OBJECTIVE: To verify the optimal cut-off points for overweight and obesity in Chinese adults based on the relationship of baseline body mass index (BMI) to all-cause mortality, and incidence of cardiovascular diseases from pooled data of Chinese cohorts. METHODS: The prospective study data of existing cohort studies in China were collected, and the age-adjusted all-cause mortality stratified by BMI were estimated. The similar analysis was repeated after excluding deaths within the first three years of follow-up and after excluding smokers. The incidence of age-adjusted coronary heart disease (CHD) and stroke stratified by BMI were also analyzed. Multiple Cox regression coefficients of BMI for the incidence of CHD and stroke after controlling other risk factors were pooled utilizing the methods of weighting by inverse of variance to reveal whether BMI had independent effect and its strength on the incidence of CHD and stroke. RESULTS: The data of 4 cohorts including 76,227 persons, with 745,346 person-years of follow-up were collected and analyzed. The age-adjusted all-cause mortality stratified by BMI showed a U-shaped curve, even after excluding deaths within the first three years of follow-up and excluding smokers. Age-adjusted all-cause mortality increased when BMI was lower than 18.5 and higher than 28. The incidence of CHD and stroke, especially ishemic stroke increased with increasing BMI, this was consistent with parallel increasing of risk factors. Cox regression analysis showed that BMI was an independent risk factor for both CHD and stroke. Each amount of 2 kg/m2 increase in baseline BMI might cause 15.4%, 6.1% and 18.8% increase in relative risk of CHD, total stroke and ischemic stroke. Reduction of BMI to under 24 might prevent the incidence of CHD by 11% and that of stroke by 15% for men, and 22% of both diseases for women. CONCLUSION: BMI < or = 18.5, 24-27.9 and > or = 28 (kg/m2) is the appropriate cut-off points for underweight, overweight and obesity in Chinese adults.
OBJECTIVE: To verify the optimal cut-off points for overweight and obesity in Chinese adults based on the relationship of baseline body mass index (BMI) to all-cause mortality, and incidence of cardiovascular diseases from pooled data of Chinese cohorts. METHODS: The prospective study data of existing cohort studies in China were collected, and the age-adjusted all-cause mortality stratified by BMI were estimated. The similar analysis was repeated after excluding deaths within the first three years of follow-up and after excluding smokers. The incidence of age-adjusted coronary heart disease (CHD) and stroke stratified by BMI were also analyzed. Multiple Cox regression coefficients of BMI for the incidence of CHD and stroke after controlling other risk factors were pooled utilizing the methods of weighting by inverse of variance to reveal whether BMI had independent effect and its strength on the incidence of CHD and stroke. RESULTS: The data of 4 cohorts including 76,227 persons, with 745,346 person-years of follow-up were collected and analyzed. The age-adjusted all-cause mortality stratified by BMI showed a U-shaped curve, even after excluding deaths within the first three years of follow-up and excluding smokers. Age-adjusted all-cause mortality increased when BMI was lower than 18.5 and higher than 28. The incidence of CHD and stroke, especially ishemic stroke increased with increasing BMI, this was consistent with parallel increasing of risk factors. Cox regression analysis showed that BMI was an independent risk factor for both CHD and stroke. Each amount of 2 kg/m2 increase in baseline BMI might cause 15.4%, 6.1% and 18.8% increase in relative risk of CHD, total stroke and ischemic stroke. Reduction of BMI to under 24 might prevent the incidence of CHD by 11% and that of stroke by 15% for men, and 22% of both diseases for women. CONCLUSION: BMI < or = 18.5, 24-27.9 and > or = 28 (kg/m2) is the appropriate cut-off points for underweight, overweight and obesity in Chinese adults.
Authors: Lindsay M Jaacks; Penny Gordon-Larsen; Elizabeth J Mayer-Davis; Linda S Adair; Barry Popkin Journal: Int J Epidemiol Date: 2013-06-14 Impact factor: 7.196