Public Use Microdata Sample Research Articles

Average age at last live birth in ‘lucky few’ and ‘late baby boom’ birth cohorts in the United States

ABSTRACTThe quantum, tempo, and characteristics of population fertility can change rapidly between birth cohorts. Understanding secular trends in fertility behavior can help inform research concerned with family and health policy. The current investigation is novel in that it uses 'intersectional markers of social stratification' with a large sample of women to examine if the average age at last live birth shifted between two birth cohorts. The analysis uses 41,884 observations from the 1990 Decennial 1% Public Use Microdata Sample (PUMS) file to capture the fertility behavior of lucky few (LF) women (born 1936–1945) and 72,489 observations from the 2010 American Community Survey PUMS file to capture the fertility behavior of late-baby boom (LBB) women (born 1956–1965). The investigation provides empirical evidence that the average age at last live birth decreased in LBB women compared to LF women.

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

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.

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

Understanding the disability-poverty relationship among minority groups within the United States (US) populations may help inform interventions aimed at reducing health disparities. Limited information exists on risk factors for disability and poverty among “Central Asians” (immigrants born in Kazakhstan, Uzbekistan, and other Central Asian regions of the former Soviet Union) in the US. The current cross-sectional analysis used information on 6,820 Central Asians to identify risk factors for disability and poverty. Data from the 2009–2013 Public Use Microdata Sample (PUMS) file from the American Community Survey (ACS) indicate that being married, non-Latino-white, and having higher levels of educational attainment are protective against disability and poverty. In contrast, older age, residing in the Middle Atlantic geographic division, and having limited English language ability are risk factors for both disability and poverty. Research should continue to develop risk profiles for understudied immigrant populations. Expanding knowledge on the well-being of Central Asians in the US may help impact public health interventions and inform health policies.

Predicting Intentional Tax Error Using Open Source Literature and Data

Intentional non-compliance in providing accurate income tax returns, also known as ‘tax evasion’ or ‘intentional error’, has been studied from both attitudinal and socio-demographic perspectives. A significant portion of previous research employs a common set of indicators, which we can exploit by pooling meta-analytically with the hopes of obtaining a unified, well-predicting model of intentional error. Towards this end, we turn to a large, nationally representative data source, namely the Census Bureau’s Public-Use Microdata Samples (PUMS), as our source of covariance between the socio-demographic covariates of interest. Additionally, the same source offers data on potential opportunities of evasion for each PUMS respondent (or agent), in certain line item/taxpayer categories, allowing us to construct distinct error models for these categories. Furthermore, we extend the error model to include attitudinal meta-analysis, by linking the General Social Survey (GSS) to the PUMS through imputation of a GSS covariate that identifies respondents who are more likely to break the law. Our meta-analysis requires an in-depth re-analysis of the selection of previously published results on non-compliance. The result is a comprehensive model of non-compliance that fits historical, published data and that can be applied generically and to specific tax issues.

Prevalence of daytime sleeping in the working population from estimates of nocturnal work shift

Background: Sunlight has been linked the circadian rhythms that regulate sleep. Few studies have attempted to provide estimates on the size of the “daytime sleeper” population. Specific aims: Estimate prevalence of daytime sleepers in the labor force population and identify which demographic characteristics are risk factors for daytime sleeping.Methods: Cross-sectional, community-dwelling, nationally representative, observational study used information on 6,405,063 labor force participants representing 132,682,344 individuals in the contiguous United States. Data from the American CommunitySurvey (ACS), Public Use Microdata Sample (PUMS), 2009-2013 (5-year) file was used to identify daytime sleepers (i.e., those who arrived at work between 7:00 PM and 2:59 AM).Findings: While nighttime sleepers represented 65.9% (n = 87,426,814) of those in the labor force population, daytime sleepers represent 3.3% (n = 4,344,311). Race-ethnic minority status, being disabled, and having low levels of educational attainment were found to be risk factors for daytime sleeping.Conclusions: Even though relatively small, the objectively large (4.3 million) number of daytime sleepers requires sleepresearch to invest resources in understanding how health varies in this population relative to those who primarily sleep in theabsence of sunlight.

