Discretionary calorie intake a priority for obesity prevention: results of rapid participatory approaches in low-income US communities
ABSTRACT Since resources are limited, selecting the most promising targets for obesity interventions is critical. We examined the relative associations of physical activity, fruit and vegetable consumption and 'junk food' consumption with BMI and the prevalence of relevant policies in school, work, food outlets and health-care settings.
We conducted intercept surveys in three low-income, high-minority California communities to assess fruit, vegetable, candy, cookie, salty snacks and sugar-sweetened beverage consumption and self-reported height, weight and physical activity. We also assessed relevant policies in selected worksites, schools and health-care settings through key informant interviews.
Data were collected from 1826 respondents, 21 schools, 40 worksites, 14 health-care settings and 29 food outlets. The average intake of salty snacks, candy, cookies and sugar-sweetened beverages was estimated at 2226 kJ (532 kcal) daily, 88% higher than the US Department of Agriculture/Department of Health and Human Services guidelines recommend. Energy from these sources was more strongly related to BMI than reported physical activity, fruit or vegetable consumption. Policies to promote healthy eating and physical activity were limited in worksites. Fruits and vegetables were less salient than junk food in community food outlets.
Targeting consumption of salty snacks, candy cookies and sugar-sweetened beverages appeared more promising than alternative approaches.
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ABSTRACT: Food-based dietary guidelines shift the focus from single nutrients to whole diet. Guideline 3 of the Australian Dietary Guidelines (ADG) recommends "limiting" discretionary foods and beverages (DF)-Those high in saturated fat, added sugars, salt, and/or alcohol. In Australia, DF contribute 35% of total energy intake. Using the ADG supporting documents, the aim of this study was to develop a food‑based educational toolkit to help translate guideline 3 and interpret portion size. The methodology used to produce the toolkit is presented here. "Additional energy allowance" is specific to gender, age, height and physical activity level, and can be met from core foods, unsaturated fats/oils/spreads and/or DF. To develop the toolkit, additional energy allowance was converted to serves equaling 600 kJ. Common DF were selected and serves were determined based on nutrient profile. Portion sizes were used to calculate number of DF serves. A consumer brochure consisting of DF, portion sizes and equivalent number of DF serves was developed. A healthcare professional guide outlines the methodology used. The toolkit was designed to assist dietitians and consumers to translate guideline 3 of the ADF and develop a personalized approach to include DF as part of the diet.Nutrients 01/2015; 7(3):2026-43. DOI:10.3390/nu7032026 · 3.15 Impact Factor
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ABSTRACT: Controlling obesity has become one of the highest priorities for public health practitioners in developed countries. In the absence of safe, effective and widely accessible high-risk approaches (e.g. drugs and surgery) attention has focussed on community-based approaches and social marketing campaigns as the most appropriate form of intervention. However there is limited evidence in support of substantial effectiveness of such interventions. To date there is little evidence that community-based interventions and social marketing campaigns specifically targeting obesity provide substantial or lasting benefit. Concerns have been raised about potential negative effects created by a focus of these interventions on body shape and size, and of the associated media targeting of obesity. A more appropriate strategy would be to enact high-level policy and legislative changes to alter the obesogenic environments in which we live by providing incentives for healthy eating and increased levels of physical activity. Research is also needed to improve treatments available for individuals already obese.BMC Public Health 02/2011; 11:136. DOI:10.1186/1471-2458-11-136 · 2.32 Impact Factor
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ABSTRACT: The purpose of this study was to determine the effects of total, chocolate, or sugar candy consumption on intakes of total energy, fat, and added sugars; diet quality; weight/adiposity parameters; and risk factors for cardiovascular disease in children 2-13 years of age (n=7,049) and adolescents 14-18 years (n=4,132) participating in the 1999-2004 National Health and Nutrition Examination Survey. Twenty-four hour dietary recalls were used to determine intake. Diet quality was determined using the Healthy Eating Index-2005 (HEI-2005). Covariate-adjusted means, standard errors, and prevalence rates were determined for each candy consumption group. Odds ratios were used to determine the likelihood of associations with weight status and diet quality. In younger children, total, chocolate, and sugar candy consumption was 11.4 g±1.61, 4.8 g±0.35, and 6.6 g±0.46, respectively. In adolescents, total, chocolate, and sugar candy consumption was 13.0 g±0.87, 7.0 g±0.56, and 5.9 g±0.56, respectively. Total candy consumers had higher intakes of total energy (2248.9 kcals±26.8 vs 1993.1 kcals±15.1, p<0.0001) and added sugars (27.7 g±0.44 vs 23.4 g±0.38, p<0.0001) than non-consumers. Mean HEI-2005 score was not different in total candy and sugar candy consumers as compared to non-consumers, but was significantly lower in chocolate candy consumers (46.7±0.8 vs 48.3±0.4, p=0.0337). Weight, body mass index (BMI), waist circumference, percentiles/z-score for weight-for-age and BMI-for-age were lower for candy consumers as compared to non-consumers. Candy consumers were 22 and 26%, respectively, less likely to be overweight and obese than non-candy consumers. Blood pressure, blood lipid levels, and cardiovascular risk factors were not different between total, chocolate, and sugar candy consumers and non-consumers (except that sugar candy consumers had lower C-reactive protein levels than non-consumers). This study suggests that candy consumption did not adversely affect health risk markers in children and adolescents.Food & Nutrition Research 06/2011; 55. DOI:10.3402/fnr.v55i0.5794 · 1.79 Impact Factor