UKCPR University of Kentucky Center for Poverty Research Discussion Paper Series DP 2016-05 ISSN: 1936-9379 Supermarket Proximity and Price: Food Insecurity and Obesity in the United States Janelle Downing, PhD, MS. Community Health and Human Development School of Public Health University of California, Berkeley Barbara Laraia, PhD, MPH, RD Community Health and Human Development School of Public Health University of California, Berkeley Preferred citation: Downing, J., & Laraia, B. (2016). Supermarket proximity and price: Food Insecurity and Obesity in the United States. University of Kentucky Center for Poverty Research Discussion Paper Series, DP2016-05. Retrieved [Date] from http://www.ukcpr.org/research/discussion-papers. This project was supported through funding by the U.S. Department of Agriculture, Economic Research Service and the Food Nutrition Service, Agreement Numbers 58-5000-1-0050 and 58-5000-3-0066. The opinions and conclusions expressed herein are solely those of the authors and should not be construed as representing the opinions or policies of the sponsoring agency. University of Kentucky Center for Poverty Research, 234 Gatton Building, Lexington, KY, 40506-0047 Phone: 859-257-7641; Fax: 859-257-6959; E-mail: ukcpr@uky.edu www.ukcpr.org
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UKCPR University of Kentucky
Center for
Poverty Research
Discussion Paper Series DP 2016-05
ISSN: 1936-9379
Supermarket Proximity and Price:
Food Insecurity and Obesity in the United States
Janelle Downing, PhD, MS. Community Health and Human Development
School of Public Health University of California, Berkeley
Barbara Laraia, PhD, MPH, RD
Community Health and Human Development School of Public Health
University of California, Berkeley
Preferred citation: Downing, J., & Laraia, B. (2016). Supermarket proximity and price: Food Insecurity and Obesity in the United States. University of Kentucky Center for Poverty Research Discussion Paper Series, DP2016-05. Retrieved [Date] from http://www.ukcpr.org/research/discussion-papers. This project was supported through funding by the U.S. Department of Agriculture, Economic Research Service and the Food Nutrition Service, Agreement Numbers 58-5000-1-0050 and 58-5000-3-0066. The opinions and conclusions expressed herein are solely those of the authors and should not be construed as representing the opinions or policies of the sponsoring agency.
University of Kentucky Center for Poverty Research, 234 Gatton Building, Lexington, KY, 40506-0047
Note: *p<0.1, **p<0.05, ***p<0.01. All models included robust standard errors clustered at the
Census Block Group. Models fit with logit produced similar results to probit estimates. Number
of Households is 4,826. Missing-Indicator approach was used. Results were nearly identical
with complete case analysis, including sampling weights, and adjusting for region.
Food APS Research Initiative – Page 13
Figure 1: Proportion of Block Groups in each Geographic Region, by Food Price
Environment
Figure 2: Proportion of Rural and Urban Block Groups in High (Top 5th) Food Price
Environment
Food APS Research Initiative – Page 14
Figure 3: Proportion of Income on Housing, by Price Environment
Figure 4: Household Reasons for Selecting Primary Supermarket, by Food Security and
Obesity
Food APS Research Initiative – Page 15
Figure 5: Predictive Margins of Food Insecurity (Binary) with 95% CI, by Reasons for
Shopping at Primary Store
Note: Reference group (not shown) is “other” reasons for selecting primary store. Graph shows the marginal effects after a logit model adjusted for full set of covariates, with robust standard errors clustered at the block group. 95% confidence intervals that cross zero are not statistically significant.
Figure 6: Predictive Margins of Food Insecurity (Binary) with 95% CI, by Shopping at
Primary Store for Low Prices
Note: Reference group (not shown) is not selecting “low prices” are reason for shopping at primary store. Graph
shows the marginal effects after a logit model adjusted for full set of covariates, with robust standard errors clustered at the block group. 95% confidence intervals that cross zero are not statistically significant.
Food APS Research Initiative – Page 16
Figure 7: Predictive Margins of Obesity (Binary) with 95% CI, by Reasons for Shopping at
Primary Store
Note: Reference group (not shown) is “other” reasons for selecting primary store. Graph shows the marginal
effects after a logit model adjusted for full set of covariates, with robust standard errors clustered at the block group. 95% confidence intervals that cross zero are not statistically significant.
