Last data update: May 06, 2024. (Total: 46732 publications since 2009)
Records 1-8 (of 8 Records) |
Query Trace: Talih M[original query] |
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National Center for Health Statistics Data presentation standards for proportions
Parker JD , Talih M , Malec DJ , Beresovsky V , Carroll M , Gonzalez JF , Hamilton BE , Ingram DD , Kochanek K , McCarty F , Moriarity C , Shimizu I , Strashny A , Ward BW . Vital Health Stat 2 2017 (175) 1-22 The National Center for Health Statistics (NCHS) disseminates information on a broad range of health topics through diverse publications. These publications must rely on clear and transparent presentation standards that can be broadly and efficiently applied. Standards are particularly important for large, cross-cutting reports where estimates cannot be individually evaluated and indicators of precision cannot be included alongside the estimates. This report describes the NCHS Data Presentation Standards for Proportions. The multistep NCHS Data Presentation Standards for Proportions are based on a minimum denominator sample size and on the absolute and relative widths of a confidence interval calculated using the Clopper-Pearson method. Proportions (usually multiplied by 100 and expressed as percentages) are the most commonly reported estimates in NCHS reports. |
Evaluation of four gamma-based methods for calculating confidence intervals for age-adjusted mortality rates when data are sparse
Talih M , Anderson RN , Parker JD . Popul Health Metr 2022 20 (1) 13 BACKGROUND: Equal-tailed confidence intervals that maintain nominal coverage (0.95 or greater probability that a 95% confidence interval covers the true value) are useful in interval-based statistical reliability standards, because they remain conservative. For age-adjusted death rates, while the Fay-Feuer gamma method remains the gold standard, modifications have been proposed to streamline implementation and/or obtain more efficient intervals (shorter intervals that retain nominal coverage). METHODS: This paper evaluates three such modifications for use in interval-based statistical reliability standards, the Anderson-Rosenberg, Tiwari, and Fay-Kim intervals, when data are sparse and sample size-based standards alone are overly coarse. Initial simulations were anchored around small populations (P = 2400 or 1200), the median crude all-cause US mortality rate in 2010-2019 (833.8 per 100,000), and the corresponding age-specific probabilities of death. To allow for greater variation in the age-adjustment weights and age-specific probabilities, a second set of simulations draws those at random, while holding the mean number of deaths at 20 or 10. Finally, county-level mortality data by race/ethnicity from four causes are selected to capture even greater variation: all causes, external causes, congenital malformations, and Alzheimer disease. RESULTS: The three modifications had comparable performance when the number of deaths was large relative to the denominator and the age distribution was as in the standard population. However, for sparse county-level data by race/ethnicity for rarer causes of death, and for which the age distribution differed sharply from the standard population, coverage probability in all but the Fay-Feuer method sometimes fell below 0.95. More efficient intervals than the Fay-Feuer interval were identified under specific circumstances. When the coefficient of variation of the age-adjustment weights was below 0.5, the Anderson-Rosenberg and Tiwari intervals appeared to be more efficient, whereas when it was above 0.5, the Fay-Kim interval appeared to be more efficient. CONCLUSIONS: As national and international agencies reassess prevailing data presentation standards to release age-adjusted estimates for smaller areas or population subgroups than previously presented, the Fay-Feuer interval can be used to develop interval-based statistical reliability standards with appropriate thresholds that are generally applicable. For data that meet certain statistical conditions, more efficient intervals could be considered. |
Measuring the magnitude of health inequality between two population subgroup proportions
Talih M , Moonesinghe R , Huang DT . Am J Epidemiol 2020 189 (9) 987-996 The paper evaluates 11 measures of inequality d(p1,p2) between two proportions p1 and p2, some of which are new to the health disparities literature. These measures are selected because they are continuous, nonnegative, equal to zero if and only if |p1-p2|=0, and maximal when |p1-p2|=1. They are also symmetric [d(p1,p2)=d(p2,p1)] and complement-invariant [d(p1,p2)=d(1-p2,1-p1)]. To study inter-measure agreement, five of the 11 measures, including the absolute difference, are retained, because they remain finite and are maximal if and only if |p1-p2|=1. Even when the two proportions are assumed to be drawn at random from a shared distribution-interpreted as the absence of an avoidable difference-the expected value of d(p1,p2) depends on the shape of the distribution (and the choice of d) and can be quite large. To allow for direct comparisons among measures, a standard measurement unit akin to a z-score is proposed. For skewed underlying beta distributions, four of the five retained measures, once standardized, offer more conservative assessments of the magnitude of inequality than the absolute difference. The paper concludes that, even for measures that share the highlighted mathematical properties, magnitude comparisons are most usefully assessed relative to an elicited or estimated underlying distribution for the two proportions. |
HPV vaccine status and sexual behavior among young sexually-active women in the US: evidence from the National Health and Nutrition Examination Survey, 2007-2014
Leidner AJ , Chesson HW , Talih M . Health Econ Policy Law 2019 15 (4) 1-19 Concern has been expressed that human papillomavirus (HPV) vaccination programs might promote risky sexual behavior through mechanisms such as risk compensation, behavioral disinhibition, or perceived endorsement of sexual activity. This study assesses whether HPV vaccination status is associated with any differences in selected sexual behaviors among young sexually-active women in the US. Our dataset includes young, adult female respondents from questionnaire data collected in the National Center for Health Statistics' National Health and Nutrition Examination Survey from 2007 to 2014. The empirical approach implements a doubly robust estimation procedure, based on inverse probability of treatment weighting. For robustness, we implement several specifications for the propensity model and the outcomes model. We find no consistent association between HPV vaccination and condom usage or frequency of sex. Specifically, we find no evidence that HPV vaccination is associated with condom usage or with whether a person had sex more than 52 or more than 104 times per year. We find inconsistent evidence that HPV vaccination is associated with a person having sex more than 12 times per year. As in previous research, HPV vaccination does not appear to have a substantive effect on sexual behavior among young sexually-active women in the US. |
