Socioeconomic Variables Research Articles

Assessing the Impact of Environmental Quality on Public Health Expenditure Central Asia

This study utilizes panel data from 2002 to 2022 in Central Asia to analyze the impact of environmental quality on public health expenditures. This study employs the ARDL model to examine the short-run and long-run relationships between healthcare expenditure and pollution levels, namely carbon dioxide (CO2), sulfur dioxide (SO2), and nitrogen dioxide (NO2). The data indicate a robust positive correlation between greenhouse gases and healthcare expenditures, demonstrating the effect of environmental pollution on public health. The study examines the relationship between socioeconomic variables, including GDP, death rates, and healthcare expenditures. This study concludes that reversing this trend hinges on improving environmental policy in the energy and industrial sectors. This research contributes to the existing knowledge by analyzing how various environmental elements and economic structures persistently impact health policy evolution in the region.

Transforming healthcare performance monitoring - A cutting-edge approach with generalized additive profiles: GAMs for healthcare quality monitoring.

Recent findings indicate a growing trend in data analysis within healthcare using statistical process control. However, the diversity of variables involved necessitates the expansion of new process control methodologies. This study examined control chart applications in cardiology by using generalized additive models (GAMs) to construct profiles while involving multiple healthcare variables (08). Two distinct statistics: deviation (D), and Hotelling (T2) were employed for constructing control charts: a commonly used single-variable statistic for nonparametric profiles and an innovative multivariate statistic that assesses the contribution of each element to process changes. These statistics were tested for monitoring ischemic and hemorrhagic strokes in 1-year acute stroke (369) patients at the Faisalabad Institute of Cardiology. Demographic parameters (age, gender), vascular risk factors (diabetes, family history, sleep), socioeconomic variables (smoking, location), and blood pressure are included in the model. The research includes the computation of zero-state average run length (ARL) for assessing the performance of control charts. The characteristics of the proposed profile were analyzed, such as the T2 control chart, performing better than the D chart for medium-to-large shifts (δ ≥ 0.50). On the other hand, for small δ = 0.25, the D control chart produces smaller ARL values but more significant standard deviations. While both statistics contribute to profile monitoring, T2 is more effective at identifying and tracing medium and large shifts. In conclusion, such handy tools may aid healthcare performance monitoring, especially for complicated predictor-response relationships. Monitored profiles demonstrated that GAMs are useful for healthcare analysis and process monitoring.

Association between temperature and occupational injuries in Spain: The role of contextual factors in workers’ adaptation

BackgroundExtensive evidence links both cold and hot temperatures to an increased incidence of occupational injuries. Contextual modifiers of the temperature-injury association have been scarcely researched. The present study addresses temporal and spatial variations to identify factors associated with (mal)adaptation to heat and cold among Spanish workers. MethodsWe assessed the association between daily mean temperature and work injuries using quasi-Poisson time-series regression models in 48 Spanish provinces over the period 1988–2019, with comparative analyses with census and economic data for the sub-periods 1989–1993, 1999–2003, 2009–2013 and 2015–2019. We explored the spatial and spatiotemporal modification of the association by demographic and socioeconomic variables via cross-sectional and longitudinal meta-regressions. Findings:We found an increased risk of work-injuries by 4 % [95 % CI: 3 %-6 %] and 12 % [95 % CI: 10 %-13 %], for the 1st and 99th percentiles of temperature, respectively, for period 1988–2019. Heat had a greater overall impact than cold, and the groups more vulnerable to heat were male workers, under 35 years, and working in agriculture, construction and hostelry. Vulnerability to heat was highest in the earliest sub-period, while vulnerability to cold rose during periods of both economic expansion and recession. High educational attainment emerged as a protective factor during the warm months in the cross-sectional meta-regressions. ConclusionsOur findings suggest an adaptation of Spanish workers to high temperatures over time. However, preventive measures are needed for traditionally exposed workers (agriculture and construction), non-traditionally vulnerable sectors (hostelry), and young, male, and less educated workers during warm months. For cold vulnerability, targeted measures should focus on women, the elderly, and tertiary service workers, especially in colder regions. Addressing temperature vulnerability would enhance worker safety, reduce injuries, and yield economic benefits.

