El Protomedicato navarro : itinerario de una investigación

En este trabajo se expone la metodología empleada en el estudio del Protomedicato navarro. Aprovechando la peculiar situación del reino de Navarra entre los siglos XV y XIX, durante los que mantuvo plena autonomía, se acometió el estudio del Protomedicato navarro a través de los fondos documentales de las demás instituciones administrativas y políticas del reino. Entre estas instituciones cabe destacar la Cofradía de médicos, cirujanos y boticarios de Pamplona, cuya existencia influyó en su evolución

Latent class models and latent transition models for dietary pattern analysis

Dietary patterns (DP) are used to study the effects of overall diet on health outcomes as opposed to the effects of individual nutrients or foods. DP are empirically derived mostly using factor and cluster analysis. Latent class models (LCM) have been shown empirically to be more appropriate to derive DP than cluster analysis, but they have not been compared yet to those derived by factor analysis. We derive DP using LCM and factor analysis on food-items, test how well the resulting classes are characterized by the factor scores, and compare subjects' direct classification from LCM versus two a posteriori classifications from factor scores: one possible classification using tertiles and a two-step classification using LCM on previously derived factor scores. In order to study changes in dietary patterns over time, we propose using latent transition models to study change as characterized by the movement between discrete dietary patterns. Latent transition models directly classify subjects into mutually exclusive DP at each time point and allow predictors for class membership and for probabilities of changing classes over time. There are several challenges particular to DP analysis: a large ([greater than or equal to]80) number of food-items, non-standard mixture distributions (continuous with a mass point at zero for non-consumption), and typical assumptions (conditional independence given the class and time point, time-invariant conditional responses, and invariant transition probabilities) may not be realistic. We compare performance, capabilities and flexibility between two software packages (Mplus and a user's derived procedure in SAS) that allow fitting latent transition models. A key decision involved when deriving DP is whether or not to collapse the primary dietary data into a smaller number of items called food groups. Advantages for collapsing include dimension reduction and decreasing the number of non-consumers to reduce the mass-point at zero. However, not collapsing helps our understanding of which combinations of specific foods are consumed. Further, food-grouping may have an impact on the association between DP and health outcomes. We explore via a Monte Carlo simulation study whether food-grouping makes a difference when deriving DP using LCM. Methods are illustrated using data from the Pregnancy, Infection and Nutrition (PIN) Study

Chronic disease risk typologies among young adults in community college

Objectives: To address chronic disease risk holistically from a behavioral perspective, insights are needed to refine understanding of the covariance of key health behaviors. This study aims to identify distinct typologies of young adults based on 4 modifiable risk factors of chronic disease using a latent class analysis approach, and to describe patterns of class membership based on demographic characteristics, living arrangements, and weight. Methods: Overall, 441 young adults aged 18-35 attending community colleges in the Minnesota Twin Cities area completed a baseline questionnaire for the Choosing Healthy Options in College Environments and Settings study, a RCT. Behavioral items were used to create indicators for latent classes, and individuals were classified using maximum-probability assignment. Results: Three latent classes were identified: ‘active, binge-drinkers with a healthy dietary intake’ (13.1%); ‘non-active, moderate-smokers and non-drinkers with poor dietary intake’ (38.2%); ‘moderately active, non-smokers and non-drinkers with moderately healthy dietary intake’ (48.7%). Classes exhibited unique demographic and weight-related profiles. Conclusions: This study may contribute to the literature on health behaviors among young adults and provides evidence that there are weight and age differences among subgroups. Understanding how behaviors cluster is important for identifying groups for targeted interventions in community colleges

Using both principal component analysis and reduced rank regression to study dietary patterns and diabetes in Chinese adults

