Cross-sectional Ecological Study Research Articles

What is the role of particulate matter 2.5 (PM2.5) on excess weight? A cross-sectional study in young Spanish people aged 2─14 years

PurposeTo assess the relationship between particulate matter 2.5 (PM2.5) levels and the prevalence of excess weight in a representative sample of Spanish young people aged 2─14 years. MethodsThis was an ecological cross-sectional study using data from the 2017 wave of the Encuesta Nacional de Salud Española (ENSE), a nationally representative survey of the Spanish young and adult population. The final sample included 4378 young Spanish people (51.0% boys). The weight (kg) and height (cm) of the study participants were proxy-reported by parents or guardians. Excess weight was determined according to the age- and sex-criteria of the International Obesity Task Force. The PM2.5 level was calculated as the annual monitoring data indicator for 2017 among the different regions in Spain. Logistic regression models were performed to estimate the relationships between PM2.5 and weight. ResultsCompared to young people located in regions with low levels of PM2.5, those reporting greater odds for excess weight were found in regions with medium PM2.5 (OR = 1.23; 95% CI, 1.02–1.49) and high PM2.5 (OR = 1.35; 95% CI, 1.11–1.64) after adjusting for several sociodemographic, lifestyle and environmental covariates. ConclusionsThe prevalence of excess weight in young people was positively associated with PM2.5 levels in Spain. This finding supports the hypothesis that air pollution exposure can result in excess weight in the young population, which, in turn, might lead to the development of metabolic disorders. From a socioecological perspective, a practical need to take environmental factors into consideration is important to address unhealthy weight in Spanish young people.

Geographic Variation in Top-10 Prescribed Medicines and Potentially Inappropriate Medication in Portugal: An Ecological Study of 2.2 Million Older Adults.

Multiple medication intake by older adults is considered a serious public health concern since it is associated with increased risk of adverse drug reactions and potentially inappropriate medication (PIM). This study described the top-10 prescribed active substances considering geographical distribution and PIM prescription in older adults. A cross-sectional ecological study using data on the active substances prescribed to people aged 65 years or older during 2020 was conducted. Information on active substances and the respective defined daily doses (DDD) stratified by age group, sex and region were collected from a Portuguese health administrative database. The average number of prescribed packages and DDD per 1000 inhabitants per day of top-10 active substances were assessed. This study included a total of 2,228,090 older adults (58% females). The furosemide and atorvastatin were the active substances with higher prescription rates (mean DDD/1000 inhabitants/day) in all ARS in both males and females, in comparison with the other top-10 active substances. Our results showed geographic differences in prescription, illustrated by more prescriptions in ARS North and Centre and fewer prescriptions in ARS Algarve. In females, two out of the 10 most prescribed active substances were PIM (benzodiazepines and opioids). Geographic disparities in PIM prescription across Portuguese regions were also observed. This study shows that drugs for the cardiovascular system were the active substances most prescribed to older adults. The prescription of benzodiazepines and opioids, classified as PIM, among females, alerts officials to the need of health policies to decrease inappropriate medication. The observed geographic differences in the 10 most prescribed active substances and in PIM prescription emphasized the importance of investing in medication optimization across the Portuguese regions.

Association of UV Radiation Exposure, Diagnostic Scrutiny, and Melanoma Incidence in US Counties

