OBJECTIVE: The objective of the study was to identify predictors of BMI in German adults by considering the BMI distribution and to determine whether the association between BMI and its predictors varies along the BMI distribution. METHODS: The sample included 9,214 adults aged 18-80 years from the German National Nutrition Survey II (NVS II). Quantile regression analyses were conducted to examine the association between BMI and the following predictors: age, sports activities, socio-economic status (SES), healthy eating index-NVS II (HEI-NVS II), dietary knowledge, sleeping duration and energy intake as well as status of smoking, partner relationship and self-reported health. RESULTS: Age, SES, self-reported health status, sports activities and energy intake were the strongest predictors of BMI. The important outcome of this study is that the association between BMI and its predictors varies along the BMI distribution. Especially, energy intake, health status and SES were marginally associated with BMI in normal-weight subjects; this relationships became stronger in the range of overweight, and were strongest in the range of obesity. CONCLUSIONS: Predictors of BMI and the strength of these associations vary across the BMI distribution in German adults. Consequently, to identify predictors of BMI, the entire BMI distribution should be considered.
OBJECTIVE: The objective of the study was to identify predictors of BMI in German adults by considering the BMI distribution and to determine whether the association between BMI and its predictors varies along the BMI distribution. METHODS: The sample included 9,214 adults aged 18-80 years from the German National Nutrition Survey II (NVS II). Quantile regression analyses were conducted to examine the association between BMI and the following predictors: age, sports activities, socio-economic status (SES), healthy eating index-NVS II (HEI-NVS II), dietary knowledge, sleeping duration and energy intake as well as status of smoking, partner relationship and self-reported health. RESULTS: Age, SES, self-reported health status, sports activities and energy intake were the strongest predictors of BMI. The important outcome of this study is that the association between BMI and its predictors varies along the BMI distribution. Especially, energy intake, health status and SES were marginally associated with BMI in normal-weight subjects; this relationships became stronger in the range of overweight, and were strongest in the range of obesity. CONCLUSIONS: Predictors of BMI and the strength of these associations vary across the BMI distribution in German adults. Consequently, to identify predictors of BMI, the entire BMI distribution should be considered.
Authors: G R Goldberg; A E Black; S A Jebb; T J Cole; P R Murgatroyd; W A Coward; A M Prentice Journal: Eur J Clin Nutr Date: 1991-12 Impact factor: 4.016
Authors: Leh Shii Law; Norhasmah Sulaiman; Wan Ying Gan; Siti Nur'Asyura Adznam; Mohd Nasir Mohd Taib Journal: Int J Environ Res Public Health Date: 2020-03-31 Impact factor: 3.390