Abstract Objective We examined the association between dietary patterns and diabetes using the strengths of two methods: principal component analysis (PCA) to identify the eating patterns of the population and reduced rank regression (RRR) to derive a pattern that explains the variation in glycated Hb (HbA1c), homeostasis model assessment of insulin resistance (HOMA-IR) and fasting glucose. Design We measured diet over a 3 d period with 24 h recalls and a household food inventory in 2006 and used it to derive PCA and RRR dietary patterns. The outcomes were measured in 2009. Setting Adults ( n 4316) from the China Health and Nutrition Survey. Results The adjusted odds ratio for diabetes prevalence (HbA1c≥6·5 %), comparing the highest dietary pattern score quartile with the lowest, was 1·26 (95 % CI 0·76, 2·08) for a modern high-wheat pattern (PCA; wheat products, fruits, eggs, milk, instant noodles and frozen dumplings), 0·76 (95 % CI 0·49, 1·17) for a traditional southern pattern (PCA; rice, meat, poultry and fish) and 2·37 (95 % CI 1·56, 3·60) for the pattern derived with RRR. By comparing the dietary pattern structures of RRR and PCA, we found that the RRR pattern was also behaviourally meaningful. It combined the deleterious effects of the modern high-wheat pattern (high intakes of wheat buns and breads, deep-fried wheat and soya milk) with the deleterious effects of consuming the opposite of the traditional southern pattern (low intakes of rice, poultry and game, fish and seafood). Conclusions Our findings suggest that using both PCA and RRR provided useful insights when studying the association of dietary patterns with diabetes

Applying recovery biomarkers to calibrate self-report measures of sodium and potassium in the Hispanic Community Health Study/Study of Latinos

Measurement error in assessment of sodium and potassium intake obscures associations with health outcomes. The level of this error in a diverse US Hispanic/Latino population is unknown

Latent Transition Models to Study Women's Changing of Dietary Patterns From Pregnancy to 1 Year Postpartum

Latent class models are useful for classifying subjects by dietary patterns. Our goals were to use latent transition models to identify dietary patterns during pregnancy and postpartum, to estimate the prevalence of these dietary patterns, and to model transition probabilities between dietary patterns as a function of covariates. Women who were enrolled in the Pregnancy, Infection, and Nutrition Study (University of North Carolina, 2000–2005) were followed for 1 year postpartum, and their diets were assessed in the second trimester and at 3 and 12 months postpartum (n = 519, 484, and 374, respectively) by using a food frequency questionnaire. After adjusting for energy intake, parity, smoking status, race, and education, we identified 3 dietary patterns and named them “prudent,” “health conscious Western,” and “Western.” Nulliparas were 2.9 and 2.1 times more likely to be in the “prudent” class than the “health conscious Western” or the “Western” class, respectively. The 3 dietary patterns were very stable, with the “health conscious Western” class being the least stable; the probability for staying in the same class was 0.74 and 0.87 at 3 and 12 months postpartum, respectively. Breastfeeding mothers were more likely than nonbreastfeeding mothers to switch dietary pattern class (P = 0.0286). Except for breastfeeding mothers, most women did not switch dietary patterns from pregnancy to postpartum

Latent Class Analysis Is Useful to Classify Pregnant Women into Dietary Patterns

Empirical dietary patterns are derived predominantly using principal components, exploratory factor analysis (EFA), or cluster analysis. Interestingly, latent variable models are less used despite their being more flexible to accommodate important characteristics of dietary data and despite dietary patterns being recognized as latent variables. Latent class analysis (LCA) has been shown empirically to be more appropriate to derive dietary patterns than k-means clustering but has not been compared yet to confirmatory factor analysis (CFA). In this article, we derived dietary patterns using EFA, CFA, and LCA on food items, tested how well the classes from LCA were characterized by the factors from CFA, and compared participants’ direct classification from LCA on food items compared with 2 a posteriori classifications from factor scores. Methods were illustrated with the Pregnancy, Infection and Nutrition Study, North Carolina, 2000–2005 (n = 1285 women). From EFA and CFA, we found that food items were grouped into 4 factors: Prudent, Prudent with coffee and alcohol, Western, and Southern. From LCA, pregnant women were classified into 3 classes: Prudent, Hard core Western, and Health-conscious Western. There was high agreement between the direct classification from LCA on food items and the classification from the 2-step LCA on factor scores [κ=0.70 (95% CI = 0.66, 0.73)] despite factors explaining only 25% of the total variance. We suggest LCA on food items to study the effect for mutually exclusive classes and CFA to understand which foods are eaten in combination. When interested in both benefits, the 2-step classification using LCA on previously derived factor scores seems promising