Although UV radiation exposure is the conventionally reported risk factor for cutaneous melanoma, an alternative exposure is diagnostic scrutiny: the more physicians look for and biopsy moles, the more melanoma they find. To assess the association of proxies for UV radiation exposure and diagnostic scrutiny with geographical patterns of melanoma incidence. This was a cross-sectional ecological analysis of the 727 continental US counties reporting to the Surveillance, Epidemiology, and End Results (SEER) Program (among a total of 3108 counties). Environmental data relevant to UV radiation exposure (from a variety of sources), Health Resources and Services Administration data relevant to diagnostic scrutiny, and SEER data on melanoma incidence among the non-Hispanic White population diagnosed with melanoma from 2012 through 2016 were combined. Data analysis was performed between January 2020 and July 2022. Three UV radiation proxies (UV daily dose, cloud variability, and temperature variability) and 3 diagnostic scrutiny proxies (median household income, dermatologists, and primary care physician supply). Melanoma incidence (in situ and invasive cancers). In total, 235 333 melanomas were diagnosed. Proxies for UV radiation exposure changed gradually across geography, while melanoma incidence and proxies for diagnostic scrutiny changed abruptly across contiguous counties. The UV daily dose, a variable the National Cancer Institute specifically developed for melanoma analyses, was uncorrelated with incidence (r = 0.03; P = .42). For context, smoking prevalence was highly correlated with lung cancer incidence in the same counties (r = 0.81; P < .001). Melanoma incidence was correlated with median household income (r = 0.43; P < .001). Counties with no dermatologists and shortages of primary care physicians had the lowest incidence, while counties amply supplied with both had the highest, despite having lower mean UV daily dose. There was little association between melanoma incidence and melanoma mortality (r = 0.09; P = .05), while the analogous association in lung cancer was strong (r = 0.96; P < .001). In this cross-sectional ecological study, the current geographical pattern of melanoma incidence across US counties was less associated with proxies for UV radiation exposure and more so with proxies for diagnostic scrutiny. Incidence-the fundamental epidemiologic measure of disease frequency-now had little association with the feared outcome of melanoma: death.

Social Determinants and Leprosy in High Endemic Regions of Myanmar: an Ecological Study between 2016 and 2019

Leprosy has been a public health problem in Myanmar for many centuries. This study aims to explore the situation of leprosy and the association between leprosy and social determinants at the township level in seven endemic regions in Myanmar. The objectives of the study are to (i) describe the incidence and severity of leprosy and the disability due to leprosy in Myanmar between 2016 and 2019, and (ii) determine the correlation between leprosy incidence and social determinants in Myanmar in 2019. We used annual surveillance data of leprosy cases between 2016 and 2019 from the National Leprosy Control Program, Myanmar, and social determinant variables from the 2019 General Administration Department Census Report of Myanmar. An ecological cross-sectional study was conducted. Univariable and multivariable analyses applying zero-inflated negative binomial regression models were used. A geographic information system mapping was used to visualize leprosy cases, disease severity, and disability due to leprosy between 2016 and 2019. The number of all leprosy indicators changing pattern was seen obvious between regions. The eastern region showed relatively an increase in detection of new cases in 2019 compared with years 2017 and 2018. The increase in the detection of multibacillary leprosy cases was also observed in the eastern region during this period. Yet, the detection of Grade-II disability cases across regions remained relatively stable throughout study years. The number of tuberculosis cases per 1,000 population was significantly correlated with leprosy incidence at the township level (risk ratio 1.27, 95% confidence interval 1.04–1.55). These findings highlight the importance of enhancing active case finding campaigns in high-endemic regions, especially the eastern states of Myanmar. Integration of leprosy and tuberculosis case-finding programmes is likely to help leverage resources and maximize efforts to cope with leprosy problems in Myanmar.

Global Association between Traditional Japanese Diet Score and All-Cause, Cardiovascular Disease, and Total Cancer Mortality: A Cross-Sectional and Longitudinal Ecological Study

Objective Studies conducted on Japanese people have suggested that a traditional Japanese diet contributes to good health, longevity, and protection against several non-communicable diseases. However, it is unknown whether traditional Japanese dietary patterns are associated with all-cause mortality, cardiovascular disease, and cancer mortality globally. The purpose of this cross-sectional and longitudinal ecological study is to clarify the global association between the traditional Japanese diet score (TJDS) and all-cause, cardiovascular disease, and total cancer mortality. Methods Data on food supply and all-cause mortality, cardiovascular disease mortality, total cancer mortality, and covariables by country were obtained from a relevant internationally available database. TJDS by country was calculated from eight food groups and the total score ranged from −8 to 8, with higher scores indicating greater adherence to a traditional Japanese diet. We evaluated the cross-sectional and 10-year longitudinal association between TJDS and all-cause, cardiovascular disease, and total cancer mortality using 2009 as the baseline in 142 countries with populations of more than one million. A cross-sectional analysis and a longitudinal analysis were performed using three general linear models or three linear mixed models with different covariables. Results In cross-sectional models controlled for fully-adjusted covariables, TJDS was negatively associated with all-cause mortality (β ± standard error; −43.819 ± 11.741, p < 0.001), cardiovascular disease mortality (−22.395 ± 4.638, p < 0.001), and total cancer mortality (−3.893 ± 1.048, p < 0.001). In 10-year longitudinal models controlled for fully-adjusted covariables, TJDS was significantly negatively associated with all-cause mortality (−31.563 ± 7.695, p < 0.001), cardiovascular disease mortality (−16.249 ± 4.054, p < 0.001), and total cancer mortality (−3.499 ± 0.867, p < 0.001). Conclusions This cross-sectional and longitudinal ecological study suggests that the traditional Japanese diet is associated with lower all-cause mortality, cardiovascular disease mortality, and total cancer mortality, worldwide.

