Wei Sheng Yan Jiu. 2021 Sep;50(5):728-734. doi: 10.19813/j.cnki.weishengyanjiu.2021.05.005.
ABSTRACT
OBJECTIVE: To explore whether the association of community urbanization levels with overweight incidence changes over time and varies by region.
METHODS: The data is from the China Health and Nutrition Survey(1991-2015). The survey applied a multistage, random cluster design to draw samples. A total of 8684 adults aged 20-64 years were confined in nine provinces(autonomous regions). Based on an urbanicity score, communities were divided into two groups: low-and high-urbanization-level groups. The nine provinces(autonomous regions) were divided into four regions, including the Coast, Central, Northeast and West. Multilevel Logistic regression models was applied to examine whether the association between urbanization levels and overweight incidence changed over time and varied by region.
RESULTS: 38.08% of respondents became overweight during the follow-up surveys. The interactions between the high urbanization level with the Coast(OR=0.45, 95%CI 0.34-0.60), the Central(OR=0.67, 95%CI 0.52-0.86), and the Northeast(OR=0.70, 95%CI 0.52-0.94) were statistically significant. The interaction between the high urbanization level and period was also statistically significant(OR=0.97, 95%CI 0.96-0.99). In 1991, the Coast(OR=0.99, 95%CI 0.77-1.26), the high urbanization level was positively associated with overweight incidence in the Central(OR=1.45, 95%CI 1.15-1.83), Northeast(OR=1.53, 95%CI 1.16-2.02) and West(OR=2.18, 95%CI 1.68-2.83), with statistical significance. In 2015, the high urbanization level was significantly negatively associated with overweight incidence in the Coast(OR=0.53, 95%CI 0.41-0.68) and Central(OR=0.77, 95%CI 0.62-0.97), while the association in the Northeast(OR=0.82, 95%CI 0.63-1.05) and West(OR=1.17, 95%CI 0.91-1.49) was statistically insignificant.
CONCLUSION: There were spatiotemporal variations in the association between urbanization levels and overweight incidence among adults in the nine provinces(autonomous regions).
PMID:34749864 | DOI:10.19813/j.cnki.weishengyanjiu.2021.05.005
