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In this paper we present a continuous extension for longitudinal analysis settings of the recently proposed Covariate Balancing Propensity Score (CBPS) methodology. While extensions of the CBPS methodology to both marginal structural models and general treatment regimes have been proposed, these extensions have been kept separately. We propose to bring them together using the generalized method of moments to estimate inverse probability weights such that after weighting the association between time-varying covariates and the treatment is minimized. A simulation analysis confirms the correlation-breaking performance of the proposed technique. As an empirical application we look at the impact the gradual roll-out of Seguro Popular, a universal health insurance program, has had on the resources available for the provision of healthcare services in Mexico.

Objective. To investigate the degree in which answer patterns in the Household Water Insecurity Experiences Scale (HWISE) relate to scores aiming at identifying latent groups with different water insecurity levels in a nationwide representative sample of the Mexican population. Materials and methods. Based on data from the 2021 National Survey on Health and Nutrition (Estudio Nacional de Salud y Nutrición 2021, Ensanut 2021), sequence data representations, and a latent class analysis (LCA), in this article we estimate the likely misclassification errors of different cutoffs proposed for the HWISE scoring system. Results. The main results suggest that a 5-item subset of the HWISE may exhibit a more reliable and cost-effective behavior than the complete 12-item set for a 2-level partition of the sample. Conclusions. Our methodological approach provides new insights regarding the efficiency and likely errors in distinguishing between levels of water insecurity based on the Mexican chapter of the HWISE. [ABSTRACT FROM AUTHOR]

Background: While the cumulative deficit model is arguably the most popular instrument for population-level frailty screening, several questions remain unanswered regarding the comparability of the resulting scores across subpopulations. Methods: Based on data from the five waves of the Mexican Health and Aging Study (MHAS) we draw upon the alignment method to test for measurement invariance of frailty scores as per the accumulation of deficits approach. Results: Our results show that adjusting for measurement non-invariance not only improves predictive validity of our frailty measures, but resulting scores are more consistent with what is theoretically expected from them in longitudinal research. Conclusions: There are clear potential benefits of measurement invariance testing as a general analytical framework from which to tackle with issues of comparability in frailty research. [ABSTRACT FROM AUTHOR]

The aim of this study is to put forward an approach designed to calculate and sum up discrepancies between the actual food acquisition or intake and any standard or norm. Based on secondary analysis of cross-sectional data from the Mexican National Survey of Household Income and Expenditure, our proposed method to produce classes of entropy-based Diet Adherence Indices generates a Food Basket Adherence Index (FBAI) for Mexico City (2129 households). Findings suggest that it is possible to measure and decompose diet adherence using a cross entropy measure. Using food expenditure data and a normative food basket for Mexico City results, we show households' deviations from the suggested norm for different food groups. The average FBAI was 0.44, far above the minimum score of 0 which would indicate full adherence to the normative food basket. Our measure has a distribution wide enough to detect meaningful changes and distinguish between groups with known differences, providing important new insights on the linkages between home food environments and income distribution, and food insecurity and household distribution. [ABSTRACT FROM AUTHOR]

Objective: To investigate the degree in which answer patterns in the Household Water Insecurity Experiences Scale (HWISE) relate to scores aiming at identifying latent groups with different water insecurity levels in a nationwide representative sample of the Mexican population., Materials and Methods: Based on data from the 2021 National Survey on Health and Nutrition (Estudio Nacional de Salud y Nutrición 2021, Ensanut 2021), sequence data representations, and a latent class analysis (LCA), in this article we estimate the likely misclassification errors of different cutoffs proposed for the HWISE scoring system., Results: The main results suggest that a 5-item subset of the HWISE may exhibit a more reliable and cost-effective behavior than the complete 12-item set for a 2-level partition of the sample., Conclusions: Our methodological approach provides new insights regarding the efficiency and likely errors in distinguishing between levels of water insecurity based on the Mexican chapter of the HWISE.