Journal of urban health : bulletin of the New York Academy of Medicine
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To provide data that can guide community-targeted practices, policies, and interventions in urban metropolitan areas, we used geospatial analysis to examine the community-level opioid overdose death determinants and their spatial variation across a study area. We obtained spatial datasets containing multiple, high-quality measures of socioeconomic conditions, public health status, and demographics for analysis and visualization in geographic information systems. We employed a multiscale modeling approach (multiscale geographically weighted regression; MGWR) to provide a comprehensive and robust analysis of opioid overdose death determinants, explain how geospatial patterns vary across scales across Milwaukee County in 2019, and examine the differential influence of factors locally, regionally, and globally. ⋯ The observed geographic variation in relationships included the impact of naloxone availability and incarceration rates on overdose deaths with pronounced differences between White communities and communities of color. Understanding, community-level factors that contribute to overdose risk should guide targeted community-level solutions. Overall, our findings demonstrate the value of precision epidemiology using MGWR analysis for defining and guiding responses to public health challenges.
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Noncommunicable diseases (NCDs) represent a significant global public health burden. As more countries experience both epidemiologic transition and increasing urbanization, it is clear that we need approaches to mitigate the growing burden of NCDs. Large and growing urban environments play an important role in shaping risk factors that influence NCDs, pointing to the ineluctable need to engage sectors beyond the health sector in these settings if we are to improve health. ⋯ BRT system policies have the opportunity to improve lifestyle choices for NCDs through a focus on safe, affordable, and effective forms of transportation. There are opportunities to improve decision-making for health by involving more available data for health, building on existing infrastructures, building stronger political leadership and commitments, and establishing formal frameworks to improve multisectoral collaborations within megacities. Future research will benefit from addressing the political and bureaucratic processes of using health data when designing public transportation services, the political and social obstacles involved, and the cross-national lessons that can be learned from other megacities.
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Housing is a paradigmatic example of a social determinant of health, as it influences and is influenced by structural determinants, such as social, macroeconomic, and public policies, politics, education, income, and ethnicity/race, all intersecting to shaping the health and well-being of populations. It can therefore be argued that housing policy is critically linked to health policy. However, the extent to which this linkage is understood and addressed in public policies is limited and highly diverse across and within countries. ⋯ This analysis demonstrates the value of viewing housing policies as public health policies that could significantly impact the health and well-being of populations, especially vulnerable groups. Moreover, the findings highlight the importance of the Health in All Policies approach to facilitate integrated policy responses to address social determinants of health such as housing. This is more critical than ever, given the context of the global pandemic that has led to worsening overall health and well-being.
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Depression accounts for a large share of the global disease burden, with an estimated 264 million people globally suffering from depression. Despite being one of the most common kinds of mental health (MH) disorders, much about depression remains unknown. There are limited data about depression, in terms of its occurrence, distribution, and wider social determinants. ⋯ There is a continuing gap in the collection and analysis of data on depression, possibly reflecting the limited priority accorded to mental health as a whole. The relatively limited use of data to inform our understanding of the HEALTHY determinants of depression suggests a substantial need for support of independent research using new data sources. Finally, there is a need to revisit the universal health coverage (UHC) frameworks, as these frameworks currently do not include depression and other mental health-related indicators so as to enable tracking of progress (or lack thereof) on such indicators.
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The inclusion of social determinants of health offers a more comprehensive lens to fully appreciate and effectively address health. However, decision-makers across sectors still struggle to appropriately recognise and act upon these determinants, as illustrated by the ongoing COVID-19 pandemic. Consequently, improving the health of populations remains challenging. ⋯ We suggest two main avenues to make the link more explicit: the use of data in giving health problems the appropriate visibility and credibility they require and the use of social determinants of health as a broader framing to more effectively attract the attention of a diverse group of decision-makers with the power to allocate resources. Social determinants of health present opportunities for decision-making, which can target modifiable factors influencing health-i.e. interventions to improve or reduce risks to population health. Future work is needed to build on this review and propose an improved, people-centred and evidence-informed decision-making tool that strongly and explicitly integrates data on social determinants of health.