Exploring COVID-19 census burdens by US hospital characteristics: Implications of quality reporting at rural and critical access hospitals.

PURPOSE: By assessing longitudinal associations between COVID-19 census burdens and hospital characteristics, such as bed size and critical access status, we can explore whether pandemic-era hospital quality benchmarking requires risk-adjustment or stratification for hospital-level characteristics. METHODS: We used hospital-level data from the US Department of Health and Human Services including weekly total hospital and COVID-19 censuses from August 2020 to August 2023 and the 2021 American Hospital Association survey. We calculated weekly percentages of total adult hospital beds containing COVID-19 patients. We then calculated the number of weeks each hospital spent at Extreme (≥20% of beds occupied by COVID-19 patients), High (10%-19%), Moderate (5%-9%), and Low (<5%) COVID-19 stress. We assessed longitudinal hospital-level COVID-19 stress, stratified by 15 hospital characteristics including joint commission accreditation, bed size, teaching status, critical access hospital status, and core-based statistical area (CBSA) rurality. FINDINGS: Among n = 2582 US hospitals, the median(IQR) weekly percentage of hospital capacity occupied by COVID-19 patients was 6.7%(3.6%-13.0%). 80,268/213,383 (38%) hospital-weeks experienced Low COVID-19 census stress, 28% Moderate stress, 22% High stress, and 12% Extreme stress. COVID-19 census burdens were similar across most hospital characteristics, but were significantly greater for critical access hospitals. CONCLUSIONS: US hospitals experienced similar COVID-19 census burdens across multiple institutional characteristics. Evidence-based inclusion of pandemic-era outcomes in hospital quality reporting may not require significant hospital-level risk-adjustment or stratification, with the exception of rural or critical access hospitals, which experienced differentially greater COVID-19 census burdens and may merit hospital-level risk-adjustment considerations.

Differential Privacy Protections in 2020 U.S. Decennial Census Data Do Not Impede Measurement of Racial and Ethnic Disparities.

Census data are vital to health care research but must also protect respondents' confidentiality. The 2020 decennial Census employs a new Differential Privacy framework; this study examines its effect on the accuracy of an important tool for measuring health disparities, the Bayesian Improved Surname and Geocoding (BISG) algorithm, which uses Census Block Group data to estimate race and ethnicity when self-reported data are unavailable. Using self-reported race and ethnicity data as our standard, we compared the accuracy of BISG estimates calculated using the original 2010 Census counts to the accuracy of estimates calculated using 2010 data but with 2020 Differential Privacy in place. The Differential Privacy methodology slightly decreases BISG accuracy for American Indian and Alaska Native people but has little effect for other groups, suggesting that the methodology will not impede health disparities research that employs BISG and similar methods.

Exposure of wetlands important for nonbreeding waterbirds to sea-level rise in the Mediterranean.

Sea-level rise (SLR) is expected to cause major changes to coastal wetlands, which are among the world's most vulnerable ecosystems and are critical for nonbreeding waterbirds. Because strategies for adaptation to SLR, such as nature-based solutions and designation of protected areas, can locally reduce the negative effects of coastal flooding under SLR on coastal wetlands, it is crucial to prioritize adaptation efforts, especially for wetlands of international importance for biodiversity. We assessed the exposure of coastal wetlands important for nonbreeding waterbirds to projected SLR along the Mediterranean coasts of 8 countries by modeling future coastal flooding under 7 scenarios of SLR by 2100 (from 44- to 161-cm rise) with a static inundation approach. Exposure to coastal flooding under future SLR was assessed for 938 Mediterranean coastal sites (≤30 km from the coastline) where 145 species of nonbreeding birds were monitored as part of the International Waterbird Census and for which the monitoring area was delineated by a polygon (64.3% of the coastal sites monitored in the Mediterranean region). Thirty-four percent of sites were threatened by future SLR, even under the most optimistic scenarios. Protected study sites and study sites of international importance for waterbirds were, respectively, 1.5 and 2 times more exposed to SLR than the other sites under the most optimistic scenario. Accordingly, we advocate for the development of a prioritization scheme to be applied to these wetlands for the implementation of strategies for adaptation to SLR to anticipate the effects of coastal flooding. Our study provides major guidance for conservation planning under global change in several countries of the Mediterranean region.

