Socioeconomic Distribution Research Articles

Sleep state of the elderly population in Korea: Nationwide cross-sectional population-based study.

Interest in sleep disorders among the elderly, especially those in Korea, has increased. We aimed to describe the overall sleep status of the elderly population in Korea using survey data and to determine the risk factors concerning different aspects of sleep status. We conducted a cross-sectional survey on 271 respondents aged 65-86 years old. We performed multistage clustered random sampling according to the population and socioeconomic distribution of all Korean territories. The survey questionnaire was used to perform a structural assessment of sociodemographic characteristics; medical comorbidities; psychiatric comorbidities; and sleep status, including sleep duration, sleep quality, presence of insomnia, excessive daytime sleepiness, sleep apnea, and restless legs syndrome. Approximately 12.5, 22.%, and 51.3% of the elderly population had poor sleep quality, excessive daytime sleepiness, and insomnia, respectively. Hypertension, dyslipidemia, insomnia, anxiety, and depression predicted poor sleep quality. Female sex, insomnia, and sleep apnea predicted excessive daytime sleepiness. Poor sleep quality and depression predicted insomnia. A substantial proportion of the elderly Korean population have sleep problems, including poor sleep quality, excessive daytime sleepiness, and insomnia. Sleep status is influenced by various factors, including age, sex, and metabolic and psychiatric comorbidities.

Local indicators of climate change impacts described by indigenous peoples and local communities: Study protocol.

In the quest to improve the understanding of climate change impacts on elements of the atmospheric, physical, and life systems, scientists are challenged by the scarcity and uneven distribution of grounded data. Through their long history of interaction with the environment, Indigenous Peoples and local communities have developed complex knowledge systems that allow them to detect impacts of climate change in the local environment. The study protocol presented here is designed 1) to inventory climate change impacts on the atmospheric, physical, and life systems based on local knowledge and 2) to test hypotheses on the global spatial, socioeconomic, and demographic distribution of reported impacts. The protocol has been developed within the framework of a project aiming to bring insights from Indigenous and local knowledge systems to climate research (https://licci.eu). Data collection uses a mixed-method approach and relies on the collaboration of a team of 50 trained partners working in sites where people's livelihood directly depend on nature. The data collection protocol consists of two steps. Step 1 includes the collection of secondary data (e.g., spatial and meteorological data) and site contextual information (e.g., village infrastructure, services). Step 1 also includes the use of 1) semi-structured interviews (n = 20-30/site) to document observations of environmental change and their drivers and 2) focus group discussions to identify consensus in the information gathered. Step 2 consist in the application of a household (n from 75 to 125) and individual survey (n from 125 to 175) using a standardized but locally adapted instrument. The survey includes information on 1) individual and household socio-demographic characteristics, 2) direct dependence on nature, 3) household's vulnerability, and 4) individual perceptions of climate change impacts. Survey data are entered in a specifically designed database. This protocol allows the systematic documentation and analysis of the patterned distribution of local indicators of climate change impacts across climate types and livelihood activities. Data collected with this protocol helps fill important gaps on local climate change impacts research and can provide tangible outcomes for local people who will be able to better reflect on how climate change impacts them.

Evaluating the Socioeconomic Factors and Distribution Challenges in Retail Dried Catfish Marketing: A Case Study of Akure South Local Government Area, Ondo State, Nigeria

This study examined the factors affecting Dried Catfish marketing in Akure South Local Government Area of Ondo State, Nigeria using Primary data. The data were sourced using a well-structured questionnaire. A multistage sampling technique was employed to randomly select 90 respondents at the final stage in the study area. The data were analyzed using descriptive statistics, gross margin, and regression analyses. The results showed that female dominated the enterprise with 100% and (83.3%) of the married respondents shows that they are still in their active and productive age. The result of the gross margin analysis shows that Catfish marketing was a profitable venture given the value of gross margin to be ₦6, 047,500 per trip. The regression analysis reveals that age, educational level and years of experience were statistically significantly for Catfish marketers in the study area. It is therefore recommended that government should assist dried Catfish marketers by making available low interest credit facilities so that marketers can have access to finance to boost their business. In lieu of external support, Catfish marketers can explore new markets and distribution channels to broaden the reach of retailed-dried catfish products, and also get involved in developing new flavors, packaging options, or introducing value-added catfish products to attract a wider consumer base.

