Proximate sources of population sex imbalance in india

There is a population sex imbalance in India. Despite a consensus that this imbalance is due to excess female mortality, the specific source of this excess mortality remains poorly understood. I use microdata on child survival in India to analyze the proximate sources of the sex imbalance. I address two questions: when in life does the sex imbalance arise, and what health or nutritional investments are specifically responsible for its appearance? I present a new methodology that uses microdata on child survival. This methodology explicitly takes into account both the possibility of naturally occurring sex differences in survival and possible differences between investments in their importance for survival. Consistent with existing literature, I find significant excess female mortality in childhood, particularly between the ages of 1 and 5, and argue that the sex imbalance that exists by age 5 is large enough to explain virtually the entire imbalance in the population. Within this age group, sex differences in vaccinations explain between 20% and 30% of excess female mortality, malnutrition explains an additional 20%, and differences in treatment for illness play a smaller role. Together, these investments account for approximately 50% of the sex imbalance in mortality in India.India has a serious population sex imbalance. There are around 108 men for every 100 women in the country as a whole. In a country with the same level of development and typical mortality patterns, one would expect to see about 100 men for every 100 women. Sen (1990, 1992) coined the phrase “missing women” to describe this population imbalance, and attributed it to sex discrimination. Consistent with this view, other authors (Kishor 1993; Visaria 1971) have argued, based on census data and other sources, that the sex imbalance is almost certainly due to excess female mortality.There is a very large literature on the underlying sources of parental sex preferences (see, e.g., Agnihotri 2000; Agnihotri, Palmer-Jones, and Parikh 2002; Murthi, Mamta, and Dreze 1995; Qian 2008; Rosenzweig and Schultz 1982) that focuses on the relative contributions of factors such as female labor-force participation and female education in determining overall sex ratios. A second literature, more closely related to this work, focuses on the proximate sources of female mortality¹: that is, conditional on preferences, what specific treatments (or lack thereof) are responsible for the differences in mortality (Basu 1989; Borooah 2004; Griffiths, Matthews, and Hinde 2002; Mishra, Roy, and Retherford 2004; Pande 2003).Despite this second literature, a coherent overall picture of the proximate sources of excess female mortality is still lacking. This article focuses on two primary questions: at what ages does most of the excess female mortality occur, and what is the relative contribution of various forms of neglect to this excess mortality? In contrast to most of the existing literature, I am concerned not only with whether various health and nutrition inputs play a role, but also with how large that role is.The methodology used here, formally outlined in the following section, differs from most of the previous literature in two ways. First, I use data from Africa on sex differences in mortality and child health investments as a comparison for India. Existing literature (e.g., Das Gupta 1987) has often focused solely on sex differences in mortality in India. However, because when boys and girls receive equal treatment by their parents or caregivers, boys are more likely to die, the lack of a comparison group likely understates the extent of excess female mortality. Second, when considering the proximate sources of excess female mortality in childhood, I consider not only the difference in treatment but also the importance of that treatment for mortality (i.e., the difference in mortality probability with and without treatment). Multiplying these two factors gives full information about the importance of each element for understanding the overall excess female mortality. The literature generally has considered only the difference across sexes in each treatment; it has not considered the importance of these treatments in mortality, which is crucial for evaluating the relative contribution of each input (Basu 1989; Borooah 2004; Griffiths et al. 2002; Mishra et al. 2004; Pande 2003).²I first use microdata to identify exactly the age source of the excess female mortality in childhood and to explore the importance of childhood sex bias in the overall imbalance. This question has, of course, been addressed by other researchers (Das Gupta and Bhat 1997; Dyson 1984; Klasen 1994; Padmanabha 1982; Preston and Bhat 1984); the work here uses a new methodology, but the results largely echo what has been found in the previous literature. In particular, the results suggest important variations within young children. All areas of India see relatively little excess female mortality between the ages of a few months and 2 years, yet substantial excess mortality between 2 and 5 years of age. I also present evidence on the contribution of the under-5 sex ratio bias to the overall bias. Using demographers’ life tables (Coale, Demeny, and Vaughn 1983), I calculate the expected sex ratio overall in India, assuming the empirically observed sex ratio at 5 years of age, and normal mortality thereafter. This exercise suggests that virtually all the sex ratio imbalance in the country can be explained by excess under-5 mortality.Following this analysis, I move on to the primary contribution of the article, exploring the proximate sources of this excess female mortality between the ages of 2 and 5. Consistent with previous literature, I focus on biases in nutrition, preventative medicine, and medical treatment. The evidence here suggests that, contrary to some of the previous literature, sex differences in vaccinations play a very large role in the sex imbalance, explaining about 20% to 30%. Malnutrition explains about 20%. Interestingly, differences in treatment for respiratory infections and diarrhea together explain only about 5% of the imbalance, and approximately 50% is left unexplained by these childhood investments.The results here have potentially important policy implications, suggesting that increases in vaccinations for girls could have a large effect on the overall sex imbalance in India.     

