean difference.

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Posadzki, P., Pieper, D., Bajpai, R. et al. Exercise/physical activity and health outcomes: an overview of Cochrane systematic reviews. BMC Public Health 20 , 1724 (2020). https://doi.org/10.1186/s12889-020-09855-3

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Ginger on Human Health: A Comprehensive Systematic Review of 109 Randomized Controlled Trials

Affiliations.

• 1 College of Pharmacy, Seoul National University, Seoul 08826, Korea.
• 2 School of Medicine, Vietnam National University, Ho Chi Minh City 70000, Vietnam.
• PMID: 31935866
• PMCID: PMC7019938
• DOI: 10.3390/nu12010157

Clinical applications of ginger with an expectation of clinical benefits are receiving significant attention. This systematic review aims to provide a comprehensive discussion in terms of the clinical effects of ginger in all reported areas. Following the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guideline, randomized controlled trials on the effects of ginger were investigated. Accordingly, 109 eligible papers were fully extracted in terms of study design, population characteristics, evaluation systems, adverse effects, and main outcomes. The reporting quality of the included studies was assessed based on the Cochrane Collaboration's tool for assessing the risk of bias in randomized trials and integrated together with studies that investigated the same subjects. The included studies that examined the improvement of nausea and vomiting in pregnancy, inflammation, metabolic syndromes, digestive function, and colorectal cancer's markers were consistently supported, whereas other expected functions were relatively controversial. Nevertheless, only 43 clinical trials (39.4%) met the criterion of having a 'high quality of evidence.' In addition to the quality assessment result, small populations and unstandardized evaluation systems were the observed shortcomings in ginger clinical trials. Further studies with adequate designs are warranted to validate the reported clinical functions of ginger.

Keywords: ginger; human health; randomized controlled trials; systematic review.

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• Systematic Review
• Colorectal Neoplasms / drug therapy*
• Digestive System / drug effects*
• Inflammation / drug therapy*
• Metabolic Syndrome / drug therapy*
• Nausea / drug therapy*
• Nausea / etiology
• Phytotherapy
• Plant Extracts / pharmacology
• Plant Extracts / therapeutic use
• Pregnancy Complications / drug therapy
• Randomized Controlled Trials as Topic
• Vomiting / drug therapy*
• Vomiting / etiology
• Zingiber officinale*
• Plant Extracts

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• Published: 03 March 2015

Health research improves healthcare: now we have the evidence and the chance to help the WHO spread such benefits globally

• Stephen R Hanney 1 &
• Miguel A González-Block 2  

Health Research Policy and Systems volume  13 , Article number:  12 ( 2015 ) Cite this article

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There has been a dramatic increase in the body of evidence demonstrating the benefits that come from health research. In 2014, the funding bodies for higher education in the UK conducted an assessment of research using an approach termed the Research Excellence Framework (REF). As one element of the REF, universities and medical schools in the UK submitted 1,621 case studies claiming to show the impact of their health and other life sciences research conducted over the last 20 years. The recently published results show many case studies were judged positively as providing examples of the wide range and extensive nature of the benefits from such research, including the development of new treatments and screening programmes that resulted in considerable reductions in mortality and morbidity.

Analysis of specific case studies yet again illustrates the international dimension of progress in health research; however, as has also long been argued, not all populations fully share the benefits. In recognition of this, in May 2013 the World Health Assembly requested the World Health Organization (WHO) to establish a Global Observatory on Health Research and Development (R&D) as part of a strategic work-plan to promote innovation, build capacity, improve access, and mobilise resources to address diseases that disproportionately affect the world’s poorest countries.

As editors of Health Research Policy and Systems ( HARPS ), we are delighted that our journal has been invited to help inform the establishment of the WHO Global Observatory through a Call for Papers covering a range of topics relevant to the Observatory, including topics on which HARPS has published articles over the last few months, such as approaches to assessing research results, measuring expenditure data with a focus on R&D, and landscape analyses of platforms for implementing R&D. Topics related to research capacity building may also be considered. The task of establishing a Global Observatory on Health R&D to achieve the specified objectives will not be easy; nevertheless, this Call for Papers is well timed – it comes just at the point where the evidence of the benefits from health research has been considerably strengthened.

The start of 2015 sees a dramatic increase in the body of evidence demonstrating the benefits arising from health research. Throughout 2014, the higher education funding bodies in the UK conducted an assessment of research, termed the Research Excellence Framework (REF), in which, for the first time, account was taken of the impact on society of the research undertaken. As part of this, UK universities and medical schools produced 1,621 case studies that aimed to show the benefits, such as improved healthcare, arising from examples of their health and other life sciences research conducted over the last 20 years. Panels of experts, including leading academics from many countries, published their assessments of these case studies in December 2014 [ 1 ], with the full case studies and an analysis of the results being made public in January 2015 [ 2 , 3 ].

As we recently anticipated [ 4 ], the expert panels concluded that the case studies did indeed overwhelmingly illustrate the wide range and extensive nature of the benefits from health research. Main Panel A covered the range of life sciences and its overview report states: “ MPA [Main Panel A] believes that the collection of impact case studies provide a unique and powerful illustration of the outstanding contribution that research in the fields covered by this panel is making to health, wellbeing, wealth creation and society within and beyond the UK ” [ 3 ], p. 1. The section of the report covering public health and health services research also notes that: “ Outstanding examples included cases focused on national screening programmes for the selection and early diagnosis of conditions ” [ 3 ], p. 30. In their section of the report, the international experts say of the REF2014: “ It is the boldest, largest, and most comprehensive exercise of its kind of any country’s assessment of its science ” [ 3 ], p. 20.

The REF2014 is therefore attracting wide international attention. Indeed, some of the methods used are already informing studies in other countries, including, for example, an innovative assessment recently published in Health Research Policy and Systems ( HARPS ) identifying the beneficial effects made on healthcare policies and practice in Australia by intervention studies funded by the National Health and Medical Research Council [ 5 ].

The REF also illustrates that, even when focusing on the research from one country, there are examples of studies in which there has been international collaboration and which have built on research conducted elsewhere. For example, one REF case study on screening describes how a major UK randomised controlled trial of screening for abdominal aortic aneurysms (AAA) involving 67,800 men [ 6 , 7 ] was the most significant trial globally. The trial provided the main evidence for the policy to introduce national screening programmes for AAA for men reaching 65 throughout the UK [ 2 ]. The importance of this trial lay partly in its size, given that it accounted for over 50% of the men included in the meta-analyses performed in the 2007 Cochrane review [ 8 ] and the 2009 practice guideline from the US Society for Vascular Surgery [ 9 ]. Nevertheless, two of the three smaller studies that were also included in these two meta-analyses came from outside the UK, specifically from Denmark [ 10 ] and Australia [ 11 ].

Moreover, a recent paper published in HARPS also included descriptions of how the research contributing to new interventions often comes from more than one country. These accounts are included in a separate set of seven extensive case studies constructed to illustrate innovative ways to measure the time that can elapse between research being conducted and its translation into improved health [ 12 ]. While being a separate set of case studies, one of them does, nevertheless, explore the international timelines involved in research on screening for AAA, and, in addition to highlighting the key role of the UK research, it also highlights that the pioneering first screening study using ultrasound had been conducted in 1983 on 73 patients in a US Army medical base [ 13 ].

These case studies therefore further reinforce the well-established argument that health research progress often involves contributions from various countries. However, as has long been argued, not all populations fully share the benefits. In recognition of this, in May 2013, the World Health Assembly requested the World Health Organization (WHO), in its resolution 66.22, to establish a Global Observatory on Health Research and Development as part of a strategic work-plan to promote innovation, build capacity, improve access, and mobilise resources to address diseases that disproportionately affect the world’s poorest countries [ 14 ].

As editors of HARPS , we are delighted that our journal has been invited to help inform the establishment of the WHO Global Observatory by publishing a series of papers whose publication costs will be funded by the WHO. In support of this WHO initiative, Taghreed Adam, John-Arne Røttingen, and Marie-Paule Kieny recently published a Call for Papers for this series [ 15 ], which can be accessed through the HARPS webpage.

The aim of the series is “ to contribute state-of-the-art knowledge and innovative approaches to analyse, interpret, and report on health R&D information… [and] to serve as a key resource to inform the future WHO-convened coordination mechanism, which will be utilized to generate evidence-informed priorities for new R&D investments to be financed through a proposed new global financing and coordination mechanism for health R&D ” [ 15 ], p. 1. The Call for Papers covers a range of topics relevant to the aims of the Global Observatory. These include ones on which HARPS has published articles in the last few months, such as approaches to assessing research results, as seen in the Australian article described above [ 5 ]; papers measuring expenditure data with a focus on R&D, as described in a recent Commentary by Young et al. [ 16 ]; and landscape analyses of platforms for implementing R&D, as described in the article by Ongolo-Zogo et al. [ 17 ], analysing knowledge translation platforms in Cameroon and Uganda, and partially in the article by Yazdizadeh et al. [ 18 ], relaying lessons learnt from knowledge networks in Iran.

Adam et al. also make clear that the topics listed in the Call for Papers are examples and that the series editors are also willing to consider other areas [ 15 ]. Indeed, in the Introduction to the Call for Papers, the importance of capacity building is highlighted. This, too, is a topic described in recent papers in HARPS , such as those by Ager and Zarowsky [ 19 ], analysing the experiences of the Health Research Capacity Strengthening initiative’s Global Learning program of work across sub-Saharan Africa, and by Hunter et al. [ 20 ], describing needs assessment to strengthen capacity in water and sanitation research in Africa.

Finally, as we noted in our earlier editorial [ 4 ], the World Health Report 2013: Health Research for Universal Coverage showed how the demonstration of the benefits from health research could be a strong motivation for further funding of such research. As the Report states, “ adding impetus to do more research is a growing body of evidence on the returns on investments … there is mounting quantitative proof of the benefits of research to health, society and the economy ” [ 21 ]. We noted, too, that since the Report’s publication in 2013, there had been further examples from many countries of the benefits from medical research. The REF2014 in the UK signifies an additional major boost to the evidence that a wide range of health research does contribute to improved health and other social benefits. The results of such evaluations highlight the appropriateness of the WHO’s actions in attempting to ensure all populations share the benefits of health research endeavours by creating the Global Observatory on Health Research and Development. This will not be an easy task, but we welcome the opportunity afforded by the current Call for Papers for researchers and other stakeholders to engage with this process and influence it [ 15 ].

Abbreviations

Abdominal aortic aneurysms

Health Research Policy and Systems

Main Panel A

Research and development

Research Excellence Framework

• World Health Organization

Higher Education Funding Council for England. Research Excellence Framework 2014: The results. 2014. http://www.ref.ac.uk/pubs/201401/ . Accessed 20 Feb 2015.

Higher Education Funding Council for England. Research Excellence Framework 2014: Results and submissions. 2015. http://results.ref.ac.uk/ . Accessed 20 Feb 2015.

Higher Education Funding Council for England. REF 2014 Panel overview reports: Main Panel A and sub-panels 1–6. 2015. http://www.ref.ac.uk/media/ref/content/expanel/member/Main%20Panel%20A%20overview%20report.pdf . Accessed 20 Feb 2015.

Hanney SR, González-Block MA. Four centuries on from Bacon: progress in building health research systems to improve health systems? Health Res Policy Syst. 2014;12:56.

Article   PubMed   PubMed Central   Google Scholar  

Cohen G, Schroeder J, Newson R, King L, Rychetnik L, Milat AJ, et al. Does health intervention research have real world policy and practice impacts: testing a new impact assessment tool. Health Res Policy Syst. 2015;13:3.

Scott RAP, Ashton HA, Buxton M, Day NE, Kim LG, Marteau TM, et al. The Multicentre Aneurysm Screening Study (MASS) into the effect of abdominal aortic aneurysm screening on mortality in men: a randomised controlled trial. Lancet. 2002;360:1531–9.

Article   PubMed   Google Scholar  

Buxton M, Ashton H, Campbell H, Day NE, Kim LG, Marteau TM, et al. Multicentre aneurysm screening study (MASS): cost effectiveness analysis of screening for abdominal aortic aneurysms based on four year results from randomised controlled trial. BMJ. 2002;325:1135–8.

Article   Google Scholar  

Cosford PA, Leng GC, Thomas J: Screening for abdominal aortic aneurysm. Cochrane Database Syst Rev 2007; (2)CD002945.

Chaikof EL, Brewster DC, Dalman RL, Makaroun MS, Illig KA, Sicard GA, et al. The care of patients with an abdominal aortic aneurysm: the Society for Vascular Surgery practice guidelines. J Vasc Surg. 2009;50(4 Suppl):S2–49.

Lindholt JS, Juul S, Fasting H, Henneberg EW. Hospital costs and benefits of screening for abdominal aortic aneurysms. Results from a randomised population screening trial. Eur J Vasc Endovasc Surg. 2002;23:55–60.

Article   CAS   PubMed   Google Scholar  

Norman PE, Jamrozik K, Lawrence-Brown MM, Le MT, Spencer CA, Tuohy RJ, et al. Population based randomised controlled trial on impact of screening on mortality from abdominal aortic aneurysm. BMJ. 2004;329(7477):1259–64.

Hanney SR, Castle-Clarke S, Grant J, Guthrie S, Henshall C, Mestre-Ferrandiz J, et al. How long does biomedical research take? Studying the time taken between biomedical and health research and its translation into products, policy, and practice. Health Res Policy Syst. 2015;13:1.

Cabellon S, Moncrief CL, Pierre DR, Cavenaugh DG. Incidence of abdominal aortic aneurysms in patients with artheromatous arterial disease. Am J Surg. 1983;146:575–6.

World Health Organization. WHA resolution 66.22: Follow up of the report of the Consultative Expert Working Group on Research and Development: financing and coordination. Geneva: WHO; 2013. http://www.who.int/phi/resolution_WHA-66.22.pdf . Accessed 20 Feb 2015.

Google Scholar  

Adam T, Røttingen JA, Kieny MP. Informing the establishment of the WHO Global Observatory on Health Research and Development: a call for papers. Health Res Policy Syst. 2015;13:9.

Young AJ, Terry RF, Røttingen JA, Viergever RF. Global trends in health research and development expenditures – the challenge of making reliable estimates for international comparison. Health Res Policy Syst. 2015;13:7.

Ongolo-Zogo P, Lavis JN, Tomson G, Sewankambo NK. Climate for evidence informed health system policymaking in Cameroon and Uganda before and after the introduction of knowledge translation platforms: a structured review of governmental policy documents. Health Res Policy Syst. 2015;13:2.

Yazdizadeh B, Majdzadeh R, Alami A, Amrolalaei S. How can we establish more successful knowledge networks in developing countries? Lessons learnt from knowledge networks in Iran. Health Res Policy Syst. 2014;12:63.

Ager A, Zarowsky C. Balancing the personal, local, institutional, and global: multiple case study and multidimensional scaling analysis of African experiences in addressing complexity and political economy in health research capacity strengthening. Health Res Policy Syst. 2015;13:5.

Hunter PR, Abdelrahman SH, Antwi-Agyei P, Awuah E, Cairncross S, Chappell E, et al. Needs assessment to strengthen capacity in water and sanitation research in Africa: experiences of the African SNOWS consortium. Health Res Policy Syst. 2014;12:68.

The World Health Organization. The World Health Report 2013: Research for Universal Health Coverage. Geneva: WHO; 2013.

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Acknowledgements

The authors thank Bryony Soper for most helpful comments on an earlier draft.

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Stephen R Hanney

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Hanney, S.R., González-Block, M.A. Health research improves healthcare: now we have the evidence and the chance to help the WHO spread such benefits globally. Health Res Policy Sys 13 , 12 (2015). https://doi.org/10.1186/s12961-015-0006-y

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Friends with health benefits: How the buddy system pays off when pursuing goals

Weekly targets, annual resolutions, five-year plans—all of them so troublingly elusive. With best intentions, most of us fail to stick with the goals we set.

Next time, consider pursuing them with a friend.

New field research by Assistant Professor Rachel Gershon, published in Management Science , suggests that pursuing our goals with friends may make them more attainable. Gershon, along with Cynthia Cryder of Washington University and Katy Milkman of the University of Pennsylvania, specifically looked at gym attendance and found that going with a friend—even with the hurdles of coordinating two schedules—increased visits by 35%.

“Despite adding the friction of working with another person, we saw people becoming more motivated and more likely to go,” Gershon says. “This illuminates how social incentives, which aren’t always taken into consideration, can help people overcome other barriers that stand in their way.”

The experiment recruited two groups of participants for a “Gym Bonus Month,” which lasted four weeks, from February 1 to February 28. Both groups paired up with a friend and were offered a $1 Amazon gift card for each visit to the gym. One group received this bonus every time they went to the gym, regardless of their friend’s activity; the other group only received the dollar if the two of them went together.

As noted, those who received payment only when they visited the gym with their friends doubled how often they went together, and increased their overall gym visits by 35%. Gershon and her colleagues concluded that the logistical costs of coordinating with someone else were eclipsed by two benefits. First, people enjoyed their visits more when the event was social, which made future visits more likely. Second, they felt a greater sense of accountability when meeting their friend at the gym.

“Our study identifies two types of accountability,” Gershon says. “People feel responsible to their friends, as they wanted them to get the reward, but they may also have reputational concerns that their friends would think less of them if they didn’t follow through.”

Social benefits

Although this might seem intuitive, when Gershon and her colleagues surveyed people about which of the two conditions they would prefer to be part of, the majority—more than 80%—said they would rather not have to coordinate their visits with a friend. While unsurprising in some ways, Gershon says, this suggests that people might readily see the drawbacks of coordinated visits but not recognize the potential benefits, from increasing motivation to creating stronger social bonds.

The researchers also found evidence that, when looking across both partners in a pair, this social attendance of the gym seemed to provide the greatest benefit for those who exercised less. Specifically, among the two friends, the one who exercised more frequently prior to the study saw a bump in how often he or she visited the gym. But the partner who exercised less frequently prior to the study saw an even larger bump in visits, suggesting these kinds of social incentives may be especially effective for distinct groups of people.

