Associations between Participation in the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) and Maternal Diet Quality.

BACKGROUND: An objective of the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) is to improve maternal diet quality, but its effectiveness remains unclear. Better understanding how WIC participation shapes women's diet quality is crucial given that maternal diet plays a critical role in determining mothers' and children's short- and long-term overall health. OBJECTIVES: This study aimed to compare the diet quality of WIC-participating women to WIC-eligible nonparticipating women and higher-income pregnant and postpartum women using a nationally representative sample. METHODS: This was a cross-sectional analysis of the National Health and Nutrition Examination Survey (NHANES) 2011-2018 cycles. Women aged 20 to 44 with at least one 24-h recall and complete data on pregnancy and postpartum status and WIC participation were included (n = 626). Diet quality was evaluated using the Healthy Eating Index-2015 (HEI-2015). Multivariable Tukey-adjusted linear models were used to compare HEI-2015 total and component scores between groups. Models were adjusted for age, pregnancy and postpartum status, breastfeeding status, race and ethnicity, and food security. RESULTS: Most women were postpartum and not pregnant (75%), nonbreastfeeding (60%), identified as non-Hispanic White (58%), and food secure (64%). WIC participants, WIC-eligible nonparticipants, and income-ineligible women had mean Total HEI-2015 scores of 52.7 (95% confidence interval [CI]: 50.6, 54.8), 54.2 (95% CI: 51.6, 56.7), and 55.0 (95% CI: 51.8, 58.2), respectively. There were no differences between groups for total and most component scores. Income-ineligible women had better Fatty Acids scores (5.7; 95% CI: 5.0, 6.4) than WIC participants (4.7; 95% CI: 4.1, 5.3; P < 0.05). WIC-eligible nonparticipants had better Refined Grains scores (6.0; 95% CI: 5.3, 6.6) than WIC participants (5.0; 95% CI: 4.4, 5.6; P < 0.05). CONCLUSIONS: Overall diet quality was similar across WIC and income groups. Lower HEI-2015 component scores for WIC participants compared with WIC-eligible nonparticipants warrant further exploration. Research evaluating WIC's impact on maternal diet quality is needed to ensure continued support for low-income women's health.

Rapid Diet Assessment Screening Tools for Cardiovascular Disease Risk Reduction Across Healthcare Settings: A Scientific Statement From the American Heart Association.

It is critical that diet quality be assessed and discussed at the point of care with clinicians and other members of the healthcare team to reduce the incidence and improve the management of diet-related chronic disease, especially cardiovascular disease. Dietary screening or counseling is not usually a component of routine medical visits. Moreover, numerous barriers exist to the implementation of screening and counseling, including lack of training and knowledge, lack of time, sense of futility, lack of reimbursement, competing demands during the visit, and absence of validated rapid diet screener tools with coupled clinical decision support to identify actionable modifications for improvement. With more widespread use of electronic health records, there is an enormous unmet opportunity to provide evidence-based clinician-delivered dietary guidance using rapid diet screener tools that must be addressed. In this scientific statement from the American Heart Association, we provide rationale for the widespread adoption of rapid diet screener tools in primary care and relevant specialty care prevention settings, discuss the theory- and practice-based criteria of a rapid diet screener tool that supports valid and feasible diet assessment and counseling in clinical settings, review existing tools, and discuss opportunities and challenges for integrating a rapid diet screener tool into clinician workflows through the electronic health record.

Sociodemographic Differences in the Dietary Quality of Food-at-Home Acquisitions and Purchases among Participants in the U.S. Nationally Representative Food Acquisition and Purchase Survey (FoodAPS).

