Adherence to Federal Dietary Recommendations for Total Fruit Consumption and the Intake of Underconsumed Nutrients: Findings from the National Health and Nutrition Examination Survey, 2015 to 2018.

BACKGROUND: A persistent gap exists between U.S. consumers' actual fruit consumption and Federal dietary recommendations for fruit. Individuals who most deviate from recommendations may be at a greater risk of underconsuming some nutrients. OBJECTIVE: We investigated how widely total fruit consumption varies across adult consumers and whether those who most deviate from recommendations also consume less vitamins A and C, calcium, magnesium, and potassium. The 2020 Dietary Guidelines Advisory Committee has identified each of these nutrients as being underconsumed by the U.S. population in general. METHODS: Data used were from the NHANES, 2015 to 2016 and 2017 to 2018 cycles. For 9832 adults (age >18), we compared their total fruit consumption to recommendations for their age and sex. We also calculated 2015 Healthy Eating Index (HEI-2015) scores. Component scores for Total Fruit and Whole Fruit were subtracted from the total HEI-2015 scores to measure adherence with dietary recommendations outside the fruit group. Two-way and 3-way contingency tables were then used to measure the association between adherence to fruit recommendations and the intake of underconsumed nutrients before and after controlling for adherence to other food group recommendations, respectively. RESULTS: About two-thirds of adults eat less than half the recommended amount of fruit on any given day. Those who routinely unconsume fruit may be at a greater risk of underconsuming potassium and vitamin C. Calcium, magnesium, and vitamin A consumption do not show a consistent relationship with fruit intake relative to recommendations after controlling for diet quality outside the fruit group. CONCLUSIONS: There is much variation across the U.S. population in fruit consumption relative to recommendations. The present study suggests that individuals who deviate the most are at a particularly increased risk of underconsuming vitamin C and potassium.

The SNAP Cycle and Diabetes Management During a One-Time Change in Disbursement Schedule.

OBJECTIVE: The 2018-2019 federal government partial shutdown resulted in a one-time disruption to the usual disbursement schedule of Supplemental Nutrition Assistance Program (SNAP) benefits nationwide. We assessed the relationship between this disruption and hyperglycemia and hypoglycemia medical encounters among beneficiaries with diabetes. RESEARCH DESIGN AND METHODS: To estimate whether the one-time change in benefit disbursement affected the monthly cycle of hyperglycemia or hypoglycemia encounter rates, we used linked administrative Medicaid claims and SNAP disbursement data from West Virginia in a fixed-effects model with interactions between week of the month and the two months of interest-January and February 2019. We controlled for week, month, year, and county effects as well as individual characteristics, and we clustered SEs by individual. RESULTS: We found that the early disbursement of SNAP benefits in January 2019 resulted in a spike in hyperglycemia four times the rate in a typical month. Further, we found a decrease in both hyperglycemia and hypoglycemia in late February. CONCLUSIONS: Our findings suggest that the early distribution of benefits led to a temporary increase in food consumption among West Virginia Medicaid beneficiaries with diabetes. Findings from late February also imply that individuals may have a way to prepare for reduced food resources. These results shed new light on the effects of unexpected changes to the timing of safety net payments as well as an understanding of unintended consequences of government shutdowns.

U.S. Fruit and Vegetable Affordability on the Thrifty Food Plan Depends on Purchasing Power and Safety Net Supports.

The Supplemental Nutrition Assistance Program (SNAP) increases the food purchasing power of lower-income households so that they can better afford a nutritious diet. Benefit amounts are based in part on the cost for a household to follow the Thrifty Food Plan (TFP), a meal pattern designed to meet the Dietary Guidelines for Americans. In October 2021, the U.S. Department of Agriculture (USDA) reformulated the TFP and increased its cost by 21%. However, the TFP still does not account for differences in food prices across the country. This study examines: (1) how geographic variation in food prices affects fruit and vegetable affordability and (2) to what extent raising the cost of the TFP (and therefore the maximum SNAP benefit) has mitigated these effects. We use data on fruit and vegetable prices from the USDA and simulation techniques to create and cost out food baskets with a sufficient quantity and variety of fruits and vegetables for a representative household to satisfy guidelines over one week. We find that the increase in SNAP benefits will increase fruit and vegetable affordability for participating households. However, households facing food prices greater than national average food prices may still face tradeoffs to purchase a balanced diet.