Mortality risk predicts global, local, and individual patterns of human reproduction

BackgroundHuman reproductive dynamics in the post-industrial world are typically explained by economic, technological, and social factors including the prevalence of contraception and increasing numbers of women in higher education and the workforce. These factors have been targeted by multiple world governments as part of family policies, yet those policies have had limited success. The current work adopts a life history perspective from evolutionary biology: like most species, human populations may respond to safer environments marked by lower morbidity and mortality by slowing their reproduction and reducing their number of offspring. We test this association on three levels of analysis using global, local, and individual data from publicly available databases.ResultsData from over 200 world nations, 3,000 U.S. counties and 2,800 individuals confirm an association between human reproductive outcomes and local mortality risk. Lower local mortality risk predicts “slower” reproduction in humans (lower adolescent fertility, lower total fertility rates, later age of childbearing) on all levels of analyses, even while controlling for socioeconomic variables (female employment, education, contraception).ConclusionsThe association between extrinsic mortality risk and reproductive outcomes, suggested by life history theory and previously supported by both animal and human data, is now supported by novel evidence in humans. Social and health policies governing human reproduction, whether they seek to boost or constrain fertility, may benefit from incorporating a focus on mortality risk.

Individual, household, and socio-economic predictors of COVID-19 testing and vaccination outcomes: a whole population linked data analysis

ObjectiveThe COVID-19 pandemic has exposed numerous social inequities in health outcomes across nations, despite early warnings of their potential. Poorer outcomes for ethnic minorities, and to a lesser extent Indigenous peoples, have been widely reported, and may be explained in part by household conditions and poorer socio-economic circumstances. This study aimed to identify the effects of diverse individual and social conditions on COVID-19 outcomes within the New Zealand population. MethodWe conducted a whole population analysis of the association between individual (e.g. ethnicity, disability status), household (e.g. household composition), and socio-economic (e.g. crowding, housing quality, income) factors and four COVID-19 health outcomes – infection, hospitalisation, mortality, and vaccination status. We constructed variables of interest from linked administrative data in New Zealand’s Integrated Data Infrastructure, and examined associations within the 2018 Census usually resident population (analysis Ns = 518,571 - 3,216,696). ResultsAnalyses showed that Māori (the Indigenous people of New Zealand) and Pacific peoples, an ethnic minority, experienced worse outcomes than other New Zealanders across all COVID-19 outcomes. These ethnic group differences were persistent, yet reduced, when accounting for household and socio-economic variables. Factors including disability status, high housing mobility, poor quality housing, and household crowding were also widely predictive of worse outcomes. ConclusionEthnic inequity in a range of COVID-19 outcomes is present in a country where the overall impacts of the pandemic were relatively limited. Individual, household, and socio-economic factors are associated with diverse COVID-19 outcomes, and policy amenable factors may help explain the presence of ethnic inequities.

Preliminary analysis of socioeconomic variable correlation with geospatial modeling in Costa Rica dengue epidemics

Dengue is a mosquito-transmitted disease that affects more than 5 million people worldwide. It is endemic in more than 100 countries and it has presence in 5 continents. Understanding the dynamics of dengue epidemics is crucial in reducing the massive public health impact this disease has. However, dengue is a complex phenomenon. There are many variables that contribute to the spread of the virus and the interconnection of those variables is not clear. We set out to explore the correlation of socioeconomic variables in dengue epidemics by using a geospatial model. Our study is centered in Costa Rica, a country with a repeated affectation by the virus. We found a possible relationship between number of dengue cases and some socioeconomic variables (dwellings with water pipes, location of work), which open the gates to consider including them in a more sophisticated epidemiological model.

