lp heflin stats fall 15' presentation
TRANSCRIPT
Distance to Store in Urban Food Deserts
Leticha Priscilla HeflinNovember 16, 2015
Introduction: In many communities here in the Hampton Roads area there are communities that have been
classified as Food Deserts. Most of the communities classified are shown to be geographically located in low income Urban Areas. The ability of an individual to have
access to fruits and vegetables are essential to the concept of healthy eating and active living. In order to
alleviate and counteract the adverse effects of urban food deserts research must be conducted to determine a
realistic and cost efficient way to effect long term change in Food Desert Communities.
PurposeTo examine the relationship among distance to store, food prices, and obesity (Bonnie Ghosh-Dastidar, 2014).
Food DesertIn the US, areas typically classified as food deserts
are those with a high proportion of low-income residents who areconstrained in their access to affordable, nutritious food because
they live far from a large grocery store and do not have easy accessto transportation
Hypothesis
H0 - There is no direct correlation between access (distance) to supermarkets and health disparities in low-income food deserts in Urban Communities.
HA - Distance to a supermarket may be an underlying cause of obesity and other health disparities in low-income food deserts in Urban Communities.
Statistical Data
The study took place in Petersburg, Pennsylvania which has a population of 32,701
This study is population specific to food deserts.
Sample size: 1, 214 Who were interview and asked questions regarding their age, ethnicity, education, marital status
PopulationFood Desert
Random samplePeople in the low income urban food desert
This study observes the relationship between the distance of a grocery store from the citizen’s living quarters, the SPI, and obesity while also observing the using t-test and chi-square test.
Today the focus is the distance of the grocery store for two body types to determine whether or not the test are significant.
Let’s take a closer look:
DATA DistanceAge (years)18–34 16.3 13.8 18.8 23.6** 14.0**
35–54 31.6 32.3 30.8 38.7** 29.3**
55–74 37.2 38.6 35.9 28.1** 40.1**
Z75 14.9 15.3 14.5 9.6** 16.6**
GenderMale 26.7 29.5* 23.9* 23.0 27.9Female 73.3 70.5* 76.1* 77.1 72.1Race-ethnicityBlack 90.0 89.3 90.6 91.4 89.5Mixed-black 3.5 3.8 3.1 5.5 2.8Other 5.9 6.3 5.6 2.4 7.0Missing 0.7 0.7 0.7 0.7 0.7EducationLess than high school 15.4 16.3 14.5 13.0 16.2High school 37.2 37.6 36.7 36.3 37.4Some college 32.4 31.3 33.4 36.6 31.0College 15.1 14.8 15.3 14.0 15.4Per capita household income ($)o5,000 15.0 16.4 13.3 17.5 14.25,000–9,999 35.9 34.3 37.6 39.7 34.710,000–19,999 30.2 31.5 29.0 26.4 31.5Z20,000 18.9 17.6 20.1 16.4 19.6Marital statusMarried or with partner 17.7 16.6 18.8 23.0** 16.1**
Never married 42.0 40.5 43.5 47.3** 40.4**
Widowed/separated/single 40.3 42.9 37.7 29.7** 43.5**
Household with kids 24.9 22.2* 27.5* 37.3** 20.9**
Own or have access to a car 55.7 50.8** 60.5** 69.4** 51.3**
Table 2. Characteristics of participants (n¼1,214) by distance and price, %All Distance r Median Distance 4 Median SPI r Median SPI 4 Median•Note: Boldface indicates statistical significance. Sample sizes reflect the total number of people who responded to the relevant survey questions (Bonnie Ghosh-Dastidar, 2014).
Sample standard deviation, s= 0.354Variance (sample), s2= 0.125Sample mean= 3.25Population standard deviation, σ2= 0.063N=1, 214Population mean= 3.25
Confidence intervals of ND
nSDSEM
SEMxCI
SEMxCI
58.2%99
96.1%95
Confidence level: 99% Range: 2.339- 4.161Degrees of Freedom: 1, 213
T-Testpopulation mean, µ= 3.25 population standard deviation, σ=0.063sample size = 28sample mean, x = 3.0 sample standard deviation, s= 0.354Null hypothesis: There is no difference between sample mean and population mean.t - statistic = 0.15, p >0.05Accept the Null Hypothesis
Summary✘ Participants who traveled both more or less than the median
distance were observed. For every additional mile traveled to shop, the odds of being obese increased by 5% (p<0.05), but that was There was no significant association between obesity and distance. Healthy food and vegetable access only negates the reality that low income urban food desert community citizen’s ability to afford the cost of such produce.
References
Special thanks to all the people who made and released these awesome resources :
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Bonnie Ghosh-Dastidar, P. D. (2014). Distance to Store, Food Prices, and Obesity in. American Jornal of Preventative Medicine, 587-595.USDA, 2009. Access to Affordable and Nutritious Food: Measuring and UnderstandingFood Deserts and Their Consequences. USDA, Washington, DC.
Walker, R., Fryer, C., Butler, J., Keane, C., Kriska, A., Burke, J., 2011. Factors influencingfood buying practices in residents of a low-income food desert and a lowincomefood oasis. J. Mix. Methods Res. 5 (3), 247e267. http://dx.doi.org/10.1177/1558689811412971.