The Dawn of Canada’s Century: Hidden Histories. Edited by Gordon Darroch (Montreal, McGill-Queen’s University Press, 2014) 498 pp. $100.00

<i>The Dawn of Canada’s Century: Hidden Histories</i>. Edited by Gordon Darroch (Montreal, McGill-Queen’s University Press, 2014) 498 pp. $100.00

Rates of Allocation for Disability Items by Mode in the American Community Survey

Knowing the prevalence of disability in a population is seen as informative to policy and public health efforts. The American Community Survey (ACS), a yearly, large scale population-based survey administered by the United States (US) Census Bureau, is the predominant source for estimating disability prevalence in the US population. To provide complete data, procedures such as “allocations” are used by the bureau to fix illogical and missing responses to survey questions. This study investigates the rate of allocation in disability items by using the ACS Public Use Microdata Sample (PUMS) 3-year (2009-2011) file. Rates of allocation are interpreted as a measure of “within-person item-completeness” (WIPC)—where the presences of high allocation rates signal low levels of questionnaire completeness. The highest rates of allocations were in found in mail mode for: males (3.5%); those with no college (4.4%); households who only speak Spanish (5.9%); non-married family households (4.3%); and for Non-Latino-Blacks (6.5%). Researchers should continue to explore how the equilibrium of population estimates from ACS sample data vary as a function of demo- and geo-graphic characteristics.

Top-Coding and Public Use Microdata Samples from the U.S. Census Bureau

Public Use Microdata Samples (PUMS) released by the U.S. Census Bureau and other data providers undergo various privacy protection transformations prior to public release of the individual records. We briefly review these methods but focus our attention on "top-coding" as implemented by the Census Bureau. In particular, we provide a brief analysis of the method used for top-coding of records within a hierarchy. We also show that top-coding artificially moves the correlation between two variables (at least one of which is top-coded) closer to zero by the transformation. We then discuss our attempts to recover the un-transformed data, or at least the original correlations, which all failed. In the final section we briefly discuss methods of disclosure avoidance in PUMS files which preserve joint probability distributions.

Disability Prevalence According to a Class, Race, and Sex (CSR) Hypothesis

Disability has been shown to be related in definite ways to social class. In modern industrial societies, disability is influenced by and has the potential to contribute to the production and reproduction of social inequality. However, markers of social stratification processes are sometimes ignored determinants of health. A Class, Race, Sex (CRS) hypothesis is presented to argue that a "low-education disadvantage"; "racial-minority disadvantage"; and "female disadvantage" will compound to affect the risks for being disable. In particular, the CRS hypothesis posits that class is more important than race and the latter more than sex when predicting presence or severity of disability. The cross-sectional study of community-dwelling adults between the ages of 45 and 64 uses data from the American Community Survey (ACS) Public Use Microdata Sample (PUMS) 2008-2012 file. By using 3,429,523 individuals-which weighted equal to 61,726,420-the results of the study suggest the CRS hypothesis applies to both Non-Latino-Blacks and Non-Latino-Whites. There is a "male disadvantage" exception for Non-Latino-Whites. Decreasing between-group differences in health may be achieved by making the age-health association at lower socioeconomic stratum similar to that of the upper socioeconomic strata.

Demographic, Economic, Household, and Health Profile of Grandparents Responsible for Grandchildren.

The objective of this brief report was to outline the demographic, economic, household, and health profile of "grandparents responsible for grandchildren" (GRfGs) in the United States (US). Public Use Microdata Sample (PUMS) from the 2009-2011 American Community Survey (ACS) 3-year file was used to investigate characteristics of GRfGs by race-ethnic groups and the geographical distribution over the US mainland (contiguous states). The 9,177 actual units in the microdata are estimated to represent about 306,122 GRfGs. Population profiles are presented in tables for GRfGs of any age and the characteristics for those aged 65 and over are discussed. Amongst GRfGs aged 65 and over (n=33,168): 27% have ambulatory difficulty; 33% own their home free and clear; 77% have resided in their current residence for more than four years; 41% care for grandchild(ren) with the parent being absent; 61% are married; 36% have a college education; 77% are not in the labor force; and the majority (55%) are Non-Latino-Whites. Qualitative comparisons from descriptive statistics suggest race-ethnic minority GRfGs may be more economically and socially vulnerable than Non-Latino-Whites. Research on GRfGs and efforts on understanding how best to assist them should continue.

Disability Estimates between Same- and Different-Sex Couples: Microdata from the American Community Survey (2009-2011).