Beyond the context of this experiment, the findings illustrate how building a social dimension into desired behaviors can promote follow-through. Companies that want to increase employee engagement with skills training, for instance, might consider using a joint-incentive program. This could boost participation while simultaneously fortifying interpersonal bonds in the workplace.

The findings also present implications for another area that Gershon studies: referrals. Many places offer a free month of membership or some other incentive if you recruit a friend. “There are all sorts of contexts where people are trying to start a new hobby, a new exercise routine, and companies can encourage them through social networks,” she says. “This work shows that referrals may be a way for companies to not only engage additional customers, but to also increase the motivation of current customers.”

Friends with Health Benefits: A Field Experiment Rachel Gershon, Cynthia Cryder, and Katherine L. Milkman Management Science , April 2024

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Research: More People Use Mental Health Benefits When They Hear That Colleagues Use Them Too

• Laura M. Giurge,
• Lauren C. Howe,
• Zsofia Belovai,
• Guusje Lindemann,
• Sharon O’Connor

A study of 2,400 Novartis employees around the world found that simply hearing about others’ struggles can normalize accessing support at work.

Novartis has trained more than 1,000 employees as Mental Health First Aiders to offer peer-to-peer support for their colleagues. While employees were eager for the training, uptake of the program remains low. To understand why, a team of researchers conducted a randomized controlled trial with 2,400 Novartis employees who worked in the UK, Ireland, India, and Malaysia. Employees were shown one of six framings that were designed to overcome two key barriers: privacy concerns and usage concerns. They found that employees who read a story about their colleague using the service were more likely to sign up to learn more about the program, and that emphasizing the anonymity of the program did not seem to have an impact. Their findings suggest that one way to encourage employees to make use of existing mental health resources is by creating a supportive culture that embraces sharing about mental health challenges at work.

“I almost scheduled an appointment about a dozen times. But no, in the end I never went. I just wasn’t sure if my problems were big enough to warrant help and I didn’t want to take up someone else’s time unnecessarily.”

• Laura M. Giurge is an assistant professor at the London School of Economics, and a faculty affiliate at London Business School. Her research focuses on time and boundaries in organizations, workplace well-being, and the future of work. She is also passionate about translating research to the broader public through interactive and creative keynote talks, workshops, and coaching. Follow her on LinkedIn  here .
• Lauren C. Howe is an assistant professor in management at the University of Zurich. As head of research at the Center for Leadership in the Future of Work , she focuses on how human aspects, such as mindsets, socioemotional skills, and leadership, play a role in the changing world of work.
• Zsofia Belovai is a behavioral science lead for the organizational performance research practice at MoreThanNow, focusing on exploring how employee welfare can drive KPIs.
• Guusje Lindemann is a senior behavioral scientist at MoreThanNow, in the social impact and organizational performance practices, working on making the workplace better for all.
• Sharon O’Connor is the global employee wellbeing lead at Novartis. She is a founding member of the Wellbeing Executives Council of The Conference Board, and a guest lecturer on the Workplace Wellness postgraduate certificate at Trinity College Dublin.

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• Published: 17 April 2024

The economic commitment of climate change

• Maximilian Kotz   ORCID: orcid.org/0000-0003-2564-5043 1 , 2 ,
• Anders Levermann   ORCID: orcid.org/0000-0003-4432-4704 1 , 2 &
• Leonie Wenz   ORCID: orcid.org/0000-0002-8500-1568 1 , 3  

Nature volume  628 ,  pages 551–557 ( 2024 ) Cite this article

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• Environmental economics
• Environmental health
• Interdisciplinary studies
• Projection and prediction

Global projections of macroeconomic climate-change damages typically consider impacts from average annual and national temperatures over long time horizons 1 , 2 , 3 , 4 , 5 , 6 . Here we use recent empirical findings from more than 1,600 regions worldwide over the past 40 years to project sub-national damages from temperature and precipitation, including daily variability and extremes 7 , 8 . Using an empirical approach that provides a robust lower bound on the persistence of impacts on economic growth, we find that the world economy is committed to an income reduction of 19% within the next 26 years independent of future emission choices (relative to a baseline without climate impacts, likely range of 11–29% accounting for physical climate and empirical uncertainty). These damages already outweigh the mitigation costs required to limit global warming to 2 °C by sixfold over this near-term time frame and thereafter diverge strongly dependent on emission choices. Committed damages arise predominantly through changes in average temperature, but accounting for further climatic components raises estimates by approximately 50% and leads to stronger regional heterogeneity. Committed losses are projected for all regions except those at very high latitudes, at which reductions in temperature variability bring benefits. The largest losses are committed at lower latitudes in regions with lower cumulative historical emissions and lower present-day income.

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Climate damage projections beyond annual temperature

Investment incentive reduced by climate damages can be restored by optimal policy

Climate economics support for the UN climate targets

Projections of the macroeconomic damage caused by future climate change are crucial to informing public and policy debates about adaptation, mitigation and climate justice. On the one hand, adaptation against climate impacts must be justified and planned on the basis of an understanding of their future magnitude and spatial distribution 9 . This is also of importance in the context of climate justice 10 , as well as to key societal actors, including governments, central banks and private businesses, which increasingly require the inclusion of climate risks in their macroeconomic forecasts to aid adaptive decision-making 11 , 12 . On the other hand, climate mitigation policy such as the Paris Climate Agreement is often evaluated by balancing the costs of its implementation against the benefits of avoiding projected physical damages. This evaluation occurs both formally through cost–benefit analyses 1 , 4 , 5 , 6 , as well as informally through public perception of mitigation and damage costs 13 .

Projections of future damages meet challenges when informing these debates, in particular the human biases relating to uncertainty and remoteness that are raised by long-term perspectives 14 . Here we aim to overcome such challenges by assessing the extent of economic damages from climate change to which the world is already committed by historical emissions and socio-economic inertia (the range of future emission scenarios that are considered socio-economically plausible 15 ). Such a focus on the near term limits the large uncertainties about diverging future emission trajectories, the resulting long-term climate response and the validity of applying historically observed climate–economic relations over long timescales during which socio-technical conditions may change considerably. As such, this focus aims to simplify the communication and maximize the credibility of projected economic damages from future climate change.

In projecting the future economic damages from climate change, we make use of recent advances in climate econometrics that provide evidence for impacts on sub-national economic growth from numerous components of the distribution of daily temperature and precipitation 3 , 7 , 8 . Using fixed-effects panel regression models to control for potential confounders, these studies exploit within-region variation in local temperature and precipitation in a panel of more than 1,600 regions worldwide, comprising climate and income data over the past 40 years, to identify the plausibly causal effects of changes in several climate variables on economic productivity 16 , 17 . Specifically, macroeconomic impacts have been identified from changing daily temperature variability, total annual precipitation, the annual number of wet days and extreme daily rainfall that occur in addition to those already identified from changing average temperature 2 , 3 , 18 . Moreover, regional heterogeneity in these effects based on the prevailing local climatic conditions has been found using interactions terms. The selection of these climate variables follows micro-level evidence for mechanisms related to the impacts of average temperatures on labour and agricultural productivity 2 , of temperature variability on agricultural productivity and health 7 , as well as of precipitation on agricultural productivity, labour outcomes and flood damages 8 (see Extended Data Table 1 for an overview, including more detailed references). References  7 , 8 contain a more detailed motivation for the use of these particular climate variables and provide extensive empirical tests about the robustness and nature of their effects on economic output, which are summarized in Methods . By accounting for these extra climatic variables at the sub-national level, we aim for a more comprehensive description of climate impacts with greater detail across both time and space.

Constraining the persistence of impacts

A key determinant and source of discrepancy in estimates of the magnitude of future climate damages is the extent to which the impact of a climate variable on economic growth rates persists. The two extreme cases in which these impacts persist indefinitely or only instantaneously are commonly referred to as growth or level effects 19 , 20 (see Methods section ‘Empirical model specification: fixed-effects distributed lag models’ for mathematical definitions). Recent work shows that future damages from climate change depend strongly on whether growth or level effects are assumed 20 . Following refs.  2 , 18 , we provide constraints on this persistence by using distributed lag models to test the significance of delayed effects separately for each climate variable. Notably, and in contrast to refs.  2 , 18 , we use climate variables in their first-differenced form following ref.  3 , implying a dependence of the growth rate on a change in climate variables. This choice means that a baseline specification without any lags constitutes a model prior of purely level effects, in which a permanent change in the climate has only an instantaneous effect on the growth rate 3 , 19 , 21 . By including lags, one can then test whether any effects may persist further. This is in contrast to the specification used by refs.  2 , 18 , in which climate variables are used without taking the first difference, implying a dependence of the growth rate on the level of climate variables. In this alternative case, the baseline specification without any lags constitutes a model prior of pure growth effects, in which a change in climate has an infinitely persistent effect on the growth rate. Consequently, including further lags in this alternative case tests whether the initial growth impact is recovered 18 , 19 , 21 . Both of these specifications suffer from the limiting possibility that, if too few lags are included, one might falsely accept the model prior. The limitations of including a very large number of lags, including loss of data and increasing statistical uncertainty with an increasing number of parameters, mean that such a possibility is likely. By choosing a specification in which the model prior is one of level effects, our approach is therefore conservative by design, avoiding assumptions of infinite persistence of climate impacts on growth and instead providing a lower bound on this persistence based on what is observable empirically (see Methods section ‘Empirical model specification: fixed-effects distributed lag models’ for further exposition of this framework). The conservative nature of such a choice is probably the reason that ref.  19 finds much greater consistency between the impacts projected by models that use the first difference of climate variables, as opposed to their levels.

We begin our empirical analysis of the persistence of climate impacts on growth using ten lags of the first-differenced climate variables in fixed-effects distributed lag models. We detect substantial effects on economic growth at time lags of up to approximately 8–10 years for the temperature terms and up to approximately 4 years for the precipitation terms (Extended Data Fig. 1 and Extended Data Table 2 ). Furthermore, evaluation by means of information criteria indicates that the inclusion of all five climate variables and the use of these numbers of lags provide a preferable trade-off between best-fitting the data and including further terms that could cause overfitting, in comparison with model specifications excluding climate variables or including more or fewer lags (Extended Data Fig. 3 , Supplementary Methods Section  1 and Supplementary Table 1 ). We therefore remove statistically insignificant terms at later lags (Supplementary Figs. 1 – 3 and Supplementary Tables 2 – 4 ). Further tests using Monte Carlo simulations demonstrate that the empirical models are robust to autocorrelation in the lagged climate variables (Supplementary Methods Section  2 and Supplementary Figs. 4 and 5 ), that information criteria provide an effective indicator for lag selection (Supplementary Methods Section  2 and Supplementary Fig. 6 ), that the results are robust to concerns of imperfect multicollinearity between climate variables and that including several climate variables is actually necessary to isolate their separate effects (Supplementary Methods Section  3 and Supplementary Fig. 7 ). We provide a further robustness check using a restricted distributed lag model to limit oscillations in the lagged parameter estimates that may result from autocorrelation, finding that it provides similar estimates of cumulative marginal effects to the unrestricted model (Supplementary Methods Section 4 and Supplementary Figs. 8 and 9 ). Finally, to explicitly account for any outstanding uncertainty arising from the precise choice of the number of lags, we include empirical models with marginally different numbers of lags in the error-sampling procedure of our projection of future damages. On the basis of the lag-selection procedure (the significance of lagged terms in Extended Data Fig. 1 and Extended Data Table 2 , as well as information criteria in Extended Data Fig. 3 ), we sample from models with eight to ten lags for temperature and four for precipitation (models shown in Supplementary Figs. 1 – 3 and Supplementary Tables 2 – 4 ). In summary, this empirical approach to constrain the persistence of climate impacts on economic growth rates is conservative by design in avoiding assumptions of infinite persistence, but nevertheless provides a lower bound on the extent of impact persistence that is robust to the numerous tests outlined above.

Committed damages until mid-century

We combine these empirical economic response functions (Supplementary Figs. 1 – 3 and Supplementary Tables 2 – 4 ) with an ensemble of 21 climate models (see Supplementary Table 5 ) from the Coupled Model Intercomparison Project Phase 6 (CMIP-6) 22 to project the macroeconomic damages from these components of physical climate change (see Methods for further details). Bias-adjusted climate models that provide a highly accurate reproduction of observed climatological patterns with limited uncertainty (Supplementary Table 6 ) are used to avoid introducing biases in the projections. Following a well-developed literature 2 , 3 , 19 , these projections do not aim to provide a prediction of future economic growth. Instead, they are a projection of the exogenous impact of future climate conditions on the economy relative to the baselines specified by socio-economic projections, based on the plausibly causal relationships inferred by the empirical models and assuming ceteris paribus. Other exogenous factors relevant for the prediction of economic output are purposefully assumed constant.

A Monte Carlo procedure that samples from climate model projections, empirical models with different numbers of lags and model parameter estimates (obtained by 1,000 block-bootstrap resamples of each of the regressions in Supplementary Figs. 1 – 3 and Supplementary Tables 2 – 4 ) is used to estimate the combined uncertainty from these sources. Given these uncertainty distributions, we find that projected global damages are statistically indistinguishable across the two most extreme emission scenarios until 2049 (at the 5% significance level; Fig. 1 ). As such, the climate damages occurring before this time constitute those to which the world is already committed owing to the combination of past emissions and the range of future emission scenarios that are considered socio-economically plausible 15 . These committed damages comprise a permanent income reduction of 19% on average globally (population-weighted average) in comparison with a baseline without climate-change impacts (with a likely range of 11–29%, following the likelihood classification adopted by the Intergovernmental Panel on Climate Change (IPCC); see caption of Fig. 1 ). Even though levels of income per capita generally still increase relative to those of today, this constitutes a permanent income reduction for most regions, including North America and Europe (each with median income reductions of approximately 11%) and with South Asia and Africa being the most strongly affected (each with median income reductions of approximately 22%; Fig. 1 ). Under a middle-of-the road scenario of future income development (SSP2, in which SSP stands for Shared Socio-economic Pathway), this corresponds to global annual damages in 2049 of 38 trillion in 2005 international dollars (likely range of 19–59 trillion 2005 international dollars). Compared with empirical specifications that assume pure growth or pure level effects, our preferred specification that provides a robust lower bound on the extent of climate impact persistence produces damages between these two extreme assumptions (Extended Data Fig. 3 ).

Estimates of the projected reduction in income per capita from changes in all climate variables based on empirical models of climate impacts on economic output with a robust lower bound on their persistence (Extended Data Fig. 1 ) under a low-emission scenario compatible with the 2 °C warming target and a high-emission scenario (SSP2-RCP2.6 and SSP5-RCP8.5, respectively) are shown in purple and orange, respectively. Shading represents the 34% and 10% confidence intervals reflecting the likely and very likely ranges, respectively (following the likelihood classification adopted by the IPCC), having estimated uncertainty from a Monte Carlo procedure, which samples the uncertainty from the choice of physical climate models, empirical models with different numbers of lags and bootstrapped estimates of the regression parameters shown in Supplementary Figs. 1 – 3 . Vertical dashed lines show the time at which the climate damages of the two emission scenarios diverge at the 5% and 1% significance levels based on the distribution of differences between emission scenarios arising from the uncertainty sampling discussed above. Note that uncertainty in the difference of the two scenarios is smaller than the combined uncertainty of the two respective scenarios because samples of the uncertainty (climate model and empirical model choice, as well as model parameter bootstrap) are consistent across the two emission scenarios, hence the divergence of damages occurs while the uncertainty bounds of the two separate damage scenarios still overlap. Estimates of global mitigation costs from the three IAMs that provide results for the SSP2 baseline and SSP2-RCP2.6 scenario are shown in light green in the top panel, with the median of these estimates shown in bold.

Damages already outweigh mitigation costs

We compare the damages to which the world is committed over the next 25 years to estimates of the mitigation costs required to achieve the Paris Climate Agreement. Taking estimates of mitigation costs from the three integrated assessment models (IAMs) in the IPCC AR6 database 23 that provide results under comparable scenarios (SSP2 baseline and SSP2-RCP2.6, in which RCP stands for Representative Concentration Pathway), we find that the median committed climate damages are larger than the median mitigation costs in 2050 (six trillion in 2005 international dollars) by a factor of approximately six (note that estimates of mitigation costs are only provided every 10 years by the IAMs and so a comparison in 2049 is not possible). This comparison simply aims to compare the magnitude of future damages against mitigation costs, rather than to conduct a formal cost–benefit analysis of transitioning from one emission path to another. Formal cost–benefit analyses typically find that the net benefits of mitigation only emerge after 2050 (ref.  5 ), which may lead some to conclude that physical damages from climate change are simply not large enough to outweigh mitigation costs until the second half of the century. Our simple comparison of their magnitudes makes clear that damages are actually already considerably larger than mitigation costs and the delayed emergence of net mitigation benefits results primarily from the fact that damages across different emission paths are indistinguishable until mid-century (Fig. 1 ).

Although these near-term damages constitute those to which the world is already committed, we note that damage estimates diverge strongly across emission scenarios after 2049, conveying the clear benefits of mitigation from a purely economic point of view that have been emphasized in previous studies 4 , 24 . As well as the uncertainties assessed in Fig. 1 , these conclusions are robust to structural choices, such as the timescale with which changes in the moderating variables of the empirical models are estimated (Supplementary Figs. 10 and 11 ), as well as the order in which one accounts for the intertemporal and international components of currency comparison (Supplementary Fig. 12 ; see Methods for further details).

Damages from variability and extremes

Committed damages primarily arise through changes in average temperature (Fig. 2 ). This reflects the fact that projected changes in average temperature are larger than those in other climate variables when expressed as a function of their historical interannual variability (Extended Data Fig. 4 ). Because the historical variability is that on which the empirical models are estimated, larger projected changes in comparison with this variability probably lead to larger future impacts in a purely statistical sense. From a mechanistic perspective, one may plausibly interpret this result as implying that future changes in average temperature are the most unprecedented from the perspective of the historical fluctuations to which the economy is accustomed and therefore will cause the most damage. This insight may prove useful in terms of guiding adaptation measures to the sources of greatest damage.

