High-income Groups Research Articles

How an increase in income affects the use of dental care services among a low-income population: evidence from the Finnish basic income experiment

BackgroundPrevious research has shown that the use of dental care services has a significant socioeconomic gradient. Lower income groups tend to use dental care services less, and they often have poorer dental health than higher income groups. The purpose of this study is to evaluate how an increase in income affects the use of dental care services among a low-income population.MethodsThe study examines the causal effect of increasing cash transfers on the use of dental care services by utilizing unique register-based data from a randomized field experiment conducted in Finland in 2017–2018. The Finnish basic income experiment introduced an exogenous increase in the income of persons who previously received basic unemployment benefits. Register-based data on the study population’s use of public and private dental care services were collected both for the treatment group (N = 2,000) and the control group (N = 173,222) of the experiment over a five-year period 2015–2019: two years before, two years during, and one year after the experiment. The experiment’s average treatment effect on the use of dental care services was estimated with OLS regressions.ResultsThe Finnish basic income experiment had no detectable effect on the overall use of dental care services. However, it decreased the probability of visiting public dental care (-2.7% points, -4.7%, p =.017) and increased the average amount of out-of-pocket spending on private care (12.1 euros, 29.8%, p =.032). The results suggest that, even in a country with a universal public dental care coverage, changes in cash transfers do affect the dental care patterns of low-income populations.

Are annuities an inferior or normal good? Evidence from a less-developed country

One crucial decision made at retirement in Chile is whether to acquire an annuity or a phased withdrawal (PW) scheme. Annuities, unlike PW, do not allow for inheritance and provide smaller initial pension benefits while protecting against longevity and capital market risks. If preferences show decreasing absolute risk aversion (DARA), then an annuity (insurance) should be considered an inferior good. We test this hypothesis on Chilean data using a binary choice model. Our results reject the DARA hypothesis for the whole sample. However, after splitting the sample into low- and high-income groups, we find that the former have increasing absolute risk aversion (IARA) behavior, whereas the latter have DARA behavior. These findings suggest that policy programs encouraging retirement savings, such as tax breaks and subsidies, should be approached with caution depending on the balance of high and low-income individuals, particularly in less-developed economies.

The Where, When, and How of Diversity: How Space, Time, and Incomes Configure the Racial-Ethnic Composition of Networks

This article investigates the relationship between income and the diversity of sociospatial networks as described by high-density mobile phone application (MPA) Global Positioning System data. Looking at the counties that contain the Atlanta, Boston, Chicago, and Los Angeles metropolitan regions in August and September 2022, this study asks the following questions: How does the racial-ethnic diversity and spatial extent of network of activity space-times—the place and time of daily activities—vary across different income levels? Given the existing literature, are more diverse networks composed of higher income classes? Are there key types of activity space-times that are more likely to be in these networks? Given that the overlap of activity spaces might lead to the formation of stronger social ties, this study aims to provide new evidence of the role of activity spaces in determining the diversity of social exposures with high-resolution spatiotemporal MPA activity. Results suggest that income is an important determinant of diversity in networks, with the highest and lowest income groups both exhibiting the least diversity in networks, whereas institutional spaces like church or school and other surprising places such as the dentist’s office are the most likely activity space-times in these networks.

Inequalities in the potential movement of social groups: A network-based indicator

Accessibility and mobility are key concerns of sustainable cities, especially in the Global South, due to the strong social inequalities. This paper contributes to the literature on mobility segregation by focusing on the potential movement of social groups in the city. We conceptualize potential movement as a network centrality, acting as an indicator of population movement when performing daily activities (working, studying, shopping, etc.). This paper’s objectives are (a) to identify the inequalities in potential movement of different social groups performing their daily activities; (b) to propose a network-based method to enhance our understanding of mobility inequalities; and (c) to address the context of medium-sized Latin American cities. We adopt a modified Betweenness Centrality model (Potential Movement) on a directed and weighted network. Our results show a similar pattern for both cities, with the CBD concentrating the potential movement for all groups; however, several inequalities were found. The high-income and white groups show higher levels of potential movement in the CBD and the low-income and non-white groups have a more distributed potential movement pattern, implying longer journeys to reach jobs and services. Income and race have shown to play a crucial role in those inequalities.