Measuring Obesogenicity and Assessing Its Impact on Child Obesity: A Cross-Sectional Ecological Study for England Neighbourhoods.

Both major influences on changing obesity levels (diet and physical activity) may be mediated by the environment, with environments that promote higher weight being denoted obesogenic. However, while many conceptual descriptions and definitions of obesogenic environments are available, relatively few attempts have been made to quantify obesogenic environments (obesogenicity). The current study is an ecological study (using area units as observations) which has as its main objective to propose a methodology for obtaining a numeric index of obesogenic neighbourhoods, and assess this methodology in an application to a major national dataset. One challenge in such a task is that obesogenicity is a latent aspect, proxied by observed environment features, such as poor access to healthy food and recreation, as well as socio-demographic neighbourhood characteristics. Another is that obesogenicity is potentially spatially clustered, and this feature should be included in the methodology. Two alternative forms of measurement model (i.e., models representing a latent quantity using observed indicators) are considered in developing the obesogenic environment index, and under both approaches we find that both food and activity indicators are pertinent to measuring obesogenic environments (though with varying relevance), and that obesogenic environments are spatially clustered. We then consider the role of the obesogenic environment index in explaining obesity and overweight rates for children at ages 10–11 in English neighbourhoods, along with area deprivation, population ethnicity, crime levels, and a measure of urban–rural status. We find the index of obesogenic environments to have a significant effect in elevating rates of child obesity and overweight. As a major conclusion, we establish that obesogenic environments can be measured using appropriate methods, and that they play a part in explaining variations in child weight indicators; in short, area context is relevant.

COVID-19 Vaccine Uptake among US Adults According to Standard Occupational Groups.

This cross-sectional ecological study examined the relationship between neighborhood-level standard occupational groups in the USA and COVID-19 vaccine uptake using 774 census tract data, each consisting of approximately 1600 housing units. The neighborhood-level COVID-19 vaccination uptake data were retrieved from Harris County Public Health, Harris County, Texas. The standard occupational group data were from the US Census Bureau. We calculated the incidence rate ratios (IRRs) for vaccine uptake using bivariate and multivariable Poisson regression models. In the adjusted models, we found that the healthcare practitioner/technician (IRR: 1.008; 95% CI: 1.003–1.014; p = 0.001), business/management/legal (IRR: 1.011; 95% CI: 1.008–1.013; p < 0.001), computer/engineering/life/physical/social science (IRR: 1.018; 95% CI: 1.013–1.023; p < 0.001), and arts/design/entertainment/sports/media (IRR: 1.031; 95% CI: 1.018–1.044; p < 0.001) occupational groups were more likely to have received the full regimen of a COVID-19 vaccine. On the contrary, the building/installation/maintenance/repair (IRR: 0.991; 95% CI: 0.987–0.995; p < 0.001), construction/extraction/production (IRR: 0.991; 95% CI: 0.988–0.995; p < 0.001), transportation/material moving (IRR: 0.992; 95% CI: 0.987–0.997; p = 0.002), food preparation/serving related (IRR: 0.995; 95% CI: 0.990–0.999; p = 0.023), and personal care/services (IRR: 0.991; 95% CI: 0.985–0.998; p = 0.017) groups were less likely to have received the complete dose of a COVID-19 vaccine. White-collar workers were more likely to be vaccinated than blue-collar workers. We adjusted for age, sex, and race/ethnicity in the multivariable analysis. The low vaccine uptake among certain occupational groups remains a barrier to pandemic control. Engaging labor-centered stakeholders in the development of vaccination interventions may increase uptake.

