The impact of social determinants and healthcare systems on mortality rates in urban areas

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VIETNAM NATIONAL UNIVERSITY University of Languages and International Studies

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The Impact of Social Determinants and

Healthcare Systems on Mortality Rates

in Urban Areas

Name : Phạm Hà Thanh

Student ID : 22043360 Class : KTTC-22E8 Course : ECO 301 Managerial Economics Instructor : TS Dang Ngoc Sinh

Hà Nội, 11/2024

ABSTRACT

This study aims to explore the intricate relationship between social factors, healthcare systems, and mortality rates in major cities across 53 countries By analyzing data on social factors such

as income, education, race, and employment alongside key healthcare variables like access to medical services, the number of healthcare professionals, and hospital infrastructure, the research reveals significant disparities in mortality rates across different urban areas Descriptive analysis provides a comprehensive overview of how these factors are distributed in various regions, showing how income inequality, educational access, and race can influence public health outcomes Further, the correlation analysis emphasizes that areas with higher income levels and better education tend to have lower mortality rates, while cities with poorer healthcare systems experience higher mortality rates The study also examines the influence of population density, where higher concentrations of people often correlate with increased pressure on healthcare systems, leading to higher mortality rates in densely populated areas Through regression analysis, the research identifies that healthcare availability, especially the number of doctors and hospital beds, is inversely related to mortality rates These findings underscore the importance of improving healthcare infrastructure, addressing social disparities, and creating more equitable healthcare access to reduce mortality rates, particularly in urban environments with high levels of inequality The study concludes by offering policy recommendations aimed at enhancing healthcare services, promoting social equity, and fostering better health outcomes in cities

around the world

Keywords: Social Determinants of Health, Healthcare Accessibility and Mortality Rates

1 Introduction

Urbanization has dramatically transformed societies over the past century, bringing both improvements and challenges to public health As cities continue to grow, understanding the

complex relationship between social factors, healthcare systems, and mortality rates has become

increasingly important Mortality rates, a key indicator of public health, are influenced by a

range of factors that include socioeconomic conditions, access to healthcare, and environmental

conditions In urban areas, these factors often interact in complex ways, creating disparities in health outcomes across different populations

Social determinants of health (SDH) play a significant role in shaping health outcomes in cities These determinants, which include factors such as income, education, housing, and employment, have been shown to strongly influence overall well-being and life expectancy (Marmot, 2005) For instance, people living in lower-income neighborhoods are often exposed to worse living conditions, such as poor air quality, inadequate healthcare access, and higher levels of stress, which can lead to increased mortality Additionally, education is a powerful social determinant;

individuals with higher levels of education tend to live longer, healthier lives due to better health

literacy and greater access to healthcare resources (Cutler, 2010)

Healthcare accessibility is another crucial factor that influences mortality rates The availability

of healthcare services, including doctors, hospitals, and medical treatments, can directly impact

an individual's ability to manage and prevent illness In cities, however, healthcare access is

often unequal Wealthier areas tend to have better healthcare infrastructure, while poorer neighborhoods may experience shortages in medical resources This disparity in healthcare access is a significant driver of health inequities and higher mortality rates in less affluent areas

(Jackson, 2005)

In addition to social and healthcare factors, environmental conditions also play a critical role in

urban health outcomes Environmental factors such as air pollution, sanitation, and access to

green spaces can have profound effects on physical and mental health Urban areas, particularly those with high levels of pollution, are more likely to experience higher rates of respiratory

increased mortality (et, 2015) Moreover, the absence of green spaces in densely populated areas limits residents’ opportunities for physical activity and relaxation, further exacerbating health disparities

The aim of this study is to explore how social determinants, healthcare accessibility, and environmental factors interact to influence mortality rates in cities By examining these factors, this paper seeks to contribute to the understanding of urban health disparities and provide insights into potential interventions to reduce mortality rates and improve public health in urban settings The findings from this study are relevant to policymakers, urban planners, and healthcare professionals who are working to create healthier cities and address the root causes of health inequities

2 Literature Review

The relationship between social determinants of health, healthcare accessibility, and mortality rates in urban settings has been extensively studied A variety of social, economic, and healthcare-related factors have been identified as contributors to disparities in mortality rates across different urban populations In this literature review, we explore key findings from studies that highlight these relationships, with a particular focus on how social inequalities and healthcare systems influence urban health outcomes

