Search

This study examines the impact of racial isolation on high school student performance in North Carolina, a state in the southeast United States. Our research goal is to investigate if increased isolation negatively impacts Black students' academic performance. Employing the North Carolina State Department of Public Instruction (NCDPI) dataset, we test for this using Algebra I and English I scores on End-of-Course exams for ninth graders (N = 134,646) during the 2007-2008 school year. We control for student-level characteristics, such as race and ethnicity, economic disadvantage (eligibility for free and reduced-price lunch), and designation as gifted. We also analyze the effect of school-level characteristics, such as teacher experience, teacher training (advanced degree), teacher accreditation (fully licensed), and the percentage of students who were Black or Latino. Our results suggest racial isolation adversely impacts student performance on Algebra I by as much as three points. With our restricted hierarchical dataset and multi-level modeling, we (a) contribute to the growing body of literature, which finds a negative association between racial isolation/segregation and student performance, and (b) find teacher attributes can moderate some of the adverse student outcomes.

Both food insecurity and diabetes are important public health concerns. For example, diabetes remained a leading cause of mortality both in the United States (U.S.) and globally during the past decade. Meanwhile, an estimated 11% of households endured food insecurity in the U.S. in 2021 with higher rates in the Southeast region. While significant advancements have occurred in better understanding food insecurity, its relationship with diabetes has yielded mixed results. Due to these inconsistent findings, a better understanding of how food insecurity may be associated with diabetes, particularly at the county-level, can improve population health and well-being. This study advanced such an area by undertaking a cross-sectional observational study for the Southeastern region of the U.S. (e.g. Alabama, Arkansas, Mississippi, and Tennessee with 319 counties as the unit of analysis), an area disproportionately impacted by both food insecurity and diabetes. The overall design applied the socio-ecological perspective within a multiscale geographically weighted regression framework or MGWR. MGWR is a recent development and a more advanced approach which allowed adjustments for geographic space and scale. Results showed food insecurity (estimate of 0.28) was positively associated with diabetes but the relation varied in magnitude and significance across space (range of −0.10 to 1.19). That is, food insecurity exhibited a strong, positive association for northwestern Arkansas, a mild association for central Mississippi and Tennessee, and a weaker association for southern Alabama and eastern Tennessee. Households without internet access also exhibited a positive association (estimate of 0.15), as did convenience stores per thousand (estimate of 0.12). These findings add value to our understanding of how geographic space and scale matter when examining health. Public health practitioners can recognize such variations when devising targeted interventions for food insecurity and diabetes care. [ABSTRACT FROM AUTHOR]

Objectives The purpose of this study was to employ simulations to model the probability of mortality from COVID-19 (i.e. coronavirus) for older adults in the United States given at best and at worst cases. Methods This study first examined current epidemiological reports to better understand the risk of mortality from COVID-19. Past epidemiological studies from severe acute respiratory syndrome were also examined given similar virology. Next, at best and at worst mortality cases were considered with the goal of estimating the probability of mortality. To accomplish this for the general population, microdata from the National Health Interview Survey pooled sample (2016, 2017, and 2018 public-use NHIS with a sample of 34,881 adults at least 60 years of age) were utilized. Primary measures included age and health status (diabetes, body mass index, and hypertension). A logit regression with 100,000 simulations was employed to derive the estimates and probabilities. Results Age exhibited a positive association for the probability of death with an odds ratio (OR) of 1.22 (p <.05, 95% confidence interval [CI]: 1.05–1.42). A positive association was also found for body mass index (BMI) (OR 1.03, p <.01, 95% CI: 1.02–1.04) and hypertension (OR 1.36, p <.01, 95% CI: 1.09–1.66) for the at best case. Diabetes was significant but only for the at best case. Discussion This study found mortality increased with age and was notable for the 74–79 age group for the at best case and the 70–79 age group of the at worst case. Obesity was also important and suggested a higher risk for mortality. Hypertension also exhibited greater risk but the increase was minimal. Given the volume of information and misinformation, these findings can be applied by health professionals, gerontologists, social workers, and local policymakers to better inform older adults about mortality risks and, in the process, reestablish public trust. [ABSTRACT FROM AUTHOR]

Objectives Asian Americans are the fastest-growing minority group in the United States, yet little is known about their functional mobility. To overcome such a gap, this study examined the association between demographic/economic characteristics and functional limitations for middle-aged and older Asian Indians, Chinese, and Filipinos. Method This study utilized microdata from the National Health Interview Survey pooled sample (2010–2016 IPUMS NHIS with a sample size of 6,767 Asians). Logit regressions were used to examine factors associated with functional limitations. Measures include age, gender, currently married, education (categorized as less than high school, high school, some college, college, advanced degree), birth and citizenship status, household income, home ownership, types of health insurance (e.g., Medicaid, Medicare, private), and geographic region (i.e., Northeast, Midwest, South, and West). Results Chinese (odds ratio [OR] 0.57, p <.01) and Filipinos (OR 0.74, p <.05) had lower odds for any functional limitations relative to Asian Indians. Currently married and individuals with a higher income were also associated with reduced odds for limitations in the overall analysis. As for the subgroup analysis, there was a positive association between age and the presence of any functional limitations for Asian Indians (OR 1.05, p <.01), Chinese (OR 1.08, p <.01), and Filipinos (OR 1.03, p <.01). In terms of gender, Asian Indian men were less likely (OR 0.51, p <.01), whereas Filipino men were more likely to have limitations (OR 1.09, p <.05). Discussion Asian Indians appeared to have a poorer health profile for limitations in dressing, eating, walking, or working when compared with Chinese and Filipinos. A pronounced difference at older ages was also apparent for Asian Indians by gender and the likelihood of having any limitations increased much faster for Asian Indian women. For Chinese, there was a dramatic increase in functional limitations after age 75 (particularly for women) and the predicted probability for this subgroup approximated 20%. For Filipinos, men were more likely to have limitations. These findings raise interesting questions about the on-set of disability by age and gender for Asian subgroups. [ABSTRACT FROM AUTHOR]