Insufficient research has explored whether sociodemographic differences in self-reported, individual-level diet quality are similarly reflected by grocery purchase quality. This cross-sectional analysis of n = 3961 U.S. households from the nationally representative Food Acquisition and Purchase Survey (FoodAPS) compared Healthy Eating Index (HEI)-2015 scores from 1 week of food-at-home acquisitions across self-reported demographic factors (race/ethnicity, Supplemental Nutrition Assistance Program (SNAP) participation, food security, and household-level obesity status). Multivariable-adjusted, survey-weighted regression models compared household HEI-2015 scores across sociodemographic groups. Respondents were primarily White and female, with a mean age of 50.6 years, 14.0% were food insecure, and 12.7% were SNAP-participating. Mean HEI-2015 scores were 54.7; scores differed across all sociodemographic exposures (p < 0.05). Interactions (p < 0.1) were detected between SNAP participation and (1) food insecurity and (2) household-level obesity, and race/ethnicity and (1) household-level obesity. HEI-2015 scores were higher among food secure, non-SNAP households than among food insecure, SNAP-participating households (53.9 ± 0.5 vs. 50.3 ± 0.7, p = 0.007); non-SNAP households without obesity had significantly higher HEI-2015 scores than other households. Household-level obesity was associated with lower HEI-2015 scores in White (50.8 ± 0.5 vs. 52.5 ± 0.7, p = 0.046) and Black (48.8 ± 1.5 vs. 53.1 ± 1.4, p = 0.018) but not Hispanic households (54.4 ± 1.0 vs. 52.2 ± 1.2, p = 0.21). Sociodemographic disparities in household HEI-2015 scores were consistent with previous research on individual-level diet quality.

Evaluating the effect of individually-targeted food incentives on grocery purchases: The smart cart study protocol for a randomized controlled cross-over trial.

BACKGROUND/AIMS: Health stakeholders are interested in the promise of healthy food incentives to improve dietary quality. The Smart Cart Study tested whether targeting healthful food incentives based on customer preferences and purchase history was effective for improving grocery purchase quality. DESIGN: Randomized controlled crossover design of 224 adults who shopped at an independent supermarket for ≥50% of their groceries, participated in the store's loyalty program, and completed validated diet and sociodemographic/behavioral questionnaires. Participants were randomized using 1:1 blocked randomization; all participants received a 5% discount on their purchases with their loyalty card. For the first 13-weeks, the intervention group received individually-targeted weekly coupons (valued up to $10) with brief nutrition education to improve grocery purchase quality. The study team developed healthy food coupons, and the study algorithm allocated targeted coupons to participants' loyalty cards using purchase history, dietary preferences/allergies, and baseline diet quality. Control participants received weekly untargeted nutrition education and occasional generic coupons. Following a 2-4 week washout period, the two groups crossed over. The primary study outcomes were purchases of targeted products and grocery purchase quality measured using the validated Grocery Purchase Quality Index-2016; the study was powered to detect a minimum 3% difference in purchase quality. CONCLUSIONS: The Smart Cart Study tested a novel application of automated individually-targeted marketing using customer purchase history, dietary quality, and preferences to identify and deliver targeted incentives to improve grocery purchase quality. Future research could scale this program through collaboration between multiple stakeholders, including supermarkets, workplace wellness initiatives and insurance companies.

Socio-economic and racial prenatal diet quality disparities in a national US sample.

OBJECTIVE: To examine differences in prenatal diet quality by socio-economic status (SES) and race/ethnicity. DESIGN: A secondary, cross-sectional analysis. Race and SES were self-reported prenatally; SES was categorized into four groups: high-income, middle-income and low-income WIC (Special Supplemental Nutrition Program for Women, Infants, and Children) participant/non-participant. The Alternative Healthy Eating Index for Pregnancy (AHEI-P) measured diet quality, including four moderation and nine adequacy components (higher scores = healthier diet). Generalized linear models adjusted for covariates and post hoc testing with Tukey adjustment compared AHEI-P scores between groups, using a threshold of P < 0·05. SETTING: Infant Feeding Practices Study II, conducted in a national US convenience cohort. PARTICIPANTS: Women in their third trimester (n 1322) with dietary history. RESULTS: Participants were of 28·9 (se 5·6) years on average and predominantly non-Hispanic White (84 %); approximately one-third participated in WIC and 17 % were high-income. The mean AHEI-P score was 61·7 (se 10·8) of 130 points. High-income women had higher total (62·4 (se 1·0)) and moderation component AHEI-P scores than middle-income (60·1 (se 0·8), P = 0·02), low-income WIC participants (58·3 (se 0·8), P < 0·0001) and non-participants (58·9 (se 0·9), P = 0·001). Non-Hispanic Black participants had lower total (57·8 (se 1·4)) and adequacy scores than Other races (i.e. neither non-Hispanic Black nor White, 62·1 (se 0·9), P = 0·02). CONCLUSIONS: Disparities in prenatal diet quality were observed, with non-Hispanic Black women, low-/middle-income and WIC participants having lower diet quality. However, interventions are needed to improve prenatal diet quality broadly among US women.

