Supermarket Shopping and The Food Retail Environment among SNAP Participants

<p>Much of the research on food deserts has focused on the relationship between the food retail environment and nutrition and health outcomes. Intermediary differences in food shopping patterns are often implicitly assumed to drive these relationships (environment hypothetically affects shopping, which hypothetically affects consumption). Research is limited, though, on whether these food shopping discrepancies exist. This article investigates whether a number of food shopping outcomes and the food retail environment are in fact associated and in which kinds of neighborhoods, using the Electronic Benefit Transfer (EBT) records of over 40 000 households receiving Supplemental Nutrition Assistance Program (SNAP) benefits in western Massachusetts. In some, though not all, food retail environments, we find a small but statistically significant negative association between continuous distance and both the percentage of SNAP redemptions spent at supermarkets and the number of benefit-spending trips taken to supermarkets. Nonetheless, SNAP households located in neighborhoods with what would be considered poor access to supermarkets still spent, on average, more than 75% of their redemptions at these retailers, only 5 percentage points lower than households located one block from a supermarket. These results suggest that SNAP participants’ inability to reach healthy food retailers is at most a minor driver of geographic disparities in nutrition and health outcomes.</p

Cohort Derivation.

<p>Flow diagram of subjects included in the study.</p

Inception characteristics of subjects in CATCH and of patients with available serial radiographs.

<p>* No significant differences identified except for anti-CCP (p<0.001); Swollen Joint Count (p<0.001), non-biologic DMARD combination therapy (p<0.01) and Steroid exposure (p = 0.003).</p><p>** Comorbidities recorded include: angina/heart attack, asthma, other heart problems, hypertension, cerebrovascular disease/accidents, anemia, bronchitis/emphysema, hypercholesterolemia, bowel disease, stomach ulcer, liver disease, kidney disease, tuberculosis, cancer, psoriasis, thyroid disease, diabetes, hepatitis, chronic infection, osteoarthritis, lupus, osteoporosis, back/spine problems, fibromyalgia, fractures, depression, mental illness, alcoholism, severe allergies, thromboembolic disease, Parkinson disease, migraines, seizures/epilepsy, gynecologic/prostate problems, HIV, herpes and/or cold sores.</p><p>*** Reported by site investigator; not from central reader</p><p>Results are reported as a Mean (SD) unless otherwise noted. RF, rheumatoid factor; Anti-CCP, anti-cyclic citrullinated peptide; ESR, erythrocyte sedimentation rate; DAS28, disease activity score using a 28-joint count; HAQ Health Assessment Questionnaire; DMARD, disease modifying anti-rheumatic drug</p

Predicted Group Trajectories in Early Rheumatoid Arthritis based on DAS28 with 95% CI (n = 1,586).

<p>Five predicted group trajectories (solid or dashed lines) and 95% confidence interval limits (shaded) are depicted from the group-based trajectory modelling. Percentages reflect the predicted proportion of subjects in each group, which differs marginally from the actual group characterization in the dataset.</p

Treatment by Trajectory Group.

<p>(A) Group Proportion on Methotrexate (≥15 mg), by Visit Month. (B) Group Proportion on Combination Methotrexate and DMARD Therapy, by Visit Month. (C) Group Proportion on Biologics, by Visit Month. (D) Group Proportion on Corticosteroids, by Visit Month.</p