Moderate low-cost modifications in diet prevent a substantial number of deaths and mitigate environmental impacts in Brazil.

This study aimed to estimate the health, economic, and environmental impacts of moderate simulated interventions on dietary intake in Brazil. Data on food price and consumption were obtained from three nationwide surveys. Baseline dietary intake was estimated for 33,859 individuals aged 25years and older. Counterfactual intakes were based on six hypothetical intervention scenarios, by changing the weekly frequency and serving size in low or high consumers of fruit and vegetables (FV), milk, whole grains, red and processed meats, and sugar-sweetened beverages. For each scenario, we estimated the attributable number of deaths and disability-adjusted life years (DALY), monetary cost, environmental impacts (14 midpoint indicators), and environmentally-mediated health impacts. Compared with the baseline intake and cost, the most expensive intervention (+ 8.3%) was to increase FV intake (+ 125g), resulting in a 1.2% reduction in all-cause mortality (16,307 deaths/year). The cheapest (- 9.9%) was to reduce red and processed meat intake (- 40g), resulting in a 1.1% reduction in all-cause mortality (14,272 deaths/year). The combined intervention was, on average, 3.7% cheaper than the baseline cost, resulting in an increase in diet cost for 30% of the population (45-22% in the lower- and higher-income groups); all-cause mortality would be reduced by 3.8% (49,488 deaths/year). Interventions targeting red and processed meats would reduce emissions and resource use by 35-55%, in addition to reducing 2300 DALYs/year. A meaningful number of deaths can be avoided and environmental impacts reduced through moderate and potentially affordable diet modifications.

Air pollution, perceived health risk, and trip decision-making: Environmental justice considerations

This study evaluates the impacts of air pollution on trip decision-making and the determinants associated with perceived health risk from air pollution, socioeconomic status, and trip routine. To analyze its impacts based on a comprehensive mechanism, we developed a conceptual framework for trip decision-making process via perceived health risk from air pollution through an extensive literature review. We conducted a survey about trip plan changes due to poor air quality in South Korea, and used an integrated choice and latent variable model to verify the hypotheses in the framework. The result reveals that high perceived health risk encourages people to seek related information, which induces more trip plan changes under poor air quality. People with greater perceived risk tend to make more drastic trip-related decisions by changing or even canceling trip schedules. Moreover, higher-income groups generally perceive greater health risks and eventually seek relevant information more. The findings imply that the gap caused by socioeconomic status brings more frequent exposure of socially disadvantaged groups to polluted air, which can connect to environmental justice problems in society. This study provides noteworthy knowledge of the relationship between air quality and travel behavior to make healthy cities for everyone through environmental justice in transportation.

Exploring Spatio-Temporal Pattern of Gentrification Processes in Intracity Slums in the Lagos Megacity

There have been increasing calls in gentrification studies to examine the geography of gentrification in slums, as little is known about the patterns and processes of slum gentrification, especially in sub-Saharan African cities where slums house over 50% of the urban population. This study explored the spatiotemporal changes in slums in Lagos, Nigeria, between 1984 and 20 on the pattern and drivers of gentrification. Data were collected from 42 slums in Lagos through remote sensing (1984–2020) and a field survey (2020–2021). The study integrated geospatial analysis with quantitative and qualitative analysis to investigate the patterns and drivers of gentrification in Lagos slums. The findings show that between 1984 and 2020, all the sampled slums had undergone gentrification processes, apart from those that were completely cleared. However, many slums continue to have deprived areas as they continue to gentrify. Almost all the slum communities have experienced slum clearance in the past. Additionally, the current and new housing developments in the study have favored middle- to high-income groups, which has led to the displacement of previous slum residents. The study identified slum clearance, fires and floodings, the presence of palaces in the community, the proportion of deprived areas in 1984, government interest in the slum, and the size of the church as drivers of slum gentrification processes in Lagos. Finally, the findings show that the vulnerability of slum dwellers increases with slum gentrification. Therefore, this study recommended developing policies and programs, such as sustainable relocation and low-cost housing, to mitigate the negative consequences of slum gentrification, especially in cities with significant shares of low-income groups.

