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1.
Lancet Reg Health Am ; : 100091, 2021 Oct 04.
Artigo em Inglês | MEDLINE | ID: mdl-34635882

RESUMO

Background: The COVID-19 pandemic and its consequences have been associated with an increase in poor population mental health. We assessed how depressive symptoms changed among U.S. adults over the course of the COVID-19 pandemic and identified the key risk factors for these symptoms. Methods: Longitudinal panel study of a nationally representative group of U.S. adults ages 18 years and older surveyed in March-April 2020 (Time 1; N=1441) and March-April 2021 (Time 2; N=1161) in the COVID-19 and Life Stressors Impact on Mental Health and Well-being study (CLIMB). The Patient Health Questionnaire-9 (PHQ-9) was used to define elevated depressive symptoms (cut-off ≥10) and depressive symptoms score (0-27). Findings: The prevalence of elevated depressive symptoms persisted from 27.8% in 2020 (95% CI: 24.9, 30.9) to 32.8% in 2021 (95% CI: 29.1, 36.8). Over time, the central drivers of depressive symptoms were low household income, not being married, and experiencing multiple stressors during the COVID-19 pandemic. The odds ratio of elevated depressive symptoms for low income relative to high income persons increased from 2.3 (95% CI: 1.2, 4.2) in 2020 to 7.0 (95% CI: 3.7, 13.3) in 2021. Fewer people reported experiencing 4 or more COVID-19 stressors in 2021 than in 2020 (47.5% in 2020 vs 37.1% in 2021), but the odds ratio of elevated depressive symptoms associated with 4 or more stressors relative to 1 stressor or less increased from 1.9 (95% CI: 1.2, 3.1) in 2020 to 5.4 (95% CI: 3.2, 9.2) in 2021. Interpretation: The burden of depressive symptoms in the U.S. adult population increased over the course of the COVID-19 pandemic. Mental health gaps grew between populations with different assets and stressor experiences during the COVID-19 pandemic. Funding: CLIMB Time 1 was sponsored by the Rockefeller Foundation-Boston University 3-D Commission. CLIMB Time 2 was sponsored by the de Beaumont Foundation.

2.
Soc Psychiatry Psychiatr Epidemiol ; 56(11): 2107-2116, 2021 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-34480595

RESUMO

PURPOSE: Rates of mental disorders in the United States military have increased in recent years. National Guard members may be particularly at risk for mental disorders, given their dual role as citizen-soldiers and their increased involvement in combat deployments during recent conflicts. The Ohio Army National Guard Mental Health Initiative (OHARNG-MHI) was launched to assess the prevalence, incidence, and potential causes and consequences of mental disorders in this unique population. METHODS: OHARNG-MHI is a decade-long dynamic cohort study that followed over 3,000 National Guard members yearly through structured telephone interviews. RESULTS: Findings thus far have applied a pre-, peri-, post-deployment framework, identifying factors throughout the life course associated with mental disorders, including childhood events and more recent events, both during and outside of deployment. An estimated 61% of participants had at least one mental disorder in their lifetime, the majority of which initiated prior to military service. Psychiatric comorbidity was common, as were alcohol use and stressful events. Latent class growth analyses revealed four distinct trajectory paths of both posttraumatic stress and depression symptoms across four years. Only 37% of soldiers with probable past-year mental disorders accessed mental health services in the subsequent year, with substance use disorders least likely to be treated. CONCLUSION: Strengths of this study include a large number of follow-up interviews, detailed data on both military and non-military experiences, and a clinical assessment subsample that assessed the validity of the telephone screening instruments. Findings, methods, and procedures of the study are discussed, and collaborations are welcome.

3.
J Urban Health ; 98(Suppl 1): 15-30, 2021 08.
Artigo em Inglês | MEDLINE | ID: mdl-34480327

RESUMO

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 seeks to describe the linkages between housing policies and health and well-being using examples from three countries at different levels of the wealth spectrum: Singapore, the UK, and Kenya.We conducted a comparative policy analysis across three country contexts (Singapore, the UK, and Kenya) to document the extent to which housing policies address health and well-being, highlighting commonalities and differences among them. To guide our analysis, we used the United Nations (UN) definition of adequate housing as it offers a broad framework to analyze the impact of housing on health and well-being.The anatomy of housing policies has a strong correlation to the provision of adequate housing across Singapore, the UK, and Kenya, especially for vulnerable groups. The paper demonstrates that contextual factors including population composition (i.e., aging versus youthful), political ideologies, legal frameworks (i.e., welfare versus market-based provision of housing), and presence (or absence) of adequate, quality, timely, reliable, robust data systems for decision-making, which are taken up by stakeholders/state, have strong implications of the type of housing policies developed and implemented, in turn directly and indirectly impacting the overall health and well-being of populations.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.


