The use of low-calorie sweeteners is associated with self-reported prior intent to lose weight in a representative sample of US adults.

BACKGROUND: Low-calorie sweeteners (LCSs) are said to be a risk factor for obesity and diabetes. Reverse causality may be an alternative explanation. METHODS: Data on LCS use, from a single 24-h dietary recall, for a representative sample of 22 231 adults were obtained from 5 cycles of the National Health and Nutrition Examination Survey (1999-2008 NHANES). Retrospective data on intent to lose or maintain weight during the prior 12-months and 10-year weight history were obtained from the weight history questionnaire. Objectively measured heights and weights were obtained from the examination. Primary analyses evaluated the association between intent to lose/maintain weight and use of LCSs and specific LCS product types using survey-weighted generalized linear models. We further evaluated whether body mass index (BMI) may mediate the association between weight loss intent and use of LCSs. The association between 10-year weight history and current LCS use was evaluated using restricted cubic splines. RESULTS: In cross-sectional analyses, LCS use was associated with a higher prevalence of obesity and diabetes. Adults who tried to lose weight during the previous 12 months were more likely to consume LCS beverages (prevalence ratio=1.64, 95% confidence interval (CI) 1.54-1.75), tabletop LCS (prevalence ratio=1.68, 95% CI 1.47-1.91) and LCS foods (prevalence ratio=1.93, 95% CI 1.60-2.33) as compared with those who did not. In mediation analyses, BMI only partially mediated the association between weight control history and the use of LCS beverages, tabletop LCS, but not LCS foods. Current LCS use was further associated with a history of prior weight change (for example, weight loss and gain). CONCLUSIONS: LCS use was associated with self-reported intent to lose weight during the previous 12 months. This association was only partially mediated by differences in BMI. Any inference of causality between attempts at weight control and LCS use is tempered by the cross-sectional nature of these data and retrospective self-reports of prior weight loss/maintenance intent.

Validating self-reported food expenditures against food store and eating-out receipts.

BACKGROUND/OBJECTIVES: To compare objective food store and eating-out receipts with self-reported household food expenditures. SUBJECTS/METHODS: The Seattle Obesity Study II was based on a representative sample of King County adults, Washington, USA. Self-reported household food expenditures were modeled on the Flexible Consumer Behavior Survey (FCBS) Module from 2007 to 2009 National Health and Nutrition Examination Survey (NHANES). Objective food expenditure data were collected using receipts. Self-reported food expenditures for 447 participants were compared with receipts using paired t-tests, Bland-Altman plots and κ-statistics. Bias by sociodemographics was also examined. RESULTS: Self-reported expenditures closely matched with objective receipt data. Paired t-tests showed no significant differences between receipts and self-reported data on total food expenditures, expenditures at food stores or eating out. However, the highest-income strata showed weaker agreement. Bland-Altman plots confirmed no significant bias across both methods-mean difference: 6.4; agreement limits: -123.5 to 143.4 for total food expenditures, mean difference 5.7 for food stores and mean difference 1.7 for eating out. The κ-statistics showed good agreement for each (κ 0.51, 0.41 and 0.49 respectively. Households with higher education and income had significantly more number of receipts and higher food expenditures. CONCLUSIONS: Self-reported food expenditures using NHANES questions, both for food stores and eating out, serve as a decent proxy for objective household food expenditures from receipts. This method should be used with caution among high-income populations, or with high food expenditures. This is the first validation of the FCBS food expenditures question using food store and eating-out receipts.

Socio-demographic correlates and trends in low-calorie sweetener use among adults in the United States from 1999 to 2008.