Do Economic Complexity Drivers Differ by Income Level? Insights From a Global Perspective

This study examines the drivers of economic complexity for 97 countries over the period 1995 to 2020 by income sub-groups. To investigate determinants of complexity, we develop five novel indexes. Using two-step system GMM (2SGMM) regression with the robust standard errors method, we found that institutional quality, health dimensions and macroeconomic conditions were enormously significant economic complexity drivers. However, the findings vary according to the country groups with different income levels. While the importance of openness and health dimensions are prominent in low and middle-income countries, capital stock and openness are the principal elements in the high-income group. The institutional quality is statistically significant and considerably affects on complexity in each group and across the panel. The education dimension of human capital has a positive effect only in the high-income group and across the panel, while it is negative in the middle and low-income groups, but its effect is weak. Moreover, these findings are valid in the long run. From a policy perspective, the findings suggest that macroeconomic policies focused on institutional quality, openness and healthcare as critical components of economic complexity should be crucial goals, especially for low and middle-income countries. JEL Classification: O11, O43, I15, I25.

Analisis dan Rekomendasi Character Pada Game Genshin Impact Berdasarkan Revenue Banner Menggunakan Algoritma Clustering

In the era of video game industry development, optimizing monetization within games has become a primary concern for developers. Analyzing revenue data from banner characters and categorizing characters are relevant steps, especially for players who are new to the game. This involves providing character recommendations based on the income generated from game banners. The main issue faced by players is the difficulty in choosing the right banner characters to invest in, considering that each banner features different characters with varying appearance statistics. Additionally, players need guidance in identifying characters with the most potential to enhance their performance. The approach employed in this research involves using Clustering Algorithms to group characters based on factors relevant to banner income, including character popularity, availability in banners, and their unique abilities. Detailed transaction data analysis in the game is conducted using K-Means Clustering and Hierarchical Clustering algorithms to generate character groups. The research results demonstrate that employing clustering algorithms produces character groups that provide insights for players to consider allocating their resources to characters categorized in high-income or low-income groups. By using character recommendations based on these groups, players can be guided to select characters that align with their preferences and gameplay styles.

Changes in the Socioeconomic Pattern of Smoking Among Male Adults in Thailand from 2001 to 2021

The smoking rate in Thailand has been steadily decreasing for decades alongside the government’s tobacco control policies. However, evidence of whether the decrease to date has occurred equally across all population groups is scarce. Therefore, this study aimed to examine the changes in the socioeconomic patterns of smoking among male adults in Thailand from 2001 to 2021. This study employed a pooled cross-sectional design with 296,011 male adults aged 15 years or older from the Health and Welfare Survey 2001 ( n = 74,003), 2003 ( n = 14,940), 2006 ( n = 25,088), 2009 ( n = 26,370), 2013 ( n = 26,919), 2015 ( n = 52,904), and 2021 ( n = 75,787). Descriptive analysis and binary logistic regression were used. The results indicated that the smoking rate decreased by approximately 25% from 46.81% in 2001 to 35.01% in 2021. This decrease was significantly greater in high- and low-level socioeconomic groups than in mid-level groups. Specifically, high- and low-income, high- and low-educated, older, married and divorced, employed, and urban and rural people exhibited larger decreases in smoking rates than middle-income, middle-educated, middle-aged and younger, single, unemployed, and Bangkok metropolitan people, respectively. Additionally, the smoking rates of low-income groups decreased as cigarette retail prices increased, whereas those of high-income groups decreased regardless of tobacco control policies. The government’s price policy and health awareness may have significantly influenced the decrease in smoking rates of the low- and high-level socioeconomic groups, respectively. Therefore, the government should continue its price policy and public relations practices to further decrease smoking rates.

