Food patterns measured by factor analysis and anthropometric changes in adults

ArticleinAmerican Journal of Clinical Nutrition 80(2):504-13 · August 2004with21 Reads
Source: PubMed
Sixty-five percent of US adults are overweight, and 31% of these adults are obese. Obesity results from weight gains over time; however, dietary determinants of weight gain remain controversial. Our objective was to examine whether food patterns derived from exploratory factor analysis are related to anthropometric changes. We hypothesized that we would derive a healthy food pattern and that it would predict smaller changes in body mass index (BMI; in kg/m(2)) and waist circumference (in cm) than would other food patterns in models adjusted for baseline anthropometric measures. The subjects were 459 healthy men and women participating in the Baltimore Longitudinal Study of Aging. Diet was assessed by using 7-d dietary records, from which 40 food groups were formed and entered into a factor analysis. Six food patterns were derived. Factor 1 (reduced-fat dairy products, fruit, and fiber) was most strongly associated with fiber (r = 0.39) and loaded heavily on reduced-fat dairy products, cereal, and fruit and loaded moderately on fruit juice, nonwhite bread, nuts and seeds, whole grains, and beans and legumes. In a multivariate-adjusted model in which the highest and lowest quintiles were compared, factor 1 was inversely associated with annual change in BMI (beta = -0.51; 95% CI: -0.82, -0.20; P < 0.05; P for trend < 0.01) in women and inversely associated with annual change in waist circumference (beta = -1.06 cm; 95% CI: -1.88, -0.24 cm; P < 0.05; P for trend = 0.04) in both sexes. Our results suggest that a pattern rich in reduced-fat dairy products and high-fiber foods may lead to smaller gains in BMI in women and smaller gains in waist circumference in both women and men.
    • "Regarding the " Animal protein and alcohol " patterns, it was positively associated with BMI, WHR, SBP, DBP, FPG, TG and LDL-C. Newby et al which also derived a " protein and alcohol " pattern found a direct association with BMI [31] and HDL [37]. Likewise, a meat [42] pattern and a " meat and potatoes " [6] pattern have also been positively related to BMI. "
    [Show abstract] [Hide abstract] ABSTRACT: Introduction: Principal component analysis is used to determine dietary behaviors of a population whereas reduced rank regression is used to construct disease-related dietary patterns. This study aimed to compare both types of DP and theirs associations with cardiovascular risk factors (CVRF). Materiel and methods: Data were derived from the cross sectional NESCAV (Nutrition, Environment and Cardiovascular Health) study, aiming to describe the cardiovascular health of the Greater region's population (Grand duchy of Luxembourg, Wallonia (Belgium), Lorraine (France)). 2298 individuals were included for this study and dietary intake was assessed using a 134-item food frequency questionnaire. Results: We found that CVRF-related patterns also reflect eating behaviours of the population. Comparing concordant food groups between both dietary pattern methods, a diet high in fruits, oleaginous and dried fruits, vegetables, olive oil, fats rich in omega 6 and tea and low in fried foods, lean and fatty meat, processed meat, ready meal, soft drink and beer was associated with lower prevalence of CVRF. In the opposite, a pattern characterized by high intakes of fried foods, meat, offal, beer, wine and aperitifs and spirits, and low intakes of cereals, sugar and sweets and soft drinks was associated with higher prevalence of CVRF. Conclusion: In sum, we found that a "Prudent" and "Animal protein and alcohol" patterns were both associated with CVRF and behaviourally meaningful. Moreover, the relationships of those dietary patterns with lifestyle characteristics support the theory that food choices are part of a larger pattern of healthy lifestyle.