Maternal vegetable intake during and after pregnancy.

BACKGROUND: Improved understanding of vegetable intake changes between pregnancy and postpartum may inform future intervention targets to establish healthy home food environments. Therefore, the goal of this study was to explore the changes in vegetable intake between pregnancy and the postnatal period and explore maternal and sociodemographic factors that are associated with these changes. METHODS: We examined sociodemographic, dietary, and health characteristics of healthy mothers 18-43y from the prospective Infant Feeding Practices II cohort (n = 847) (2005-2012). Mothers completed a modified version of the diet history questionnaire, a food-frequency measure, developed by the National Cancer Institute. We created four categories of mothers, those that were: meeting vegetable recommendations post- but not prenatally (n = 121; improved intake), not meeting vegetable recommendations during pregnancy and postnatally (n = 370; stable inadequate), meeting recommendations pre- but not postnatally (n = 123; reduced intake), and meeting recommendations at both time points (n = 233; stable adequate). To make our results more relevant to public health recommendations, we were interested in comparing the improved vegetable intake group vs. stable inadequate vegetable intake group, as well as those that reduced their vegetable intake compared to the stable adequate vegetable intake group. Separate multivariable-adjusted logistic regression were used to examine sociodemographic predictors of improved vs. stable inadequate and reduced vs. stable adequate vegetable intake. RESULTS: Women with improved vegetable intake vs. stable inadequate smoked fewer cigarettes while women with reduced vegetable intake vs. stable adequate were more likely to experience less pregnancy weight gain. In adjusted models, employed women had greater odds of reduced vegetable intake (OR = 1.64 95% CI 1.14-2.36). In exploratory analyses, employment was associated with greater odds of reduced vegetable intake among low-income (OR = 1.79; 95% CI 1.03-3.1), but not higher income women (OR = 1.31; 95% CI 0.94-1.84). After further adjustment for paid maternity leave, employment was no longer associated with vegetable intake among lower income women (OR: 1.53; 95% CI: 0.76-3.05). CONCLUSIONS: More women with reduced vs. stable adequate vegetable intake were lower income and worked full time. Improved access to paid maternity leave may help reduce disparities in vegetable quality between lower and higher income women.

Geographic Differences in the Dietary Quality of Food Purchases among Participants in the Nationally Representative Food Acquisition and Purchase Survey (FoodAPS).

Objective grocery transactions may reflect diet, but it is unclear whether the diet quality of grocery purchases mirrors geographic and racial/ethnic disparities in diet-related diseases. This cross-sectional analysis of 3961 households in the nationally representative Food Acquisition and Purchase Survey evaluated geographic and racial/ethnic disparities in grocery purchase quality. Respondents self-reported demographics and recorded purchases over 7 days; the Healthy Eating Index (HEI) 2015 assessed diet quality. Survey-weighted multivariable-adjusted regression determined whether there were geographic and racial/ethnic differences in HEI-15 scores. Respondents were, on average, 50.6 years, non-Hispanic white (NHW) (70.3%), female (70.2%), and had attended some college (57.8%). HEI-15 scores differed across geographic region (p < 0.05), with the highest scores in the West (57.0 ± 0.8) and lowest scores in the South (53.1 ± 0.8), and there was effect modification by race/ethnicity (p-interaction = 0.02). Regionally, there were diet disparities among NHW and non-Hispanic black (NHB) households; NHWs in the South had HEI-15 scores 3.2 points lower than NHWs in the West (p = 0.003). Southern NHB households had HEI-15 scores 8.1 points lower than Western NHB households (p = 0.013). Racial/ethnic disparities in total HEI-15 by region existed in the Midwest and South, where Hispanic households in the Midwest and South had significantly lower diet quality than NHW households. Heterogeneous disparities in the diet quality of grocery purchases by region and race/ethnicity necessitate tailored approaches to reduce diet-related disease.

Processing level and diet quality of the US grocery cart: is there an association?