유기인증 신뢰성이 유기가공식품 소비에 미치는 영향

This study examines the impact of consumer trust in organic certification on organic processed food consumption. Propensity score matching is utilized to analyze the impact of organic certification credibility on expanding organic processed food consumption. Results show that the credibility of organic certification has a positive effect on the expansion of organic processed food consumption. When comparing before and after the outbreak of the COVID-19 pandemic, the credibility of organic certification led to a greater increase in organic processed food consumption before the outbreak of the pandemic. As a result of analyzing the effect of the credibility of organic certification by age on the expansion of organic processed food consumption, the effect of credibility on the expansion of consumption in the young generation is greater than the effect in the middle-aged. In addition, the effect of credibility on the expansion of consumption is more significant for higher-income groups. Through the results, we provide evidence for establishing related policies and marketing strategies to expand the market for certified organic agricultural products.

A comparative analysis of distracted driving behavior among drivers of different income levels: A case study in huainan, China

This research aims to investigate the differences and causes behind distracted driving behavior among drivers with varying income levels. A comparative survey of 1121 drivers in Huainan City, China, was conducted, including 562 drivers from high-end communities representing the high-income group, and 559 drivers from general communities representing the low-income group. Employing social norms, risk perception, and experience as independent variables, the study further examines the role of in-group bias as a mediating variable, with distracted driving behavior serving as the dependent variable, through the construction of two structural equation models for analysis. The study found that among the high-income driver group, in-group bias significantly mediates the impact of social norms, risk perception, and experience on distracted driving behavior; however, this mediating effect is less pronounced in the low-income driver group. This finding is crucial for understanding the potential distracted driving behaviors induced by in-group bias within the high-income driver group and for effectively promoting driving safety. In summary, this research provides new insights into reducing distracted driving behavior among the high-income driver group, thereby enhancing road safety.

Behavior-encoded models reveal differentiated access to public cooling environment by race and income

Extreme heat events caused by continuous anthropogenic climate change have been increasing. Establishing public cooling environments (PCEs) is imperative for protecting public health and enhancing productivity. Yet, disparities in access to PCEs based on race, travel behavior, and income status can undermine their role in helping communities cope with extreme heat. This study investigates the varied access to three types of PCEs across 40 U.S. counties. Our findings reveal that White people enjoy greater access to PCEs than other groups, especially to tree-covered green spaces (TCGSs), outperforming Black people approximately three times. Driving can disproportionately narrow the racial/ethnic inequality gap compared to walking. Non-expense-required public environments (NERPEs) and expense-required public environments (ERPEs) are less accessible to high-income groups. Our research underscores the ongoing challenges in achieving environmental justice through equitable PCE access and stresses the importance of further studies and policy actions to eliminate disparities.

Exploring the association between social determinants and aphasia impairment: A retrospective data integration approach.

Traditionally, the study of aphasia focused on brain trauma, clinical biomarkers, and cognitive processes, rarely considering the social determinants of health. This study evaluates the relationship between aphasia impairment and demographic, socioeconomic, and contextual determinants among people with aphasia (PWA). PWA indexed within AphasiaBank-a database populated by multiple clinical aphasiology centers with standardized protocols characterizing language, neuropsychological functioning, and demographic information-were matched with respondents in the Medical Expenditure Panel Survey based on response year, age, sex, race, ethnicity, time post stroke, and mental health status. Generalized log-linear regression models with bootstrapped standard errors evaluated the association between scores on the Western Aphasia Battery-Revised Aphasia Quotient (WAB-R AQ) and demographic, economic, and contextual characteristics accounting for clustering of respondents and the stratification of data collection. Region, age, and income specific models tested the sensitivity of results. PWA over age 60 had 2.4% (SE = 0.020) lower WAB-R AQ scores compared with younger PWA. Compared to White PWA, Black and Hispanic PWA had 4.7% (SE = 0.03) and 0.81% (SE = 0.06) lower WAB-R AQ scores, respectively, as did those and living in the Southern US (-2.2%, SE = 0.03) even after controlling for age, family size, and aphasia type. Those living in larger families (β = 0.005, SE = 0.008), with income over $30,000 (β = 0.017, SE = 0.022), and a college degree (β = 0.030, SE = 0.035) had higher WAB-R AQ relative to their counterparts. Region-specific models showed that racial differences were only significant in the South and Midwest, while ethnic differences are only significant in the West. Sex differences only appeared in age-specific models. Racial and ethnic differences were not significant in the high-income group regression. These findings support evidence that circumstances in which individuals live, work, and age are significantly associated with their health outcomes including aphasia impairment.

