Welfare benefits and family-size decisions of never-married women

Since the 1970s, the out-of-wedlock birthrate has been increasing rapidly in the United States and has prompted several states to propose (and in some cases, enact) legislation to deny access to higher AFDC benefits for families in which the mother gives birth while receiving AFDC. The authors investigate whether AFDC benefit levels are systematically related to the family-size decisions of never-married women. Using a Poisson Regression model, applied to Current Population Survey data from the years 1980-1988, they find that the basic benefit level positively influences family size for white and Hispanic women, but not for black women. Incremental benefits for larger families, however, do not affect family-size decisions, suggesting that reducing (or eliminating) this differential will not necessarily reduce the number of illegitimate births. The basic benefit level positively affects the family-size decision of high school dropouts, but not of high school graduates. This suggests that to discourage nonmarital births, policymakers should consider altering the AFDC benefit structure in such a way as to encourage single mothers to complete high school. However, being a high school dropout might be a proxy for some other underlying characteristic of the woman, and inducing women to complete high school who otherwise would not might have no effect whatsoever on nonmarital births.

Mid-winter temperatures, not spring temperatures, predict breeding phenology in the European starling Sturnus vulgaris

In many species, empirical data suggest that temperatures less than 1 month before breeding strongly influence laying date, consistent with predictions that short lag times between cue and response are more reliable, decreasing the chance of mismatch with prey. Here we show in European starlings (Sturnus vulgaris) that mid-winter temperature ca 50–90 days before laying (8 January–22 February) strongly (r2 = 0.89) predicts annual variation in laying date. Mid-winter temperature also correlated highly with relative clutch size: birds laid later, but laid larger clutches, in years when mid-winter temperatures were lower. Despite a high degree of breeding synchrony (mean laying date 5–13 April = ±4 days; 80% of nests laid within 4.8 days within year), European starlings show strong date-dependent variation in clutch size and productivity, but this appears to be mediated by a different temporal mechanism for integration of supplemental cue (temperature) information. We suggest the relationship between mid-winter temperature and breeding phenology might be indirect with both components correlating with a third factor: temperature-dependent development of the starling\u27s insect (tipulid) prey. Mid-winter temperatures might set the trajectory of growth and final biomass of tipulid larvae, with this temperature cue providing starlings with information on breeding season prey availability (though exactly how remains unknown)

Mid-winter temperatures, not spring temperatures, predict breeding phenology in the European starling Sturnus vulgaris

In many species, empirical data suggest that temperatures less than 1 month before breeding strongly influence laying date, consistent with predictions that short lag times between cue and response are more reliable, decreasing the chance of mismatch with prey. Here we show in European starlings (Sturnus vulgaris) that mid-winter temperature ca 50–90 days before laying (8 January–22 February) strongly (r2 = 0.89) predicts annual variation in laying date. Mid-winter temperature also correlated highly with relative clutch size: birds laid later, but laid larger clutches, in years when mid-winter temperatures were lower. Despite a high degree of breeding synchrony (mean laying date 5–13 April = ±4 days; 80% of nests laid within 4.8 days within year), European starlings show strong date-dependent variation in clutch size and productivity, but this appears to be mediated by a different temporal mechanism for integration of supplemental cue (temperature) information. We suggest the relationship between mid-winter temperature and breeding phenology might be indirect with both components correlating with a third factor: temperature-dependent development of the starling\u27s insect (tipulid) prey. Mid-winter temperatures might set the trajectory of growth and final biomass of tipulid larvae, with this temperature cue providing starlings with information on breeding season prey availability (though exactly how remains unknown)

