Sohyun Park1, Bo Youl Choi, Youfa Wang, Elizabeth Colantuoni, Joel Gittelsohn. 1. Department of Preventive Medicine, College of Medicine, Hanyang University, Seongdong-gu, Seoul, South Korea; Center for Human Nutrition and Johns Hopkins Global Center on Childhood Obesity, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland. Electronic address: sopark@hanyang.ac.kr.
Abstract
PURPOSE: We examined the association between the school and neighborhood nutrition environments and adolescent nutrition behaviors and weight status. METHODS: We conducted a cross-sectional survey with 1,342 fourth to ninth graders in 15 schools on their food-eating behaviors. Participants were randomly selected from eight predetermined districts in Seoul, South Korea. Height and weight data from the school annual health check-ups were obtained. Dietitians from each school completed questionnaires on the school nutrition environment. Types of food outlets in a 500-meter radius of the schools were recorded. Healthy eating index was created based on 10 questions on students' eating behaviors, such as breakfast skipping, fruit consumption, and ramen noodle consumption (possible score range 0-10). Generalized estimating equation method was used for statistical modeling. RESULTS: Higher density of supermarkets and traditional markets in the school neighborhoods was associated with a greater likelihood of child obesity after controlling for individual-level covariates (odds ratio = 1.37, 1.21-1.54). The school nutrition environment was not associated with student's healthy eating habits and weight status. Students who were younger, female, from more affluent families, who had less weekly screen time, or had stay-at-home mothers had higher scores on the healthy eating index. There was a gender difference in the associations between environmental factors and students' eating behaviors and obesity status. CONCLUSIONS: These findings suggest that the relationship between environmental factors and individual factors and weight status may be more complicated than previously reported in other parts of the world.
PURPOSE: We examined the association between the school and neighborhood nutrition environments and adolescent nutrition behaviors and weight status. METHODS: We conducted a cross-sectional survey with 1,342 fourth to ninth graders in 15 schools on their food-eating behaviors. Participants were randomly selected from eight predetermined districts in Seoul, South Korea. Height and weight data from the school annual health check-ups were obtained. Dietitians from each school completed questionnaires on the school nutrition environment. Types of food outlets in a 500-meter radius of the schools were recorded. Healthy eating index was created based on 10 questions on students' eating behaviors, such as breakfast skipping, fruit consumption, and ramen noodle consumption (possible score range 0-10). Generalized estimating equation method was used for statistical modeling. RESULTS: Higher density of supermarkets and traditional markets in the school neighborhoods was associated with a greater likelihood of childobesity after controlling for individual-level covariates (odds ratio = 1.37, 1.21-1.54). The school nutrition environment was not associated with student's healthy eating habits and weight status. Students who were younger, female, from more affluent families, who had less weekly screen time, or had stay-at-home mothers had higher scores on the healthy eating index. There was a gender difference in the associations between environmental factors and students' eating behaviors and obesity status. CONCLUSIONS: These findings suggest that the relationship between environmental factors and individual factors and weight status may be more complicated than previously reported in other parts of the world.
Authors: Lauren Fiechtner; Mona Sharifi; Thomas Sequist; Jason Block; Dustin T Duncan; Steven J Melly; Sheryl L Rifas-Shiman; Elsie M Taveras Journal: Child Obes Date: 2015-04-29 Impact factor: 2.992
Authors: Mika Matsuzaki; Brisa N Sánchez; Maria Elena Acosta; Jillian Botkin; Emma V Sanchez-Vaznaugh Journal: Obes Rev Date: 2020-02-05 Impact factor: 9.213
Authors: Kun Mei; Hong Huang; Fang Xia; Andy Hong; Xiang Chen; Chi Zhang; Ge Qiu; Gang Chen; Zhenfeng Wang; Chongjian Wang; Bo Yang; Qian Xiao; Peng Jia Journal: Obes Rev Date: 2020-07-28 Impact factor: 9.213
Authors: Julianne Williams; Peter Scarborough; Nick Townsend; Anne Matthews; Thomas Burgoine; Lorraine Mumtaz; Mike Rayner Journal: PLoS One Date: 2015-07-17 Impact factor: 3.240
Authors: Trudy M A Wijnhoven; Joop M A van Raaij; Agneta Sjöberg; Nazih Eldin; Agneta Yngve; Marie Kunešová; Gregor Starc; Ana I Rito; Vesselka Duleva; Maria Hassapidou; Eva Martos; Iveta Pudule; Ausra Petrauskiene; Victoria Farrugia Sant'Angelo; Ragnhild Hovengen; João Breda Journal: Int J Environ Res Public Health Date: 2014-10-30 Impact factor: 3.390