The impact of digital inclusive finance on rural income growth in China: evidence from quantile regression approach

ABSTRACT Based on a panel data set from 2013 to 2021 of Chinese provinces and regions, this research aims to reveal the impact of digital inclusive finance on rural disposable income in China. The linear regression approach with Driscoll-Kraay standard errors and the quantile regression approach are applied in this research. Both approaches show that digital inclusive finance significantly impacts China’s rural income growth. The regression results of China’s east, middle and west area separately imply that the impact of digital inclusive finance in on rural disposable income is higher in the east area and middle area than that in the west area. The quantile regression results show that the impact in the higher quantile is larger than in the lower quantile, which indicates rural high-income groups get more benefits from digital inclusive finance than rural low-income groups. Moreover, this research finds that the development of e-commerce contributes significantly to rural disposable income growth. The empirical results of this research indicate that the establishment of digital inclusive finance in the west backward area still need to be improved to increase the access of digital inclusive finance for rural low-income groups.

Factors associated with depressive symptoms among returnee migrants and non-migrants working adults in Madi municipality in Nepal: a community-based cross-sectional study

BackgroundMental health is a growing concern worldwide. It is not well understood whether international labour migrants from Nepal who return to Nepal are at higher risk of developing mental health problems. The purpose of our study was to determine the prevalence of and examine the associated factors for depressive symptoms among returnee migrants and non-migrant working male adults in Nepal.MethodsA cross-sectional survey of a probability-based sample of 725 participants was conducted in February 2020. The sample was comprised of two groups based on migration status: returning migrants and non-migrants. The 21-item Beck Depression Inventory (BDI-21) questionnaire was used to assess depressive symptoms. Logistic regression was applied to investigate factors associated with symptoms of depression.ResultsThe overall prevalence of depressive symptoms was 10.1%. However, the prevalence of depressive symptoms was lower (7%) among returnee migrants compared to non-migrants (13.7%). Men in the lower income group had a higher chance of having depressive (AOR = 5.88, 95% CI: 2.17–15.96) than those in the higher income group. Similarly, Buddhists and Christians were more likely to be depressed (AOR = 2.20, 95% CI: 1.03–4.68) than Hindus. Participants with more than two children had a higher chance of having of depressive symptoms (AOR = 4.80, 95% CI: 1.15–20.05) compared with those without children. Unmarried men were more likely to be depressed (AOR = 4.07, 95%, CI:1.11–14.92) than those who were married.ConclusionThe working Nepali adult male population in Nepal, including returning migrants, is at risk of depressive symptoms, but this association was lower in those in the higher income group, returnee migrants, those who were married, Hindus and those with no children. Our results highlight the need to monitor and develop national policies to ensure the mental health of the Nepali male adult population, including returnee migrants.

Network dynamics of solar PV adoption: Reconsidering flat tax-credits and influencer seeding for inclusive renewable energy access in Albany county, New York

Governments often use price-based policies such as tax-subsidies and rebates to encourage households to shift to renewable energy sources like rooftop solar photovoltaics (PV). These policies, however, have primarily benefited high-income homeowners, leaving others behind. This paper proposes leveraging social networks’ influence on attitudes and perceptions to design more equitable solar PV adoption programs. Using data from Albany county (New York State, USA) we develop an Agent-based model, integrating a novel implementation of circles of influence into the theory of planned behavior. We test two policy categories (generic and targeted) under two network scenarios (integrated and segregated). Resulting solar PV adoption rates are evaluated using egalitarian, utilitarian and cost metrics to analyze policy impact on different income groups. Our findings indicate that network structure significantly influences adoption rates within income groups. Low-income groups in segregated networks can experience higher adoption driven by positive attitudes towards solar PV, while high-income groups in segregated networks may face poor policy performance despite higher affordability. Seeding policies and information dissemination through influential network members may not necessarily improve adoption rates, as trust can a more important role. The study underscores the importance of trusted information sources in influencing adoption decisions. The insights gained from this research can guide policy design for tailored interventions to improve access to renewable energy for all income groups.