Disability and sexual orientation have been used by some to unjustly discriminate against differently-abled and differently-oriented minority groups. Because little is known about the disability rates of individuals in same-sex unions, this technical report presents disability rates by separating couples into: same-sex-female; same-sex-male; different-sex-married; and different-sex-unmarried couples. Data from the American Community Survey (ACS) Public Use Microdata Sample (PUMS) 2009-2011 3-year file is utilized to produce estimates (and their standard errors) for the following six disability items: independent living; ambulatory; self-care; cognitive; hearing; and vision. Estimates of disability by selected geographies-i.e., Public Use Microdata Areas (PUMAs)-are also presented as is a figure showing a PUMA polygon. Qualitative comparisons seem to indicate that: same-sex-female couples have higher rates of disability compared to the other three groups; that in general, disability estimates for individuals in same-sex couples have a greater degree of uncertainty; and that disability-item-allocations are most prevalent in same-sex couples. Because societal marginalization may increase through cumulative processes, public health professionals should continue to seek out ways to identify underserved populations.

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

&lt;p&gt;&lt;strong&gt;Abstract&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;BACKGROUND: &lt;/strong&gt;The American Community Survey (ACS) in the United States (US) collects detailed demographic information on the US population. Pressures to use year-to-year population estimates to analyze “trends” (i.e., between-year differences on the characteristics of interest) have motivated the need to explore how single- or multi-year estimates can be used to investigate changes in US population over time. &lt;strong&gt;OBJECTIVE: &lt;/strong&gt;The specific aim of this manuscript is to provide empirical evidence that between-year differences in population characteristics have difference levels of uncertainty around point-estimates. &lt;strong&gt;METHODS:&lt;/strong&gt; Six ACS Public Use Microdata Sample (PUMS) single year files from 2005 through 2010 are used to empirically show the heterogeneity of uncertainty in “between-year differences” on level of education, for a birth cohort born between 1960 and 1970 of non-Latino-whites and Mexican Latinos/as. &lt;strong&gt;RESULTS: &lt;/strong&gt;The data show the precision of the education estimate decreases as the specificity of the population increases. For example, Mexican’s 99% confidence intervals have wider and more time-varying bandwidths than non-Latino-whites. &lt;strong&gt;CONCLUSIONS: &lt;/strong&gt;Inferring meaningful population change requires the challengeable assumption that between-year differences are not the product of data artifacts. Harvesting reputable ACS data demands further research before between-year differences can be treated as “real change.” &lt;/p&gt;&lt;p&gt; &lt;/p&gt;

Proxy-Reports in the Ascertainment of Disability Prevalence with American Community Survey Data.

Population estimates on disability prevalence inform policy makers and public health professionals. Understanding how factors capable of affecting measurement (e.g., proxy-report) vary in the population is important for establishing level of confidence in sample-derived population estimates. To establish how use of proxy-reports varies by six disability types stratified by sex, race-ethnicity, and age group. Specific aim is achieved by investigating the number of proxy-reports used amongst the disable population. Cross-sectional study using American Community Survey (ACS) Public Use Microdata Sample (PUMS) 3-year file collected during 2009-2011 survey period. Community-dwelling population in continental United States (US). The unweighted count of 6,003,183 individuals in the microdata are said to represent about 193,277,485 individuals in the continental US population. Stratified disability period estimates are computed. Amongst the disable: the number of proxy-reports; allocations; and Person Inflation Ratios (PRIs) are presented by disability type. Half of all the reported disabilities are derived through the use of proxy-report. In addition, high rates of item-allocation and PRIs are generally found in race-ethnic minorities. Proxy-report use and PRIs are lower for those aged > 65-but not allocation rates. Although use of proxy report in the ascertainment of disability varies in complex ways, data suggest prevalence of proxy reports is lowest amongst Non-Latino-Black females ages 21 to 64. Efforts toward providing clinicians with high quality descriptive epidemiology should continue as a reliable thermometer for measuring disability in the population is needed.

PRECISION IN ESTIMATES OF DISABILITY PREVALENCE FOR THE POPULATION AGED 65 AND OVER IN THE UNITED STATES BY RACE AND ETHNICITY.

