Journal of urban health : bulletin of the New York Academy of Medicine
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The expansion in the scope, scale, and sources of data on the wider social determinants of health (SDH) in the last decades could bridge gaps in information available for decision-making. However, challenges remain in making data widely available, accessible, and useful towards improving population health. While traditional, government-supported data sources and comparable data are most often used to characterize social determinants, there are still capacity and management constraints on data availability and use. ⋯ The Philippines has a more consistent distribution of the use of new data sources across the HEALTHY determinants than Kenya, where there is greater variation of the number of publications across determinants. The results suggest that both countries use limited SDH data from new data sources. This limited use could be due to a number of factors including the absence of standardized indicators of SDH, inadequate trust and acceptability of data collection methods, and limited infrastructure to pool, analyze, and translate data.
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The Sexual and Reproductive Health Burden Index (SRHBI) was developed to provide a composite spatial measure of sexual and reproductive health (SRH) indicators that can be widely adopted by urban public health departments for the planning of SRH services. The index was constructed using eight indicators: teen births, low birthweight, infant mortality, new HIV diagnoses, people living with HIV, and incidences of gonorrhea, chlamydia, and syphilis. Chicago Department of Public Health data (2014-2017) were used to calculate index scores for Chicago community areas; scores were mapped to provide geovisualization and global Moran's I was calculated to assess spatial autocorrelation. ⋯ Linear regression revealed that the percent of Black residents, percent of household couples that are same-sex, community violence, economic hardship, and population density were significant predictors of the SRHBI. The SRHBI provides a valid, useful, and replicable measure to assess and communicate community-level SRH burden in urban environments. The SRHBI may be scaled through a multi-city public data dashboard and utilized by urban public health departments to optimally target and tailor SRH interventions to communities.
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Access to energy is an important social determinant of health, and expanding the availability of affordable, clean energy is one of the Sustainable Development Goals. It has been argued that climate mitigation policies can, if well-designed in response to contextual factors, also achieve environmental, economic, and social progress, but otherwise pose risks to economic inequity generally and health inequity specifically. Decisions around such policies are hampered by data gaps, particularly in low- and middle-income countries (LMICs) and among vulnerable populations in high-income countries (HICs). ⋯ Understanding how to maximize gains in energy efficiency and uptake of new technologies requires a deeper understanding of how work and life is shaped by socioeconomic inequalities between and within countries. This is particularly the case for LMICs and in local contexts where few data are currently available, and for whom existing evidence may not be directly applicable. Big data approaches may offer some value in tracking the uptake of new approaches, provide greater data granularity, and help compensate for evidence gaps in low resource settings.
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More than a decade after the World Health Organization Commission on the Social Determinants of Health (SDoH), it is becoming widely accepted that social and economic factors, including but not limited to education, energy, income, race, ethnicity, and housing, are important drivers of health in populations. Despite this understanding, in most contexts, social determinants are not central to local, national, or global decision-making. Greater clarity in conceptualizing social determinants, and more specificity in measuring them, can move us forward towards better incorporating social determinants in decision-making for health. ⋯ Third, we problematize the gap in data across contexts on different dimensions of social determinants and describe data that could be curated to better understand the influence of social determinants at the local and national levels. Fourth, we describe the necessity of using data to understand social determinants and inform decision-making to improve health. Our overall goal is to provide a path for our collective understanding of the foundational causes of health, facilitated by advances in data access and quality, and realized through improved decision-making.
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Collective sex venues (places where people have sex in groups or in the presence of others, such as bathhouses or sex clubs) are locations where SARS-CoV-2 transmission is likely to occur. We conducted an online survey to examine the impact of the COVID-19 pandemic among 342 sexual and gender minority (SGM) individuals who had attended collective sex venues (CSV) in New York City (NYC) in the prior year. Almost 1 in 10 (9.9%) participants reported having received a positive test for SARS-CoV-2 infection or antibodies. ⋯ In open survey answers, participants described reasons for or against attending CSV during the pandemic, as well as risk reduction strategies that would make them more comfortable attending (e.g., screening for test results, doing temperature checks, holding outdoor events, or restricting events to lower risk sexual practices). SGM individuals who attend CSV might be at increased risk for COVID-19. Public health officials should provide CSV organizers and attendees with guidelines on how to prevent or minimize transmission risk in the context of pandemics such as COVID-19.