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Epidemiology and Population Health

Gender differences in midlife to later-life cumulative burden and variability of obesity measures and risk of all-cause and cause-specific mortality

International Journal of Obesity volume 48, pages 495–502 (2024)Cite this article

Subjects

Abstract

Background/Objectives

Previous studies have reported the gender-specific association between general and central obesity measures, using snapshot assessments, and mortality events. This study seeks to further explore this link by examining how the longitudinal cumulative burden and variability of obesity measures from midlife to later-life impact mortality events in the Atherosclerosis Risk in Communities (ARIC) study population, specifically in relation to gender differences.

Subjects/Methods

Using data from the ARIC study, a total of 7615 (4360 women) participants free of cardiovascular disease, cancer, and early mortality events were included in the data analysis. Longitudinal cumulative burden (estimated by the area under the curve (AUC) using a quadratic mixed-effects method) and variability (calculated according to average successive variability (ASV)) were considered as exposures, separately and all together. Cox proportional hazard regression models were used to estimate multivariable-adjusted standardized hazard ratios.

Results

The mean age was 62.4 and the median follow-up was 16.9 years. In men, AUCs of waist-related obesity measures, and also ASVs of all obesity measures were associated with increased all-cause mortality risk. In women, waist circumference and waist-to-height ratio AUCs were associated with increased all-cause mortality risk. Regarding cardiovascular mortality, all adiposity measures ASVs in both genders and waist-related obesity measures AUCs in men were associated with increased risk. Significant gender differences were found for the associations between cumulative and variability of waist-to-hip ratio for all-cause mortality and all adiposity measures ASVs for cardiovascular mortality risk with higher impact among men.

Conclusions

Cumulative burden and variability in general and central obesity measures were associated with higher all-cause and cardiovascular mortalities among men. In women, general obesity measures variability, as well as cumulative and variability of central adiposity measure, increased all-cause mortality risk.

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Fig. 1: Longitudinal trajectories of anthropometric measures during middle age to later life in men and women.
Fig. 2: Standardized hazard ratios (HRs) and 95% confidence intervals (CIs) of cumulative burden (AUC) and variability (ASV) of anthropometric measures after adjustment for each other in final multivariable-adjusted models for mortality events.

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Data availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author upon reasonable request.

References

  1. Lu Y, Hajifathalian K, Ezzati M, Woodward M, Rimm EB, Danaei G, et al. Metabolic mediators of the effects of body-mass index, overweight, and obesity on coronary heart disease and stroke: a pooled analysis of 97 prospective cohorts with 1.8 million participants. Lancet. 2014;383:970–83.

    Article  PubMed  Google Scholar 

  2. Bray GA, Frühbeck G, Ryan DH, Wilding JP. Management of obesity. The Lancet. 2016;387:1947–56.

    Article  Google Scholar 

  3. Ward ZJ, Willett WC, Hu FB, Pacheco LS, Long MW, Gortmaker SL. Excess mortality associated with elevated body weight in the USA by state and demographic subgroup: A modelling study. EClinicalMedicine. 2022;48:101429.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Liu B, Du Y, Wu Y, Snetselaar LG, Wallace RB, Bao W. Trends in obesity and adiposity measures by race or ethnicity among adults in the United States 2011-18: population based study. BMJ. 2021;372:n365.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Fryar CD, Kruszan-Moran D, Gu Q, Ogden CL. Mean body weight, weight, waist circumference, and body mass index among adults: United States, 1999-2000 through 2015-2016. Natl Health Stat Report. 2018;122:1–16.

    Google Scholar 

  6. Peters SAE, Muntner P, Woodward M. Sex differences in the prevalence of, and trends in, cardiovascular risk factors, treatment, and control in the United States, 2001 to 2016. Circulation. 2019;139:1025–35.

    Article  CAS  PubMed  Google Scholar 

  7. Cameron NA, Petito LC, McCabe M, Allen NB, O’brien MJ, Carnethon MR, et al. Quantifying the sex‐race/ethnicity‐specific burden of obesity on incident diabetes mellitus in the United States, 2001 to 2016: MESA and NHANES. J Am Heart Assoc. 2021;10:e018799.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Adams KF, Schatzkin A, Harris TB, Kipnis V, Mouw T, Ballard-Barbash R, et al. Overweight, obesity, and mortality in a large prospective cohort of persons 50 to 71 years old. N Engl J Med. 2006;355:763–78.