Stroke in women between 2006 and 2018: Demographic, socioeconomic, and age disparities.

Black Americans have a higher prevalence of stroke and stroke-related deaths than any other racial group. Racial disparities in stroke outcomes are even wider among women than men. Conventional studies have cited differences in lifestyle (i.e. smoking, alcohol consumption, etc.) and vascular risk factors between races as the source of these disparities. However, these studies fail to account for the higher prevalence of minoritized populations at the lower end of the socioeconomic distribution. This study explores differences in stroke risk factors across age and socioeconomic cohorts to determine whether comorbidities can sufficiently explain disparities at all ages and income levels. Using the 2006-2018 National Health Interview Survey data, statistical analysis evaluated differences in risk factors among a full sample cohort (aged 18-85 years; n = 131,091) and a "young" subsample cohort (aged 18-59 years; n = 6183) of women. Logistics and unconditional quantile regression models assessed the relationship between stroke and comorbid, demographic, and behavioral characteristics across socioeconomic classes. Results suggest that Black women had a 1.415-fold (confidence interval = 1.259, 1.591) higher likelihood of stroke compared with White women after controlling for age, behavior, and comorbidities. Racial disparities were not statistically significant at the higher income ranges for either the full (odds ratio = 1.404, p = 0.3114) or young samples (odds ratio = 1.576, p = 0.7718). However, Blacks had significantly higher odds of stroke in the lower quartiles (lower odds ratio: 1.329, p = 0.0242; lower middle odds ratio: 1.233, p = 0.0486; and upper middle odds ratio: 1.994, p = 0.0005). Disparities were larger among young women (odds ratio = 1.449, confidence interval = 1.211, 1.734). While comorbidities were highly associated with stroke prevalence in all socioeconomic cohorts, Blacks only had higher relative odds in the lower income classes. Lack of biological or behavioral explanations for these findings suggests that unobserved or uncontrolled factors such as systemic racism, prejudicial institutions, or differential treatment may contribute to this.

Abstract A054: Disparities in the availability of neuro-oncology clinical providers and infrastructure in the United States

Abstract BACKGROUND: Barriers to clinical trial access have significant implications for patient care. Motivated by previous work which identified geographical and socioeconomic disparities in neuro-oncology trials’ accessibility in the United States (US), we assessed the role of these factors on the availability of neuro-oncology providers and member institutions of trial collaboratives and community outreach programs. METHODS: US Census data on population and geography and the Neighborhood Atlas’ Area Deprivation Index (ADI) were obtained. Data on UCNS-certified neuro-oncology subspecialists, NRG Oncology Main Member institutions, and NCI Community Oncology Research Program (NCORP) sites were obtained and mapped to 5-digit zip code tabulation areas (ZCTAs) using Google Geocode. Linear and logistic regression and spatial analyses were conducted in R using the spdep and spatialreg libraries, to assess the role of geography, disadvantage, and population on infrastructure accessibility. RESULTS: We identified 316 neuro-oncologists, 130 NRG institutions, and 963 NCORP sites, in 0.6%, 0.4%, and 2.2% of all ZCTAs in the US (N = 33120), respectively. Neuro-oncologists and NRG institutions were more likely to exist in more populated (OR=1.86, p<0.001; OR=1.80, p<0.001) and less-disadvantaged (OR=0.98, p<0.001; OR=0.98, p<0.001) regions, reflecting urban-rural and socioeconomic disparities. Moreover, neuro-oncologists were more likely to exist in geographically adjacent regions (OR=320.594, p<0.001), while NRG institutions were geographically more broadly distributed (OR=1.49, p=0.859). Where existent, a greater number of neuro-oncologists served less-disadvantaged regions (β=-0.014, p=0.021), while the number of NRG institutions was more equitably distributed overall (Moran’s I data=0.002, p=0.394; Moran’s I residuals=0.002, p=0.489; population: β=0.004, p=0.778; ADI: β=-0.0001, p=0.919). On the other hand, NCORP sites were more likely to exist in areas of greater disadvantage (OR=1.01, p=0.001), reflecting the NCORP mission to reach more diverse communities. However, NCORP sites were more likely to exist and were more prevalent among more populated (OR=2.79, p<0.001; β=0.076, p=0.007) and geographically adjacent regions (OR=8.23, p<0.001; ρ=0.120, p<0.001), reflecting urban-rural disparities. CONCLUSION: The identified disparities in availability of neuro-oncologists and institutions capable of hosting clinical trials may explain the previously reported disparities in trial sites. Disparities in neuro-oncologist availability suggest the need for neuro-oncology specific measures involving telehealth and local oncologists. The more equitable geographic and socioeconomic distribution of NRG institutions, and the more equitable socioeconomic distribution of NCORP sites reaffirm the importance of the mission and ability of such initiatives to bridge geographic and socioeconomic barriers. Finally, the existence of disparities across all infrastructure levels raises the concern that these disparities reflect broader disparities in access to neuro-oncology care. Citation Format: Yeonju Kim, Terri S. Armstrong, Mark R. Gilbert, Orieta Celiku. Disparities in the availability of neuro-oncology clinical providers and infrastructure in the United States [abstract]. In: Proceedings of the 15th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2022 Sep 16-19; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr A054.

