Body mass index is negatively associated with telomere length: a collaborative cross-sectional meta-analysis of 87 observational studies

Abstract

Background: Even before the onset of age-related diseases, obesity might be a contributing factor to the cumulative burden of oxidative stress and chronic inflammation throughout the life course. Obesity may therefore contribute to accelerated shortening of telomeres. Consequently, obese persons are more likely to have shorter telomeres, but the association between body mass index (BMI) and leukocyte telomere length (TL) might differ across the life span and between ethnicities and sexes.

Objective: A collaborative cross-sectional meta-analysis of observational studies was conducted to investigate the associations between BMI and TL across the life span.

Design: Eighty-seven distinct study samples were included in the meta-analysis capturing data from 146,114 individuals. Study-specific age- and sex-adjusted regression coefficients were combined by using a random-effects model in which absolute [base pairs (bp)] and relative telomere to single-copy gene ratio (T/S ratio) TLs were regressed against BMI. Stratified analysis was performed by 3 age categories ("young": 18-60 y; "middle": 61-75 y; and "old": >75 y), sex, and ethnicity.

Results: Each unit increase in BMI corresponded to a -3.99 bp (95% CI: -5.17, -2.81 bp) difference in TL in the total pooled sample; among young adults, each unit increase in BMI corresponded to a -7.67 bp (95% CI: -10.03, -5.31 bp) difference. Each unit increase in BMI corresponded to a -1.58 × 10(-3) unit T/S ratio (0.16% decrease; 95% CI: -2.14 × 10(-3), -1.01 × 10(-3)) difference in age- and sex-adjusted relative TL in the total pooled sample; among young adults, each unit increase in BMI corresponded to a -2.58 × 10(-3) unit T/S ratio (0.26% decrease; 95% CI: -3.92 × 10(-3), -1.25 × 10(-3)). The associations were predominantly for the white pooled population. No sex differences were observed.

Conclusions: A higher BMI is associated with shorter telomeres, especially in younger individuals. The presently observed difference is not negligible. Meta-analyses of longitudinal studies evaluating change in body weight alongside change in TL are warranted.

FIGURE 1

Study inclusion flow chart. L/C ratio, telomere/centromere ratio; T/S ratio, telomere to single-copy gene ratio.

FIGURE 2

Forest plot of the β estimates (regression coefficients) from the meta-analysis of the association between BMI and absolute telomere length (base pairs) as the outcome in the total pooled population. Random effect model was used and adjusted for age and sex. Statistical heterogeneity was estimated by I² statistics for each of the 12 meta-analyses. The shaded boxes indicate the inverse variance weighting of each estimate, and the size of the box indicates the weight. In case no shaded box is visible, the weight is very small. COPD, Chronic Obstructive Lung disease cohort; CURES, Chennai Urban Rural Epidemiology Study; ES, estimate; ESTHER, Epidemiological Study on the Chances of Prevention, Early Recognition, and Optimised Treatment of Chronic Diseases in the Older Population; HyperGEN, Hypertension Genetic Epidemiology Network study; LRC, Lipid Research Clinic; LSADT, Longitudinal Study of Aging Danish Twins (https://www.icpsr.umich.edu/icpsrweb/NACDA/studies/21041); NHSC, Nutrition and Health in Southwest China study; RPCI, Roswell Park Cancer Institute; SOLVABLE, Study of Lupus Vascular and Bone Longterm Endpoints; ZTL2008, Zannolli Telomere Length 2008.

FIGURE 3

Forest plot of the β estimates (regression coefficients) from the meta-analysis of the association between BMI and relative telomere length (T/S ratio) as outcome in the total pooled population. The unit of the estimates and 95% CI is 10⁻³. A random-effects model was used and adjusted for age and sex. Statistical heterogeneity was estimated by I² statistics for each of the 12 meta-analyses. The shaded boxes indicate the inverse variance weighting of each estimate, and the size of the box indicates the weight. In case no shaded box is visible, the weight is very small. ACCT, Anglo-Cardiff Collaborative Trial; BASE-II, Berlin Aging Study; CAS, calcific aortic valve stenosis study; CAVASIC, Cardiovascular Disease in Intermittent Claudication; DALS, Diet, Activity and Lifestyle Study; DHS, Dallas Heart Study; EARSII, European Atherosclerosis Study II; ECRAN, Envejecimiento y Enfermedades Crónicas Asociadas a Nutrición (Aging and Nutrition Associated Chronic Diseas); EPIDREAM, Epidemiologic study of the Screenes for DREAM (Diabetes Reduction Assessment with Ramipril and Rosiglitazone Medication); ES, estimate; GAHR2, Prospective evaluation of Gender and Age differences in the impact of Hostility and Reactivity on intermediary coronary artery disease risk factors; HBCS, Helsinki Birth Cohort Study; KORA F3, Cooperative Health Research in the Region of Augsburg F3 (2004/2005) survey; KORA F4, Cooperative Health Research in the Region of Augsburg F4 (2006/2008) survey; MDCC, Malmö Diet and Cancer Cohort; MESA, Multi-Ethnic Study of Atherosclerosis (https://www.mesa-nhlbi.org/); MONICA, Multinational Monitoring of Trends and Determinants in Cardiovascular Disease; NESDA, The Netherlands Study of Depression and Anxiety; NESDO, The Netherlands Study of Depression in older persons; NHANES, National Health and Nutrition Examination Survey; Not publ, not published; PATH 40, Personality and Total Health Through Life Project AGE 40-44; PATH 60, Personality and Total Health Through Life Project AGE 60-64; PREDIMED, Prevención con Dieta Mediterránea; PREVEND, Prevention of Renal and Vascular End-stage Disease; PRT, Progressive Resistance Training; Ref, reference; RPE, Richard Paul Ebstein; SAPHIR, Salzburg Atherosclerosis Prevention program in subjects at High Individual Risk Study; SWHS, Shanghai Women's Health Study; T/S ratio, telomere to single-copy gene ratio; UMED, Uniwersytet MEDyczny w Łodzi (Medical University of Lodz (MUL)); UMS, ultra-marathon study; USKCS, US Kidney Cancer Study; YMCA, Young Men Cardiovascular Association.

