Nearly 3 billion additional urban dwellers are forecasted by 2050, an unprecedented wave of urban growth. While cities struggle to provide water to these new residents, they will also face equally unprecedented hydrologic changes due to global climate change. Here we use a detailed hydrologic model, demographic projections, and climate change scenarios to estimate per-capita water availability for major cities in the developing world, where urban growth is the fastest. We estimate the amount of water physically available near cities and do not account for problems with adequate water delivery or quality. Modeled results show that currently 150 million people live in cities with perennial water shortage, defined as having less than 100 L per person per day of sustainable surface and groundwater flow within their urban extent. By 2050, demographic growth will increase this figure to almost 1 billion people. Climate change will cause water shortage for an additional 100 million urbanites. Freshwater ecosystems in river basins with large populations of urbanites with insufficient water will likely experience flows insufficient to maintain ecological process. Freshwater fish populations will likely be impacted, an issue of special importance in regions such as India's Western Ghats, where there is both rapid urbanization and high levels of fish endemism. Cities in certain regions will struggle to find enough water for the needs of their residents and will need significant investment if they are to secure adequate water supplies and safeguard functioning freshwater ecosystems for future generations.

BackgroundExposure to environmental toxicants is associated with numerous disease outcomes, many of which involve underlying immune and inflammatory dysfunction.ObjectivesTo address the gap between environmental exposures and immune dysfunction, we investigated the association of two endocrine-disrupting compounds (EDCs) with markers of immune function.MethodsUsing data from the 2003–2006 National Health and Nutrition Examination Survey, we compared urinary bisphenol A (BPA) and triclosan levels with serum cytomegalovirus (CMV) antibody levels and diagnosis of allergies or hay fever in U.S. adults and children ≥ 6 years of age. We used multivariate ordinary least squares linear regression models to examine the association of BPA and triclosan with CMV antibody titers, and multivariate logistic regression models to investigate the association of these chemicals with allergy or hay fever diagnosis. Statistical models were stratified by age (< 18 years and ≥ 18 years).ResultsIn analyses adjusted for age, sex, race, body mass index, creatinine levels, family income, and educational attainment, in the ≥ 18-year age group, higher urinary BPA levels were associated with higher CMV antibody titers (p < 0.001). In the < 18-year age group, lower levels of BPA were associated with higher CMV antibody titers (p < 0.05). However, triclosan, but not BPA, showed a positive association with allergy or hay fever diagnosis. In the < 18-year age group, higher levels of triclosan were associated with greater odds of having been diagnosed with allergies or hay fever (p < 0.01).ConclusionsEDCs such as BPA and triclosan may negatively affect human immune function as measured by CMV antibody levels and allergy or hay fever diagnosis, respectively, with differential consequences based on age. Additional studies should be done to investigate these findings.

Despite the widespread use of self-rated health (SRH) in population health studies, the meaning of this holistic health judgment remains an open question. Gender differences in health, an issue of utmost importance in population research and policy, are often measured with SRH; the comparisons could be biased if men and women differ in how they form their health judgment. The aim of this study is to examine whether men and women differ in how health inputs predict their health rating across the adult life span. We use the 2002–2015 National Health Interview Survey data from US-born respondents aged 25–84. Ordered logistic models of SRH as a function of 24 health measures including medical conditions and symptoms, mental health, functioning, health care utilization, and health behaviors, all interacted with gender, test how the measures influence health ratings and the extent to which these influences differ by gender. Using a Bayesian approach, we then compare how closely a select health measure (K6 score) corresponds to SRH levels among men and women. We find little systematic gender difference in the structure of SRH: men and women use wide-ranging health-related frames of reference in a similar way when making health judgments, with some exceptions: mid-life and older men weigh physical functioning deficits and negative health behaviors more heavily than women. Women report worse SRH than men on average but this only holds through mid-adulthood and is reversed at older ages; moreover, the gross female disadvantage disappears when differences in socio-economic and health covariates are considered. Our findings suggest that the meaning of SRH is similar for women and men. Both groups use a broad range of health-related information in forming their health judgment. This conclusion strengthens the validity of SRH in measuring gender differences in health.