Exposición de los humedales de importancia para las aves acuáticas no reproductoras al incremento del nivel del mar en el Mediterráneo Resumen Se espera que el incremento en el nivel del mar (INM) cause cambios importantes en los humedales costeros, los cuales se encuentran entre los ecosistemas más vulnerables y son críticos para las aves acuáticas no reproductoras. Es crucial la priorización de los esfuerzos de adaptación, especialmente en los humedales con importancia internacional para la biodiversidad, ya que las estrategias de adaptación ante el INM, como las soluciones basadas en la naturaleza y la designación de áreas protegidas, pueden reducir localmente los efectos negativos de las inundaciones costeras por INM en los humedales costeros. Evaluamos la exposición de los humedales costeros con importancia para las aves acuáticas no reproductoras ante el INM proyectado en las costas del Mediterráneo en ocho países con un modelo de inundaciones costeras en el futuro bajo siete escenarios de INM para el año 2100 (de 44 a 161 cm) con un enfoque de inundación estática. Evaluamos la exposición a las inundaciones costeras bajo el INM futuro en 938 sitios costeros del Mediterráneo (≤ 30 km a partir de la costa), en donde monitoreamos a 145 especies de aves no reproductoras como parte del Censo Internacional de Aves Acuáticas y para los cuales el área de monitoreo estuvo delineada con un polígono (64.3% de los sitios costeros monitoreados en la región Mediterránea). El 34% de los sitios se vio amenazado por el INM en el futuro, incluso con los escenarios más optimistas. Los sitios de estudio protegidos y los sitios de estudio de importancia internacional para las aves acuáticas estuvieron expuestos 1.5 y 2 veces más al INM que otros sitios con el escenario más optimista. De acuerdo con esto, abogamos por el desarrollo de un esquema de priorización para aplicarse en estos humedales para la implementación de estrategias de adaptación al INM para anticipar los efectos de las inundaciones costeras. Nuestro estudio proporciona información importante para la planeación de la conservación bajo el cambio global en varios de los países del Mediterráneo.

Development and status quo of digestive endoscopy in China: An analysis based on the national census in 2013 and 2020.

Background and Objectives: Technique and practice of digestive endoscopy are undergoing speedy development all over the world. This study aimed to evaluate its status quo and development in China. Methods: All hospitals performing digestive endoscopy in mainland China participated in the national census in 2013 and 2020. Retrospective data of hospitals, endoscopists, volumes, and qualities were collected via an online structured questionnaire, and its accuracy and rationality were verified by logical tests and manual reviews. Data from other countries were used to compare with that of China. Results: From 2012 to 2019, the number of hospitals performing digestive endoscopy increased from 6,128 to 7,470 (1.22-fold), in which primary healthcare played a minor role. The median hospitals per 100,000 inhabitants per provincial region increased from 0.49 (IQR, 0.39-0.57) to 0.55 (IQR, 0.49-0.63). The endoscopists increased from 26,203 to 39,638 (1.51-fold), but their average workload even expanded. Overall volume increased from 28.8 million to 44.5 million (1.55-fold), and most types of endoscopic procedures recorded a high growth rate. Contrastingly, the specific utilization rates were low and paled in comparison with some developed countries. Nationwide, regional utilization rates showed a significant correlation with GDP per capita (P <0.001). Overall qualities of digestive endoscopy were excellent, but certain results of quality indicators posed a huge challenge, such as the detection rates of adenoma and early cancers. Conclusions: Impressive progress has been made in digestive endoscopy with rapidly expanding economy in China. However, primary healthcare, utilization rates, and income-related inequality of regional services were needed to be improved to promote public health better.

Utilizing social determinants of health to identify most vulnerable neighborhoods-Latent class analysis and GIS map.