Estimates of the median projected reduction in sub-national income per capita across emission scenarios (SSP2-RCP2.6 and SSP2-RCP8.5) as well as climate model, empirical model and model parameter uncertainty in the year in which climate damages diverge at the 5% level (2049, as identified in Fig. 1 ). a , Impacts arising from all climate variables. b – f , Impacts arising separately from changes in annual mean temperature ( b ), daily temperature variability ( c ), total annual precipitation ( d ), the annual number of wet days (>1 mm) ( e ) and extreme daily rainfall ( f ) (see Methods for further definitions). Data on national administrative boundaries are obtained from the GADM database version 3.6 and are freely available for academic use ( https://gadm.org/ ).

Nevertheless, future damages based on empirical models that consider changes in annual average temperature only and exclude the other climate variables constitute income reductions of only 13% in 2049 (Extended Data Fig. 5a , likely range 5–21%). This suggests that accounting for the other components of the distribution of temperature and precipitation raises net damages by nearly 50%. This increase arises through the further damages that these climatic components cause, but also because their inclusion reveals a stronger negative economic response to average temperatures (Extended Data Fig. 5b ). The latter finding is consistent with our Monte Carlo simulations, which suggest that the magnitude of the effect of average temperature on economic growth is underestimated unless accounting for the impacts of other correlated climate variables (Supplementary Fig. 7 ).

In terms of the relative contributions of the different climatic components to overall damages, we find that accounting for daily temperature variability causes the largest increase in overall damages relative to empirical frameworks that only consider changes in annual average temperature (4.9 percentage points, likely range 2.4–8.7 percentage points, equivalent to approximately 10 trillion international dollars). Accounting for precipitation causes smaller increases in overall damages, which are—nevertheless—equivalent to approximately 1.2 trillion international dollars: 0.01 percentage points (−0.37–0.33 percentage points), 0.34 percentage points (0.07–0.90 percentage points) and 0.36 percentage points (0.13–0.65 percentage points) from total annual precipitation, the number of wet days and extreme daily precipitation, respectively. Moreover, climate models seem to underestimate future changes in temperature variability 25 and extreme precipitation 26 , 27 in response to anthropogenic forcing as compared with that observed historically, suggesting that the true impacts from these variables may be larger.

The distribution of committed damages

The spatial distribution of committed damages (Fig. 2a ) reflects a complex interplay between the patterns of future change in several climatic components and those of historical economic vulnerability to changes in those variables. Damages resulting from increasing annual mean temperature (Fig. 2b ) are negative almost everywhere globally, and larger at lower latitudes in regions in which temperatures are already higher and economic vulnerability to temperature increases is greatest (see the response heterogeneity to mean temperature embodied in Extended Data Fig. 1a ). This occurs despite the amplified warming projected at higher latitudes 28 , suggesting that regional heterogeneity in economic vulnerability to temperature changes outweighs heterogeneity in the magnitude of future warming (Supplementary Fig. 13a ). Economic damages owing to daily temperature variability (Fig. 2c ) exhibit a strong latitudinal polarisation, primarily reflecting the physical response of daily variability to greenhouse forcing in which increases in variability across lower latitudes (and Europe) contrast decreases at high latitudes 25 (Supplementary Fig. 13b ). These two temperature terms are the dominant determinants of the pattern of overall damages (Fig. 2a ), which exhibits a strong polarity with damages across most of the globe except at the highest northern latitudes. Future changes in total annual precipitation mainly bring economic benefits except in regions of drying, such as the Mediterranean and central South America (Fig. 2d and Supplementary Fig. 13c ), but these benefits are opposed by changes in the number of wet days, which produce damages with a similar pattern of opposite sign (Fig. 2e and Supplementary Fig. 13d ). By contrast, changes in extreme daily rainfall produce damages in all regions, reflecting the intensification of daily rainfall extremes over global land areas 29 , 30 (Fig. 2f and Supplementary Fig. 13e ).

The spatial distribution of committed damages implies considerable injustice along two dimensions: culpability for the historical emissions that have caused climate change and pre-existing levels of socio-economic welfare. Spearman’s rank correlations indicate that committed damages are significantly larger in countries with smaller historical cumulative emissions, as well as in regions with lower current income per capita (Fig. 3 ). This implies that those countries that will suffer the most from the damages already committed are those that are least responsible for climate change and which also have the least resources to adapt to it.

Estimates of the median projected change in national income per capita across emission scenarios (RCP2.6 and RCP8.5) as well as climate model, empirical model and model parameter uncertainty in the year in which climate damages diverge at the 5% level (2049, as identified in Fig. 1 ) are plotted against cumulative national emissions per capita in 2020 (from the Global Carbon Project) and coloured by national income per capita in 2020 (from the World Bank) in a and vice versa in b . In each panel, the size of each scatter point is weighted by the national population in 2020 (from the World Bank). Inset numbers indicate the Spearman’s rank correlation ρ and P -values for a hypothesis test whose null hypothesis is of no correlation, as well as the Spearman’s rank correlation weighted by national population.

To further quantify this heterogeneity, we assess the difference in committed damages between the upper and lower quartiles of regions when ranked by present income levels and historical cumulative emissions (using a population weighting to both define the quartiles and estimate the group averages). On average, the quartile of countries with lower income are committed to an income loss that is 8.9 percentage points (or 61%) greater than the upper quartile (Extended Data Fig. 6 ), with a likely range of 3.8–14.7 percentage points across the uncertainty sampling of our damage projections (following the likelihood classification adopted by the IPCC). Similarly, the quartile of countries with lower historical cumulative emissions are committed to an income loss that is 6.9 percentage points (or 40%) greater than the upper quartile, with a likely range of 0.27–12 percentage points. These patterns reemphasize the prevalence of injustice in climate impacts 31 , 32 , 33 in the context of the damages to which the world is already committed by historical emissions and socio-economic inertia.

Contextualizing the magnitude of damages

The magnitude of projected economic damages exceeds previous literature estimates 2 , 3 , arising from several developments made on previous approaches. Our estimates are larger than those of ref.  2 (see first row of Extended Data Table 3 ), primarily because of the facts that sub-national estimates typically show a steeper temperature response (see also refs.  3 , 34 ) and that accounting for other climatic components raises damage estimates (Extended Data Fig. 5 ). However, we note that our empirical approach using first-differenced climate variables is conservative compared with that of ref.  2 in regard to the persistence of climate impacts on growth (see introduction and Methods section ‘Empirical model specification: fixed-effects distributed lag models’), an important determinant of the magnitude of long-term damages 19 , 21 . Using a similar empirical specification to ref.  2 , which assumes infinite persistence while maintaining the rest of our approach (sub-national data and further climate variables), produces considerably larger damages (purple curve of Extended Data Fig. 3 ). Compared with studies that do take the first difference of climate variables 3 , 35 , our estimates are also larger (see second and third rows of Extended Data Table 3 ). The inclusion of further climate variables (Extended Data Fig. 5 ) and a sufficient number of lags to more adequately capture the extent of impact persistence (Extended Data Figs. 1 and 2 ) are the main sources of this difference, as is the use of specifications that capture nonlinearities in the temperature response when compared with ref.  35 . In summary, our estimates develop on previous studies by incorporating the latest data and empirical insights 7 , 8 , as well as in providing a robust empirical lower bound on the persistence of impacts on economic growth, which constitutes a middle ground between the extremes of the growth-versus-levels debate 19 , 21 (Extended Data Fig. 3 ).

Compared with the fraction of variance explained by the empirical models historically (<5%), the projection of reductions in income of 19% may seem large. This arises owing to the fact that projected changes in climatic conditions are much larger than those that were experienced historically, particularly for changes in average temperature (Extended Data Fig. 4 ). As such, any assessment of future climate-change impacts necessarily requires an extrapolation outside the range of the historical data on which the empirical impact models were evaluated. Nevertheless, these models constitute the most state-of-the-art methods for inference of plausibly causal climate impacts based on observed data. Moreover, we take explicit steps to limit out-of-sample extrapolation by capping the moderating variables of the interaction terms at the 95th percentile of the historical distribution (see Methods ). This avoids extrapolating the marginal effects outside what was observed historically. Given the nonlinear response of economic output to annual mean temperature (Extended Data Fig. 1 and Extended Data Table 2 ), this is a conservative choice that limits the magnitude of damages that we project. Furthermore, back-of-the-envelope calculations indicate that the projected damages are consistent with the magnitude and patterns of historical economic development (see Supplementary Discussion Section  5 ).

Missing impacts and spatial spillovers

Despite assessing several climatic components from which economic impacts have recently been identified 3 , 7 , 8 , this assessment of aggregate climate damages should not be considered comprehensive. Important channels such as impacts from heatwaves 31 , sea-level rise 36 , tropical cyclones 37 and tipping points 38 , 39 , as well as non-market damages such as those to ecosystems 40 and human health 41 , are not considered in these estimates. Sea-level rise is unlikely to be feasibly incorporated into empirical assessments such as this because historical sea-level variability is mostly small. Non-market damages are inherently intractable within our estimates of impacts on aggregate monetary output and estimates of these impacts could arguably be considered as extra to those identified here. Recent empirical work suggests that accounting for these channels would probably raise estimates of these committed damages, with larger damages continuing to arise in the global south 31 , 36 , 37 , 38 , 39 , 40 , 41 , 42 .

Moreover, our main empirical analysis does not explicitly evaluate the potential for impacts in local regions to produce effects that ‘spill over’ into other regions. Such effects may further mitigate or amplify the impacts we estimate, for example, if companies relocate production from one affected region to another or if impacts propagate along supply chains. The current literature indicates that trade plays a substantial role in propagating spillover effects 43 , 44 , making their assessment at the sub-national level challenging without available data on sub-national trade dependencies. Studies accounting for only spatially adjacent neighbours indicate that negative impacts in one region induce further negative impacts in neighbouring regions 45 , 46 , 47 , 48 , suggesting that our projected damages are probably conservative by excluding these effects. In Supplementary Fig. 14 , we assess spillovers from neighbouring regions using a spatial-lag model. For simplicity, this analysis excludes temporal lags, focusing only on contemporaneous effects. The results show that accounting for spatial spillovers can amplify the overall magnitude, and also the heterogeneity, of impacts. Consistent with previous literature, this indicates that the overall magnitude (Fig. 1 ) and heterogeneity (Fig. 3 ) of damages that we project in our main specification may be conservative without explicitly accounting for spillovers. We note that further analysis that addresses both spatially and trade-connected spillovers, while also accounting for delayed impacts using temporal lags, would be necessary to adequately address this question fully. These approaches offer fruitful avenues for further research but are beyond the scope of this manuscript, which primarily aims to explore the impacts of different climate conditions and their persistence.

Policy implications

We find that the economic damages resulting from climate change until 2049 are those to which the world economy is already committed and that these greatly outweigh the costs required to mitigate emissions in line with the 2 °C target of the Paris Climate Agreement (Fig. 1 ). This assessment is complementary to formal analyses of the net costs and benefits associated with moving from one emission path to another, which typically find that net benefits of mitigation only emerge in the second half of the century 5 . Our simple comparison of the magnitude of damages and mitigation costs makes clear that this is primarily because damages are indistinguishable across emissions scenarios—that is, committed—until mid-century (Fig. 1 ) and that they are actually already much larger than mitigation costs. For simplicity, and owing to the availability of data, we compare damages to mitigation costs at the global level. Regional estimates of mitigation costs may shed further light on the national incentives for mitigation to which our results already hint, of relevance for international climate policy. Although these damages are committed from a mitigation perspective, adaptation may provide an opportunity to reduce them. Moreover, the strong divergence of damages after mid-century reemphasizes the clear benefits of mitigation from a purely economic perspective, as highlighted in previous studies 1 , 4 , 6 , 24 .

Historical climate data

Historical daily 2-m temperature and precipitation totals (in mm) are obtained for the period 1979–2019 from the W5E5 database. The W5E5 dataset comes from ERA-5, a state-of-the-art reanalysis of historical observations, but has been bias-adjusted by applying version 2.0 of the WATCH Forcing Data to ERA-5 reanalysis data and precipitation data from version 2.3 of the Global Precipitation Climatology Project to better reflect ground-based measurements 49 , 50 , 51 . We obtain these data on a 0.5° × 0.5° grid from the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) database. Notably, these historical data have been used to bias-adjust future climate projections from CMIP-6 (see the following section), ensuring consistency between the distribution of historical daily weather on which our empirical models were estimated and the climate projections used to estimate future damages. These data are publicly available from the ISIMIP database. See refs.  7 , 8 for robustness tests of the empirical models to the choice of climate data reanalysis products.

Future climate data

Daily 2-m temperature and precipitation totals (in mm) are taken from 21 climate models participating in CMIP-6 under a high (RCP8.5) and a low (RCP2.6) greenhouse gas emission scenario from 2015 to 2100. The data have been bias-adjusted and statistically downscaled to a common half-degree grid to reflect the historical distribution of daily temperature and precipitation of the W5E5 dataset using the trend-preserving method developed by the ISIMIP 50 , 52 . As such, the climate model data reproduce observed climatological patterns exceptionally well (Supplementary Table 5 ). Gridded data are publicly available from the ISIMIP database.

Historical economic data

Historical economic data come from the DOSE database of sub-national economic output 53 . We use a recent revision to the DOSE dataset that provides data across 83 countries, 1,660 sub-national regions with varying temporal coverage from 1960 to 2019. Sub-national units constitute the first administrative division below national, for example, states for the USA and provinces for China. Data come from measures of gross regional product per capita (GRPpc) or income per capita in local currencies, reflecting the values reported in national statistical agencies, yearbooks and, in some cases, academic literature. We follow previous literature 3 , 7 , 8 , 54 and assess real sub-national output per capita by first converting values from local currencies to US dollars to account for diverging national inflationary tendencies and then account for US inflation using a US deflator. Alternatively, one might first account for national inflation and then convert between currencies. Supplementary Fig. 12 demonstrates that our conclusions are consistent when accounting for price changes in the reversed order, although the magnitude of estimated damages varies. See the documentation of the DOSE dataset for further discussion of these choices. Conversions between currencies are conducted using exchange rates from the FRED database of the Federal Reserve Bank of St. Louis 55 and the national deflators from the World Bank 56 .

Future socio-economic data

Baseline gridded gross domestic product (GDP) and population data for the period 2015–2100 are taken from the middle-of-the-road scenario SSP2 (ref.  15 ). Population data have been downscaled to a half-degree grid by the ISIMIP following the methodologies of refs.  57 , 58 , which we then aggregate to the sub-national level of our economic data using the spatial aggregation procedure described below. Because current methodologies for downscaling the GDP of the SSPs use downscaled population to do so, per-capita estimates of GDP with a realistic distribution at the sub-national level are not readily available for the SSPs. We therefore use national-level GDP per capita (GDPpc) projections for all sub-national regions of a given country, assuming homogeneity within countries in terms of baseline GDPpc. Here we use projections that have been updated to account for the impact of the COVID-19 pandemic on the trajectory of future income, while remaining consistent with the long-term development of the SSPs 59 . The choice of baseline SSP alters the magnitude of projected climate damages in monetary terms, but when assessed in terms of percentage change from the baseline, the choice of socio-economic scenario is inconsequential. Gridded SSP population data and national-level GDPpc data are publicly available from the ISIMIP database. Sub-national estimates as used in this study are available in the code and data replication files.

Climate variables

Following recent literature 3 , 7 , 8 , we calculate an array of climate variables for which substantial impacts on macroeconomic output have been identified empirically, supported by further evidence at the micro level for plausible underlying mechanisms. See refs.  7 , 8 for an extensive motivation for the use of these particular climate variables and for detailed empirical tests on the nature and robustness of their effects on economic output. To summarize, these studies have found evidence for independent impacts on economic growth rates from annual average temperature, daily temperature variability, total annual precipitation, the annual number of wet days and extreme daily rainfall. Assessments of daily temperature variability were motivated by evidence of impacts on agricultural output and human health, as well as macroeconomic literature on the impacts of volatility on growth when manifest in different dimensions, such as government spending, exchange rates and even output itself 7 . Assessments of precipitation impacts were motivated by evidence of impacts on agricultural productivity, metropolitan labour outcomes and conflict, as well as damages caused by flash flooding 8 . See Extended Data Table 1 for detailed references to empirical studies of these physical mechanisms. Marked impacts of daily temperature variability, total annual precipitation, the number of wet days and extreme daily rainfall on macroeconomic output were identified robustly across different climate datasets, spatial aggregation schemes, specifications of regional time trends and error-clustering approaches. They were also found to be robust to the consideration of temperature extremes 7 , 8 . Furthermore, these climate variables were identified as having independent effects on economic output 7 , 8 , which we further explain here using Monte Carlo simulations to demonstrate the robustness of the results to concerns of imperfect multicollinearity between climate variables (Supplementary Methods Section  2 ), as well as by using information criteria (Supplementary Table 1 ) to demonstrate that including several lagged climate variables provides a preferable trade-off between optimally describing the data and limiting the possibility of overfitting.

We calculate these variables from the distribution of daily, d , temperature, T x , d , and precipitation, P x , d , at the grid-cell, x , level for both the historical and future climate data. As well as annual mean temperature, \({\bar{T}}_{x,y}\) , and annual total precipitation, P x , y , we calculate annual, y , measures of daily temperature variability, \({\widetilde{T}}_{x,y}\) :

the number of wet days, Pwd x , y :

and extreme daily rainfall:

in which T x , d , m , y is the grid-cell-specific daily temperature in month m and year y , \({\bar{T}}_{x,m,{y}}\) is the year and grid-cell-specific monthly, m , mean temperature, D m and D y the number of days in a given month m or year y , respectively, H the Heaviside step function, 1 mm the threshold used to define wet days and P 99.9 x is the 99.9th percentile of historical (1979–2019) daily precipitation at the grid-cell level. Units of the climate measures are degrees Celsius for annual mean temperature and daily temperature variability, millimetres for total annual precipitation and extreme daily precipitation, and simply the number of days for the annual number of wet days.