Measurement of health disparities, health inequities, and social determinants of health to support the advancement of health equity
Penman-Aguilar A , Talih M , Huang D , Moonesinghe R , Bouye K , Beckles G . J Public Health Manag Pract 2016 22 Suppl 1 S33-42 Reduction of health disparities and advancement of health equity in the United States require high-quality data indicative of where the nation stands vis-a-vis health equity, as well as proper analytic tools to facilitate accurate interpretation of these data. This article opens with an overview of health equity and social determinants of health. It then proposes a set of recommended practices in measurement of health disparities, health inequities, and social determinants of health at the national level to support the advancement of health equity, highlighting that (1) differences in health and its determinants that are associated with social position are important to assess; (2) social and structural determinants of health should be assessed and multiple levels of measurement should be considered; (3) the rationale for methodological choices made and measures chosen should be made explicit; (4) groups to be compared should be simultaneously classified by multiple social statuses; and (5) stakeholders and their communication needs can often be considered in the selection of analytic methods. Although much is understood about the role of social determinants of health in shaping the health of populations, researchers should continue to advance understanding of the pathways through which they operate on particular health outcomes. There is still much to learn and implement about how to measure health disparities, health inequities, and social determinants of health at the national level, and the challenges of health equity persist. We anticipate that the present discussion will contribute to the laying of a foundation for standard practice in the monitoring of national progress toward achievement of health equity. |
Examining socioeconomic health disparities using a rank-dependent Renyi index
Talih M . Ann Appl Stat 2015 9 (2) 992-1023 The Rényi index (RI) is a one-parameter class of indices that summarize health disparities among population groups by measuring divergence between the distributions of disease burden and population shares of these groups. The rank-dependent RI introduced in this paper is a two-parameter class of health disparity indices that also accounts for the association between socioeconomic rank and health; it may be derived from a rank-dependent social welfare function. Two competing classes are discussed and the rank-dependent RI is shown to be more robust to changes in the distribution of either socioeconomic rank or health. The standard error and sampling distribution of the rank-dependent RI are evaluated using linearization and resampling techniques, and the methodology is illustrated using health survey data from the U.S. National Health and Nutrition Examination Survey and registry data from the U.S. Surveillance, Epidemiology and End Results Program. Such data underlie many population-based objectives within the U.S. Healthy People 2020 initiative. The rank-dependent RI provides a unified mathematical framework for eliciting various societal positions with regards to the policies that are tied to such wide-reaching public health initiatives. For example, if population groups with lower socioeconomic position were ascertained to be more likely to utilize costly public programs, then the parameters of the RI could be selected to reflect prioritizing those population groups for intervention or treatment. |
Social determinants of disparities in weight among US children and adolescents
Rossen LM , Talih M . Ann Epidemiol 2014 24 (10) 705-713 e2 PURPOSE: To explore whether contextual variables attenuate disparities in weight among 18,639 US children and adolescents aged 2 to 18 years participating in the National Health and Nutrition Examination Survey, 2001 to 2010. METHODS: Disparities were assessed using the Symmetrized Renyi Index, a new measure that summarizes disparities in the severity of a disease, as well as the prevalence, across multiple population groups. Propensity score subclassification was used to ensure covariate balance between racial and ethnic subgroups and account for individual-level and contextual covariates. RESULTS: Before propensity score subclassification, significant disparities were evident in the prevalence of overweight and/or obesity and the degree of excess weight among overweight/obese children and adolescents. After propensity score subclassification, racial/ethnic disparities in the prevalence and severity of excess weight were completely attenuated within matched groups, indicating that racial and ethnic differences were explained by social determinants such as neighborhood socioeconomic and demographic factors. CONCLUSIONS: The limited overlap in covariate distributions between various racial/ethnic subgroups warrants further attention in disparities research. The attenuation of disparities within matched groups suggests that social determinants such as neighborhood socioeconomic factors may engender disparities in weight among US children and adolescents. |
Invited commentary: can changes in the distributions of and associations between education and income bias estimates of temporal trends in health disparities?
Talih M . Am J Epidemiol 2013 177 (9) 882-4 Chen et al. (Am J Epidemiol. 2013) develop a simulation study for comparing various measures of socioeconomic health disparities when bias can arise from temporal changes in the bivariate distribution of education and income. In this commentary, I argue that, in relation to health, the "meaning" of education cannot be reduced to its socioeconomic value; improved health literacy, for instance, can result in important health benefits. Further, I suggest that unless there is a substantial prior understanding of the data-generating mechanism, directed acyclic graph models should be avoided because causal relationships cannot be inferred from regression. An alternative is to resort to conditional independence graphs, which use only undirected edges. Finally, although the slope index of inequality can, in some specific cases, be seen to reduce bias in temporal comparisons of socioeconomic health disparities, it was not designed for causal inference. The slope index of inequality simply describes the average change in the proportion in poor health when the population is ordered by socioeconomic status. |
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