Carlos Siordia

Mexican Americans’ Lucky Few and Baby Boom Cohorts: How Is Relative Cohort Size Related to the Likelihood of Being Out-of-Poverty?

Generational cohorts influence individuals’ economic life chances. Retrospective analysis has found that the “Lucky Few” generation had better life chances than previous generations. We focus on Mexican Americans in the United States and offer a prospective analysis to explore how relative cohort size plays a role in the odds of their being out-of-poverty. Using Public Use Microdata Sample files from 1990, 2000, and 2010, we test the hypothesis by comparing Early Baby Boom (those born between 1946 and 1955) and Late Baby Boom (those born between 1956 and 1965) cohorts to the Lucky Few (born between 1936 and 1945) cohort. Models predicting the odds of being out-of-poverty during the peak wage-earning years indicate that belonging to the Lucky Few cohort affords Mexican Americans no economic advantage. Our findings demonstrate that the relative cohort size hypothesis may not always be generalized to Mexican American minority samples.

Number of People in the United States Experiencing Ambulatory and Independent Living Difficulties

Estimating the characteristics of the “disabled” population is necessary for some governments and of interest to health researchers concerned with producing disability prevalence rates. Because generating easy-to-understand estimates of disability in the population is important, this article provides U.S. population estimates for two disability-related measures by using the 2009 to 2011 American Community Survey Public Use Microdata Sample file. The number of people who have “independent living” and “ambulatory” difficulties is calculated from a sample of 9,204,437 (representing >309 million people). The percentage for “disabled” is found to vary by racial and ethnic category, sex, age, citizenship status, educational attainment, and state-level regions divided by weather.

Physical Performance and Short-Term Mortality in Very Old Mexican Americans

Background/Study Context: Physical performance measures have been found to be strong predictors of adverse outcomes in aging populations. Few studies have examined the predictive ability of physical performance measures exclusively within populations of the very old. This study explores the predictive ability of the Short Physical Performance Battery (SPPB) and its three subcomponents—a timed walk, balance test, and repeated timed chair stands—on mortality in a sample of Mexican Americans aged 75 and older. Methods: Logistic regression analyses were used with data from the Hispanic Established Population for the Epidemiological Study of the Elderly (Hispanic EPESE), to investigate the relationship between timed walk, balance test, repeated timed chair stands, and the SPPB and mortality over a 2½-year period. Results: The authors find that being unable to complete the timed walk, the balance test, and repeated timed chair stands, or unable to complete any of the SPPB was significantly associated with mortality over 2½ years. Conclusion: These findings indicate that physical performance measures may be less predictive of short-term mortality in very old Mexican Americans than previously thought. More research is needed to understand this relationship.

Married Once, Twice, and Three or More Times: Data From the American Community Survey

Some people might marry more than once in their lifetime. The demographic characteristics of groups by number of marriages have received little attention. As there is limited knowledge about how demographic profiles differ by number of remarriages, this descriptive report offers detailed tabulations of basic demographic characteristics by number of marriages. The logistic regression predicting the likelihood of having 2 or more marriages in a sample of ever married adults (age > 21) complements the project. By using data from the single-year American Community Survey 2010 Public Use Microdata Sample file, it is found that about 20% of the population reports being married more than once. Regression results indicate that educational attainment, race or ethnic status, age, nativity, disability, and personal income are all associated with the probability of experiencing multiple marriages. Future efforts should continue to provide descriptive characteristics of the population by number of marriages to better understand population-level trends.

