Fisher-Hoch SP, Rentfro
AR, Salinas JJ, Pérez A, Brown HS, Reininger BM, et al.
Socioeconomic status and prevalence of obesity and diabe-
tes in a Mexican American community, Cameron County,
Texas, 2004-2007. Prev Chronic Dis 2010;7(3)
In this article, the risk for obesity and diabetes is examined in a small county on the U.S-Mexico border in Texas. The study is partial to Mexican-Americans, as the county is predominately made up of Mexican-Americans. Randomly selected and studied persons aged 35-64 year olds are looked at along with their socioeconomic status and the correlation to diabetes risk along with obesity. The final sample, after going through multiple cuts to make the sample more accurate, was made up of all hispanics with 68% being female.
Variables such as, BMI, waist circumference, fasting blood glucose and insulin were taken into account. They then took this information and compared it too the annual household income, using GIS "to visualize spatial distribution" by different income quartiles. The findings were phenomenal, as this county was found to have a large uninsured racial minority population. People in the lower income stratum were found to be more likely to have undiagnosed diabetes, as the risk increases with age. Oddly enough, there were no differences between socioeconomic status with prevalence of obesity.
In this article, the risk for obesity and diabetes is examined in a small county on the U.S-Mexico border in Texas. The study is partial to Mexican-Americans, as the county is predominately made up of Mexican-Americans. Randomly selected and studied persons aged 35-64 year olds are looked at along with their socioeconomic status and the correlation to diabetes risk along with obesity. The final sample, after going through multiple cuts to make the sample more accurate, was made up of all hispanics with 68% being female.
Variables such as, BMI, waist circumference, fasting blood glucose and insulin were taken into account. They then took this information and compared it too the annual household income, using GIS "to visualize spatial distribution" by different income quartiles. The findings were phenomenal, as this county was found to have a large uninsured racial minority population. People in the lower income stratum were found to be more likely to have undiagnosed diabetes, as the risk increases with age. Oddly enough, there were no differences between socioeconomic status with prevalence of obesity.
I do not believe this study satisfies the zero conditional mean theory, which invalidates the study because it contains biased estimators. For one, the study needs to account for educational attainment levels of the individuals because it influences nutrition and income. Furthermore, the parent’s education levels needs to be included because it also determines the amount of education offspring will finish and it too influences birth weight, nutrition, and income. A variable for parks may reveal that the area is too poor to afford park construction, thus Mexican-Americans do not have a place to exercise. Another important variable would be access to a grocery store. The study needs to include the entire racial composition of the county because it may reveal that whites have lower levels of obesity in the area compared to Mexican-Americans. In conclusion, the study leaves out key variables that also effect obesity. By not accounting for these variables, the study is biased and gives incorrect obesity figures.
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