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The obesity paradox is mostly driven by decreased noncardiovascular disease mortality in the oldest old in China: a 20-year prospective cohort study

Nature Aging volume 2, pages 389–396 (2022)Cite this article

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Abstract

National and international recommendations of healthy body mass index (BMI) are primarily based on evidence in young and middle-aged populations, with an insufficient representation of the oldest old (aged ≥80 years). Here, we report associations between BMI and mortality risk in 27,026 community-dwelling oldest old (mean age, 92.7 ± 7.5 years) in China from 1998 to 2018. Nonlinear curves showed reverse J-shaped associations of BMI with cardiovascular disease (CVD), non-CVD and all-cause mortality, with a monotonic decreased risk up to BMIs in the overweight and mild obesity range and flat hazard ratios thereafter. Compared to normal weight, overweight and obesity were significantly associated with decreased non-CVD and all-cause mortality, but not with CVD mortality. Similar associations were found for waist circumference. Our results lend support to the notion that optimal BMI in the oldest old may be around the overweight or mild obesity range and challenge the application of international and national guidelines on optimal BMI in this age group.

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Fig. 1: Associations of BMI with all-cause, CVD and non-CVD mortality in Cox models with penalized splines.
Fig. 2: Association of BMI with all-cause, CVD and non-CVD mortality in the oldest old.
Fig. 3: Association of waist circumference with all-cause, CVD and non-CVD mortality in Cox models with penalized splines for men and women.
Fig. 4: Associations of weight change with all-cause, CVD and non-CVD mortality in the oldest old.

Data availability

The data that support the findings of the study are available from X.S. upon reasonable request.

Code availability

SAS version 9.4 and R version 3.5.0 code used are available from X.S. upon reasonable request.

References

  1. NCD Risk Factor Collaboration (NCD-RisC). Trends in adult body-mass index in 200 countries from 1975 to 2014: a pooled analysis of 1698 population-based measurement studies with 19.2 million participants. Lancet 387, 1377–1396 (2016).

  2. Berrington de Gonzalez, A. et al. Body-mass index and mortality among 1.46 million white adults. N. Engl. J. Med. 363, 2211–2219 (2010).

    Article  CAS  PubMed  Google Scholar 

  3. Banack, H. R. & Kaufman, J. S. The obesity paradox: understanding the effect of obesity on mortality among individuals with cardiovascular disease. Prev. Med. 62, 96–102 (2014).

    Article  PubMed  Google Scholar 

  4. Bosello, O. & Vanzo, A. Obesity paradox and aging. Eat Weight Disord. 26, 27–35 (2021).

    Article  PubMed  Google Scholar 

  5. Bhaskaran, K., Dos-Santos-Silva, I., Leon, D. A., Douglas, I. J. & Smeeth, L. Association of BMI with overall and cause-specific mortality: a population-based cohort study of 3.6 million adults in the UK. Lancet Diabetes Endocrinol. 6, 944–953 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  6. Stevens, J. et al. The effect of age on the association between body-mass index and mortality. N. Engl. J. Med. 338, 1–7 (1998).

    Article  CAS  PubMed  Google Scholar 

  7. Javed A. A. Defining Age-Appropriate BMI Cut-points for Older Adults. MSc thesis, McMaster University (2019).

  8. Kuk, J. L. & Ardern, C. I. Influence of age on the association between various measures of obesity and all-cause mortality. J. Am. Geriatr. Soc. 57, 2077–2084 (2009).

    Article  PubMed  Google Scholar 

  9. Woo, J., Ho, S. C. & Sham, A. Longitudinal changes in body mass index and body composition over 3 years and relationship to health outcomes in Hong Kong Chinese age 70 and older. J. Am. Geriatr. Soc. 49, 737–746 (2001).

    Article  CAS  PubMed  Google Scholar 

  10. Dobson, A. et al. Impact of behavioral risk factors on death within 10 years for women and men in their 70s: absolute risk charts. BMC Public Health. 12, 669 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  11. Flicker, L. et al. Body mass index and survival in men and women aged 70 to 75. J. Am. Geriatr. Soc. 58, 234–241 (2010).