Populations are aging worldwide. In the United States (US), the older adult (aged ≥65) population will increase rapidly in the decades to come. Identifying public health needs in older adults requires that sample-derived estimates of disability prevalence be produced using transparent methodologies. Produce estimates of disabilities for the US older adult population by race and ethnicity and present measures on the 'level of precision' in the estimates. Cross-sectional study used American Community Survey (ACS) Public Use Microdata Sample (PUMS) 3-year file collected during 2009-2011 survey period. Community dwelling population aged ≥65 in US. The 1,494,893 actual survey participants (unweighted count) are said to represent 40,496,512 individuals after population weights are applied (weighted count). From the weighted counts, the average age is 75, about 56% are females, and most (80%) are Non-Latino-Whites (NLW). Qualitative comparisons provide some evidence that except for hearing, disability prevalence is highest in Non-Latino-Blacks along the following disability items: independent living (25%); ambulatory (34%); self-care (15%); cognitive (11%); and vision (11%). Person inflation ratios, width of 95% confidence interval, and rates of allocations are smaller in NLWs than all the other race-ethnic groups-suggesting disability estimates for NLWs merit the highest level of confidence. Improving measures of health in the older adult population requires that efforts continue to highlight how estimates of disability prevalence have the potential to vary in precision and as a function of various known and unknown factors.

CONTIGUITY PRINCIPLE FOR GEOGRAPHIC UNITS: EVIDENCE ON THE QUANTITY, DEGREE, AND LOCATION OF PUBLIC USE MICRODATA AREA (PUMA) FRAGMENTATION

Social scientists investigating how context varies by geographical location and/or how macro - level phenomenon affects individual outcomes often make use of U.S. Census Bureau Public Use Microdata Sample (PUMS) files where micro - units can only be geographic ally located to Public Use Microdata Area (PUMA) polygons. Most spatial analysis investig a- tions with PUMAs ignore the fact that many of them are multipart polygons — spatially separated polygons that share the same attribute and are stored as a single featu re in a vector file. We briefly discuss the theoretical premises of how ge o- graphical boundaries are created for macro units and investigate the quantity, degree, and location of PUMA fragment a- tion. We argue that the basic contiguity principle (the assumpti on that spatial analysis uses polygon centroids for solid and contiguous geographic units) in spatial dependence analysis is being violated with many PUMAs in the U.S. mainland — where Texas, California, Tennessee, and Illinois merit special attention. Futur e research should outline a method for ha n- dling multipart polygons in spatial and hierarchical analyses.

Maximum Entropy Dasymetric Modeling for Demographic Small Area Estimation

This article describes a framework for maximum entropy dasymetric modeling based on spatial allocations of public use microdata sample (PUMS) files provided by the U.S. Census Bureau. The spatial units of the PUMS (PUMAs; public use microdata areas) are too large for fine‐scale geographic analysis of populations because the common expectation is high degrees of variation within one PUMA (containing about 100,000 people). Limited demographic attribution is available at finer spatial resolutions in census summary tables for tracts and block groups. The described method (i.e., the coupling of spatial allocation procedures with dasymetric modeling) extends the literature and implements related variable associations and limiting variable constraints for allocating microdata household records to census tracts, based on sampling weights imputed using maximum entropy models. We present techniques to quantify household‐level uncertainty and to show how this information is useful for guiding the dasymetric modeling and for improving the choice of limiting and related ancillary variables. We demonstrate our methods with a PUMA in Davidson County, Tennessee. Census summary statistics are used as related variables, and land cover‐derived residential areas are included as limiting variables to refine the solution spatially to a subtract level.本文提出了基于美国人口统计局提供的公众微观采样数据（PUMS）的空间布局分析的最大熵密度建模框架。因一个PUMA(包含10万人的统计区)通常被认为有高的变异度，导致其空间单元对于精细尺度的人口地理分析而言过大。在区块组的人口普查表中少有精细尺度的人口属性收。本文所提方法（即基于密度建模的耦合空间配置过程），基于最大熵模型对采样权重进行填充，扩展了现有方法，实现了相关变量的集成以及面向微观住户记录对空间配置的限制变量约束。我们给出了量化住户水平的不确定性量化技术，展示了该信息如何有效指导了密度建模以及增强了限制变量和相关辅助变量的选择。以西安纳西州戴维森的一个PUMA的基础统计作为相关变量，并将土地覆盖‐居民区分布作为限制变量，演示了将结果空间精细化至向亚调查块层次。

Public Use Microdata Area Fragmentation: Research and Policy Implications of Polygon Discontiguity