Analytical evidence of social epidemiology in sociobiological context – A narrative review

Social epidemiology is a relatively newer field of epidemiology that evaluates the socioeconomic distribution and determinants of health and disease and how those factors affect the health of individuals and populations. The explanation of the causal relationships between socioeconomic circumstances, health status, and consequences is a key challenge in social epidemiology. The current study was conducted to analyze the key substantive areas of focus in epidemiology in the sociobiological context. Data were collected electronically using databases such as PubMed, ScienceDirect, Scopus, Google Scholar, and three authorized textbooks to conduct relevant searches. Since the beginning of the history of public health, the relationship between socioeconomic class and health has been a significant study area. The impact which social factors have on both individual and population health is the central and initial question that needs to be addressed in social epidemiology. The recent attention given to this issue using modern epidemiological techniques is a relatively new phenomenon. Social epidemiology’s primary goal is to produce fundamental knowledge. Social epidemiology must be necessarily multimethod, interdisciplinary, and broad due to its subject of research.

Cost-Effectiveness and Distributional Impact of Opportunistic Screening for People at High-Risk of Cardiovascular Disease in Sri Lanka: A Modelling Study.

While hypertension, diabetes, hypercholesterolemia and high-risk of cardiovascular disease can be easily diagnosed and treated with cost-effective medicines, a large proportion of people remain undiagnosed. We assessed the potential effectiveness, cost, and distributional impact of opportunistically screening for these chronic conditions at outpatient patient departments in Sri Lanka. We used nationally representative data on biomarkers and healthcare utilization in 2019 to model the screening of people aged 40+ without preexisting CVD and without a reported diagnosis of hypertension, diabetes, or hypercholesterolemia. We modelled an intensive one month program that would screen a proportion of those making an outpatient visit to a public or private clinic and follow-up a proportion of those screened to confirm diagnoses. We also modelled a less intensive one year program. The main outcomes were the new diagnoses of any of the chronic conditions. Program costs were calculated and the socioeconomic distributions of individuals screened, new cases diagnosed, and treatments delivered were estimated. Sensitivity analyses varied the probability of screening and follow-up. Using data on 2,380 survey participants who met the inclusion criteria, we estimated that the one month program would diagnose 8.2% (95% CI: 6.8, 9.6) of those with a chronic condition who would remain undiagnosed without the program. The one year program would diagnose 26.9% (95% CI: 26.5, 27.4) of the otherwise undiagnosed and would have a cost per person newly diagnosed of USD 6.82 (95% CI: 6.61, 7.03) in the public sector and USD 16.92 (95% CI: 16.37, 17.47) in the private sector. New diagnoses would be evenly distributed over the socioeconomic distribution, with public (private) clinics diagnosing a higher proportion of poorer (richer) individuals. Both programs would reduce underdiagnosis among males relative to females. Opportunistic screening for cardiovascular diseases at outpatient clinics in Sri Lanka could be cost-effective and equitable.

