Lower household income has been consistently associated with poorer diet quality. Household food purchases may be an important intervention target to improve diet quality among low income ...populations. Associations between household income and the diet quality of household food purchases were examined.
Food purchase receipt data were collected for 14 days from 202 urban households participating in a study about food shopping. Purchase data were analyzed using NDS-R software and scored using the Healthy Eating Index 2010 (HEI 2010). HEI total and subscores, and proportion of grocery dollars spent on food categories (e.g. fruits, vegetables, sugar sweetened beverages) were examined by household income-to-poverty ratio.
Compared to lower income households, after adjusting for education, marital status and race, higher income households had significantly higher HEI total scores (mean sd = 68.2 13.3 versus 51.6 13.9, respectively, adjusted p = 0.05), higher total vegetable scores (mean sd = 3.6 1.4 versus 2.3 1.6, respectively, adjusted p < .01), higher dairy scores (mean sd = 5.6 3.0 versus 5.0 3.3, p = .05) and lower proportion of grocery dollars spent on frozen desserts (1% .02 versus 3% .07, respectively, p = .02).
Lower income households purchase less healthful foods compared with higher income households. Food purchasing patterns may mediate income differences in dietary intake quality.
ClinicalTrials.gov identifier: NCT02073643.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Food purchasing is considered a key mediator between the food environment and eating behavior, and food purchasing patterns are increasingly measured in epidemiologic and intervention studies. ...However, the extent to which food purchases actually reflect individuals' dietary intake has not been rigorously tested. This study examined cross-sectional agreement between estimates of diet quality and nutrient densities derived from objectively documented household food purchases and those derived from interviewer-administered 24-h diet recalls. A secondary aim was to identify moderator variables associated with attenuated agreement between purchases and dietary intake.
Primary household food shoppers (N = 196) collected and annotated receipts for all household food and beverage purchases (16,356 total) over 14 days. Research staff visited participants' homes four times to photograph the packaging and nutrition labels of each purchased item. Three or four multiple-pass 24-h diet recalls were performed within the same 14-d period. Nutrient densities and Healthy Eating Index-2010 (HEI-2010) scores were calculated from both food purchase and diet recall data.
HEI-2010 scores derived from food purchases (median = 60.9, interquartile range 49.1-71.7) showed moderate agreement (ρc = .57, p < .0001) and minimal bias (-2.0) with HEI-2010 scores from 24-h recalls (median = 60.1, interquartile range 50.8-73.9). The degree of observed bias was unrelated to the number of food/beverage purchases reported or participant characteristics such as social desirability, household income, household size, and body mass. Concordance for individual nutrient densities from food purchases and 24-h diet recalls varied widely from ρc = .10 to .61, with the strongest associations observed for fiber (ρc = .61), whole fruit (ρc = .48), and vegetables (ρc = .39).
Objectively documented household food purchases yield an unbiased and reasonably accurate estimate of overall diet quality as measured through 24-h diet recalls, but are generally less useful for characterizing dietary intake of specific nutrients. Thus, some degree of caution is warranted when interpreting food purchase data as a reflection of diet in epidemiological and clinical research. Future work should examine agreement between food purchases and nutritional biomarkers.
ClinicalTrials.gov, NCT02073643 . Retrospectively registered.
There is great interest in reshaping the Supplemental Nutrition Assistance Program (SNAP) so that it better supports family nutrition, and an array of program changes have been proposed.We note the ...importance of considering the unique needs of rural SNAP participants when considering and implementing these changes. We also describe the SNAP-related needs and challenges unique to rural SNAP participants, and through this lens we discuss changes to SNAP that have been proposed and special considerations related to each. The special considerations we identified include allowing canned, frozen, and dried fruits and vegetables as eligible items in financial incentive programs in rural areas; changing direct education programming to address transportation-related barriers many rural families face in attending in-person classes; and supporting rigorous research to evaluate the potential benefits and unintended consequences of proposed program changes for which scant high-quality evaluation data exist.Evaluation studies should include rural SNAP participants so that effects in this important population group are known.