    Article  PubMed  Google Scholar 

  12. Woo, J. Body mass index and mortality. Age Ageing. 45, 331–333 (2016).

    Article  PubMed  Google Scholar 

  13. Thinggaard, M., Jacobsen, R., Jeune, B., Martinussen, T. & Christensen, K. Is the relationship between BMI and mortality increasingly U-shaped with advancing age? A 10-year follow-up of persons aged 70-95 years. J. Gerontol. A Biol. Sci. Med. Sci. 65, 526–531 (2010).

    Article  PubMed  Google Scholar 

  14. Takata, Y. et al. Association between body mass index and mortality in an 80-year-old population. J. Am. Geri. Soc. 55, 913–917 (2007).

    Article  Google Scholar 

  15. Lisko, I. et al. Body mass index, waist circumference, and waist-to-hip ratio as predictors of mortality in nonagenarians: the Vitality 90+ Study. J. Gerontol. A Biol. Sci. Med. Sci. 66, 1244–1250 (2011).

    Article  PubMed  Google Scholar 

  16. Mattila, K., Haavisto, M. & Rajala, S. Body mass index and mortality in the elderly. BMJ 292, 867–868 (1986).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Weverling-Rijnsburger, A. W. et al. Total cholesterol and risk of mortality in the oldest old. Lancet 350, 1119–1123 (1997).

    Article  CAS  PubMed  Google Scholar 

  18. Satish, S., Freeman, D. H. Jr, Ray, L. & Goodwin, J. S. The relationship between blood pressure and mortality in the oldest old. J. Am. Geriatr. Soc. 49, 367–374 (2001).

    Article  CAS  PubMed  Google Scholar 

  19. Whitlock, G. et al. Body-mass index and cause-specific mortality in 900 000 adults: collaborative analyses of 57 prospective studies. Lancet 373, 1083–1096 (2009).

    Article  PubMed  Google Scholar 

  20. World Health Organization. Appropriate body-mass index for asian populations and its implications for policy and intervention strategies. Lancet 363, 157–163 (2004).

    Article  Google Scholar 

  21. Katzmarzyk, P. T. et al. Ethnic-specific BMI and waist circumference thresholds. Obesity 19, 1163–1170 (2011).

    Article  CAS  Google Scholar 

  22. St-Onge, M. P. & Gallagher, D. Body composition changes with aging: the cause or the result of alterations in metabolic rate and macronutrient oxidation? Nutrition 26, 152–155 (2010).

    Article  CAS  PubMed  Google Scholar 

  23. Lee, D. H. et al. Predicted lean body mass, fat mass, and all cause and cause specifc mortality in men: prospective US cohort study. BMJ 362, k2575 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  24. World Health Organization. Physical Status: The Use and Interpretation of Anthropometry. Report of a WHO Expert Committee (World Health Organization, 2019).

  25. Corrada, M. M., Kawas, C. H., Mozaffar, F. & Paganini-Hill, A. Association of body mass index and weight change with all-cause mortality in the elderly. Am. J. Epidemiol. 163, 938–949 (2006).

    Article  PubMed  Google Scholar 

  26. Launer, L. J., Harris, T., Rumpel, C. & Madans, J. Body mass index, weight change, and risk of mobility disability in middle-aged and older women. The epidemiologic follow-up study of NHANES I. JAMA 271, 1093–1098 (1994).

    Article  CAS  PubMed  Google Scholar 

  27. Chen, Y. et al. Association between body mass index and cardiovascular disease mortality in east Asians and south Asians: pooled analysis of prospective data from the Asia Cohort Consortium. BMJ 347, f5446 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  28. Myrskylä, M. & Chang, V. W. Weight change, initial BMI, and mortality among middle- and older-aged adults. Epidemiology. 20, 840–8 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  29. WHO expert consultation. Appropriate body-mass index for Asian populations and its implications for policy and intervention studies. Lancet 363, 157–163 (2004).

    Article  Google Scholar 

  30. Chen, C. & Lu, F. C. Department of Disease Control Ministry of Health, PR China. Guidelines for overweight and obesity of Chinese adult prevention and control. Biomed. Environ. Sci. 17, 1–36 (2004).

    PubMed  Google Scholar 

  31. World Health Organization. Obesity: Preventing and Managing the Global Epidemic. Report on a WHO Consultation on Obesity, Geneva, 3–5 June, 1997 (World Health Organization, 2000).

  32. Woo, J., Ho, S. C., Yu, A. L. M. & Sham, A. Is waist circumference a useful measure in predicting health outcomes in the elderly? Int. J. Obesity 26, 1349–1355 (2002).