Surgical Management of Lutembacher’s Syndrome in Congestive Cardiac Failure: A Case Report & Review of Literature

Introduction: Lutembacher’s syndrome is a rare clinical entity. In 1916, French physician Rene Lutembacher described his first case of 61 years old woman with a combination of congenital ASD with acquired MS. But he attributed this mitral lesion to congenital mitral stenosis. The definition of this syndrome named after him has undergone many changes since then. The current consensus defines Lutembacher Syndrome (LS) as any combination of ASD (congenital or iatrogenic) and MS (congenital or acquired). The clinical presentation of LS is a result of the interplay between the size of ASD, the severity of MS, pulmonary vascular resistance and RV compliance. Financial constraints also add to the delayed diagnosis and adequate treatment in our part of the world. Here we have discussed a case of LS with severe TR and moderate PAH in congestive cardiac failure which was successfully treated by surgery thereby demonstrating cost-effective and successful surgical management of a rare cardiac disease where vascular resistance, compliance, size and severity of lesions interplay causing cardiac failure. Case report: A 42 years old thin built, poorly nourished housewife presented with chest discomfort and fatigue for the last 4 years. She was diagnosed with an atrial septal defect four years back but could not receive appropriate treatment due to financial constraints. For the last 15 days, she had breathlessness even at rest and paroxysmal episodes that interrupted her sleep. Icterus and pedal edema was also present. As we evaluated the patient, her clinical examination could not be entirely explained by ASD alone. Soon, our suspicion of LS was confirmed by TTE and the diagnosis of Lutembacher Syndrome with Severe Tricuspid Regurgitation with Moderate PAH was made. As the patient presented to us with atrial fibrillation & heart failure, she was admitted for optimization. The patient was then successfully managed by MVR [#27 SJM, metallic] with pericardial patch closure of ASD with Devaga’s Tricuspid Valve annuloplasty and discharged on a postop day 11. Conclusions: Early diagnosis and surgical treatment bear a good prognosis and prolong survival. If a patient is diagnosed late, pulmonary hypertension and heart failure set in and the outcome becomes poor. The higher cost of surgical intervention and low socio-economic distribution of the disease in developing countries like India should not challenge the patient’s right to receive the standard treatment.

The importance of wage loss in the financial burden of illness: Longitudinal evidence from India

BackgroundA key aim of Universal Health Coverage (UHC) is to protect individuals and households against the financial risk of illness, and large-scale health insurance expansions are a central focus of the UHC agenda. Importantly, however, health insurance does not protect against a key dimension of financial risk associated with illness: forgone wage income. In this paper, we quantify the economic burden of illness in India attributable – separately – to wage loss and to medical care spending, as well as differences in them across the socio-economic distribution. MethodsWe use data from two longitudinal Indian household surveys: (i) the Village Dynamics in South Asia (VDSA) survey (1300 households surveyed every month for 60 months between 2010 and 2015) and (ii) the Indian Human Development Survey (IHDS) (more than 40,000 households surveyed in 2005 and again in 2011). Our regression models include a series of fixed effects that account for time-invariant household- (or individual-) level and time-varying unobservables common across households. FindingsWe find that, in the VDSA sample, wage loss accounts for more than 80% of the total economic burden of illness among the poorest households, but only about 20% of the economic burden of illness among the most affluent. Estimates from the IHDS sample confirm that this socio-economic gradient is present in the Indian population generally. ConclusionsWage loss accounts for a substantial share of the total economic burden of illness in India – and disproportionately so among the poorest households. Our findings imply that if UHC is to achieve its objective of protecting households against the financial risk of illness – particularly poor households, the inclusion of wage loss insurance or another illness-related income replacement benefit is needed.