Examining disparities in diet quality between SNAP participants and non-participants using Oaxaca-Blinder decomposition analysis.

Recent studies have reported that SNAP participants have poorer diet quality than non-participants. This study aimed to examine how differences in socio-demographic, household, and health-related measures explain disparities in diet quality between SNAP participants and non-participants using Oaxaca-Blinder decomposition analysis. We analyzed cross-sectional data on 14,331 adult respondents of the National Health and Nutrition Examination Survey (NHANES) 2009 - 2014. To measure diet quality, we applied the Healthy Eating Index (HEI)-2015 to respondents' 24-hour dietary recall data (scale: 0-100 points). We used Oaxaca-Blinder decomposition analysis to determine how much of the disparity in HEI-2015 total score between SNAP participants and non-participants was explained by socio-demographic (e.g., age, race/ethnicity, educational), household (e.g., household size, food security status), and health-related measures (e.g., BMI, smoking status). Analyses performed revealed significant differences in HEI-2015 total score by SNAP participation status (p < 0.001). We found that the total gap in HEI-2015 total score between SNAP participants and income-ineligible non-participants was 6.30 points. Socio-demographic measures alone explained 72.40% of the disparity. All measures together explained 86.31% of the disparity. The total gap between SNAP participants and income-eligible non-participants was 3.24 points. Socio-demographic measures alone explained 35.51% of this disparity while all measures together explained 56.86%. We observed disparities in diet quality between SNAP participants and non-participants. Socio-demographic, household, and health-related measures explained a significant amount of the disparity that existed between SNAP participants and income-ineligible non-participants; they explained less of the disparity between SNAP participants and income-eligible non-participants.

Information sources for obesity prevention policy research: a review of systematic reviews.

BACKGROUND: Systematic identification of evidence in health policy can be time-consuming and challenging. This study examines three questions pertaining to systematic reviews on obesity prevention policy, in order to identify the most efficient search methods: (1) What percentage of the primary studies selected for inclusion in the reviews originated in scholarly as opposed to gray literature? (2) How much of the primary scholarly literature in this topic area is indexed in PubMed/MEDLINE? (3) Which databases index the greatest number of primary studies not indexed in PubMed, and are these databases searched consistently across systematic reviews? METHODS: We identified systematic reviews on obesity prevention policy and explored their search methods and citations. We determined the percentage of scholarly vs. gray literature cited, the most frequently cited journals, and whether each primary study was indexed in PubMed. We searched 21 databases for all primary study articles not indexed in PubMed to determine which database(s) indexed the highest number of these relevant articles. RESULTS: In total, 21 systematic reviews were identified. Ten of the 21 systematic reviews reported searching gray literature, and 12 reviews ultimately included gray literature in their analyses. Scholarly articles accounted for 577 of the 649 total primary study papers. Of these, 495 (76%) were indexed in PubMed. Google Scholar retrieved the highest number of the remaining 82 non-PubMed scholarly articles, followed by Scopus and EconLit. The Journal of the American Dietetic Association was the most-cited journal. CONCLUSIONS: Researchers can maximize search efficiency by searching a small yet targeted selection of both scholarly and gray literature resources. A highly sensitive search of PubMed and those databases that index the greatest number of relevant articles not indexed in PubMed, namely multidisciplinary and economics databases, could save considerable time and effort. When combined with a gray literature search and additional search methods, including cited reference searching and consulting with experts, this approach could help maintain broad retrieval of relevant studies while improving search efficiency. Findings also have implications for designing specialized databases for public health research.