    Article  CAS  PubMed  Google Scholar 

  9. Feng B, Chen S, Wang X, Hu S, Zhang X, Zhang J, et al. Effect of cumulative body mass index exposure and long‐term related change on incident non‐alcoholic fatty liver disease. Liver Int. 2023;43:345–56.

    Article  CAS  PubMed  Google Scholar 

  10. Yan Y, Li S, Guo Y, Fernandez C, Bazzano L, He J, et al. Life-course cumulative burden of body mass index and blood pressure on progression of left ventricular mass and geometry in midlife: the Bogalusa Heart Study. Circul Res. 2020;126:633–43.

    Article  CAS  Google Scholar 

  11. Cook NR, Rosner BA, Chen W, Srinivasan SR, Berenson GS. Using the area under the curve to reduce measurement error in predicting young adult blood pressure from childhood measures. Stat Med. 2004;23:3421–35.

    Article  PubMed  Google Scholar 

  12. Massey RJ, Siddiqui MK, Pearson ER, Dawed AY. Weight variability and cardiovascular outcomes: a systematic review and meta-analysis. Cardiovascul Diabetol. 2023;22:1–12.

    Article  Google Scholar 

  13. Zou H, Yin P, Liu L, Liu W, Zhang Z, Yang Y, et al. Body-weight fluctuation was associated with increased risk for cardiovascular disease, all-cause and cardiovascular mortality: a systematic review and meta-analysis. Front Endocrinol. 2019;10:728.

    Article  Google Scholar 

  14. Kim DH, Nam GE, Han K, Kim Y-H, Park K-Y, Hwang H-S, et al. Variabilities in weight and waist circumference and risk of myocardial infarction, stroke, and mortality: a nationwide cohort study. Endocrinol Metab. 2020;35:933.

    Article  Google Scholar 

  15. Investigators A. The Atherosclerosis risk in COMMUNIT (ARIC) study: design and objectives. Am J Epidemiol. 1989;129:687–702.

    Article  Google Scholar 

  16. Ferrario M, Carpenter M, Chambless L. Reliability of body fat distribution measurements. The ARIC Study baseline cohort results. Atherosclerosis Risk in Communities Study. Int J Obesity Related Metab Disord. 1995;19:449–57.

    CAS  Google Scholar 

  17. Baecke JA, Burema J, Frijters JE. A short questionnaire for the measurement of habitual physical activity in epidemiological studies. Am J Clin Nutr. 1982;36:936–42.

    Article  CAS  PubMed  Google Scholar 

  18. Pinheiro J, Bates D, DebRoy S, Sarkar D, Heisterkamp S, Van Willigen B, et al. Package ‘nlme’. Linear and nonlinear mixed effects models, version. 2017;3.

  19. Echouffo-Tcheugui JB, Zhao S, Brock G, Matsouaka RA, Kline D, Joseph JJ. Visit-to-visit glycemic variability and risks of cardiovascular events and all-cause mortality: the ALLHAT study. Diabetes Care. 2019;42:486–93.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Lu Z, Geurts S, Arshi B, Tilly MJ, Aribas E, van Lennep JR, et al. editors. Longitudinal anthropometric measures and risk of new-onset atrial fibrillation among community-dwelling men and women. Mayo Clinic Proceedings; 2022: Elsevier.

  21. Yang Y, Dugué P-A, Lynch BM, Hodge AM, Karahalios A, MacInnis RJ, et al. Trajectories of body mass index in adulthood and all-cause and cause-specific mortality in the Melbourne Collaborative Cohort Study. BMJ Open. 2019;9:e030078.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Zheng H, Tumin D, Qian Z. Obesity and mortality risk: new findings from body mass index trajectories. Am J Epidemiol. 2013;178:1591–9.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Hirko KA, Kantor ED, Cohen SS, Blot WJ, Stampfer MJ, Signorello LB. Body mass index in young adulthood, obesity trajectory, and premature mortality. Am J Epidemiol. 2015;182:441–50.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Cho IJ, Chang HJ, Sung JM, Yun YM, Kim HC, Chung N. Associations of changes in body mass index with all-cause and cardiovascular mortality in healthy middle-aged adults. PLoS One. 2017;12:e0189180.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Alharbi TA, Paudel S, Gasevic D, Ryan J, Freak-Poli R, Owen AJ. The association of weight change and all-cause mortality in older adults: a systematic review and meta-analysis. Age Ageing. 2021;50:697–704.

