Poverty Index Research Articles

A Portrait of Multidimensional Poverty of Indonesian Agricultural Households

The problem of poverty is not only measured by purchasing power but also by access to fulfillment of needs such as education, health, and quality of life. Poverty measured from this perspective is referred to as multidimensional poverty. This study aims to identify the multidimensional poverty conditions of households in the agricultural sector, which is the sector that contributes the highest monetary poverty rate in Indonesia. The data used is data from the National Socio-Economic Survey (SUSENAS) from 2017 to 2021. This research was conducted on 34 provinces in Indonesia. The portrait of multidimensional poverty is processed using the Alkire-Foster method using three dimensions, namely the dimensions of education, health, and quality of life. The three dimensions are measured using thirteen indicators that have been adjusted to the indicators in SDG'S 2030. The results of this study state that the deprivation of agricultural households is still high in the indicators of years of schooling, ownership of health insurance and availability of proper sanitation. The province with the highest Multidimensional Poverty Index (MPI) value is Papua, followed by four other provinces, namely, East Nusa Tenggara, Banten, West Nusa Tenggara, and West Java. In addition, this study also identifies multidimensional poverty in the agricultural sector by regional classification and gender of the household head.

Multidimensional energy poverty and its urban-rural and regional disparities: Evidence from China

This study develops a conceptual framework of multidimensional energy poverty by using a multidimensional poverty index that considers energy accessibility, affordability, and service availability. The index is then utilized to evaluate the extent, depth, and intensity of multidimensional energy poverty (MEP) in China. Specifically, this study aims to identify factors that contribute to the urban-rural and regional MEP disparities in China. The results reveal that (1) MEP is widespread in China; (2) Rural areas experience 2.5 times more MEP compared to urban areas, while inland regions have 1.5 times higher MEP rates than coastal regions; and (3) these disparities are primarily caused by low-income levels, lack of non-agricultural employment opportunities, and educational attainment. Therefore, policies targeting low-income, unemployed, and less-educated individuals are necessary to address this issue. In addition, promoting urbanization and eliminating the household registration system are crucial steps to address MEP disparities in China. Furthermore, improving energy infrastructure and increasing knowledge dissemination can also help reduce reliance on traditional energy sources.

Analyzing the Impact: The Role of MSME Growth in Reducing Unemployment Amidst High Levels of Poverty

This study employs a quantitative research method to examine the impact of the number of MSMEs and poverty rates on unemployment rates in Indonesia from 2011 to 2022, utilizing data from the Central Bureau of Statistics (BPS Indonesia) and Bank Indonesia. The analysis reveals a significant relationship between the increase in MSMEs, poverty index fluctuations, and unemployment rate changes during this period. The findings demonstrate a strong correlation between the growth of MSMEs and a reduction in unemployment, whereas the relationship between poverty levels and unemployment rates is weak. This suggests that the expansion of MSMEs is an effective strategy for reducing unemployment and improving economic conditions. The study aims to enhance understanding of the factors influencing unemployment and the challenges policymakers face, providing valuable insights for efforts to combat unemployment. Additionally, the dataset used may benefit other studies addressing unemployment issues in Indonesia and similar regions. The results confirm the crucial role of MSME development in lowering unemployment rates, highlighting its potential as a viable policy approach for economic improvement.

Energy Poverty and Democratic Values: A European Perspective

This paper explores the complex relationship between energy poverty and the maintenance of democratic values within the European Union (EU), suggesting that energy poverty not only impacts economic stability and health outcomes but also poses significant challenges to democratic engagement and equity. To measure energy poverty, a composite index is developed using the entropy method, which surpasses traditional measures focused solely on access to energy or its developmental implications. To assess the level of democratic governance in EU countries, the voice and accountability index (VEA), which is part of the World Governance Indicators compiled by the World Bank, is utilized. By analyzing EU data from 2006 to 2022, the findings suggest that a 1% improvement in VEA quality, represented by a coefficient of 0.122, is correlated with a notable improvement in the energy poverty index. This suggests that the EU should focus on enhancing transparency and public participation in energy decision-making, along with ensuring accountability in policy implementation. The research also differentiates between full and flawed democracies, noting that tailored approaches are needed. In full democracies, leveraging economic prosperity and trade is crucial due to their significant positive impacts on the energy poverty index. In contrast, in flawed democracies, enhancing governance and accountability is more impactful, as evidenced by a higher coefficient of 0.193. Strengthening legal and regulatory frameworks, improving regulatory quality, and ensuring public engagement in governance could substantially mitigate energy poverty in these contexts. In addition, this paper demonstrates that this relationship is influenced by factors such as income inequality, energy intensity, and trade openness.