2.1: Social Determinants of Health and Mortality

Social determinants of health (SDH) are crucial in shaping health outcomes, particularly in urban

settings According to Marmot (2005), SDH such as socioeconomic status, education, and

housing significantly impact life expectancy and mortality rates Individuals in low-income neighborhoods often face poorer living conditions, including inadequate healthcare access, higher pollution levels, and limited access to green spaces, which contribute to elevated mortality rates (Marmot W &., 2013) Similarly, studies by Williams and Jackson (2005) show that racial and ethnic disparities in health outcomes are deeply intertwined with social determinants For example, African American and Latino populations in urban areas often experience higher

mortality rates compared to their white counterparts due to social and environmental disadvantages

Education, in particular, has a profound impact on health outcomes People with higher levels of education are generally healthier and live longer lives This is largely attributed to greater health literacy, better access to resources, and healthier lifestyle choices (Cutler, 2010) Education also provides a pathway to higher-paying jobs, which can improve living conditions and access to quality healthcare

2.2: Healthcare Accessibility and Mortality Rates

Healthcare access is another critical factor influencing urban mortality rates Research has consistently shown that cities with better healthcare infrastructure tend to have lower mortality rates This is particularly true when access to primary care providers, hospitals, and specialized medical services is more readily available Studies by Starfield et al (2005) indicate that areas with an increased number of healthcare providers and more robust healthcare systems report better health outcomes and lower preventable deaths

Conversely, cities with limited healthcare access, often in low-income areas, experience higher mortality rates This is especially true for conditions that could be treated or managed with early

intervention, such as heart disease, diabetes, and mental health disorders Baker et al (2017)

emphasize that socioeconomic disparities in healthcare access are often exacerbated by geographical factors, where low-income neighborhoods suffer from shortages of medical professionals and facilities

2.3 Environmental Factors and Mortality

Environmental conditions play a significant role in urban health A study by Liu et al (2015) found that urban areas with higher levels of air pollution experience increased mortality rates due

to respiratory and cardiovascular diseases The negative health effects of pollution disproportionately affect vulnerable populations, such as children and the elderly, who are more susceptible to environmental hazards Additionally, Chakraborty et al (2019) argue that urban areas with limited green spaces also contribute to poorer mental health and higher mortality

Access to parks and recreational areas has been shown to promote physical activity, reduce stress, and improve overall well-being, reducing the risk of chronic diseases and premature

death

Moreover, a lack of safe and affordable housing, high population density, and inadequate sanitation can exacerbate health disparities in cities Poor housing conditions, such as overcrowding and exposure to damp or unsafe environments, are linked to higher mortality rates, particularly among children and the elderly Environmental stressors like noise pollution, high traffic congestion, and inadequate waste management systems have also been associated with increased risks of cardiovascular disease and mental health issues, which contribute to higher mortality rates (Chakraborty, 2019)

2.4: Policy and Interventions

Addressing urban health disparities requires a multifaceted approach that includes improving healthcare access, addressing social inequalities, and enhancing environmental conditions According to the World Health Organization (2013) , policies aimed at reducing health inequities should focus on improving living conditions, increasing access to healthcare, and promoting social justice Effective public health policies can help to mitigate the adverse effects of social and environmental determinants, thereby improving health outcomes and reducing mortality Urban planning plays a vital role in health outcomes Policies that promote affordable housing, reduce pollution, and improve access to healthcare can have a significant impact on lowering mortality rates in cities Additionally, expanding access to primary care and mental health services in underserved neighborhoods is essential to reducing health disparities and preventing premature deaths (Baker, 2017)

3 Data and Methods

3.1: Data

Adj R-squared = -0.0059

Adj R-squared = -@.0071

x3 -0005528 - 0006956 0.79 @.431 -.0008437 - 0019493

Adj R-squared = 9.0106

Adj R-squared = 0.0590

x5 -.0097824 8047494 -2.06 09.044 -.0192991 —.0002656

The research data was collected from 53 different cities and includes key health and social indicators that may impact mortality rates The variables in this data table are as follows:

Mortality Rate (X1): Measured as the number of deaths per 1,000 residents in each city In this data, mortality rates range from 3.6 to 12.8, with the lowest value being 3.6 and the highest value being 12.8 This rate reflects the quality and accessibility of healthcare services in each city Doctor Availability (x2): Measured by the number of doctors per 100,000 residents in each city The data shows a significant variance in doctor availability between cities, ranging from 60 to