    Article  PubMed  Google Scholar 

  26. Wilsgaard T, Jacobsen BK, Mathiesen EB, Njølstad I. Weight loss and mortality: a gender-specific analysis of the Tromsø study. Gend Med. 2009;6:575–86.

    Article  PubMed  Google Scholar 

  27. Tamakoshi K, Yatsuya H, Kondo T, Ishikawa M, Zhang H, Murata C, et al. Long-term body weight variability is associated with elevated C-reactive protein independent of current body mass index among Japanese men. Int J Obesity. 2003;27:1059–65.

    Article  CAS  Google Scholar 

  28. Strohacker K, McFarlin BK. Influence of obesity, physical inactivity, and weight cycling on chronic inflammation. Front Biosci (Elite edition). 2010;2:98–104.

    CAS  Google Scholar 

  29. Patsouras MD, Vlachoyiannopoulos PG. Evidence of epigenetic alterations in thrombosis and coagulation: a systematic review. J Autoimmun. 2019;104:102347.

    Article  CAS  PubMed  Google Scholar 

  30. Hunt BJ, editor Hemostasis at extremes of body weight. Seminars in Thrombosis and Hemostasis; 2018: Thieme Medical Publishers.

  31. McGee DL, Collaboration DP. Body mass index and mortality: a meta-analysis based on person-level data from twenty-six observational studies. Annals of epidemiology. 2005;15:87–97.

    Article  PubMed  Google Scholar 

  32. Yatsuya H, Tamakoshi K, Yoshida T, Hori Y, Zhang H, Ishikawa M, et al. Association between weight fluctuation and fasting insulin concentration in Japanese men. Int J Obes Relat Metab Disord. 2003;27:478–83.

    Article  CAS  PubMed  Google Scholar 

  33. Anastasiou CA, Yannakoulia M, Pirogianni V, Rapti G, Sidossis LS, Kavouras SA. Fitness and weight cycling in relation to body fat and insulin sensitivity in normal-weight young women. J Am Dietetic Assoc. 2010;110:280–4.

    Article  Google Scholar 

  34. French SA, Jeffery RW, Folsom AR, Williamson DF, Byers T. Relation of weight variability and intentionality of weight loss to disease history and health-related variables in a population-based sample of women aged 55–69 years. Am J Epidemiol. 1995;142:1306–14.

    Article  CAS  PubMed  Google Scholar 

  35. Waring ME, Eaton CB, Lasater TM, Lapane KL. Incident diabetes in relation to weight patterns during middle age. Am J Epidemiol. 2010;171:550–6.

    Article  PubMed  PubMed Central  Google Scholar 

  36. Field AE, Manson JE, Laird N, Williamson DF, Willett WC, Colditz GA. Weight cycling and the risk of developing type 2 diabetes among adult women in the United States. Obesity Res. 2004;12:267–74.

    Article  Google Scholar 

  37. Wing RR, Jeffery RW, Hellerstedt WL. A prospective study of effects of weight cycling on cardiovascular risk factors. Arch Internal Med. 1995;155:1416–22.

    Article  CAS  Google Scholar 

  38. Olson MB, Kelsey SF, Bittner V, Reis SE, Reichek N, Handberg EM, et al. Weight cycling and high-density lipoprotein cholesterol in women: evidence of an adverse effect: a report from the NHLBI-sponsored WISE study. J Am College of Cardiol. 2000;36:1565–71.

    Article  CAS  Google Scholar 

  39. Cereda E, Malavazos AE, Caccialanza R, Rondanelli M, Fatati G, Barichella M. Weight cycling is associated with body weight excess and abdominal fat accumulation: a cross-sectional study. Clin Nutr. 2011;30:718–23.

    Article  PubMed  Google Scholar 

  40. Wallner S, Luschnigg N, Schnedl W, Lahousen T, Sudi K, Crailsheim K, et al. Body fat distribution of overweight females with a history of weight cycling. Int J Obesity. 2004;28:1143–8.

    Article  CAS  Google Scholar 

  41. Pankow JS, Tang W, Pankratz N, Guan W, Weng L-C, Cushman M, et al. Identification of genetic variants linking protein C and lipoprotein metabolism: the ARIC study (Atherosclerosis Risk in Communities). Arteriosclerosis Thrombosis Vascular Biol. 2017;37:589–97.