    Full-text · Article · Aug 2016
    • "Specifically, yogurt and milk consumption have often been associated with a better overall dietary profile and inversely associated with the consumption of sugar-sweetened beverages, especially soda and fruit juices [70][71][72]. Regarding anthropometric outcomes, a longitudinal study showed that a healthy dietary pattern high in reduced-fat dairy was inversely associated with BMI and with waist circumfer- ence [73]. In the case of dietary patterns as exposures, the individual contribution of specific food groups to the effect cannot be quantified, but rather the results are seen as the effect of the interaction of this complex network of foods over the outcome. "
    [Show abstract] [Hide abstract] ABSTRACT: Background: The current state of knowledge regarding the association of dairy products and weight gain, overweight, and obesity is based on studies reporting contradicting and inconclusive results. The aim of the present study was thus to clarify the link between dairy consumption in relation to changes in anthropometric measures/adiposity by a meta-analytical approach. Methods: For the meta-analysis PubMed, EMBASE, Web of Sciences, and google scholar were searched by two independent authors up to May 2016 with no restriction to language or calendar date. Prospective cohort studies reporting about intake of dairy consumption (including milk, yogurt, cheese, butter) and changes in body weight or waist circumference, risk of overweight, obesity, or weight gain were eligible. Pooled effects were calculated using a random effects model, and also a fixed effect model for sensitivity analysis. Due to the heterogeneity of statistical analytical approaches of the studies the analysis were done separately for beta-coefficients of changes in body weight and/or waist circumference per serving of dairy, for differences in weight gain/gain in waist circumference when comparing extreme categories of dairy consumption, and for odds ratios in regard to weight gain, overweight/obesity, or abdominal obesity. Findings: 24 studies (27 reports) met the inclusion criteria for the systematic review, and 22 studies provided sufficient data for inclusion in the meta-analysis. The meta-analysis of the five studies on changes in body weight per serving of dairy no significant results could be found for whole fat dairy and low fat dairy. However, there was inverse association between changes in body weight for each serving's increase of yogurt (beta: -40.99 gram/year, 95% CI, -48.09 to -33.88), whereas each serving's increase of cheese was positively associated (beta: -10.97 gram/year, 95% CI, 2.86 to 19.07). Furthermore, the highest dairy intake category was associated with a reduced risk of abdominal obesity (OR: 0.85; 95% CI, 0.76 to 0.95), and risk of overweight (OR: 0.87; 95% CI, 0.76 to 1.00) compared to the lowest intake category. No significant association could be observed for risk of weight gain. Conclusion: In summary the results of the meta-analysis still reflect that dairy consumption was not positively related to changes in body weight. Yogurt was the only dairy food that showed some evidence for a beneficial effect, where higher intakes were inversely associated a reduced risk of obesity, changes in body weight or waist circumference. Further research is needed, since the overall interpretation of the results is limited by heterogeneous risk estimates.
    Full-text · Article · Jun 2016
    • "Similar to our results in men, a dietary pattern characterized by high-fiber and low-fat food choices was associated with a less 4-year weight gain in male participants of the German EPIC-Potsdam study [6]. Likewise, in a sample of the US males a dietary pattern rich in reduced-fat dairy products, fruit, and fiber foods was associated with lower WC gain over a 25-month follow-up [21], while it was not associated with change in BMI.Table 2 Baseline characteristics of women according to tertiles of dietary patterns: the Nambour Study n = 682 and varies for individual covariates due to missing values; each participant has a score for each factor; tertile 1: lowest, tertile 3: highest (n = 227 for T1 and T3, and 228 for T2) "
    [Show abstract] [Hide abstract] ABSTRACT: Background Dietary intake is one of the most modifiable risk factors associated with obesity. However, data on the relationship between dietary patterns and long-term weight change are limited. Purpose We therefore investigated the association between dietary patterns and 15-year weight change in a sample of 1186 Australian adults (1992–2007). Methods We measured body weight and collected data on socio-demographic and lifestyle characteristics in 1992 and 2007. Applying principal component analysis to 38 food groups from a food frequency questionnaire collected at baseline, we identified two dietary patterns: ‘meat-and-fat’ and ‘fruit-and-vegetable.’ Using generalized estimating equations, multivariable regression models, stratified by sex, were adjusted for concurrent changes in socio-demographic and lifestyle variables. Results The average increase in body weight of men in the highest tertile of the meat-and-fat pattern was more than twice that of men in the lowest tertile; mean weight change (95 % CI): 4.8 (−0.1, 9.7) kg versus 2.3 (−2.6, 7.1) kg, P-for-trend = 0.02. In contrast, average weight gain of men in the highest tertile of the fruit-and-vegetable pattern was only about half that of men in the lowest tertile; mean weight change (95 % CI): 2.9 (−2.0, 7.8) kg versus 5.4 (−1.5, 10.4) kg, P-for-trend = 0.02. Among women, dietary patterns were not related to weight change. Conclusions These dietary patterns predict change in body weight in men, but not in women. In this cohort, a dietary pattern high in fruit and vegetables was related to less weight gain in men than a dietary pattern high in meat and fat.
    Full-text · Article · Feb 2016
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