Understanding links between adolescent health and educational attainment

The educational and economic consequences of poor health during childhood and adolescence have become increasingly clear, with a resurgence of evidence leading researchers to reconsider the potentially significant contribution of early-life health to population welfare both within and across generations. Meaningful relationships between early-life health and educational attainment raise important questions about how health may influence educational success in young adulthood and beyond, as well as for whom its influence is strongest. Using data from the National Longitudinal Survey of Youth 1997, I examine how adolescents’ health and social status act together to create educational disparities in young adulthood, focusing on two questions in particular. First, does the link between adolescent health and educational attainment vary across socioeconomic and racial/ethnic groups? Second, what academic factors explain the connection between adolescent health and educational attainment? The findings suggest that poorer health in adolescence is strongly negatively related to educational attainment, net of both observed confounders and unobserved, time-invariant characteristics within households. The reduction in attainment is particularly large for non-Hispanic white adolescents, suggesting that the negative educational consequences of poor health are not limited to only the most socially disadvantaged adolescents. Finally, I find that the link between adolescent health and educational attainment is explained by academic factors related to educational participation and, most importantly, academic performance, rather than by reduced educational expectations. These findings add complexity to our understanding of how the educational consequences of poor health apply across the social hierarchy, as well as why poor health may lead adolescents to complete less schooling.In a presidential address to the Population Association of America, Palloni (2006) emphasized the need for research on early-life health as a mechanism in the intergenerational transmission of socioeconomic status. Although poor health is well known as a consequence of childhood and family socioeconomic conditions, it is also clear that illness during childhood and adolescence has lasting educational and socioeconomic effects (Case, Fertig, and Paxson 2005; Conley and Bennett 2000; Smith 2005). What remains less clear is how health early in life influences educational success in young adulthood and beyond. Do those with a health disadvantage graduate from high school at lower rates, for example, because they perform poorly in school or because they and their families develop reduced expectations for the future? In addition, how do race/ethnicity and socioeconomic status complicate these relationships? Our understanding of how health’s influence on educational attainment differs across groups is unclear.This article considers these complexities by asking several questions. It confirms that health during adolescence is strongly negatively associated with educational attainment and then examines this relationship in greater depth than is typical. First, I examine variation in the link between health and educational attainment along socioeconomic and racial/ethnic lines. Are the families of adolescents in poorer health better able to mitigate the negative educational consequences of a condition if they are socially and/or economically advantaged? Or do youths in these families suffer an equal or greater disadvantage? Second, I evaluate the role of academic factors—specifically, educational participation, performance, and expectations—that may explain the connection between adolescents’ health and educational attainment. I examine these questions with data from the National Longitudinal Survey of Youth 1997 (NLSY97), with an overall goal of understanding the ways in which health and social status act together to create educational disparities in the early life course.     