From test to rest: evaluating socioeconomic differences along the COVID-19 care pathway in the Netherlands

IntroductionThe COVID-19 pandemic exacerbated healthcare needs and caused excess mortality, especially among lower socioeconomic groups. This study describes the emergence of socioeconomic differences along the COVID-19 pathway of testing, healthcare use and mortality in the Netherlands.MethodologyThis retrospective observational Dutch population-based study combined individual-level registry data from June 2020 to December 2020 on personal socioeconomic characteristics, COVID-19 administered tests, test results, general practitioner (GP) consultations, hospital admissions, Intensive Care Unit (ICU) admissions and mortality. For each outcome measure, relative differences between income groups were estimated using log-link binomial regression models. Furthermore, regression models explained socioeconomic differences in COVID-19 mortality by differences in ICU/hospital admissions, test administration and test results.ResultsAmong the Dutch population, the lowest income group had a lower test probability (RR = 0.61) and lower risk of testing positive (RR = 0.77) compared to the highest income group. However, among individuals with at least one administered COVID-19 test, the lowest income group had a higher risk of testing positive (RR = 1.40). The likelihood of hospital admissions and ICU admissions were higher for low income groups (RR = 2.11 and RR = 2.46, respectively). The lowest income group had an almost four times higher risk of dying from COVID-19 (RR = 3.85), which could partly be explained by a higher risk of hospitalization and ICU admission, rather than differences in test administration or result.DiscussionOur findings indicated that socioeconomic differences became more pronounced at each step of the care pathway, culminating to a large gap in mortality. This underlines the need for enhancing social security and well-being policies and incorporation of health equity in pandemic preparedness plans.

Examining the magnitude and causes of variation in electricity use in a sample of Indian dwellings with and without air conditioning

ABSTRACT Understanding the factors that drive the use of residential electricity in India is essential for designing policies that can reduce its expected growth. This study empirically examines the magnitude and causes of variation in electricity use in a sample of Indian dwellings with and without air conditioning (AC), using an interview-based survey approach applied in 41 dwellings located across two cities representing the composite climate of India. Statistical analysis was used to unpack the relationship between electricity use and socio-technical factors. Despite the small sample size and having the same climatological realm, there was a wide variation observed in electricity use by income groups and the presence of ACs. The mean annual residential electricity consumption (REC) was observed to be highest in high-income group dwellings (5,618 kWh/year), followed by middle-income group dwellings (3,870 kWh/year) and lowest in low-income group dwellings (2,169 kWh/year). The mean REC of AC dwellings (4,208 kWh/year) was found to be nearly double that of non-AC dwellings (2,260 kWh/year) with significant seasonal variation. Multivariate regression analysis revealed that the presence of ACs, household size (number of occupants), annual non-AC appliance hours, dwelling size (number of rooms) and income group accounted for 80% of the variability in REC across the study sample. Residential energy policy in India should consider these key factors that drive REC. To be effective, such policy programmes need to be customised for different income groups, adopting incentives as well as energy awareness campaigns to influence both purchasing and habitual behaviours.

Health burden from food systems is highly unequal across income groups.

Food consumption contributes to the degradation of air quality in regions where food is produced, creating a contrast between the health burden caused by a specific population through its food consumption and that faced by this same population as a consequence of food production activities. Here we explore this inequality within China's food system by linking air-pollution-related health burden from production to consumption, at high levels of spatial and sectorial granularity. We find that low-income groups bear a 70% higher air-pollution-related health burden from food production than from food consumption, while high-income groups benefit from a 29% lower health burden relative to their food consumption. This discrepancy largely stems from a concentration of low-income residents in food production areas, exposed to higher emissions from agriculture. Comprehensive interventions targeting both production and consumption sides can effectively reduce health damages and concurrently mitigate associated inequalities, while singular interventions exhibit limited efficacy.