FIGURE 4

Forest plot of the β estimates (regression coefficients) from the meta-analysis of the association between BMI and absolute telomere length (base pairs) as outcome in the “young” pooled population (age ≥18 and ≤60 y). A random-effects model was used and adjusted for sex. Statistical heterogeneity was estimated by I² statistics for each of the 12 meta-analyses. The shaded boxes indicate the inverse variance weighting of each estimate, and the size of the box indicates the weight. In case no shaded box is visible, the weight is very small. COPD, Chronic Obstructive Lung disease cohort; CURES, Chennai Urban Rural Epidemiology Study; ES, estimate; ESTHER, Epidemiological Study on the Chances of Prevention, Early Recognition, and Optimised Treatment of Chronic Diseases in the Older Population; HyperGEN, Hypertension Genetic Epidemiology Network study; LRC, Lipid Research Clinic; LSADT, Longitudinal Study of Aging Danish Twins (https://www.icpsr.umich.edu/icpsrweb/NACDA/studies/21041); NHSC, Nutrition and Health in Southwest China study; Not publ, not published; Ref, reference; RPCI, Roswell Park Cancer Institute; SOLVABLE, Study of Lupus Vascular and Bone Longterm Endpoints; ZTL2008, Zannolli Telomere Length 2008.

FIGURE 5

Forest plot of the β estimates (regression coefficients) from the meta-analysis of the association between BMI and relative telomere length (T/S ratio) as the outcome in the “young” pooled population (age ≥18 y and ≤60 y). The unit of the estimates and 95% CI is 10⁻³. A random-effects model was used and adjusted for sex. Statistical heterogeneity was estimated by I² statistics for each of the 12 meta-analyses. The shaded boxes indicate the inverse variance weighting of each estimate, and the size of the box indicates the weight. In case no shaded box is visible, the weight is very small. ACCT, Anglo-Cardiff Collaborative Trial; BASE-II, Berlin Aging Study; CAS, calcific aortic valve stenosis study; CAVASIC, Cardiovascular Disease in Intermittent Claudication; DALS, Diet, Activity and Lifestyle Study; DHS, Dallas Heart Study; EARSII, European Atherosclerosis Study II; ECRAN, Envejecimiento y Enfermedades Crónicas Asociadas a Nutrición (Aging and Nutrition Associated Chronic Diseas); EpiDREAM, Epidemiologic study of the Screenes for DREAM (Diabetes Reduction Assessment with Ramipril and Rosiglitazone Medication); ES, estimate; GAHR2, Prospective evaluation of Gender and Age differences in the impact of Hostility and Reactivity on intermediary coronary artery disease risk factors; HBCS, Helsinki Birth Cohort Study; KORA F3, Cooperative Health Research in the Region of Augsburg F3 (2004/2005) survey; KORA F4, Cooperative Health Research in the Region of Augsburg F4 (2006/2008) survey; MDCC, Malmö Diet and Cancer Cohort; MESA, Multi-Ethnic Study of Atherosclerosis (https://www.mesa-nhlbi.org/); MONICA, Multinational Monitoring of Trends and Determinants in Cardiovascular Disease; NESDA, The Netherlands Study of Depression and Anxiety; NESDO, The Netherlands Study of Depression in older persons; Not publ, not published; PATH 40, Personality and Total Health Through Life Project AGE 40–44; PREDIMED, Prevención con Dieta Mediterránea; PREVEND, Prevention of Renal and Vascular End-stage Disease; PRT, Progressive Resistance Training; Ref, reference; RPE, Richard Paul Ebstein; SAPHIR, Salzburg Atherosclerosis Prevention program in subjects at High Individual Risk Study; SWHS, Shanghai Women's Health Study; T/S ratio, telomere-to–single-copy gene ratio; UMED, Uniwersytet MEDyczny w Łodzi (Medical University of Lodz (MUL)); UMS, ultra-marathon study; USKCS, US Kidney Cancer Study; YMCA, Young Men Cardiovascular Association.