OBJECTIVES: Public Health officials are often challenged to effectively allocate limited resources. Social determinants of health (SDOH) may cluster in areas to cause unique profiles related to various adverse life events. The authors use the framework of unintended teen pregnancies to illustrate how to identify the most vulnerable neighborhoods. METHODS: This study used data from the U.S. American Community Survey, Princeton Eviction Lab, and Connecticut Office of Vital Records. Census tracts are small statistical subdivisions of a county. Latent class analysis (LCA) was employed to separate the 832 Connecticut census tracts into four distinct latent classes based on SDOH, and GIS mapping was utilized to visualize the distribution of the most vulnerable neighborhoods. GEE Poisson regression model was used to assess whether latent classes were related to the outcome. Data were analyzed in May 2021. RESULTS: LCA's results showed that class 1 (non-minority non-disadvantaged tracts) had the least diversity and lowest poverty of the four classes. Compared to class 1, class 2 (minority non-disadvantaged tracts) had more households with no health insurance and with single parents; and class 3 (non-minority disadvantaged tracts) had more households with no vehicle available, that had moved from another place in the past year, were low income, and living in renter-occupied housing. Class 4 (minority disadvantaged tracts) had the lowest socioeconomic characteristics. CONCLUSIONS: LCA can identify unique profiles for neighborhoods vulnerable to adverse events, setting up the potential for differential intervention strategies for communities with varying risk profiles. Our approach may be generalizable to other areas or other programs. KEY MESSAGES: What is already known on this topic Public health practitioners struggle to develop interventions that are universally effective. The teen birth rates vary tremendously by race and ethnicity. Unplanned teen pregnancy rates are related to multiple social determinants and behaviors. Latent class analysis has been applied successfully to address public health problems. What this study adds While it is the pregnancy that is not planned rather than the birth, access to pregnancy intention data is not available resulting in a dependency on teen birth data for developing public health strategies. Using teen birth rates to identify at-risk neighborhoods will not directly represent the teens at risk for pregnancy but rather those who delivered a live birth. Since teen birth rates often fluctuate due to small numbers, especially for small neighborhoods, LCA may avoid some of the limitations associated with direct rate comparisons. The authors illustrate how practitioners can use publicly available SDOH from the Census Bureau to identify distinct SDOH profiles for teen births at the census tract level. How this study might affect research, practice or policy These profiles of classes that are at heightened risk potentially can be used to tailor intervention plans for reducing unintended teen pregnancy. The approach may be adapted to other programs and other states to prioritize the allocation of limited resources.

Unveiling value patterns via deep reinforcement learning in heterogeneous data analytics.

Artificial intelligence has substantially improved the efficiency of data utilization across various sectors. However, the insufficient filtering of low-quality data poses challenges to uncertainty management, threatening system stability. In this study, we introduce a data-valuation approach employing deep reinforcement learning to elucidate the value patterns in data-driven tasks. By strategically optimizing with iterative sampling and feedback, our method is effective in diverse scenarios and consistently outperforms the classic methods in both accuracy and efficiency. In China's wind-power prediction, excluding 25% of the overall dataset deemed low-value led to a 10.5% improvement in accuracy. Utilizing just 42.8% of the dataset, the model discerned 80% of linear patterns, showcasing the data's intrinsic and transferable value. A nationwide analysis identified a data-value-sensitive geographic belt across 10 provinces, leading to robust policy recommendations informed by variances in power outputs and data values, as well as geographic climate factors.

Golden lion tamarin metapopulation dynamics five years after heavy losses to yellow fever.

The golden lion tamarin (GLT) is an Endangered primate endemic to Brazil's lowland Atlantic Forest. After centuries of deforestation and capture for the pet trade, only a few hundred individuals survived, all in isolated forest fragments 85 km from Rio de Janeiro city. Intensive conservation actions, including reintroduction of zoo-born tamarins, increased numbers to about 3700 in 2014. The most severe yellow fever epidemic/epizootic in Brazil in 80 years reduced two of the largest GLT populations by over 90%. Herein we report the results of a 2023 survey of GLTs designed to examine the dynamics of population recovery following yellow fever. Results indicate that populations hard hit by yellow fever are recovering due in part to immigration from adjacent forest fragments. No local extirpations were observed. About 4800 GLTs live in the survey area. This represents a 31% increase since the baseline survey completed in 2014. Two factors explain most of the increase: four large areas that had no GLTs or very low-density populations in 2014 are now at moderate density (three areas) or low density (one area), explaining 71% of overall increase since 2014. Increase in forest area within our survey area may explain up to 16% of the increase in GLT numbers since 2014. Results of computer simulations suggest that strengthening forest connectivity will facilitate metapopulation resilience in the face of mortality factors such as yellow fever.

