County-level political group density, partisan polarization, and individual-level mortality among adults in the United States: A lagged multilevel study.

Objective: To investigate the associations between county-level political group density, partisan polarization, and individual-level mortality from all causes and from coronary heart disease (CHD) in the United States. Methods: Using data from five survey waves (1998-2006) of the General Social Survey-National Death Index dataset and the County Presidential Election Return 2000 dataset, we fit weighted Cox proportional hazards models to estimate the associations between (1) political group density and (2) partisan polarization measured at the county level in 2000 (n = 313 counties) categorized into quartiles with individual-level mortality (n = 14,983 participants) from all causes and CHD, controlling for individual- and county-level factors. Maximum follow-up was from one year after the survey up until 2014. We conducted these analyses using two separate measures based on county-level vote share differences and party affiliation ideological extremes. Results: In the overall sample, we found no evidence of associations between county-level political group density and individual-level mortality from all causes. There was evidence of a 13% higher risk of dying from heart disease in the highest quartile of county-level polarization (hazards ratio, HR = 1.13; 95% CI = 0.74-1.71). We observed heterogeneity of effects based on individual-level political affiliation. Among those identifying as Democrats, residing in counties with high (vs. low) levels of polarization appeared to be protective against mortality, with an associated 18% lower risk of dying from all causes (HR = 0.82, 95% CI = 0.71-0.94). This association was strongest in areas with the highest concentrations of Democrats. Conclusions: Among all study participants, political group density and polarization at the county level in 2000 were not linked to individual-level mortality. At the same time, we found that Democratic party affiliation may be protective against the adverse effects of high polarization, particularly in counties with high concentrations of Democrats. Future research should further explore these associations to potentially identify new structural interventions to address political determinants of population health.

Why People Stayed Home During the COVID-19 Pandemic: Implications for Health Communication Across Four Countries.

Staying at home substantially reduces the spread of COVID-19. Moreover, understanding why people stayed at home by addressing its social cognitive determinants can help create more effective communication to change behaviors. This study analyzed this outcome through an extended model of the theory of planned behavior based on risk perception and personal norms in four countries: the United States, Japan, Brazil, and Taiwan. 1,196 individuals participated in this study through a questionnaire focused on planned behavior, moral norms, and risk perception. The data showed that intention and perceived behavioral control influenced behavior significantly, while attitude, injunctive norms, perceived behavioral control, personal norms, and risk perception influenced intention. With multigroup analysis and ANOVA, we verified significant differences in the estimates and mean scores across cultures, revealing the need for scholars to analyze outcomes based on geography and local political culture. Given that health communications played a key role in managing the pandemic, this study clarifies the social cognitive determinants of staying at home and how the local political culture can impact their influence. Thus, we provide an evidence-based prescription for focused communications.

Putting a Price on Nature: Ecosystem Service Value and Ecological Risk in the Dongting Lake Area, China.

Understanding the relationship between ecosystem service value and ecological risk evolutions holds great theoretical and practical significance, as it helps to ensure the quality management of ecosystems and the sustainable development of human-land system interactions. We analyzed this relationship in the Dongting Lake area in China from 1995 to 2020 using data from remote sensing-interpreted land use with ArcGIS and Geoda. We used the equivalent factor method to estimate the ecosystem service value, constructed a landscape ecological risk index to quantitatively describe the ecological risk of Dongting Lake, and analyzed their correlation. The results show that: (1) over the last 25 years, the ecosystem service value decreased by 31.588 billion yuan, with higher values in the middle of the area and lower values in the surroundings-the highest value was found in forested land and the lowest was for unutilized land; (2) the ecological risk index also decreased slowly over time, from the perspective of single land use type, the ecological risk value of construction land was the lowest, followed by woodland, grassland, and cultivated land, with water area being the highest-the ecological risk level presents the distribution state of whole piece and local aggregation; and (3) the ecological risk index in Dongting Lake area demonstrated positive spatial correlation, and the spatial agglomeration of land with similar risk levels showed a decreasing trend. Areas with strong partial spatial correlations between ecosystem service value and ecological risk index are mainly distributed in the central water areas and their surrounding areas. This study investigates the rational utilization of land resources, and the sustainable development of regional ecological security in Dongting Lake area.