Determinants of Perception, Adaptation Strategy and Measuring Composite Vulnerability of Agricultural Households to Climate Change in the Desert State Rajasthan, India

The study aims to assess agricultural households’ vulnerability, perception and adaptation to climate change in the desert state of Rajasthan, India. A data set of 600 households was collected using a purposive random sampling technique from six districts: Ajmer, Barmer, Jodhpur, Jaipur, Dausa and Tonk. While using the binary logit model, factors affecting the perception and adaptation of agricultural households were assessed, and a composite livelihood vulnerability index was constructed to determine the households’ susceptibility to climate change. The findings suggest that the majority of the households are moderately vulnerable. Of the total households surveyed, 89 per cent of the agricultural households perceive climate change. 83.3 per cent of perceived households used adaptation strategies such as mixed cropping, crop rotation and farm ponds. Socioeconomic variables like the educational status of the household head, farming experience, type of agriculture financial support, agricultural training, land size and access to agricultural institutions influence farmers’ adaptation decisions. Further, lack of information, extension services, access to credit, improved seeds and water, insufficient capital, infertile soil and a labour shortage are barriers to adaptive strategies. Hence, the study recommends effective government policies to enhance credit availability, financial support and agricultural mechanisation for agricultural households. JEL Codes: Q54, Q12, Q18

Wildfire Loss Modeling: A Flexible Semiparametric Approach

Wildfires have emerged as one of the most devastating natural disasters worldwide, which, in addition to a loss of life, results in billions of dollars in annual losses. This study aims to identify factors that contribute to the frequency and severity of wildfire losses. We propose a semiparametric modeling approach to analyze wildfire property losses in the United States from 1995 to 2020. Our methodology incorporates flexible generalized additive models for location, scale, and shape (GAMLSS), which integrate climate, socioeconomic, and geographical variables into the modeling process. Through empirical analysis, we demonstrate the critical role of spatial effects in modeling wildfire-related property losses. Additionally, we identify key variables, including house index, state population, wildfire duration, and climate index, that significantly contribute to explaining the average property loss. These findings offer valuable insights for enhancing catastrophe risk management for insurance companies and government agencies. Furthermore, the proposed approach can be easily applied to diverse regions grappling with spatially varying catastrophe risks.

Risk factors for student dropout in higher education institutions in latin america

Introduction: In Latin America, university dropouts significantly influence the individual development of students and the socioeconomic progress of the region. Identifying risk factors allows educational institutions to recognize and address the specific needs of their students to create effective methods that foster academic success and retention. Objective: Analyze the various risk factors for student Dropout in Higher Education Institutions in Latin America with the purpose of proposing strategies that reduce the negative rates of this problem. Methods: A bibliographic review of studies published between 2010 and 2024 on risk factors for student dropout in higher education in Latin America was carried out, using relevant databases and applying rigorous inclusion and exclusion criteria. Results: Personal, academic, institutional and socioeconomic variables are part of the risk factors for University Dropout. The lack of access to Higher Education has a significant impact on the economic and social growth of Latin America since it is essential for the training of qualified professionals. The high dropout rate contributes to a less prepared workforce and limits job opportunities for young people. Conclusions: The prevalent risk factors were academic and personal associated with university dropout in Latin America, which is why various strategies were proposed to generate inclusive and equitable higher education through the reformulation of public and institutional policies.

The impact of war on forest logging: Changes in logging practices in Syrian rural communities

Syria has been struggling with a prolonged and brutal war for over a decade, leaving much of the country in devastation and its forests severely degraded. While many studies have identified logging for firewood as a significant driver of deforestation during the war, there is a notable absence of research specifically addressing logging behavior within the context of war. This research seeks to address this gap by examining the changes in logging behavior among local communities, the effects of violence and socioeconomic variables on wood harvesting, the contribution of wood income to people's survival during the war. To do that, we conducted survey questionnaires in two coastal villages in Syria—Blouta and Nehel al Annaze—which experienced high and low levels of violence, respectively. Our findings reveal that logging activities increased once the war began, with more people involved in forest harvesting and average days spent logging per week significantly increasing from 1.5 to 4. Additionally, the war appeared to reduce the gender disparity in logging activities: before the conflict, women engaged in logging significantly more frequently than men, but this difference became insignificant during the war. The level of violence alone did not significantly affect the amount of wood logged per month. Furthermore, income generated from wood harvesting played a substantial role in bridging the gap between the monthly income needed to cover their basic necessities and the actual income of families in both villages by 46.94 % and 84.83 % of the gap in Nehel al Annaze and Blouta, respectively. These results highlight the crucial role of forest resources in supporting rural livelihoods during times of war. Post-war effective forest management will be vital to ensure the sustainable use and recovery of forest resources, supporting both ecological restoration and economic stability for the rural communities.