Early teen marriage and future poverty

Both early teen marriage and dropping out of high school have historically been associated with a variety of negative outcomes, including higher poverty rates throughout life. Are these negative outcomes due to preexisting differences, or do they represent the causal effect of marriage and schooling choices? To better understand the true personal and societal consequences, in this article, I use an instrumental variables (IV) approach that takes advantage of variation in state laws regulating the age at which individuals are allowed to marry, drop out of school, and begin work. The baseline IV estimate indicates that a woman who marries young is 31 percentage points more likely to live in poverty when she is older. Similarly, a woman who drops out of school is 11 percentage points more likely to be poor. The results are robust to a variety of alternative specifications and estimation methods, including limited information maximum likelihood (LIML) estimation and a control function approach. While grouped ordinary least squares (OLS) estimates for the early teen marriage variable are also large, OLS estimates based on individual-level data are small, consistent with a large amount of measurement error.Historically, individuals were allowed to enter into a marriage contract at a very young age. In Ancient Rome, the appropriate minimum age was regarded as 14 for males and 12 for females. When Rome became Christianized, these age minimums were adopted into the ecclesiastical law of the Catholic Church. This canon law governed most marriages in Western Europe until the Reformation. When England broke away from the Catholic Church, the Anglican Church carried with it the same minimum age requirements for the prospective bride and groom. The minimum age requirements of 12 and 14 were eventually written into English civil law. By default, these provisions became the minimum marriage ages in colonial America. These common laws inherited from the British remained in force in America unless a specific state law was enacted to replace them (see “Marriage Law,” Encyclopædia Britannica 2005; http://www.britannica.com).While Roman, Catholic, English, and early American law may have allowed marriage at 12 for girls and 14 for boys, many questioned the advisability of such early unions. Researchers and policymakers around the turn of the twentieth century recognized that teens may be especially ill-prepared to assume the familial responsibilities and financial pressures associated with marriage.¹ As a result of the changing economic and social landscape of the United States, in the latter part of the nineteenth century and throughout the twentieth century, individual states began to slowly raise the minimum legal age at which individuals were allowed to marry. In the United States, as in most developed countries, age restrictions have been revised upward so that they are now between 15 and 21 years of age.During this same time period, dramatic changes were also occurring in the educational system of the United States (see Goldin 1998, 1999; Goldin and Katz 1997, 2003; Lleras-Muney 2002). Free public schooling at the elementary level spread across the United States in the middle of the nineteenth century, and free secondary schooling proliferated in the early part of the twentieth century. As secondary schooling became more commonplace, states began to pass compulsory schooling laws. States often also passed child labor laws that stipulated minimum age or schooling requirements before a work permit would be granted. These state-specific compulsory schooling and child labor laws are correlated with the legal restrictions on marriage age, indicating that it might be important to consider the impact of all the laws simultaneously.There are at least two rationales often given for the use of state laws as policy instruments to limit teenagers’ choices. The first argument is that teens do not accurately compare short-run benefits versus long-run costs. If teens are making myopic decisions, restrictive state laws could prevent decisions they will later regret. It is also argued that the adverse effects associated with teenagers’ choices impose external costs on the rest of society. If these effects can be prevented, external costs (such as higher welfare expenditures) would also argue for restrictive state laws. Both teenage marriage and dropping out of high school are closely associated with a variety of negative outcomes, including poverty later in life. To assess the relevance of either argument, however, it is important to know whether the observed effects are causal.Any observed negative effects may be due to preexisting differences rather than a causal relationship between teen marriage (or schooling choices) and adverse adult outcomes. Women who marry as teens or drop out of school may come from more disadvantaged backgrounds or possess other unobserved characteristics that would naturally lead to worse outcomes. For example, teens choosing to marry young might have lower unobserved earnings ability, making it hard to draw conclusions about the causal relationship between teenage marriage and poverty.To identify the effect of a teenager’s marriage and schooling choices on future poverty, I use state-specific marriage, schooling, and child labor laws as instruments. Variation in these laws across states and over time can be used to identify the causal impact that teen marriage and high school completion have on future economic well-being. Although compulsory schooling laws have been used as instruments in a variety of settings, this appears to be the first time marriage laws have been used as instruments. The idea of the marriage law instrument is that states with restrictive marriage laws will prevent some teenagers from marrying who would have married young had they lived in a state with more permissive laws.Using the marriage, schooling, and labor laws affecting teens as instruments for early marriage and high school completion, I find strong negative effects for both variables on future poverty status. The baseline instrumental variables (IV) estimates imply that a woman who marries young is 31 percentage points more likely to live in poverty when she is older. Similarly, a woman who drops out of school is 11 percentage points more likely to be living in a family whose income is below the poverty line. The IV results are robust to a variety of alternative specifications and estimation methods, including limited information maximum likelihood (LIML) estimation and a control function approach. In comparison, the ordinary least squares (OLS) estimates are very sensitive to how the data is aggregated, particularly for the early marriage variable. OLS estimates using grouped data are also large, while OLS estimates using individual-level data indicate a small effect for early teen marriage. Auxiliary data indicate a large amount of measurement error in the early marriage variable, suggesting the presence of attenuation bias in the individual-level OLS estimates.The remainder of the article proceeds as follows. I first briefly review the negative outcomes associated with teenage marriage and dropping out of school and discuss alternative perspectives on why teens might make these decisions. The following section describes the data and presents OLS estimates. The next section discusses the early marriage, compulsory schooling, and child labor laws that will be used as instruments. I then present the instrumental variable estimates and conduct several specification and robustness checks, including a discussion of measurement error issues and a reconciliation with the literature on teenage childbearing.     

