A GIS Analysis of Los Angeles County Food Resources by Type and their Relationship to Obesity and Poverty

Lauren Minnick HSC4933.318: Intro to GIS for Public Health, Spring 2013

INTRODUCTION Obesity has been on the rise in the United States and has come to the forefront of the discussion of Public Health policy. According to

the CDC’s 2009-2010 obesity data 35.7% of adults in the U.S. were obese (BMI > 30). Obesity contributes to many of our nations health

problems, including diabetes, cardiovascular disease, hypertension, and some cancers, making it an important health concern (Ogden,

2012). One focus of current public health initiatives is the concept of ‘food deserts,’ areas where there exists a lack of healthy food

options (USDA, 2010). However, it is also important to consider the prevalence and availability of unhealthy and inexpensive food

options and the impact this may have on obesity. An additional factor for consideration is socioeconomic status. According to an obesity

report issued by the LA County Health Department, among individuals with incomes below the federal poverty level the obesity rate

was 30.2%, compared to 19.9% among individuals at 200% or above the federal poverty level (County of Los Angeles Public Health,

2012).

JUSTIFICATION

Considering the importance that has been placed on the concept of ‘food deserts’ in current efforts to fight obesity and the emphasis that

this concept places the lack of healthy options. It is also worth considering the prevalence of unhealthy food options and the impact that

this has on obesity. Mapping the prevalence of fast food restaurants is valuable, as these options are both unhealthy and inexpensive and

relate to the known correlation between poverty and obesity.

OBJECTIVE

1.Analyze the spatial relationship between the prevalence of obesity by health district and concentrations of unhealthy food options.

2.Analyze the spatial relationship between the prevalence of obesity by health district and healthy food options.

3.Analyze the spatial relationship between poverty data by census tract, obesity and food resources.

Map 1 Map 2

Map 1. A chloropleth map of the percent of the adult

population in Los Angeles County that are obese, organized by

health district boundaries. Areas of special interest are the

Antellope Valley Health District in the North East with 36.1%

adult obesity and the Inglewood (45.3% obesity), Compton

(32.8% obesity), San Antonio (32% obesity), and East LA

(37.3% obesity) Health Districts in the South Central part of

the county.

Note: Obesity status is based on Body Mass Index (BMI)

calculated from self-reported weight and height. A BMI ≥ 30 is

considered obese (Ogden, 2012).

Map 2. A chloropleth map of the percentage of the population

living below the poverty level by census tract overlaid with

health district boundaries. The darkest purple areas are the

parts of the county with the highest percentage living in

poverty. The health districts with the highest average poverty

rates are Southeast (39.3%), South (32.1%), Southwest

(28.2%), Central (27.7%), Compton (23.2%).

Note: The areas in white have no census data available.

METHODOLOGY • A GIS analysis was performed to identify the locations of healthy and unhealthy food sources

• GPS data was compiled for the locations of the top 5 grossing fast food restaurants in the United States (McDonalds,

Burger King, Wendy’s, Taco Bell, and Pizza Hut) (McConnell, 2012). These separate layers were merged to create a

single fast food layer.

• Other studies mapping food deserts analyze the accessibility of fresh groceries, so for my analysis GPS data was

compiled for farmer’s markets and 4 common grocery stores in LA County (Farmer’s Markets, Von’s, Ralph’s Grocery

Market, Albertson’s and Walmart Supercenter) (Burns, 2007). These layers were merged to form a single grocery food

source layer.

•A point density analysis was performed for both the fast food locations and grocery locations, in order to assess areas with a high

concentration of locations for each category.

•Obesity data was obtained from the 2011 Los Angeles County Health Survey and prepared in an excel file and joined to health district

polygons.

•Census data regarding poverty levels was obtained from the US Census Bureau and joined to the census tract shapefile. Note: Santa Catalina Island and San Clemente Island, both part of the Harbor Health District in LA County, have been omitted from this analysis .

Map 4

Map 6 Map 5

Map 3

Map 3. GPS point locations where fresh groceries can be

purchased within Los Angeles County.