Associations between Florida counties' COVID-19 case and death rates and meaningful use among Medicaid providers: Cross-sectional ecologic study.

Although the Health Information Technology for Economic and Clinical Health (HITECH) Act has accelerated adoption of Electronic Health Records (EHRs) among Medicaid providers, only half achieved Meaningful Use. Furthermore, Meaningful Use' impact on reporting and/or clinical outcomes remains unknown. To address this deficit, we assessed the difference between Medicaid providers who did and did not achieve Meaningful Use regarding Florida county-level cumulative COVID-19 death, case and case fatality rates (CFR), accounting for county-level demographics, socioeconomic and clinical markers, and healthcare environment. We found that cumulative incidence rates of COVID-19 deaths and CFRs were significantly different between the 5025 Medicaid providers not achieving Meaningful Use and the 3723 achieving Meaningful Use (mean 0.8334/1000 population; SD = 0.3489 vs. mean = 0.8216/1000; SD = 0.3227, respectively) (P = .01). CFRs were .01797 and .01781, respectively, P = .04. County-level characteristics independently associated with increased COVID-19 death rates and CFRs include greater concentrations of persons of African American or Black race, lower median household income, higher unemployment, and higher concentrations of those living in poverty and without health insurance (all P < .001). In accordance with other studies, social determinants of health were independently associated with clinical outcomes. Our findings also suggest that the association between Florida counties' public health outcomes and Meaningful Use achievement may have had less to do with using EHRs for reporting of clinical outcomes and more to do with using EHRs for coordination of care-a key measure of quality. The Florida Medicaid Promoting Interoperability Program which incentivized Medicaid providers towards achieving Meaningful Use, has demonstrated success regarding both rates of adoption and clinical outcomes. Because the Program ends in 2021, we support programs such as HealthyPeople 2030 Health IT which address the remaining half of Florida Medicaid providers who have not yet achieved Meaningful Use.

1218-P: Immigrant Density and Prevalence of Diabetes in American Neighborhoods

Background: The “healthy immigrant effect” suggests that despite immigrants generally demonstrating lower socioeconomic status than non-immigrants, they have lower age-related disease prevalence and mortality compared to non-immigrants. Recent evidence suggests immigrants may have higher levels of physical activity and may also influence their neighbors to decrease sedentary behavior. Drawing from the literature, we investigated the association between immigrant density with the prevalence of diabetes in neighborhoods and of both foreign-born and U.S.-born populations by ZIP code level. Methods: In this retrospective, cross-sectional ecological study, we used data from the American Community Survey (ACS) and the CDC Behavioral Risk Factor Surveillance System (BRFSS) for 2018. We performed multiple regression to test our predictive model that appointed obesity and physical activity as possible mediators between immigrant density and diabetes. Participants: ZIP codes with more than 16 foreign-born individuals (324out of 41692 total ZCTAs) Results: Higher immigrant density in a neighborhood is associated with lower prevalence of diabetes (beta estimate = −0.056657; r-squared = 0.02709) ; this remains true even after adjusting for prevalence of obesity (0.038646; 0.5356) , physical activity (-0.014093; 0.7097) , and both (−0.001015; 0.7168) , with all p-values &amp;lt; 0.001. We concluded that immigrant density is a potential protective factor of diabetes, and the relationship is mediated by the prevalence of obesity and physical activity. Discussion: The effects may differ depending on the racial/ethnic composition of the neighborhood. A previous study has shown that living in communities with a high Hispanic concentration (&amp;gt;=25%) was associated with an increase in body mass index (BMI) and higher odds for obesity in non-Hispanic Whites, respectively; meanwhile, the opposite effect is observed for communities with high Asian concentration. As a next step, we will disaggregate our results by race.

Socioeconomic status and COVID-19-related cases and fatalities in the world: A cross-sectional ecological study.