Lessons from Germany for levelling up in the UK

This paper suggests how lessons from Germany’s national-level, comprehensively focused place-based regeneration (or levelling up) efforts could be applied in the UK. It draws the direct linkage between spatial inequality and the decline of large-scale heavy manufacturing industry at the end of the 20th century in Germany and the UK. It also posits that rapid deindustrialisation, poor-quality education and other indices of poverty and economic inequality have fuelled political fragmentation — including loss of public trust in government, national and civic institutions — in both countries. The paper explores and compares two sets of German redevelopment efforts over time, in the industrial heartland of the former West German Ruhr region and across the former East Germany, to assess their impacts on reducing political polarisation as well as bolstering redevelopment. It highlights which elements of these efforts have been most successful and why. The German experience, as described in the paper, clearly demonstrates that it takes decades to achieve measurable positive economic outcomes from redevelopment programmes. Political outcomes can also be mixed, even negative, if grassroots sentiment and public well-being are ignored or discounted in the process. In the former East Germany, despite huge transfers of development funds, grievances rooted in the economic and political dislocation of German unification in the 1990s have fuelled anti-establishment politics. The paper also examines how grassroots, philanthropic and private sector actors work alongside regional and federal governments in Germany in shaping positive political as well as socio-economic outcomes and how this might be most effectively adapted for the UK.

Disparities in diagnosis and access to care in patients with young-onset rectal cancers in northeast Ohio.

e15521 Background: The rising incidence of young-onset colorectal cancers (YO-CRC) in individuals < 50 years old is alarming. Despite the updated USPSTF recommended age for CRC screening ( < 45) in 2021, disparities in receiving proper care for YO-CRC remained largely under addressed. We sought to identify modifiable disparities to be addressed with future interventions for patients with YO-rectal cancer (YO-RC). Methods: We analyzed a cohort of patients with newly diagnosed YO-RC from 2001 to 2023 at a large academic center in Northeast Ohio. Demographic data included sex, race, age, smoking status, and poverty index. A retrospective chart review was completed to assess diagnosis date and time from symptom onset to diagnosis. Access to guideline-concordant care was assessed via clinic visits with specialty providers in medical oncology, radiation oncology, colorectal surgery, genetics, and onco-fertility. Chi-square testing and Cox regression modeling was used for statistical analyses. Results: We identified 83 patients with YO-RC, 52% female (n = 43) and 48% male (n = 40), of which 76% were White (n = 63), 21% Black (n = 17), 2% Hispanic (n = 2), and 1% Asian (n = 1). Median age at diagnosis was 44 years (IQR[39-49]). Non-White (NW) patients had a greater delay from symptom onset to diagnosis compared to White (W) patients, with an average time of 6.9mo vs 1.3mo (p < 0.00001). Colonoscopy completion rates after symptom onset for NW and W patients at 2-months was 11% vs 81% and 33% vs 98% at 4-months (p < 0.0001, respectively). Rate of access to specialty care once diagnosed was not statistically significant for either groups, but there is a lower percentage of all YO-RC patients who accessed onco-fertility (13%, n = 11) or genetics services (46%, n = 38). The median 1-year overall survival was 50% for NW patients vs 85.7% for W patients, which was statically significant on univariate analysis (p = 0.04), but not on multivariate analysis. Conclusions: We found significant disparities for YO-RC from symptom onset to diagnosis with longer delays noted in NW patients. Such delays in diagnosis may lead to higher staging upon presentation and impact survival. Once a diagnosis was made, access to specialty oncology care rates was similar across groups. This study encourages further evaluation and consideration of socioeconomic factors and care access patterns to address disparities in diagnosis, access, and treatment of YO-CRC. [Table: see text]

Assessing survival effects of persistent poverty and payer status in non-elderly adults with lung or breast cancer.

1608 Background: Persistent poverty (PP), defined as area poverty ≥20% over 30 years has been associated with increased cancer incidence and worse survival. We examined 1) whether residing in a PP area has larger survival effects than areas with similar contemporary poverty rates; 2) whether adjusting for sociodemographics and payer status reduces PP effects; and 3) whether effects differ for relatively poor (lung and bronchus, LCa) vs good prognosis (female breast; BrCa) cancers. Methods: We used Surveillance, Epidemiology, and End Results (SEER) data linked to Medicaid and Medicare enrollment records (2007-2013), with census-tract level indicators for PP and current poverty (CP) as of 2010. We selected adults aged 19-64, diagnosed with LCa or BrCa. We created a hierarchical poverty status measure (PP, CP>20%, CP 10-20%, CP <10%). Primary payer at diagnosis (SEER) was edited using Medicaid and Medicare enrollment records. Covariates include patient sociodemographics (including age, race, sex (LCa only), marital status), rurality, and region. We used Cox proportional hazard models to estimate effects of poverty status and payer on survival, starting with a limited Model I (poverty status, rurality, and cancer stage), adding sociodemographics, region, and diagnosis year (Model II), plus primary payer (Model III). Results: Among LCa (BrCa) 8.8% (5.3%) of 70,964 (246,405) patients lived in PP areas, with 19.1% (13.7%) in areas with CP >20%; primary payers included 51.9% (75.0%) private, 28.7% (16.9%) Medicaid, and 3.1% (1.1%) uninsured. For both cancers, adjusted hazard of death increased with increasing poverty levels; PP areas showed the highest risk (table). The magnitude of the poverty gradient was smaller for LCa vs BrCa. Adjusting for sociodemographic measures and primary payer reduced the magnitude of poverty status effects, particularly for BrCa. Conclusions: We observed significant but distinct associations of poverty status, including PP, with survival for non-elderly adults with LCa and BrCa. With better prognosis, BrCa patients have longer exposure to PP, which may increase the impact on outcomes. Person-level characteristics and health insurance are also key factors affecting care access and survival. These results highlight the need to consider both area context and personal socioeconomic characteristics when targeting and evaluating interventions to enhance survival outcomes. [Table: see text]

