scholarly journals Enhancing understandings of social determinants of health in China: Linkage and analysis of a national multilevel population health surveillance with routinely collected mortality records for 98 058 people in 31 provinces of mainland China

2019 ◽  
Author(s):  
Yunning Liu ◽  
Thomas Astell-Burt ◽  
Xiaoqi Feng ◽  
Fan Mao ◽  
Ruiming Liang ◽  
...  
Keyword(s):  
Infectious Disease ◽  
Social Determinants Of Health ◽  
Population Health ◽  
Social Determinants ◽  
Communicable Disease ◽  
Mainland China ◽  
Health Surveillance ◽  
Determinants Of Health ◽  
County Level ◽  
Injury Mortality

Abstract Background: The aim of this study was to enhance capability in research on social determinants of health in China by linking and analyzing routinely-collected death records over 5 years with national population health surveillance.Methods: Linkage of 98 058 participants in the 2010 China Chronic Disease and Risk Factor Surveillance (CCDRFS) to records in the national death surveillance data from 2011 to 2015 was conducted through a matching program involving identification numbers, name, gender and residential address, followed by a structured checking process. Multilevel regressions were used to investigate five-year odds of all-cause, non-communicable disease (NCD), infectious disease and injury mortality in relation to person- and county-level factors.Results: A total of 3,365 deaths were observed in the linked mortality and population health surveillance. Cross-checks and comparisons with national mortality distributions provided assurance that the linkage was reasonable. Geographic variation in mortality was observed via age and gender adjusted median odds ratios for all-cause mortality (>1.30), infectious disease (>2.01), NCD (>1.24) and injury (>1.12). Increased odds of all-cause and all three cause-specific mortality outcomes were higher with age and among men. Low educational attainment was a predictor of all-cause, NCD and injury mortality. Longer mean years of education at the county-level was only associated with lower injury mortality. Divorcees had a higher odd of all-cause and NCD mortality than singletons. Rurality was a predictor of all-cause and NCD mortality.Conclusion: The results of this study provide utility for future investigations of social determinants of health and mortality using linked data in China.

scholarly journals Integrating Social Determinants of Health to Precision Medicine through Digital Transformation: An Exploratory Roadmap

2021 ◽  
Vol 18 (9) ◽  
pp. 5018
Author(s):  
Ik-Whan G. Kwon ◽  
Sung-Ho Kim ◽  
David Martin
Keyword(s):  
Precision Medicine ◽  
Social Determinants Of Health ◽  
Population Health ◽  
Social Determinants ◽  
Information Technologies ◽  
Healthcare Delivery ◽  
Healthcare Providers ◽  
Determinants Of Health ◽  
Collaborative Tools ◽  
High Level

The COVID-19 pandemic has altered healthcare delivery platforms from traditional face-to-face formats to online care through digital tools. The healthcare industry saw a rapid adoption of digital collaborative tools to provide care to patients, regardless of where patients or clinicians were located, while mitigating the risk of exposure to the coronavirus. Information technologies now allow healthcare providers to continue a high level of care for their patients through virtual visits, and to collaborate with other providers in the networks. Population health can be improved by social determinants of health and precision medicine working together. However, these two health-enhancing constructs work independently, resulting in suboptimal health results. This paper argues that artificial intelligence can provide clinical–community linkage that enhances overall population health. An exploratory roadmap is proposed.

600 Social Determinants and Their Impact on Burn Surgery Outcomes

2021 ◽  
Vol 42 (Supplement_1) ◽  
pp. S151-S152
Author(s):  
Luis H Quiroga ◽  
Tomer Lagziel ◽  
Mohammed Asif ◽  
Raymond Fang ◽  
Grace F Rozycki ◽  
...  
Keyword(s):  
Mental Health ◽  
Diabetes Mellitus ◽  
Social Determinants Of Health ◽  
Population Health ◽  
Social Determinants ◽  
Determinants Of Health ◽  
Hospital Charges ◽  
Burn Patients ◽  
Increased Risk ◽  
History Of