Abstract The American Community Survey (ACS) is created by the Unites States Census Bureau and contains the most recent and detailed information on the population. The U.S. Census Bureau releases Public Use Microdata Sample (PUMS) ACS files to allow public entities the ability to examine detailed individual-level data. In order to protect the confidentiality of survey participants, the Census only allows individual-level observations to be geographically referenced with Public Use Microdata Areas (PUMAs)—polygons that contain at least 100,000 people. Microdata files offer the unique advantage of creating custom tabulations on the population that are not made available elsewhere. The advantages from using PUMS files are limited by the typology of PUMAs. Our project fills a gap by introducing the reader to how PUMA typology is produced and how it affects research. The specific aim of this project is to highlight the fact that PUMAs can be fragmented—made up of physically non-adjacent/multi-part polygons. This is important because the treatment of fragmented/multi-part polygons as contiguous spatial entities erroneously imposes a false structure of contiguity that challenges theoretical and statistical assumptions in geographically aware research. By providing evidence from three metropolitan areas in Texas (USA) and displaying the degree of polygon discontiguity concentration by state, we outline some of the implications of polygon discontiguity for research and policy. We compliment our descriptive investigation by discussing solutions in closing and by identifying and discussing the three general elements in polygon fragmentation: quantity, distance, and size.

English fluency of the US immigrants: Assimilation effects, cohort variations, and periodical changes

Using 1% Public-Use Microdata Samples (PUMSs) of the 1980, 1990, and 2000 census and the 2010 American Community Survey (ACS), this study evaluates three simultaneous longitudinal trends in immigrants’ English fluency: the assimilation process, variations across arrival cohorts, and periodical changes. The key findings include that the declining initial English fluency among new immigrants reported in a previous study based on 1980 and 1990 data (Carliner, 2000) was reversed in the 1990s and 2000s. Immigrants who arrived during the 2000s have the highest level of English fluency at the year of entry among all cohorts. Immigrants are assimilating. However, changes in social and linguistic environment in the US during the past two decades have suppressed the advancement of immigrants. The decline in the average English attainment from the 1980s to the 1990s reported in a previous study (Pitkin and Myers, 2011) was found to extend to the 2000s. Using new census data, this study updated the current knowledge on immigrants’ English fluency by revealing a never documented upward trend among recent immigrants and suppressive period effects from 1990 to 2010.

Acute Leukemia in Hispanic Americans: Incidence and Incidence Rate Differences by Nativity.