The short term adaptation of the autonomic nervous systems (ANS) by type of urban environment and ethnicity

BackgroundPrevious studies examined the effects of urban environments on the Autonomic Nervous System (ANS). These studies measured the effects of environments on Heart Rate Variability (HRV) averaging different time intervals to one value. Yet, the dynamics of change, reflecting the functions and their derivatives that describe the adaptation to the new environments remain unknown. In addition, ethnic differences in the ANS adaptation were not investigated.Method: Forty-eight Arab and 24 Jewish women ages 20–35 years, all healthy, non-smokers were recruited by a snowball sample. Both groups were of a similar socioeconomic status and BMI distributions. Using a portable monitor, the HRV response was continuously analyzed for 35 min of sedentary sitting in each of the three environments: a park, a city center and a residential area. LF/HF polynomial function was adapted to describe the dynamic change in each environment for each ethnic group. ResultsGreen area exposure was associated with 90% immediate change while in built-up areas, the change in HRV is about 40% adaptive (changing gradually). The adaptive process of HRV may stabilize after 15 min in the city center yet not even after 35 min in the residential environment. The total change (immediate + adaptive) reached 24% in city centers and 10% in residential areas. Changes in HRV rates in the park and the city center environments were higher among Arab women as compared to Jewish women but similar between the two groups in the residential area. The distributions of LF/HF in each time cohort were normal, meaning that shifting the focus to analyze functions of change in HRV, opens the possibility to employ analytic methods that assume the normal distribution. ConclusionsChanging the focus from average levels of HRV to functions of change and their derivatives brings new insight into the understanding of the ANS response to environmental challenges. ANS short term adaptation to different environments is gradual and spans differently both in magnitude of response and latencies between different environments. Importantly, in green areas, the response is immediate unlike the adaptation to urban environments that is significantly more gradual. The ethnic differences in ANS adaptation is also noteworthy. In addition, adaptation proceeesses are normaly distributed in each time cohort suggesting a possible novel ANS index.

Effect of Social Vulnerability on Taxi Trip Times during Hurricane Sandy

The increase in the availability of GPS-based movement data has enabled the exploration of mobility patterns in urban transportation networks. Understanding the relationship between social vulnerability and transportation flows from big data during natural disasters is crucial for utilities and policymakers for decision-making purposes, such as evacuation and restoration planning. In this study, we explore the geographic variation of changes in trip times of taxi trips in New York City (NYC) before and after Hurricane Sandy (2012) using GPS trajectory data in relation to the underlying socio-economic distribution of impacted populations using localized regression technique with GWR. The findings reveal how the spatial patterns of trip change times with respect to SVI, income levels and population density in NYC.

Which combinations of health behaviours are associated with highest risk? An exploration of the UK Biobank population cohort

