Stephanie K Tanamas1, Winda L Ng1, Kathryn Backholer1, Allison Hodge2, Paul Z Zimmet3, Anna Peeters1. 1. Obesity and Population Health, Baker IDI Heart and Diabetes Institute, Melbourne, Victoria, Australia. 2. Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Victoria, 3004, Australia. 3. Department of Clinical Diabetes and Epidemiology, Baker IDI Heart and Diabetes Institute, Melbourne, Victoria, 3004, Australia.
Abstract
OBJECTIVE: To determine the risk of mortality associated with and quantify the deaths attributable to combinations of body mass index (BMI) and waist circumference (WC). METHODS: This study included 41,439 participants. For the hazard ratio (HR) calculation, adiposity categories were defined as: BMI(N) /WC(N) , BMI(N) /WC(O) , BMI(O) /WC(N) , and BMI(O) /WC(O) (N = non-obese, O = obese). For the population attributable fraction analysis, obesity was classified as: (i) obese by BMI and/or WC; (ii) obese by BMI; and (iii) obese by WC. Mortality data was complete to the end of 2012. RESULTS: The prevalence of BMI(N) /WC(N) , BMI(N) /WC(O) , BMI(O) /WC(N) , and BMI(O) /WC(O) was 73%, 6%, 6%, and 15%, respectively. There was an increased risk of all-cause and cardiovascular disease (CVD) mortality in those with BMI(N) /WC(O) (HR (95% CI) 1.2 (1.2, 1.3) and 1.3 (1.1, 1.6)) and BMI(O) /WC(O) (1.3 (1.3, 1.4) and 1.7 (1.5, 1.9)) compared to those with BMI(N) /WC(N) . The estimated proportion of all-cause and CVD mortality attributable to obesity defined using WC or using BMI and/or WC was higher compared to obesity defined using BMI. CONCLUSIONS: Current population obesity monitoring misses those with BMI(N) /WC(O) who are at increased risk of mortality. By targeting reductions in population WC, the potential exists to prevent more deaths in the population than if we continue to target reductions in BMI alone.
OBJECTIVE: To determine the risk of mortality associated with and quantify the deaths attributable to combinations of body mass index (BMI) and waist circumference (WC). METHODS: This study included 41,439 participants. For the hazard ratio (HR) calculation, adiposity categories were defined as: BMI(N) /WC(N) , BMI(N) /WC(O) , BMI(O) /WC(N) , and BMI(O) /WC(O) (N = non-obese, O = obese). For the population attributable fraction analysis, obesity was classified as: (i) obese by BMI and/or WC; (ii) obese by BMI; and (iii) obese by WC. Mortality data was complete to the end of 2012. RESULTS: The prevalence of BMI(N) /WC(N) , BMI(N) /WC(O) , BMI(O) /WC(N) , and BMI(O) /WC(O) was 73%, 6%, 6%, and 15%, respectively. There was an increased risk of all-cause and cardiovascular disease (CVD) mortality in those with BMI(N) /WC(O) (HR (95% CI) 1.2 (1.2, 1.3) and 1.3 (1.1, 1.6)) and BMI(O) /WC(O) (1.3 (1.3, 1.4) and 1.7 (1.5, 1.9)) compared to those with BMI(N) /WC(N) . The estimated proportion of all-cause and CVD mortality attributable to obesity defined using WC or using BMI and/or WC was higher compared to obesity defined using BMI. CONCLUSIONS: Current population obesity monitoring misses those with BMI(N) /WC(O) who are at increased risk of mortality. By targeting reductions in population WC, the potential exists to prevent more deaths in the population than if we continue to target reductions in BMI alone.
Authors: Michael C Farruggia; Maria J van Kooten; Emily E Perszyk; Mary V Burke; Dustin Scheinost; R Todd Constable; Dana M Small Journal: Physiol Behav Date: 2020-05-14
Authors: J Tuomela; J Kaprio; P N Sipilä; K Silventoinen; X Wang; M Ollikainen; M Piirtola Journal: Obes Res Clin Pract Date: 2019-11-21 Impact factor: 5.214