Social Security Disability Insurance May Reduce Benefits by 2016: Population at Financial Risk from Reductions

In the United States, 10.9 million people are receiving Social Security Disability Insurance (SSDI) benefits with an average pay of

Extending the Boundaries of Place

12,000 per year. If the U.S. House of Congress fails to enact a new bill by the end of fiscal-year 2016, SSDI benefits are estimated to be reduced by

Precision of Disability Estimates for Southeast Asians in the American Community Survey 2008-2010 Microdata

2,300 per-person per year. In the pass, the U.S. Congress has always found a way to enact new bills capable of maintains benefits at existing levels. The specific aim of this project was to report the number of people potentially at risk for experiencing an economic impact if SSDI benefits are reduced. The cross-sectional analysis used data from the American Community Survey, 2009-2013 Public Use Microdata Sample file. Characteristics on a total of 153,627 actual survey participants were used to generalize findings to 2,748,735 residents of the United States. Results indicate non-Hispanic Whites, the Pacific and South Atlantic geographic divisions are at the largest risk for being affected by changes to SSDI benefits.

Prevalence and Risk for Negative Disability Outcomes Between American Indians-Alaskan Natives and Other Race-Ethnic Groups in the Southwestern United States

Innovation in demography has been driven by new data, tools, and methods and less by theoretical advances. The thesis of this chapter is that new scholarship in demography requires a synthesis of existing theories and conceptualizations of place. More rigorous conceptual models will help enhance our understanding of the processes by which place ‘gets into people.’ Here we focus on measuring place in contextual analysis; this is, ironically, one of the weakest theoretical areas of current practice in demography and other disciplines new to spatial analysis. For the most part, studies of the relationship between demographic and health outcomes and place have been based on several conventional, and we argue naive, assumptions about place. Specifically, places are often administratively bounded, static, and exist as isolated islands removed from meaningful nested and non-nested contexts. With revised conceptual models we will be better able to take advantage of the new spatial data on people and places and the emerging GIS-related technologies of the twenty-first century.

Risk for Disability and Poverty Among Central Asians in the United States

Detailed social data about the United States (US) population were collected as part of the US decennial Census until 2000. Since then, the American Community Survey (ACS) has replaced the long form previously administered in decennial years. The ACS uses a sample rather than the entire US population, and therefore only estimates can be created from the data. This investigation computes disability estimates, standard error, margin of error, and a more comprehensive “range of uncertainty” measure for non-Latino-whites (NLW) and four Southeast Asian groups. Findings reveal that disability estimates for Southeast Asians have a much higher degree of imprecision than for NLW. Within Southeast Asian groups, Vietnamese have the highest level of certainty, followed by the Hmong. Cambodian and Laotian disability estimates contain high levels of uncertainty. Difficulties with self-care and vision contain the highest level of uncertainty relative to ambulatory, cognitive, independent living, and hearing difficulties.

Detecting “real” population changes with American Community Survey data: The implicit assumption of treating between-year differences as “trends”

In the USA, some race-ethnic minorities are unjustly relegated to the margins of society. As a consequence, these groups are more frequently found to have risk profiles associated with adverse health than individuals from the majority group (non-Hispanic Whites). Limited research has been devoted to investigating how American Indians and Alaska Natives (AIANs) differ from other race-ethnic minorities and the majority group with regard to prevalence and risk for self-care, independent living, and ambulatory disabilities. Our investigation attempts to quantify both of these tracks by accounting for race-ethnic and poverty status. Our cross-sectional analysis used nationally representative data from the American Community Survey (ACS) 5-year (2009–2013) Public Use Microdata Sample (PUMS) file to address this literature gap. We selected survey participants from the four states with the largest concentration of AIANs in the USA (Arizona, California, New Mexico, and Oklahoma). We used information on 2,428,233 individuals to generalize prevalence of and risk for disability to 49,994,332 individuals in the Southwest US. We found disability (self-reported) prevalence differed between our six race-ethnic groups in statistically significant and complex ways. Population-weighted logistic regression analyses adjusting for age, sex, and citizenship found AIANs have a higher risk for disability than non-Hispanic Whites, non-Hispanic Asians, and Hispanics. In order to impact public health and build a more equitable society, efforts should continue to identify health disparities. Researchers should continue to advance conceptual frameworks on plausible causal mechanisms between markers of social stratification and disablement processes.