Opposing views: associations of political polarization, political party affiliation, and social trust with COVID-19 vaccination intent and receipt.

INTRODUCTION: Political polarization has increased in the USA within recent years. Studies have shown Republicans are less likely to accept COVID-19 vaccinations than Democrats; however, little is known regarding the association between COVID-19 vaccination acceptance and political polarization. METHODS: We used data from a nationally-representative survey of 1427 participants conducted between 9 February 2021 and 17 February 2021. We estimated multivariate-adjusted odds ratios for COVID-19 vaccination intent and receipt according to perceived political polarization (measured as the perceived size of the ideological gap between Democrats and Republicans), political party affiliation, and social trust, controlling for demographic and socioeconomic factors. RESULTS: Among participants perceiving high levels of polarization, Republicans (versus Democrats) reported a 90% lower odds of vaccination intent (OR = 0.10 [0.05, 0.19], P < 0.001). Participants with high (versus low) social trust and low perceived polarization had a 2-folder higher vaccination intent (OR = 2.39 [1.34, 4.21], P = 0.003); this association was substantially weaker in the high perceived polarization group. CONCLUSIONS: High perceived levels of political polarization appear to magnify the decrease in the odds of receiving the COVID-19 vaccine and the intent to get vaccinated among Republicans versus Democrats. Political polarization may further attenuate the protective associations of high social capital with vaccination.

Uneven paths: Soft Policy's benefits to recovery in Louisiana Parishes after Hurricanes Katrina and Rita.

Factors driving community recovery trajectories after disaster are not well understood. We assess why some communities show stronger recoveries from disaster than others, examining the role of four policy toolkits that U.S. county governments frequently adopt to recover from disaster. Using mixed methods, we examine the cases of Hurricanes Katrina and Rita with a novel dataset of recovery policies adopted within each Louisiana parish following the disasters. We typologize recovery strategies and analyze policy adoption patterns after crises. To compare which policy toolkit leads to the best recovery outcomes, we use synthetic control experiments on the 20 parishes hit by Hurricanes Katrina and Rita between August and September 2005, tracking net income inflow and net in-migration measures from 1997 to 2018 over 1408 parish-year observations, paired with qualitative case studies of parish policies and recovery outcomes. On average, soft and local recovery policies focused on community policies and feedback helped parishes stem the flow of finances away from the disaster-zone, as did infrastructural 'hard' policies, to a degree. in comparison, state policies focused on top-down planning experienced weaker recovery. Evidence shows that soft and local policy toolkits can accelerate recovery and that governments seeking to rebuild infrastructure should invest in locally-engaged community development in order to attain better overall recovery.

Social capital building interventions and self-reported post-disaster recovery in Ofunato, Japan.

Evidence shows that communal resources, cohesion, and social infrastructure can mitigate shocks and enhance resilience. However, we know less about how specific social capital building interventions facilitate recovery in post-disaster environments. Using a survey of over 1000 residents of Ofunato, Japan after the 2011 Tohoku earthquake and tsunami, this study demonstrates that the individuals who actively participated in a community center-created for and led by neighborhood elders-reported higher levels of family and neighborhood recovery than similar individuals who did not participate. Results from ordinal logistic regression analyses, propensity score matching (PSM) and coarsened exact matching (CEM) show arguably stronger causal links between bottom-up, microlocal programs to boost connections in post-disaster areas and post-disaster outcomes. Community-based programs that strengthen social ties even among elderly residents can measurably improve their recoveries.

A predictive model towards understanding the effect of reinforcement agglomeration on the stiffness of nanocomposites.

Nanocomposite technologies can be significantly enhanced through a careful exploration of the effects of agglomerates on mechanical properties. Existing models are either overly simplified (e.g., neglect agglomeration effects) or often require a significant amount of computational resources. In this study, a novel continuum-based model with a statistical approach was developed. The model is based on a modified three-phase Mori-Tanaka model, which accounts for the filler, agglomerate, and matrix regions. Fillers are randomly dispersed in a defined space to predict agglomeration tendency. The proposed model demonstrates good agreement with the experimentally measured elastic moduli of spin-coated cellulose nanocrystal reinforced polyamide-6 films. The techniques and methodologies presented in the study are sufficiently general in that they can be extended to the analyses of various types of polymeric nanocomposite systems.