OBJECTIVE: The majority of groceries purchased by US households are industrially processed, yet it is unclear how processing level influences diet quality. We sought to determine if processing level is associated with diet quality of grocery purchases. DESIGN: We analysed grocery purchasing data from the National Household Food Acquisition and Purchase Survey 2012-2013. Household grocery purchases were categorized by the NOVA framework as minimally processed, processed culinary ingredients, processed foods or ultra-processed foods. The energy share of each processing level (percentage of energy; %E) and Healthy Eating Index-2015 (HEI-2015) component and total scores were calculated for each household's purchases. The association between %E from processed foods and ultra-processed foods, respectively, and HEI-2015 total score was determined by multivariable linear regression. Foods purchased by households with the highest v. lowest ultra-processed food purchases and HEI-2015 total score <40 v. ≥60 were compared using linear regression. SETTING: USA. PARTICIPANTS: Nationally representative sample of 3961 households. RESULTS: Processed foods and ultra-processed foods provided 9·2 (se 0·3) % and 55·8 (se 0·6) % of purchased energy, respectively. Mean HEI-2015 score was 54·7 (se 0·4). Substituting 10 %E from minimally processed foods and processed culinary ingredients for ultra-processed foods decreased total HEI-2015 score by 1·8 points (ß = -1·8; 95 % CI -2·0, -1·5). Processed food purchases were not associated with diet quality. Among households with high ultra-processed food purchases, those with HEI-2015 score <40 purchased less minimally processed plant-foods than households with HEI-2015 score ≥60. CONCLUSIONS: Increasing purchases of minimally processed foods, decreasing purchases of ultra-processed foods and selecting healthier foods at each processing level may improve diet quality.

Staple Food Item Availability among Small Retailers in Providence, RI.

Inventory requirements for authorized Supplemental Nutrition Assistance Program (SNAP) retailers have undergone several revisions to increase the availability of healthful foods. A proposed rule of 84 staple food items was not implemented due to concerns that stores would not withstand this expansion, resulting in a final rule requiring 36 items. This study used the Food Access Research Atlas data to characterize food provisions in 30 small retailers in areas with high and low proportions of SNAP and racial minority residents in Providence, Rhode Island (RI). Stores were assessed with an audit instrument to tally variety, perishability, and depth of stock of four staple food categories. Descriptive, analysis of variance, and chi-square analyses were performed. Across stores, 80% were compliant with the final rule, but 66.7% would need to expand their offerings to meet the proposed rule. Mean dairy variety was lowest among all categories (p < 0.05). Most stores met the perishability (92.3%) and depth-of-stock requirements (96.1%) under both rules. No difference was detected between areas with high and low proportions of SNAP and racial minority residents. Future expansion of requirements may increase healthful food availability without imposing undue burdens on retailers in Providence, RI, excluding increased requirements for dairy variety.

Targeted retail coupons influence category-level food purchases over 2-years.

BACKGROUND: Targeted coupons strongly influence purchasing behavior and may represent an innovative approach for improving dietary behaviors. METHODS: The retail analytics firm, Dunnhumby, provided secondary retail data containing grocery transactions, targeted coupon exposures, and coupon use for 2500 households over 2-years. The USDA Quarterly At-Home Food Purchasing Database was used to categorize individual foods into 52 categories and combined into 12 food groups. Mixed effects linear models estimated the difference-in-difference effects of coupon exposure on category-level purchase rate/wk. pre- and post-campaign; models also tested effect modification by food category. RESULTS: Category-level food purchases significantly increased post-campaign. Mean (SD) food purchases/wk. Among exposed households (17.34 (13.08) units/wk) vs. unexposed households (3.75 (4.59) units/wk) were higher (p < 0.001). Difference-in-difference effects of coupon exposure showed a higher increase in purchase rate among exposed vs. unexposed households (5.73 vs. 0.67, p < 0.001). Food category significantly modified the association between coupon exposure and coupon campaign. Category-level purchase rate among exposed vs. unexposed households was relatively higher in less healthful (e.g. convenience foods) vs. more healthful categories (e.g. nuts) with a 1.17 unit/wk. increase in convenience foods purchase (p < 0.001) vs. a 0.03 unit/wk. increase in nuts (p < 0.001). Exploratory analyses suggested that price elasticity of food categories for targeted coupons (1.02-2.81) was higher than previous estimates for untargeted coupons. CONCLUSION: Across food categories, coupon exposure increased category-level purchase rate, with a relatively larger effect size for less healthful than more healthful categories. Promising results from this preliminary study suggest that experimental research is warranted to determine whether targeting with the explicit purpose of improving dietary quality can more effectively influence diet, and whether it can do so more cost effectively.