The Total Economic Value of Lands with Civic Uses as a Tool for Their Protection and Enhancement: A Case Study in Tuscany

This study aims to quantify the economic value of environmental externalities by proposing an approach tailored to areas designated for “civic uses”. These areas fall within the broader category of “collective goods” on which the legislator places particular emphasis, especially in regard to their protection and enhancement. The technique applied in this study is the total economic value (TEV), quantified through a spatialization and modeling of socioeconomic and environmental variables on Geographic Information Systems. The methodology was used for a specific case study area, the forests of Land Association “Bosco dei Bardi” in the Tuscany region of central Italy. This area exhibits the same characteristics and fulfills the same functions as those designated for civic uses. The results demonstrate the importance of providing public decision-makers with appropriate tools to protect and enhance these areas. The results also underscore the economic significance of forest ecosystem services compared to average regional values. The study finally confirms that Land Associations present a promising avenue for revitalizing abandoned territories, consistent with civic use objectives.

Accelerometer-Based Physical Activity and Health-Related Quality of Life in Korean Adults: Observational Study Using the Korea National Health and Nutrition Examination Survey.

Health-related quality of life (HRQoL) reflects an individual's perception of their physical and mental health over time. Despite numerous studies linking physical activity to improved HRQoL, most rely on self-reported data, limiting the accuracy and generalizability of findings. This study leverages objective accelerometer data to explore the association between physical activity and HRQoL in Korean adults. The objective of this study is to analyze the relationship between objectively measured physical activity using accelerometers and HRQoL among Korean adults, aiming to inform targeted interventions for enhancing HRQoL through physical activity. This observational study included 1298 participants aged 19-64 years from the Korea National Health and Nutrition Examination Survey (KNHANES) VI, who wore an accelerometer for 7 consecutive days. HRQoL was assessed using the EQ-5D questionnaire, and physical activity was quantified as moderate-to-vigorous physical activity accelerometer-total (MVPA-AT) and accelerometer-bout (MVPA-AB). Data were analyzed using logistic regression to determine the odds ratio (ORs) for low HRQoL, adjusting for socioeconomic variables and mental health factors. Participants with higher HRQoL were younger, more likely to be male, single, highly educated, employed in white-collar jobs, and had higher household incomes. They also reported less stress and better subjective health status. The high HRQoL group had significantly more participants meeting MVPA-AB ≥600 metabolic equivalents (P<.01). Logistic regression showed that participants meeting MVPA-AB ≥600 metabolic equivalents had higher odds of high HRQoL (OR 1.55, 95% CI 1.11-2.17). Adjusted models showed consistent results, although the association weakened when adjusting for mental health factors (OR 1.45, 95% CI 1.01-2.09). The study demonstrates a significant association between HRQoL and moderate to vigorous physical activity sustained for at least 10 minutes, as measured by accelerometer. These findings support promoting physical activity, particularly sustained moderate to vigorous activity, to enhance HRQoL. Further interventional studies focusing on specific physical activity domains such as occupational, leisure-time, and commuting activities are warranted.

