Purpose of the Study
The main purpose of the article by Chen, Janickee, and Volpe (2016) was to assess the link between obesity and various aspects of food environments in 2104 counties across the United States. The impact of food choices and environment on health has been a widely researched and discussed topic in since early1990s. Some of the research studies show that no significant relationship between the health and food choices and environment. However, other research studies results indicate a significant relationship between and individual’s health and food choices and environment. This paper presents a review of the research methods, data analysis technique, results, and the limitations of the article by Chen et al. (2016).
Research Questions
How was obesity and overweight status influenced by different factors, such as, age, gender, race, education, income, and environment?
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Hypothesis
The environment around individuals, whether at home or the neighborhood, does have an impact on obesity.
Research Methods
The study applied a quantitative research method by involving 2104 counties in various states. The researchers employed observational study design by collecting data from sources of food stores and restaurants establishment data. The study utilized a sample of 38, 650 people from 18,381 households from the selected counties in the year 2014. Individuals’ food purchases from the stores and supermarket were recorded by home-scanning device from 2008 to 2012. This shows that a longitudinal research design was applied to assess the consumption changes over the four-year period. Chan et al. (2016) collected secondary data from two sources. The main source of data was the IRi Consumer Panel. The other source of data used was the IRi MedProfiler and Rural–Urban Continuum Codes and census tract–level food desert information. IRi Consumer Panel and the IRi MedProfiler data provided individual and household level data required for the study. In addition, Rural–Urban Continuum Codes and census tract–level food desert information was utilized to give information on individual-level data. The two data collection methods were appropriate because it gave people access to what foods individuals’ households were buying. The MedProfiler gave data on weight and height to determine people’s BMI.) .Generally, the collected data was numerical form such as, height, weight, and age to find the numerical answers for BMI and obesity rates.
Data Analysis Techniques
The researcher utilized descriptive statistics using like odds, intra class correlation, and standard deviation to analyze the collected data. The estimated obesity for persons living in the household had a highest score of USDA 13 and lowest of 1. Correlation analysis was used to establish the extent of association between food environment and obesity. The key demographics of the data were income, household-race and size, education, and marital status collected from various stores and restaurants and the Census Bureau extracted the information from 2104 counties in the United States of America.
Results
Descriptive statistics results showed that at least one third (1/3) of the survey sample size was overweight and other one third was obese. The average Body Mass Index (BMI) of adults was approximately 28.50. the results show that a one-point USDA score increase, results to 7% obesity decrease with a 95 percent confidence interval of (0.90,0.96). In addition, the county level obesity and USDA are negatively related with a correlation coefficient of -0.12. The relationship between county level obesity and USDA is statistically significant with a probability of 0.001 at 5% significance level.
Under controlled home environment factors, poverty level at county level and obesity are not correlated in any way. Also, people living in counties that are close to the cities had a high probability of being obese or overweight, the results of the article shows. According to the results, a significant relationship between individual’s health and food choices and environment exist. USDA score and obesity status of an individual are negatively correlated while food desert status and obesity was positively correlated. It was found that the food environment factors have a significant correlation or association with obese state of and individual under normal conditions. Moreover, under controlled home environment factors, food environment factors have a significant correlation or association with obese state of and individual.
Limitations
The study techniques and data collections methods employed by Chen et al. (2016) were adequate and reliable. However, there are few potential limitations of the study. One of the potential limitations is the fact that the data used was not only secondary data, but also self-reported. Self-reported data do not always reflect factual details. In addition, the data extracted from the Census Bureau extracted the demographics information from 2104 counties in the United States may not be consistent as at the year 2016. There is a possibility that the same individuals had already changed their food consumption behaviors. Another potential limitation of the study is that the data was self-reported and collected but no information on whether people actually ate the food that was purchased. For instance, the food that was scanned only showed food purchased not consumed.
Reference
Chen, D., Jaenicke, E., & Volpe, R. (2016). Food Environments and Obesity: Household Diet Expenditure versus Food Deserts. American Journal of Public Health , 106 (5), 881-888. doi: 10.2105/ajph.2016.303048