Assuntos
Habitação , Determinantes Sociais da Saúde , Humanos , Quênia , Política Pública , Singapura , Reino Unido
4.
J Urban Health ; 98(Suppl 1): 51-59, 2021 08.
Artigo em Inglês | MEDLINE | ID: mdl-34480328

RESUMO

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. This paper seeks to draw insights from the literature to better understand decision-making processes affecting health and the potential to integrate data on social determinants. We summarised commonly cited conceptual approaches across all stages of the policy process, from agenda-setting to evaluation. Nine conceptual approaches were identified, including two frameworks, two models and five theories. From across the selected literature, it became clear that the context, the actors and the type of the health issue are critical variables in decision-making for health, a process that by nature is a dynamic and adaptable one. The majority of these conceptual approaches implicitly suggest a possible role for data on social determinants of health in decision-making. 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.


Assuntos
COVID-19 , Determinantes Sociais da Saúde , Política de Saúde , Humanos , Pandemias , SARS-CoV-2
5.
Am J Public Health ; 111(10): 1733-1735, 2021 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-34554818
6.
J Urban Health ; 98(Suppl 1): 31-40, 2021 08.
Artigo em Inglês | MEDLINE | ID: mdl-34472014

RESUMO

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. Conversely, privately held data may not be shared. This study reviews and discusses the nature, sources, and uses of data on SDH, with illustrations from two middle-income countries: Kenya and the Philippines. The review highlights opportunities presented by new data sources, including the use of big data technologies, to capture data on social determinants that can be useful to inform population health. We conducted a search between October 2010 and September 2020 for grey and scientific publications on social determinants using a search strategy in PubMed and a manual snowball search. We assessed data sources and the data environment in both Kenya and the Philippines. We found limited evidence of the use of new sources of data to study the wider SDH, as most of the studies available used traditional sources. There was also no evidence of qualitative big data being used. Kenya has more publications using new data sources, except on the labor determinant, than the Philippines. 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.


Assuntos
Países em Desenvolvimento , Determinantes Sociais da Saúde , Humanos , Renda , Armazenamento e Recuperação da Informação , Quênia
7.
J Urban Health ; 98(Suppl 1): 41-50, 2021 08.
Artigo em Inglês | MEDLINE | ID: mdl-34409557

RESUMO

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. This work examined the use of novel data sources for assessing the scope and social determinants of depression, with a view to informing the reduction of the global burden of depression.This study focused on new and traditional sources of data on depression and its social determinants in two middle-income countries (LMICs), namely, Brazil and India. We identified data sources using a combination of a targeted PubMed search, Google search, expert consultations, and snowball sampling of the relevant literature published between October 2010 and September 2020. Our search focused on data sources on the following HEALTHY subset of determinants: healthcare (H), education (E), access to healthy choices (A), labor/employment (L), transportation (T), housing (H), and income (Y).Despite the emergence of a variety of data sources, their use in the study of depression and its HEALTHY determinants in India and Brazil are still limited. Survey-based data are still the most widely used source. In instances where new data sources are used, the most commonly used data sources include social media (twitter data in particular), geographic information systems/global positioning systems (GIS/GPS), mobile phone, and satellite imagery. Often, the new data sources are used in conjunction with traditional sources of data. In Brazil, the limited use of new data sources to study depression and its HEALTHY determinants may be linked to (a) the government's outsized role in coordinating healthcare delivery and controlling the data system, thus limiting innovation that may be expected from the private sector; (b) the government routinely collecting data on depression and other MH disorders (and therefore, does not see the need for other data sources); and (c) insufficient prioritization of MH as a whole. In India, the limited use of new data sources to study depression and its HEALTHY determinants could be a function of (a) the lack of appropriate regulation and incentives to encourage data sharing by and within the private sector, (b) absence of purposeful data collection at subnational levels, and (c) inadequate prioritization of MH. 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.


Assuntos
Países em Desenvolvimento , Determinantes Sociais da Saúde , Depressão/epidemiologia , Humanos , Renda , Cobertura Universal do Seguro de Saúde
8.
J Urban Health ; 98(Suppl 1): 4-14, 2021 08.
Artigo em Inglês | MEDLINE | ID: mdl-34414512

RESUMO

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. In this paper, first, we summarize the evolution of the social framing of health. Second, we describe how the social determinants are conceptualized and contextualized differently at the global, national, and local levels. With this, we seek to demonstrate the importance of analyzing and understanding SDoH relative to the contexts in which they are experienced. 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.