Abstract Introduction To our knowledge, no studies have been conducted assessing the social determinants of health and the impact on the outcomes for burn patients. Such studies are needed considering burn injuries are associated with high costs, severe psychological impact, and a high burden placed on the healthcare systems. The burden is hypothesized to be aggravated by the increasing amount of diabetes and obesity seen in the general population which put patients at increased risk for developing chronic wounds. Studies have shown that several socioeconomic status (SES) factors are associated with increased risk of burns, but none have documented the outcomes of burn patients based on their social determinants of health. In our study, we will be comparing patients in the burn ICU (BICU) to patients in the surgical ICU (SICU). The purpose of this comparison is to evaluate whether the same social determinants of health have similar influences in both groups. Methods We performed a retrospective analysis of population group data from patients admitted to the BICU and SICU from January 1, 2016, to November 18, 2019. The primary outcomes were length-of-stay (LOS), mortality, 30-day-readmission, and hospital charges. Pearson’s chi-square test for categorical variables and t-test for continuous variables were used to compare population health groups. Results We analyzed a total of 487 burn and 510 surgical patients. When comparing BICU and SICU patients, we observed significantly higher mean hospital charges and LOS in burn patients with a history of mental health (mean difference: $42,756.04, p=0.013 and 7.12 days, p=0.0085), ESRD ($57,8124.7, p=0.0047 and 78.62 days, p=0.0104), sepsis ($168,825.19, p=< 0.001 and 20.68 days, p=0.0043), and VTE ($63,9924.1, p=< 0.001 and 72.9 days, p=0.002). Also, higher mortality was observed in burn patients with ESRD, STEMI, sepsis, VTE, and diabetes mellitus. Burn patients with a history of mental health, drug dependence, heart failure, and diabetes mellitus also had greater 30-day-readmissions rates. Conclusions This study sheds new knowledge on the considerable variability that exists between the different population health groups in terms of outcomes for each cohort of critically ill patients. It demonstrates the impacts of population health group on outcomes. These population groups and social determinants have different effects on BICU versus SICU patients and this study provides supporting evidence for the need to identify and develop new strategies to decrease overspending in healthcare. Further research to develop relevant and timely interventions that can improve these outcomes.

scholarly journals Structural and Social Determinants of Health Factors Associated with County-Level Variation in Non-Adherence to Antihypertensive Medication Treatment

2020 ◽  
Vol 17 (18) ◽  
pp. 6684
Author(s):  
Macarius M. Donneyong ◽  
Teng-Jen Chang ◽  
John W. Jackson ◽  
Michael A. Langston ◽  
Paul D. Juarez ◽  
...  
Keyword(s):  
Food Insecurity ◽  
Social Determinants Of Health ◽  
Social Determinants ◽  
Antihypertensive Medication ◽  
Social Supports ◽  
Determinants Of Health ◽  
P Value ◽  
County Level ◽  
Medication Treatment ◽  
Factors Associated

Background: Non-adherence to antihypertensive medication treatment (AHM) is a complex health behavior with determinants that extend beyond the individual patient. The structural and social determinants of health (SDH) that predispose populations to ill health and unhealthy behaviors could be potential barriers to long-term adherence to AHM. However, the role of SDH in AHM non-adherence has been understudied. Therefore, we aimed to define and identify the SDH factors associated with non-adherence to AHM and to quantify the variation in county-level non-adherence to AHM explained by these factors. Methods: Two cross-sectional datasets, the Centers for Disease Control and Prevention (CDC) Atlas of Heart Disease and Stroke (2014–2016 cycle) and the 2016 County Health Rankings (CHR), were linked to create an analytic dataset. Contextual SDH variables were extracted from the CDC-CHR linked dataset. County-level prevalence of AHM non-adherence, based on Medicare fee-for-service beneficiaries’ claims data, was extracted from the CDC Atlas dataset. The CDC measured AHM non-adherence as the proportion of days covered (PDC) with AHM during a 365 day period for Medicare Part D beneficiaries and aggregated these measures at the county level. We applied confirmatory factor analysis (CFA) to identify the constructs of social determinants of AHM non-adherence. AHM non-adherence variation and its social determinants were measured with structural equation models. Results: Among 3000 counties in the U.S., the weighted mean prevalence of AHM non-adherence (PDC < 80%) in 2015 was 25.0%, with a standard deviation (SD) of 18.8%. AHM non-adherence was directly associated with poverty/food insecurity (β = 0.31, P-value < 0.001) and weak social supports (β = 0.27, P-value < 0.001), but inversely with healthy built environment (β = −0.10, P-value = 0.02). These three constructs explained one-third (R2 = 30.0%) of the variation in county-level AHM non-adherence. Conclusion: AHM non-adherence varies by geographical location, one-third of which is explained by contextual SDH factors including poverty/food insecurity, weak social supports and healthy built environments.