We also calculated weighted standard deviations of monthly rainfall totals as also used in ref.  8 but do not include them in our projections as we find that, when accounting for delayed effects, their effect becomes statistically indistinct and is better captured by changes in total annual rainfall.

Spatial aggregation

We aggregate grid-cell-level historical and future climate measures, as well as grid-cell-level future GDPpc and population, to the level of the first administrative unit below national level of the GADM database, using an area-weighting algorithm that estimates the portion of each grid cell falling within an administrative boundary. We use this as our baseline specification following previous findings that the effect of area or population weighting at the sub-national level is negligible 7 , 8 .

Empirical model specification: fixed-effects distributed lag models

Following a wide range of climate econometric literature 16 , 60 , we use panel regression models with a selection of fixed effects and time trends to isolate plausibly exogenous variation with which to maximize confidence in a causal interpretation of the effects of climate on economic growth rates. The use of region fixed effects, μ r , accounts for unobserved time-invariant differences between regions, such as prevailing climatic norms and growth rates owing to historical and geopolitical factors. The use of yearly fixed effects, η y , accounts for regionally invariant annual shocks to the global climate or economy such as the El Niño–Southern Oscillation or global recessions. In our baseline specification, we also include region-specific linear time trends, k r y , to exclude the possibility of spurious correlations resulting from common slow-moving trends in climate and growth.

The persistence of climate impacts on economic growth rates is a key determinant of the long-term magnitude of damages. Methods for inferring the extent of persistence in impacts on growth rates have typically used lagged climate variables to evaluate the presence of delayed effects or catch-up dynamics 2 , 18 . For example, consider starting from a model in which a climate condition, C r , y , (for example, annual mean temperature) affects the growth rate, Δlgrp r , y (the first difference of the logarithm of gross regional product) of region r in year y :

which we refer to as a ‘pure growth effects’ model in the main text. Typically, further lags are included,

and the cumulative effect of all lagged terms is evaluated to assess the extent to which climate impacts on growth rates persist. Following ref.  18 , in the case that,

the implication is that impacts on the growth rate persist up to NL years after the initial shock (possibly to a weaker or a stronger extent), whereas if

then the initial impact on the growth rate is recovered after NL years and the effect is only one on the level of output. However, we note that such approaches are limited by the fact that, when including an insufficient number of lags to detect a recovery of the growth rates, one may find equation ( 6 ) to be satisfied and incorrectly assume that a change in climatic conditions affects the growth rate indefinitely. In practice, given a limited record of historical data, including too few lags to confidently conclude in an infinitely persistent impact on the growth rate is likely, particularly over the long timescales over which future climate damages are often projected 2 , 24 . To avoid this issue, we instead begin our analysis with a model for which the level of output, lgrp r , y , depends on the level of a climate variable, C r , y :

Given the non-stationarity of the level of output, we follow the literature 19 and estimate such an equation in first-differenced form as,

which we refer to as a model of ‘pure level effects’ in the main text. This model constitutes a baseline specification in which a permanent change in the climate variable produces an instantaneous impact on the growth rate and a permanent effect only on the level of output. By including lagged variables in this specification,

we are able to test whether the impacts on the growth rate persist any further than instantaneously by evaluating whether α L  > 0 are statistically significantly different from zero. Even though this framework is also limited by the possibility of including too few lags, the choice of a baseline model specification in which impacts on the growth rate do not persist means that, in the case of including too few lags, the framework reverts to the baseline specification of level effects. As such, this framework is conservative with respect to the persistence of impacts and the magnitude of future damages. It naturally avoids assumptions of infinite persistence and we are able to interpret any persistence that we identify with equation ( 9 ) as a lower bound on the extent of climate impact persistence on growth rates. See the main text for further discussion of this specification choice, in particular about its conservative nature compared with previous literature estimates, such as refs.  2 , 18 .

We allow the response to climatic changes to vary across regions, using interactions of the climate variables with historical average (1979–2019) climatic conditions reflecting heterogenous effects identified in previous work 7 , 8 . Following this previous work, the moderating variables of these interaction terms constitute the historical average of either the variable itself or of the seasonal temperature difference, \({\hat{T}}_{r}\) , or annual mean temperature, \({\bar{T}}_{r}\) , in the case of daily temperature variability 7 and extreme daily rainfall, respectively 8 .

The resulting regression equation with N and M lagged variables, respectively, reads:

in which Δlgrp r , y is the annual, regional GRPpc growth rate, measured as the first difference of the logarithm of real GRPpc, following previous work 2 , 3 , 7 , 8 , 18 , 19 . Fixed-effects regressions were run using the fixest package in R (ref.  61 ).

Estimates of the coefficients of interest α i , L are shown in Extended Data Fig. 1 for N  =  M  = 10 lags and for our preferred choice of the number of lags in Supplementary Figs. 1 – 3 . In Extended Data Fig. 1 , errors are shown clustered at the regional level, but for the construction of damage projections, we block-bootstrap the regressions by region 1,000 times to provide a range of parameter estimates with which to sample the projection uncertainty (following refs.  2 , 31 ).

Spatial-lag model

In Supplementary Fig. 14 , we present the results from a spatial-lag model that explores the potential for climate impacts to ‘spill over’ into spatially neighbouring regions. We measure the distance between centroids of each pair of sub-national regions and construct spatial lags that take the average of the first-differenced climate variables and their interaction terms over neighbouring regions that are at distances of 0–500, 500–1,000, 1,000–1,500 and 1,500–2000 km (spatial lags, ‘SL’, 1 to 4). For simplicity, we then assess a spatial-lag model without temporal lags to assess spatial spillovers of contemporaneous climate impacts. This model takes the form:

in which SL indicates the spatial lag of each climate variable and interaction term. In Supplementary Fig. 14 , we plot the cumulative marginal effect of each climate variable at different baseline climate conditions by summing the coefficients for each climate variable and interaction term, for example, for average temperature impacts as:

These cumulative marginal effects can be regarded as the overall spatially dependent impact to an individual region given a one-unit shock to a climate variable in that region and all neighbouring regions at a given value of the moderating variable of the interaction term.

Constructing projections of economic damage from future climate change

We construct projections of future climate damages by applying the coefficients estimated in equation ( 10 ) and shown in Supplementary Tables 2 – 4 (when including only lags with statistically significant effects in specifications that limit overfitting; see Supplementary Methods Section  1 ) to projections of future climate change from the CMIP-6 models. Year-on-year changes in each primary climate variable of interest are calculated to reflect the year-to-year variations used in the empirical models. 30-year moving averages of the moderating variables of the interaction terms are calculated to reflect the long-term average of climatic conditions that were used for the moderating variables in the empirical models. By using moving averages in the projections, we account for the changing vulnerability to climate shocks based on the evolving long-term conditions (Supplementary Figs. 10 and 11 show that the results are robust to the precise choice of the window of this moving average). Although these climate variables are not differenced, the fact that the bias-adjusted climate models reproduce observed climatological patterns across regions for these moderating variables very accurately (Supplementary Table 6 ) with limited spread across models (<3%) precludes the possibility that any considerable bias or uncertainty is introduced by this methodological choice. However, we impose caps on these moderating variables at the 95th percentile at which they were observed in the historical data to prevent extrapolation of the marginal effects outside the range in which the regressions were estimated. This is a conservative choice that limits the magnitude of our damage projections.

Time series of primary climate variables and moderating climate variables are then combined with estimates of the empirical model parameters to evaluate the regression coefficients in equation ( 10 ), producing a time series of annual GRPpc growth-rate reductions for a given emission scenario, climate model and set of empirical model parameters. The resulting time series of growth-rate impacts reflects those occurring owing to future climate change. By contrast, a future scenario with no climate change would be one in which climate variables do not change (other than with random year-to-year fluctuations) and hence the time-averaged evaluation of equation ( 10 ) would be zero. Our approach therefore implicitly compares the future climate-change scenario to this no-climate-change baseline scenario.

The time series of growth-rate impacts owing to future climate change in region r and year y , δ r , y , are then added to the future baseline growth rates, π r , y (in log-diff form), obtained from the SSP2 scenario to yield trajectories of damaged GRPpc growth rates, ρ r , y . These trajectories are aggregated over time to estimate the future trajectory of GRPpc with future climate impacts:

in which GRPpc r , y =2020 is the initial log level of GRPpc. We begin damage estimates in 2020 to reflect the damages occurring since the end of the period for which we estimate the empirical models (1979–2019) and to match the timing of mitigation-cost estimates from most IAMs (see below).

For each emission scenario, this procedure is repeated 1,000 times while randomly sampling from the selection of climate models, the selection of empirical models with different numbers of lags (shown in Supplementary Figs. 1 – 3 and Supplementary Tables 2 – 4 ) and bootstrapped estimates of the regression parameters. The result is an ensemble of future GRPpc trajectories that reflect uncertainty from both physical climate change and the structural and sampling uncertainty of the empirical models.

Estimates of mitigation costs

We obtain IPCC estimates of the aggregate costs of emission mitigation from the AR6 Scenario Explorer and Database hosted by IIASA 23 . Specifically, we search the AR6 Scenarios Database World v1.1 for IAMs that provided estimates of global GDP and population under both a SSP2 baseline and a SSP2-RCP2.6 scenario to maintain consistency with the socio-economic and emission scenarios of the climate damage projections. We find five IAMs that provide data for these scenarios, namely, MESSAGE-GLOBIOM 1.0, REMIND-MAgPIE 1.5, AIM/GCE 2.0, GCAM 4.2 and WITCH-GLOBIOM 3.1. Of these five IAMs, we use the results only from the first three that passed the IPCC vetting procedure for reproducing historical emission and climate trajectories. We then estimate global mitigation costs as the percentage difference in global per capita GDP between the SSP2 baseline and the SSP2-RCP2.6 emission scenario. In the case of one of these IAMs, estimates of mitigation costs begin in 2020, whereas in the case of two others, mitigation costs begin in 2010. The mitigation cost estimates before 2020 in these two IAMs are mostly negligible, and our choice to begin comparison with damage estimates in 2020 is conservative with respect to the relative weight of climate damages compared with mitigation costs for these two IAMs.

Data availability

Data on economic production and ERA-5 climate data are publicly available at https://doi.org/10.5281/zenodo.4681306 (ref. 62 ) and https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era5 , respectively. Data on mitigation costs are publicly available at https://data.ene.iiasa.ac.at/ar6/#/downloads . Processed climate and economic data, as well as all other necessary data for reproduction of the results, are available at the public repository https://doi.org/10.5281/zenodo.10562951  (ref. 63 ).

Code availability

All code necessary for reproduction of the results is available at the public repository https://doi.org/10.5281/zenodo.10562951  (ref. 63 ).

Glanemann, N., Willner, S. N. & Levermann, A. Paris Climate Agreement passes the cost-benefit test. Nat. Commun. 11 , 110 (2020).

Article   ADS   CAS   PubMed   PubMed Central   Google Scholar  

Burke, M., Hsiang, S. M. & Miguel, E. Global non-linear effect of temperature on economic production. Nature 527 , 235–239 (2015).

Article   ADS   CAS   PubMed   Google Scholar  

Kalkuhl, M. & Wenz, L. The impact of climate conditions on economic production. Evidence from a global panel of regions. J. Environ. Econ. Manag. 103 , 102360 (2020).

Article   Google Scholar  

Moore, F. C. & Diaz, D. B. Temperature impacts on economic growth warrant stringent mitigation policy. Nat. Clim. Change 5 , 127–131 (2015).

Article   ADS   Google Scholar  

Drouet, L., Bosetti, V. & Tavoni, M. Net economic benefits of well-below 2°C scenarios and associated uncertainties. Oxf. Open Clim. Change 2 , kgac003 (2022).

Ueckerdt, F. et al. The economically optimal warming limit of the planet. Earth Syst. Dyn. 10 , 741–763 (2019).

Kotz, M., Wenz, L., Stechemesser, A., Kalkuhl, M. & Levermann, A. Day-to-day temperature variability reduces economic growth. Nat. Clim. Change 11 , 319–325 (2021).

Kotz, M., Levermann, A. & Wenz, L. The effect of rainfall changes on economic production. Nature 601 , 223–227 (2022).

Kousky, C. Informing climate adaptation: a review of the economic costs of natural disasters. Energy Econ. 46 , 576–592 (2014).

Harlan, S. L. et al. in Climate Change and Society: Sociological Perspectives (eds Dunlap, R. E. & Brulle, R. J.) 127–163 (Oxford Univ. Press, 2015).

Bolton, P. et al. The Green Swan (BIS Books, 2020).

Alogoskoufis, S. et al. ECB Economy-wide Climate Stress Test: Methodology and Results European Central Bank, 2021).

Weber, E. U. What shapes perceptions of climate change? Wiley Interdiscip. Rev. Clim. Change 1 , 332–342 (2010).

Markowitz, E. M. & Shariff, A. F. Climate change and moral judgement. Nat. Clim. Change 2 , 243–247 (2012).

Riahi, K. et al. The shared socioeconomic pathways and their energy, land use, and greenhouse gas emissions implications: an overview. Glob. Environ. Change 42 , 153–168 (2017).

Auffhammer, M., Hsiang, S. M., Schlenker, W. & Sobel, A. Using weather data and climate model output in economic analyses of climate change. Rev. Environ. Econ. Policy 7 , 181–198 (2013).

Kolstad, C. D. & Moore, F. C. Estimating the economic impacts of climate change using weather observations. Rev. Environ. Econ. Policy 14 , 1–24 (2020).

Dell, M., Jones, B. F. & Olken, B. A. Temperature shocks and economic growth: evidence from the last half century. Am. Econ. J. Macroecon. 4 , 66–95 (2012).

Newell, R. G., Prest, B. C. & Sexton, S. E. The GDP-temperature relationship: implications for climate change damages. J. Environ. Econ. Manag. 108 , 102445 (2021).

Kikstra, J. S. et al. The social cost of carbon dioxide under climate-economy feedbacks and temperature variability. Environ. Res. Lett. 16 , 094037 (2021).

Article   ADS   CAS   Google Scholar  

Bastien-Olvera, B. & Moore, F. Persistent effect of temperature on GDP identified from lower frequency temperature variability. Environ. Res. Lett. 17 , 084038 (2022).

Eyring, V. et al. Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization. Geosci. Model Dev. 9 , 1937–1958 (2016).

Byers, E. et al. AR6 scenarios database. Zenodo https://zenodo.org/records/7197970 (2022).

Burke, M., Davis, W. M. & Diffenbaugh, N. S. Large potential reduction in economic damages under UN mitigation targets. Nature 557 , 549–553 (2018).

Kotz, M., Wenz, L. & Levermann, A. Footprint of greenhouse forcing in daily temperature variability. Proc. Natl Acad. Sci. 118 , e2103294118 (2021).

Article   CAS   PubMed   PubMed Central   Google Scholar  

Myhre, G. et al. Frequency of extreme precipitation increases extensively with event rareness under global warming. Sci. Rep. 9 , 16063 (2019).

Min, S.-K., Zhang, X., Zwiers, F. W. & Hegerl, G. C. Human contribution to more-intense precipitation extremes. Nature 470 , 378–381 (2011).

England, M. R., Eisenman, I., Lutsko, N. J. & Wagner, T. J. The recent emergence of Arctic Amplification. Geophys. Res. Lett. 48 , e2021GL094086 (2021).

Fischer, E. M. & Knutti, R. Anthropogenic contribution to global occurrence of heavy-precipitation and high-temperature extremes. Nat. Clim. Change 5 , 560–564 (2015).

Pfahl, S., O’Gorman, P. A. & Fischer, E. M. Understanding the regional pattern of projected future changes in extreme precipitation. Nat. Clim. Change 7 , 423–427 (2017).

Callahan, C. W. & Mankin, J. S. Globally unequal effect of extreme heat on economic growth. Sci. Adv. 8 , eadd3726 (2022).

Diffenbaugh, N. S. & Burke, M. Global warming has increased global economic inequality. Proc. Natl Acad. Sci. 116 , 9808–9813 (2019).

Callahan, C. W. & Mankin, J. S. National attribution of historical climate damages. Clim. Change 172 , 40 (2022).

Burke, M. & Tanutama, V. Climatic constraints on aggregate economic output. National Bureau of Economic Research, Working Paper 25779. https://doi.org/10.3386/w25779 (2019).

Kahn, M. E. et al. Long-term macroeconomic effects of climate change: a cross-country analysis. Energy Econ. 104 , 105624 (2021).

Desmet, K. et al. Evaluating the economic cost of coastal flooding. National Bureau of Economic Research, Working Paper 24918. https://doi.org/10.3386/w24918 (2018).

Hsiang, S. M. & Jina, A. S. The causal effect of environmental catastrophe on long-run economic growth: evidence from 6,700 cyclones. National Bureau of Economic Research, Working Paper 20352. https://doi.org/10.3386/w2035 (2014).

Ritchie, P. D. et al. Shifts in national land use and food production in Great Britain after a climate tipping point. Nat. Food 1 , 76–83 (2020).

Dietz, S., Rising, J., Stoerk, T. & Wagner, G. Economic impacts of tipping points in the climate system. Proc. Natl Acad. Sci. 118 , e2103081118 (2021).

Bastien-Olvera, B. A. & Moore, F. C. Use and non-use value of nature and the social cost of carbon. Nat. Sustain. 4 , 101–108 (2021).

Carleton, T. et al. Valuing the global mortality consequences of climate change accounting for adaptation costs and benefits. Q. J. Econ. 137 , 2037–2105 (2022).

Bastien-Olvera, B. A. et al. Unequal climate impacts on global values of natural capital. Nature 625 , 722–727 (2024).

