Nutrition in Transition: Dietary Patterns of Rural Amazonian Women During a Period of Economic Change

Objectives: The goal of this study was to understand the relationship between economic change (wage labor, retirement, and the Bolsa Familia program) and dietary patterns in the rural Amazon and to determine the extent to which these changes followed the pattern of the nutrition transition. Methods: The study was longitudinal. The weighed-inventory method and economic interviews were used to collect data on dietary intake and household economics in a sample of 30 and 52 women in 2002 and 2009, respectively. Twenty of the women participated in both years and make-up the longitudinal sub-sample. Comparative statistics were used to identify changes in dietary patterns over time and multiple linear regressions were used to explore the relationship between economics, subsistence strategies, and diet. Results: There was a significant decline in kcal (P < 0.01) and carbohydrate (P < 0.01) but no change in protein intake over time in both the larger and smaller, longitudinal subsample. The percent of energy, carbohydrate, protein, and fat purchased increased in the larger and longitudinal samples (P <= 0.02) and there was an increase in refined carbohydrate and processed, fatty-meat consumption over time. The abandonment of manioc gardens was associated with increased dependence on purchased food (P = 0.03) while receipt of the Bolsa Familia was associated with increased protein intake and adequacy (P = 0.02). Conclusions: The dietary changes observed are only in partial agreement with predictions of the nutrition transition literature. The relationship between the economic and diet changes was shaped by the local context which should be considered when implementing CCT programs, like the Bolsa Familia. Am. J. Hum. Biol. 23:458-469, 2011. (C) 2011 Wiley-Liss, Inc.

A bivariate regression model for matched paired survival data: local influence and residual analysis

The use of bivariate distributions plays a fundamental role in survival and reliability studies. In this paper, we consider a location scale model for bivariate survival times based on the proposal of a copula to model the dependence of bivariate survival data. For the proposed model, we consider inferential procedures based on maximum likelihood. Gains in efficiency from bivariate models are also examined in the censored data setting. For different parameter settings, sample sizes and censoring percentages, various simulation studies are performed and compared to the performance of the bivariate regression model for matched paired survival data. Sensitivity analysis methods such as local and total influence are presented and derived under three perturbation schemes. The martingale marginal and the deviance marginal residual measures are used to check the adequacy of the model. Furthermore, we propose a new measure which we call modified deviance component residual. The methodology in the paper is illustrated on a lifetime data set for kidney patients.