BackgroundCombinations of unhealthy behaviours are associated with greater mortality than single behaviours, but some combinations might have stronger associations than others. High-risk combinations might be more prevalent among socioeconomically deprived populations. We examined associations between combinations of 11 unhealthy behaviours and mortality and explored socioeconomic distributions of high-risk combinations. MethodsWe used the UK Biobank population cohort (n=502 459; aged 37–73 years) recruited between 2006 and 2010. Analysis included 229 197 participants with complete data. Main exposures were any combination of smoking, alcohol, physical activity, television time, sleep, added salt, social isolation, intake of red meat, processed meat, oily fish, and fruit and vegetables (each classified as healthy or unhealthy via guidelines or latest evidence). Townsend index was used to explore socioeconomic distribution. Cox proportional hazard models were used to examine associations between behaviours and all-cause mortality. Models were adjusted for demographic, health, and socioeconomic factors. FindingsOver a median follow-up of 11·6 years, 9739 (4·2%) of 229 197 participants died. From 716 unique combinations, 77 (11%) were associated with mortality with hazard ratios (HRs) greater than that for smoking alone (2·31 [95% CI 2·11–2·53]); HRs ranged from 9·44 to 2·34. Of these 77 high-risk combinations, smoking featured in 61 (79%), low fruit and vegetables in 45 (58%), and low oily fish in 41 (53%). All combinations featuring social isolation (18 [23%] of 77) had HRs greater than 3·00. Participants with high-risk combinations had greater deprivation scores than those with no unhealthy behaviours. Median deprivation scores of the ten highest risk combinations ranged from –2·0 to 2·1, whereas for participants with no unhealthy behaviours the score was –2·5. Examining women and men separately resulted in similar findings. Examination of ethnic differences was severely limited by small numbers of participants in minority ethnic groups. InterpretationMany unique unhealthy behaviour combinations are strongly associated with mortality and high-risk combinations are more prevalent among more deprived populations than among more affluent populations. Exploring unique combinations of a wide range of health behaviours can identify high-risk populations. Future work with adequately sampled minority ethnic groups is required to examine high-risk combinations by ethnicity. Supporting healthy living in deprived populations, including tackling structural barriers to health, could address a wide range of health behaviours in combination. FundingUK Medical Research Council.

CONSUMPTION PATTERNS OF TOBACCO AND INTOXICANTS IN INDIA

Tobacco smoking and binge alcohol drinking are two of the leading risk factors for premature mortality worldwide. In India, studies have examined the geographic distributions of tobacco smoking and alcohol drinking only at the state-level; sub-state variations and the spatial association between the two consumptions are poorly understood. We analyze the consumption patterns, socio-economic distribution and the household choice of a variety of harmful tobacco and alcohol products across India.

Empirical Exploration of Involvement in Philanthropic Organizations: Focusing on Perceptions of Welfare and Social Fairness1)

This study aims to examine the influence of citizens' perceptions of welfare and social fairness on philanthropic behaviors utilizing the responses of 8,077 individuals from the Social Integration Survey 2021. As a result of the ordered logistic regression analysis, it was found that perceived importance of distribution and willingness to pay additional taxes had a significant positive effect on involvement in philanthropic organizations, while, civic responsibility to help people in need had a significant negative effect on involvement in philanthropic organizations. In addition, it was found that perceived fairness of socioeconomic distribution structure had
 a significant positive effect, while, perceived fairness of health and medical benefits had a significant negative effect on involvement in philanthropic organizations. This study examined the influence on philanthropic behaviors from various point of views by addressing individual's perceptions of welfare and society. In particular, this study is meaningful as it deepens understanding of individual philanthropic behavior by considering, both of influence, on the perceptions of the subject of welfare (expenses), and how fair major sectors of the society such as education, employment, and distribution structure.

The Relationship between School Socioeconomic Composition and Academic Achievement in Turkiye

The socioeconomic distribution of students influences school contexts and learning processes. In this manner, a school’s socioeconomic composition has the remarkable potential to shape school climate. This study examines the relationship socioeconomic status (SES) at both the student and school levels has with academic achievement for the first time in Turkiye with regard to academic and vocational tracks. High-stake assessment data of more than 1.4 million students over the last 10 years have been analyzed using two-level hierarchical linear modelling (HLM). The results show parents’ education level to be a significant predictor for both academic and vocational tracks, while family income significantly predicts academic achievement just in regard to vocational track. The results highlight both students’ and peers’ SES to be significantly related to their academic achievement. Additionally, parents’ education level is a stronger predictor of achievement than family income level. The results also emphasize the importance the recent improvements and academic support programs from the Ministry of National Education (MoNE) have had in alleviating achievement gaps among schools.

Revisiting socio-economic inequalities in sedentary leisure time in Sweden: An intersectional analysis of individual heterogeneity and discriminatory accuracy (AIHDA).

