The New Jersey Childhood Obesity Study, funded by the Robert Wood Johnson Foundation, aims to provide vital information for planning, implementing and evaluating interventions aimed at preventing childhood obesity in five New Jersey municipalities: Camden, Newark, New Brunswick, Trenton, and Vineland.
These five communities are being supported by RWJF's New Jersey Partnership for Healthy Kids program to plan and implement policy and environmental change strategies to prevent childhood obesity.
Effective interventions for addressing childhood obesity require community-specific information on who is most at risk and on contributing factors that can be addressed through tailored interventions that meet the needs of the community.
Using a comprehensive research study, the Center for State Health Policy at Rutgers University is working collaboratively with the State Program Office for New Jersey Partnership for Healthy I<ids and the five communities to address these information needs. The main components of the study include:
• A household survey of 1700 families with 3 -18 year old children
• De-identified heights and weights data from public school districts
• Assessment of the food and physical activity environments using objective data
Data books and maps based on the results of the study are being shared with the community coalitions in the five communities to help them plan their interventions.
The tables and graphs in this chartbook were created using data collected by Camden Public Schools for the school year 2008-2009. Rutgers Center for State Health Policy obtained de-identified data from the schools and computed a BMI score and a BMI percentile (BMIPCT) for each child. Weight status is defined using the following BMIPCT categories.
BMIPCT < 85
BMIPCT ~ 85
BMIPCT ~ 95
BMIPCT ~ 97
Not Overweight or Obese
Overweight and Obese
BMIPCT categories are presented at the city level and in sub-group analysis by age, gender, and race. Aggregate data are also presented at the school level, with notation, where representativeness of the data was a concern.
Tables and graphs on pages 5, 7, 9, and 11 show comparisons with national estimates (National Health and Nutrition Examination Survey, 2007-2008). The national data are representative of all 2-19 year old children in the US.
Each graph and table is accompanied by brief summary statements. Readers are encouraged to review the actual data presented in tables and graphs as there is much more detail.
This study aims to determine if there are differences in body mass index (BMI) across ethnic groups in the United States. Modern medicine is increasingly going the way of personalized medicine, and existing literature has begun to suggest that cultural differences may have an effect on physical health. Initially, this study was to explore anorexia nervosa prevalence, but the data is simply not there; this led to a shift in focus to exploring health differences in terms of BMI. The data analyzed is from the National Health and Nutritional Examination Survey (NHANES) collected by the Centers of Disease Control and Prevention (CDC) from 1999-2013. The subjects used were aged 13-25, and the ethnicities compared were African American, Caucasian American, Mexican American, Other Hispanic American, Asian American, and Other (including multiracial). Statistical tests were run through the software program SAS and included ANOVA tests, t-tests, and z-tests. It was found that there are differences across ethnicities, and that there are far more differences among females than among males. Asian American males and Mexican American males appear to be the groups that caused males to have significant differences. Asian Americans were also found to have the lowest average BMI by far. On the other hand, African Americans and Mexican Americans appeared to have the highest average BMIs. Although these findings and others detailed in the paper are intriguing, the BMI data is not strictly normal, and is still not normalized even by transforming the variable into a log of BMI. The data is still right skewed, and must be attacked in the future with different transformations and non-parametric tests to increase the accuracy and strength of these findings.
The rate of obesity has increased noticeably in China since the 1980s, brought about by the "After Mao" revolution. This dissertation examines the social determinants of obesity and weight gain among men and women, using 1991-2009 waves of the longitudinal China Health and Nutrition Survey. The first study emphasizes that rapid technological adoption at home may also have the potential to lead to obesity epidemics. I hypothesize that adopting household technology is a factor in weight gain, independent from daily calorie consumption and energy expenditure in exercise. The results show household technology ownership and weight gain are linked, while changes in overall energy intake and exercise may not function as mediators for this relationship. Future public health policy may evaluate interventions that are focused on increasing low-intensity activities impacted by household technologies. My second study discusses whether obesity wage penalties seen in Western societies, such as wage reductions for obese individuals, are observed in modern China. The results indicate that obese women are not subject to wage penalties, while current male obesity rates may be worsened by heightened economic outcomes and greater social acceptance by customers and colleagues. With increasing interpersonal interactions in the workplace in Chinese industries, and the lack of public awareness of the risks of obesity, Chinese public health strategies for preventing and controlling obesity should target male non-manual laborers, the most vulnerable population in the future. The third study analyzes the impact of parental and own socioeconomic status on adult body weight and extends the research by estimating the influence of intergenerational social mobility on current body mass index. In the context of increasing social inequality in China, the study shows parental SES, own SES, and social mobility to be negatively associated with body mass index among women; while respondent's SES is positively associated with body mass index among men. The study results support the theory that parental SES has a more significant impact on current body weight for men and women after controlling social mobility; indicating that social mobility may function as a mediator for the relationship between parental SES and current body mass index.