Social capital's impact on COVID-19 outcomes at local levels.

Over the past thirty years, disaster scholars have highlighted that communities with stronger social infrastructure-including social ties that enable trust, mutual aid, and collective action-tend to respond to and recover better from crises. However, comprehensive measurements of social capital across communities have been rare. This study adapts Kyne and Aldrich's (Risk Hazards Crisis Public Policy 11, 61-86, 2020) county-level social capital index to the census-tract level, generating social capital indices from 2011 to 2018 at the census-tract, zipcode, and county subdivision levels. To demonstrate their usefulness to disaster planners, public health experts, and local officials, we paired these with the CDC's Social Vulnerability Index to predict the incidence of COVID-19 in case studies in Massachusetts, Wisconsin, Illinois, and New York City. We found that social capital predicted 41-49% of the variation in COVID-19 outbreaks, and up to 90% with controls in specific cases, highlighting its power as diagnostic and predictive tools for combating the spread of COVID.

Attracting altruists: explaining volunteer turnout during natural hazard events in Japan.

Volunteers play a crucial role in post-disaster situations, providing resources, emotional support, and labour when local and national government capacity may be diminished. The number of volunteers who assist can range from dozens to more than one million. Yet, little is known about the broader conditions that result in more (or fewer) of them heading to disaster sites. Using a new dataset of 57 disasters in Japan between 1995 and 2019, this study analyses the factors influencing volunteer turnout. Controlling for a number of aspects, three are found to correlate most strongly: the number of dead and missing; the size of the population affected by the shock; and the time period of the year. Moving beyond tables of regression coefficients, simulations and graphics are used to illustrate the relationship between key variables of interest as well as uncertainty about the predictions. The study's findings-robust across multiple model types-have important policy and practical implications.

Combined Use of Aspirin and Statin is Associated With a Decreased Incidence of Hepatocellular Carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is a leading cause of cancer and cancer-related mortality worldwide. Studies have suggested that aspirin (ASA) and statins may be associated with a decrease in incident HCC. GOALS: We aimed to evaluate the effect of ASA and statin use on the incidence of HCC in a prospective cohort of patients with liver cirrhosis and to identify if there was an increased risk of esophageal variceal hemorrhage (VH) in patients with ASA use. STUDY: We conducted a retrospective study of 521 patients with data collected from July 1, 2012 to December 31, 2017. We used competing risk analysis to assess the association between risk factors and HCC; and the association between ASA and VH. RESULTS: ASA use alone was associated with a decreased incidence of HCC in the univariate and multivariate models; [hazard ratio (HR) confidence interval (CI): 0.348 (0.124-0.976); P=0.0448] and [HR (CI): 0.266 (0.094-0.755); P=0.0129, respectively]. The combination of ASA and statin use was associated with a decreased hazard of HCC [HR (CI): 0.15 (0.036-0.624); P=0.0090] and this remained statistically significant in the multivariable model [HR (CI): 0.113 (0.026-0.483); P=0.0033]. Among daily ASA users compared with non-users, there was not a significant increase in risk of VH. CONCLUSIONS: Daily ASA use was associated with a decrease risk of incident HCC. The combination of daily ASA use and statin use decreased the risk of incident HCC suggesting there is beneficial interaction. Finally, no excess VH was observed in daily ASA users compared with non-users.

The harmful effects of partisan polarization on health.

Partisan polarization significantly drives stress and anxiety among Americans, and recent aggregate-level studies suggest polarization may be shaping their health. This individual-level study uses a new representative dataset of 2,752 US residents surveyed between December 2019 and January 2020, some US residents report more days of poor physical and mental health per month than others. Using negative binomial models, zero inflated models, and visualizations, we find evidence that polarization is linked to declines in physical health: the more distant an individual feels politically from the average voter in their state, the worse health outcomes he or she reports. By uncovering the individual-level political correlates of health, this study aims to encourage further study and attention to the broader consequences of political polarization on American communities.

Bowling alone or distancing together? The role of social capital in excess death rates from COVID19.

