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Objective:We aim to contextualize the growing body of research on the sequelae of military service in the wars in Afghanistan and Iraq. We employ a social–ecological (SE) framework for the taxonomy of military health research and classify risk as arising from the individual, family, community, and the institutional levels. We intend for this review to inform enhanced health promotion efforts in military communities.Data Source:Articles reviewed were extracted from Web of Science, PubMed, and Scopus.Inclusion and Exclusion Criteria:Research focused on somatic and psychological sequelae of combat deployment published from 2001—the year the war in Afghanistan began—through the end of 2014. We excluded studies of non-US military personnel, other systematic reviews, meta-analyses, book chapters, and theoretical papers.Data Extraction:We examined and summarized the aims, participants, methods, study design, SE framework tier, risk factors, and health outcomes.Data Synthesis:Studies were categorized according to SE tier, whether they focused on somatic, behavioral, or psychological outcomes, and by risk factor.Results:Of the 352 peer-reviewed papers, 84% focused on war's sequelae on the index military personnel, and 75% focused on mental or behavioral health outcomes—mostly on post-traumatic stress disorder. We find comparatively little research focusing on the family, community, or institutional tiers.Conclusions:We know relatively little about how family and community respond to the return of personnel from combat deployment; how family resources affect the health of returning military personnel; and how a war's persistence presents challenges for federal, state, and local agencies to meet military health-care needs. Such work is especially salient as US troops return home from war—particularly in communities where there are substantial military populations.

ObjectiveDuring the 1970s and 1980s in the U.S., population movement, urban sprawl and urban governance reform led to a proliferation of local, autonomous jurisdictions. Prior literature examines how this creation of local governments, also referred to as political fragmentation, contributes to economic growth and social inequality. We examine the impact of political fragmentation on health equity by testing the hypothesis that the mortality disparity between whites and African-Americans varies positively with political fragmentation.MethodsWe retrieved mortality data from the multiple cause-of-death file and calculated total number of local governments per 1000 residents in a county to measure the degree of political fragmentation. We focused on 226 U.S. counties with population size greater than 200,000 and restricted the analysis to four distinct periods with overlapping government and mortality data (1972-73, 1977-78, 1982-83, and 1987-88). We applied generalized estimating equation methods that permit analysis of clustered data over time. Methods also controlled for the age structure of the population, reductions in mortality over time, and confounding by county-level sociodemographic variables.ResultsAdjusted coefficients of fragmentation are positive and statistically significant for both whites (coef: 2.60, SE: 0.60, p<0.001) and African-Americans (coef: 5.31, SE: 1.56, p<0.001). The two-fold larger positive coefficient for African-Americans than for whites indicates a greater racial disparity in mortality among more politically fragmented urban counties and/or time periods.ConclusionsFrom 1972 to 1988, political fragmentation in large urban counties moves positively with the racial/ethnic gap in mortality between whites and African-Americans. We discuss intervening mechanisms through which political fragmentation may disproportionately affect mortality among African-Americans.

Objective:During the 1970s and 1980s in the U.S., population movement, urban sprawl and urban governance reform led to a proliferation of local, autonomous jurisdictions. Prior literature examines how this creation of local governments, also referred to as political fragmentation, contributes to economic growth and social inequality. We examine the impact of political fragmentation on health equity by testing the hypothesis that the mortality disparity between whites and African-Americans varies positively with political fragmentation. Methods:We retrieved mortality data from the multiple cause-of-death file and calculated total number of local governments per 1000 residents in a county to measure the degree of political fragmentation. We focused on 226 U.S. counties with population size greater than 200,000 and restricted the analysis to four distinct periods with overlapping government and mortality data (1972-73, 1977-78, 1982-83, and 1987-88). We applied generalized estimating equation methods that permit analysis of clustered data over time. Methods also controlled for the age structure of the population, reductions in mortality over time, and confounding by county-level sociodemographic variables. Results:Adjusted coefficients of fragmentation are positive and statistically significant for both whites (coef: 2.60, SE: 0.60, p<0.001) and African-Americans (coef: 5.31, SE: 1.56, p<0.001). The two-fold larger positive coefficient for African-Americans than for whites indicates a greater racial disparity in mortality among more politically fragmented urban counties and/or time periods. Conclusions:From 1972 to 1988, political fragmentation in large urban counties moves positively with the racial/ethnic gap in mortality between whites and African-Americans. We discuss intervening mechanisms through which political fragmentation may disproportionately affect mortality among African-Americans.