    Article  CAS  Google Scholar 

  33. Miller, M. D. et al. BMI: a simple, rapid and clinically meaningful index of under-nutrition in the oldest old? Br. J. Nutr. 101, 1300–1305 (2009).

    Article  CAS  PubMed  Google Scholar 

  34. Veronese, N. et al. Inverse relationship between body mass index and mortality in older nursing home residents: a meta-analysis of 19,538 elderly subjects. Obes. Rev. 16, 1001–1015 (2015).

    Article  CAS  PubMed  Google Scholar 

  35. Breeze, E., Clarke, R., Shipley, M. J., Marmot, M. G. & Fletcher, A. E. Cause-specific mortality in old age in relation to body mass index in middle age and in old age: follow-up of the Whitehall cohort of male civil servants. Int. J. Epidemiol. 35, 169–178 (2006).

    Article  PubMed  Google Scholar 

  36. Mayeda, E. R., Filshtein, T. J., Tripodis, Y., Glymour, M. M. & Gross, A. L. Does selective survival before study enrolment attenuate estimated effects of education on rate of cognitive decline in older adults? A simulation approach for quantifying survival bias in life course epidemiology. Int. J. Epidemiol. 47, 1507–1517 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  37. Kramer, C. K., Zinman, B. & Retnakaran, R. Are metabolically healthy overweight and obesity benign conditions? A systematic review and meta-analysis. Ann. Intern. Med. 159, 758–769 (2013).

    Article  PubMed  Google Scholar 

  38. Oreopoulos, A., Kalantar-Zadeh, K., Sharma, A. M. & Fonarow, G. C. The obesity paradox in the elderly: potential mechanisms and clinical implications. Clin. Geriatr. Med. 25, 643–659 (2009).

    Article  PubMed  Google Scholar 

  39. Bouillanne, O. et al. Fat mass protects hospitalized elderly persons against morbidity and mortality. Am. J. Clin. Nutr. 90, 505–510 (2009).

    Article  CAS  PubMed  Google Scholar 

  40. Muscaritoli, M. et al. Consensus definition of sarcopenia, cachexia and pre-cachexia: joint document elaborated by Special Interest Groups (SIG) ‘cachexia-anorexia in chronic wasting diseases’ and ‘nutrition in geriatrics’. Clin. Nutr. 29, 154–159 (2010).

    Article  CAS  PubMed  Google Scholar 

  41. Cruz-Jentoft, A. J. et al. Sarcopenia: European consensus on definition and diagnosis: report of the European Working Group on sarcopenia in older people. Age Ageing 39, 4120–4123 (2010).

    Article  Google Scholar 

  42. Lee, C. G. et al. Mortality risk in older men associated with changes in weight, lean mass, and fat mass. J. Am. Geriatr. Soc. 59, 233–240 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  43. Gu D., Dupre M. E. Assessment of Reliability of Mortality and Morbidity in the 1998–2002 CLHLS Waves. Healthy Longevity in China (Springer Science Business Media, 2008).

  44. Lv, Y. B. et al. Revisiting the association of blood pressure with mortality in oldest old people in China: community based, longitudinal prospective study. BMJ 361, k2158 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  45. Lv, Y. B. et al. Association of body mass index with disability in activities of daily living among Chinese adults 80 years of age or older. JAMA Netw. Open 1, e181915 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  46. Institute of Medicine Committee to Develop Criteria for Evaluating the Outcomes of Approaches to Prevent and Treat Obesity. Weighing the Options: Criteria for Evaluating Weight-Management Programs. Thomas P. R. (ed) (National Academies Press, 1995).

  47. Greenberg, J. A. Correcting biases in estimates of mortality attributable to obesity. Obesity 14, 2071–2079 (2006).

    Article  PubMed  Google Scholar 

  48. Ensrud, K. E. et al. Comparison of 2 frailty indexes for prediction of falls, disability, fractures, and death in older women. Arch. Intern. Med. 168, 382–389 (2008).

