Impact of body mass index and metabolically unhealthy status on mortality in the Japanese general population: The JMS cohort study
Autoři:
Toshihide Izumida aff001; Yosikazu Nakamura aff002; Shizukiyo Ishikawa aff002
Působiště autorů:
Kamitaira Clinic, Nanto, Toyama, Japan
aff001; Division of Public Health, Center for Community Medicine, Jichi Medical University, Shimotsuke, Tochigi, Japan
aff002
Vyšlo v časopise:
PLoS ONE 14(11)
Kategorie:
Research Article
doi:
https://doi.org/10.1371/journal.pone.0224802
Souhrn
This study aimed to investigate the associations of body mass index (BMI) and metabolically unhealthy weight with all-cause mortality, cardiovascular disease (CVD) mortality, and cancer mortality as well as the effect of age on the associations. This prospective study enrolled Japanese individuals in the general population. Participants were divided into eight phenotypes according to the BMI classification and metabolic status. Hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated using a Cox regression hazard model. In total, 10,824 individuals with a mean age of 55.3 years were evaluated. During a mean follow-up of 18.4 years (198,776 person-years), 2,274 participants died. Among the metabolically unhealthy, the association between BMI and mortality was J-shaped after adjustment for various confounders (multivariable HR [95% CI] for all-cause mortality: underweight, 2.0 [1.5–2.7]; obesity 2.8 [2.1–3.6]). The association remained the same in metabolically unhealthy participants aged <65 years and ≥65 years. The results were compatible in the analyses restricted to subjects who never smoked. Regardless of age, metabolically unhealthy underweight (MUHU) have approximately a 3-fold higher risk of CVD mortality, compared with metabolically healthy normal weight. Not only metabolically unhealthy obesity, but also MUHU was strongly associated with an increased risk of mortality. More attention should be given to the health issues of metabolically unhealthy participants without obesity, particularly those with MUHU.
Klíčová slova:
Body Mass Index – Cardiovascular diseases – Glucose metabolism – Glucose tolerance tests – Cholesterol – Obesity – Physical activity
Zdroje
1. Ärnlöv J, Ingelsson E, Sundström J, Lind L. Impact of Body Mass Index and the Metabolic Syndrome on the Risk of Cardiovascular Disease and Death in Middle-Aged Men. Circulation. 2010;121:230–236. doi: 10.1161/CIRCULATIONAHA.109.887521 20038741
2. Saito I, Iso H, Kokubo Y, Inoue M, Tsugane S. Metabolic syndrome and all-cause and cardiovascular disease mortality: Japan Public Health Center-based Prospective (JPHC) Study. Circ J. 2009;73:878–84. doi: 10.1253/circj.cj-08-1025 19282609
3. Bea JW, Sweitzer NK. More Appropriate Cardiovascular Risk Screening Through Understanding Complex Phenotypes: Mind the Gap. J Am Coll Cardiol. 2017;70:1438–1440. doi: 10.1016/j.jacc.2017.07.742 28911507
4. Huang K, Liu F, Han X, Huang C, Huang J, Gu D, et al. Association of BMI with total mortality and recurrent stroke among stroke patients: A meta-analysis of cohort studies. Atherosclerosis. 2016;253:94–101. doi: 10.1016/j.atherosclerosis.2016.08.042 27596134
5. Tsugane S, Sasaki S, Tsubono Y. Under- and overweight impact on mortality among middle-aged Japanese men and women: a 10-y follow-up of JPHC Study cohort I. Int J Obes Relat Metab Disord. 2002;26:529–537. doi: 10.1038/sj.ijo.0801961 12075580
6. Dehlendorff C, Andersen KK, Olsen TS. Body mass index and death by stroke: no obesity paradox. JAMA Neurol. 2014;71:978–987. doi: 10.1001/jamaneurol.2014.1017 24886975
7. Berrington de Gonzalez A, Hartge P, Cerhan JR, Flint AJ, Hannan L, MacInnis RJ, et al. Body-Mass Index and Mortality among 1.46 Million White Adults. N Engl J Med. 2010;363:2211–2219. doi: 10.1056/NEJMoa1000367 21121834
