OBJECTIVE: To examine the longitudinal association between red meat consumption and changes in body mass index(BMI), body weight and overweight risk in Chinese adults. METHODS: Data from the open, prospective cohort study 'China Health and Nutrition Survey' (CHNS), 18 006 adults(47.5% males)were chosen as the study subjects who participated in at least one wave of survey between 1991 and 2009. Three-level(community-individual-measure occasion) mixed effect modeling was performed to investigate the effect of red meat consumption on BMI, body weight changes and risk of overweight. The average daily red meat intake was assessed using consecutive 3 d 24 h recalls. RESULTS: In general, participants with higher red meat intake appeared to be those with younger age, higher personal income and higher education level, lower physical activities, higher total energy intake, smokers and alcohol drinkers. 3-level mixed-effects linear regression models showed that red meat intake was positively associated with changes in BMI and body weight. Compared to those who consumed no red meat, men and women in the highest quartile of red meat intake showed an increase of 0.17(95% CI:0.08-0.26, P < 0.0001)and 0.12 kg/m(2) (95%CI:0.02-0.22, P < 0.05) on BMI and increase of 596 g (95%CI:329-864, P < 0.0001) and 400 g (95%CI:164-636, P < 0.0001) on body weight, respectively, after adjustment for potential confounders (age, income, education, smoking, alcohol, physical activity level, community urbanization index and total energy intake). After adjustment for above confounders and baseline BMI, results from the 3-level mixed effect logistic model indicated that the odds ratios of being overweight in males and females who had the highest quartile of red meat intake were 1.21 (95%CI:1.01-1.46, P < 0.05)and 1.18(95% CI:1.01-1.37, P < 0.05) in comparison with non-consumers of red meat, respectively. CONCLUSION: Higher red meat intake was associated with increased BMI and body weight, as well as increased overweight risk.
OBJECTIVE: To examine the longitudinal association between red meat consumption and changes in body mass index(BMI), body weight and overweight risk in Chinese adults. METHODS: Data from the open, prospective cohort study 'China Health and Nutrition Survey' (CHNS), 18 006 adults(47.5% males)were chosen as the study subjects who participated in at least one wave of survey between 1991 and 2009. Three-level(community-individual-measure occasion) mixed effect modeling was performed to investigate the effect of red meat consumption on BMI, body weight changes and risk of overweight. The average daily red meat intake was assessed using consecutive 3 d 24 h recalls. RESULTS: In general, participants with higher red meat intake appeared to be those with younger age, higher personal income and higher education level, lower physical activities, higher total energy intake, smokers and alcohol drinkers. 3-level mixed-effects linear regression models showed that red meat intake was positively associated with changes in BMI and body weight. Compared to those who consumed no red meat, men and women in the highest quartile of red meat intake showed an increase of 0.17(95% CI:0.08-0.26, P < 0.0001)and 0.12 kg/m(2) (95%CI:0.02-0.22, P < 0.05) on BMI and increase of 596 g (95%CI:329-864, P < 0.0001) and 400 g (95%CI:164-636, P < 0.0001) on body weight, respectively, after adjustment for potential confounders (age, income, education, smoking, alcohol, physical activity level, community urbanization index and total energy intake). After adjustment for above confounders and baseline BMI, results from the 3-level mixed effect logistic model indicated that the odds ratios of being overweight in males and females who had the highest quartile of red meat intake were 1.21 (95%CI:1.01-1.46, P < 0.05)and 1.18(95% CI:1.01-1.37, P < 0.05) in comparison with non-consumers of red meat, respectively. CONCLUSION: Higher red meat intake was associated with increased BMI and body weight, as well as increased overweight risk.
Authors: Z H Wang; F Y Zhai; H J Wang; J G Zhang; W W Du; C Su; J Zhang; H R Jiang; B Zhang Journal: Eur J Clin Nutr Date: 2014-10-29 Impact factor: 4.016
Authors: Z Wang; B Zhang; F Zhai; H Wang; J Zhang; W Du; C Su; J Zhang; H Jiang; B M Popkin Journal: Nutr Metab Cardiovasc Dis Date: 2014-03-20 Impact factor: 4.222
Authors: Zhihong Wang; Linda S Adair; Jianwen Cai; Penny Gordon-Larsen; Anna Maria Siega-Riz; Bing Zhang; Barry M Popkin Journal: J Nutr Date: 2017-10-04 Impact factor: 4.798