The Big Cities Health Coalition (BCHC) provided two "mini-grants" to graduate students for work related to the Big Cities Health Inventory (BCHI) Data Platform. The data platform is an innovative tool that allows the user to easily explore, compare and share 30,000 public health data points from 30 cities. These students were asked to analyze data from the platform and present their findings at the National Association of County and City Health Officials (NACCHO) Annual Conference in 2018.

What is the relationship between obesity and income? Insights from the Big Cities Health Inventory

Michael Benusic, MD, CCFP is a Master of Public Health student at Johns Hopkins Bloomberg School of Public Health. He analyzed data from the BCHI data platform to determine the relationship between obesity prevalence and income in big cities. 

Report Summary

Obesity, a risk factor for many diseases, has a complex association with socioeconomic factors. Further clarification of this association could guide population interventions. To determine the relationship between obesity prevalence, socioeconomic indicators, race/ethnicity, and physical activity in large US cities, a cross-sectional multivariable linear regression of city-level variables of residents of large American cities was performed, using 2012-2014 data from the Big Cities Health Inventory. The main outcome was the association of obesity prevalence with median household income, with secondary variables of race/ethnicity, educational attainment, and the proportion of the population meeting physical activity guidelines.

Increased household income was significantly associated with decreased obesity prevalence when analyzing the entire dataset (Figure 1), and this relationship remained in a subset analysis of White and Black populations. This relationship was not seen for Hispanic populations. No association was found between obesity prevalence and the proportion of the population meeting physical activity guidelines (Figure 1).

At the population level of large US cities, obesity prevalence is inversely associated with median household income in White and Black populations. Strategies to increase socioeconomic status may also decrease obesity. Critical appraisal of physical activity-based programs as an obesity intervention may be warranted.

Figure 1. Scatter matrix of median household income (scale: log-transformed, 10,000 USD), obesity prevalence (%), and proportion meeting physical activity guidelines (%), among racial/ethnic groups of cities in the Big Cities Health Inventory.

Figure 1. Scatter matrix of median household income (scale: log-transformed, 10,000 USD), obesity prevalence (%), and proportion meeting physical activity guidelines (%), among racial/ethnic groups of cities in the Big Cities Health Inventory.