Malik, A. et al. Impacts of climate change and extreme weather on food supply chains cascade across sectors and regions in Australia. Nat. Food 3 , 631–643 (2022).

Article   ADS   PubMed   Google Scholar  

Kuhla, K., Willner, S. N., Otto, C., Geiger, T. & Levermann, A. Ripple resonance amplifies economic welfare loss from weather extremes. Environ. Res. Lett. 16 , 114010 (2021).

Schleypen, J. R., Mistry, M. N., Saeed, F. & Dasgupta, S. Sharing the burden: quantifying climate change spillovers in the European Union under the Paris Agreement. Spat. Econ. Anal. 17 , 67–82 (2022).

Dasgupta, S., Bosello, F., De Cian, E. & Mistry, M. Global temperature effects on economic activity and equity: a spatial analysis. European Institute on Economics and the Environment, Working Paper 22-1 (2022).

Neal, T. The importance of external weather effects in projecting the macroeconomic impacts of climate change. UNSW Economics Working Paper 2023-09 (2023).

Deryugina, T. & Hsiang, S. M. Does the environment still matter? Daily temperature and income in the United States. National Bureau of Economic Research, Working Paper 20750. https://doi.org/10.3386/w20750 (2014).

Hersbach, H. et al. The ERA5 global reanalysis. Q. J. R. Meteorol. Soc. 146 , 1999–2049 (2020).

Cucchi, M. et al. WFDE5: bias-adjusted ERA5 reanalysis data for impact studies. Earth Syst. Sci. Data 12 , 2097–2120 (2020).

Adler, R. et al. The New Version 2.3 of the Global Precipitation Climatology Project (GPCP) Monthly Analysis Product 1072–1084 (University of Maryland, 2016).

Lange, S. Trend-preserving bias adjustment and statistical downscaling with ISIMIP3BASD (v1.0). Geosci. Model Dev. 12 , 3055–3070 (2019).

Wenz, L., Carr, R. D., Kögel, N., Kotz, M. & Kalkuhl, M. DOSE – global data set of reported sub-national economic output. Sci. Data 10 , 425 (2023).

Article   PubMed   PubMed Central   Google Scholar  

Gennaioli, N., La Porta, R., Lopez De Silanes, F. & Shleifer, A. Growth in regions. J. Econ. Growth 19 , 259–309 (2014).

Board of Governors of the Federal Reserve System (US). U.S. dollars to euro spot exchange rate. https://fred.stlouisfed.org/series/AEXUSEU (2022).

World Bank. GDP deflator. https://data.worldbank.org/indicator/NY.GDP.DEFL.ZS (2022).

Jones, B. & O’Neill, B. C. Spatially explicit global population scenarios consistent with the Shared Socioeconomic Pathways. Environ. Res. Lett. 11 , 084003 (2016).

Murakami, D. & Yamagata, Y. Estimation of gridded population and GDP scenarios with spatially explicit statistical downscaling. Sustainability 11 , 2106 (2019).

Koch, J. & Leimbach, M. Update of SSP GDP projections: capturing recent changes in national accounting, PPP conversion and Covid 19 impacts. Ecol. Econ. 206 (2023).

Carleton, T. A. & Hsiang, S. M. Social and economic impacts of climate. Science 353 , aad9837 (2016).

Article   PubMed   Google Scholar  

Bergé, L. Efficient estimation of maximum likelihood models with multiple fixed-effects: the R package FENmlm. DEM Discussion Paper Series 18-13 (2018).

Kalkuhl, M., Kotz, M. & Wenz, L. DOSE - The MCC-PIK Database Of Subnational Economic output. Zenodo https://zenodo.org/doi/10.5281/zenodo.4681305 (2021).

Kotz, M., Wenz, L. & Levermann, A. Data and code for “The economic commitment of climate change”. Zenodo https://zenodo.org/doi/10.5281/zenodo.10562951 (2024).

Dasgupta, S. et al. Effects of climate change on combined labour productivity and supply: an empirical, multi-model study. Lancet Planet. Health 5 , e455–e465 (2021).

Lobell, D. B. et al. The critical role of extreme heat for maize production in the United States. Nat. Clim. Change 3 , 497–501 (2013).

Zhao, C. et al. Temperature increase reduces global yields of major crops in four independent estimates. Proc. Natl Acad. Sci. 114 , 9326–9331 (2017).

Wheeler, T. R., Craufurd, P. Q., Ellis, R. H., Porter, J. R. & Prasad, P. V. Temperature variability and the yield of annual crops. Agric. Ecosyst. Environ. 82 , 159–167 (2000).

Rowhani, P., Lobell, D. B., Linderman, M. & Ramankutty, N. Climate variability and crop production in Tanzania. Agric. For. Meteorol. 151 , 449–460 (2011).

Ceglar, A., Toreti, A., Lecerf, R., Van der Velde, M. & Dentener, F. Impact of meteorological drivers on regional inter-annual crop yield variability in France. Agric. For. Meteorol. 216 , 58–67 (2016).

Shi, L., Kloog, I., Zanobetti, A., Liu, P. & Schwartz, J. D. Impacts of temperature and its variability on mortality in New England. Nat. Clim. Change 5 , 988–991 (2015).

Xue, T., Zhu, T., Zheng, Y. & Zhang, Q. Declines in mental health associated with air pollution and temperature variability in China. Nat. Commun. 10 , 2165 (2019).

Article   ADS   PubMed   PubMed Central   Google Scholar  

Liang, X.-Z. et al. Determining climate effects on US total agricultural productivity. Proc. Natl Acad. Sci. 114 , E2285–E2292 (2017).

Desbureaux, S. & Rodella, A.-S. Drought in the city: the economic impact of water scarcity in Latin American metropolitan areas. World Dev. 114 , 13–27 (2019).

Damania, R. The economics of water scarcity and variability. Oxf. Rev. Econ. Policy 36 , 24–44 (2020).

Davenport, F. V., Burke, M. & Diffenbaugh, N. S. Contribution of historical precipitation change to US flood damages. Proc. Natl Acad. Sci. 118 , e2017524118 (2021).

Dave, R., Subramanian, S. S. & Bhatia, U. Extreme precipitation induced concurrent events trigger prolonged disruptions in regional road networks. Environ. Res. Lett. 16 , 104050 (2021).

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Acknowledgements

We gratefully acknowledge financing from the Volkswagen Foundation and the Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH on behalf of the Government of the Federal Republic of Germany and Federal Ministry for Economic Cooperation and Development (BMZ).

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Extended data figures and tables

Extended data fig. 1 constraining the persistence of historical climate impacts on economic growth rates..

The results of a panel-based fixed-effects distributed lag model for the effects of annual mean temperature ( a ), daily temperature variability ( b ), total annual precipitation ( c ), the number of wet days ( d ) and extreme daily precipitation ( e ) on sub-national economic growth rates. Point estimates show the effects of a 1 °C or one standard deviation increase (for temperature and precipitation variables, respectively) at the lower quartile, median and upper quartile of the relevant moderating variable (green, orange and purple, respectively) at different lagged periods after the initial shock (note that these are not cumulative effects). Climate variables are used in their first-differenced form (see main text for discussion) and the moderating climate variables are the annual mean temperature, seasonal temperature difference, total annual precipitation, number of wet days and annual mean temperature, respectively, in panels a – e (see Methods for further discussion). Error bars show the 95% confidence intervals having clustered standard errors by region. The within-region R 2 , Bayesian and Akaike information criteria for the model are shown at the top of the figure. This figure shows results with ten lags for each variable to demonstrate the observed levels of persistence, but our preferred specifications remove later lags based on the statistical significance of terms shown above and the information criteria shown in Extended Data Fig. 2 . The resulting models without later lags are shown in Supplementary Figs. 1 – 3 .

Extended Data Fig. 2 Incremental lag-selection procedure using information criteria and within-region R 2 .

Starting from a panel-based fixed-effects distributed lag model estimating the effects of climate on economic growth using the real historical data (as in equation ( 4 )) with ten lags for all climate variables (as shown in Extended Data Fig. 1 ), lags are incrementally removed for one climate variable at a time. The resulting Bayesian and Akaike information criteria are shown in a – e and f – j , respectively, and the within-region R 2 and number of observations in k – o and p – t , respectively. Different rows show the results when removing lags from different climate variables, ordered from top to bottom as annual mean temperature, daily temperature variability, total annual precipitation, the number of wet days and extreme annual precipitation. Information criteria show minima at approximately four lags for precipitation variables and ten to eight for temperature variables, indicating that including these numbers of lags does not lead to overfitting. See Supplementary Table 1 for an assessment using information criteria to determine whether including further climate variables causes overfitting.

Extended Data Fig. 3 Damages in our preferred specification that provides a robust lower bound on the persistence of climate impacts on economic growth versus damages in specifications of pure growth or pure level effects.

Estimates of future damages as shown in Fig. 1 but under the emission scenario RCP8.5 for three separate empirical specifications: in orange our preferred specification, which provides an empirical lower bound on the persistence of climate impacts on economic growth rates while avoiding assumptions of infinite persistence (see main text for further discussion); in purple a specification of ‘pure growth effects’ in which the first difference of climate variables is not taken and no lagged climate variables are included (the baseline specification of ref.  2 ); and in pink a specification of ‘pure level effects’ in which the first difference of climate variables is taken but no lagged terms are included.

Extended Data Fig. 4 Climate changes in different variables as a function of historical interannual variability.

Changes in each climate variable of interest from 1979–2019 to 2035–2065 under the high-emission scenario SSP5-RCP8.5, expressed as a percentage of the historical variability of each measure. Historical variability is estimated as the standard deviation of each detrended climate variable over the period 1979–2019 during which the empirical models were identified (detrending is appropriate because of the inclusion of region-specific linear time trends in the empirical models). See Supplementary Fig. 13 for changes expressed in standard units. Data on national administrative boundaries are obtained from the GADM database version 3.6 and are freely available for academic use ( https://gadm.org/ ).

Extended Data Fig. 5 Contribution of different climate variables to overall committed damages.

a , Climate damages in 2049 when using empirical models that account for all climate variables, changes in annual mean temperature only or changes in both annual mean temperature and one other climate variable (daily temperature variability, total annual precipitation, the number of wet days and extreme daily precipitation, respectively). b , The cumulative marginal effects of an increase in annual mean temperature of 1 °C, at different baseline temperatures, estimated from empirical models including all climate variables or annual mean temperature only. Estimates and uncertainty bars represent the median and 95% confidence intervals obtained from 1,000 block-bootstrap resamples from each of three different empirical models using eight, nine or ten lags of temperature terms.

Extended Data Fig. 6 The difference in committed damages between the upper and lower quartiles of countries when ranked by GDP and cumulative historical emissions.

Quartiles are defined using a population weighting, as are the average committed damages across each quartile group. The violin plots indicate the distribution of differences between quartiles across the two extreme emission scenarios (RCP2.6 and RCP8.5) and the uncertainty sampling procedure outlined in Methods , which accounts for uncertainty arising from the choice of lags in the empirical models, uncertainty in the empirical model parameter estimates, as well as the climate model projections. Bars indicate the median, as well as the 10th and 90th percentiles and upper and lower sixths of the distribution reflecting the very likely and likely ranges following the likelihood classification adopted by the IPCC.

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Kotz, M., Levermann, A. & Wenz, L. The economic commitment of climate change. Nature 628 , 551–557 (2024). https://doi.org/10.1038/s41586-024-07219-0

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Vegetarian Diet: An Overview through the Perspective of Quality of Life Domains

Shila minari hargreaves.

1 Department of Nutrition, Faculty of Health Sciences, University of Brasilia (UnB), Campus Darcy Ribeiro, Asa Norte, Brasilia, DF 70910-900, Brazil; rb.bnu@zpataner

António Raposo

2 CBIOS (Research Center for Biosciences and Health Technologies), Universidade Lusófona de Humanidades e Tecnologias, Campo Grande 376, 1749-024 Lisboa, Portugal

Ariana Saraiva

3 Department of Animal Pathology and Production, Bromatology and Food Technology, Faculty of Veterinary, Universidad de Las Palmas de Gran Canaria, Trasmontaña s/n, 35413 Arucas, Spain; tp.kooltuo@32_anaira

Renata Puppin Zandonadi

Associated data.

The study did not report any data.

Vegetarianism has gained more visibility in recent years. Despite the well-described effects of a vegetarian diet on health, its influence on the quality of life of the individuals who follow it still needs to be properly investigated. Quality of life relates to a subjective perception of well-being and functionality, and encompasses four main life domains: physical, psychological, social, and environmental. The adoption of a vegetarian diet, despite being a dietary pattern, could potentially influence and be influenced by all of these domains, either positively or negatively. This review aims to present an overview of the background, conceptualization, features, and potential effects of vegetarianism in all quality of life domains. The choice of adopting a vegetarian diet could have positive outcomes, such as better physical health, positive feelings related to the adoption of a morally correct attitude, an increased sense of belonging (to a vegetarian community), and lower environmental impact. Other factors, however, could have a negative impact on the quality of life of those choosing to abstain from meats or other animal products, especially when they go beyond one’s control. These include the environment, the social/cultural group in which a person is inserted, gender-based differences, economic aspects, and a limited access to a wide variety of plant-based foods. It is important to understand all the effects of adopting a vegetarian diet—beyond its nutritional aspects. Not only do studies in this area provide more consistent data, but they may also contribute to mitigating all factors that might prevent individuals from adopting a vegetarian diet, or that may have a negative impact on the quality of life of those who already follow it.

1. Introduction

Vegetarianism has its origins in 3200 BC, when ancient Egyptian civilizations started adopting vegetarian diets based on the belief that abstaining from meat consumption would facilitate reincarnation [ 1 ]. In India, another important cradle of vegetarianism, this practice was also associated with the fact that Hindus see cows as sacred and uphold nonviolence principles [ 2 ]. Later, Greek philosophers also adopted a vegetarian diet, with Pythagoras being a leading figure among them—indeed, for many centuries, vegetarianism was known as the “Pythagorean” diet [ 3 , 4 ]. In the Christian Era, vegetarianism lost its strength, gaining some visibility again only in the late 18th and early 19th centuries, when Darwin’s theory of evolution challenged the Church’s views that animals had no souls, and that their only purpose on Earth was to serve human beings [ 1 , 5 ].

Throughout history, the expansion of vegetarianism has been associated with religions that preach respect for all living beings and adopt nonviolence principles, such as Hinduism, Jainism, Sikhism, Buddhism, the Hare Krishna movement, and the Seventh-day Adventist Church. In addition, in the 20th and 21st centuries, science has observed several health benefits potentially associated with the reduction in meat consumption. Such benefits have strengthened the practice of vegetarianism around the world, and attracted more and more followers [ 4 ].

Currently, the worldwide prevalence of vegetarianism is not uniform. Asia is the continent with the highest prevalence, with 19 percent of the population adopting this practice [ 6 ]. India, the single country with the highest prevalence in the world (almost 40 percent of the population), contributes to the results of the Asian continent [ 7 ]. The prevalence in Africa and the Middle East is about 16 percent; and in Central and South America, 8 percent. The lowest prevalence of vegetarianism is found in North America (about 6 percent of the population are vegetarians) and Europe, where vegetarianism is adopted by only 5 percent of the population.

Vegetarianism encompasses different types of diets, classified according to how restrictive they are. Generally, vegetarianism is understood as the exclusion of meat from one’s diet, but other less restrictive eating patterns can also be classified within the scope of vegetarianism. These include, for example, flexitarians, who consume meat sporadically, or even once a week; pescatarians, who avoid all meat, except fish and seafood; and ovolactovegetarians, who banish all types of meat but consume products of animal origin, such as eggs and dairy products. A strict vegetarian diet, on the other hand, excludes all foods of animal origin. Veganism is a broader concept, which involves the adoption of a strict vegetarian diet, as well as the exclusion of other consumer items made from animal products, or which rely on animal exploitation, such as cosmetics and clothing items [ 8 , 9 ]. For didactic purposes, a strict vegetarian diet is often referred to as a vegan diet.

Different motivations can lead to adopting a vegetarian diet [ 10 , 11 , 12 , 13 ]. Ethical concerns are the main reasons, building on the idea that animal slaughter for human consumption is morally inappropriate. Another important motivation is health and the potential beneficial effects of vegetarianism. Religions that encourage abstaining from meat consumption and concerns about the environmental impacts of meat production are also important motivators for adopting vegetarianism [ 7 , 9 ].

According to the World Health Organization (WHO), quality of life (QoL) is a subjective concept that comprehends physical, psychological, social, environmental, and spiritual aspects [ 14 , 15 ]. Changes in eating patterns can influence individuals’ QoL, both positively and negatively [ 16 ]. A systematic review study assessed the nutritional quality of vegetarian diets, and found—based on data from 12 surveys—higher nutritional quality levels among vegetarians than omnivores [ 17 ]. According to the Academy of Nutrition and Dietetics [ 18 ], vegetarian diets are nutritionally adequate for all stages of life, as long as they are well planned. However, some precautions need to be taken to minimize the risk of nutritional deficiencies.

In view of the recent growth in the number of individuals adopting a vegetarian diet, as well as the wider interest in the topic in recent years, it is critical to understand the different effects of vegetarianism on one’s QoL. Therefore, this review aims to present an overview of the background, conceptualization, features and potential effects of vegetarianism considering all QoL domains.

2. Historical Background of Vegetarianism

Over most of their 24 million years of evolution, humans’ anthropoid ancestors were almost exclusively vegetarian, except for the occasional ingestion of insects and larvae. Anatomically, both humans and their ancestors present significant features that distance them from meat-eating animals, including, for example, wide flat teeth and more mobile jaws, which facilitate the chewing of grains and seeds, as opposed to sharp teeth and jaw movements on a vertical axis, which are characteristic of carnivores. In addition, carnivorous animals have shorter intestines, which enable the rapid elimination of toxins, unlike humans and other predominantly herbivorous animals, with long intestines that allow longer digestion, fermentation and absorption processes [ 19 , 20 ].