Electronic Health Literacy Across the Lifespan: Measurement Invariance Study

Background: Electronic health (eHealth) information is ingrained in the healthcare experience to engage patients across the lifespan. Both eHealth accessibility and optimization are influenced by lifespan development, as older adults experience greater challenges accessing and using eHealth tools as compared to their younger counterparts. The eHealth Literacy Scale (eHEALS) is the most popular measure used to assess patient confidence locating, understanding, evaluating, and acting upon online health information. Currently, however, the factor structure of the eHEALS across discrete age groups is not well understood, which limits its usefulness as a measure of eHealth literacy across the lifespan. Objective: The purpose of this study was to examine the structure of eHEALS scores and the degree of measurement invariance among US adults representing the following generations: Millennials (18-35-year-olds), Generation X (36-51-year-olds), Baby Boomers (52-70-year-olds), and the Silent Generation (71-84-year-olds). Methods: Millennials (N=281, mean 26.64 years, SD 5.14), Generation X (N=164, mean 42.97 years, SD 5.01), and Baby Boomers/Silent Generation (N=384, mean 62.80 years, SD 6.66) members completed the eHEALS. The 3-factor (root mean square error of approximation, RMSEA=.06, comparative fit index, CFI=.99, Tucker-Lewis index, TLI=.98) and 4-factor (RMSEA=.06, CFI=.99, TLI=.98) models showed the best global fit, as compared to the 1- and 2-factor models. However, the 4-factor model did not have statistically significant factor loadings on the 4th factor, which led to the acceptance of the 3-factor eHEALS model. The 3-factor model included eHealth Information Awareness, Search, and Engagement. Pattern invariance for this 3-factor structure was supported with acceptable model fit (RMSEA=.07, Δχ2=P>.05, ΔCFI=0). Compared to Millennials and members of Generation X, those in the Baby Boomer and Silent Generations reported less confidence in their awareness of eHealth resources (P<.001), information seeking skills (P=.003), and ability to evaluate and act on health information found on the Internet (P<.001). Results: Young (18-48-year olds, N=411) and old (49-84-year olds, N=419) adults completed the survey. A 3-factor model had the best fit (RMSEA=.06, CFI=.99, TLI=.98), as compared to the 1-factor, 2-factor, and 4-factor models. These 3-factors included eHealth Information Awareness (2 items), Information Seeking (2 items), and Information and Evaluation (4 items). Pattern invariance was supported with the acceptable model fit (RMSEA=.06, Δχ2=P>.05, ΔCFI=0). Compared with younger adults, older adults had less confidence in eHealth resource awareness (P<.001), information seeking skills (P<.01), and ability to evaluate and act upon online health information (P<.001). Conclusions: The eHEALS can be used to assess, monitor uniquely, and evaluate Internet users’ awareness of eHealth resources, information seeking skills, and engagement abilities. Configural and pattern invariance was observed across all generation groups in the 3-factor eHEALS model. To meet gold the standards for factor interpretation (ie, 3 items or indicators per factor), future research is needed to create and assess additional eHEALS items. Future research is also necessary to identify and test items for a fourth factor, one that captures the social nature of eHealth

Heterogeneity in Health Insurance Coverage Among US Latino Adults

We sought to determine the differences in observed and unobserved factors affecting rates of health insurance coverage between US Latino adults and US Latino adults of Mexican ancestry. Our hypothesis was that Latinos of Mexican ancestry have worse health insurance coverage than their non-Mexican Latino counterparts. The National Health Interview Survey (NHIS) database from 1999–2007 consists of 33,847 Latinos. We compared Latinos of Mexican ancestry to non-Mexican Latinos in the initial descriptive analysis of health insurance coverage. Disparities in health insurance coverage across Latino categories were later analyzed in a multivariable logistic regression framework, which adjusts for confounding variables. The Blinder-Oaxaca technique was applied to parse out differences in health insurance coverage into observed and unobserved components. US Latinos of Mexican ancestry consistently had lower rates of health insurance coverage than did US non-Mexican Latinos. Approximately 65% of these disparities can be attributed to differences in observed characteristics of the Mexican ancestry population in the US (e.g., age, sex, income, employment status, education, citizenship, language and health condition). The remaining disparities may be attributed to unobserved heterogeneity that may include unobserved employment-related information (e.g., type of employment and firm size) and behavioral and idiosyncratic factors (e.g., risk aversion and cultural differences). This study confirmed that Latinos of Mexican ancestry were less likely to have health insurance than were non-Mexican Latinos. Moreover, while differences in observed socioeconomic and demographic factors accounted for most of these disparities, the share of unobserved heterogeneity accounted for 35% of these differences