During the 1970s and 1980s in the U.S., population movement, urban sprawl and urban governance reform led to a proliferation of local, autonomous jurisdictions. Prior literature examines how this creation of local governments, also referred to as political fragmentation, contributes to economic growth and social inequality. We examine the impact of political fragmentation on health equity by testing the hypothesis that the mortality disparity between whites and African-Americans varies positively with political fragmentation.We retrieved mortality data from the multiple cause-of-death file and calculated total number of local governments per 1000 residents in a county to measure the degree of political fragmentation. We focused on 226 U.S. counties with population size greater than 200,000 and restricted the analysis to four distinct periods with overlapping government and mortality data (1972-73, 1977-78, 1982-83, and 1987-88). We applied generalized estimating equation methods that permit analysis of clustered data over time. Methods also controlled for the age structure of the population, reductions in mortality over time, and confounding by county-level sociodemographic variables.Adjusted coefficients of fragmentation are positive and statistically significant for both whites (coef: 2.60, SE: 0.60, p<0.001) and African-Americans (coef: 5.31, SE: 1.56, p<0.001). The two-fold larger positive coefficient for African-Americans than for whites indicates a greater racial disparity in mortality among more politically fragmented urban counties and/or time periods.From 1972 to 1988, political fragmentation in large urban counties moves positively with the racial/ethnic gap in mortality between whites and African-Americans. We discuss intervening mechanisms through which political fragmentation may disproportionately affect mortality among African-Americans.

•We study political fragmentation in urban areas from 1972 to 1988.•We use local governments per 1000 persons as a fragmentation metric.•Our panel data and methods permit robust population health estimates.•Fragmented governance increases African-American more than white mortality.

The recent global economic recession has renewed interest in knowing whether a declining economy affects population health. Understanding the extreme case of the Great Depression may inform the current debate as well as theory regarding biological and behavioral adaptations to unwanted economic change. We test the hypothesis, recently suggested in the literature, that period life expectancy at birthimprovedduring the Great Depression. We applied time‐series methods to annual period life expectancy data of the civilian population from eleven European countries. Methods control for trends and other forms of autocorrelation in life expectancy that could induce spurious associations. We cannot reject the null hypothesis that period life expectancy at birth during the Great Depression remained within the interval forecasted from historical values. Additional analyses using an automated, rule‐based methodology also cannot reject the null hypothesis. During the most severe phase of the Great Depression, period life expectancy in eleven European countries generally did not rise above expected levels.

AbstractPrior research based on Swedish data suggests that collective optimism, as measured by monthly incidence of suicides, correlates inversely with selection in utero against male twins in a population. We test this finding in the US, which reports the highest suicide rate of all high-income countries, and examine whether monthly changes in overall suicides precede changes in the ratio of male twin to male singleton live births. Consistent with prior work, we also examine as a key independent variable, suicides among women aged 15−49 years. We retrieved monthly data on suicides and the ratio of male twin to singleton live births from CDC WONDER, 2003 to 2019, and applied Box-Jenkins iterative time-series routines to detect and remove autocorrelation from both series. Results indicate that a 1% increase in monthly change in overall suicides precedes a 0.005 unit decline in male twin live births ratio 6 months later (coefficient = −.005, p value = .004). Results remain robust to use of suicides among reproductive-aged women as the independent variable (coefficient = −.0012, p value = .014). Our study lends external validity to prior research and supports the notion that a decline in collective optimism corresponds with greater selection in utero.

Abstract
Objective
To determine whether Latino undocumented immigrants had a steeper decline in Emergency Department (ED) utilization compared to Latino Medi-Cal patients in a Los Angeles safety-net hospital, March 13, 2020, to May 8, 2020.

Study Design
The data were extracted from patient medical records for ED visits at LAC + USC Medical Center from January 2018 to September 2020. We analyzed weekly ED encounters among undocumented Latino patients in the nine-week period after COVID was declared a national emergency. We applied time-series routines to identify and remove autocorrelation in ED encounters before examining its relation with the COVID-19 pandemic. We included Latino patients 18 years of age and older who were either on restricted or full-scope Medi-Cal (n = 230,195).