Objective: This study contributes to the body of literature examining smoking cessation and body mass index (BMI) for adults aged 50 and older. Method: Utilizing the 2004 and 2010 waves of the RAND Health and Retirement Study, this analysis utilized Fixed Effects (FE) regression on a sample of 1,316 adults aged 50 and older. Results: Older adults undergo a small change in BMI after a transition from smoking to nonsmoking during a 6-year period, and this occurs after accounting for individual-level unobserved heterogeneity. More specifically, men experience a BMI gain of 1.24 (p< .01) and women experience a BMI gain of 1.58 (p< .01). Discussion: Gerontologists/health professionals can use these results to inform older adults about the potential for a small increase in BMI and, in the process, assuage any apprehensions about excessive weight gain. This insight may encourage a greater number of older adults to cease smoking. [ABSTRACT FROM AUTHOR]

Purpose:The purpose of this study was to showcase an advanced methodological approach to model disability and institutional entry. Both of these are important areas to investigate given the on-going aging of the United States population. By 2020, approximately 15% of the population will be 65 years and older. Many of these older adults will experience disability and require formal care. Methods:A probit analysis was employed to determine which disabilities were associated with admission into an institution (i.e. long-term care). Since this framework imposes strong distributional assumptions, misspecification leads to inconsistent estimators. To overcome such a short-coming, this analysis extended the probit framework by employing an advanced semi-nonparamertic maximum likelihood estimation utilizing Hermite polynomial expansions. Results:Specification tests show semi-nonparametric estimation is preferred over probit. In terms of the estimates, semi-nonparametric ratios equal 42 for cognitive difficulty, 64 for independent living, and 111 for self-care disability while probit yields much smaller estimates of 19, 30, and 44, respectively. Conclusions:Public health professionals can use these results to better understand why certain interventions have not shown promise. Equally important, healthcare workers can use this research to evaluate which type of treatment plans may delay institutionalization and improve the quality of life for older adults. Implications for rehabilitationWith on-going global aging, understanding the association between disability and institutional entry is important in devising successful rehabilitation interventions.Semi-nonparametric is preferred to probit and shows ambulatory and cognitive impairments present high risk for institutional entry (long-term care).Informal caregiving and home-based care require further examination as forms of rehabilitation/therapy for certain types of disabilities. [ABSTRACT FROM AUTHOR]

With the on-going ageing of the United States population, resolving health disparities continues to be a prominent and worthwhile goal, particularly in the areas of promoting minority health and reducing racial/ethnic disparities. This analysis employs the 2004 and 2005 Household Component records from the Medical Expenditures Panel Survey, which correspond to data files H89 and H97, to examine utilisation by race across the entire distribution function; more specifically, applying the behavioural model of health services utilisation and employing a Quantile Regression (QR) framework. This is a noteworthy contribution because the conditional mean may not be the best approximation for a skewed-location distribution. In contrast, QR is robust to outliers and scale effects since the estimation minimises least absolute deviation. The sample consists of 2,525 older adults at least 65 years of age with 303 corresponding to Black and 2,222 corresponding to White. Results suggest older Blacks continue to utilise health services (i.e. office or clinic visits with a physician or medical provider) at lower levels and this is more pronounced at and below the median quantile (i.e. below the 50th cut-off). Usual source of care (USC) continues to play an important role. Beliefs surrounding the need for insurance and medical intervention are also significant and explain some of the racial disparities. Although utilisation disparities persist for older Blacks, collaborative and flexible models of care can reach this group. [ABSTRACT FROM PUBLISHER]

Objectives: This research article tests Litwak and Longino’s first-move hypothesis by taking chain migration into account. Besides adding to the body of literature examining later-life migration and disability using large-scale and current data, my scholarly contribution is noteworthy because this analysis is among the handful which accounts for the influence of historical flows. Methods: Using the American Community Survey (ACS) from 2006 to 2007, the author employs multinomial logit (MNL) to test the likelihood of migrating within the state, outside the state, Florida, or Arizona based on mobility difficulty, personal care limitation, physical limitation, and cognitive difficulty. In addition, the author constructs chain migration variables from Census inflow–outflow tabulations and Internal Revenue Service (IRS) county-to-county migration files. Results: The descriptive statistics and MNL estimates show the probability of migration is greater for individuals with fewer disabilities (i.e., better health), even after controlling for long-standing patterns of established inflows. More specifically, migration to Florida is greater for those without physical limitations and cognitive difficulties, married, with greater income, and higher education levels. Interestingly, the author discovers migration to Florida remains high despite disability status, if and only if the individual comes from an area of chain migration. Discussion: Given the first wave of the baby boom generation having reached retirement age in 2011 and a steady increase in these numbers for the upcoming few decades, examining this group’s geographic mobility serves a practical purpose for economic growth. Several independent studies show migrating retirees boost local businesses and provide increased sales tax revenue. However, states must balance this financial gain with increased use of health services, roadways, and community resources. [ABSTRACT FROM PUBLISHER]