Agrarian Distress in Indian Agriculture: Causes, Socio-economic Consequences and Coping Strategies

Agrarian distress is the economic, political and social challenges faced by the farmers and rural communities due to factors such as low crop yields, fluctuating prices of agricultural produce, high input costs, indebtedness, and lack of access to credit, markets, and infrastructure. Over 8,00,000 individuals are dies by suicide each year because of various reasons. More over the suicides are happening in the families whose own land is less than 1-2 hectares, who are in debt, have been identified the most at risk for suicide. The present article aims at better understanding of the causes, consequences and possible coping strategies for the agrarian distress in India. Causes such as fluctuations in crop sales, weather and climate conditions, dependent on natural resources, etc. are discussed in detail. Consequences of agrarian stress are suicides of farmers, rural migration, food insecurity, environmental impacts and so on. Solutions such as strengthening the forward markets, comprehensive crop insurance schemes for the framers where the non-MSP (Minimum Support Price) crops also may be covered, assured price to the farmers are discussed. Many researchers argued that farmers suicides are increasing but the research is limited in the specialised area of interest. In addition to that, researchers are focussing only on the socio-economic variables rather than the psychological variables. In order to mitigate the risks out of agrarian distress, farmers should be encouraged by the government and extension service providers to take up the subsidiary occupations and secondary agricultural occupations which helps them in getting profits in the situations where the crop damages due to the extreme weather patterns. As rightly pointed out by National Bank for Agriculture and Rural Development (NABARD), distress of the framers should have a long-term potential solution such as major reforms in the existing agricultural laws rather than farm loan waivers which acts as the short-term relief to the farmers.

Human capital indicators as influenced by SES, cognitive and non-cognitive skills: evidence from Taiwan’s PISA performance

Taiwan’s high performance in the PISA surveys has not been unnoticed by researchers. However, both individual level research and cross-national research which is relevant for Taiwan’s PISA achievement is typically lacking, especially as regards later surveys. This article examined Taiwan’s PISA mathematics and reading achievement in 2018, using individual level data (Valid N = 6863) and cross-national data with aggregated data for 77 countries. At the individual level, socioeconomic and non-cognitive variables explain the most variance of PISA mathematics and reading. At the cross-national level, cognitive ability and average income were statistically significant with cognitive ability as the strongest predictor. As Taiwan has a high level of average cognitive ability it may regarded as a strong comparative advantage with regard to human capital.

Prediction of delayed breastfeeding initiation among mothers having children less than 2 months of age in East Africa: application of machine learning algorithms.

Delayed breastfeeding initiation is a significant public health concern, and reducing the proportion of delayed breastfeeding initiation in East Africa is a key strategy for lowering the Child Mortality rate. However, there is limited evidence on this public health issue assessed using advanced models. Therefore, this study aimed to assess prediction of delayed initiation of breastfeeding initiation and associated factors among women with less than 2 months of a child in East Africa using the machine learning approach. A community-based, cross-sectional study was conducted using the most recent Demographic and Health Survey (DHS) dataset covering the years 2011 to 2021. Using statistical software (Python version 3.11), nine supervised machine learning algorithms were applied to a weighted sample of 31,640 women and assessed using performance measures. To pinpoint significant factors and predict delayed breastfeeding initiation in East Africa, this study also employed the most widely used outlines of Yufeng Guo's steps of supervised machine learning. The pooled prevalence of delayed breastfeeding initiation in East Africa was 31.33% with 95% CI (24.16-38.49). Delayed breastfeeding initiation was highest in Comoros and low in Burundi. Among the nine machine learning algorithms, the random forest model was fitted for this study. The association rule mining result revealed that home delivery, delivered by cesarean section, poor wealth status, poor access to media outlets, women aged between 35 and 49 years, and women who had distance problems accessing health facilities were associated with delayed breastfeeding initiation in East Africa. The prevalence of delayed breastfeeding initiation was high. The findings highlight the multifaceted nature of breastfeeding practices and the need to consider socioeconomic, healthcare, and demographic variables when addressing breastfeeding initiation timelines in the region. Policymakers and stakeholders pay attention to the significant factors and we recommend targeted interventions to improve healthcare accessibility, enhance media outreach, and support women of lower socioeconomic status. These measures can encourage timely breastfeeding initiation and address the identified factors contributing to delays across the region.