Education and Male-Female Differences in Later-Life Cognition: International Evidence From Latin America and the Caribbean

This study explores the role of early-life education for differences in cognitive functioning between men and women aged 60 and older from seven major urban areas in Latin America and the Caribbean. After documenting statistically significant differences in cognitive functioning between men and women for six of the seven study sites, I assess the extent to which these differences can be explained by prevailing male-female differences in education. I decompose predicted male-female differences in cognitive functioning based on various statistical models for later-life cognition and find robust evidence that male-female differences in education are a major driving force behind cognitive functioning differences between older men and women. This study therefore suggests that early-life differences in educational attainment between boys and girls during childhood have a lasting impact on gender inequity in cognitive functioning at older ages. Increases in educational attainment and the closing of the gender gap in education in many countries in Latin America and the Caribbean may thus result in both higher levels and a more gender-equitable distribution of later-life cognition among the future elderly in those countries.     

Spousal Mobility and Earnings

An important finding in the literature on migration has been that the earnings of married women typically decrease with a move, while the earnings of married men often increase with a move, suggesting that married women are more likely to act as the “trailing spouse.” This article considers a related but largely unexplored question: what is the effect of having an occupation that is associated with frequent migration on the migration decisions of a household and on the earnings of the spouse? Further, how do these effects differ between men and women? The Public Use Microdata Sample from the 2000 U.S. decennial census is used to calculate migration rates by occupation and education. The analysis estimates the effects of these occupational mobility measures on the migration of couples and the earnings of married individuals. I find that migration rates in both the husband’s and wife’s occupations affect the household migration decision, but mobility in the husband’s occupation matters considerably more. For couples in which the husband has a college degree (regardless of the wife’s educational level), a husband’s mobility has a large, significant negative effect on his wife’s earnings, whereas a wife’s mobility has no effect on her husband’s earnings. This negative effect does not exist for college-educated wives married to non-college-educated husbands.In the substantial literature on the relationship between migration and earnings, an important finding has been that the earnings of married women typically decrease with a move, while the earnings of married men often increase with a move. This is consistent with the notion that married women are more likely to act as the “trailing spouse” or to be a “tied mover.” This article considers a related but largely unexplored question: what is the effect of having an occupation that is associated with frequent migration on the migration decisions of a household as well as on the earnings of the spouse? And how do these effects differ between men and women?There are three reasons to move beyond the previous analysis of household moves to studying the effect of occupational mobility on migration and earnings. First, the analysis of changes in employment and earnings of movers is only part of a broader discovery concerning the extent to which the earnings of husbands and wives are affected by the ability to move to or stay in optimal locations. Second, the existing literature relies on the comparison of movers to nonmovers. Even longitudinal comparisons will not completely eliminate the bias in this comparison because movers likely differ in their earnings growth, not just the level of premigration earnings. Third, the methods used in the literature often do not adequately adjust for occupational differences between men and women, so it is difficult to know whether the current findings in the literature are the result of differences in jobs held by men and women, or rather are the result of differences in influence on location decisions. The question pursued in this article is, controlling for an individual’s own occupation and the earnings potential in that occupation, how does the migration rate in a spouse’s occupation affect one’s own labor market outcomes?This article uses the Public Use Microdata Sample (PUMS) from the 2000 U.S. decennial census to calculate mobility measures by occupation and education class. Mobility is measured by the fraction of workers who, in the past five years, have either (a) changed metropolitan area or (b) if in a nonmetropolitan area, changed Public Use Microdata Area (PUMA).