Much attention on the spread and impact of the ongoing pandemic has focused on institutional factors such as government capacity along with population-level characteristics such as race, income, and age. This paper draws on a growing body of evidence that bonding, bridging, and linking social capital - the horizontal and vertical ties that bind societies together - impact public health to explain why some U.S. counties have seen higher (or lower) excess deaths during the COVID19 pandemic than others. Drawing on county-level reports from the Centers for Disease Control and Prevention (CDC) since February 2020, we calculated the number of excess deaths per county compared to 2018. Starting with a panel dataset of county observations over time, we used coarsened exact matching to create smaller but more similar sets of communities that differ primarily in social capital. Controlling for several factors, including politics and governance, health care quality, and demographic characteristics, we find that bonding and linking social capital reduce the toll of COVID-19 on communities. Public health officials and community organizations should prioritize building and maintaining strong social ties and trust in government to help combat the pandemic.

Is divisive politics making Americans sick? Associations of perceived partisan polarization with physical and mental health outcomes among adults in the United States.

OBJECTIVES: To investigate whether changes in perceived partisan polarization since the 2016 US presidential election and current perceptions of polarization are associated with the onset of physical and mental health conditions in adults. METHODS: We surveyed a nationally-representative sample (n = 2752) of US adults between December 2019 and January 2020. We used multivariable logistic regression to estimate associations between perceived polarization and the incidence of hypertension, high cholesterol, obesity, diabetes, and anxiety, depressive, and sleep disorders in or after 2016 and current self-rated health. Our secondary exposure variables measured perceptions of mass and elite polarization at the state and national level. Perceived mass polarization measured perceptions of the partisan gap between Democrat and Republican voters; perceived elite polarization measured perceptions of the partisan gap between Democrat and Republican elected officials. RESULTS: Participants reporting an increase in polarization had 52-57% higher odds of developing depressive disorders (OR = 1.52, 95% CI: 1.01, 2.29, P = 0.047) and anxiety disorders (OR = 1.57, 95% CI: 1.07, 2.29, P = 0.02) compared to participants who perceived no change in polarization. Those reporting high (vs. low) levels of perceived state-level mass polarization had a 49% higher odds of incident depressive disorders (P = 0.03). Participants who perceived high levels of state-level elite polarization reported a 71% higher odds of incident depressive disorders (P = 0.004) and a 49% higher odds of incident sleep disorders (P = 0.03). CONCLUSIONS: Perceptions of partisan polarization may represent important factors that are linked to the onset of mental health and sleep disorders.

The dual effect of social ties on COVID-19 spread in Japan.

We investigate why some communities experience worse COVID-19 outcomes than others. Past studies have linked the resilience of communities against crisis to social vulnerability and the capacity of local governments to provide public goods and services like health care. Disaster studies, which frequently examine the effect of social ties and mobility, may better help illuminate the current spread of COVID-19. We analyze Japan's 47 prefectures from February 12 to August 31 using 62,722 individual confirmed cases of COVID-19, paired with daily tallies of aggregate Facebook user movement among neighborhoods. Controlling for mobility levels, health care systems, government finance, gender balance, age, income, and education levels of communities, our analysis indicates that areas with strong linking social ties see no or far lower levels of COVID-19 case rates initially. However, case fatality rates rise in such communities once the disease enters as they lack horizontal (bonding) ties which can mitigate its health impacts. We anticipate this study to be a starting point for broader studies of how social ties and mobility influence COVID-19 outcomes worldwide along with shining a light on how different types of social relationships play different roles as a crisis or disaster progresses.

In the hands of a few: Disaster recovery committee networks.

When disaster strikes, urban planners often rely on feedback and guidance from committees of officials, residents, and interest groups when crafting reconstruction policy. Focusing on recovery planning committees after Japan's 2011 earthquake, tsunami, and nuclear disasters, we compile and analyze a dataset on committee membership patterns across 39 committees with 657 members. Using descriptive statistics and social network analysis, we examine 1) how community representation through membership varied among committees, and 2) in what ways did committees share members, interlinking members from certain interests groups. This study finds that community representation varies considerably among committees, negatively related to the prevalence of experts, bureaucrats, and business interests. Committee membership overlap occurred heavily along geographic boundaries, bridged by engineers and government officials. Engineers and government bureaucrats also tend to be connected to more members of the committee network than community representatives, giving them prized positions to disseminate ideas about best practices in recovery. This study underscores the importance of diversity and community representation in disaster recovery planning to facilitate equal participation, information access, and policy implementation across communities.