scholarly journals The Social Determinants of Health in Disaster Risk Reduction

2019 ◽  
Vol 34 (s1) ◽  
pp. s95-s95
Author(s):  
Joseph Cuthbertson ◽  
Frank Archer ◽  
Jose Rodriguez-llanes ◽  
Andrew Robertson
Keyword(s):  
Social Determinants Of Health ◽  
Population Health ◽  
Social Determinants ◽  
Disaster Risk ◽  
Determinants Of Health ◽  
Health Determinants ◽  
Community Perception ◽  
Individual Interviews ◽  
The Social ◽  
Socially Isolated

Introduction:The rationale for undertaking this study was to investigate how characteristics of population health relate to and impact disaster risk, resilience, vulnerability, impact, and recovery. The multi-disciplinary environment that contextualizes disaster practice can influence determinants of health. Robust health determinants, or lack thereof, may influence the outcomes of disaster events affecting an individual or a community.Aim:To investigate how the social determinants of health inform community perceptions of disaster risk.Methods:Community perception of disaster risk in reference to the social determinants of health was assessed in this study. Individual interviews with participants from a community were conducted, all of whom were permanent community residents. Thematic analysis was conducted using narrative inquiry to gather firsthand insights on their perceptions of how characteristics of population health relate to and impact an individual’s disaster risk.Results:Analysis demonstrated commonality between interviewees in perceptions of the influence of the social determinants of health on individual disaster risk by determinant type. Interviewees sensed a strong correlation between low community connection and disaster risk vulnerability. Specific populations thought to have low community connection were perceived to be socially isolated, resulting in low knowledge or awareness of the surrounding disaster risks, or how to prepare and respond to disasters. In addition, they had reduced access to communication and support in time of need.Discussion:The importance of a strong social community connection was a feature of this research. Further research on how health determinants can enable disaster risk awareness and disaster risk communication is warranted.

scholarly journals Usability Evaluation of a Portable Health Information Kiosk Using a SMAARTTM Intervention Framework

2017 ◽  
Vol 9 (8) ◽  
pp. 153 ◽  
Author(s):  
Ashish Joshi ◽  
Mohit Arora ◽  
Bhavya Malhotra
Keyword(s):  
Social Determinants Of Health ◽  
Health Information ◽  
Clinical Data ◽  
Social Determinants ◽  
Communicable Disease ◽  
Urban Slum ◽  
Determinants Of Health ◽  
Empirical Literature ◽  
Individual Risk ◽  
Convenience Sample

Empirical literature has shown that interventions to address social determinants of health are limited owing to poor integration of social and clinical data. The objective of this study was to describe a Sustainable, Multisector, Accessible, Affordable, Reimbursable, and Tailored framework (SMAARTTM) which was utilized to design and pilot test portable health information kiosk that can facilitate the integration of social determinants of health data with clinical data to enhance population health outcomes in global settings. The SMAART TM framework was designed using a combined approach of Data, Information Knowledge, Human Centered approach and behavioral humanistic and learning theories, and was applied to develop and evaluate an interactive, bi-lingual computer enabled portable health information kiosk. A convenience sample (recruitment based on accessibility to the researcher) of 149 individuals aged 18 years and above living in urban slum settings of India were enrolled in the year 2013. Subjective and objective data gathering included socio-demographics, clinical history, health behaviors and knowledge, attitude and practices. Weight and blood pressure levels were measured using physiological sensors. Usability assessment of the health information kiosk was also conducted. Results showed an increased burden of chronic non-communicable disease (NCD) risk factors and related knowledge, and lack of healthy lifestyle practices among urban slum individuals. Our study showed that the technology enabled SMAART TM framework can be utilized to develop an individual risk profile for better disease prevention, monitoring and management of chronic NCDs.

scholarly journals Differences in COVID-19 Risk by Race and County-Level Social Determinants of Health among Veterans

2021 ◽  
Vol 18 (24) ◽  
pp. 13140
Author(s):  
Hoda S. Abdel Magid ◽  
Jacqueline M. Ferguson ◽  
Raymond Van Cleve ◽  
Amanda L. Purnell ◽  
Thomas F. Osborne
Keyword(s):  
Social Determinants Of Health ◽  
Social Determinants ◽  
Linear Models ◽  
Determinants Of Health ◽  
Health Concern ◽  
County Level ◽  
Department Of Veterans Affairs ◽  
Optimal Care ◽  
Level Data ◽  
Significant Public Health

