Another 'futile quest'? A simulation study of Yang and Land's Hierarchical Age-Period-Cohort model

Background: Whilst some argue that a solution to the age-period-cohort (APC) 'identification problem' is impossible, numerous methodological solutions have been proposed, including Yang and Land's Hierarchical-APC (HAPC) model: a multilevel model considering periods and cohorts as cross-classified contexts in which individuals exist. Objective: To assess the assumptions made by the HAPC model, and the situations in which it does and does not work. Methods: Simulation study. Simulation scenarios assess the effect of (a) cohort trends in the Data Generating Process (DGP) (compared to only random variation), and (b) grouping cohorts (in both DGP and fitted model). Results: The model only works if either (a) we can assume that there are no linear (or non-linear) trends in periods or cohorts, (b) we control any cohort trend in the model's fixed part and assume there is no period trend, or (c) we group cohorts in such a way that they exactly match the groupings in the (unknown) DGP. Otherwise, the model can arbitrarily reapportion APC effects, radically impacting interpretation. Conclusions: Since the purpose of APC analysis is often to ascertain the presence of period and/or cohort trends, and since we rarely have solid (if any) theory regarding cohort groupings, there are few circumstances in which this model achieves what Yang and Land claim it can. The results bring into question findings of several published studies using the HAPC model. However, the structure of the model remains a conceptual advance that is useful when we can assume the DGP has no period trends

County-Level Hispanic Ethnic Density and Cardiovascular Disease Mortality.

Background Hispanics are the fastest growing ethnic group in the United States, and little is known about how Hispanic ethnic population density impacts cardiovascular disease ( CVD ) mortality. Methods and Results We examined county-level deaths for Hispanics and non-Hispanic whites from 2003 to 2012 using data from the National Center for Health Statistics' Multiple Cause of Death mortality files. Counties with more than 20 Hispanic deaths (n=715) were included in the analyses. CVD deaths were identified using International Classification of Diseases, Tenth Revision (ICD-10), I00 to I78, and population estimates were calculated using linear interpolation from 2000 and 2010 census data. Multivariate linear regression was used to examine the association of Hispanic ethnic density with Hispanic and non-Hispanic white age-adjusted CVD mortality rates. County-level age-adjusted CVD mortality rates were adjusted for county-level demographic, socioeconomic, and healthcare factors. There were a total of 4 769 040 deaths among Hispanics (n=382 416) and non-Hispanic whites (n=4 386 624). Overall, cardiovascular age-adjusted mortality rates were higher among non-Hispanic whites compared with Hispanics (244.8 versus 189.0 per 100 000). Hispanic density ranged from 1% to 96% in each county. Counties in the highest compared with lowest category of Hispanic density had 60% higher Hispanic mortality (215.3 versus 134.2 per 100 000 population). In linear regression models, after adjusting for county-level demographic, socioeconomic, and healthcare factors, increasing Hispanic ethnic density remained strongly associated with mortality for Hispanics but not for non-Hispanic whites. Conclusions CVD mortality is higher in counties with higher Hispanic ethnic density. County-level characteristics do not fully explain the higher CVD mortality among Hispanics in ethnically concentrated counties

Dynamics of Racial Residential Segregation and Gentrification in New York City

Racial residential segregation is interconnected with several other phenomena such as income inequalities, property values inequalities, and racial disparities in health and education. Furthermore, recent literature suggests the phenomenon of gentrification as a cause of perpetuation or increase of racial residential segregation in some American cities. In this paper, we analyze the dynamics of racial residential segregation for white, black, Asian, and Hispanic citizens in New York City in 1990, 2000, and 2010. It was possible to observe that segregation between white and Hispanic citizens and between white and Asian ones has grown, while segregation between white and black is relatively stable. Furthermore, we analyzed the per capita income and the Gini coefficient in each segregated zone, showing that the highest inequalities occur in the zones where there is an overlap of high-density zones of pair of races. Focusing on the changing of the density of population across the city during these 20 years, and by analyzing white and black people's segregation, our analysis reveals that a positive flux of white (black) people is associated with a substantial increase (decrease) of the property values, as compared with the city mean. Furthermore, by clustering the region with the higher density of black citizens, we measured the variation of area and displacement of the four most significant clusters from 1990 to 2010. The large displacements ( & AP; 1.6 k m ) observed for two of these clusters, namely, one in the neighborhood of Harlem and the other inside the borough of Brooklyn, led to the emergence of typically gentrified regions

Do measures matter? Comparing surface-density-derived and census-tract-derived measures of racial residential segregation