Background and AimsThe COVID‐19 pandemic poses an extraordinary threat to global public health. We designed an ecological study to explore the association between socioeconomic factors and the COVID‐19 outcomes in 184 countries, using the geographic map and multilevel regression models.MethodsWe conducted a cross‐sectional ecological study in 184 countries. We performed regression analysis to assess the association of various socioeconomic variables with COVID‐19 outcomes in 184 countries, using ordinary least squares and multilevel modeling analysis. We performed two‐level analyses with countries at Level 1 and geographical regions at Level 2 in multilevel modeling analysis, using the same set of predictor variables used in ordinary least squares.ResultsThere was a significant relationship between COVID‐19 cases rate (Log) per 100,000 inhabitants‐day at risk with human development index (HDI), percentage of the urban population, unemployment, and cardiovascular disease prevalence. The results displayed that the variances are varied between Level 1 (country level) and Level 2 (World Health Organization [WHO] regions), meaning that the geographic distribution represented a proportion of the changes in the COVID‐19 outcomes.ConclusionThe study suggests that in addition to the socioeconomic status affects the COVID‐19 outcomes, countries' geographical location makes a part of changes in outcomes of diseases. Therefore, health policy‐makers could overcome morbidity and mortality in COVID‐19 by controlling the socioeconomics factors.

Sea Level Rise and City-Level Climate Action

Background: Climate change is the greatest threat to global health in the 21st century. Rising sea levels are one particularly concerning manifestation of this and many of the world’s largest cities are vulnerable to sea level rise (SLR). Thus, urban climate adaptation and mitigation policies are increasingly important to protect population health. Objectives: This study aimed to determine whether being at risk of SLR was associated with city-level climate action. It also aimed to assess the wider drivers of climate action in cities, in order to guide ongoing efforts to motivate climate action, assess public health preparedness and identify research gaps. Methods: This is an ecological cross-sectional study using secondary data from CDP, the Urban Climate Change Research Network (UCCRN), World Bank, United Nations Cities and EM-DAT (Emergency Events Database). The study population consisted of 517 cities who participated in CDP’s 2019 Cities Survey. Multivariable logistic regression was utilized to assess the relationship between risk of SLR and city-level climate action, and secondly, to assess the wider determinants of city-level climate action. Results: There was evidence of crude associations between risk of SLR and three outcome variables representing city-level climate action. However, after adjusting for confounding variables, these crude associations disappeared. World region, national income status and urban population were shown to be stronger predictors of city-level climate action. Conclusion: It is concerning for population health that there is no association demonstrated between risk of SLR and climate action. This could indicate a lack of awareness of the risks posed by SLR within urban governance. To fulfil their health protection responsibilities, it is essential that public health professionals take a leading role in advocating for climate action.

Geospatial models for SARS-CoV-2 outbreak control in Cartagena and Barranquilla, Colombia, 2020Modelos geoespaciais para controle de surtos de SARS-CoV-2 em Cartagena e Barranquilla, Colômbia, 2020

RESUMENObjetivo.Determinar la estructura temporal y espacial del virus del síndrome respiratorio agudo grave (SARS-CoV-2, por su sigla en inglés), causante de la enfermedad por coronavirus (COVID-19, por su sigla en inglés) en las ciudades de Cartagena y Barranquilla para tomar acciones necesarias que apoyen el rastreo de contactos.Métodos.Estudio ecológico transversal que incluye análisis espacial basado en densidades Kernel de variables como casos, alertas desde una aplicación móvil, vulnerabilidad poblacional, índice de pobreza multidimensional, aplicación de interpolación espacial (IDW, por su sigla en inglés) de los casos activos y, por último, la aplicación de la técnica de superposición espacial como resultado final. Se utilizó la base de datos del Instituto Nacional de Salud de las ciudades de Cartagena y Barranquilla y el Departamento de Estadística Nacional.Resultados.El análisis determinó el comportamiento epidemiológico ascendente de los casos en las dos ciudades e identificó la dirección espacial de propagación de la enfermedad en los barrios, a través de la interpolación espacial. Se detectaron las zonas en las cuales intervenir en 15 barrios de Cartagena y 13 de Barranquilla, en 50 metros alrededor de los casos activos con menos de 21 días de evolución y según las capas de riesgo geográfico, como mecanismo para frenar la propagación de la COVID-19.Conclusiones.El análisis espacial permitió determinar la estructura temporal y espacial como metodología complementaria útil para el rastreo de contactos, y aportó la evidencia científica necesaria para la aplicación de medidas de intervención directa donde fuera necesario, dirigidas a reducir el contagio del SARS-CoV-2.