8. Gao B, Zhang L, Zhao M. Underweight but metabolically abnormal phenotype: Metabolic features and its association with cardiovascular disease. Eur J Intern Med. 2016;29:46–51. doi: 10.1016/j.ejim.2015.11.020 26703431
9. Caleyachetty R, Thomas GN, Toulis KA, Mohammed N, Gokhale KM, Balachandran K, et al. Metabolically healthy obese and incident cardiovascular disease events among 3.5 million men and women. J Am Coll Cardiol 2017;70:1429–37. doi: 10.1016/j.jacc.2017.07.763 28911506
10. Nakao YM, Miyamoto Y, Ueshima K, Nakao K, Nakai M, Nishimura K, et al. Effectiveness of nationwide screening and lifestyle intervention for abdominal obesity and cardiometabolic risks in Japan: The metabolic syndrome and comprehensive lifestyle intervention study on nationwide database in Japan (MetS ACTION-J study). PLoS One. 2018;13:e0190862. doi: 10.1371/journal.pone.0190862 29315322
11. Lee SH, Han K, Yang HK, Kim HS, Cho JH, Kwon HS, et al. A novel criterion for identifying metabolically obese but normal weight individuals using the product of triglycerides and glucose. Nutr Diabetes. 2015;5:e149. doi: 10.1038/nutd.2014.46 25915739
12. Stefan N, Schick F, Häring HU. Causes, Characteristics, and Consequences of Metabolically Unhealthy Normal Weight in Humans. Cell Metab. 2017;26:292–300. doi: 10.1016/j.cmet.2017.07.008 28768170
13. Finucane MM, Stevens GA, Cowan MJ, Danaei G, Lin JK, Paciorek CJ, et al. National, regional, and global trends in body-mass index since 1980: systematic analysis of health examination surveys and epidemiological studies with 960 country-years and 9·1 million participants. Lancet. 2011;377:557–567. doi: 10.1016/S0140-6736(10)62037-5 21295846
14. Ahuja V, Kadowaki T, Evans RW, Kadota A, Okamura T, El Khoudary SR, et al. Comparison of HOMA-IR, HOMA-β% and disposition index between US white men and Japanese men in Japan: the ERA JUMP study. Diabetologia. 2015;58:265–271. doi: 10.1007/s00125-014-3414-6 25316435
15. Kramer CK, Zinman B, Retnakaran R. Are metabolically healthy overweight and obesity benign conditions?: A systematic review and meta-analysis. Ann Intern Med. 2013;159:758–769. doi: 10.7326/0003-4819-159-11-201312030-00008 24297192
16. Ng TP, Jin A, Chow KY, Feng L, Nyunt MSZ, Yap KB. Age-dependent relationships between body mass index and mortality: Singapore longitudinal ageing study. PLoS ONE. 2017;12:e0180818. doi: 10.1371/journal.pone.0180818 28738068
17. Deurenberg P, Yap M, Van Staveren WA. Body mass index and percent body fat: a meta analysis among different ethnic groups. Int J Obes Relat Metab Disord. 1998; 22:1164–1171. doi: 10.1038/sj.ijo.0800741 9877251
18. Wu C-Y, Chou Y-C, Huang N, Chou Y-J, Hu H-Y, Li C-P. Association of Body Mass Index with All-Cause and Cardiovascular Disease Mortality in the Elderly. PLoS ONE. 2014;9:e102589. doi: 10.1371/journal.pone.0102589 25014070
19. Jee SH, Sull JW, Park J, Lee SY, Ohrr H, Guallar E, et al. Body-mass index and mortality in Korean men and women. N Engl J Med. 2006;355:779–787. doi: 10.1056/NEJMoa054017 16926276
20. Ishikawa S, Gotoh T, Nago N, Kayaba K. The Jichi Medical School (JMS) Cohort Study: design, baseline data and standardized mortality ratios. J Epidemiol 2002;12:408–417. doi: 10.2188/jea.12.408 12462275
21. Hirokawa K, Tsutusmi A, Kayaba K. Impacts of educational level and employment status on mortality for Japanese women and men: the Jichi Medical School cohort study. Eur J Epidemiol 2006;21: 641–651. doi: 10.1007/s10654-006-9049-2 17048083
22. Kannel WB, Sorlie P. Some health benefits of physical activity. The Framingham Study. Arch Intern Med 1979;139:857–861. doi: 10.1001/archinte.139.8.857 464698