Environmental Justice Index and adverse pregnancy outcomes.

BACKGROUND: The Environmental Justice Index is a tool released by the Centers for Disease Control and Prevention that quantifies and ranks the environmental burden and social vulnerability of each census tract. Racial and ethnic disparities in adverse pregnancy outcomes are well established. The relative contributions of individual (person-level) and environmental (neighborhood-level) risk factors to disease prevalence remain poorly understood. OBJECTIVE: This study aimed to determine whether the Environmental Justice Index is associated with adverse pregnancy outcomes after adjustment for individual clinical and sociodemographic risk factors. STUDY DESIGN: This was a retrospective cross-sectional study of all patients who delivered a singleton newborn at ≥23 weeks of gestation between January 2019 and February 2022 at 7 hospitals within a large academic health system in New York. Patients were excluded if their home address was not available, if the address could not be geocoded to a census tract, or if the census tract did not have corresponding Environmental Justice Index data. Patients were also excluded if they had preexisting diabetes or hypertension. For patients who had multiple pregnancies during the study period, only the first pregnancy was included for analysis. Clinical and demographic data were obtained from the electronic medical record. Environmental Justice Index score, the primary independent variable, ranges from 0 to 1. Higher Environmental Justice Index scores indicate communities with increased cumulative environmental burden and increased social vulnerability. The primary outcome was adverse pregnancy outcome, defined as the presence of ≥1 of any of the following conditions: hypertensive disorders of pregnancy, gestational diabetes, preterm birth, fetal growth restriction, low birthweight, small for gestational age newborn, placental abruption, and stillbirth. Multivariable logistic regression was performed to investigate the relationship between Environmental Justice Index score and adverse pregnancy outcome, adjusting for potential confounding variables, including body mass index group, race and ethnicity group, advanced maternal age, nulliparity, public health insurance, and English as the preferred language. RESULTS: A total of 65,273 pregnancies were included for analysis. Overall, adverse pregnancy outcomes occurred in 37.6% of pregnancies (n=24,545); hypertensive disorders of pregnancy (13.4%) and gestational diabetes (12.2%) were the most common adverse pregnancy outcome conditions. On unadjusted analysis, the strongest associations between Environmental Justice Index score and individual adverse pregnancy outcome conditions were observed for stillbirth (odds ratio, 1.079; 95% confidence interval, 1.025-1.135) and hypertensive disorders of pregnancy (odds ratio, 1.052; 95% confidence interval, 1.042-1.061). On multivariable logistic regression, every 0.1 increase in Environmental Justice Index score was associated with 1.4% higher odds of adverse pregnancy outcome (adjusted odds ratio, 1.014; 95% confidence interval, 1.007-1.021). The strongest associations with adverse pregnancy outcomes were observed with well-established clinical and social risk factors, including class 3 obesity (adjusted odds ratio, 1.710; 95% confidence interval, 1.580-1.849; reference: body mass index <25 kg/m2) and certain race and ethnicity groups (reference: non-Hispanic White), particularly Asian and Pacific Islander (adjusted odds ratio, 1.817; 95% confidence interval, 1.729-1.910), and non-Hispanic Black (adjusted odds ratio, 1.668; 95% confidence interval, 1.581-1.760) people. CONCLUSION: Environmental Justice Index score is positively associated with adverse pregnancy outcomes, and most strongly associated with stillbirth and hypertensive disorders of pregnancy. Geospatial analysis with Environmental Justice Index may help to improve our understanding of health inequities by identifying neighborhood characteristics that increase the risk of pregnancy complications.

Disadvantaged groups have greater spatial access to pharmacies in New York state.

