Population Research and Policy Review最新文献

Despite a developing literature on the consequences of parental incarceration, its effects on childhood obesity are not evident. Our research project fills this knowledge gap by describing the relationship between parental incarceration and childhood obesity among children aged 3–15 and determining if and how this association differs across race. We use four consecutive waves of data on 3,302 children from the Fragile Families and Child Wellbeing Study. Our analysis finds little evidence that parental incarceration influences the probability of obesity among all children as a group. Moreover, our findings reveal critical racial disparities in the relationship between parental incarceration and childhood obesity. In particular, parental lifetime incarceration is not associated with risks of obesity for White or Hispanic children but is associated with a significantly decreased chance of obesity for Black children. This research effort can initiate an interdisciplinary conversation on the important intersection of family and corrections in order to alleviate the intergenerational erosion of physical health and well-being.

Research on the legacies of historical redlining has lacked nationally representative and multilevel data. We advance this literature by analyzing new data that links historical redlining maps to the residential addresses of participants in the National Longitudinal Study of Adolescent to Adult Health (Add Health), a diverse and national cohort of adolescents who transitioned to adulthood between the mid-1990s and late 2010s (N = 10,897). We report three key findings. First, while most participants did not live within the boundaries of historical redlining maps, Black (22%) and Hispanic (28%) participants were several times more likely than their White peers (8%) to live in either a formerly yellow- or red-lined urban area in adolescence. Second, adolescents who resided in yellow- or red-lined areas also tended to live in the most disadvantaged households and neighborhoods and attained the lowest levels of socioeconomic status in adulthood. Third, Black and White adolescents who lived in rural areas also experienced similar or worse adult outcomes than their peers who lived in redlined urban areas. We also find anomalous but inconclusive patterns for the small group of Black and Hispanic participants who lived in historically affluent “green-lined” areas in adolescence, including poor adult health and high risk of contact with the criminal justice system. Given these findings, we outline avenues for future research that could include historical redlining maps, but also expand beyond urban redlining to consider nonmetropolitan areas and other contemporary indicators of structural racism.

Child marriage has lasting negative health, human capital, and welfare consequences. Conflict settings are characterized by a number of complex changes that can potentially increase the risk of child marriage, but there has been limited population-based research directly estimating the relationship between conflict and child marriage. Using data from 19 conflict-affected countries, this paper estimates the relationship between conflict and child marriage. It identifies the relationship based on variation over space and time in conflict intensity. The findings are mixed; in some countries conflict is associated with an increase in child marriage, in others it is associated with a decrease in child marriage, and in some cases there is not a statistically significant relationship. These findings underscore how efforts to reduce child marriage need to consider conflict as a potential risk factor, but also one that is likely to interact with local economic, social, and demographic environments.

We examine the utility of data on active and vacant residential addresses to inform local and timely monitoring and assessments of how areas impacted by wildfires and extreme weather events more broadly lose (or not) and subsequently recover (or not) their populations. Provided by the U.S. Postal Service to the U.S. Department of Housing and Urban Development and other users, these data are an underutilized and potentially valuable tool to study population change in disaster-affected areas for at least three reasons. First, as they are aggregated to the ZIP + 4 level, they permit highly local portraits of residential and, indirectly, of population change. Second, they are tabulated on a quarterly basis starting in 2010 through the most recent quarter, thereby allowing for timely assessments than other data sources. Third, one mechanism of population change—namely, underlying changes in residential occupancies and vacancies—is explicit in the data. Our findings show that these data are sufficient for detecting signals of residential and, indirectly, of population change during and after particularly damaging wildfires; however, there is also noticeable variation across cases that requires further investigations into, for example, the guidance the U.S. Postal Services provides its postal offices and carriers to classify addresses as vacant.

Japan’s population aging is the most advanced in the world today. No nationwide study has been conducted using small area population projection data on Japan’s aging population. This is because such projection data was unavailable for Japan before the 2016 launch of the website ‘The Web System of Small Area Population Projections for the Whole Japan’ (SAPP for Japan). SAPP for Japan opened the small-area and long-term projected population of Japan for the first time on the World Wide Web. The purpose of this study is to quantitatively analyze the future aging process using data from the SAPP for Japan and, based on this analysis, to attempt to present the standard aging process that developed countries will experience after the demographic transition, taking advantage of the fact that Japan has the most aged population in the world. Subsequently, a non-hierarchical cluster analysis was performed using two statistics on aging: the elderly population proportion and the elderly population change index, and the small areas were classified into seven clusters. Furthermore, this study examined the demographic and geographical features of the clusters, introduced a new concept of the stage in the population aging process, and analyzed the relationship between the features and the stages. To conclude, the following findings were obtained regarding the future process of Japan’s population aging. In each area of Japan, first, the total population begins to decline, second, the elderly population begins to decrease, and finally, its proportion begins to decrease. These stage shifts generally proceed earlier in areas with a higher elderly population proportion and are attributed to the reduced size of younger cohorts owing to long-term fertility decline. This process would be the norm in many developed countries after the demographic transition.

