Project description:The disproportionately high rates of both infections and deaths among racial and ethnic minorities (especially Blacks and Hispanics) in the United States during the COVID-19 pandemic are consistent with the conclusion that structural inequality can produce lethal consequences. However, the nature of this structural inequality in relation to COVID-19 is poorly understood. Here, we hypothesized that two structural features, racial residential segregation and income inequality, of metropolitan areas in the United States have contributed to health-compromising conditions, which, in turn, have increased COVID-19 fatalities; moreover, that these two features, when combined, may be particularly lethal. To test this hypothesis, we examined the growth rate of confirmed COVID-19 cases and deaths in an early 30-day period of the outbreak in the counties located in each of the 100 largest metropolitan areas in the United States. The growth curves for cases and deaths were steeper in counties located in metropolitan areas where Blacks and Hispanics are residentially segregated from Whites. Moreover, the effect of racial residential segregation was augmented by income inequality within each county. These data strongly suggest that racial and economic disparities have caused a greater death toll during the current pandemic. We draw policy implications for making virus-resilient cities free from such consequences.
Project description:Background: Domestic violence is a traumatic experience that can lead to physical consequences, mental disorders and financial damage. Over 18 cases per 100,000 inhabitants were reported in Brazil between 2013 and 2014. The ministry of health poses a mandatory notification of all cases of domestic violence, which is essential, bearing in mind its systemic relation to various social issues and the extensive regional differences and high socioeconomic inequalities present in Brazil. Aim: To analyze the characteristics of the notification rates of domestic violence and investigate the correlation of these with health and socioeconomic characteristics of large Brazilian cities. Methods: Retrospective data on notifications of domestic violence was collected from the National Information System for Notifiable Diseases for Brazil, 2017. Dependent variables were collected from the Brazilian Institute of Geography and Statistics and Ministry of Citizenship. Inclusion criteria were: cities larger than 100.000 habitants and that had at least 20 reports, totaling 68.313 reports in 259 cities. These were stratified by age, race and sex of victim, type of violence used, violence perpetrator, place of occurrence and means of aggression. Proportional number of notified cases was calculated for each city to expose different characteristics of reports. A multiple linear regression model was used to investigate the correlation between report rates and different socioeconomic and health variables. Results: The analysis showed a high proportion of repeated violence, use of body strength and over 50% were perpetrated by a partner or boyfriend. Report rates were higher for women, black individuals and children under four, highlighting subgroups of the population that were more vulnerable. Indeed, these groups were correlated differently with socioeconomic variables. Poverty, assessed as Bolsa Família investment, was correlated with domestic violence report rates across vulnerable groups. Conclusion: The study showed that black women and children are more vulnerable to domestic violence, highlighting deleterious effects of patriarchy and structural racism within Brazilian society. Altogether, we suggest that reducing poverty, patriarchy and structural racism could lead to fewer cases of domestic violence.
Project description:The authors estimate the associations between community socioeconomic composition and changes in coronavirus disease 2019 (COVID-19) vaccination levels in eight large cities at three time points. In March, communities with high socioeconomic status (SES) had significantly higher vaccination rates than low-SES communities. Between March and April, low-SES communities had significantly lower changes in percentage vaccinated than high-SES communities. Between April and May, this difference was not significant. Thus, the large vaccination gap between communities during restricted vaccine eligibility did not narrow when eligibility opened up. The link between COVID-19 vaccination and community disadvantage may lead to a bifurcated recovery whereby advantaged communities move on from the pandemic more quickly while disadvantaged communities continue to suffer.