COVID-19 disparities by area-level social determinants of health (SDH) have been a significant public health concern and may also be impacting U.S. Veterans. This retrospective analysis was designed to inform optimal care and prevention strategies at the U.S. Department of Veterans Affairs (VA) and utilized COVID-19 data from the VAs EHR and geographically linked county-level data from 18 area-based socioeconomic measures. The risk of testing positive with Veterans’ county-level SDHs, adjusting for demographics, comorbidities, and facility characteristics, was calculated using generalized linear models. We found an exposure–response relationship whereby individual COVID-19 infection risk increased with each increasing quartile of adverse county-level SDH, such as the percentage of residents in a county without a college degree, eligible for Medicaid, and living in crowded housing.

Abstract P178: Social Determinants Of Health And Preventable Hospitalization For Hypertension

Hypertension ◽  
2021 ◽  
Vol 78 (Suppl_1) ◽  
Author(s):  
Priyadarshini Pattath ◽  
Rexford Anson-Dwamena
Keyword(s):  
Air Quality ◽  
Social Determinants Of Health ◽  
Social Determinants ◽  
Principal Component ◽  
Healthcare Research ◽  
Hospitalization Rate ◽  
Material Deprivation ◽  
Determinants Of Health ◽  
County Level ◽  
Preventable Hospitalization

Introduction: Social determinants of health (SDH) can have a significant impact on the risk of hypertension related hospitalization. Understanding the drivers of potentially preventable hospitalizations for hypertension improves health outcomes and reduce associated costs. Identifying place and associated SDH has implications for tailored interventions to address disparities for high burden population for preventable hypertension hospitalization as hypertension and associated cardiovascular disease. Methods: County level preventable hospitalization rates for hypertension for Virginia was obtained using prevention quality indicators published by the Agency for Healthcare Research and Quality. The Health Opportunity Index (HOI), developed by the Virginia Department of Health to identify vulnerable populations is a multivariate tool that uses complex SDH indicators of a community and comprises of 13 indices - affordability, income inequality, Townsend/Material deprivation, job participation, employment access, education, air quality, segregation, food accessibility, population density, population churning, walkability, and access to care. Principal component analysis was used to develop the composite HOI and further aggregated into simple quintiles at the county level. Step-wise multiple regression analysis was performed to explore SDH and preventable hospitalization for hypertension. Results: Material deprivation index ( r = -.44), affordability index ( r = -.42) and air quality index ( r = -.23) were found to be significantly associated with preventable hospitalization rate for hypertension. Together the model accounted for 23% of the variability in the preventable hypertension hospitalization rate ( p > 0.05). Conclusions: Findings indicate that neighborhoods that spend most on housing and transportation and that are materially deprived of goods, services, amenities and resources and physical environment have higher rates of preventable hospitalization for hypertension. Areas with higher air pollution may result in hypertension. Addressing these disparities by targeted approach is one possible approach to reducing the burden of preventable hospitalization for hypertension in Virginia.

Epidemiological Transition and Population Health: Understanding Social Determinants of Health in China

2016 ◽  
Vol 26 (3) ◽  
pp. 223-246
Author(s):  
Soma Hewa ◽  
Bo Liu
Keyword(s):  
Health Promotion ◽  
Social Determinants Of Health ◽  
Chronic Diseases ◽  
Population Health ◽  
Social Determinants ◽  
Social Epidemiology ◽  
Determinants Of Health ◽  
Effective Population ◽  
Future Health ◽  
Mortality And Morbidity

This article has twin objectives: First, the article briefly examines major theoretical interpretations of disease causations in Western medicine, their limitations in understanding social epidemiology, and the gradual development of the population health approach to health promotion and disease prevention in the context of chronic diseases in Western industrialized societies. Second, the article examines the current epidemiological trends in China and the relevance of population health perspectives and strategies to promote health. While analyzing some recent findings on social determinants of health in China, the article argues that effective population health strategies for health promotion must be based on a social epidemiology that provides information necessary to promote health. Although infectious diseases still make a significant contribution to China’s mortality and morbidity figures, the incidence of chronic diseases such as malignancies, heart disease, respiratory disease, and cerebrovascular disease is steadily increasing. Finally, in view of the current epidemiological trend, and the need to tackle the multiple health challenges, this discursive analysis proposes a number of key research areas within the broader context of social epidemiology that may facilitate future health policies in China.

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