Minimum-wage employees are more likely to be obese than those who earn higher wages, according to a new study by UC Davis public health researchers. The study is the latest in a growing body of evidence that shows being poor is a risk factor for unhealthy weight.
"Estimating the Effects of Wages on Obesity" was published in May 2010 in the Journal of Occupational and Environmental Medicine. The authors, DaeHwan Kim and John Paul Leigh, identified several possible reasons why lower wages could support the tendency to be obese:
- Poorer people tend to live in less-safe neighborhoods with reduced access to parks and other means of physical activity
- Healthy, lower-calorie foods tend to be more expensive
- Low-income families have less access to healthier foods and often have to travel greater distances than others to find healthier food options and lower cost
"The outcome leads us to believe that raising minimum wages could be part of the solution to the obesity epidemic," Leigh said.
In a news release, Leigh noted that a novel statistic technique used for the study gave the scientists a chance to evaluate an independent factor that is definitely not caused by obesity - minimum wages.
UC Davis Cooperative Extension nutrition specialist Sheri Zidenberg-Cherr said experts are aware of the higher incidence of obesity among the poor, and believe that the causal relationship may go both ways.
"We know there have been cases of discrimination against the obese seeking employment for various types of positions," Zidenberg-Cherr said. "It is also true that, for minimum-wage earners, it is easier and cheaper to buy foods that are high in fat and sugar. They may not have the access or the education to make healthy food choices."
Leigh noted that the scientists' sample for the study were 85 percent men and 90 percent Caucasian.
"Future research should address wage and obesity correlations among samples that include more African-Americans, Hispanics, Asians and women," Leigh said. "Obesity is a complex problem that likely has multiple causes. The more we can pinpoint those causes for specific populations, the greater chances there are for reducing its impact."