BACKGROUND/OBJECTIVES: Replacing added sugars in beverages and foods with low-calorie sweeteners (LCSs) is one strategy to reduce calories and manage body weight. There are few studies on LCS consumption by product category and by consumer socio-demographic status. SUBJECTS/METHODS: Data for a representative sample of 22 231 adults were obtained from five cycles of the National Health and Nutrition Examination Survey (1999-2008 NHANES). A single 24-h recall was used to identify consumers of LCS beverages, foods and tabletop sweeteners. Time-trend analyses were conducted for total LCS consumption and for LCS beverages. RESULTS: Approximately 30% of US adults consumed some type of LCS, with 19.5% consuming LCS beverages, 11.4% consuming tabletop LCS and 4.6% consuming LCS foods. LCS consumption by product category peaked at different ages, with older adults more likely to consume tabletop LCS and LCS foods. In age-adjusted analyses, LCS consumers in every product category were more likely to be women, 45-65 years old, non-Hispanic whites, US-born adults, college graduates and with higher household incomes. Predictors of LCS consumption were not altered upon adjustment for body mass index and diabetes status. LCS consumption from all sources and from LCS beverages increased between 1999 and 2008. CONCLUSIONS: LCS use was more common among populations with a lower burden of obesity and related chronic disease, specifically, non-Hispanic whites and those with more education/higher incomes. The reasons for this observed paradox are complex and merit additional research.

The relation of potassium and sodium intakes to diet cost among U.S. adults.

The 2010 Dietary Guidelines recommended that Americans increase potassium and decrease sodium intakes to reduce the burden of hypertension. One reason why so few Americans meet the recommended potassium or sodium goals may be perceived or actual food costs. This study explored the monetary costs associated with potassium and sodium intakes using national food prices and a representative sample of US adults. Dietary intake data from the 2001-2002 National Health and Nutrition Examination Survey were merged with a national food prices database. In a population of 4744 adults, the association between the energy-adjusted sodium and potassium intakes, and the sodium-to-potassium ratio (Na:K) and energy-adjusted diet cost was evaluated. Diets that were more potassium-rich or had lower Na:K ratios were associated with higher diet costs, while sodium intakes were not related to cost. The difference in diet cost between extreme quintiles of potassium intakes was $1.49 (95% confidence interval: 1.29, 1.69). A food-level analysis showed that beans, potatoes, coffee, milk, bananas, citrus juices and carrots are frequently consumed and low-cost sources of potassium. Based on existing dietary data and current American eating habits, a potassium-dense diet was associated with higher diet costs, while sodium was not. Price interventions may be an effective approach to improve potassium intakes and reduce the Na:K ratio of the diet. The present methods helped identify some alternative low-cost foods that were effective in increasing potassium intakes. The identification and promotion of lower-cost foods to help individuals meet targeted dietary recommendations could accompany future dietary guidelines.

The geographic distribution of obesity by census tract among 59 767 insured adults in King County, WA.

OBJECTIVE: To evaluate the geographic concentration of adult obesity prevalence by census tract (CT) in King County, WA, in relation to social and economic factors. METHODS AND DESIGN: Measured heights and weights from 59 767 adult men and women enrolled in the Group Health (GH) healthcare system were used to estimate obesity prevalence at the CT level. CT-level measures of socioeconomic status (SES) were median home values of owner-occupied housing units, percent of residents with a college degree and median household incomes, all drawn from the 2000 Census. Spatial regression models were used to assess the relation between CT-level obesity prevalence and socioeconomic variables. RESULTS: Smoothed CT obesity prevalence, obtained using an Empirical Bayes tool, ranged from 16.2-43.7% (a 2.7-fold difference). The spatial pattern of obesity was non-random, showing a concentration in south and southeast King County. In spatial regression models, CT-level home values and college education were more strongly associated with obesity than household incomes. For each additional $100 000 in median home values, CT obesity prevalence was 2.3% lower. The three SES factors together explained 70% of the variance in CT obesity prevalence after accounting for population density, race/ethnicity, age and spatial dependence. CONCLUSIONS: To our knowledge, this is the first report to show major social disparities in adult obesity prevalence at the CT scale that is based, moreover, on measured heights and weights. Analyses of data at sufficiently fine geographic scale are needed to guide targeted local interventions to stem the obesity epidemic.