BACKGROUND: The accessibility of pharmacies has been associated with overall health and wellbeing. Past studies have suggested that low income and racial minority communities are underserved by pharmacies. However, the literature is inconsistent in finding links between area-level income or racial and ethnic composition and access to pharmacies. Here we aim to assess area-level spatial access to pharmacies across New York State (NYS), hypothesizing that Census Tracts with higher poverty rates and higher percentages of Black and Hispanic residents would have lower spatial access. METHODS: The population weighted mean shortest road network distance (PWMSD) to a pharmacy in 2018 was calculated for each Census Tract in NYS. This statistic was calculated from the shortest road network distance to a pharmacy from the centroid of each Census block within a tract, with the mean across census blocks weighted by the population of the census block. Cross-sectional analyses were conducted to assess links between Tract-level socio demographic characteristics and Tract-level PWMSD to a pharmacy. RESULTS: Overall the mean PWMSD to a pharmacy across Census tracts in NYS was 2.07 Km (SD = 3.35, median 0.85 Km). Shorter PWMSD to a pharmacy were associated with higher Tract-level % poverty, % Black/African American (AA) residents, and % Hispanic/Latino residents and with lower Tract-level % of residents with a college degree. Compared to tracts in the lowest quartile of % Black/AA residents, tracts in the highest quartile had a 70.7% (95% CI 68.3-72.9%) shorter PWMSD to a pharmacy. Similarly, tracts in the highest quartile of % poverty had a 61.3% (95% CI 58.0-64.4%) shorter PWMSD to a pharmacy than tracts in the lowest quartile. CONCLUSION: The analyses show that tracts in NYS with higher racial and ethnic minority populations and higher poverty rates have higher spatial access to pharmacies.

Intra- and post-pandemic impact of the COVID-19 outbreak on Stanford Health Care.

Stanford Health Care, which provides about 7% of overall healthcare to approximately 9 million people in the San Francisco Bay Area, has undergone significant changes due to the opening of a second hospital in late 2019 and, more importantly, the COVID-19 pandemic. We examine the impact of these events on anatomic pathology (AP) cases, aiming to enhance operational efficiency in response to evolving healthcare demands. We extracted historical census, admission, lab tests, operation, and AP data since 2015. An approximately 45% increase in the volume of laboratory tests (P < 0.0001) and a 17% increase in AP cases (P < 0.0001) occurred post-pandemic. These increases were associated with progressively increasing (P < 0.0001) hospital census. Census increase stemmed from higher admission through the emergency department (ED), and longer lengths of stay mostly for transfer patients, likely due to the greater capability of the new ED and changes in regional and local practice patterns post-pandemic. Higher census led to overcapacity, which has an inverted U relationship that peaked at 103% capacity for AP cases and 114% capacity for laboratory tests. Overcapacity led to a lower capability to perform clinical activities, particularly those related to surgical procedures. We conclude by suggesting parameters for optimal operations in the post-pandemic era.

Best Practices in Evolving Privacy Frameworks for Patient Age Data: Census Data Study.

BACKGROUND: Over the previous 4 decennial censuses, the population of the United States has grown older, with the proportion of individuals aged at least 90 years old in the 2010 census being more than 2 and a half times what it was in the 1980 census. This suggests that the threshold for constraining age introduced in the Safe Harbor method of the HIPAA (Health Insurance Portability and Accountability Act) in 1996 may be increased without exceeding the original levels of risk. This is desirable to maintain or even increase the utility of affected data sets without compromising privacy. OBJECTIVE: In light of the upcoming release of 2020 census data, this study presents a straightforward recipe for updating age-constrained thresholds in the context of new census data and derives recommendations for new thresholds from the 2010 census. METHODS: Using census data dating back to 1980, we used group size considerations to analyze the risk associated with various maximum age thresholds over time. We inferred the level of risk of the age cutoff of 90 years at the time of HIPAA's inception in 1996 and used this as a baseline from which to recommend updated cutoffs. RESULTS: The maximum age threshold may be increased by at least 2 years without exceeding the levels of risk conferred in HIPAA's original recommendations. Moreover, in the presence of additional information that restricts the population in question to a known subgroup with increased longevity (for example, restricting to female patients), the threshold may be increased further. CONCLUSIONS: Increasing the maximum age threshold would enable the data user to gain more utility from the data without introducing risk beyond what was originally envisioned with the enactment of HIPAA. Going forward, a recurring update of such thresholds is advised, in line with the considerations detailed in the paper.

Survival analysis under imperfect record linkage using historic census data.

