Discussion
We used data from approximately 1.6 million children from California from 2010 through 2012 to assess the association between family income and physical fitness score, BMI z-score, and obesity. For all 8 racial/ethnic groups, children with lower family income were found to be less physically fit, have higher BMI z-score, and have higher prevalence of obesity than children with higher family income. The percentage of children with low family income was disproportionately high among Hispanic or Latino and African American children. Approximately 75% of Hispanic or Latino and 67% of African American children were identified as low income, compared with only 24% of white children.
Previous studies of children's physical fitness have been limited to examining either income or race/ethnicity and its relationship to physical fitness. Two previous studies also used the Fitnessgram protocol to examine children's fitness and also reported higher physical fitness for children with higher income, but no race-specific relationships were tested in these studies. A separate study examined racial/ethnic differences in physical activity and found that white and Asian children were more likely to participate in moderate to vigorous activity than Hispanic and African American children. We expand on this work by showing that children with lower family income were found to be significantly less physically fit compared with higher income children in 8 different racial/ethnic groups. In our study, the magnitude of the association between family income and fitness scores was smaller for Filipino, Hispanic or Latino, and African American children than that seen in American Indian or Alaska Native and white children.
There are several possible reasons for the relationship between low family income and lower physical fitness. First, populations with low SES may be more likely to live in low SES communities. Parents from low SES communities have reported higher perceived neighborhood crime and unpleasant neighborhood features compared with those from high SES communities. This concern for safety could make low SES parents less inclined to let their children play outside, thereby restricting physical activity. Low SES communities may have fewer physical activity facilities, particularly few free activity resources, than high SES communities, thus limiting access to opportunities for physical activity. At an individual level, lower income families may experience many stressors and barriers to health and as a result may place less priority on leisure time physical activity compared with higher income families. Many leisure activities may also be cost-prohibitive for low-income parents due to membership, participation, or equipment fees.
Within all racial/ethnic groups, children with lower family income also had significantly higher risk of obesity than children with higher family income. This finding contrasts with those of previous studies, which have shown that SES is inversely related to obesity only among white children. In fact, the magnitude of the association between family income and obesity was as large for Asian girls as it was for white girls and was only slightly higher than the magnitude seen among girls of 2 or more races and Pacific Islanders or Native Hawaiians. Similar findings were seen among boys, where whites also had the largest magnitude of association, but this was only slightly higher than that seen for Asians and Pacific Islanders or Native Hawaiians. These findings are in contrast to findings from Hispanic and African American children in NHANES. Previous NHANES data showed no consistent pattern for Hispanic children, and among African American children, there was a positive association. In another study of teens and young adults, only white children (and not black or Hispanic children) showed clear decreasing overweight prevalence with increasing income. We suspect that our large sample size allowed us to detect these differences within racial/ethnic groups and sex, whereas the limited nonwhite sample in NHANES is not able to pick up these differences. However, the magnitude of increased risk was substantial and cannot be a case of picking up very small differences as merely a result of having a large sample. By pooling over a range of ages, analyses using NHANES data may have missed these disparities in children aged 10 to 17 years.
Potential reasons for this association between family income and obesity are the same as those for the association with physical activity, because low physical activity participation and sedentary lifestyle could be the cause of higher prevalence of overweight and obesity. Additional reasons for the observed relationship could include the price of healthy food compared with unhealthy food and food insecurity.
In terms of sex differences and the association between family income and fitness score, within racial/ethnic groups, income-based differences were larger for girls than boys, in general. Boys are generally more likely to participate in physical activity than girls, so boys with low family income could be more physically active than their female counterparts, resulting in less difference in fitness scores between lower family and higher family income.
A strength of this study was the large sample size and diverse population, which allowed us to assess whether family income was associated with obesity and fitness for 8 racial/ethnic groups. An additional strength was the measurement of fitness, rather than using self-reported activity. Finally, the data are representative of public school students in California.
Our study also has limitations. Data from students in private schools were not available. Use of data from this population would influence the estimation of actual sociodemographic distribution of the students in California, because private school students may have different socioeconomic characteristics, including higher incomes. NSLP information was not available in the data before 2010, so we were unable to analyze time trends in these relationships. Family income was only categorized into 2 groups on the basis of NSLP eligibility, which may have limited power because there is less distinction between the highest and the lowest income groups. Area SES may influence the physical activity of children but was not analyzed in this study. Also, we cannot determine whether the association between family income and childhood obesity or children's physical fitness is causal because the data used were cross-sectional. We did not have detailed information on additional parental characteristics, such as education, occupation, BMI, or motivation, all of which could be associated with family income and may also be associated with child BMI and physical fitness, creating unmeasured confounding. Finally, the results may not be generalizable to other states.
We conclude that children with low family income tend to be less physically fit and have higher risk of obesity than children with higher family income. We observed this relationship for 8 racial/ethnic groups and for both boys and girls. This information is relevant for targeting policies and programs aimed at improving the fitness levels and decreasing the obesity risk of children.