However, possibly due to other reasons linked to survival, self-defense and territorial protection, hominids began hunting other species, which led to the introduction of meat in the diet of Homo erectus , considered the first hunters. Humans’ ability to survive on different types of food was an essential factor in our evolution, which allowed our species, Homo sapiens sapiens , to adapt to the most diverse conditions and spread throughout the planet [ 19 , 20 ].

During the Paleolithic era, different food types were consumed, such as wild plants, seafood, reptiles, birds, and mammals. After the emergence of agricultural practices (about 13,000 years ago), there is no evidence that humans were essentially vegetarian, and the domestication of animals, including for consumption, became a routine activity by that time. However, it is speculated that many farmers lived primarily as vegetarians due to the wider availability of crops [ 19 ].

It is not known for certain when people started voluntarily abstaining from meat. However, the first reports date from 3200 BC in ancient Egypt, when the practice was motivated by religious factors, based on the belief that not consuming meat would facilitate reincarnation [ 1 ]. Another important region that is part of the history of vegetarianism is India, where the practice is also linked to religious issues. Hinduism has two basic principles among its foundations: ahimsa, or the principle of nonviolence (which includes violence against humans and other animals); and the recognition of the cow as a sacred animal [ 2 ].

Some of the philosophers of the pre-Christian era also contributed to the spread of vegetarianism. The practice was adopted at that time for health reasons as well as for religious, ecological, and philosophical reasons. It was believed that the act of killing another living being for food would have a brutal influence on one’s mind, negatively affecting one’s body and soul [ 3 ]. The supporters of vegetarianism included big names like Plato, Prophyry, Diogenes and Plutarch. The most prominent philosopher in this field was Pythagoras, who lived in the 6th century BC. Due to his influence, vegetarianism was known as the “Pythagorean” diet over many centuries, a name that lasted until the middle of the 19th century in Europe and the Mediterranean region [ 4 , 19 ].

In Ancient Greece, it was believed that animals could think and communicate, and that humans should be responsible for their lives. In addition, the Greeks believed that eating meat would be harmful to one’s health and mind [ 21 ]. Vegetarianism was also present during the Roman Empire, influenced by the Greek culture. However, with the rise of Christianity, abstaining from animal consumption lost its importance. Famous Christian thinkers such as Saint Thomas Aquinas and Saint Augustine sought to provide rational justifications for the exploitation and consumption of animals, spreading the idea that, unlike animals, human beings have souls and free will, and that animals are inferior beings, placed on Earth at the service of humans [ 3 , 4 , 5 ]. Only a few monks still maintained the practice, based on the belief that meat consumption would hinder their spiritual progress in some way because it was linked to impulsive behaviors [ 5 ].

In the 15th century, vegetarianism was advocated by Leonardo da Vinci, who believed that there was no distinction between the murder of humans and animals. However, it was only after the spread of Darwin’s theory of evolution that vegetarianism gained strength again in the late 18th century and early 19th century. Darwinism refuted the idea that human beings are fundamentally different from other animals—therefore, there were no plausible justifications for meat consumption [ 5 ]. At that time, the first vegetarian societies also began to emerge, and some Christian groups began to preach in favor of abstaining from meat based on the belief that animals should also be worthy of pity. It was only then that the term “vegetarianism” came to be used. Despite the general belief that it refers to “eating vegetables”, the term actually derives from “vegetus”, a Latin word that means “active” or “vigorous” [ 22 ]. An important name in the history of vegetarianism, in addition to the various vegetarian groups and societies that emerged in the 20th century, was Mahatma Gandhi, who contributed to its dissemination [ 19 ].

Albert Einstein believed that humanity’s evolution toward a vegetarian diet would be fundamental for the survival of life on Earth [ 21 ]. In Europe, the first International Vegetarian Union was founded in 1908, after other vegetarian societies had already emerged in several countries. From the 1960s onwards, a greater concern with food and health, associated with evidence of the potential benefits of a vegetarian diet for disease prevention, contributed to the spread of vegetarianism. Religious practices that preach respect for life and adopt nonviolence principles, such as Hinduism, Jainism, Sikhism, Buddhism, the Hare Krishna movement, and the Seventh-day Adventist Church, were also fundamental to this growth. Therefore, the world has seen a significant rise and expansion of the practice since the mid-20th century [ 4 ].

In recent years, vegetarianism has gained more visibility and a greater number of followers. Rosenfeld [ 23 ] describes a great expansion in the scientific literature on the psychological and social effects of choosing a vegetarian diet. Some topics started to attract more attention, such as motivations; barriers to adopting such diets; differences between vegetarians and vegans; morality; and gender differences. New research lines have emerged to explore issues associated with personal identity and social and cultural experiences [ 23 ].

Adherence to a vegetarian diet goes beyond food. Vegetarianism can be considered a social identity, as it reflects the motivations, feelings, and attitudes of those who choose to adopt it [ 24 ]. The main motivations for choosing a vegetarian diet are related to ethical and health aspects. Animal welfare is the main motivator, followed by concerns with major environmental impacts caused by the production and consumption of food of animal origin. Regarding health, general well-being and weight maintenance are the factors that most motivate the adoption of vegetarianism [ 23 ]. In addition, religious aspects can lead individuals to adopt a vegetarian diet, and religions such as Hinduism, Adventism and Spiritism preach abstaining from meat. Other less frequent factors, such as aversion to the taste of meat, food intolerances and allergies, and the influence of other people (family members, for example) can also be considered motivators for adopting a vegetarian diet [ 4 , 7 , 9 , 21 ].

There are several types of vegetarian diets commonly described in the literature. The most consensual classification consists of four different types, namely: (1) flexitarian or semivegetarian diet, in which people consume meat sporadically (up to once a week) or exclude red meat, but consume white meat; (2) pesco-vegetarian or pescatarian diet, which excludes all meats, except fish and seafood; (3) ovolactovegetarian diet, which excludes all types of meat, but allows products of animal origin, such as dairy products and eggs; and (4) strict vegetarianism, which excludes all products of animal origin [ 8 , 25 ].

In addition to these categories, other diets can be considered subclassifications of vegetarianism, namely: (1) raw vegan diet, which is mostly based on food in its most natural (raw) state, with an emphasis on the choice of organic and self-grown products; (2) frugal or frugivorous diet, which is similar to the raw vegan diet, but with 70–80 percent of the diet being composed of fruits, with a small proportion of nuts, seeds and some vegetables; and (3) macrobiotic diets, which encompass various degrees of restriction but are primarily composed of whole grains, soybeans, algae and some vegetables [ 25 , 26 ].

3. Quality of Life

According to the WHO, QoL is a multifactorial concept that includes the following domains: physical (physical state), psychological (affective and cognitive state), social (interpersonal relationships and social roles in the lives of individuals) and environmental (quality of the environment in which individuals live). Conceptual, pragmatic and empirical dimensions, as well as spiritual and religious aspects, can also contribute to people’s QoL and their ability to perform certain activities, or “functionality”. Building on that, QoL is defined as “individuals’ perception of their position in life in the context of the culture and value systems in which they live and in relation to their goals, expectations, standards and concerns” [ 14 , 15 ].

The terms “quality of life” and “well-being” are often used to indicate how well an individual feels. There is, however, a problem of interpretation resulting from the subjectivity of these concepts, which may acquire a broader or more specific connotation depending on the context. QoL can be subdivided into: the quality of the environment in which one lives, involving the physical structure of the environment and people’s integration in the society in which they live; physical and mental health, encompassing a wide range of individual capacities; usefulness, which involves the feeling of “being useful”, contributing to the welfare of other people, society, and the environment; and the appreciation of life, which is associated with tangible (wealth, for example) and intangible (such as life satisfaction and happiness) aspects [ 27 ].

Although it is difficult to group all these qualities into a single concept, the best general indicator of QoL would be how happy you feel and how long you live. The concept of “well-being”, in turn, usually denotes QoL in a wider sense, as well as a positive subjective assessment of life, or an appreciation of life. However, sometimes the concepts of “well-being” and “quality of life” are used interchangeably [ 27 ].

The connection between vegetarianism and QoL may be analyzed through different perspectives [ 14 , 15 ]. In the context of vegetarianism, each QoL domain proposed by the WHO (physical, psychological, social, and environmental) may be influenced by the adoption of a vegetarian diet. The opposite may also be said, that is, specific aspects of each domain might influence one’s decision to adopt a vegetarian diet. Moreover, these influences could be either positive or negative. The possible connections between vegetarianism and QoL domains are illustrated in Figure 1 .

Connections between aspects of vegetarianism and quality of life domains. The arrows indicate the direction of the influence, that is, whether a given domain influences or is influenced by certain aspects of vegetarianism. The plus (+) and minus (−) symbols indicate positive and negative influences, respectively. NCD: noncommunicable diseases; VD: vegetarian diet.

3.1. Physical Domain

The physical domain refers to aspects as pain, discomfort, energy, fatigue, sleep, and rest. Aspects that positively contribute to a general feeling of physical well-being are therefore relevant for understanding QoL. These include better general health, lower rates of chronic and inflammatory diseases, and lifespan [ 28 ].

3.1.1. Influence of Adopting a Vegetarian Diet on the Physical Domain

Positive influence.

Following a vegetarian diet may lead to better health outcomes and a lower risk of noncommunicable diseases, which could positively influence the QoL physical domain ( Figure 1 ). A nutritionally adequate diet is essential to achieving and maintaining good overall health. A systematic review published by Parker and Vadiveloo [ 17 ] compared the quality of vegetarian and nonvegetarian diets based on diet quality indexes. That review included 12 studies and showed that vegetarians have better diet quality results than omnivores. Furthermore, among vegetarians, vegans achieved the best results. Although different indexes were used in the studies, several common points allowed a combined analysis of the results. Higher consumption of fruits, green vegetables, whole grains, and vegetable sources of protein—and lower consumption of saturated fat and sodium—contributed to the best results found among vegetarians [ 17 ].

A cross-sectional study carried out with vegetarians in Brazil (n = 3319) observed that vegetarians have better diet quality markers than the general Brazilian population, according to parameters used in a national annual survey carried out by the Ministry of Health [ 29 , 30 ]. It was observed that a higher proportion of vegetarians had a more adequate daily consumption of fruits and vegetables [ 29 ] compared to the general Brazilian population (38.1 percent versus 23.1 percent), based on WHO recommendations (five servings a day) [ 31 ]. In addition, a lower regular weekly consumption of soft drinks and artificial juices was also observed among vegetarians (3.9 percent versus 14.4 percent). Of the different types of vegetarians, vegans showed the best results. It was also observed that vegetarians in Brazil follow the recommendations set out in the Dietary Guidelines for the Brazilian Population with regard to consuming more fresh foods and fewer processed and ultraprocessed foods [ 32 ].

Vegetarian diets, including strict vegetarianism (veganism), are considered healthy and nutritionally adequate, and can supply people’s nutritional needs at all life stages, as long as such diets are well planned [ 18 ]. Moreover, the benefits related to the prevention and better control of chronic diseases among vegetarians have already been described, and could also lead to positive outcomes in their QoL.

The role of intestinal microbiota in the regulation of several biological functions and in the prevention of chronic diseases is well known, as well as the fundamental role of the diet in the microbiota and intestinal health of individuals [ 33 , 34 , 35 ]. Excessive protein consumption could alter intestinal microbiota patterns by stimulating the proliferation of bacteria capable of fermenting amino acids. Such fermentation results in the production of molecules responsible for increased intestinal permeability, inflammation, and even cancer [ 36 ]. The consumption of vegetable sources of protein, on the other hand, is not associated with such adverse effects, possibly because they contain carbohydrates and fibers, which could mitigate the potentially deleterious effects observed in the intestine caused by the ingestion of proteins [ 36 ]. The intake of saturated fats, present mainly in animal foods, is another factor that contributes to an increase in systemic inflammation, possibly through the activation of Toll-like receptors (TLR), which, once activated, trigger a proinflammatory intestinal and systemic immune response [ 37 ]. The activation of TLRs and the subsequent inflammatory cascade result in an increased risk of metabolic disorders and chronic diseases, such as cancer, insulin resistance, and cardiovascular diseases [ 37 ].

Vegetarian diets usually have a higher content of carbohydrates and fibers, in addition to lower levels of proteins and fats—in particular saturated fats. Studies comparing the microbiota of vegetarians and nonvegetarians show that a plant-based diet can benefit the diversity and profile of the bacteria that make up the intestinal microbiota. In addition to differences observed in the microbiota, with a more favorable bacterial profile, a vegetarian diet (with high consumption of whole foods, fruits, and vegetables) leads to increased production of metabolites from the fermentation of prebiotics and phytochemicals by these bacteria, which also have a positive effect on the host’s health, both at intestinal and systemic levels, contributing to the prevention of chronic diseases [ 38 ].

Among chronic diseases, cardiovascular diseases account for 43.6 percent of deaths worldwide [ 39 ]. Positive results in the control of cardiovascular disease risk factors were observed in clinical trials that promoted lifestyle changes, including adopting vegetarian, vegan, and plant-based diets [ 40 , 41 , 42 , 43 ]. A review of observational studies conducted in 2018 assessed cardiovascular risk factors in vegans. In most countries, vegetarian diets were associated with a lower intake of energy and saturated fat, and a better cardiovascular profile (lower body weight, LDL cholesterol levels, blood pressure, fasting glucose, and triglycerides) [ 44 ].

A 2019 review study conducted by the Diabetes and Nutrition Study Group (DNSG) of the European Association for the Study of Diabetes (EASD) associated vegetarian eating patterns with a 28 percent reduction in the incidence of coronary heart disease, and a 22 percent drop in mortality from such conditions. That study gathered data from systematic reviews with meta-analyses correlating different dietary patterns and cardiometabolic outcomes in diabetic patients [ 45 ]. Following a balanced vegetarian diet can reduce systemic inflammation and the risk of diabetes, two factors that are closely linked to the onset and progression of cardiovascular disease [ 46 ].

The consumption of refined carbohydrates, saturated fats, processed meats, and sugary drinks increases the risk of type-2 diabetes, especially when combined with low consumption of dietary fibers. On the other hand, a low-calorie plant-based diet has a protective effect [ 47 ].

The prevalence of diabetes among vegetarians is 1.6 to 2 times lower than among omnivores [ 48 ]. In a 24-week controlled trial with diabetics, the individuals who followed a vegetarian diet showed greater weight loss (6.2 kg versus 3.2 kg, on average), better insulin sensitivity (30 percent versus 20 percent), greater reduction in visceral fat and medication use, in addition to a better hormonal profile (increased adiponectin and reduced leptin) and better levels of antioxidants, as compared to the ones following a standard diet for diabetes control [ 49 ].

Several factors contribute to the reduction in risks and a better control of diabetes. The first one is vegetarians’ better weight control. It is known that both obesity and the accumulation of visceral fat are linked to increased insulin resistance, which contributes to the onset of diabetes [ 47 ]. Vegetarians’ lower intake of saturated fats [ 17 ] also contributes to reducing the risk of diabetes. It has been shown that reducing the consumption of saturated fats or replacing them with unsaturated fats may contribute to improving insulin sensitivity [ 50 ]. Other factors, such as higher fiber intake [ 51 ], lower ferritin levels and lower intake of heme iron [ 52 ] among vegetarians are also related to better insulin resistance and lower risk of diabetes.

A vegetarian diet may also contribute to improving inflammation control. Foods of plant origin—when consumed in their most natural form—are rich in antioxidants, which can assist directly in the control of free radicals in the body (as in the case of antioxidant vitamins C and E), or even through several signaling pathways that modulate our immune response and the production of antioxidant compounds and enzymes, suppressing inflammatory responses [ 48 , 53 , 54 ]. Therefore, a plant-based diet that is rich in fruits, vegetables, whole grains, seeds, and nuts can help to control inflammatory processes.

A vegetarian diet may also bring benefits regarding cancer prevention. In addition to vegetarians’ better weight control results [ 55 ], which can be considered a protective factor against cancer [ 56 ], their higher consumption of dietary fibers could have protective effects due to the modulation of the intestinal microbiota. In addition, as previously described, excessive protein consumption can lead to an increased production of inflammatory metabolites by the intestinal microbiota [ 36 ], and the consumption of saturated fats (found mainly in foods of animal origin) is capable of activating Toll-like receptors in immune system cells. This stimulates the production of proinflammatory cytokines [ 37 ], and all these factors together can create a cancer-promoting environment.

In addition to the most common chronic diseases mentioned above, adopting a vegetarian diet can help to prevent and treat other inflammatory diseases. A healthier microbiota, higher consumption of antioxidants and lower consumption of potentially inflammatory compounds, in addition to better weight control, are important factors that positively contribute to the health of vegetarians. In fact, how long an individual has been following a vegetarian diet may have an important influence on their results—which depend on continuous exposure to this type of dietary pattern. In a study that evaluated only individuals who had been on a vegetarian diet for at least 15 years (n = 45), lower levels of oxidative stress markers were observed compared to omnivorous individuals (n = 30) [ 57 ].

Furthermore, promising results have already been achieved with the adoption of a vegetarian diet by individuals suffering from fibromyalgia, for example, including improvements in pain symptoms, QoL, sleep quality, and anxiety depression [ 58 ]. In autoimmune diseases, such as rheumatoid arthritis, a diet rich in fruits, vegetables, whole grains and legumes—and low in animal foods—can help to control some of the symptoms [ 59 ]. A vegetarian diet could also be a beneficial tool to prevent other autoimmune diseases, such as multiple sclerosis [ 60 ], due to its role in the health of the intestinal microbiota [ 61 ].

Several factors related to lifestyle may influence the emergence of diseases and how long an individual can live. Habits such as regular physical activities, stress control, good personal relationships, and a balanced diet have a positive impact on longevity [ 62 ]. A more detailed analysis of the dietary patterns followed by the world’s longest-living populations, who live in regions known as Blue Zones, can help us understand important food-related aspects that might contribute to improving people’s health and life expectancy. The five regions considered Blue Zones are: Loma Linda (California—United States), Nicoya (Costa Rica), Sardinia (Italy) Ikaria (Greece), and Okinawa (Japan). In all of them, individuals adopt a predominantly plant-based diet, with sporadic meat consumption (on average five times a month, in small portions). On the other hand, the consumption of legumes is frequent in all of them, being part of their daily diet, in addition to vegetables, tubers, cereals, fruits, and other regional foods, including dairy products [ 63 ].