BACKGROUND: Advancements in linking publicly available census records with vital and administrative records have enabled novel investigations in epidemiology and social history. However, in the absence of unique identifiers, the linkage of the records may be uncertain or only be successful for a subset of the census cohort, resulting in missing data. For survival analysis, differential ascertainment of event times can impact inference on risk associations and median survival. METHODS: We modify some existing approaches that are commonly used to handle missing survival times to accommodate this imperfect linkage situation including complete case analysis, censoring, weighting, and several multiple imputation methods. We then conduct simulation studies to compare the performance of the proposed approaches in estimating the associations of a risk factor or exposure in terms of hazard ratio (HR) and median survival times in the presence of missing survival times. The effects of different missing data mechanisms and exposure-survival associations on their performance are also explored. The approaches are applied to a historic cohort of residents in Ambler, PA, established using the 1930 US census, from which only 2,440 out of 4,514 individuals (54%) had death records retrievable from publicly available data sources and death certificates. Using this cohort, we examine the effects of occupational and paraoccupational asbestos exposure on survival and disparities in mortality by race and gender. RESULTS: We show that imputation based on conditional survival results in less bias and greater efficiency relative to a complete case analysis when estimating log-hazard ratios and median survival times. When the approaches are applied to the Ambler cohort, we find a significant association between occupational exposure and mortality, particularly among black individuals and males, but not between paraoccupational exposure and mortality. DISCUSSION: This investigation illustrates the strengths and weaknesses of different imputation methods for missing survival times due to imperfect linkage of the administrative or registry data. The performance of the methods may depend on the missingness process as well as the parameter being estimated and models of interest, and such factors should be considered when choosing the methods to address the missing event times.

Development of a community severance index for urban areas in the United States: A case study in New York City.

BACKGROUND AND AIMS: Traffic-related exposures, such as air pollution and noise, have a detrimental impact on human health, especially in urban areas. However, there remains a critical research and knowledge gap in understanding the impact of community severance, a measure of the physical separation imposed by road infrastructure and motorized road traffic, limiting access to goods, services, or social connections, breaking down the social fabric and potentially also adversely impacting health. We aimed to robustly quantify a community severance metric in urban settings exemplified by its characterization in New York City (NYC). METHODS: We used geospatial location data and dimensionality reduction techniques to capture NYC community severance variation. We employed principal component pursuit, a pattern recognition algorithm, combined with factor analysis as a novel method to estimate the Community Severance Index. We used public data for the year 2019 at census block group (CBG) level on road infrastructure, road traffic activity, and pedestrian infrastructure. As a demonstrative application of the Community Severance Index, we investigated the association between community severance and traffic collisions, as a proxy for road safety, in 2019 in NYC at CBG level. RESULTS: Our data revealed one multidimensional factor related to community severance explaining 74% of the data variation. In adjusted analyses, traffic collisions in general, and specifically those involving pedestrians or cyclists, were nonlinearly associated with an increasing level of Community Severance Index in NYC. CONCLUSION: We developed a high spatial-resolution Community Severance Index for NYC using data available nationwide, making it feasible for replication in other cities across the United States. Our findings suggest that increases in the Community Severance Index across CBG may be linked to increases in traffic collisions in NYC. The Community Severance Index, which provides a novel traffic-related exposure, may be used to inform equitable urban policies that mitigate health risks and enhance well-being.

A tale of many neighborhoods: Latent profile analysis to derive a national neighborhood typology for the US.

INTRODUCTION: Neighborhoods are complex and multi-faceted. Analytic strategies used to model neighborhoods should reflect this complexity, with the potential to better understand how neighborhood characteristics together impact health. We used latent profile analysis (LPA) to derive a residential neighborhood typology applicable for census tracts across the US. METHODS: From tract-level 2015-2019 American Community Survey (ACS) five-year estimates, we selected five indicators that represent four neighborhood domains: demographic composition, commuting, socioeconomic composition, and built environment. We compared model fit statistics for up to eight profiles to identify the optimal number of latent profiles of the selected neighborhood indicators for the entire US. We then examined differences in national tract-level 2019 prevalence estimates of physical and mental health derived from CDC's PLACES dataset between derived profiles using one-way analysis of variance (ANOVA). RESULTS: The 6-profile LPA model was the optimal categorization of neighborhood profiles based on model fit statistics and interpretability. Neighborhood types were distinguished most by demographic composition, followed by commuting and built environment domains. Neighborhood profiles were associated with meaningful differences in the prevalence of health outcomes. Specifically, tracts characterized as "Less educated non-immigrant racial and ethnic minority active transiters" (n = 3,132, 4%) had the highest poor health prevalence (Mean poor physical health: 18.6 %, SD: 4.30; Mean poor mental health: 19.6 %, SD: 3.85), whereas tracts characterized as "More educated metro/micropolitans" (n = 15, 250, 21%) had the lowest prevalence of poor mental and physical health (Mean poor physical health: 10.6 %, SD: 2.41; Mean poor mental health: 12.4 %, SD: 2.67; p < 0.001). CONCLUSION: LPA can be used to derive meaningful and standardized profiles of tracts sensitive to the spatial patterning of social and built conditions, with observed differences in mental and physical health by neighborhood type in the US.