Adult Anopheles Mosquito Distribution at a Low and High Malaria Transmission Site in Tanzania.

Malaria parasites are only transmitted by female mosquitoes of the genus Anopheles; hence, the disease's distribution is linked to that of the vector mosquitoes. As such, the goal of this study was to find out the spatial and temporal distribution of Anopheles mosquito adults in the research sites. This was a repeated cross-sectional ecological study that took place in Morogoro and Dodoma, Tanzania. Vacuum aspiration was used to collect mosquitoes both outside and inside human dwellings. All mosquito-related data was collected and entered into appropriate data collection forms. Female mosquitoes were recognized morphologically using Gillies and Coetzee morphological criteria, followed by PCR. In total, about 2742 Anopheles mosquitoes with an average collection of 18.21 ± 1.12 per day were collected outside human houses of which 1717 (10.51 ± 1.17) and 1025 (8.42 ± 1.41) were collected from Morogoro and Dodoma, respectively. Of the captured mosquitoes, 89.0%, 10.0%, and 1.0% were recognized as Anopheles arabiensis, Anopheles gambiae s.s., and Anopheles quadrianulatus, respectively. The distribution varied significantly with seasons, whereby 302 (4.72 ± 1.04) and 2440 (12.96 ± 1.52) mosquitoes were captured in the cold-dry and warm-wet season, respectively (p < 0.0001). Of the captured mosquitoes, 42.33%, 16.33%, 14.96%, and 4.27 were found on the ceiling, stored junks, verandas, and barks/tree, respectively. In malaria-endemic countries, vector control forms an important component of the malaria control efforts. This study found significant variation of Anopheles mosquito abundance in time and space with Anopheles arabiensis being the most predominant malaria vector. This signifies the need to introduce mosquito control methods that will target the less anthropophilic Anopheles arabiensis or the immature aquatic stages. The study further found that underbeds, store room/piled bags, and undisturbed curtains were the most preferred resting places by mosquitoes signifying to be the most effective strategic sites for spraying insecticides during the implementation of indoor residual spraying (IRS).

National characteristics associated with prevalence of depression and anxiety symptoms: a cross-sectional ecological study

Cross-national comparisons of the prevalence of mental disorders have relied on lay-administered interviews scored using complex diagnostic algorithms. However, this approach has led to some paradoxical findings, with more vulnerable countries showing lower prevalence, and its appropriateness for cross-national comparisons has been questioned. This study used an alternative method involving simple questions from social surveys to assess the prevalence of specific depression and anxiety symptoms, and investigated their association with national indicators of human development, quality of government, mental health resources, and mental health governance. The study used data on the prevalence of three symptoms indicating depression or anxiety: sadness, worry, and unhappiness. These data were taken from the Gallup World Poll (142 countries) and the World Values Survey (77 countries). National characteristics examined covered indicators of human development (income, life span, education, gender equality), quality of government (human freedom, perceptions of corruption), mental health resources (per capita numbers of psychiatrists, mental health nurses, psychologists, and social workers), and mental health governance (whether there is a national mental health plan and a mental health law). All the human development and quality of government indicators, and some of the mental health resource indicators, were strongly associated with a lower prevalence of symptoms. Populations of nations with higher human development, quality of government, and mental health resources have better mental health when measured by the prevalence of specific symptoms.