<p>Abstract</p> <p>Background</p> <p>Racial residential segregation is hypothesized to affect population health by systematically patterning health-relevant exposures and opportunities according to individuals' race or income. Growing interest into the association between residential segregation and health disparities demands more rigorous appraisal of commonly used measures of segregation. Most current studies rely on census tracts as approximations of the local residential environment when calculating segregation indices of either neighborhoods or metropolitan areas. Because census tracts are arbitrary in size and shape, reliance on this geographic scale limits understanding of place-health associations. More flexible, explicitly spatial derivations of traditional segregation indices have been proposed but have not been compared with tract-derived measures in the context of health disparities studies common to social epidemiology, health demography, or medical geography. We compared segregation measured with tract-derived as well as GIS surface-density-derived indices. Measures were compared by region and population size, and segregation measures were linked to birth record to estimate the difference in association between segregation and very preterm birth. Separate analyses focus on metropolitan segregation and on neighborhood segregation.</p> <p>Results</p> <p>Across 231 metropolitan areas, tract-derived and surface-density-derived segregation measures are highly correlated. However overall correlation obscures important differences by region and metropolitan size. In general the discrepancy between measure types is greatest for small metropolitan areas, declining with increasing population size. Discrepancies in measures are greatest in the South, and smallest in Western metropolitan areas. Choice of segregation index changed the magnitude of the measured association between segregation and very preterm birth. For example among black women, the risk ratio for very preterm birth in metropolitan areas changed from 2.12 to 1.68 for the effect of high versus low segregation when using surface-density-derived versus tract-derived segregation indices. Variation in effect size was smaller but still present in analyses of neighborhood racial composition and very preterm birth in Atlanta neighborhoods.</p> <p>Conclusion</p> <p>Census tract-derived measures of segregation are highly correlated with recently introduced spatial segregation measures, but the residual differences among measures are not uniform for all areas. Use of surface-density-derived measures provides researchers with tools to further explore the spatial relationships between segregation and health disparities.</p

A New Index for Comparing the Diversity of Population Inflows and Population Stocks

The paper introduces a new “diversification index” (DIV), which compares the composition of the current or recent population inflow and the composition of pre-existing population stock, with positive (negative) values signifying a process generating more (less) diversity in the stock. Higher absolute values for DIV signify larger differences in the composition of the inflows and the pre-existing stocks of population. DIV is easy to compute and interpret, adaptable to handle population inflows or outflows, and widely applicable to a variety of phenomena. The paper defines DIV, discusses its properties, and calculates it for several hypothetical cases as a way of showing its intuitive appeal, such as how it would reflect a neighborhood gentrification scenario. DIV indices for both race and income groupings are computed from 1992 to 2006 for three neighborhoods in Chicago to demonstrate how inter-temporal trends in DIV provide insights into neighborhood dynamics. Finally, the paper discusses extensions, potential weaknesses, and other caveats related to the use of DIV in future applied research

Changes in the nutritional status of Bolivian women 1994-1998: demographic and social predictors

Introduction: Bolivia, as one of the poorest Latin American countries, has dealt with the problems of undernutrition for the last 50 y. Little importance has been given to the increase in overweight and obesity among the population, despite the scientific evidence linking overweight and obesity with mortality and morbidity. Objective: To describe the social and demographic determinants of the nutritional status among women in Bolivia between 1989 and 1998 to gain a better understanding of the nutrition transition phenomena and to identify urgent research needs. Methodology: Secondary analysis of the raw data of the Bolivian National Demographic and Health Surveys of 1994 and 1998. Changes in the prevalence of underweight, obesity and overweight are described by sociodemographic characteristics of Bolivian women. Social and demographic determinants of nutritional status have been fitted into a logistic model. Results: The prevalence of overweight (defined as 25 less than or equal to BMI < 30 kg/m(2)) among women of reproductive age (20-44 y) increased by 9 percentage points between 1994 and 1998 (P < 0.001), while the prevalence of normal BMI decreased by 10 percentage points (P < 0.001). The decrease in the prevalence of underweight (defined as BMI <18.5 kg/m(2)) from 2.4% in 1994 to less than 1% in 1998 was statistically significant (P < 0.001). Obesity (defined as BMI &GE;30 kg/m(2)) was positively associated with geographical region (P = 0.001), educational level (P < 0.001), age (P = 0.003) and total number of children (P = 0.001) and negatively associated to rural locality (P = 0.001) and native languages(P < 0.001). Overweight was inversely associated with rural locality (P = 0.013) and with Quechua language (P = 0.04), while the total number of children (P < 0.001) and year of survey (P < 0.001) were positively associated. Underweight decreased dramatically (P < 0.001), being positively associated with the region of residence (P = 0.04) and inversely associated with the total number of children (P = 0.006). Conclusion: The present study suggests that the population of Bolivia is in a transitional stage, with overweight becoming as much of a problem as undernutrition