Assuntos
Renda , Determinantes Sociais da Saúde , Escolaridade , Grupos Étnicos , Habitação , Humanos
9.
Health Serv Res ; 56(5): 747-750, 2021 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-34382231
10.
BMJ Open ; 11(8): e044125, 2021 08 09.
Artigo em Inglês | MEDLINE | ID: mdl-34373289

RESUMO

OBJECTIVE: To document the prevalence of anxiety disorders in the USA during the COVID-19 pandemic. DESIGN: A cross-sectional analysis. SETTING: A nationally representative sample in the USA between 31 March and 13 April 2020. PARTICIPANTS: 1450 English-speaking adult participants in the AmeriSpeak Panel. AmeriSpeak is a probability-based panel designed to be representative of households in the USA. MAIN OUTCOME MEASURES: Prevalence of probable generalised anxiety disorder (GAD) using the GAD-7 and post-traumatic stress symptoms (PTSS) using the four-item PTSD (post-traumatic stress disorder) checklist. Both outcomes were stratified by demographics and COVID-19-related stressors. RESULTS: The majority of participants were female (51.8%), non-Hispanic white (62.9%) and reported a household saving of $5000 or more. Those between 18 and 29 years old were the largest age group (38.1%) compared with 40-59 years (32.0%) and 60 years or more (29.9%). The prevalence of probable GAD was 10.9% (95% CI 9.1% to 13.2%) and the prevalence of PTSS was 21.7% (95% CI 19.1% to 24.6%). Among participants reporting five or more COVID-19-related stressors, the prevalence of probable GAD was 20.5% (95% CI 16.1% to 25.8%) and the prevalence of PTSS was 35.7% (95% CI 30.2% to 41.6%). Experiencing five or more COVID-19-related stressors was a predictor of both probable GAD (OR=4.5, 95% CI 2.3 to 8.8) and PTSS (OR=3.3, 95% CI 2.1 to 5.1). CONCLUSIONS: The prevalence of probable anxiety disorders in the USA, as the COVID-19 pandemic and policies implemented to tackle it unfolded, is higher than estimates reported prior to the pandemic and estimates reported following other mass traumatic events. Exposure to COVID-19-related stressors is associated with higher prevalence of both probable GAD and PTSS, highlighting the role these stressors play in increasing the risk of developing anxiety disorders in the USA. Mitigation and recovery policies should take into account the mental health toll the pandemic had on the USA population.


Assuntos
COVID-19 , Pandemias , Adolescente , Adulto , Ansiedade , Transtornos de Ansiedade/epidemiologia , Estudos Transversais , Depressão , Feminino , Humanos , Masculino , Saúde Mental , Pessoa de Meia-Idade , SARS-CoV-2 , Estados Unidos/epidemiologia , Adulto Jovem
11.
Prev Med ; 153: 106751, 2021 Jul 31.
Artigo em Inglês | MEDLINE | ID: mdl-34343593

RESUMO

Healthcare stakeholders are increasingly investing to address social determinants of health (SDOH) as they seek to improve health outcomes and reduce total healthcare costs in their communities. Policy heavily shapes SDOH, and healthcare lobbying on SDOH issues may offer large impacts through positive policy change. Federal lobbying disclosures from the ten highest spending health insurance and healthcare provider organizations and related associations between 2015 and 2019 were reviewed to identify lobbying reported on the salient SDOH issues, defined based on the Accountable Health Communities Model health-related social needs screening tool. Five of the organizations reported lobbying on some SDOH issues, including financial strain, employment, food insecurity, and interpersonal safety, but none reported lobbying on other issues, such as non-healthcare-related employment, housing instability, transportation, or education. Lobbying has been a missed opportunity for addressing SDOH. Healthcare organizations have the opportunity to expand their lobbying on upstream SDOH policy issues to increase the impact of their SDOH strategy and further improve population health.

12.
J Psychiatr Res ; 142: 275-282, 2021 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-34403969

RESUMO

BACKGROUND: Accurate identification of persons at risk of suicide is challenging because suicide is a rare outcome with a multifactorial origin. The purpose of this study was to predict suicide among persons with depression using machine learning methods. METHODS: A case-cohort study was conducted in Denmark between January 1, 1995 and December 31, 2015. Cases were all persons who died by suicide and had an incident depression diagnosis in Denmark (n = 2,774). The comparison subcohort was a 5% random sample of all individuals in Denmark at baseline, restricted to persons with an incident depression diagnosis during the study period (n = 11,963). Classification trees and random forests were used to predict suicide. RESULTS: In men with depression, there was a high risk of suicide among those who were prescribed other analgesics and antipyretics (i.e., non-opioid analgesics such as acetaminophen), prescribed hypnotics and sedatives, and diagnosed with a poisoning (n = 96; risk = 81%). In women with depression, there was an elevated risk of suicide among those who were prescribed other analgesics and antipyretics, anxiolytics, and hypnotics and sedatives, but were not diagnosed with poisoning nor cerebrovascular diseases (n = 338; risk = 58%). DISCUSSION: Psychiatric disorders and their associated medications were strongly indicative of suicide risk. Notably, anti-inflammatory medications (e.g., acetaminophen) prescriptions, which are used to treat chronic pain and illnesses, were associated with suicide risk in persons with depression. Machine learning may advance our ability to predict suicide deaths.