In this paper we focus on modelling and forecasting gross interregional migration in a way that can be embedded within multiregional population projections. We revisit, and apply, a family of spatial interaction models first formulated during the 1970s. The classic gravity model—in which migration is positively related to the populations of sending and receiving areas, but inversely related to various types of spatial friction associated with migrating between them—is a special case that is nested within this family of models. We investigate which member of the family of models gives the best fit when modelling five-year migration flows between the 66 Territorial Authorities (TAs) of Aotearoa New Zealand, using 2013 and 2018 census data. We find that predicting migration between two TAs can be improved by taking into account, firstly, an index of the ‘draw’ from all other TAs when modelling out-migration of any TA and, secondly, an index of the ‘competitiveness’ of a TA vis-à-vis all other TAs when modelling in-migration of any TA. We highlight the properties of the statistically-preferred model by simulating the impact on internal migration of an exogenous increase in Auckland’s population. In this model, such a population change affects not only migration flows from and to Auckland, but also migration between other TAs. The usefulness of this approach for population projections is assessed by forecasting the 2013–18 migration matrix by means of 2013 census data only. In this specific case, the model outperforms the classic gravity model in terms of forecasting gross migration, but not net migration.

Over the past few decades, interracial and interethnic marriages have increased significantly. The rise in intermarriages has been celebrated for their potential to reduce ethnoracial distinctions and ethnoracial inequality. Whether the increase in interracial and interethnic unions can reduce disparities in homeownership across ethnoracial groups is unknown. Using data on the 2008–2021 American Community Survey (ACS), we compare the homeownership rates of Millennials in intermarriages with those of couples in endogamous unions and identify the factors contributing to differences in homeownership rates between interracial and couples in ethnoracial endogamy. Our results show that the homeownership rates of interracial couples fall somewhere between those of endogamous couples belonging to the husband’s or wife’s ethnoracial groups. These differences emerge primarily due to variations in nativity composition, educational attainment, family income, average value of homes, and proportion of rentals. The intermediary homeownership rates of interracial couples suggest that the rise in intermarriages will reduce ethnoracial inequality in homeownership rates. Nonetheless, couples in marriages involving an ethnoracial minority spouse have lower homeownership rates than endogamous White couples. This White/non-White divide in homeownership rates highlights the need for a housing policy that enhances opportunities for homeownership among interracial and endogamous minority couples.

Not all U.S. populations have equal access to a primary care provider (PCP). This study presents one of the first population-based evidence of inequities in access to PCPs at the intersection of race/ethnicity, sexual orientation, and gender. We analyzed pooled data from the Behavioral Risk Factor Surveillance System from 2016 to 2021 across 42 states and 1 territory in the United States. The final sample encompassed 1,142,344 respondents aged 18 and older. Logistic regression models, stratified by gender spectrum, were estimated to compare predicted probabilities of having a PCP across 20 sexual and racial/ethnic identity groups. Among those on the feminine spectrum, most sexual minorities of color exhibited lower rates of having a PCP compared to heterosexual White individuals. Even when sociodemographic and health factors were accounted for, PCP access disadvantages remained significant in some groups of Native and Hispanic sexual minorities. Among sexual minorities of color on the masculine spectrum, inequities were less prominent, and sociodemographic and health factors nearly explained all their disadvantages. Sexual orientation, gender, and race/ethnicity intersect to shape the access to PCPs. Future research, policy designs, and clinical practices should adopt an intersectional approach to achieve a better understanding of healthcare inequities and to reduce inequities.

In multi-level and multi-layered foundations of gendered approaches for understanding the kinship system, family-building behavior, son preference, and male-skewed child sex ratios in India; patriarchy and patrilineality have received greater attention than patrilocality. To fill this gap, we construct a measure of patrilocality and hypothesize that households practice sex selection and daughter discrimination because of patrilocality norms that dictate the later life co-residence between parents and sons. Our findings reveal that the child sex ratio, sex ratio at birth, and sex ratio at last birth are negatively correlated with patrilocality rates across states and districts of India. The robustness of these findings is verified by using alternative definitions of patrilocality, examining the association between patrilocality and patrilineality, and assessing the relationship between patrilocality and child sex ratios across states and by urbanization levels. We conclude that, in the absence of strong social security measures and a lack of preference for old-age homes, amidst the accepted practice of patrilocality coupled with increasingly lower fertility norms, the dependency on sons will continue, leading to the continuation of sex selection in India.

In this study, we improve on the research results of relational models that enable life table estimates from a small number of demographic indices, such as the Log Quad Model by Wilmoth et al. (Popul Stud 66(1):1–28, 2012) and the Extended Log Quad Model 1 by Horiguchi (J Popul Stud 58:13–28, 2022). Consequently, we propose the Extended Log Quad Model 2. This is a mortality rate model that reflects the remarkable improvement in old-age mortality rates in Japan since the 1970s. This is intended for application to the estimation of municipal life tables in Japan. The Extended Log Quad Model 2 is useful for municipal policymaking because it is possible to estimate future life tables with a high level of accuracy by projecting only life expectancy at the age of 65. It is also suggested that the Extended Log Quad Model 2 will be applicable to other developed countries, such as Australia, Canada, France, and New Zealand.