The association of trajectories of protein intake and age-specific protein intakes from 2 to 22 years with BMI in early adulthood

Abstract No study has analysed how protein intake from early childhood to young adulthood relate to adult BMI in a single cohort. To estimate the association of protein intake at 2, 11, 15, 19 and 22 years with age- and sex-standardised BMI at 22 years (early adulthood), we used linear regression models with dietary and anthropometric data from a Filipino birth cohort (1985–2005, n 2586). We used latent growth curve analysis to identify trajectories of protein intake relative to age-specific recommended daily allowance (intake in g/kg body weight) from 2 to 22 years, then related trajectory membership to early adulthood BMI using linear regression models. Lean mass and fat mass were secondary outcomes. Regression models included socioeconomic, dietary and anthropometric confounders from early life and adulthood. Protein intake relative to needs at age 2 years was positively associated with BMI and lean mass at age 22 years, but intakes at ages 11, 15 and 22 years were inversely associated with early adulthood BMI. Individuals were classified into four mutually exclusive trajectories: (i) normal consumers (referent trajectory, 58 % of cohort), (ii) high protein consumers in infancy (20 %), (iii) usually high consumers (18 %) and (iv) always high consumers (5 %). Compared with the normal consumers, ‘usually high’ consumption was inversely associated with BMI, lean mass and fat mass at age 22 years whereas ‘always high’ consumption was inversely associated with male lean mass in males. Proximal protein intakes were more important contributors to early adult BMI relative to early-childhood protein intake; protein intake history was differentially associated with adulthood body size

Maternal Dietary Patterns during the Second Trimester Are Associated with Preterm Birth

Background: Preterm birth is one of the leading causes of neonatal morbidity in the United States. Despite decades of research, the etiology is largely unknown

Persistent disparities over time in the distribution of sugar-sweetened beverage intake among children in the United States

Background Recent research suggests that sugar-sweetened beverage (SSB) consumption has been declining among US children aged 2-18 y. However, most studies focused on changes in mean intake, ignore high SSB consumers and do not examine intake among vulnerable groups and, including adolescents, low-income households, and several racial/ethnic minorities. Objective The aim was to estimate usual SSB intake from NHANES surveys from 2003-2004 to 2013-2014 to examine shifts at both the median and 90th percentile among US children, evaluating the extent to which intake disparities in total SSBs and subtypes have persisted. Design Children 2-18 y from NHANES 2003, 2005, 2007, 2009, 2011 and 2013. SSBs were all non-diet beverages sweetened with sugars including revising all beverages to as consumed status and excluding soy and dairy based beverages. The NCI usual intake method was used to estimate usual intake from two 24-hour recalls. A 2-part correlated model accounted for nonconsumers. Quantile regression was then used to examine differences in SSB usual intakes at the 50th and 90th percentiles by race-ethnicity, and examine interactions indicating whether racial-ethnic disparities in intake were modified by income. Results Despite considerable declines, children's SSB intake remains high, particularly among heavy consumers. Among adolescents, median SSB intake in 2013-2014 was on the order of 150-200 kcal/d, and heavy intake at the 90th percentile was on the order of 250-300 kcal/d. There were important disparities in intake that persisted over time. Although high household income was associated with lower SSB intake in non-Hispanic white (NHW) children, intakes of non-Hispanic black (NHB) and Mexican-American (MA) children from these households were similar to or higher than those from poor households. There were also large racial/ethnic differences in the types of SSBs consumed. The consumption of regular sodas by NHB children was somewhat lower than among MA and NHW children, whereas fruit drink intake was markedly higher. Conclusions Overall, these findings suggest that, despite recent declines, strategies are needed to further reduce SSB consumption, and particularly heavy intake, especially among NHB children where fruit drinks also are key source of SSBs