Substitute or complement? How social capital, age and socioeconomic status interacted to impact mortality in Japan's 3/11 tsunami.

BACKGROUND: Research underscoring the critical nature of social capital and collective action during crises often overlooks the ways that social ties interact with vulnerability factors such as age and socioeconomic status. METHODS: We use three different data structures and five types of regression models to study mortality rates across 542 inundated neighborhoods from nearly 40 cities, towns, and villages in Japan's Tohoku region which was flooded by the 11 March 2011 tsunami. RESULTS: Controlling for factors thought important in past studies - including geographic administrative, and demographic conditions - we find that social capital interacts with age and socioeconomic status to strongly correlate with mortality at the neighborhood level. For the elderly and those with lower socioeconomic status, ceteris paribus, deeper reservoirs of social capital are linked with lower levels of mortality. CONCLUSION: While most societies invest heavily in physical infrastructure to mitigate future shocks, this paper reinforces the growing call for spending on social infrastructure to develop communities which can cooperate and collaborate during crises. For the elderly and poor, social ties can serve as a literal lifeline during times of need.

Social capital's role in recovery: evidence from communities affected by the 2010 Pakistan floods.

Pakistan suffered large-scale flooding in summer 2010 that caused damage amounting to approximately USD 43 billion, claimed the lives of at least 1,700 people, and negatively affected some 20 million others. Observers have debated the degree to which social capital plays a role in recovery after a catastrophe of this magnitude. Using new survey data on 450 residents impacted by the disaster, this study found that, controlling for various confounding factors, the social capital levels of victims serve as robust correlates of life recovery. Other important variables connected with recovery include education and income, family size, occupation, material damage suffered, stability of home, and trauma experience. The findings point to a number of relevant policy recommendations, most notably that during and following major shocks, disaster managers should work to keep the social networks of victims intact so that they can benefit from interaction with family, friends, and neighbours.

Creating Community Resilience Through Elder-Led Physical and Social Infrastructure.

OBJECTIVE: Natural disasters and rapidly aging populations are chronic problems for societies worldwide. We investigated the effects of an intervention in Japan known as Ibasho, which embeds elderly residents in vulnerable areas within larger social networks and encourages them to participate in leadership activities. This project sought to deepen the connections of these elderly residents to society and to build elderly leadership and community capacity for future crises. METHODS: We carried out surveys of participants and nonparticipant residents across the city of Ofunato in Tohoku, Japan, 1 year after the intervention began. Our surveys included questions assessing participation levels in Ibasho, demographic characteristics, efficacy, social networks, and a sense of belonging. RESULTS: Regression analysis and propensity score matching of more than 1100 respondents showed that regular participation in the Ibasho project had a statistically significant and positive connection with various measures of social capital. CONCLUSIONS: Given its relatively low cost and focus on deepening cohesion, we suggest that this community-based project could be replicated and scaled up in other countries to deepen resilience, elder health, and social capital. Moving away from an emphasis on investing in physical infrastructure, we believe that disaster risk reduction strategies should center on social infrastructure. (Disaster Med Public Health Preparedness. 2017;11:120-126).

The physical and social determinants of mortality in the 3.11 tsunami.

The human consequences of the 3.11 tsunami were not distributed equally across the municipalities of the Tohoku region of northeastern Japan. Instead, the mortality rate from the massive waves varied tremendously from zero to ten percent of the local residential population. What accounts for this variation remains a critical question for researchers and policy makers alike. This paper uses a new, sui generis data set including all villages, towns, and cities on the Pacific Ocean side of the Tohoku region to untangle the factors connected to mortality during the disaster. With data on demographic, geophysical, infrastructure, social capital, and political conditions for 133 municipalities, we find that tsunami height, stocks of social capital, and level of political support for the long-ruling LDP strongly influenced mortality rates. Given the high probability of future large scale catastrophes, these findings have important policy implications for disaster mitigation policies in Japan and abroad.