Results
All low-income Latino patients, regardless of immigration status, experienced a significant decline in ED utilization during the first nine weeks of the pandemic. Undocumented patients, however, experienced an even steeper decline. ED visits for this group fall below expected levels between March 13, 2020, and May 8, 2020 (coef. =  − 38.67; 95% CI =  − 71.71, − 5.63). When applied to the weekly mean of ED visits, this translates to a 10% reduction below expected levels in ED visits during this time period.

Conclusion
Undocumented immigrants' health care utilization was influenced by external events that occurred early in the pandemic, such as strict stay-at-home orders and the public charge rule change. Health care institutions and local policy efforts could work to ensure that hospitals are safer spaces for undocumented immigrants to receive care without immigration concerns.

The 2016 election of United States (U.S.) President Donald Trump was a political event that may have affected population-level mental health. A prominent theme in the Trump election was anti-immigrant policy that contributed to a racist and xenophobic sociopolitical climate. Applying a symbolic dis/empowerment framework, this study examines whether there was an effect of the Trump election on the mental health of the U.S. population that differed by race/ethnicity, language of interview, and state-level support for Trump or Clinton. We used data from the Centers for Disease Control and Prevention's Behavioral Risk Factor Surveillance System 2011-2018 to examine trends in poor mental health days in the five months after the U.S Presidential election (November 2016 to March 2017) compared to all other survey months. We conducted difference-in-differences analyses using negative binomial regression models to examine the effect of the five post-election months on the rate of poor mental health days, comparing six population categories: 1) non-Latinx white populations in Trump states, 2) non-Latinx white populations in Clinton states, 3) English-speaking Latinx populations in Trump states, 4) English-speaking Latinx populations in Clinton states, 5) Spanish-speaking Latinx populations in Trump states, and 6) Spanish-speaking Latinx populations in Clinton states. White populations in Clinton states reported more poor mental health days in response to the five months post-election period compared to white populations in Trump states. English-speaking Latinx people living in Trump states experienced higher than expected poor mental health days in November 2016 and February 2017. Spanish-speaking Latinx people, by contrast, reported fewer poor mental health days in the post-election period. The 2016 U.S. presidential election preceded population-level changes in mental health that support a symbolic dis/empowerment framework. We discuss possible explanations and the mental health implications for future major political ...

The 2016 election of United States (U.S.) President Donald Trump was a political event that may have affected population-level mental health. A prominent theme in the Trump election was anti-immigrant policy that contributed to a racist and xenophobic sociopolitical climate. Applying a symbolic dis/empowerment framework, this study examines whether there was an effect of the Trump election on the mental health of the U.S. population that differed by race/ethnicity, language of interview, and state-level support for Trump or Clinton. We used data from the Centers for Disease Control and Prevention's Behavioral Risk Factor Surveillance System 2011-2018 to examine trends in poor mental health days in the five months after the U.S Presidential election (November 2016 to March 2017) compared to all other survey months. We conducted difference-in-differences analyses using negative binomial regression models to examine the effect of the five post-election months on the rate of poor mental health days, comparing six population categories: 1) non-Latinx white populations in Trump states, 2) non-Latinx white populations in Clinton states, 3) English-speaking Latinx populations in Trump states, 4) English-speaking Latinx populations in Clinton states, 5) Spanish-speaking Latinx populations in Trump states, and 6) Spanish-speaking Latinx populations in Clinton states. White populations in Clinton states reported more poor mental health days in response to the five months post-election period compared to white populations in Trump states. English-speaking Latinx people living in Trump states experienced higher than expected poor mental health days in November 2016 and February 2017. Spanish-speaking Latinx people, by contrast, reported fewer poor mental health days in the post-election period. The 2016 U.S. presidential election preceded population-level changes in mental health that support a symbolic dis/empowerment framework. We discuss possible explanations and the mental health implications for future major political events.

While sex ratios at birth (SRB) have been shown to vary within and across populations, after over a century of research, explanations have remained elusive. A variety of ecological, demographic, economic, and social variables have been evaluated, yet their association with SRB has been equivocal. Here, in an attempt to shed light on this unresolved topic within the literature, we approach the question of what drives variation in SRB using detailed longitudinal data spanning the frontier-era to the early 20th century in a population from the US state of Utah. Using several measures of environmental harshness, we find that fewer boys are born during challenging times. However, these results hold only for the frontier-era and not into a period of rapid economic and infrastructure development. We argue that the mixed state of the literature may result from the impact and frequency of exogenous stressors being dampened due to industrialization.