AbstractAbstract 3160 Introduction:Acute leukemias (AL) have a distinct incidence pattern in Hispanics versus Caucasians, with higher rates of B-cell acute lymphoblastic leukemia (ALL) and acute promyelocytic leukemia (APL), and lower rates of non-APL acute myeloid leukemia (AML). Despite the fact that incidence differentials between foreign- and native-born populations can inform the relative contributions of environmental and genetic factors in cancer etiology, no such investigation has been undertaken in Hispanics with AL. Methods:To better understand heritable genetic versus environmental contributors to occurrence patterns, we assessed AL incidence in a large population of California Hispanics according to birthplace. Cancer incidence data were obtained from the California Cancer Registry, part of the National Cancer Institute’s Surveillance, Epidemiology, and End Results Program. Patients were included if they were living in California and diagnosed between 2000–2009 with AL. Population estimates were obtained from the 2000 Census Summary Files 3, and estimates by nativity were derived from the 20% Integrated Public-Use Microdata Sample of the censuses. Results:Compared to Caucasians, Hispanics had an increased incidence of B-cell ALL and APL, with incidence rate ratios (IRR) of 2.13 (95% confidence interval [CI] 1.93–2.35) and 1.33 (95% CI 1.12–1.57), respectively. There was no difference in B-cell ALL incidence by nativity, with an IRR for foreign- to native-born Hispanics of 1.07 (95% CI 0.85–1.34). However, foreign-born Hispanics had a greater incidence of APL than native-born Hispanics (IRR 1.79, 95% CI 1.11–2.94). Conclusions:Our findings suggest the increased B-cell ALL incidence for foreign-born Hispanics is influenced by heritable genetic factors. Furthermore, the increased incidence of APL for foreign-born Hispanics may result from environmental exposures currently not described and which require further epidemiologic investigation.Table 1:Age-adjusted incidence rates (per 100,000 person-years) of acute leukemias and incidence rate ratios (IRR) by race/ethnicity among non-Hispanic Whites and Hispanics, and nativity among Hispanics*, 2000–2004 and 2000–2009Hematological MalignancyRace/Ethnicity† or NativityMaleFemaleMale and FemaleCasesIncidence Rate* (95% CI)IRR (95% CI)CasesIncidence Rate* (95% CI)IRR (95% CI)CasesIncidence Rate* (95% CI)IRR (95% CI)B-Cell ALL†White4780.78 (0.71–0.85)1.00 (reference)3650.54 (0.48–0.60)1.00 (reference)8430.65 (0.61–0.70)1.00 (reference)Hispanic5421.39 (1.26–1.54)1.80 (1.57–2.06)4511.36 (1.23–1.50)2.53 (2.19–2.94)9931.39 (1.30–1.49)2.13 (1.93–2.35)Non–APL AML†White31184.87 (4.70–5.04)1.00 (reference)24803.17 (3.04–3.30)1.00 (reference)55983.91 (3.81–4.02)1.00 (reference)Hispanic8463.83 (3.54–4.14)0.79 (0.72–0.86)6942.63 (2.42–2.84)0.83 (0.76–0.91)15403.13 (2.96–3.31)0.80 (0.75–0.85)APL†White2070.33 (0.28–0.38)1.00 (reference)1620.24 (0.21–0.29)1.00 (reference)3690.29 (0.26–0.32)1.00 (reference)Hispanic1340.36 (0.30–.044)1.11 (0.87–1.42)1410.40 (0.33–0.47)1.61 (1.26–2.06)2750.38 (0.33–0.43)1.33 (1.12–1.57)B–Cell ALL**US-Born911.28 (1.00–1.63)1.00 (reference)691.10 (0.83–1.42)1.00 (reference)1601.24 (1.04–1.48)1.00 (reference)Foreign-Born1421.33 (1.07–1.65)1.04 (0.75–1.45)1141.23 (0.99–1.50)1.11 (0.80–1.57)2561.32 (1.15–1.52)1.07 (0.85–1.34)Non–APL AML**US–Born1694.37 (3.66–5.18)1.00 (reference)1473.16 (2.65–3.73)1.00 (reference)3163.64 (3.22–4.10)1.00 (reference)Foreign-Born2243.95 (3.34–4.63)0.90 (0.71–1.15)1892.72 (2.31–3.17)0.86 (0.68–1.09)4133.21 (2.86–3.58)0.88 (0.75–1.04)APL**US–Born12******210.29 (0.17–0.47)1.00 (reference)330.23 (0.15–400.34)1.00 (reference)Foreign-Born400.41 (0.27–0.59)***420.42 (0.30–0.59)1.44 (0.78–2.72)820.41 (0.32–0.53)1.79 (1.11–2.94)□Age-adjusted incidence rates (per 100,000 person-years) of acute leukemias and incidence rate ratios (IRR) by race/ethnicity among non-Hispanic Whites and Hispanics age 3 20 in California, 2000–2009*Standardized to the 2000 US population age standard**Age-adjusted incidence rates (per 100,000 person-years) of hematological malignancies and incidence rate ratios by nativity among Hispanics >/= 20 in California, 2000–2004***Insufficient case counts to calculate rate Disclosures:No relevant conflicts of interest to declare.

Residential Segregation, Nativity Status, and Hispanic Living Arrangements in Later Life

This study examined the relationship between residential segregation in metropolitan areas and the living arrangements of middle-aged and older Hispanics. We specifically considered whether the relationship between residential segregation and living arrangements was different depending on nativity status. This study also explored whether measures of assimilation were related to living arrangements. Using data from the 2000 Census Public-Use Microdata Sample (5 %), our multilevel logistic regression models showed that residing in metropolitan areas with higher residential segregation indexes of evenness, isolation, and clustering was related to an increased likelihood of living in a co-resident household versus an independent household. We discovered that the relationship was in the same direction for US-born and foreign-born Hispanics but the relationship was stronger for US-born Hispanics. Finally, we found that as assimilation increased, so did the likelihood of living independently and that persons living in the ten largest immigrant gateway cities were most likely to co-reside as compared to live independently. These results underscored the importance of developing theoretic models of ethnic group living arrangements that include characteristics of both individuals and the community.