    Article  PubMed  Google Scholar 

  49. Lajous, M. et al. Body mass index, diabetes, and mortality in French women: explaining away a ‘paradox’. Epidemiology. 25, 10–14 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

The Chinese Longitudinal Healthy Longevity Survey, which provided the data analyzed in this article, is jointly supported by National Natural Sciences Foundation of China (82025030, 81941023 and 82003500), the National Key R&D Program of China (2018YFC2000400), the National Institute on Aging (2P01AG031719), the United Nations Fund for Population Activities and the Claude D. Pepper Older Americans Independence Center (National Institute on Aging grant 5P30AG028716 to V.B.K.). The funders had no role in the study design or implementation; data collection, management, analysis and interpretation; manuscript preparation, review or approval; or decision to submit the manuscript for publication. All authors confirm that they had full access to all the data in the study and accept responsibility to submit for publication.

Author information

Authors and Affiliations

  1. China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China

    Yuebin Lv, Jinhui Zhou, Jun Duan, Wentao Wang, Jiaonan Wang & Xiaoming Shi

  2. Division of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, Guangdong, China

    Chen Mao, Jinqiu Yuan & Zhihao Li

  3. Department of Nutrition and Food Hygiene, School of Public Health, Fudan University, Shanghai, China

    Xiang Gao

  4. Vanke School of Public Health, Tsinghua University, Beijing, China

    John S. Ji

  5. Environmental Sciences and Policy, Nicholas School of the Environment, Duke University, Durham, NC, USA

    John S. Ji

  6. Duke Molecular Physiology Institute and Department of Medicine, Duke University School of Medicine, Durham, NC, USA

    Virginia Byers Kraus

  7. Division of Non-Communicable Disease Control and Community Health, Chinese Center for Disease Control and Prevention, Beijing, China

    Zhaoxue Yin & Jiesi Luo

  8. Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA

    Huashuai Chen & Qingyang Zhu

  9. Center for the study of Aging and Human Development and the Geriatric Division of School of Medicine, Duke University, Durham, NC, USA

    Yi Zeng

  10. Center for Study of Healthy Aging and Development Studies, Peking University, Beijing, China

    Yi Zeng

  11. Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China

    Jiaonan Wang & Xiaoming Shi

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Contributions

X.S. takes responsibility for the integrity of the data and the accuracy of the data analysis. Y.L., C.M., X.G., J.S.J. and J.Y. conducted the data analysis, interpreted the results and drafted the manuscript. Y.Z. and X.S. designed the survey. X.G. helped to conduct data analysis. V.B.K. assisted with data interpretation and drafting of the manuscript. Y.Z., X.S. and V.B.K. provided funding support. V.B.K., Z.Y., H.C., J.S.L., J.Z., Z.L., J.D., W.W. and J.W. helped to implement the survey. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Xiaoming Shi.

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The authors declare no competing interests.

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Nature Aging thanks Parminder Raina, Jean Woo and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data figures and tables

Extended Data Fig. 1 Subgroup analyses: association of body mass index with all-cause, CVD and non-CVD mortality in the oldest old.

Two-sided P < 0.05 was defined as statistically significant; multiple comparisons were not adjusted. *<0.05; **<0.01; ***<0.001 † Adjusted for sex, age (continuous and linear), residence, educational background, occupation, source of income, current marital status, living pattern, smoking status, alcohol drinking status, regular exercise, diagnoses of heart disease, cerebrovascular disease, digestive system diseases, respiratory disease, hypertension, cognitive impairment, and disability in activities of daily living. Data are presented as point estimates of effects ±1.96 s.e. (that is, 95% CIs). The Nodes represents the point estimates; the line segment represents the CIs; the solid line is the reference line. Analyses were performed based on the data of 27,026 Chinese oldest old, 17,070 of whom All-cause mortality, 2,389 of whom CVD, and 14,681 of whom non-CVD.

Extended Data Fig. 2 The linear association of age with all-cause mortality in Cox models with penalized splines.

The Cox models with penalized spilnes were used to explore the linear or nonlinear association of age with mortality on the basis of Akaike Information Criterion (AIC), and the linear association was detected.

Supplementary information

43587_2022_201_MOESM1_ESM.pdf

Supplementary study design, Figures 1 and 2, methodological issues in subgroup analyses, Tables 1–13 and Strengthening the Reporting of Observational Studies in Epidemiology statement.

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Lv, Y., Mao, C., Gao, X. et al. The obesity paradox is mostly driven by decreased noncardiovascular disease mortality in the oldest old in China: a 20-year prospective cohort study. Nat Aging 2, 389–396 (2022). https://doi.org/10.1038/s43587-022-00201-3

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