23. WHO Expert Consultation. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet. 2004;363:157–163. doi: 10.1016/S0140-6736(03)15268-3 14726171
24. Grundy SM, Cleeman JI, Daniels SR, Donato KA, Eckel RH, Franklin BA, et al. Diagnosis and management of the metabolic syndrome: an American Heart Association/National Heart, Lung, and Blood Institute Scientific Statement. Circulation. 2005;112:2735–2752. doi: 10.1161/CIRCULATIONAHA.105.169404 16157765
25. Ridker PM, Wilson PWF, Grundy SM. Should C-Reactive Protein Be Added to Metabolic Syndrome and to Assessment of Global Cardiovascular Risk? Circulation. 2004;109:2818–2858. doi: 10.1161/01.CIR.0000132467.45278.59 15197153
26. Karelis AD, Faraj M, Bastard JP, St-Pierre DH, Brochu M, Prud'homme D, et al. The Metabolically Healthy but Obese Individual Presents a Favorable Inflammation Profile. J Clin Endocrinol Metab. 2005;90:4145–4150. doi: 10.1210/jc.2005-0482 15855252
27. Bhaskaran K, Dos-Santos-Silva I, Leon DA, Douglas IJ, 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. 2018;6:944–953. doi: 10.1016/S2213-8587(18)30288-2 30389323
28. Iacobini C, Pugliese G, Fantauzzi CB, Federici M, Menini S. Metabolically healthy versus metabolically unhealthy obesity. Metabolism. 2019;92:51–60. doi: 10.1016/j.metabol.2018.11.009 30458177
29. Lotta LA, Gulati P, Day FR, Payne F, Ongen H, van de Bunt M, et al. Integrative genomic analysis implicates limited peripheral adipose storage capacity in the pathogenesis of human insulin resistance. Nat Genet. 2016;49:17–26. doi: 10.1038/ng.3714 27841877
30. Ruderman N, Chisholm D, Pi-Sunyer X, Schneider S. The metabolically obese, normal-weight individual revisited. Diabetes. 1998;47:699–713. doi: 10.2337/diabetes.47.5.699 9588440
31. Scherbakov N, Dirnagl U, Doehner W. Body Weight After Stroke: lessons from the obesity paradox. Stroke. 2011;42:3646–3650. doi: 10.1161/STROKEAHA.111.619163 21960580
32. Lundin H, Sääf M, Strender LE, Mollasaraie HA, Salminen H. Mini nutritional assessment and 10-year mortality in free-living elderly women: a prospective cohort study with 10-year follow-up. Eur J Clin Nutr. 2012;66:1050–1053. doi: 10.1038/ejcn.2012.100 22947901
33. Winslow UC, Rode L, Nordestgaard BG. High tobacco consumption lowers body weight: a Mendelian randomization study of the Copenhagen General Population Study. International Journal of Epidemiology. 2015;44:540–550. doi: 10.1093/ije/dyu276 25777141
34. Aune D, Sen A, Prasad M, Norat T, Janszky I, Tonstad S, et al. BMI and all cause mortality: systematic review and non-linear dose-response meta-analysis of 230 cohort studies with 3.74 million deaths among 30.3 million participants. BMJ. 2016;353:i2156–17. doi: 10.1136/bmj.i2156 27146380
35. Sundvall J, Leiviskä J, Laatikainen T, Peltonen M, Salomaa V, Vanhala M, et al. The use of fasting vs. non-fasting triglyceride concentration for estimating the prevalence of high LDL-cholesterol and metabolic syndrome in population surveys. BMC Med Res Methodol. 2011;11:63. doi: 10.1186/1471-2288-11-63 21569280
36. Nordestgaard BG, Langsted A, Mora S, Kolovou G, Baum H, Bruckert E, Watts GF, et al. Fasting is not routinely required for determination of a lipid profile: clinical and laboratory implications including flagging at desirable concentration cut-points-a joint consensus statement from the European Atherosclerosis Society and European Federation of Clinical Chemistry and Laboratory Medicine. Eur Hear J. 2016; 37: 1944–1958. doi: 10.1093/eurheartj/ehw152 27122601
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PLOS One
2019 Číslo 11
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