Characteristics Associated With Purchasing Sugar-Sweetened Beverages and Bottled Water Among US Households, 2015.

BACKGROUND: Frequent intake of sugar-sweetened beverages (SSBs) among US adults is a public health concern because it has been associated with increased risks for adverse health outcomes such as obesity, type 2 diabetes, and cardiovascular disease. In contrast, drinking plain water (such as tap, bottled, or unsweetened sparkling water) instead of drinking SSBs might provide health benefits by improving diet quality and helping prevent chronic diseases. However, there is limited information on estimated expenditures on SSBs or bottled water among US households. OBJECTIVE: This study examined differences in SSB and bottled water purchasing according to household and geographic area characteristics and estimated costs spent on purchasing SSB and bottled water from retail stores among a nationally representative sample of US households. DESIGN: This study is a secondary analysis of the 2015 Circana (formerly Information Resources Inc) Consumer Network Panel data, which were merged with the US Department of Agriculture nutrition data using the US Department of Agriculture Purchase-to-Plate Crosswalk-2015 dataset (the latest available version of the Purchase-to-Plate Crosswalk at the time the study began), and the Child Opportunity Index 2.0 data. PARTICIPANTS/SETTINGS: A total of 63,610 households, representative of the contiguous US population, consistently provided food and beverage purchase scanner data from retail stores throughout 2015. EXPLANATORY VARIABLES: The included demographic and socioeconomic variables were household head's age, marital status, highest education level, race and ethnicity of the primary shopper in the household, family income relative to the federal poverty level, and presence of children in the household. In addition, descriptors of households' residential areas were included, such as the county-level poverty prevalence, urbanization, census region, and census tract level Child Opportunity Index. MAIN OUTCOME MEASURES: Annual per capita spending on SSB and bottled water and daily per capita SSB calories purchased. STATISTICAL ANALYSIS: Unadjusted and multivariable adjusted mean values of the main outcome measures were compared by household demographic, socioeconomic, and geographic characteristics using linear regression analysis including Circana's household projection factors. RESULTS: Nearly all households reported purchasing SSBs at least once during 2015 and spent on average $47 (interquartile range = $20) per person per year on SSBs, which corresponded to 211 kcal (interquartile range = 125 kcal) of SSBs per person per day. About seven in 10 households reported purchasing bottled water at least once during 2015 and spent $11 (interquartile range = $5) per person on bottled water per year. Both annual per capita SSB and bottled water spending, and daily per capita SSB calories purchased was highest for households whose heads were between 40 and 59 years of age, had low household income, or lived in poor counties, or counties with a low Child Opportunity Index. Annual per capita spending was also higher for households with never married/widowed/divorced head, or at least 1 non-Hispanic Black head, and households without children, or those living in the South. Daily per capita SSB calorie purchases were highest for households where at least 1 head had less than a high school degree, households with at least 1 Hispanic or married head, and households with children or those living in the Midwest. CONCLUSIONS: These findings suggest that households that had lower socioeconomic status had higher annual per capita spending on SSBs and bottled water and higher daily per capita total SSB calories purchased than households with higher socioeconomic status.

Association Between County-Level Food Retail and Socioeconomic Environment and Nutritional Quality of Household Food Purchases, 2015.

BACKGROUND: About 40 million Americans do not have easy access to affordable nutritious foods. Healthier foods are less likely to be available to those living in rural and/or lower-income communities. OBJECTIVE: The objective of this study was to analyze the association between nutritional quality of household food purchases and county-level food retail environment; county-level demographic, health, and socioeconomic indicators; and household composition, demographic characteristics, and socioeconomic characteristics. DESIGN: This study is a secondary analysis of the 2015 Information Resources Inc Consumer Network panel; Purchase-to-Plate Crosswalk, which links US Department of Agriculture nutrition databases to Information Resources Inc scanner data; County Health Rankings; and the Food Environment Atlas data. PARTICIPANTS AND SETTINGS: A total of 63,285 households, representative of the contiguous US population, consistently provided food purchase scanner data from retail stores throughout 2015. MAIN OUTCOME MEASURES: Nutritional quality of retail food purchases was assessed using the Healthy Eating Index 2015 (HEI-2015). STATISTICAL ANALYSIS: Multivariate linear regression analysis was used to simultaneously test the relationship between the main outcome and household-level demographic and socioeconomic characteristics as well as the county-level demographic, health, socioeconomic, and retail food environment. RESULTS: Household heads who had higher education and households with higher incomes purchased food of better nutritional quality (ie, higher HEI-2015 scores). Also, the association between retail food purchase HEI-2015 scores and the food environment was weak. Higher density of convenience stores was associated with lower retail food purchase nutritional quality for higher-income households and households living in urban counties, whereas low-income households in counties with higher specialty (including ethnic) store density purchased higher nutritional quality food. Both in the full sample and when stratified by household income or county rural vs urban status, no association was found between grocery store, supercenters, fast-food outlets, and full-service restaurant densities and retail food purchase HEI-2015 scores. HEI-2015 scores were negatively correlated with the county average number of mental health days for higher income and urban households. CONCLUSIONS: The study findings suggest that availability of healthier food alone may not improve healthfulness of retail food purchases. Future studies examining the influence of demand-side factors/interventions, such as habits, cultural preferences, nutrition education, and cost/affordability, on household purchasing patterns could provide complementary evidence to inform effective intervention strategies.

Association between the Nutritional Quality of Household At-Home Food Purchases and Chronic Diseases and Risk Factors in the United States, 2015.

Lower diet quality is a leading preventable risk factor for obesity and chronic diseases. This study assesses differences in the nutritional quality of at-home food purchases, using the Healthy Eating Index (HEI)-2015 and its components, among households with and without a member reporting type 2 diabetes (T2D), cardiovascular disease (CVD), obesity, and/or smoking. We use the 2015 IRI Consumer Network nationally representative household food purchase scanner data, combined with the IRI MedProfiler and the USDA's Purchase-to-Plate Crosswalk datasets. For each/multiple condition(s), the difference in mean HEI score adjusted for covariates is tested for equivalence with the respective score against households without any member with the condition(s). The HEI score is higher for households without a member with reported T2D (2.4% higher), CVD (3.2%), obesity (3.3%), none of the three conditions (6.1%, vs. all three conditions), and smoking (10.5%) than for those with a member with the respective condition. Households with a member with T2D score better on the added sugar component than those with no member reporting T2D. We found that the average food purchase quality is lower than the recommended levels, especially for households with at least one member reporting a chronic condition(s).