Actual counts of grocery locations in in Health Districts with

the highest point density concentrations:

• West Health District- 69

•Hollywood-Wilshire Health District- 34

•Central Health District- 21

•Pasadena Health District- 13

•Torrance Health District-39

•Southwest Health District-17

CONCLUSION •In comparing the map layouts of obesity and poverty there is an apparent correlation between poverty and obesity.

•The Central Health District is a notable outlier, with high levels of poverty (27.7%) and a lower level of obesity (19.1%). Central Health District also contains a

high density of locations to purchase fresh groceries in comparison to other high poverty areas. Indicating that a higher number of locations to purchase fresh

groceries could have a positive impact in decreasing obesity.

•In examining the point density map of locations for purchasing fresh groceries there is a notable low density in the south central part of the county where there

is a high level of obesity and high level of poverty.

•The fast food point density shows a high density of fast food restaurants in several districts that have high levels of poverty and several with high levels of

obesity.

•The maps of locations to purchase fresh groceries contain locations for several major grocery store chains and for farmers markets in LA County. It is not a

complete list and I was unable to obtain data for smaller chains with many locations in the Los Angeles area. A future analysis containing a more complete map

of grocery locations may show a greater density in areas with high poverty and high obesity.

•The scale of obesity data is useful for health districts to know their status in comparison to other districts in the county and is also valuable for the county to

allocate resources. Further research might examine obesity data at a more focused scale, such as neighborhood or census tract, in order to more accurately

identify factors that may contribute to obesity.

Map 4. GPS point locations of fast food restaurants within

Los Angeles County.

Actual counts of fast food locations in Health Districts with

the highest point density concentrations:

•Central Health District- 37

•Southwest Health District- 39

•Southeast Health District- 7

•South- 10

•San Antonio- 41

•Inglewood- 43

Map 5. Point Density Analysis of locations with the highest

concentration of locations where fresh groceries can be

purchased. The West, Hollywood-Wilshire, Central,

Pasadena, Torrance, and Southwest Health Districts contain

the areas with the highest concentrations of fresh grocery

locations. Areas of note that contain a low density are the

Southeast, East LA, San Antonio, South, Compton, and North

East Health Districts.

Map 6. Point Density Analysis of locations with the highest

concentration of fast food restaurants. The Central, Southeast,

Southwest, South, Inglewood, and San Antonio Health

Districts contain the areas with the highest concentrations of

locations where fresh groceries can be purchased.

REFERENCES

Burns, C. Inglis, A. (2007, December). Measuring food access in Melbourne: Access to healthy and fast foods by car, bus, and foot in an urban municipality in Melbourne. Health & Place, 13(4), 877-885. http://www.sciencedirect.com.ezproxy.lib.usf.edu/science/article/pii/S1353829207000263?

McConnell, A. Bhasin, K. (2012, July 12). Ranked: the most popular fast food restaurants in America. Retrieved from http://www.businessinsider.com/the-most-popular-fast-food-restaurants-in-america-2012-7?op=1#ixzz2RRC1Z4VA

Ogden, C. Carroll, M. Kit, B. and Flegal, K. (2012, January). NCHS data brief, 82. Prevalence of obesity in the United States, 2009-2010. Retrieved from http://www.cdc.gov/nchs/data/databriefs/db82.pdf

LA County GIS Data Portal. (2012). Health Districts [Data file]. Available from http://egis3.lacounty.gov/dataportal/2012/03/01/health-districts-hd-2012/

LA County Health Survey. (2011). Obesity/overweight [Data file]. Available from http://publichealth.lacounty.gov/ha/LACHSDataTopics2011.htm

Los Angeles County Public Health. (2012, September). Trends in obesity: adult obesity continues to rise. LA Health. Retrieved from http://publichealth.lacounty.gov/ha/reports/LAHealthBrief_2011/Obesity/Obesity_2012_sFinal.pdf

US Census Bureau. (2011). Poverty status in the past 12 months [Data file] Available from http://factfinder2.census.gov/faces/nav/jsf/pages/guided_search.xhtml

US Census Bureau. (2011). California census tracts [Data file]. Available from http://www.census.gov/cgi-bin/geo/shapefiles2011/layers.cgi USDA. (2010, May). Health food financing initiative. Retrieved from http://www.ams.usda.gov/AMSv1.0/getfile?dDocName=STELPRDC5085689