Food frequency questionnaires (FFQs) are less time consuming and inexpensive instruments for collecting dietary intake when compared with 24-h dietary recalls or double-labelled water; however, the validation of FFQ is important as incorrect information may lead to biased conclusions about associations. Therefore, the relative validity of the Block Kids Food Screener (BKFS) developed for use with children was examined in a convenience sample of 99 youth recruited from the Portland, OR metropolitan area. Three 24-h dietary recalls served as the reference. The relative validity was analysed after natural log transformation of all variables except glycaemic index prior to correlation analysis. Daily cup equivalent totals from the BKFS and 'servings' from 24-h recalls were used to compute average daily intake of fruits, vegetables, potatoes, whole grains, legumes, meat/fish/poultry and dairy. Protein grams (g), total kcalories, glycaemic index (glucose reference), glycaemic load (glucose reference), total saturated fat (g) and added sugar (g) were also calculated by each instrument. The correlation between data obtained from the two instruments was corrected for the within-subject variation in food intake reported by the 24-h recalls using standard nutritional assessment methodology. The de-attenuated correlations in nutritional intake between the two dietary assessment instruments ranged from 0.526 for vegetables, to 0.878 for potatoes. The 24-h recall estimated higher levels of saturated fat and added sugar consumption, higher glycaemic loads and glycaemic indices; the de-attenuatted correlations of these measures ranged from 0.478 to 0.768. Assessment of Bland-Altman plots indicated no systematic difference between the two instruments for vegetable, dairy and meat/fish/poultry fat consumption. BKFS is a useful dietary assessment instrument for the nutrients and food groups it was designed to assess in children age 10-17 years.
Background Cost-effective interventions to improve diet and physical activity are a public health priority. Alive! is an email-based intervention to increase physical activity, reduce saturated and trans fats and added sugars, and increase fruit and vegetable consumption. It was shown to improve these behaviors in a large randomized controlled trial.Objective (1) To describe the components and behavioral principles underlying Alive!, and (2) to report effects of the intervention on the secondary outcomes: health-related quality of life, presenteeism, self-efficacy, and stage of change.Methods The Alive! behavior change model is designed to elicit healthy behaviors and promote their maintenance. Behavioral strategies include assessments followed by individualized feedback, weekly goal-setting, individually tailored goals and tips, reminders, and promotion of social support. Alive! was tested among non-medical employees of Kaiser Permanente of Northern California, who were randomized to either the intervention group or the wait-list control group. After randomization, intervention group participants chose one topic to undertake for the intervention period: increasing physical activity, increasing fruits and vegetables, or decreasing saturated and trans fats and added sugars. Pre-post questionnaires assessed changes in SF-8 health-related quality of life, presenteeism, self-efficacy, and stage of change. Mixed effects multiple linear regression and ordinal logistic regression models were used, with department as a random effect factor. Analyses were by intention to treat: the 30% (238/787) who did not respond to the follow-up questionnaires were assigned change scores of zero.ResultsParticipants were 19 to 65 years (mean 44.0 +/- 10.6), and 74.3% (585/787) were female. Mean SF-8 Physical quality of life score increased significantly more in the intervention group than in the control group, 1.84 (95% CI 0.96-2.72) vs 0.72 (95% CI -0.15-1.58) respectively, P = .02. SF8 Mental score also improved significantly more in the intervention group than in the control group (P = .02). The odds ratio for improvement in self-assessed health status was 1.57 (95% CI 1.21-2.04, P < .001) for the intervention group compared to the control group. The odds ratio for having a reduction in difficulty accomplishing work tasks because of physical or emotional problems, a measure of presenteeism, was 1.47 (95% CI 1.05-2.05, P = .02) for the intervention group compared to the control group. The odds of having an improvement in self-efficacy for changing diet was 2.05 (95% CI 1.44-2.93) for the intervention vs the control group (P < .001). Greater improvement in stage of change for physical activity (P = .05), fats (P = .06), and fruits/vegetables (P = .006) was seen in the intervention group compared to the control group. Significant effects on diet and physical activity behavior change are reported elsewhere.Conclusions Cost-effective methods that can reach large populations with science-based interventions are urgently needed. Alive! is a...
OBJECTIVES: This study examined US trends in nutrient intake, using almost identical methods and nutrient databases in two time periods. METHODS: An extensive dietary intake questionnaire was included in supplements to the 1987 and 1992 National Health Interview Surveys. Dietary data from approximately 11,000 persons in each of those years were analyzed. RESULTS: The total and saturated fat intake and the percentage of energy from fat declined among Whites and Hispanics, but only minimal changes were seen in Black Americans. The changes in fat intake were attributable principally to behavioral changes in frequency and type of fat-containing foods consumed rather than to the increased availability of leaner cuts of meat. Dietary cholesterol showed one of the largest declines of the nutrients examined. Less desirable changes were also seen. Cereal fortification played an important role in the observed changes in several micronutrients. CONCLUSIONS: Educational campaigns on dietary fat and cholesterol have been moderately effective, but not in all racial/ethnic groups. Future campaigns should emphasize maintaining or increasing micronutrient intake.
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