全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...
PLOS ONE  2014 

Dynamic Association of Mortality Hazard with Body Shape

DOI: 10.1371/journal.pone.0088793

Full-Text   Cite this paper   Add to My Lib

Abstract:

Background A Body Shape Index (ABSI) had been derived from a study of the United States National Health and Nutrition Examination Survey (NHANES) 1999–2004 mortality data to quantify the risk associated with abdominal obesity (as indicated by a wide waist relative to height and body mass index). A national survey with longer follow-up, the British Health and Lifestyle Survey (HALS), provides another opportunity to assess the predictive power for mortality of ABSI. HALS also includes repeat observations, allowing estimation of the implications of changes in ABSI. Methods and Findings We evaluate ABSI z score relative to population normals as a predictor of all-cause mortality over 24 years of follow-up to HALS. We found that ABSI is a strong indicator of mortality hazard in this population, with death rates increasing by a factor of 1.13 (95% confidence interval, 1.09–1.16) per standard deviation increase in ABSI and a hazard ratio of 1.61 (1.40–1.86) for those with ABSI in the top 20% of the population compared to those with ABSI in the bottom 20%. Using the NHANES normals to compute ABSI z scores gave similar results to using z scores derived specifically from the HALS sample. ABSI outperformed as a predictor of mortality hazard other measures of abdominal obesity such as waist circumference, waist to height ratio, and waist to hip ratio. Moreover, it was a consistent predictor of mortality hazard over at least 20 years of follow-up. Change in ABSI between two HALS examinations 7 years apart also predicted mortality hazard: individuals with a given initial ABSI who had rising ABSI were at greater risk than those with falling ABSI. Conclusions ABSI is a readily computed dynamic indicator of health whose correlation with lifestyle and with other risk factors and health outcomes warrants further investigation.