Evaluation of the impact of hydrological changes on reservoir water management: A comparative analysis the CanESM5 model and the optimized SWAT-SVR-LSTM

This research examines the impacts of climate change and socio-economic variables on the hydrological cycle, reservoir water management, and hydropower capacity at the Gezhouba Dam. The Gezhouba Dam serves as a crucial hydroelectric power station and dam, playing a vital role in regulating river flow and generating electricity. In this study, an innovative method is employed, combining the Soil and Water Assessment Tool (SWAT), Support Vector Regression (SVR), and Long Short-Term Memory (LSTM) models. This model is optimized using the Developed Thermal Exchange Optimizer. This optimized combined model significantly enhances the reliability and precision of the forecasting inflow and reservoir levels. By utilizing the Canadian Earth System Model version 5 (CanESM5), we examine climate variables across various scenarios of Representative Concentration Pathway (RCP) and Shared Socioeconomic Pathway (SSP). Under the SSP5-RCP8.5 scenario, the most aggressive in terms of emissions, we project a temperature rise of 2.6 % and a precipitation decrease of 2.7 %. This scenario leads to the most substantial changes in the hydrological cycle and altered river flow patterns. The results show a direct correlation between precipitation and inflow (0.952) and a strong inverse correlation between temperature and inflow (0.893). The study predicts significant decreases in all flow metrics, with mean high flow (Q5) periods affecting hydropower generation, especially under the SSP5-RCP8.5 scenario. Additionally, the filling frequency rate (FFR) and mean filling level (MFL) are projected to decrease, with a more pronounced decline in the far future, indicating a potential compromise of the reservoir's water storage and power generation capabilities, especially under the SSP5-RCP8.5 scenario.

Public health infrastructure and COVID-19 spread: An air transportation network analysis

This study examines the effectiveness of public health infrastructure, specifically hospital and Intensive Care Unit (ICU) capacities, in mitigating the spread of COVID-19 in various US counties. We use the air transportation network to quantify the risk of importing COVID-19-infected passengers to a given county in the United States. Utilizing a dataset that encompasses COVID-19 case rates, healthcare resources, and socioeconomic and transportation-related variables across multiple destination counties, we found that increased availability of hospital and ICU beds is statistically significantly associated with a reduced risk of COVID-19 spread, after controlling for origin county infection rates, travel patterns, and socioeconomic factors. These findings underline the critical role of robust healthcare infrastructure in public health crisis management and suggest targeted policy interventions to bolster healthcare capacity as a viable strategy for mitigating pandemic impacts.

Early Adversity and Socioeconomic Factors in Pediatric Multiple Sclerosis: A Case-Control Study.

Psychosocial adversity and stress, known to predispose adults to neurodegenerative and inflammatory immune disorders, are widespread among children who experience socioeconomic disadvantage, and the associated neurotoxicity and proinflammatory profile may predispose these children to multiple sclerosis (MS). We sought to determine associations of socioeconomic disadvantage and psychosocial adversity with odds of pediatric-onset MS (POMS), age at POMS onset, and POMS disease activity. This case-control study used data collected across 17 sites in the United States by the Environmental and Genetic Risk Factors for Pediatric Multiple Sclerosis Study. Cases (n = 381) were youth aged 3-21 years diagnosed with POMS or a clinically isolated demyelinating syndrome indicating high risk of MS. Frequency-matched controls (n = 611) aged 3-21 years were recruited from the same institutions. Prenatal and postnatal adversity and postnatal socioeconomic factors were assessed using retrospective questionnaires and zip code data. The primary outcome was MS diagnosis. Secondary outcomes were age at onset, relapse rate, and Expanded Disability Status Scale (EDSS). Predictors were maternal education, maternal prenatal stress events, child separation from caregivers during infancy and childhood, parental death during childhood, and childhood neighborhood disadvantage. MS cases (64% female, mean age 15.4 years, SD 2.8) were demographically similar to controls (60% female, mean age 14.9 years, SD 3.9). Cases were less likely to have a mother with a bachelor's degree or higher (OR 0.42, 95% CI 0.22-0.80, p = 0.009) and were more likely to experience childhood neighborhood disadvantage (OR 1.04 for each additional point on the neighborhood socioeconomic disadvantage score, 95% CI 1.00-1.07; p = 0.025). There were no associations of the socioeconomic variables with age at onset, relapse rate, or EDSS, or of prenatal or postnatal adverse events with risk of POMS, age at onset, relapse rate, or EDSS. Low socioeconomic status at the neighborhood level may increase the risk of POMS while high parental education may be protective against POMS. Although we did not find associations of other evaluated prenatal or postnatal adversities with POMS, future research should explore such associations further by assessing a broader range of stressful childhood experiences.