The increased consumption of fruits and vegetables—rich in phytochemicals—may contribute to longevity through several mechanisms. The control of low-grade inflammation provided by antioxidant protection can prevent cell structure damage, slowing down the aging process [ 64 ]. On the other hand, prioritizing the consumption of proteins from animal sources could have a negative impact on one’s life expectancy. The profile of the amino acids found in these foods, with a higher content of methionine and branched-chain amino acids, leads to greater stimulation of IGF-1 and mTOR, in addition to greater cell proliferation. This contributes to the cellular senescence process and, consequently, to aging [ 65 , 66 , 67 , 68 ].

These potential health benefits of consuming a mostly or strictly plant-based diet can contribute to better physical health and well-being, resulting in better QoL. In fact, a cross-sectional study conducted with a total of 4628 individuals in the United Kingdom (with a wide range of diseases and conditions) showed that people who were ill had lower QoL scores than those feeling well. Post hoc comparisons indicated higher differences in the physical domain, especially among patients with musculoskeletal conditions (arthritis/arthroplasty, chronic pain), and those with cardiovascular disease awaiting a heart transplant [ 69 ]. Therefore, a diet that helps to prevent chronic and inflammatory diseases could also reduce the negative effects of these conditions on people’s QoL.

Negative Influence

Despite the potential health benefits from adopting a vegetarian diet, special attention should be given to the adequacy of iron, zinc, vitamins B12 and D, calcium, iodine, omega-3, and protein in adults [ 70 ], and especially in infants [ 71 ]. Low intake of such nutrients could lead to nutritional deficiencies and impair an individual’s health [ 70 , 72 ], with a negative impact on their QoL.

Vitamin B12 deficiency should be highlighted, as this nutrient can only be found in animal-origin foods. Vegetarians (especially vegans) have been shown to have lower levels of serum vitamin B12. In addition, increased homocysteine levels [ 73 , 74 , 75 ] are observed, a metabolite that is elevated due to deficiency of vitamin B12 (and other nutrients), and which is associated with increased inflammation. B12 deficiency and increased homocysteine can lead to neurological problems, anemia and developmental delay in children, in addition to increasing the risks of cardiovascular disease, dementia, osteoporosis and death [ 73 , 75 ]. For this reason, it is necessary to monitor and supplement vitamin B12 levels among this groups, and possibly encourage the intake of fortified foods.

Iron, an essential mineral used for hemoglobin formation and oxygen transport in the body, also needs to be carefully adjusted. Vegetarians have been shown to have lower serum ferritin levels, a protein responsible for storing iron in the body. Lower levels of iron could increase the risk of developing anemia [ 76 ], which might also be caused by vitamin B12 deficiency [ 75 ]. In this scenario, an inadequately planned vegetarian diet could negatively affect aspects related to “energy and fatigue” in the physical domain of QoL [ 28 ].

Bone health should also be addressed when considering the potential negative effects of a vegetarian diet. A systematic review published in 2019 showed that vegetarians and vegans had lower bone mineral density than omnivores, and vegans also had higher fracture rates. Such results were unlikely explained only by lower calcium intake, as bone health encompasses many complex mechanisms and depends on different nutrients [ 77 ]. A recent cross-sectional study also found lower bone health in vegans when compared to omnivores (measured using quantitative ultrasound—QUS) [ 78 ], which reinforces the need for proper diet planning and careful bone health monitoring among vegetarians.

3.1.2. Influence of the Physical Domain on the Adoption of a Vegetarian Diet

Seeking health improvement is one of the reasons why people chose to adopt a vegetarian diet [ 7 ]. According to Hopwood et al. [ 79 ], health was the most common reason why nonvegetarians considered adhering to a vegetarian diet. Vegetarianism is currently being more widely studied, and a growing number of scientific papers about the topic have been published over the past few years [ 80 ]. Consequently, the topic has received more attention from the media, and more information is reaching the general population. As more people are informed about the health benefits of adopting a vegetarian diet, the need or desire to improve their health might serve as a trigger. A study conducted in Germany with 329 vegans showed that more than two-thirds of them (69.6 percent), despite having more than one motive for following the diet, included health and well-being among them [ 81 ].

In this sense, following a vegetarian diet is both the cause and consequence of the positive outcomes related to the physical domain. People who seek health improvement may be prone to adopting a vegetarian diet; and, once they do it, the physical benefits may serve as further motivation for maintaining their new diet.

3.2. Psychological Domain

The psychological domain is related to positive or negative feelings, self-esteem and body image/appearance, and thinking/learning/memory/concentration. Different aspects of vegetarianism can either influence or be influenced by psychological factors ( Figure 1 ) [ 28 ].

3.2.1. Influence of Adopting a Vegetarian Diet on the Psychological Domain

Avoiding meat and other animal products can enhance positive feelings arising from the fact that person is adopting an attitude that confirms their beliefs. The positive psychological impact goes beyond the individual sphere, as it can also increase social connections with others adopting similar ideas and behaviors. According to Rosenfeld and Burrow [ 24 ], being a vegetarian goes beyond the choice of a dietary pattern, as it gives individuals a new social identity, which influences their way of thinking, behaving, and socializing. The adoption of a plant-based diet can have a positive effect on well-being and contentment, which could positively impact someone’s QoL [ 82 ].

The different motivations for adopting vegetarianism are also able to influence individuals psychologically. Those who adopt vegetarianism for ethical reasons tend to create more aversion to meat due to the association between its consumption and animal suffering. Such individuals also exclude more animal foods and tend to adopt stricter diets than those who become vegetarians for health or environmental reasons [ 23 ]. That does not necessarily implicate a negative outcome, though. As it has been shown by Cruwys et al. [ 83 ], vegetarians and vegans are more likely to report no barriers to diet adherence (25.2 percent of vegans and 15.6 percent of vegetarians) when compared to individuals following a gluten-free, paleo, or weight-loss diet. Indeed, both vegans and vegetarians had higher diet adherence when compared to the other groups, which might be connected to positive psychological effects related to the social identification within the vegetarian/vegan community.

Potentially negative outcomes of vegetarianism in the psychological domain could be related to mental health impairment. The data related to the effect of vegetarianism on mental health are conflicting. Adopting a vegetarian diet was positively associated with a better mood in a cross-sectional study with Seventh-day Adventists [ 84 ]. A study of South Asians living in the United States found that the likelihood of depression was 43 percent lower among vegetarians [ 85 ]. However, a contrary association has also been observed: in the United Kingdom, a positive association of depressive symptoms was found in men, even after adjusting for confounding factors such as nutritional deficiencies and sociodemographic data [ 86 ]. Similar results were found among adolescents in a study conducted in Turkey, in which higher levels of anxiety, as well as eating disorders, were observed. That study raises the possibility that a vegetarian diet might be adopted among young people as a way of limiting food intake, and that it might be related to preexisting eating disorders [ 87 ].

Discrepant results have already been observed in a study that evaluated mental health in representative population samples from Germany, Russia, and the United States, in addition to samples from students in China and Germany. An increase in anxiety and depression was observed only in the sample from China, but the result was considered mild since a vegetarian diet would explain only 1 percent of the variance in cases of depression and anxiety. In addition, the motivations that led Chinese students to adopt a vegetarian diet differed from those of the other groups studied, being more related to cultural and economic factors [ 88 ]. A study with Chinese elderly people also found a positive association between adopting a plant-based diet and depression compared to a meat-based diet. However, the correlation was observed only in men [ 89 ].

A French cohort’s cross-section study carried out a separate analysis by types of vegetarian diets, and identified a positive association between depressive symptoms and a fish diet and an ovo-lacto-vegetarian diet. However, no association was found with a vegan diet, which contradicts the idea that a stricter diet (excluding more or all animal products) would lead to more severe symptoms of depression [ 90 ]. The authors claim that differences in motivation (between vegans and other vegetarians) may have contributed to this group’s lack of association. In addition, the same study found a positive association between depressive symptoms and the exclusion of items from the diet, both for foods of animal and vegetable origin. That is, the more items excluded (not types of food, but number of products excluded), the greater the symptoms. Such a result could indicate that the higher levels of depression found in vegetarians in several studies could reflect an increase in risk related to diet restriction, and not necessarily to vegetarianism itself [ 90 ].

Another point that needs to be considered is that studies on depression in vegetarians are predominantly transversal, and therefore do not enable the determination of a cause-and-effect relationship. A study that evaluated mental disorders and adopting a vegetarian diet in the previous 12 months (through interviews with a population sample in Germany) also found a positive association between the two variables. However, the time difference between the beginning of both suggests that mental disorders preceded the change in diet, thus refuting the hypothesis that vegetarianism might cause mental disorders [ 91 ].

A systematic review study carried out by Medawar et al. [ 92 ] points out that, despite several health benefits related to adopting a vegetarian diet, its effect on mental health has yet to be properly studied. It is possible that nutritional deficiencies, such as lower levels of vitamin B12, contribute to worsening the nervous system’s health. On the other hand, a diet that favors a more balanced intestinal microbiota, such as a vegetarian diet, positively contributes to the maintenance of neurological functions due to its importance in modulating the gut-brain axis [ 92 ]. In a meta-analysis study published in 2016, it has also been observed that the consumption of fruits and vegetables is inversely associated with the risk of depression [ 93 ]. Vegetarians consume more fruits and vegetables than omnivorous individuals [ 17 ], and also tend to have better health markers and lower risk of other chronic diseases [ 94 ]. In view of this, the conflicting results on the relationship between vegetarianism and depression may reflect a lack of standardization with regard to diet quality and adequate intake (or supplementation) of nutrients in some of the studies, as well as the possibility already raised of reverse causality.

3.2.2. Influence of the Psychological Domain on the Adoption of a Vegetarian Diet

The main reason individuals decide to adopt a vegetarian diet is because of ethical/moral reasons [ 7 , 9 ], which is related to compassion and empathy towards the animals. Since some people feel that eating animal products is wrong, abstaining from their consumption could contribute to a better psychological state. Adopting a vegetarian diet can bring about positive feelings, such as altruism and a sense of purpose, while the pursuit of such guilt-free peace of mind could also positively influence one’s choice to adopt a vegetarian diet. A study conducted by Antonetti and Maklan [ 95 ] showed that experiencing either guilt or pride could change consumers’ behavior and their intention to purchase more sustainable products. Building on that, feeling guilty about eating animal products could lead to a behavioral change, and feeling proud of doing it could reinforce the maintenance of a vegetarian diet.

Moreover, some individuals adopt a vegetarian diet due to spiritual or religious reasons [ 7 ]. Spirituality is a concept related to people’s quest for the meaning in life and a connection to a higher or sacred power. On the other hand, religiousness is related to the degree in which an individual believes, follows, and practices a religion, which might influence how one chooses to live their lives [ 96 ]. An individual who follows a religion that preaches abstention from animal products might feel encouraged to adopt a vegetarian diet. Good adherence to the diet could, in this case, be a positive psychological reinforcement, as it would be in line with their own beliefs. As it has already been demonstrated, high levels of spirituality and religiosity are associated with better social, psychological, and environmental QoL outcomes [ 96 ].

Despite the positive outcomes related to the adoption of a vegetarian diet, some challenges can be found. For many, the barriers to adopting vegetarianism outweigh the possible benefits, and may prevent them from taking that step. Studies corroborate the evidence that attachment to the taste of meat constitutes an obstacle to adopting vegetarianism [ 97 , 98 ]. In addition, other barriers may be considered, such as the fear that a vegetarian diet could be nutritionally inadequate or monotonous, or that it may not favor satiety; the belief that preparing vegetarian meals is harder; difficulties in finding options when eating in restaurants; living with people who eat meat; and a lack of knowledge about meat-free eating [ 97 , 99 , 100 , 101 ]. Especially among men, meat is considered a “comfort food”, and its intake is associated with strength, muscle building, and masculinity. These beliefs represent a barrier to reducing meat consumption, as demonstrated by a study with soldiers from Norway who evaluated their perception of the implementation of the “Meatless Monday” program [ 97 ]. The program is a worldwide campaign, adopted in more than 40 countries, which aims to make people aware of the advantages of reducing meat consumption [ 102 ].

These results are in line with older studies conducted by Lea et al. [ 103 , 104 ]. Having a taste for meat was considered the main barrier for the adoption of a vegetarian diet, but other important factors have also been described, such as, for example, difficulties in changing one’s eating pattern; the fact that family and friends may still eat meat; little knowledge about the subject; and difficulties in finding vegetarian options when eating out [ 103 ].

Moreover, according to another study from Lea et al. [ 104 ], some of the factors that prevent or hinder the adoption of a plant-based dietary pattern are related to one’s family (family members or close people do not adopt this eating pattern); convenience (difficulty finding options or preparing food); health (fear of iron, protein and other nutrient deficiencies); cost and lack of options for eating out; and lack of information about vegetarianism. The low prevalence of adopting a plant-based diet among the participants demonstrates that several factors discourage its adoption—even though it is a more flexible dietary pattern than a vegetarian diet.

All these barriers interconnect with the social domain, as they are influenced by the social context in which an individual is inserted. Nevertheless, the negative psychological effects refer to how individuals react to these fears or barriers, which might negatively affect their choice of adopting a vegetarian diet. As described by Schmitt et al. [ 105 ], the perception of discrimination, both about an individual and a group, has an impact on well-being, with potential psychological consequences (contributing to mental stress, anxiety, depression) and affecting other aspects, such as self-esteem, humor, and satisfaction with life [ 105 ].

3.3. Social Domain

The social domain related to QoL includes personal relationships and social support [ 28 ]. In fact, having good social connections is essential for mental health and well-being, positively influencing one’s QoL. In this case, the consequences of adopting a vegetarian diet have to be analyzed based on the social and cultural group in which an individual is inserted, as well as the attitudes of close people towards vegetarianism.

3.3.1. Influence of Adopting a Vegetarian Diet on the Social Domain

Unlike other dietary patterns, vegetarianism goes beyond the definition of one’s food choices. Rather, it is defined as a social identity, which consists of how a person identifies themselves in terms of the social group in which they believe to belong. A study conducted with young vegan women revealed that not only did they identify with the diet, but they also passionately engaged in a “vegan lifestyle”. The choice of becoming a vegan had positive effects in many different ways, including social relationships, and identification and sense of connection with the vegan subculture [ 106 ]. Therefore, the choice of following a vegetarian diet can enhance one’s connection with other people who share the same life philosophy [ 107 ], strengthening social bonds and positively influencing one’s QoL ( Figure 1 ).

Many of those who decide to adopt vegetarianism suffer rejection from others and are victims of stereotyping and discrimination. Such negative attitudes towards vegetarians and vegans are known as “vegaphobia” or “veganophobia”, a term already spread in the scientific literature. A possible explanation for the discrimination against vegetarians and vegans is related to the cognitive dissonance suffered by individuals who eat meat. In this context, cognitive dissonance refers to the contradiction experienced by individuals who like animals and feel compassion for them, but, at the same time, consume meat. Therefore, individuals who eat meat may discriminate against vegetarians not out of fear or dislike, but because they represent an affirmation that eating meat is not necessary and is, therefore, unjustified [ 108 ].

In order to avoid conflict and embarrassment, many vegetarians prefer to omit their dietary choice. In fact, social aspects are so relevant that the greatest reason why vegetarians make exceptions and eat meat is due to pressure from friends, family, and coworkers. According to Rosenfeld and Tomiyama [ 109 ], in a qualitative study that evaluated dieters’ motivations to break their diet, 51 percent of individuals reported having already eaten meat after adopting vegetarianism. In general, their justifications do not involve missing meat itself, but rather an attempt to avoid uncomfortable situations in a social context. The fear of being rude or offending some family culture or tradition, the need to make a good impression, or the fear of being stigmatized are some of the most important factors that lead vegetarians to stop following their diets momentarily. Such a study reinforces the idea that vegetarianism goes far beyond a dietary choice, creating a social identity that influences the entire context in which an individual is inserted [ 109 ].

The negative consequences of a vegetarian identity usually have a stronger impact on vegans than vegetarians because the former suffer more rejection and are viewed more negatively by omnivores [ 23 ]. Such discrimination comes not only from nonvegetarian people, but also from the media, as demonstrated by Cole and Morgan [ 110 ] in a study that evaluated how veganism was reported in UK newspapers. Such a study concluded that the media tends to present vegans as sentimentalists, fanatics and extremists, in addition to mocking veganism and considering it impossible to maintain in practice.

3.3.2. Influence of the Social Domain on the Adoption of a Vegetarian Diet

Vegetarians and vegans also showed more adherence to their diet when compared to individuals who follow a paleo, gluten-free, or weight-loss diet. Social identification was an important predictor of adherence in both quantitative and qualitative analyses. According to Cruwys et al. [ 83 ], vegetarians and vegans described their diet not as an individual choice, but as a manifestation of their social ethics. Ethical and moral concerns were considered the most important facilitators of diet adherence, and a lack of adherence would go against the group’s moral code. Feeling part of a social group can also positively influence how strictly one sticks to a dietary pattern. The sense of belonging and the in-group social reinforcement could make it easier for individuals to maintain their dietary patterns, provided they feel supported by the group.

Vegetarians that have a close circle of vegetarian contacts (friends, family or coworkers) have been shown to have higher QoL than those who do not [ 13 ]. In this case, they can be positively influenced by their social environment. Moreover, just as the social context in which vegetarians are inserted may influence their adherence to the diet, individuals who eat meat may also be influenced by living with vegetarians. In their study, Geerts, Backer, and Erreygers [ 108 ] described some characteristics of meat-consuming individuals, with emphasis on the fact that meat consumption is considerably lower among those living with vegetarians in the same household. In addition, discrimination against vegetarians was less common among individuals who had vegetarians in their household or circle of friends. Thus, greater acceptance and lower levels of veganophobia among meat consumers (resulting from their close contacts with vegetarians) may have a positive influence on other individuals’ feeling more comfortable when adopting a vegetarian diet.