Body Mass Index and Employment-Based Health Insurance

<p>Abstract</p> <p>Background</p> <p>Obese workers incur greater health care costs than normal weight workers. Possibly viewed by employers as an increased financial risk, they may be at a disadvantage in procuring employment that provides health insurance. This study aims to evaluate the association between body mass index [BMI, weight in kilograms divided by the square of height in meters] of employees and their likelihood of holding jobs that include employment-based health insurance [EBHI].</p> <p>Methods</p> <p>We used the 2004 Household Components of the nationally representative Medical Expenditure Panel Survey. We utilized logistic regression models with provision of EBHI as the dependent variable in this descriptive analysis. The key independent variable was BMI, with adjustments for the domains of demographics, social-economic status, workplace/job characteristics, and health behavior/status. BMI was classified as normal weight (18.5–24.9), overweight (25.0–29.9), or obese (≥ 30.0). There were 11,833 eligible respondents in the analysis.</p> <p>Results</p> <p>Among employed adults, obese workers [adjusted probability (AP) = 0.62, (0.60, 0.65)] (<it>P </it>= 0.005) were more likely to be employed in jobs with EBHI than their normal weight counterparts [AP = 0.57, (0.55, 0.60)]. Overweight workers were also more likely to hold jobs with EBHI than normal weight workers, but the difference did not reach statistical significance [AP = 0.61 (0.58, 0.63)] (<it>P </it>= 0.052). There were no interaction effects between BMI and gender or age.</p> <p>Conclusion</p> <p>In this nationally representative sample, we detected an association between workers' increasing BMI and their likelihood of being employed in positions that include EBHI. These findings suggest that obese workers are more likely to have EBHI than other workers.</p

Retiree Health Benefit Coverage and Retirement

Employer-provided health benefits for workers who retire before age 65 has fallen over the last decade. We examine a cohort of male workers from the Health and Retirement Survey to explore the dynamics of retiree health benefits and the relationship between retiree health benefits and retirement behavior. A better understanding of this relationship is important to the policy debate over the best way to increase health coverage for older Americans without reducing work incentives. Concerning the dynamics at work, we find that, between 1992 and 1996, 24 percent of full-time workers who had retiree health benefits lost their coverage, while 15 percent of full-time workers who lacked coverage gained it. Also, of the full-time employed men who were covered by retiree health benefits in 1992 and had retired by 1996, 3 percent were uninsured, and 15 percent were covered by health insurance other than employer-provided insurance. On the relationship between retiree health benefits and retirement, we find that workers with retiree benefits were 29 to 55 percent more likely to retire than those without. We also find that workers who are eligible for retiree health benefits tend to take advantage of them when they are relatively young

Economic Perspectives on Aging

The aging of the American population will be a critical public policy issue in the years ahead. This paper surveys the recent literature on the economics of aging, with a special emphasis on government spending on the aged. The U.S. Census Bureau projects that the proportion of the elderly in the total population will increase while the proportion of the working-age population will decline. This demographic shift implies a significant growth in the number of beneficiaries of major federal entitlement programs. Existing rules and escalating health care costs are expected to lead to fiscal pressures and to pose challenges for economic growth. The paper offers the author’s assessment of the forces that determine government spending on retirees. It also examines how the retirement and health care of older citizens might be financed, and measures the potential impact of different reform proposals. Finally, it provides an introduction to an edited volume, Government Spending on the Elderly