¹ Using the sample of white, non-Hispanic married couples between the ages of 25 and 55 in the 2000 census, I perform migration and earnings analyses separately for four groups of couples: both have college degrees (“power couples”), only the husband has a college degree, only the wife has a college degree; and neither has a college degree.Results indicate that the mobility rates in both the husband’s and wife’s occupation affect the household migration decision, but mobility in the husband’s occupation matters considerably more. Comparison analysis for never-married individuals indicates that among individuals with college degrees, never-married men and women are equally responsive to occupation mobility in their migration behavior.The earnings analysis uses occupation fixed-effects and average wage in occupation-education class to control for substantial heterogeneity in earnings potential. For couples in which the husband has a college degree, the wife’s mobility has no effect on the husband’s earnings, regardless of the wife’s education. However, the husband’s mobility has a large, significant negative effect on the wife’s earnings. This negative effect does not exist for couples in which only the wife has a college degree.     

Cognitive Disparities: The Impact of the Great Depression and Cumulative Inequality on Later-Life Cognitive Function

Population aging has driven a spate of recent research on later-life cognitive function. Greater longevity increases the lifetime risk of memory diseases that compromise the cognitive abilities vital to well-being. Alzheimer’s disease, thought to be the most common underlying pathology for elders’ cognitive dysfunction (Willis and Hakim 2013), is already the sixth leading cause of death in the United States (Alzheimer’s Association 2016). Understanding social determinants of pathological cognitive decline is key to crafting interventions, but evidence is inconclusive for how social factors interact over the life course to affect cognitive function. I study whether early-life exposure to the Great Depression is directly associated with later-life cognitive function, influences risky behaviors over the life course, and/or accumulates with other life-course disadvantages. Using growth curve models to analyze the Health and Retirement Study, I find that early-life exposure to the Great Depression is associated with fluid cognition, controlling for intervening factors—evidence for a critical period model. I find little support for a social trajectory model. Disadvantage accumulates over the life course to predict worse cognitive function, providing strong evidence for a cumulative inequality model.     

Domestic Outsourcing,Housework Shares and Subjective Time Pressure: Gender Differences in the Correlates of Hiring Help

We use data from matched dual earner couples from the Australian Time Use Survey 2006 (n = 926 couples) to investigate predictors of different forms of domestic outsourcing, and whether using each type of paid help is associated with reduced time in male or female-typed tasks, narrower gender gaps in housework time and/or lower subjective time pressure. Results suggest domestic outsourcing does not substitute for much household time, reduces domestic time for men at least as much as for women, and does not ameliorate gender gaps in domestic labor. The only form of paid help associated with significant change in gender shares of domestic work was gardening and maintenance services, which were associated with women doing a greater share of the household total domestic work. We found no evidence that domestic outsourcing reduced feelings of time pressure. We conclude that domestic outsourcing is not effective in ameliorating time pressures or in changing gender dynamics of unpaid work.     