    Article  CAS  Google Scholar 

  42. Gaillard R, Steegers EA, Tiemeier H, Hofman A, Jaddoe VW. Placental vascular dysfunction, fetal and childhood growth, and cardiovascular development: the generation R study. Circulation. 2013;128:2202–10.

    Article  PubMed  Google Scholar 

  43. Heise L, Greene ME, Opper N, Stavropoulou M, Harper C, Nascimento M, et al. Gender inequality and restrictive gender norms: framing the challenges to health. The Lancet. 2019;393:2440–54.

    Article  Google Scholar 

  44. Stringhini S, Carmeli C, Jokela M, Avendaño M, Muennig P, Guida F, et al. Socioeconomic status and the 25× 25 risk factors as determinants of premature mortality: a multicohort study and meta-analysis of 1· 7 million men and women. The Lancet. 2017;389:1229–37.

    Article  Google Scholar 

  45. Dwivedi AK, Vishwakarma D, Dubey P, Reddy SY. Air pollution and the heart: updated evidence from meta-analysis studies. Curr Cardiol Rep. 2022;24:1811–35.

    Article  PubMed  Google Scholar 

  46. Dubey P, Reddy SY, Singh V, Shi T, Coltharp M, Clegg D, et al. Association of exposure to phthalate metabolites with sex hormones, obesity, and metabolic syndrome in US women. JAMA Network Open. 2022;5:e2233088-e.

    Article  Google Scholar 

  47. Kander MC, Cui Y, Liu Z. Gender difference in oxidative stress: a new look at the mechanisms for cardiovascular diseases. J Cellular Mol Med. 2017;21:1024–32.

    Article  Google Scholar 

  48. Han X, Stevens J, Truesdale KP, Bradshaw PT, Kucharska-Newton A, Prizment AE, et al. Body mass index at early adulthood, subsequent weight change and cancer incidence and mortality. Int J Cancer. 2014;135:2900–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Argyrakopoulou G, Dalamaga M, Spyrou N, Kokkinos A. Gender differences in obesity-related cancers. Curr Obesity Rep. 2021;10:100–15.

    Article  Google Scholar 

  50. Harrington M, Gibson S, Cottrell RC. A review and meta-analysis of the effect of weight loss on all-cause mortality risk. Nutr Res Rev. 2009;22:93–108.

    Article  PubMed  Google Scholar 

  51. Locher JL, Roth DL, Ritchie CS, Cox K, Sawyer P, Bodner EV, et al. Body mass index, weight loss, and mortality in community-dwelling older adults. J Gerontol A Biol Sci Med Sci. 2007;62:1389–92.

    Article  PubMed  Google Scholar 

  52. Kaze AD, Santhanam P, Erqou S, Ahima RS, Bertoni AG, Echouffo-Tcheugui JB. Body weight variability and risk of cardiovascular outcomes and death in the context of weight loss intervention among patients with type 2 diabetes. JAMA Netw Open. 2022;5:e220055-e.

    Article  Google Scholar 

  53. St-Onge MP, Gallagher D. Body composition changes with aging: the cause or the result of alterations in metabolic rate and macronutrient oxidation? Nutrition. 2010;26:152–5.

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

We thank the participants ARIC study and the Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC) website staff for their contributions.

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Authors and Affiliations

  1. Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran

    Karim Kohansal, Siamak Afaghi, Davood Khalili, Danial Molavizadeh & Farzad Hadaegh

  2. Department of Epidemiology and Biostatistics, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran

    Karim Kohansal & Davood Khalili

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Contributions

FH and KK were responsible for the study conceptualization and design, analysis of demographic data, interpretation of results, and preparation of the manuscript. KK was responsible for analytic design and data analysis. KK, FH, SA, DK, and DM were responsible for the conceptualization of the study. All listed authors reviewed the manuscript and agree to be accountable for all aspects of this work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

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Correspondence to Farzad Hadaegh.

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Kohansal, K., Afaghi, S., Khalili, D. et al. Gender differences in midlife to later-life cumulative burden and variability of obesity measures and risk of all-cause and cause-specific mortality. Int J Obes 48, 495–502 (2024). https://doi.org/10.1038/s41366-023-01440-z

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