Figure 8: Predictive Margins of Obesity (Binary) with 95% CI, by Shopping at Primary
Store for Low Prices
Note: Reference group (not shown) is not selecting “low prices” are reason for shopping at primary store. Graph shows the marginal effects after a logit model adjusted for full set of covariates, with robust standard errors clustered at the block group. 95% confidence intervals that cross zero are not statistically significant.
Food APS Research Initiative – Page 17
Figure 9: Predictive Margins of Food Security (Ordinal) with 95% CI, by Food Desert
(Block Group)
Note: Graph shows the marginal effects of living in a food desert on high, marginal, low, and very low food security
after a multinomial logit model adjusted for full set of covariates, with robust standard errors clustered at the block group. 95% confidence intervals that cross zero are not statistically significant.
Figure 10: Predictive Margins of Food Insecurity (Binary) in Poor Block Groups with 95%
CI, by Food Tundra (3mi)
Note: Reference group (not shown) is not residing in a block group with food prices in top 5th. Graph shows the
marginal effects of food insecurity after a logit model adjusted for full set of covariates, with robust standard errors
clustered at the block group. 95% confidence intervals that cross zero are not statistically significant.
Food APS Research Initiative – Page 18
Figure 11: Predictive Margins of Food Security (Ordinal) with 95% CI, by Food Tundra
(3mi)
Note: Graph shows the marginal effects of residing in a food tundra (3mi) on high, marginal, low, and very low food
security after a multinomial logit model adjusted for full set of covariates, with robust standard errors clustered at
the block group. 95% confidence intervals that cross zero are not statistically significant.
Figure 12: Predictive Margins of Food Security (Ordinal) in Poor Block Groups with 95%
CI, by Food Tundra (3mi)
Note: Graph shows the marginal effects of residing in a food tundra on high, marginal, low, and very low food
security among residents of poor block groups after a multinomial logit model adjusted for full set of covariates,
with robust standard errors clustered at the block group. 95% confidence intervals that cross zero are not statistically
significant.
Food APS Research Initiative – Page 19
Figure 13: Predictive Margins of Food Security (Ordinal) with 95% CI, by Food Tundra
(5mi)
Note: Graph shows the marginal effects of residing in a food tundra (5mi) on high, marginal, low, and very low food security after a multinomial logit model adjusted for full set of covariates, with robust standard errors clustered at
the block group. 95% confidence intervals that cross zero are not statistically significant.
Figure 14: Predictive Margins of Food Security (Ordinal) with 95% CI, by Food Tundra
(10mi)
Note: Graph shows the marginal effects of residing in a food tundra (10mi) on high, marginal, low, and very low
food security after a multinomial logit model adjusted for full set of covariates, with robust standard errors clustered
at the block group. 95% confidence intervals that cross zero are not statistically significant.
Food APS Research Initiative – Page 20
Figure 15: Predictive Margins of BMI (log) with 95% CI, by Reasons for Shopping at
Primary Store
Note: Reference group (not shown) is “other” reason. Graph shows the marginal effects of shopping at a primary
store on the log of BMI after a linear model adjusted for full set of covariates, with robust standard errors clustered at the block group. 95% confidence intervals that cross zero are not statistically significant.
Food APS Research Initiative – Page 21
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Food APS Research Initiative – Page 23
Appendix
Figure A1: Mean and Standard Deviation of County Weekly Store-Level Basket Prices
Note: The weekly Thrifty Food Plan (TFP) store-level basket prices were created from IRI store sales data using
both the Universal Product Code (UPC) and random-weight purchases. For stores that do not report store-level
sales, data from aggregate sales at a Regional Market Area (RMA) level was used. The median price was weighted
by the TFP category weights for a family of four (male 19 to 50, female 19 to 50, child age 6 to 8, child age 9 to
11) for
each TFP category.
Figure A2: Mean and Standard Deviation of County Weekly Low Store-Level Basket
Prices
Note: The weekly Thrifty Food Plan (TFP) store-level basket prices were created from IRI store sales data using
both the Universal Product Code (UPC) and random-weight purchases. For stores that do not report store-level sales, data from aggregate sales at a Regional Market Area (RMA) level was used. To create the “low-cost food basket” measure, the 10th percentile of price for each category was adjusted by the TFP category weights for a family of four (male 19 to 50, female 19 to 50, child age 6 to 8, child age 9 to 11)