Social Networks,Social Cohesion,and Later-Life Health

Our study contributes to the literature acknowledging the joint role of social networks and social cohesion in shaping individual’s health, focusing on the older population aged 50 and over. Exploiting rich ego-centered social network data from the Survey of Health, Ageing and Retirement in Europe and following the conceptual model of social integration and health proposed by Berkman et al. (Soc Sci Med 51:843–857. doi:10.1016/S0277-9536(00)00065-4, 2000), we estimate multilevel models of self-reported and observer-measured later-life health outcomes. These models simultaneously account for (a) characteristics of 39,551 respondents’ personal social networks and (b) a measure of social cohesion—namely, participation in social organizations—across 57 Continental European regions, clustered in 14 countries. We find significant associations between individuals’ health and various social network characteristics (size, support, quality) as well as social cohesion. Moreover, cross-level interaction effects suggest that the social-network-health nexus is contextually bound. We conclude with a discussion of limitations and perspectives for future research.     

Health profiles and profile-specific health expectancies of older women and men: The Netherlands

This study focuses on gender differences in health profiles, and examines which health profiles drive gender differences in remaining life expectancy in women and men aged 65 and over in The Netherlands. Data from the first two cycles of the Longitudinal Aging Study Amsterdam (n = 2,141 and 1,659, respectively) were used to calculate health profiles for individuals of 65-85 years. For both women and men, six profiles were found: I. cancer; II. "other" chronic diseases; III. cognitive impairment; IV. frailty or multimorbidity; V. cardiovascular diseases; and VI. good health. The further characterization of these types showed some gender differences. Remaining life expectancy for women was greater than for men in each health profile. A decomposition into health expectancies showed that both women and men could expect to live about 5 years in good health from age 66. The greatest gender differences in years spent with health problems were found for profile IV and for profile III. Their greater number of years spent in these health states have direct consequences for the type and cost of care women need.     

Household air pollution as a silent killer: women’s status and solid fuel use in developing nations

Household air pollution is a leading cause of death globally, as 4.3 million people die prematurely each year from illness attributable to use of solid fuels (WHO 2016a). Many studies contend that gender inequalities are likely to greatly shape the global distribution of solid fuel use and its negative health consequences. We conduct an analysis of 91 developing nations using structural equation models on the prevalence of female indoor air pollution deaths among women and the ratio of female to male indoor air pollution deaths. The results illustrate that women’s status is a robust predictor of solid fuel use, and that improved women’s status also correlates directly with lower female to male indoor air pollution deaths ratios and indirectly with reduced female death prevalence through lower solid fuel dependence. Women’s status additionally mediates the effects of some other notable predictors, such as economic development. Overall, the results bring attention to a “silent killer” in less-developed nations and illustrate that greater female empowerment is an important avenue in addressing this global pandemic.     

Impact of Family Environment on Future Mental Health Professionals' Attitudes Toward Lesbians and Gay Men

This study explored the relationship between dimensions of functioning in the family of origin of graduate students in helping profession programs and their attitudes toward lesbians and gay men. One hundred forty-three participants completed the Family Environment Scale (FES-R: Moos & Moos, 1986 Moos, R. H. and Moos, B. S. 1986. Family Environment Scale, 2nd, Palo Alto, CA: Consulting Psychologists Press.  [Google Scholar]), the Attitudes Toward Lesbians and Gay Men scale (ATLG: Herek, 1994 Herek, G. M. 1994. “Assessing attitudes toward lesbians and gay men: A review of empirical research with the ATLG scale”. In Lesbian and gay psychology: Theory, research, and clinical applications, Edited by: Greene, B. and Herek, G.M. 206–224. Thousand Oaks, CA: Sage. [Crossref] , [Google Scholar]), and demographic questions. Results suggest that three family dimensions (conflict, intellectual-cultural orientation, and moral-religious emphasis) significantly predicted attitudes toward lesbians and gay men. The results also revealed that younger students held more negative attitudes toward lesbians and gay men than their older peers. Implications for educators, researchers, and practitioners are discussed.     