Abstract Background Snacking behaviors have been linked with higher energy intake and excess weight. However, results have been inconsistent. In addition, few data are available on the extent to ...which snacking affects diet quality. Objective This study describes snacking behaviors, including total snacking energy, frequency, time of day, and percentage of snacking energy intake by food groups, and their associations with diet quality and body mass index (BMI; calculated as kg/m2 ). Design Snacking behaviors and dietary intake were examined cross-sectionally among 233 adults participating in a community-based worksite nutrition intervention from September 2010 through February 2013. Three telephone-administered 24-hour dietary recalls were collected (2 weekdays; 1 weekend day). Diet quality was characterized by the Healthy Eating Index 2010 and BMI was computed using measured height and weight. Setting The setting was a large metropolitan medical complex in Minneapolis, Minnesota. Main outcome measures Outcome measures included diet quality and BMI. Statistical analyses General linear regression models were used to examine associations between each of the snacking behaviors as independent variables, and diet quality and BMI as dependent variables. Results Percent of snacking energy from fruit and juice (β=.13; P =0.001) and nuts (β=.16; P =0.008) were significantly positively associated with diet quality. Percent of snacking energy from desserts and sweets (β=−.16; P <0.001) and sugar-sweetened beverages (β=−.22; P =0.024) were significantly inversely associated. Percent of snacking energy from vegetables (β=−.18; P =0.044) was significantly associated with lower BMI. Percent snacking energy from desserts and sweets was significantly associated with a higher BMI (β=.04; P =0.017). Conclusions Snack food choices, but not total energy from snacks, frequency, or time of day, were significantly associated with diet quality and BMI.
• Purpose of review is to spark integrative thinking in the area of eating behaviors. • Eating behavior constructs are reviewed related to energy intake, body mass index and weight gain. • Positive ...associations with body mass index; fewer reported with energy intake or food choices. • Integrative conceptual model needed to highlight environment-individual interaction.
The purpose of this review is to spark integrative thinking in the area of eating behaviors by critically examining research on exemplary constructs in this area. The eating behaviors food responsiveness, enjoyment of eating, satiety responsiveness, eating in the absence of hunger, reinforcing value of food, eating disinhibition and impulsivity/self-control are reviewed in relation to energy intake, body mass index and weight gain over time. Each of these constructs has been developed independently, and little research has explored the extent to which they overlap or whether they differentially predict food choices, energy intake and weight gain in the naturalistic environment. Most available data show positive cross-sectional associations with body mass index, but fewer studies report associations with energy intake or food choices. Little prospective data are available to link measures of eating behaviors with weight gain. Disinhibition has the largest and most consistent body of empirical data that link it prospectively with weight gain. An overarching conceptual model to integrate the conceptual and empirical research base for the role of eating behavior dimensions in the field of obesity research would highlight potential patterns of interaction between individual differences in eating behaviors, specific aspects of the individual’s food environment and individual variation in state levels of hunger and satiety.
Eating away from home has increased in prevalence among US adults and now comprises about 50% of food expenditures. Calorie labeling on chain restaurant menus is one specific policy that has been ...proposed to help consumers make better food choices at restaurants. The present review evaluates the available empirical literature on the effects of calorie information on food choices in restaurant and cafeteria settings.
Computer-assisted searches were conducted using the PUBMED database and the Google Scholar world wide web search engine to identify studies published in peer-review journals that evaluated calorie labeling of cafeteria or restaurant menu items. Studies that evaluated labeling only some menu items (e.g. low calorie foods only) were excluded from the review since the influence of selective labeling may be different from that which may be expected from comprehensive labeling.
Six studies were identified that met the selection criteria for this review. Results from five of these studies provide some evidence consistent with the hypothesis that calorie information may influence food choices in a cafeteria or restaurant setting. However, results from most of these studies suggest the effect may be weak or inconsistent. One study found no evidence of an effect of calorie labeling on food choices. Each of the studies had at least one major methodological shortcoming, pointing toward the need for better designed studies to more rigorously evaluate the influence of point-of-purchase calorie labeling on food choices.
More research is needed that meets minimum standards of methodological quality. Studies need to include behavioral outcomes such as food purchase and eating behaviors. Also, studies need to be implemented in realistic settings such as restaurants and cafeterias.
Pricing Effects on Food Choices French, Simone A.