A população indígena Xavante em Mato Grosso: características sociodemográficas relacionadas à saúde

ABSTRACT Objective To compare Xavante sociodemographic indicators from six indigenous lands with the non-indigenous population residing in rural areas of four adjacent microregions. Method This is an ecological cross-sectional study, with comparative analyzes between indigenous and non-indigenous residents in the state of Mato Grosso, Brazil. Age and sex structure, literacy rate, income, household sanitation conditions and mortality were compared. Results A total of 14,905 Xavante people and 78,106 non-indigenous people (white, black, yellow and brown) residing in rural areas were characterized. The age structure revealed divergent patterns, 40.0% of Xavante were under 10 years old, against 15.0% of non-indigenous people in the same age group. Regarding non-indigenous people, the Xavante had a higher illiteracy rate (31.3% vs. 9.9%), and 84.1% of the households did not have a bathroom or toilet, 39.6% of Xavante people did not declare an income against 6.5% for the non-indigenous. Conclusion and implication for practice Data on ethnicity, collected for the first time by a census, are essential for demographic analyzes of specific segments of the population, and in the case of the Xavante, they reveal inequalities in relation to non-indigenous people.

County-level factors underlying opioid mortality in the United States

Background Mortality from overdoses involving opioids in the United States (U.S.) has reached epidemic proportions. More research is needed to examine the underlying factors contributing to opioid-related mortality regionally. This study’s objective was to identify and examine the county-level factors most closely associated with opioid-related overdose deaths across all counties in the U.S. Methods: Using a national cross-sectional ecological study design, we analyzed the relationships between 17 county-level characteristics in four categories (i.e. socio-economic, availability of medical care, health-related concerns, and demographics) with opioid mortality. Data were extracted from the Robert Wood Johnson County Health Rankings aggregate database and Centers for Disease Control and Prevention (CDC)’s Wide-ranging Online Data for Epidemiological Research (WONDER) system. Results: There were 1058 counties (33.67% of 3142 nationally) with reported opioid-related fatalities. Median opioid-related mortality was 15.61 per 100,000 persons. Multivariate regression results indicate that counties with the highest opioid-related mortality had increased rates of tobacco use, HIV, Non-Hispanic Caucasians, and females and were rural areas, but lower rates of food insecurity and uninsured adults. The rates of tobacco use and HIV had the strongest association with mortality. Availability of either mental health or primary care providers were not significantly associated with mortality. Severe housing problems, high school graduation rate, obesity, violent crime, and median household income also did not contribute to county-level differences in overdose mortality. Conclusions: Future health policies should fund further investigations and ultimately address the most influential and significant underlying county-level factors associated with opioid-related mortality.

PHYSICAL ACTIVITY AND MORTALITY DUE TO COVID-19 IN THE BRAZILIAN CAPITALS: AN ECOLOGICAL ANALYSIS

ABSTRACT Introduction: Few studies have analyzed the association between physical activity and hospitalizations or mortality as a result of the new coronavirus, particularly in Brazil. Objective: To analyze the association between physical activity and deaths by Covid-19 in the Brazilian capitals. Method: An observational cross-sectional ecological study, in which data on the prevalence of physical activity during leisure time, and deaths by Covid-19 were analyzed for twenty-six Brazilian capitals plus the Federal District. Data were collected through the Risk Factor Surveillance System for chronic non-communicable diseases, and SUS Analytical for COVID-19 in Brazil, of the Brazilian Ministry of Health. For the data analysis, simple Pearson correlation and multiple regression were used, with a level of significance of 5%. Results: The data show the existence of an inverse correlation between physical activity during leisure time and accumulated deaths (r = −0.44, p = 0.03), mortality rate/100,000 inhabitants (r = −0.43, p = 0.02), and the lethality of the disease (r = −0.51, p = 0.01). They also show an inverse association between physical activity during leisure time and accumulated deaths (β = −485.1, p = 0.04), as well as with the lethality of the disease (β = −0.21, p = 0.02), even after adjusting for confounding variables. Conclusion: The inverse association observed between physical activity, accumulated deaths, and lethality of Covid-19 can bring important reflections on the actions that have been implemented by government agencies, at both state and municipal levels, in relation to the practice of physical activity by the population. Level of evidence III; Cross-sectional ecological study.