Project description:INTRODUCTION:Both excessive weight gain and weight loss are important risk factors in the older population. Neighborhood environment may play an important role in weight change, but neighborhood effects on weight gain and weight loss have not been studied separately. This study examined the associations between neighborhood socioeconomic deprivation and excessive weight gain and weight loss. METHODS:This analysis included 153,690 men and 105,179 women (aged 51-70 years). Baseline addresses were geocoded into geographic coordinates and linked to the 2000 U.S. Census at the Census tract level. Census variables were used to generate a socioeconomic deprivation index by principle component analysis. Excessive weight gain and loss were defined as gaining or losing >10% of baseline (1995-1996) body weight at follow-up (2004-2006). The analysis was performed in 2015. RESULTS:More severe neighborhood socioeconomic deprivation was associated with higher risks of both excessive weight gain and weight loss after adjusting for individual indicators of SES, disease conditions, and lifestyle factors (Quintile 5 vs Quintile 1: weight gain, OR=1.36, 95% CI=1.28, 1.45 for men and OR=1.20, 95% CI=1.13, 1.27 for women; weight loss, OR=1.09, 95%% CI=1.02, 1.17 for men and OR=1.23, 95% CI=1.14, 1.32 for women). The findings were fairly consistent across subpopulations with different demographics and lifestyle factors. CONCLUSIONS:Neighborhood socioeconomic deprivation predicts higher risk of excessive weight gain and weight loss.
Project description:ObjectivesTo present the COVID Local Risk Index (CLRI), a measure of city- and neighborhood-level risk for SARS COV-2 infection and poor outcomes, and validate it using sub-city SARS COV-2 outcome data from 47 large U.S. cities.MethodsCross-sectional validation analysis of CLRI against SARS COV-2 incidence, percent positivity, hospitalization, and mortality. CLRI scores were validated against ZCTA-level SARS COV-2 outcome data gathered in 2020-2021 from public databases or through data use agreements using a negative binomial model.ResultsCLRI was associated with each SARS COV-2 outcome in pooled analysis. In city-level models, CLRI was positively associated with positivity in 11/14 cities for which data were available, hospitalization in 6/6 cities, mortality in 13/14 cities, and incidence in 33/47 cities.ConclusionsCLRI is a valid tool for assessing sub-city risk of SARS COV-2 infection and illness severity. Stronger associations with positivity, hospitalization and mortality may reflect differential testing access, greater weight on components associated with poor outcomes than transmission, omitted variable bias, or other reasons. City stakeholders can use the CLRI, publicly available on the City Health Dashboard (www.cityhealthdashboard.com), to guide SARS COV-2 resource allocation.
Project description:ObjectiveTo investigate the influence of demographic and socioeconomic factors on the COVID-19 case-fatality rate (CFR) globally.DesignPublicly available register-based ecological study.SettingTwo hundred and nine countries/territories in the world.ParticipantsAggregated data including 10 445 656 confirmed COVID-19 cases.Primary and secondary outcome measuresCOVID-19 CFR and crude cause-specific death rate were calculated using country-level data from the Our World in Data website.ResultsThe average of country/territory-specific COVID-19 CFR is about 2%-3% worldwide and higher than previously reported at 0.7%-1.3%. A doubling in size of a population is associated with a 0.48% (95% CI 0.25% to 0.70%) increase in COVID-19 CFR, and a doubling in the proportion of female smokers is associated with a 0.55% (95% CI 0.09% to 1.02%) increase in COVID-19 CFR. The open testing policies are associated with a 2.23% (95% CI 0.21% to 4.25%) decrease in CFR. The strictness of anti-COVID-19 measures was not statistically significantly associated with CFR overall, but the higher Stringency Index was associated with higher CFR in higher-income countries with active testing policies (regression coefficient beta=0.14, 95% CI 0.01 to 0.27). Inverse associations were found between cardiovascular disease death rate and diabetes prevalence and CFR.ConclusionThe association between population size and COVID-19 CFR may imply the healthcare strain and lower treatment efficiency in countries with large populations. The observed association between smoking in women and COVID-19 CFR might be due to the finding that the proportion of female smokers reflected broadly the income level of a country. When testing is warranted and healthcare resources are sufficient, strict quarantine and/or lockdown measures might result in excess deaths in underprivileged populations. Spatial dependence and temporal trends in the data should be taken into account in global joint strategy and/or policy making against the COVID-19 pandemic.
Project description:A growing body of research suggests that housing eviction is more common than previously recognized and may play an important role in the reproduction of poverty. The proportion of children affected by housing eviction, however, remains largely unknown. We estimate that one in seven children born in large U.S. cities in 1998-2000 experienced at least one eviction for nonpayment of rent or mortgage between birth and age 15. Rates of eviction were substantial across all cities and demographic groups studied, but children from disadvantaged backgrounds were most likely to experience eviction. Among those born into deep poverty, we estimate that approximately one in four were evicted by age 15. Given prior evidence that forced moves have negative consequences for children, we conclude that the high prevalence and social stratification of housing eviction are sufficient to play an important role in the reproduction of poverty and warrant greater policy attention.