Reevaluating the Spatial Scale of Residential Segregation: Racial Change Within and Between Neighborhoods.

This study evaluates the extent to which metropolitan racial segregation occurs between neighborhoods-from tract to tract-and within neighborhoods-from block to block-and is framed theoretically by Putnam's (2007) "hunkering down" hypothesis. Analyses are based on complete-count block, tract, and metropolitan data from the last four U.S. decennial censuses. We document recent patterns of block-to-block segregation between Whites and racial and ethnic minorities (Blacks, Asians, and Hispanics) and between different minority pairs. For example, roughly 40% of all metro Black-White segregation is due to segregation from block to block within neighborhoods. Among Asians, the between-neighborhood component of metropolitan segregation has increased over time but was largely compensated by declines in the within-neighborhood (or block) component. Metropolitan fixed-effects models show that trends and racial and ethnic differences in segregation-overall and within and between neighborhoods-are broadly observed across metro areas but are most evident in the largest, oldest, and most highly segregated metro areas. The results are robust to alternative estimates that adjust for differential privacy, metropolitan reclassification, and neighborhood boundary changes. Analyses of neighborhood change in Atlanta, Georgia, further reinforce the generality of our multiscale approach.

Testing methods to estimate population size for wastewater treatment plants using census data: Implications for wastewater-based epidemiology.

In wastewater-based epidemiology (WBE), wastewater loads are commonly reported as a per capita value. Census population counts are often used to obtain a population size to normalise wastewater loads. However, the methods used to calculate the population size of wastewater treatment plants (WWTPs) from census data are rarely reported in the WBE literature. This is problematic because the geographical extents of wastewater catchments and census area units rarely align perfectly with each other and exist at different spatial scales. This complicates efforts to estimate the number of people serviced by WWTPs in these census area units. This study compared four geospatial methods to combine wastewater catchment areas and census area units to calculate the census population size of wastewater treatment plants. These methods were applied nationally to WWTPs across New Zealand. Population estimates varied by up to 73 % between the methods, which could skew comparisons of per capita wastewater loads between sites. Variability in population estimates (relative standard deviation, RSD) was significantly higher in smaller catchments (rs = -0.727, P < .001), highlighting the importance of method selection in smaller sites. Census population estimates were broadly similar to those provided by wastewater operators, but significant variation was observed for some sites (ranging from 42 % lower to 78 % higher, RSD = 262 %). We present a widely applicable method to calculate population size from census, which involves disaggregating census area units by individual properties. The results reinforce the need for transparent reporting to maintain confidence in the comparison of WBE across sites and studies.

Descriptive summary of fatal work-related injuries, Western States, 2011-2017.

