1. 1 Representations of the Childhood Overweight Problem in Los Angeles County June 24, 2007 County of Los Angeles Public Health Department Nutrition Program Christopher J. Jarosz, Ph.D. Ethnicity

2. 2 Introduction The role of ethnicity in childhood overweight rates was examined as a factor in explaining differences among cities and communities of Los Angeles County. A body of scientific literature has implicated ethnicity, which is supported by a cursory examination of the geographic distribution of childhood overweight rates in these analyses. The objective was to apply a level of analytic rigor in determining if associations existed among median family income, ethnicity, and childhood overweight rates. This analysis was an exploratory effort, which would then need to be conducted with greater discipline and depth.

3. 3 Methodology The analysis is based on U.S. 2000 census data for ethnicity from secondary sources based on their immediate availability (subsequent work will access the census reports directly). Ethnicity data were available for African American, Asian, American Indian and Alaskan Native, and Hispanic / Latino populations for incorporated cities in California. Data were also available for White and Other populations but they happen to be partial supersets of other ethnicities, and especially the Hispanic / Latino population. For this reason White and Other census populations were not included in the analysis. Data were not available for this analysis for Native Hawaiian and Other Pacific Islander. Multiple linear regression was performed on the childhood overweight rates (2004), ethnic data (2000), and median family incomes (2000) for Los Angeles County.

4. 4 Methodology (continued) A second regression analysis was performed for the agricultural communities in California because of similarly high childhood overweight rates as identified in the initial analysis. Although more work needs to be conducted on the role of ethnicity this initial effort enabled the methodology aspects to be defined, explored and extended.

5. 5 Childhood Overweight Rates, Median Family Income, and Ethnicity

6. 6 Conclusions The multiple regression coefficient for ethnicity, median family income, and childhood overweight rates is slightly higher (R =.8703) than the regression coefficient for the median family income and childhood overweight rates (r = -.8434). Median family income and Hispanic / Latino were statistically significant at p <.001 and p <.05, respectively. No other ethnicities displayed a strong association with childhood overweight but African American had a weak but not statistically significant association. A user interface was developed to enable an experiential view of interactions among the childhood overweight rates, median family income, and ethnicity. The user interface makes obvious that median family income has the largest (inverse) association with childhood overweight rates in Los Angeles County. Hispanic / Latino shows the second largest (direct) association although not nearly as strong.

7. 7 The user interface was expanded in the accompanying Excel spreadsheet to enable comparison of multiple conditions or scenarios, say, for a single city. The interface can be used to conduct simulations of demographic changes in some cities in the County. This interface can also be used to extrapolate childhood overweight rates for cities in Los Angeles County that were not part of the 2004 statewide study on childhood overweight. A regression analysis was also performed for California’s agricultural cities to compare apparently similar trends in childhood overweight patterns. The multiple regression coefficient was slightly less than for Los Angeles County (R = 0.8104 versus 0.8703). Conclusions (continued)

8. 8 Although both Los Angeles County and California’s agricultural areas include a substantial number of the state’s lowest income cities and communities, the agricultural areas are more homogeneous on the socioeconomic dimension. For example, 47 percent of the cities in agricultural areas have median family incomes less than $40K, and 16 percent have median family incomes above $50K (maximum $74K). In comparison Los Angeles County has median family incomes across a much wider socioeconomic spectrum—as much as a five-fold difference and possibly even higher since 2000. The strongest predictor variable for Los Angeles County and agricultural areas is median family income and ethnicity, respectively (among the limited number of factors explored in these analyses). In comparison median family income had a weaker association (r = - 0.5105), and ethnicity generally had a stronger association (which was also evident in exercising the user interface).

9. 9 Conclusions (continued) Ethnicity and socioeconomic status are known to co-vary, which makes it hard to disentangle the two. A possible next step would be to decouple ethnicity from socioeconomic status by evaluating, for example, childhood overweight rates of Hispanics / Latinos in areas of high median income. A key outcome of these series of analyses is that socioeconomic status has a substantial effect on childhood overweight rates in Los Angeles County, which has implications for social justice and how the problem can best be addressed.