Evaluation of the potential of infrastructure funds: The case of inland waterways in Germany

Given the critical need for sustainable transportation solutions, inland waterways (IWs) constitute a crucial yet underfunded mode of transport. This study examines deficiencies in current infrastructure funding and analyzes infrastructure funds (IFs) as an alternative funding mechanism and potential means to revitalize German waterways.Central to this investigation is the analysis of the German population's willingness to pay (WTP) for such funds. To this end, a comprehensive online survey of German households was conducted, and multivariate regression analysis was employed to identify key factors influencing public support for various fund designs.The results reveal that personal experiences with flooding significantly affect WTP and underscore the role of socio-economic variables in shaping public attitudes toward infrastructure funding. The findings indicate that well-designed IFs, combined with effective communication strategies to raise awareness of the importance of waterways, could significantly enhance public support. The study demonstrates that IFs have significant potential as a strategic tool for mobilizing public funding, thereby supporting the sustainable development and maintenance of essential yet underfunded infrastructure. IFs present a promising solution to the financial challenges facing critical public goods such as waterways.

Accessibility, neighborhood socioeconomic disadvantage and expenditures on electronic gambling machines: a spatial analysis based on player account data

BackgroundGambling and its harmful effects on human health and well-being represent a significant public health concern in many countries, with electronic gambling machines (EGMs) recognized as one of the most detrimental forms of gambling. Previous research has established an association between EGM accessibility, expenditure, gambling harm, and the socioeconomic status (SES) of neighborhoods. However, there is limited understanding of the direct impact of SES and EGM accessibility on individual player expenditures. Prior estimations of expenditure often rely on self-reported data or venue-level revenue statistics. This study uses high spatial resolution socioeconomic data together with individual-level account-based location and expenditure (point of sales) data (71,669 players, 745 EGM venues) to explore the association between EGM accessibility and neighborhood SES and to examine whether the EGM expenditure of neighborhood residents is associated with EGM accessibility and neighborhood SES.Data and methodsPlayer account data include information on the home location and expenditure of the entire EGM gambling population across every EGM venue located in the Helsinki region, Finland. High-resolution (250 × 250 m) grid-level data on socioeconomic variables were used to obtain the local socioeconomic conditions of the players. EGM accessibility was estimated for every grid cell using a calibrated gravity model derived from the player account data. Statistical analyses included correlation analysis, spatial autocorrelation analysis, and regression models.ResultsFirst, significantly higher levels of EGM accessibility were found in areas with lower local SES. Second, regression analysis revealed that both higher EGM accessibility and lower local SES were associated with higher annual losses per adult. These results, in combination with visual and spatial autocorrelation analyses, revealed that accessibility to EGM gambling is highly concentrated, especially in lower socioeconomic neighborhoods with higher levels of EGM expenditure.ConclusionsThe results lay the groundwork for future spatial research on gambling harm, expenditure, accessibility, and SES utilizing detailed account data on the interaction between players and venues. The results underscore the importance of spatial restrictions when regulating EGM accessibility, particularly in areas with vulnerable populations, as a crucial measure for public health and harm prevention. The results also enable targeted gambling harm prevention actions at the local level.