The Journal of nutrition,
03/2003, Letnik:
133, Številka:
3
Journal Article
Recenzirano
Odprti dostop
Individual dietary choices are primarily influenced by such considerations as taste, cost, convenience and nutritional value of foods. The current obesity epidemic has been linked to excessive ...consumption of added sugars and fat, as well as to sedentary lifestyles. Fat and sugar provide dietary energy at very low cost. Food pricing and marketing practices are therefore an essential component of the eating environment. Recent studies have applied economic theories to changing dietary behavior. Price reduction strategies promote the choice of targeted foods by lowering their cost relative to alternative food choices. Two community-based intervention studies used price reductions to promote the increased purchase of targeted foods. The first study examined lower prices and point-of-purchase promotion on sales of lower fat vending machine snacks in 12 work sites and 12 secondary schools. Price reductions of 10%, 25% and 50% on lower fat snacks resulted in an increase in sales of 9%, 39% and 93%, respectively, compared with usual price conditions. The second study examined the impact of a 50% price reduction on fresh fruit and baby carrots in two secondary school cafeterias. Compared with usual price conditions, price reductions resulted in a four-fold increase in fresh fruit sales and a two-fold increase in baby carrot sales. Both studies demonstrate that price reductions are an effective strategy to increase the purchase of more healthful foods in community-based settings such as work sites and schools. Results were generalizable across various food types and populations. Reducing prices on healthful foods is a public health strategy that should be implemented through policy initiatives and industry collaborations. J. Nutr. 133: 841S–843S, 2003.
To prospectively examine the bidirectional relationship between parental feeding practices (eg, instrumental feeding, encouragement to eat) and child eating behaviors (eg, food responsiveness, ...emotional eating) in low-income, ethnically diverse preschool children over a 3-year period.
Parent/child (age 2-4 years at baseline) pairs (n = 222 non-Hispanics; n = 312 Hispanics) participated in NET-Works (Now Everybody Together for Amazing and Healthful Kids), a randomized controlled trial carried out in community and in-home settings in urban areas of Minnesota. Data were collected at baseline and 12, 24, and 36 months. The present study is a secondary data analysis using cross-lagged models to identify bidirectional associations between parental feeding practices and child eating behaviors.
Three models showed significant cross-lagged effects (P < .05): model 1, parental instrumental feeding influencing later child food responsiveness; model 2, parental emotional feeding influencing later child food responsiveness; and model 3, parental emotional feeding influencing later child eating satiety. Model 1 showed significant bidirectional temporal paths, whereas models 2 and 3 showed significant unidirectional temporal paths from parental feeding practices to child eating behaviors.
Parental instrumental and emotional feeding practices prospectively influence child food responsiveness and satiety. This study demonstrates causal temporality between parental feeding practices and child eating behaviors. Heath care providers may want to use findings regarding parent feeding practices as part of their anticipatory guidance during well-child visits with parents of preschoolers.
One way in which to modify food purchases is to change prices through tax policy, subsidy policy, or both. We reviewed the growing body of experimental research conducted in the laboratory and in the ...field that investigates the following: the extent to which price changes influence purchases of targeted and nontargeted foods, total energy, or macronutrients purchased; the interaction of price changes with adjunctive interventions; and moderators of sensitivity to price changes. After a brief overview of economic principles and observational research that addresses these issues, we present a targeted review of experimental research. Experimental research suggests that price changes modify purchases of targeted foods, but research on the overall nutritional quality of purchases is mixed because of substitution effects. There is mixed support for combining price changes with adjunctive interventions, and there are no replicated findings on moderators to price sensitivity in experiments. Additional focused research is needed to better inform food policy development with the aim of improving eating behavior and preventing obesity.
Objective
This study examined whether the efficacy of a standard‐of‐care pediatric obesity treatment was affected by the COVID‐19 pandemic.
Methods
Analyses leveraged data from an ongoing pediatric ...obesity treatment trial involving 230 lower‐income, urban children aged 6 to 12 years. Mixed‐effects regression models compared children who participated in a 12‐month weight‐management intervention before versus during the COVID‐19 pandemic on change from baseline in BMI z score (ΔzBMI) at 3, 6, 9, and 12 months.
Results
The observed pattern of ΔzBMI was significantly different before versus during the pandemic (χ2 = 22.73, p < 0.0001). Children treated before the pandemic maintained an average weight loss of −0.06 ΔzBMI at 12 months, whereas children treated during the pandemic steadily gained weight over time, averaging a net gain of 0.11 ΔzBMI at 12 months (χ2 = 34.99, p < 0.0001). Treatment session completion did not differ before versus during the pandemic (60.4% vs. 55.7%, respectively; p = 0.30) or account for differences in ΔzBMI.
Conclusions
Similar reductions in intervention efficacy may be anticipated in other pediatric obesity treatment trials conducted during the COVID‐19 pandemic. Many families that have struggled with managing their child’s weight during this period may need encouragement to continue engaging in structured weight management as society renormalizes.
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