Assessing the Predictive Value of Fertility Expectations Through a Cognitive–Social Model

This paper grounds its analysis in a novel model (Bachrach and Morgan in Popul Dev Rev, 39:459–485, 2013) that suggests that responses to questions about fertility intentions may reflect distinct phenomena at distinct points in the life course. The model suggests that women form "true" intentions when their circumstances make the issue of childbearing salient and urgent enough to draw the cognitive resources needed to make a conscious plan; before this, women report intentions based on cognitive images of family and self. We test the implications of this model for reported fertility expectations using NLSY79 data that measure expectations throughout the life course. We find that early in the life course, before marriage and parenthood, women’s fertility expectations are associated with family background and cognitive images of family and future self. Later in the life course, as women experience life course transitions that confer statuses normatively associated with childbearing—such as marriage—and parenthood itself, their reported expectations are better predictors of their fertility than before they passed these life course milestones. Our empirical results provide support for a model which has important implications for both the measurement and conceptualization of women’s intended and expected fertility.     

Measuring Attitudes About Intimate Partner Violence Against Women: The ATT-IPV Scale

In lower-income settings, women more often than men justify intimate partner violence (IPV). Yet, the role of measurement invariance across gender is unstudied. We developed the ATT-IPV scale to measure attitudes about physical violence against wives in 1,055 married men and women ages 18–50 in My Hao district, Vietnam. Across 10 items about transgressions of the wife, women more often than men agreed that a man had good reason to hit his wife (3 % to 92 %; 0 % to 67 %). In random split-half samples, one-factor exploratory factor analysis (EFA) (N ₁ = 527) and confirmatory factor analysis (CFA) (N ₂ = 528) models for nine items with sufficient variability had significant loadings (0.575–0.883; 0.502–0.897) and good fit (RMSEA = 0.068, 0.048; CFI = 0.951, 0.978, TLI = 0.935, 0.970). Three items had significant uniform differential item functioning (DIF) by gender, and adjustment for DIF revealed that measurement noninvariance was partially masking men’s lower propensity than women to justify IPV. A CFA model for the six items without DIF had excellent fit (RMSEA = 0.019, CFI = 0.994, TLI = 0.991) and an attitudinal gender gap similar to the DIF-adjusted nine-item model, suggesting that the six-item scale reliably measures attitudes about IPV across gender. Researchers should validate the scale in urban Vietnam and elsewhere and decompose DIF-adjusted gender attitudinal gaps.     

Occupational Stratification of Hispanics,Whites, and Blacks in Southern Rural Destinations: A Quantitative Analysis

Since the 1990s, many rural communities in the Southern US have experienced an unprecedented influx of Latino migrants. Some research undertaken on such “new Hispanic destinations” suggests that the newcomers tend to assume low-status jobs shunned by non-Hispanic residents and thus form a segmented labor market, but other work indicates that they heavily compete with natives (particularly African Americans) for less-skilled positions. Drawing on data from the 2000 census and 2009–2011 American Community Survey, this paper examines patterns of occupational stratification between Latino, white, and black men in the rural South to identify whether Hispanic economic relations in the area are better characterized by segmentation or competition. Specifically, occupational dissimilarity indexes and status scores are calculated to map the groups’ relative economic positions in the rural portions of five Southeastern states home to fast-growing nonmetro Latino populations: Alabama, Arkansas, Georgia, North Carolina, and South Carolina. Consistent with the segmentation hypothesis, the results reveal that Latinos are highly occupationally dissimilar from non-Hispanic whites and blacks and rank significantly below both in mean occupational status. Standardization of the stratification measures shows that Hispanics’ labor market isolation and disadvantage can be substantially accounted for by their lower average levels of human capital and US citizenship.     