Work-related deaths are a persistent occupational health issue that can be prevented. However, prevention opportunities can be hampered by a lack of adequate public health resources. The Western States Occupational Network (WestON) is a network of federal, state, and local occupational health professionals that includes a 19-state region of the United States. To encourage public health collaboration, WestON partners examined work-related fatalities within the region. Fatality counts (numerators) were obtained from the U.S. Bureau of Labor Statistics (BLS) Census of Fatal Occupational Injuries restricted-access research files for all workers ages ≥15 years and fatally injured in WestON states from 2011 through 2017. Estimates of full-time equivalent hours worked (FTE) (denominators) were retrieved from the BLS Current Population Survey. Annual average fatality rates were calculated as number of fatalities per 100,000 FTE over the study period. Rates were stratified by state, select demographics, industry sector, and event/exposure types. Pearson chi-squared tests and rate ratios with 95% confidence probability limits were used to assess rate differences. All analyses were conducted using SAS v.9.4. From 2011 through 2017, the annual average overall occupational fatality rate for the WestON region was 3.5 fatalities per 100,000 FTE, comparable to the overall U.S. fatality rate. Male workers had a fatality rate almost 10 times higher than female workers in the region. Fatality rates increased with successive age groups. Alaska and New Mexico had significantly higher fatality rates for all racial/ethnic groups compared to respective regional rates. Wyoming, North Dakota, and Montana had the three highest occupational fatality rates among foreign-born workers. Agriculture/forestry/fishing, mining/oil/gas extraction, and transportation/warehousing/utilities were industry sector groups with the three highest fatality rates regionally. Transportation-related incidents were the most frequent event type associated with occupational fatalities for all 19 states. Work-related fatalities are a crosscutting occupational public health priority. This analysis can be an impetus for collaborative multistate initiatives among a dynamic and varied occupational public health network to better meet the needs of a rapidly changing workforce.

Prevalence and correlates of disability in older adults, Ghana: evidence from the Ghana 2021 Population and Housing Census.

BACKGROUND: Although there are studies on disabilities in older persons, most of these studies have been carried out in developed countries. Hence, there are limited studies on disability in older adults in sub-Saharan Africa, including Ghana. The few studies that have examined the prevalence and correlates of disability in older adults used survey data for their analyses. To contribute to addressing this knowledge gap that has arisen, this study used a national census, the 2021 Ghana Population and Housing Census, to examine the prevalence and correlates of disability in older adults in Ghana. METHODS: The 2021 Ghana Population and Housing Census data was used for this study. A sample size of 197,057 Ghanaians aged 60 years and above was used for this study. The Washington Group questions on disability were used to measure disability by asking older adults about their difficulties in performing the six domains of disability (physical, sight, intellectual, hearing, self-care, and speech). A multinomial logistic regression housed in STATA was used to analyse the correlates of disability in older adults in Ghana. A p-value less than 0.05 was used for statistical significance. RESULTS: The results show that slightly more than one-third (38.4%) of the older adults were disabled. In terms of the number of disabilities in older adults, 16.9% had one disability condition, while 2.4% had six disability conditions. Also, 9.4% had two disability conditions. Older adults who were females, aged 70-79 years and 80 years and above, resided in rural areas, with primary, JHS/Middle, SHS, unaffiliated with religion, ever married and never married, unemployed, and belonged to the middle and rich households were more likely to have a disability condition. Also, older adults residing in the Middle and Northern zones, having no health insurance, and using clean cooking fuel were less likely to have a disability condition. CONCLUSIONS: The results show that socio-demographic and household factors were associated with disability in older adults in Ghana. Hence, policymakers and researchers should target these factors when designing appropriate policies, programmes, and interventions to improve the wellbeing of older adults.

Population status of proboscis monkeys in Balikpapan Bay and their potential survival challenges in Nusantara, the proposed new capital city of Indonesia.

Populations of rare and endangered species are nowadays in peril due to large-scale habitat conversion, and even sizeable and stable populations are confronted with unexpected challenges. We conducted a full census of a proboscis monkey (Nasalis larvatus) population in Balikpapan Bay and located 292 one-male-multifemale units and 67 all-male units in 2022. Using data on average group size, subsampled from Balikpapan Bay, we estimated a total population size of 3907 individuals. The rate of proboscis monkey habitat loss in Balikpapan Bay has been slowing down to the current 0.69% per year. It is predicted that habitat recovery may exceed habitat loss after 13 years. The Indonesian capital city relocation was announced in 2019 with spatial plans designed to cover a total land area of 2,560 km2 across various habitats until 2045. A total number of 1449 individuals (37.08% of the population) were found on 80.55 km2 (41.29%) of habitat that overlapped with current spatial plans of Nusantara Capital city. The construction work just started; before that, the government had already claimed it would be a "smart, green, beautiful, and sustainable city". We, therefore, include our recommendations to mitigate the impact of the construction and to pursue the goal to construct the most sustainable capital city, concerning local biodiversity and thus become a pioneer in a new direction of proboscis monkey conservation.