These results suggest caution in relying on self-reported health measures to quantify and explain health disparities by socioeconomic status and race/ethnicity/ethnicity in the United States. The findings support expansion of the use of anchoring vignettes to properly account for reporting differences in self-reports of health.

Appraisal of urbanization trends is limited by the lack of a globally consistent definition of what is meant by urban. This article seeks to identify and explain differences in the definition of “urbanness” as used in two largely distinct research communities. We compare the Global Rural–Urban Mapping Project (GRUMP), which defines urban areas based primarily on satellite imagery of nighttime lights, to the urban classification found in Demographic and Health Surveys (DHS), which relies on the urban definitions of individual countries' national statistical offices. We analyze the distribution of DHS clusters falling within and outside of GRUMP urban extents and examine select characteristics of these clusters (notably, household electrification). Our results show a high degree of agreement between the two data sources on what areas are considered urban; furthermore, when used together, GRUMP and DHS data reveal urban characteristics that are not evident when one data source is used independently. GRUMP urban extents are overwhelmingly medium and large highly electrified localities. DHS clusters that are classified as non‐urban but that fall within GRUMP extents tend to be peri‐urban areas.

Background Despite the serious biases that characterize self-rated health, researchers rely heavily on these ratings to predict mortality. Using newly collected survey data, we examine whether simple ratings of participants' health provided by interviewers and physicians can markedly improve mortality prediction. Methods We use data from a prospective cohort study based on a nationally representative sample of older adults in Taiwan. We estimate proportional hazard models of all-cause mortality between the 2006 interview and 30 June 2011 (mean 4.7 years follow-up). Results Interviewer ratings were more strongly associated with mortality than physician or self-ratings, even after controlling for a wide range of covariates. Neither respondent nor physician ratings substantially improve mortality prediction in models that include interviewer ratings. The predictive power of interviewer ratings likely arises in part from interviewers' incorporation of information about the respondents' physical and mental health into their assessments. Conclusions The findings of this study support the routine inclusion of a simple question at the end of face-to-face interviews, comparable to self-rated health, asking interviewers to provide an assessment of respondents' overall health. The costs of such an undertaking are minimal and the potential gains substantial for demographic and health researchers. Future work should explore the strength of the link between interviewer ratings and mortality in other countries and in surveys that collect less detailed information on respondent health, functioning, and well-being.

Depression is the most prevalent mood disorder in the United States, and disparities in depressive symptoms and treatment by socioeconomic status have been well-documented. Recent evidence suggests the prevalence of depression is increasing, but less is known about time trends in disparities. Using nationally representative data from the National Health and Nutrition Examination Survey, we examined patterns of depressive symptoms (Patient Health Questionnaire-9) and treatment (self-reported psychotherapy and psychopharmacology). We assessed time trends in depression disparities by educational attainment among U.S. adults 2005-2014 using logistic regression models. Among the least educated groups, the odds of moderate to severe depressive symptoms increased; for the most educated, they remained stable (women) or decreased (men). At the same time, odds of receiving treatment, conditional on being depressed, declined (women) or remained stable (men) for the least educated group, whereas treatment rates stayed steady (women) or increased (men) for the most educated. Between 2005 and 2014, overall depression prevalence increased. Despite recent policies designed to improve mental health care coverage, depression treatment rates were unable to keep pace. The least educated consistently had the highest rates of moderate to severe depressive symptoms and the lowest rates of treatment. Disparities in depression by educational attainment have persisted or worsened. Public Policy Relevance StatementRecent evidence suggests the prevalence of depression is increasing, but less is known about whether socioeconomic disparities in depression have changed. This study shows that despite policies designed to improve access to mental health care, disparities in depression by educational attainment have persisted or worsened between 2005 and 2014.

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