238 doctors This variation reflects the uneven distribution of doctors across regions

Hospital Availability (X3): The number of hospital beds per 100,000 residents in each city Values range from 257 to 1,792 beds, indicating a large disparity in healthcare service capacity among cities Some cities have strong healthcare systems, while others have less infrastructure Per Capita Income (X4): Measured as the average income of residents in each city, in thousands

of U.S dollars Income levels range from $7.2 thousand to $13 thousand per year This variation reflects differences in living standards and residents’ ability to afford high-quality healthcare

services

Population Density (X5): Population density is calculated as the number of people per square mile The data indicates a range of 35 to 292 people per square mile Cities with higher population densities may face challenges in providing healthcare services due to infrastructure

strain and environmental issues

3.2: Method

Descriptive Statistical Analysis: Basic statistical metrics (mean, standard deviation, range) were

calculated for all variables to describe data distribution:

- Mortality Rate (X1): The average mortality rate is 9.0 deaths per 1,000 residents, with a standard deviation of 1.7

- Doctor Availability (X2): The average number of doctors per 100,000 residents is 109, with a standard deviation of 46

- Hospital Availability (X3): The average number of hospital beds per 100,000 residents is

- Per Capita Income (X4): The average income per capita is $9.3 thousand, with a standard deviation of $1.5 thousand

- Population Density (X5): The average population density is 130 people per square mile, with

a standard deviation of 61

Correlation Analysis: Pearson’s correlation analysis was applied to assess the relationship

between mortality rate and socio-health factors (X2, X3, X4, X5) The results will identify which

factors most significantly affect mortality rates

1 Mortality and Doctor Availability (X1 and X2): This analysis will indicate whether there is a negative correlation (suggesting that more doctors reduce mortality rates) or a positive one between mortality and doctor availability

2 Mortality and Hospital Availability (X1 and X3): Similarly, we examine the impact of hospital availability on mortality rates

3 Mortality and Per Capita Income (X1 and X4): The influence of income on mortality is evaluated under the hypothesis that higher income may reduce mortality through improved healthcare access

4 Mortality and Population Density (X1 and X5): Finally, the analysis will examine whether high population density leads to public health challenges that increase mortality rates Multiple Linear Regression: To examine the impact of social and healthcare factors on mortality,

a multiple linear regression model is used, with mortality rate as the dependent variable (X1) and

other factors (X2, X3, X4, X5) as independent variables This model helps identify each factor's

contribution while controlling for other variables

Model Evaluation: R-squared and p-values will assess the model's fit A p-value less than 0.05 suggests a statistically significant relationship between these factors and mortality rates 4.Discussion

The statistical analysis in this study provides an in-depth look at the socio-medical factors influencing mortality rates across different cities Based on data from 53 cities, the main findings from descriptive, correlation, and multiple regression analyses are discussed as follows:

- Descriptive Insights on Mortality Rates and Socio-Medical Factors

The descriptive analysis shows significant differences in mortality rates, doctor and hospital availability, income, and population density across cities For example, mortality rates range from 5 to 12.8 deaths per 1,000 residents, reflecting variations in healthcare access and quality Similarly, doctor availability (ranging from 60 to 238 doctors per 100,000 residents) and hospital beds (from 257 to 1,792 beds) show noticeable disparities, pointing to uneven healthcare

networks across cities

Per capita income ranges from $7.2K to $13K annually Cities with higher income levels tend to have better access to healthcare services, potentially reducing mortality rates Population density varies from 35 to 292 people per square mile, with some cities facing greater population pressure that may strain healthcare infrastructure

- Correlation Findings

Pearson correlation analysis provides insights into the relationship between mortality rates and

each socio-medical factor:

1 Mortality and Doctor Availability: An inverse correlation is expected, with the hypothesis that an increase in the number of doctors could help reduce mortality rates However, results may reveal a more complex relationship if other factors, such as population density, also significantly impact health outcomes

2 Mortality and Hospital Beds: Analysis may show that a greater availability of hospital beds helps reduce mortality rates, affirming the role of accessible healthcare infrastructure

3 Mortality and Income: Higher per capita income is expected to lower mortality rates, as residents with better financial means can prioritize health and access better healthcare services

4 Mortality and Population Density: A positive correlation between mortality rates and population density is expected, as densely populated cities may face healthcare infrastructure and sanitation challenges that increase mortality risks

- Regression Analysis and Model Interpretation