Swedish public health reports have repeatedly provided information about socio-economic inequalities in sedentary leisure time, despite that, in the interest of health equity, physical activity should be equally distributed in the population. Such public health reports, however, neither consider the intersection of multiple socio-demographic factors nor the individual heterogeneity around group averages. Drawing on intersectionality theory, this study aimed to revisit previous findings on sedentary leisure time from Swedish public health surveys and demonstrate how the analysis of individual heterogeneity and discriminatory accuracy (AIHDA) can be used for analysing complex health inequalities. Using data from Swedish national public health surveys (2004-2015), we applied the AIHDA to define 72 intersectional groups by categories of age, gender, educational achievement, migration status and household composition. We then calculated (a) the absolute and relative risk of sedentary leisure time and (b) the discriminatory accuracy (DA) of the intersectional grouping. The average risk of sedentary leisure time ranged from 5.8% among native-born, highly educated, young women living alone to 41.0% among immigrated young men, living alone, with low education. The risk was higher in strata comprising immigrated people with low education and lower in strata including native-born, highly educated people. However, the DA of the grouping was poor, indicating a substantial overlap of individual risk between groups. Using the AIHDA and drawing on intersectionality, this study provides an improved mapping of the socio-economic distribution of sedentary leisure time in Sweden, with the poor DA suggesting universal rather than targeted physical activity interventions.

Harmful alcohol habits did not explain the social gradient of sickness absence in Swedish women and men


 Background: the aim of this study was to examine the prevalence and socioeconomic distribution of harmful alcohol habits in sick-listed women and men, and whether the social gradient in sickness absence could be explained by the socioeconomic distribution of harmful alcohol habits.
 Methods: this cross-sectional questionnaire study included newly sick-listed individuals (n=2 798, 19-64 years, 66% women) from Sweden. The outcome variable, self-reported harmful alcohol habits, was measured with the Alcohol Use Disorder Identification Test. Registered socioeconomic variables (education, income, occupational class) were explanatory variables with age as confounder and selfreported health, symptoms, mental wellbeing, and self-efficacy as mediators. Chi2-tests and logistic regression models were applied.
 Results: 9% of sick-listed women and 22% of men had harmful alcohol habits. Women with a low annual income (≤149 000 SEK) had higher odds ratios (OR=2.47; 95% CI=1.43-4.27) of harmful alcohol habits than those with ≥300 000 SEK/year. The significance of low income remained when mediators were introduced into the logistic regression model (OR=2.03, 95% CI=1.13-3.65). In the model including age, income was no longer significant. Men with low income were more likely to have harmful alcohol habits than men with high income (OR=2.59; 95% CI=1.45-4.62). When mediators were included low income remained significant (OR=2.88; 95% CI=1.56-5.31). Income was no longer significant when age was introduced. Education and occupational status were not significant.
 Conclusions: harmful alcohol habits were common among sick-listed women and men. The socioeconomic differences in harmful alcohol habits did not explain the social gradient in sickness absence.

Exploring the effect of urban spatial development pattern on carbon dioxide emissions in China: A socioeconomic density distribution approach based on remotely sensed nighttime light data

Exploring the effect of urban spatial development pattern (UPD) on carbon dioxide emissions (CDEs) (EUC) is important for understanding low-carbon sustainable development. Numerous studies on EUC have mainly focused on individual cities or regions within the mixed conclusions due to the lack of reliable UPD indices and reasonable methods. Thus, taking China's 257 prefecture-level cities as experimental objects, a novel system approach was developed from the perspective of socioeconomic density distribution (SED) index to measure UPD on the basis of the Suomi National Polar-orbiting Partnership (NPP) visible infrared imaging radiometer suite (VIIRS) nighttime light data. EUC was then analyzed on the basis of the dynamic panel data model from multiple perspectives. Results show that the SED index can effectively measure UPD with rich spatial information from multiple dimensions. The coefficients of SED and (SED)2 are 0.129 and − 1.240, respectively, indicating that EUC shows a clear inverted U-shaped curve in China, i.e., an increase in UPD compactness increases CDEs at the beginning, and when a certain height is reached, an increase in UPD compactness decreases CDEs. Heterogeneity analysis indicates a U-shaped curve of EUC is found in megalopolis, and inverse U-shaped curve are observed in medium and small cities. Bus passenger volume, energy consumption, infrastructure, and housing demand are proven as the transmission factors of EUC. It is suggested that utilizing the positive externality effect of agglomeration and accelerating the inflection point of the inverse U-shaped curve may be necessary because the improvement of urban socioeconomic agglomeration will improve the UPD compactness and reduce CDEs.