Project description:In dealing with the impacts of climate change, mitigation efforts play a crucial role. As one of the G20 countries on the list of the top 5 biggest contributors to emissions, Indonesia must play an active role. With all their characteristics and as one of the most significant contributors to global emissions, cities are fully responsible as a core area for climate mitigation. By analyzing the spatial and socioeconomic characteristics within the city scope, this study examines 32 representative cities and municipalities in Indonesia to understand the condition of carbon emissions and sequestration. Emissions and sequestration in selected cities in Indonesia show varying statuses; most cities have higher emission levels than sequestration, but some cities do the opposite. In addition, emissions and sequestration are also influenced by many complex and interrelated factors, including spatial (distribution, intensity, LULC, geographical conditions, total area), social (total population, urbanization rate, employment rate), economic (GDP/GRDP), and technological (industry structure and energy sector). As an archipelagic country, the uniqueness of cities in Indonesia, primarily located in coastal and waterfront areas, also influences the emission intensity, which tends to be lower in these areas on a micro basis. Cities classified as economically developed contribute more emissions at the national level. Therefore, a characteristic-based classification of the selected cities can encourage policy implications according to the characteristics of each city. These cities can learn from each other, especially from cities with high sequestration rates, to develop in a sustainable way while supporting national mitigation targets.
Project description:Osteoporosis is the most common disease of the musculoskeletal system in old age. Therefore, research on osteoporosis risk factors is actively being conducted. However, whether socioeconomic inequality is associated with the prevalence and diagnosis experience of osteoporosis remains largely unexplored. This study aims to investigate whether socioeconomic inequality can be a risk factor for osteoporosis in postmenopausal women. Cross-sectional data of 1,477 postmenopausal women aged over 50 obtained from the Korea National Health and Nutrition Examination Survey V-2 were analyzed. Univariate analyses were performed to calculate the prevalence of osteoporosis and the rate of osteoporosis diagnosis experience according to the risk factor categories. Multivariate logistic regression analysis was performed to identify the independent variables' associations with osteoporosis prevalence and diagnosis experience. The prevalence of osteoporosis was 34.8%, while the diagnosis experience rate was 22.1%. The higher the age, the higher the probability of osteoporosis presence and diagnosis experience. The lowest household income level was associated with a 1.63 times higher risk of osteoporosis. On the contrary, this factor was not significant for diagnosis experience. These results were similar for the 50-59 and 60-69 age groups. Among postmenopausal women, those who are older and have low socioeconomic levels are at a high risk of developing osteoporosis. Moreover, the lower the socioeconomic level, the lower the awareness of osteoporosis. Therefore, there is a need to develop more proactive preventive measures in postmenopausal women with low socioeconomic levels.
Project description:Housing vacancies have become a major issue in depopulating, or shrinking, cities. All urban areas, however, are subject to some degree of vacant housing. A small percentage is necessary to allow mobility and sufficient space for growth, and is an indicator of healthy urbanization. Conversely, widespread housing vacancies may indicate structural crisis due to property abandonment. Land area and population changes, shifts in employment, demographic trends, development intensity, and economic conditions are primary drivers of housing vacancies. The degree to which these interrelated factors contribute can fluctuate by city. This paper explores relationships between factors contributing to housing vacancies over time to identify changes in underlying factors. The research examines U.S. cities of over 100,000 population over the period of 1960-2010, conducting multivariate regression analyses in 10-year periods and performing longitudinal panel analyses. The regressions examine changes in urban housing vacancy factors over time while the panel models assess which factors have remained consistent. The panel model results indicate that population change, percent nonwhite populations, unemployment and density are consistent, significant predictors of housing vacancies, The incremental regression models suggest that unemployment and regional location have also been strong indicators of housing vacancies. These results, while somewhat exploratory, provide insight into long-term data that cities should track over time to determine the optimal policy approaches to offset housing vacancies.