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ObjectiveTo design and develop a questionnaire that can account for an individual’s adherence to a Mediterranean lifestyle including the assessment of diet and physical activity patterns, as well as social interaction.DesignThe Mediterranean Lifestyle (MEDLIFE) index was created based on the current Spanish Mediterranean food guide pyramid. MEDLIFE is a twenty-eight-item derived index consisting of questions about food consumption (fifteen items), traditional Mediterranean dietary habits (seven items) and physical activity, rest and social interaction habits (six items). Linear regression models and Spearman rank correlation were fitted to assess content validity and internal consistency.SettingA subset of participants in the Aragon Workers’ Health Study cohort (Zaragoza, Spain) provided the data for development of MEDLIFE.SubjectsParticipants (n 988) of the Aragon Workers’ Health Study cohort in Spain.ResultsMean MEDLIFE score was 11·3 (sd 2·6; range: 0–28), and the quintile distribution of MEDLIFE score showed a significant association with each of the individual items as well as with specific nutrients and lifestyle indicators (intra-validity). We also quantified MEDLIFE correspondence with previously reported diet quality indices and found significant correlations (ρ range: 0·44–0·53; P<0·001) for the Alternate Healthy Eating Index, the Alternate Mediterranean Diet Index and Mediterranean Diet Adherence Screener.ConclusionsMEDLIFE is the first index to include an overall assessment of lifestyle habits. It is expected to be a more holistic tool to measure adherence to the Mediterranean lifestyle in epidemiological studies. [ABSTRACT FROM AUTHOR]

Background: While food pricing is a promising strategy to improve diet, the prospective impact of food pricing on diet has not been systematically quantified. Objective: To quantify the prospective effect of changes in food prices on dietary consumption. Design: We systematically searched online databases for interventional or prospective observational studies of price change and diet; we also searched for studies evaluating adiposity as a secondary outcome. Studies were excluded if price data were collected before 1990. Data were extracted independently and in duplicate. Findings were pooled using DerSimonian-Laird's random effects model. Pre-specified sources of heterogeneity were analyzed using meta-regression; and potential for publication bias, by funnel plots, Begg's and Egger's tests. Results: From 3,163 identified abstracts, 23 interventional studies and 7 prospective cohorts with 37 intervention arms met inclusion criteria. In pooled analyses, a 10% decrease in price (i.e., subsidy) increased consumption of healthful foods by 12% (95%CI = 10–15%; N = 22 studies/intervention arms) whereas a 10% increase price (i.e. tax) decreased consumption of unhealthful foods by 6% (95%CI = 4–8%; N = 15). By food group, subsidies increased intake of fruits and vegetables by 14% (95%CI = 11–17%; N = 9); and other healthful foods, by 16% (95%CI = 10–23%; N = 10); without significant effects on more healthful beverages (-3%; 95%CI = -16-11%; N = 3). Each 10% price increase reduced sugar-sweetened beverage intake by 7% (95%CI = 3–10%; N = 5); fast foods, by 3% (95%CI = 1–5%; N = 3); and other unhealthful foods, by 9% (95%CI = 6–12%; N = 3). Changes in price of fruits and vegetables reduced body mass index (-0.04 kg/m2 per 10% price decrease, 95%CI = -0.08–0 kg/m2; N = 4); price changes for sugar-sweetened beverages or fast foods did not significantly alter body mass index, based on 4 studies. Meta-regression identified direction of price change (tax vs. subsidy), number of intervention components, intervention duration, and study quality score as significant sources of heterogeneity (P-heterogeneity<0.05 each). Evidence for publication bias was not observed. Conclusions: These prospective results, largely from interventional studies, support efficacy of subsidies to increase consumption of healthful foods; and taxation to reduce intake of unhealthful beverages and foods. Use of subsidies and combined multicomponent interventions appear most effective.

Introduction: The neighborhood food environment - locations and density of different types of stores and restaurants - is of great interest to reduce obesity. However, prior meta-analyses have focused on cross-sectional studies, for which reverse causation is a major limitation. Meta-analyses restricted to longitudinal study designs evaluating the food environment and change in BMI have yet to be conducted. Hypothesis: We hypothesized that increased exposure to fast food restaurants would be associated with increased change in BMI. Methods: Eleven databases were searched for longitudinal studies evaluating convenience stores, fast food restaurants, grocery stores, or supermarkets and change in BMI. Inclusion criteria consisted of: (1) interventional, quasi-experimental, or cohort studies; (2) adult or children populations; (3) any country; (4) geographic density or distance of food outlets; (5) a multivariable-adjusted change in BMI over time and corresponding uncertainty. Data were extracted independently and in duplicate, and studies pooled using fixed and random-effects models. Heterogeneity was quantified using Cochrane's Q, and publication bias using funnel plots, Egger's test, and Begg's test. Results: 13 studies including 98,268 subjects were identified. In random effects models, no significant association was seen between food environments and change in BMI (Figure). A nonsignificant trend was seen toward lower BMI with increasing density of supermarkets; however, a similar nonsignificant trend was also observed between increasing density of fast food restaurants and lower BMI. Evidence for publication bias was not identified. Conclusion: In available longitudinal studies, no significant relationships were identified between food environments and change in BMI. Our novel findings support the need for further longitudinal and especially interventional studies of how the built food environment, including new measures related to cost and accessibility, may influence health and weight. [ABSTRACT FROM AUTHOR]