Socio-economic and demographic determinants of COVID-19 infections and spread at household level: case study from Nigeria

ABSTRACT Many studies have associated the dynamics of diseases’ prevalence with differences in social, economic and demographic status, but it is not yet clear if the same variables explain the spatial distribution of COVID-19 infections in parts of sub-Saharan Africa. This study assessed the spatial spread of COVID-19 infections in relation to socio-demographic risk factors in a typical administrative state – a relatively typical ethnocentric community – in Southwestern Nigeria. Data used were socio-demographics, income variables, COVID-19 status and travel history of 40,300 households. Data were analysed for frequency, prevalence and spatial distributions. The results revealed that COVID-19 cases were heterogeneously distributed within the state. The number of cases was relatively higher in the north and south-eastern parts of the State than in other areas. Male respondents had a higher prevalence (3.7%) of COVID-19 cases compared to their female (2.4%) counterparts. Transmission was most dominant among respondents aged above 70 years old (3.5%), widowed (3.3%) and those who lived in households with between 6 and 10 (4.9%) members. Transmission was also relatively high among those with travel history within the State (9.1%), those that aquired tertiary education (3.8%) and self-employed (3.0%). The study associated imbalanced socio-economic distributions to a diverse range of COVID-19 transmission in the area and therefore advocated for improved policy on residents’ education and sustainable living.

Geographical and socioeconomic inequalities in the double burden of malnutrition among women in Southeast Asia: A population-based study

Countries in the South and Southeast Asia region grapple with significant challenges due to the double burden of malnutrition (DBM) in women. An understanding of the country specific DBM geographical and socioeconomic distribution in South and Southeast Asian countries will enable targeting of DBM interventions towards high-risk populations in the region. This study aimed to analyse anthropometric indicators for women's nutrition at national and subnational levels in seven South and Southeast Asian countries and assess the association between nutritional status and socioeconomic factors. We used population-representative cross-sectional data from the Demographic and Health Surveys conducted between 2000 and 2017, for seven South and Southeast Asian countries (Bangladesh, Cambodia, India, Myanmar, Nepal, Pakistan, and Timor-Leste) and estimated national and subnational prevalence of women underweight and overweight. Using a concentration index (CI), we measured relative and absolute inequality across underweight and overweight in urban and rural areas in these countries. In addition, we estimated the health achievement index, integrating mean coverage of nutritional status and the distribution of coverage by rural and urban populations. The prevalence of underweight women ranged from 7.0% (95% CI: 7.0-8.0%) in Pakistan in 2017 to 44.0% (95% CI: 42-45%) in Bangladesh in 2000 and overweight from 11.0% (95% CI: 10-12%) in Bangladesh in 2000 to 67.0% (95% CI: 66-68%) in Pakistan in 2017. In most countries, underweight disproportionately affected the poorest. The concentration indices for underweight were significant in all countries and ranged from –0.04 in Cambodia in 2014 to –0.38 in Pakistan in 2017. In contrast, overweight disproportionately affected the richest, with concentration indices for overweight significant in all countries, ranging from 0.16 in Cambodia in 2010 to 0.45 in Bangladesh in 2007. In most of the countries an absolute measure of inequality decreased overtime, whereas relative measures increased. Disachievement of underweight is more pronounced in rural populations compared to the urban ones. We noted large geographical and socioeconomic disparities in women DBM in South and Southeast Asian countries, at national and subnational levels. Planning, implementation, and evaluation of existing intervention programmes for food and nutrition should be based on subnational level needs and outcomes. This research is partially funded by the Australian Government through the Australian Research Council's Centre of Excellence for Children and Families over the Life Course (Project ID CE200100025).