Australian demography at the millennium

This paper looks backwards over the last ten years to see what topics might concern Australian demographers in the future. The possibility of convergence or ’sameness’ is considered, but not proven. The main areas considered are historical demography, mortality, fertility, marriage, fertility regulation, internal migration, international migration, human resources, ageing, forecasting, the family life cycle, policy, and gender.     

Racial-Ethnic Differences in U.S. Married Women’s and Men’s Housework

Married women continue to spend more time doing housework than men and economic resources influence women’s housework more strongly than men’s. To explain this, gender theorists point to how gender figures into identities, family interactions, and societal norms and opportunity structures. The extent of this configuration varies culturally and, in the United States, by race-ethnicity because of how race-ethnicity conditions access to resources and influences gender relations within marriages. Housework levels and gender differences may be lower in Black married couples compared to other couples because of Black women’s higher historical levels of employment and consequently long-standing need to balance work and family responsibilities. Race-ethnicity also likely conditions the symbolic meaning and thus association of economic resources and housework. We use pooled time diary data from the 2003 to 2007 American Time Use Study from 26,795 married women and men to investigate how and why race-ethnicity influences housework. Our results indicate Hispanic and Asian women do more cooking and cleaning compared with White and Black women and the inverse relationship between women’s earnings and housework is steeper for Hispanic women compared with other women. We find no evidence that married Black men devote more time to housework than White men, either core or occasional, unlike earlier studies.     

Mediating Effects of Affect and Loneliness on the Relationship Between Core Self-evaluation and Life Satisfaction Among Two Groups of Chinese Adolescents

This study examined the mediating effects of affect (positive and negative affect) and loneliness on the relationship between core self-evaluations (CSE) and life satisfaction among two groups of Chinese adolescents. Three hundred adolescents (169 males and 131 females) from Shenzhen and Xi’an in China completed the Core Self-evaluations Scale, Positive and Negative Affect Scale, UCLA Loneliness and Satisfaction with Life Scale. Research revealed that positive and negative affect, and loneliness fully mediated the relationship between CSE and life satisfaction. The relationship between CSE and loneliness was partially mediated by positive and negative affect. Loneliness partially mediated the relation between positive and negative affect and life satisfaction. The final model also indicated two significant paths from CSE through positive and negative affect and loneliness to life satisfaction. Furthermore, a multi-group analysis found that the paths did not differ across gender. Limitations of the study are considered and implications of the results for enhancing adolescents’ life satisfaction are discussed.     

Core American Values and the Structure of Antigay Prejudice

This work presents a new scale to measure conflicting attitudes toward sexual minorities. This scale parallels existing measures of conflicting racial attitudes (anti-Black and pro-Black attitudes; Katz & Hass, 1988 Katz, I. and Hass, G. R. 1988. Racial ambivalence and American value conflict: Correlational and priming studies of dual cognitive processes. Journal of Personality and Social Psychology, 55: 893–905. [Web of Science ®] , [Google Scholar]). After constructing and validating measures of antigay and progay attitudes, we tested relationships among core American values with racial and sexual minority attitudes. We examined relations among the Protestant Work Ethic (PWE), Traditional Family Ideology (TFI), and egalitarian values with attitudes toward racial outgroups and sexual minorities. The results revealed that both PWE values and egalitarian values predicted anti-Black attitudes. By contrast, endorsement of egalitarian values, but not PWE values, predicted pro-Black attitudes. Results also revealed a similar but distinct pattern among values and heterosexuals' attitudes toward sexual minorities. TFI, but not egalitarian value endorsement, predicted antigay attitudes, whereas both TFI and egalitarian value endorsement predicted progay attitudes. The implications of these findings are discussed.