Trends of amenable deaths due to healthcare within the European Union countries. Exploring the association with the economic crisis and education

The study of premature deaths from causes that are generally preventable given the current availability of healthcare – called amenable deaths due to healthcare – provides information on the quality of services. However, they are not only impacted by healthcare characteristics: other factors are also likely to influence. Therefore, identifying the association between amenable deaths due to healthcare and health determinants, such as education, might be the key to preventing these deaths in the future. Still unclear however, is how this works and how amenable deaths due to healthcare are distributed and evolve within the European Union (EU) below the national level. We therefore studied the geographical and temporal patterns of amenable deaths due to healthcare in the 259 EU regions from 1999 to 2016, including the 2007–2008 financial crisis and the post-2008 economic downturn, and identified whether any association with education exists.A cross-sectional ecological study was carried out. Using a hierarchical Bayesian model, we estimated the average smoothed Standardized Mortality Ratios (sSMR). A regression model was also applied to measure the relative risks (RR) at 95% credible intervals for cause-specific mortality association with education.Results show that amenable deaths due to healthcare decreased globally. Nevertheless, the decrease is not the same across all regions, and inequalities within countries do persist, with lower mortality ratios seen in regions from Central European countries and higher mortality ratios in regions from Eastern European countries. Also, the evolution trend reveals that after the financial crisis, the number of these deaths increased in regions across almost all EU countries. Moreover, educational disparities in mortality emerged, and a statistical association was found between amenable deaths due to healthcare and early exit from education and training.These results confirm that identifying and understanding the background of regional differences may lead to a better understanding of the amenable deaths due to healthcare and allow for the application of more effective policies.

Investigating geographical variation in the use of mental health services by area of England: a cross-sectional ecological study

BackgroundThere is evidence of geographical variation in the use of mental health services in the UK and in international settings. It is important to understand whether this variation reflects differences in the prevalence of mental disorders, or if there is evidence of variation related to other factors, such as population socioeconomic status and access to primary care services.MethodsThis is a cross-sectional ecological study using Public Health England data. The unit of analysis was the population served by clinical commissioning groups (CCGs), National Health Service (NHS) catchment areas. The analysis explored associations between area characteristics and the number of people in contact with mental health services using regression modelling. Explanatory variables included age, gender, prevalence of severe mental illness (SMI), prevalence of common mental disorder (CMD), index of multiple deprivation (IMD), unemployment, proportion of the population who are Black and Minority Ethnic (BAME), population density, access to and recovery in primary care psychological therapies. Unadjusted results are reported, as well as estimates adjusted for age, prevalence of CMD and prevalence of SMI.ResultsThe populations of 194 CCGs were included, clustered within 62 trusts (NHS providers of mental health services). The number of people in contact with mental health services showed wide variation by area (range from 1131 to 5205 per 100,000 population). Unemployment (adjusted IRR 1.11; 95% CI 1.05 to 1.17; p < 0.001) and deprivation (adjusted IRR 1.02 95% CI 1.01 to 1.04; p < 0.001) were associated with more people being in contact with mental health services. Areas with a higher proportion of the population who are BAME (IRR 0.95 95% CI 0.92 to 0.99 p = 0.007) had lower service use per 100,000 population. There was no evidence for association with access to primary care psychological therapies.ConclusionsThere is substantial variation in the use of mental health services by area of England. Social factors including deprivation, unemployment and population ethnicity continued to be associated with the outcome after controlling for the prevalence of mental illness. This suggests that there are factors that influence the local population use of mental health services in addition to the prevalence of mental disorder.

Mapping the geodemographics of racial, economic, health, and COVID-19 deaths inequalities in the conterminous US

A large number of studies have examined individual-level factors that increase COVID-19 fatalities. However, no research has focused on the geodemographic classification of the most susceptible communities to COVID-19. In this cross-sectional ecological study, we used local fuzzy geographically-weighted clustering to create the socioeconomic profile of the US counties in relation to COVID-19 death rates. We demonstrate that living in a county which has households with lower income, people with a lack of health insurance, a high African-American percentage, and lower education level, lead to 27.12% higher COVID-19 death rates than the national median, and 72.56% higher compared to the least vulnerable counties. Compared to counties with a high COVID-19 death rate, counties with a low COVID-19 death rate have 44.90% higher annual median household income and nearly double house worth (89.51% more). Results show that the effects of the COVID-19 pandemic are not universal and that the minoritised and impoverished populations suffer more. Our analysis can effectively pinpoint the most vulnerable counties and importantly allows for understanding the socioeconomic context in which tailored interventions can be applied to mitigate COVID-19 deaths.