References

[1]  Krakauer NY, Krakauer JC (2012) A new body shape index predicts mortality hazard independently of body mass index. PLoS ONE 7: e39504. doi: 10.1371/journal.pone.0039504
[2]  He S, Chen X (2013) Could the new body shape index predict the new onset of diabetes mellitus in the Chinese population? PLoS ONE 8: e50573. doi: 10.1371/journal.pone.0050573
[3]  Matsha TE, Hassan MS, Hon GM, Soita DJ, Kengne AP, et al. (2013) Derivation and validation of a waist circumference optimal cutoff for diagnosing metabolic syndrome in a South African mixed ancestry population. International Journal of Cardiology 168: 2954–2955. doi: 10.1016/j.ijcard.2013.03.150
[4]  Duncan MJ, Mota J, Vale S, Santos MP, Ribeiro JC (2013) Associations between body mass index, waist circumference and body shape index with resting blood pressure in Portuguese adolescents. Annals of Human Biology 40: 163–167. doi: 10.3109/03014460.2012.752861
[5]  Cheung YB (2014) “A Body Shape Index” in middle-age and older Indonesian population: scaling exponents and association with incident hypertension. PLoS ONE 9: e85421. doi: 10.1371/journal.pone.0085421
[6]  Ahima RS, Lazar MA (2013) The health risk of obesitybetter metrics imperative. Science 341: 856–858. doi: 10.1126/science.1241244
[7]  Boniface DR (2013) A new obesity measure based on relative waist circumference – how useful is it? European Journal of Public Health 23: 16.
[8]  Cambridge University School of Clinical Medicine (2001) Health and lifestyle survey users’ manual. Technical report. Available: http://www.esds.ac.uk/doc/2218/mrdoc/pdf?/b2218uab.pdf.
[9]  Cox BD, Whichelow MJ, Prevost AT (1998) The development of cardiovascular disease in relation to anthropometric indices and hypertension in British adults. International Journal of Obesity 22: 966–973. doi: 10.1038/sj.ijo.0800705
[10]  Cambridge University School of Clinical Medicine (2001) HALS2 Working Manual. Technical report. Available: http://www.esds.ac.uk/doc/3279/mrdoc/pdf?/3279workman.pdf.
[11]  Cox BD (1988). Health and Lifestyle Survey, 1984–1985. computer file. doi:10.5255/UKDA-SN-2218-1.
[12]  Cox BD (1995) Health and Lifestyle Survey: Seven-Year Follow-Up, 1991–1992. computer file. doi:10.5255/UKDA-SN-3279-1.
[13]  Cox BD (2009) Health and Lifestyle Survey Deaths and Cancer Data, June 2009. computer file. doi:10.5255/UKDA-SN-6339-1.
[14]  Kom EL, Graubard BI, Midthune D (1997) Time-to-event analysis of longitudinal follow-up of a survey: choice of the time-scale. American Journal of Epidemiology 145: 72–80. doi: 10.1093/oxfordjournals.aje.a009034
[15]  Therneau TM, Grambsch PM (2000) Modeling survival data: extending the Cox model. New York: Springer-Verlag.
[16]  Burnham KP, Anderson DR (2004) Multimodel inference: Understanding AIC and BIC in model selection. Sociological Methods and Research 33: 261–304. doi: 10.1177/0049124104268644
[17]  Nagelkerke NJD (1991) A note on a general definition of the coefficient of determination. Biometrika 78: 691–692. doi: 10.1093/biomet/78.3.691
[18]  Flegal KM, Kit BK, Orpana H, Graubard BI (2013) Association of all-cause mortality with overweight and obesity using standard body mass index categories: a systematic review and meta-analysis. Journal of the American Medical Association 309: 71–82. doi: 10.1001/jama.2012.113905
[19]  Kuczmarski RJ, Flegal KM, Campbell SM, Johnson CL (1994) Increasing prevalence of overweight among US adults: The National Health and Nutrition Examination Surveys, 1960 to 1991. Journal of the American Medical Association 272: 205–211. doi: 10.1001/jama.272.3.205
[20]  Cox BD, Whichelow M (1996) Ratio of waist circumference to height is better predictor of death than body mass index. British Medical Journal 7: 313. doi: 10.1136/bmj.313.7070.1487
[21]  Mayhew L, Richardson J, Rickayzen B (2009) A study into the detrimental effects of obesity on life expectancy in the UK. Technical report, The Actuarial Profession, London. Available: http://www.actuaries.org.uk/sites/all/fi?les/documents/pdf/Mayhew_obesity.pdf.
[22]  Kvaavik E, Batty GD, Ursin G, Huxley R, Gale CR (2010) Influence of individual and combined health behaviors on total and cause-specific mortality in men and women: the United Kingdom Health and Lifestyle Survey. JAMA Internal Medicine 170: 711–718. doi: 10.1001/archinternmed.2010.76
[23]  Afsar B, Elsurer R, Kirkpantur A (2013) Body shape index and mortality in hemodialysis patients. Nutrition.
[24]  Ross R, Berentzen T, Bradshaw AJ, Janssen I, Kahn HS, et al. (2008) Does the relationship between waist circumference, morbidity and mortality depend on measurement protocol for waist circumference? Obesity Reviews 9: 312–325. doi: 10.1111/j.1467-789x.2007.00411.x
[25]  Wannamethee SG, Shaper AG, Lennon L (2005) Reasons for intentional weight loss, unintentional weight loss, and mortality in older men. Archives of Internal Medicine 165: 1035–1040. doi: 10.1001/archinte.165.9.1035
[26]  Field AE, Malspeis S, Willett WC (2009) Weight cycling and mortality among middle-aged or older women. Archives of Internal Medicine 169: 881–886. doi: 10.1001/archinternmed.2009.67
[27]  Atlantis E, Browning C, Kendig H (2010) Body mass index and unintentional weight change associated with all-cause mortality in older Australians: the Melbourne Longitudinal Studies on Healthy Ageing (MELSHA). Age and Ageing 39: 559–565. doi: 10.1093/ageing/afq073
[28]  Shea MK, Houston DK, Nicklas BJ, Messier SP, Davis CC, et al. (2010) The effect of randomization to weight loss on total mortality in older overweight and obese adults: the ADAPT study. Journals of Gerontology 65A: 519–525. doi: 10.1093/gerona/glp217
[29]  Shea MK, Nicklas BJ, Houston DK, Miller ME, Davis CC, et al. (2011) The effect of intentional weight loss on all-cause mortality in older adults: results of a randomized controlled weight-loss trial. American Journal of Clinical Nutrition 94: 839–846. doi: 10.3945/ajcn.110.006379
[30]  Lee Dc, Sui X, Artero EG, Lee IM, Church TS, et al. (2011) Long-term effects of changes in cardiorespiratory fitness and body mass index on all-cause and cardiovascular disease mortality in men: the Aerobics Center Longitudinal Study. Circulation 124: 2483–2490. doi: 10.1161/circulationaha.111.038422
[31]  Look AHEAD Research Group (2013) Cardiovascular effects of intensive lifestyle intervention in type 2 diabetes. New England Journal of Medicine 369: 145–154. doi: 10.1056/nejmoa1212914
[32]  Han TS, Richmond P, Avenell A, Lean MEJ (1997) Waist circumference reduction and cardiovascular benefits during weight loss in women. International Journal of Obesity 21: 127–134. doi: 10.1038/sj.ijo.0800377
[33]  Ross R, Dagnone D, Jones PJ, Smith H, Paddags A, et al. (2000) Reduction in obesity and related comorbid conditions after diet-induced weight loss or exercise-induced weight loss in men. Annals of Internal Medicine 133: 92–103. doi: 10.7326/0003-4819-133-2-200007180-00008
[34]  King NA, Hopkins M, Caudwell P, Stubbs RJ, Blundell JE (2009) Beneficial effects of exercise: shifting the focus from body weight to other markers of health. British Journal of Sports Medicine 43: 924–927. doi: 10.1136/bjsm.2009.065557
[35]  Romaguera D, ?ngquist L, Du H, Jakobsen MU, Forouhi NG, et al. (2010) Dietary determinants of changes in waist circumference adjusted for body mass index C a proxy measure of visceral adiposity. PLoS ONE 5: e11588. doi: 10.1371/journal.pone.0011588
[36]  Gregg EW, Gerzoff RB, Thompson TJ, Williamson DF (2003) Intentional weight loss and death in overweight and obese U.S. adults 35 years of age and older. Annals of Internal Medicine 138: 383–389. doi: 10.7326/0003-4819-138-5-200303040-00007
[37]  Gregg EW, Gerzoff RB, Thompson TJ, Williamson DF (2004) Trying to lose weight, losing weight, and 9-year mortality in overweight U.S. adults with diabetes. Diabetes Care 27: 657–662. doi: 10.2337/diacare.27.3.657

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133