Personalized dietary behavioral interventions could be enhanced by understanding factors accounting for individual variability in dietary decisions.
This study was a secondary analysis of the Smart ...Cart randomized controlled trial to determine whether participant characteristics predicted high responsiveness to personalized grocery incentives for purchasing healthy food.
This secondary analysis of a 9-mo crossover study included 192 regular shoppers (86%) from a Rhode Island supermarket. To analyze whether health, behavioral, and/or sociodemographic characteristics predicted responsiveness to a personalized grocery incentive intervention, participants were divided into 3 categories high (n = 47), moderate (n = 50), and unresponsive (n = 95) based on percentage changes in their Grocery Purchase Quality Index scores during the intervention versus control period calculated from sales data. We tested whether participant characteristics, including individual, household, and intervention-related factors, differed across responsiveness groups using ANOVA and whether they predicted the likelihood of being high responsive versus unresponsive or moderate responsive using logistic regression.
Participants had a mean (SD) age of 56.0 (13.8) y and were 89% female. Education, self-reported BMI, income, diet-related medical condition, food insecurity, cooking adequacy, and value consciousness differed across responsiveness categories (P < 0.1). High versus moderate and unresponsive participants increased their percentage of spending on targeted foods (P < 0.0001) and purchased fewer unique items (P = 0.01). In multinomial adjusted models, the odds of being high versus unresponsive or moderate responsive were lower for participants with a BMI (in kg/m
) <25 versus ≥25 (OR: 0.41; 95% CI: 0.19, 0.90) and higher with a diet-related medical condition present (OR: 3.75; 95% CI: 1.20, 11.8). Other characteristics were not associated with responsiveness.
Findings demonstrated that a BMI ≥25 and having a diet-related medical condition within the household predicted high responsiveness to a personalized grocery purchasing intervention, suggesting that personalized dietary interventions may be particularly effective for households with higher health risk. This trial is registered at www.
gov as NCT03748056.
Various diet quality scores are consistently and similarly associated with mortality risk. Emerging evidence suggests that individual diet quality components are differentially associated with ...mortality risk, but it is unclear whether or not modified weights reflective of relative component differences would strengthen mortality associations.
This study examined whether Healthy Eating Index 2015 (HEI-2015) scores with modified (vs standard) component weights are differentially associated with mortality risk.
This was a longitudinal analysis of the National Health and Nutrition Examination Survey III (1988-94) with 23 years of mortality follow-up. The HEI-2015 and modified-weight scores were calculated from one 24-hour recall. The a priori Key Facets HEI was a subset score equivalently weighting fruits, vegetables, whole grains, and seafood and plant proteins. In the least absolute shrinkage and selection operator regression-weighted HEI, components were assigned weights reflecting relative mortality risk associations.
Analyses included 10,789 US adults (aged 20 years and older) who were not pregnant and without prior diabetes, cancer, cardiovascular disease, or chronic kidney disease diagnoses.
All-cause and cardiovascular disease mortality risk were the primary outcomes examined.
Three energy-adjusted HEI scores were assigned to quintiles; covariate-adjusted sex-stratified Cox models with age as the timescale assessed associations between and trends across quintiles of HEI scores and all-cause and cardiovascular disease mortality risk.
Modified-weight HEI scores were associated with 23% to 38% reduced all-cause mortality risk in the highest vs lowest quintile, whereas comparisons were only significant for women (Key Facets P = 0.02 and least absolute shrinkage and selection operator regression-weighted P = 0.001; for men P = 0.06 on both scores), trends across quintiles of modified-weight scores were significant for men and women. The HEI-2015 was not significantly associated with all-cause mortality risk, and none of the scores were associated with cardiovascular disease mortality risk.
Only modified-weight HEI scores were associated with reduced all-cause mortality risk. Findings suggest modified diet quality weighting schemes warrant further examination to determine their replicability.
Refining existing dietary assessment methods to reduce measurement error and facilitate the routine evaluation of dietary quality is essential to inform health policy. Notable advancements in ...technology in the past decade have enhanced the precision and transformation of dietary assessment methods with applications toward both population health and precision nutrition. Within population health, innovative applications of big data including use of automatically collected food purchasing data, quantitative measurement of food environments, and novel, yet simplified dietary quality metrics provide important complementary data to traditional self-report methods. Precision nutrition is similarly advancing with greater use of validated biomarkers for assessing dietary patterns and understanding individual variability in metabolism. Concurrently enhancing our understanding of diet–disease relations at the population health and precision nutrition levels provides tremendous potential to generate evidence needed to advance public health nutrition policy. This commentary highlights the importance of these advances toward progressing the field of dietary assessment and discusses the application of food purchasing data, data analytics, alternative dietary quality metrics, and -omics technology in population and clinical medicine.
Statement of Significance: The present work synthesizes the application of emerging technologies in dietary assessment toward population health and clinical practice. Notably, it highlights how concomitant use of novel technologies enhances traditional methods and helps address their limitations to robustly characterize dietary quality and diet–disease relations.
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
= 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 (
< 0.05). Interactions (
< 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,
= 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,
= 0.046) and Black (48.8 ± 1.5 vs. 53.1 ± 1.4,
= 0.018) but not Hispanic households (54.4 ± 1.0 vs. 52.2 ± 1.2,
= 0.21). Sociodemographic disparities in household HEI-2015 scores were consistent with previous research on individual-level diet quality.
Few longitudinal studies carried out in US adults have evaluated long-term dietary fat intakes and compared them with the national recommendations during the two-decade period when the prevalence of ...obesity and insulin resistance increased substantively. In the present study, we examined trends in the intakes of dietary fats and rich dietary sources of fats in the Framingham Heart Study Offspring Cohort over a 17-year period. The cohort was established in 1971-75 with follow-up examinations being conducted approximately every 4 years. Dietary data were collected using a semi-quantitative FFQ beginning in 1991 (exam 5). We included 2732 adults aged ≥ 25 years with complete dietary data in at least three examinations from 1991 to 2008. Descriptive statistics were generated using SAS version 9.3, and a repeated-measures model was used to examine trends in macronutrient and food intakes using R. Over the 17 years of follow-up, the percentage of energy derived from total fat and protein increased (27·3-29·8% of energy and 16·8-18·0% of energy, respectively) and that derived from carbohydrate decreased (51·0-46·8% of energy; P-trend < 0·001). Increases in the percentage of energy derived from all fat subtypes were observed, except for that derived from trans-fats, which decreased over time (P-trend < 0·001). Trends were similar between the sexes, although women exhibited a greater increase in the percentage of energy derived from saturated fat and less reduction in the percentage of energy derived from trans-fats (P interaction < 0·05). Trends in fat intake were similar across the BMI categories. The number of weekly servings of cheese, eggs, ice cream desserts, nuts, butter and sausages/processed meats increased, whereas the intake of milk, margarine, poultry, confectioneries, chips and breads decreased (P-trend < 0·001). In this cohort of predominantly Caucasian older adults, the percentage of energy derived from dietary fats increased over time, but it remained within the national recommendations of less than 35 % of total energy, on average.
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