Cultural aspects are relevant predictors of meat consumption. The consumption of different species of animals varies between cultures. Animals considered suitable for consumption in some countries may not be seen in the same way by individuals of other nationalities. As demonstrated by Ruby [ 111 ], in countries considered individualistic (such as the United States and Canada), a feeling of disgust is the primary attitude of certain individuals when faced with the idea of eating certain animals. On the other hand, in more collectivist nations, such as China and India, cultural norms influence individual emotions and the sense of morality, being the greatest predictor for not consuming meat.

Moreover, gender differences may also influence one’s choice of eating or avoiding animal products. Meat consumption is usually seen as a symbol of masculinity and dominance over other species in several cultures where meat is considered a proper food for men [ 23 , 97 ]. In addition, men tend to eat less fruits and vegetables; care less about the nutritional properties of the food they eat; and agree more with the belief that a healthy diet needs to include meat [ 7 , 112 ]. According to Rosenfeld and Tomiyama [ 98 ], men are more resistant to adopting a vegetarian diet, mainly because they believe that a meatless diet would not be tasty. In addition, women are more likely to believe that meat consumption is harmful to the environment and that adopting vegetarianism is a plausible and healthy choice [ 113 ]. In fact, large population studies such as the Epic-Oxford [ 114 ] and the Adventist Health Study 2 [ 115 ] identified a higher proportion of females among vegetarians, with 78 percent and 65 percent of the sample consisting of women.

Such gender differences may influence the adoption of vegetarianism depending on the sociocultural context in which an individual is inserted. A study by Ruby et al. [ 116 ] with participants from Argentina, Brazil, the United States, and France (countries that are among the largest consumers of beef in the world) revealed that men consume beef more frequently and enjoy the taste of it more, while women show more negative attitudes towards the consumption of red meat, such as disgust. The same study also demonstrated that there are cultural differences related to the acceptance of vegetarianism. American women showed greater admiration for vegetarianism, while French women were the ones who admired vegetarians the least. Participants from Brazil and Argentina, considering the entire sample, demonstrated more positive attitudes toward beef consumption, followed by participants from France and, finally, from the United States [ 116 ].

3.4. Environmental Domain

The environment in which an individual is inserted also exerts an important influence on their QoL. Living in a safe and healthy environment, with proper social care and an efficient transport system, opportunities for acquiring new information and skills, as well as recreation/leisure areas, are all relevant factors. Moreover, having good financial resources can positively contribute to a good QoL. On the other hand, factors that have a negative impact on the environment, such as pollution and climate change, could also negatively affect one’s QoL [ 28 ].

3.4.1. Influence of Adopting a Vegetarian Diet on the Environmental Domain

Following a more sustainable diet, which will contribute to a healthier environment, could positively influence QoL ( Figure 1 ). In general, plant-based diets are more sustainable than those based on animal foods, as they require fewer natural resources for food production and have a lower impact on the environment. An omnivorous diet is estimated to require 2.9 times more water, 2.5 times more energy, 13 times more fertilizers, and 1.4 times more pesticides than a vegetarian diet [ 117 ]. In addition, meat and dairy production contribute 80 percent of all gas emissions from food production, and 24 percent of total greenhouse gases coming from food. Livestock production uses about 70 percent of all agricultural land globally, and consumes 29 percent of all water spent on agriculture [ 118 ].

Regarding the analysis of different types of diets, the data from 34 articles gathered in a systematic review showed that the more a diet is plant-based, the more sustainable it is. The vegan diet was considered the most sustainable of all, with the lowest greenhouse gas emissions and the least environmental impact, especially when based on locally produced foods and with a lower consumption of ultraprocessed meat substitutes. Ovolactovegetarian diets have a greater environmental impact than vegan diets, and it has been shown that 40 percent of greenhouse gases from ovolactovegetarian diets are attributed to the consumption of dairy products [ 118 ].

The production of animal-origin food is very inefficient in terms of energy, as it requires the use of many resources (water, energy, land, food) to keep animals alive. The animals themselves use much of the energy and nutrients in the form of food to maintain their metabolism, whereas only a small part of it is actually stored and converted into food for humans in the form of meat. This amount of energy wasted during production, standardized through the rate of the conversion of energy into protein, varies considerably from one animal to another. Whereas 4 calories from fossil fuels are required for each calorie of chicken protein that is produced, 40 calories are required for the production of 1 calorie of beef protein. For pork and dairy production, the rate is 14 fuel calories for each calorie of protein. In the case of eggs, the value is similar to that of beef (39 calories). On average, the energy used to produce each gram of animal protein (25 kcal/g) is 11 times greater than that used to produce vegetable proteins (2.2 kcal/g) [ 119 ].

In general, in the case of plant-origin foods, the higher the protein concentration, the greater the energy efficiency (which means that such foods need less energy to provide greater amounts of protein, as they are more concentrated in protein). Such an association does not exist for foods of animal origin, as their energy demand is very high—in fact, a decline in energy efficiency is observed as protein concentration increases (that is, foods with a higher protein concentration are those that demand more energy) [ 120 , 121 ].

According to Aleksandrowicz et al. [ 122 ], the change from a typical Western diet to more sustainable food patterns could reduce greenhouse gas emissions and land use related to food production by up to 80 percent, in addition to a 50 percent reduction in water use. In that study, all diets involved reducing or replacing animal foods with others of plant origin (such as, for example, vegetarian, vegan, Mediterranean and pescatarian diets), in addition to replacing the consumption of ruminant animals with monogastric animals [ 122 ]. Similar results were observed in a study by Rosi et al. [ 12 ] in Italy, which showed that vegetarian diets (ovolactovegetarian and vegan) had a lower ecological footprint in the three aspects assessed: CO 2 production, water consumption, and land use. Corroborating these data, a global analysis of different dietary strategies to reduce the environmental impact and improve health estimated that, in developed countries, the replacement of animal foods with plant-origin foods could reduce the number of premature deaths by up to 12 percent, and greenhouse gas emissions by up to 84 percent [ 123 ].

3.4.2. Influence of the Environmental Domain on the Adoption of a Vegetarian Diet

Environmental issues are part of the motivations that lead individuals to reduce meat consumption or adopt a vegetarian diet. The concept of sustainability applied to food refers to a diet that, in addition to being nutritionally adequate and healthy, respects biodiversity and ecosystems, is accessible, culturally accepted, and contributes to preserving natural resources [ 124 ].

A motivation to live in a healthier and more sustainable environment may positively influence people to adopt and maintain a vegetarian diet, as it has already been proved that a more plant-based diet has a lower environmental impact when compared to animal-based diets [ 122 ]. Individuals who are naturally engaged in sustainability and environmental issues are more likely to have positive feelings related to a sense of altruism achieved from adopting a vegetarian diet. The possibility of protecting their own environment and contributing to a better world can bring a sense of purpose in life [ 125 ], which could positively influence diet adherence and QoL.

Adopting a vegetarian diet may depend on other factors beyond an individual’s will. Economic aspects, both at the global level (economic situation of the country) and the individual level (income and social status), could influence food choices. In general, the lower the income, the greater its influence on food. People with higher income suffer less from fluctuations in food prices and are more demanding in their choices. Likewise, in poorer countries, the consumption of certain foods is highly influenced by their prices, which does not occur with the same intensity in developed countries [ 126 ]. The influence of economic aspects on the nutritional quality of a diet is quite variable. For example, it has been shown that increased income leads to a higher intake of fruit. However, the same increase might lead to eating out more often, or consuming more processed foods, in addition to eating more meat and fewer legumes [ 126 ]. Moreover, a cross-sectional study carried out in the United States showed that lower income levels were associated with poorer quality of food—in particular, lower consumption of fruits and vegetables and higher consumption of sugary drinks and frozen desserts [ 127 ].

The economic context is one of the factors that may influence the adoption of vegetarianism. On the one hand, the price of animal-origin foods may cause individuals to reduce their consumption. A study carried out in Canada found that an increase in meat price led 37.9 percent of individuals to reduce or eliminate their consumption. Still, as it is a food that is part of local culture, individuals value meat consumption more than any other food group. Therefore, despite economic issues, cultural aspects may also be considered an important barrier to reducing meat consumption [ 128 ]. In Australia, it has been shown that price increases are the biggest motivators for reductions in meat consumption, a factor that was considered more relevant than health, religious, ethical, and environmental aspects, among others [ 129 ]. Therefore, understanding the economic context in which individuals live is essential for understanding the motivations that lead them to reduce their meat consumption and possibly adopt vegetarianism.

Reducing meat consumption also depends on access to various plant-origin foods, which is also limited by economic issues. In Brazil, for example, the consumption of fruits and vegetables is influenced by prices and family income, with the cost burden being indicated as the primary barrier [ 130 ]. Data from the Brazilian Household Budget Survey (POF) showed that individuals from lower income groups spend a higher percentage of their budget on food. Families with a monthly income of up to BRL 1908.00 spend 22.6 percent of their household budget on food, compared with only 7.6 percent among families whose monthly income exceeds BRL 23,850.00 [ 131 ]. One of the barriers to adopting a vegetarian diet is the perception that it would be more expensive [ 98 ]. However, a vegetarian diet could be considered cheaper than an omnivorous diet, since meat is often the most expensive food item. In Brazil, a national survey from 2017–18 revealed that over 20 percent of all household food expenses were spent on “meats, viscera and fish”, a percentage higher than to any other food item [ 131 ]. Still, a vegetarian diet could become more expensive when more meat-substitute foods (which are less accessible) are consumed [ 132 ].

Another factor that could hinder the adoption of a healthy vegetarian diet is the logistics involving access to fresh fruits and vegetables. As they are perishable foods and are usually eaten fresh (unlike meats and other foods, which are often frozen and stored for longer), many types of fruits and vegetables require more frequent trips to the market, and adequate storage to minimize losses. Therefore, the consumption of fresh fruits and vegetables could be affected by people’s lack of time to purchase these foods frequently, and by losses resulting from inadequate storage. In other words, the perishability of fruits and vegetables could generate a cost increase. In addition, especially among low-income individuals, a more restricted access to fresh food is a factor that negatively influences its consumption [ 133 ]. Moreover, lower education levels could also negatively influence one’s decision to adopt a vegetarian diet, as a positive association has been demonstrated between higher educational levels and the adoption of a vegetarian diet [ 114 , 134 ]. In view of this, educating individuals to make healthier and more economically viable choices could encourage more people to adopt vegetarianism. Public policies that help reduce prices and facilitate access to fruits, vegetables, and other plant-origin foods could also help more people to reduce their meat consumption.

4. Vegetarians’ Quality of Life

A vegetarian diet’s effect on QoL was assessed in a cross-sectional study carried out with runners. A convenience sample was selected from German-speaking countries, namely Germany, Switzerland and Austria, and a total of 281 individuals (158 vegetarians and 123 omnivores) participated in the study. The instrument used to assess QoL was the WHOQOL-BREF, which was applied virtually to the study subjects. The results showed that all participants scored high on QoL, regardless of the type of diet adopted, with no difference between groups. Therefore, it was concluded that runners have high levels of QoL, and that a vegetarian diet was as good as an omnivorous diet for this population segment [ 135 ].

In Brazil, a specific questionnaire to evaluate the QoL of vegetarians was developed and validated, since other studies used only general questionnaires or others that were not specific to vegetarians [ 13 ]. The responses showed that vegetarians have satisfactory levels of QoL (average scores between 70 and 80 on a 100-point scale). Among the different types of vegetarians, vegans were the ones with the highest scores. Other factors that had an influence on participants’ QoL included their age, how long they had been following a vegetarian diet, and whether they had other vegetarians in their close circle of contacts [ 13 ].

In a clinical trial conducted with diabetic patients, the effect of a vegetarian diet on their QoL and eating behavior was compared to a standard diet used to treat type 2 diabetes. QoL was assessed using the Obesity and Weight-Loss QoL questionnaire (OWQOL) and Weight-Related Symptom Measure questionnaire (WRSM). Both diets led to positive effects on QoL and mood, but the effect was stronger in the group that followed a vegetarian diet, demonstrating that such a dietary pattern can have positive effects not only on the physical health, but also on the mental health of patients with type 2 diabetes [ 136 ].

Older studies [ 137 , 138 , 139 ] show similar results, with positive QoL outcomes when individuals were exposed to a vegetarian diet. Katcher, Ferdowsian, Hoover, Cohen, and Barnard [ 137 ] developed a workplace study in a US-based company as part of a health promotion program, in which volunteers adopted a vegan diet for 22 weeks. At the beginning and the end of the period, individuals answered the Food Acceptability Questionnaire—FAQ (SF) and the Work Productivity and Activity Impairment questionnaire (WPAI). The responses to the questionnaires showed that individuals who adopted the vegan diet reported improvement in general health, physical fitness, mental health, vitality and overall satisfaction with the diet, in addition to the reduced cost of food items. However, they reported more difficulty in finding options when eating out. Still, the vegan diet was effective in improving the participants’ QoL. QoL was also assessed in a study conducted at a health institute in the United States that offers a raw vegan diet to visitors and guests. Participants who remained at the institute for at least a week and who would maintain the raw vegan diet after leaving the institute were selected. A QoL analysis was performed at the beginning of the study and 12 weeks after the intervention, with a questionnaire that evaluated individual satisfaction with taste, food cost, convenience (ease of buying, planning and preparing food), and self-care perception. Individuals who followed the raw vegan diet for 12 weeks were compared to those who did not. There was an improvement both in the parameters of general QoL (assessed by SF-36), as well as in the QoL associated with changes in the diet, cost aspects and the perception of self-care. This shows the positive effect that this type of food can have in QoL, when used as a clinical treatment [ 138 ]

A study conducted in the United States by Barnard, Scialli, Bertron, Hurlock, and Edmonds [ 139 ] assessed the acceptability of a low-fat vegan diet in women. The study was carried out with 35 nonmenopausal women divided into two groups: one adopting the diet for a period equivalent to two menstrual cycles, and the other group not following any diet, with a crossover design. The low-fat vegan diet had high adherence and good acceptability, although the participants reported that maintaining the diet required more effort. They also reported weight loss and improved sleep, digestion and energy levels, which can positively contribute to improving QoL.

5. Summary of Knowledge and Future Directions

Adopting a vegetarian diet can have a positive influence on all four QoL domains. Better health outcomes and lower rates of noncommunicable diseases have a positive impact on the physical domain. Positive feelings associated with doing something good, together with a feeling of belonging or stronger in-group bonds created with the vegetarian community, have a positive effect on the psychological and social domains, respectively. Finally, the lower environmental impact of vegetarian diets benefits the environmental domain.

On the other hand, negative effects on QoL might also result from adopting a vegetarian diet. Despite better overall health, a nonbalanced vegetarian diet could lead to nutritional deficiencies that would be detrimental to health, affecting the physical domain. As vegetarians are still a minority group, rejection and stigmatization from nonvegetarians may have a negative impact on the social domain. The psychological and mental effects of a vegetarian diet are not clear, although some studies point to an increased risk of depression.

Several aspects of different QoL domains can also have an impact on one’s decision whether or not to adopt a vegetarian diet. Improving one’s health can be an important motivator to try a vegetarian diet. Ethical/moral and religious/spiritual reasons are important psychological aspects that can lead to the adoption of vegetarianism, while an attempt to reduce one’s environmental impact can motivate someone to adopt such a diet. Becoming part of a social group and achieving a sense of belonging can also be a trigger for someone to become vegetarian.

Just as some individuals might feel motivated to follow a vegetarian diet for a number of different reasons, others might feel discouraged due to psychological, social, or environmental factors. A fear of being stigmatized or excluded from their social group could hinder one’s intention of becoming a vegetarian. Moreover, cultural aspects that enhance meat consumption could have the same effect, together with the connection that people make between meat and masculinity. Finally, since the adoption of an alternative dietary pattern also relies on environmental factors, such as food availability and economics, individuals may face difficulties when adopting a vegetarian diet if they lack a good supply of plant-based food options.

6. Conclusions

In conclusion, vegetarianism can either influence or be influenced by different QoL domains. The choice of adopting a vegetarian diet can have positive consequences, such as better physical health, positive feelings related to the adoption of a morally correct attitude, an increased sense of belonging (to a vegetarian community) and lower environmental impact. On the other hand, factors that go beyond an individual’s control, such as the environment and social/cultural group in which they are inserted, as well as gender-based differences, economic aspects, and limited access to a wide variety of plant-based foods, can negatively impact the QoL of those choosing to abstain from meats or other animal products. Despite the low number of studies on vegetarianism and quality of life, the existing evidence points toward a more positive impact. It is important to understand all the effects of adopting a vegetarian diet—beyond its nutritional aspects. Not only do studies in this area provide more consistent data, but they may also contribute to mitigating all factors that might prevent individuals from adopting a vegetarian diet, or that may have a negative impact on the quality of life of those who already follow it. Further studies are necessary to understand how strongly these connections between QoL domains and vegetarianism can influence the individuals who adopt this dietary pattern.

Acknowledgments

The authors acknoledge the “Programa de Pós Graduação em Nutrição Humana da Universidade de Brasília (PPGNH/UnB)” and Luiz Eduardo S. Hargreaves for the support.

Author Contributions

Conceptualization, S.M.H. and R.P.Z.; methodology, S.M.H. and R.P.Z.; investigation, S.M.H. and R.P.Z.; writing—original draft preparation, S.M.H. and R.P.Z.; writing—review and editing, S.M.H., A.R., A.S. and R.P.Z.; visualization, S.M.H., R.P.Z., A.R.; supervision, R.P.Z. All authors have read and agreed to the published version of the manuscript.

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Data availability statement, conflicts of interest.

The authors declare no conflict of interest.

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