A Scan of Obesogenic Environments and a Spatial Inference of Obesity Prevalence in Chinese Children and Adolescents: Based on the Chinese Health and Nutrition Survey 2011 Data

Objective To identify the characteristics of Chinese obesogenic environments at a provincial level, infer a spatial distribution map of obesity prevalence in 31 provinces, and provide a foundation for development of policy to reduce obesity in children and adolescents. Methods After scanning obesity data on subjects aged 7-17 years from 12 provinces in the China Health and Nutrition Survey 2011 and environmental data on 31 provinces from the China Statistical Yearbook 2011 and other sources, we selected 12 predictors. We used the 12 surveyed provinces as a training sample to fit an analytical model with partial least squares regression and prioritized the 12 predictors using variable importance in projection. We also fitted a predictive model with Bayesian analysis. Results We identified characteristics of obesogenic environments. We fitted the predictive model with a deviance information criterion of 61.96 and with statistically significant（P 〈 0.05） parameter estimates of intercept [95% confidence interval（CI）： 329.10, 963.11], log（oil）（CI： 13.11, 20.30）, log（GDP）（CI： 3.05, 6.93）, log（media）（CI：-234.95,-89.61）, and log（washing-machine）（CI： 0.92, 5.07）. The total inferred average obesity prevalence among those aged 7-17 was 9.69% in 31 Chinese provinces in 2011. We also found obvious clustering in occurrences of obesity in northern and eastern provinces in the predicted map. Conclusion Given complexity of obesity in children and adolescents, concerted efforts are needed to reduce consumption of edible oils, increase consumption of vegetables, and strengthen nutrition, health, and physical activity education in Chinese schools. The northern and eastern regions are the key areas requiring intervention.

Spatial Distribution of Liver Cancer Incidence in Shenqiu County,Henan Province,China:a Spatial Analysis

Liver cancer is a common and leading cause of cancer death in China.We used the cancer registry data collected from 2009 to 2011 to describe the spatial distribution of liver cancer incidence at village level in Shengqiu county,Henan province,China.Spatial autocorrelation analysis was employed to detect significant differences from a random spatial distribution of liver cancer incidence.Spatial scan statistics were used to detect and evaluate the clusters of liver cancer cases.Spatial

Increases in Height among Chinese Children and Adolescents by Gender: An Age-Period-Cohort Analysis

Objective To examine increases in average height among Chinese children and adolescents.Methods The data were obtained from the China Health and Nutrition Survey conducted during the period 1989–2015. A stratified multistage cluster sampling method was utilized to select participants aged 2–22 years in each province. Linear regression was used to examine the effects of age, birth cohort, and survey period on height.Results A total of 15,227 males and 13,737 females were included in the final analysis. Age(A) showed a continuous effect on height. The average heights of the investigated groups increased continuously during the investigation period. By 2015, the average height of the overall group increased by 7.87 cm compared to the average height during the 1989 survey. Moreover, birth year(cohort, C) also had a stable effect on height. Using the height of individuals born in or before 1975 as a reference, the average height of each birth cohort increased in comparison to the previous birth cohort.Conclusions The height of Chinese children and adolescents was affected by age, period, and cohort effects, and this effect is governed by certain rules. The age-period-cohort model can be used to analyze the trends of children’s and adolescent’s heights. The findings provide a scientific basis for the formulation of children’s and adolescents’ growth and development policies in China.