13.
Am J Public Health ; 111(7): 1202-1203, 2021 07.
Artigo em Inglês | MEDLINE | ID: mdl-34370522
15.
J Urban Health ; 98(Suppl 1): 79-88, 2021 08.
Artigo em Inglês | MEDLINE | ID: mdl-34374032

RESUMO

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). The rise of "big data" offers the potential to address some of these gaps. This scoping review sought to explore the literature linking energy, big data, health, and decision-making.Literature searches in PubMed, Embase, and Web of Science were conducted. English language articles up to April 1, 2020, were included. Pre-agreed study characteristics including geographic location, data collected, and study design were extracted and presented descriptively, and a qualitative thematic analysis was performed on the articles using NVivo.Thirty-nine articles fulfilled eligibility criteria. These included a combination of review articles and research articles using primary or secondary data sources. The articles described health and economic effects of a wide range of energy types and uses, and attempted to model effects of a range of technological and policy innovations, in a variety of geographic contexts. Key themes identified in our analysis included the link between energy consumption and economic development, the role of inequality in understanding and predicting harms and benefits associated with energy production and use, the lack of available data on LMICs in general, and on the local contexts within them in particular. Examples of using "big data," and areas in which the articles themselves described challenges with data limitations, were identified.The findings of this scoping review demonstrate the challenges decision-makers face in achieving energy efficiency gains and reducing emissions, while avoiding the exacerbation of existing inequities. 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.


Assuntos
Renda , Pobreza , Humanos
16.
J Urban Health ; 98(Suppl 1): 69-78, 2021 08.
Artigo em Inglês | MEDLINE | ID: mdl-34414511

RESUMO

Food is an important determinant of health, featuring prominently in the Sustainable Development Goals. The term "big data" is seldom used in relation to food, partly because food data are scattered across different sectors. The increasing availability of food-related data presents an opportunity to glean new insights on food and food systems. These insights may enhance the quality of products and services and improve decision-making on optimizing food availability, all to the end of producing better health. Yet, knowledge gaps remain about the unique opportunities and challenges linked to big data on food and their use in decision-making. This scoping review explored the available literature linking food with big data and decision-making, using the following research question: What is the current literature on data about food, and how are these data used in decision-making? We searched PubMed until 29 February 2020 and Embase, Web of Sciences, and the Cochrane Database of Systematic Reviews until 8 March 2020. We included studies written in English and conducted narrative analyses to identify relevant themes from included studies. Sixteen studies fulfilled our eligibility criteria, including big data analyses, modelling studies, and reviews. These studies described the added value of using big data and how evidence from big data had or can be used for decision-making, as well as challenges and opportunities for such use. The majority of the included studies examined the link between food and big data, while hypothesizing of how these insights could inform decision-making, including policies, interventions, programs, and financing. There were only two examples wherein big data on food informed decision-making directly. The review highlights several false dichotomies in how the subject is approached in the literature and the importance of context, both between and within countries, in shaping the availability and types of data that can be used as meaningful evidence to inform decision-making. This review shows the paucity of research around the intersection of food, big data, and decision-making, as well as the potential in using big data on food systems to the end of informing decisions to improve the health of populations. Future research and decision-making around health systems can benefit from examining the full spectrum of perspectives on the subject. Future research and decision-making around health systems can also employ the steadfast embrace of technology, which will potentially reduce disparities in big data availability, to the end of improving the health of populations.


Assuntos
Big Data , Desenvolvimento Sustentável , Análise de Dados , Humanos , Revisões Sistemáticas como Assunto
18.
J Urban Health ; 98(Suppl 1): 60-68, 2021 08.
Artigo em Inglês | MEDLINE | ID: mdl-34435262

RESUMO

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. By way of one example, the transportation sector plays a critical role in building and sustaining health outcomes in urban environments in general and in megacities in particular. We conducted a qualitative comparative case study design. We compared Bus Rapid Transit (BRT) policies in 3 megacities-Lagos (Africa), Bogotá (South America), and Beijing (Asia). We examined the extent to which data on the social determinants of health, equity considerations, and multisectoral approaches were incorporated into local politics and the decision-making processes surrounding BRT. We found that all three megacities paid inadequate attention to health in their agenda-setting, despite having considerable healthy transportation policies in principle. 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.


Assuntos
Doenças não Transmissíveis , Saúde da População , Cidades , Política de Saúde , Humanos , Nigéria , Doenças não Transmissíveis/epidemiologia , Transportes
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