Regional disparity in energy poverty: A spatial analysis of Odisha

Energy poverty is one of the major deprivations that has direct effect on the well-being of a household at micro level. At macro level, it also has significant effect and hinders the sustainable development of a nation. The binary measurement, commonly used to identify the energy poor population, has major drawbacks as it only takes accessibility of the services into consideration, whereas, in the contemporary period more emphasis should be on the affordability, quality, reliability and legal implications of energy services. The present study, therefore, tries to estimate the energy poverty condition by following a multi-dimensional approach and also tries to identify the actual energy poor by analysing the spatial disparity prevalent in the state of Odisha. A multidimensional framework is used to capture different aspects of energy provisioning at household level and an energy poverty index is constructed by assigning equal weights for the parameters. Spatial disparity is measured by considering proxies for the social parameters and following Gini’s coefficient of disparity measurement. The results indicated persistence of disparity in energy poverty at regional, inter and intra-district levels.

Pooled lagged effect of runoff on leptospirosis cases in Colombia

Leptospirosis is a global zoonotic disease caused by spirochete bacteria of the genus Leptospira. The disease exhibits a notable incidence in tropical and developing countries, and in Colombia, environmental, economic, social, and cultural conditions favor disease transmission, directly impacting both mortality and morbidity rates. Our objective was to establish the pooled lagged effect of runoff on leptospirosis cases in Colombia. For our study, we included the top 20 Colombian municipalities with the highest number of leptospirosis cases. Monthly cases of leptospirosis, confirmed by laboratory tests and spanning from 2007 to 2022, were obtained from the National Public Health Surveillance System. Additionally, we collected monthly runoff and atmospheric and oceanic data from remote sensors. Multidimensional poverty index values for each municipality were sourced from the Terridata repository. We employed causal inference and distributed lag nonlinear models to estimate the lagged effect of runoff on leptospirosis cases. Municipality-specific estimates were combined through meta-analysis to derive a single estimate for all municipalities under study. The pooled results for the 20 municipalities suggest a lagged effect for the 0 to 2, and 0–3 months of runoff on leptospirosis when the runoff is < 120 g/m2. No effect was identified for longer lagged periods (0–1, 0 to 4, 0 to 5, and 0–6 months) or higher runoff values. Incorporation of the multidimensional poverty index into the meta-analysis of runoff contributed to the models for the lagged periods of 0–3, and 0–4 months.

Predictive stability study of poverty trend in Uganda using selected indicators

This study investigates poverty dynamics in Uganda, employing an extensive stability analysis of different socioeconomic indicators to understand long-term trends and likely drivers of poverty. An eighteen years yearly secondary data from 1992 to 2020 on poverty rates for the selected indicators under review sourced from World Bank site was utilized for all the data analysis. Outcomes from extensive data analysis shows considerable reductions in poverty rates over time, especially in outlying areas of eastern and northern Uganda despite increasing income inequality as suggested by the increasing Gini coefficient. All the metrics have a significant impact on Uganda's poverty rates, with the exception of the poverty headcount ratio, which stands at USD 6.85 per day (2017 PPP) as a percentage of the population. Particularly, the forecasted values also show a fluctuating trend movement, both downward and upward, suggesting possible variability in future poverty rates in Uganda. The necessity to carefully evaluate as well as monitor poverty dynamics to guide policy interventions aimed at reducing poverty is underlined by this information. Additionally, the stability analysis framework suggested in this research provides insights into the viability as well as resilience of Uganda's socioeconomic system in tackling poverty, enabling evidence based policies and interventions in poverty reduction. The study suggests more examination of various other dimensions of poverty and non-monetary indicators of well-being to better our understanding and support better poverty alleviation methods in Uganda along with other similar settings.

Informal Economy and Poverty Reduction

The study investigated the role of informal economy and poverty reduction in selected business activities in Ogba/Egbema/Ndoni Local Government Area of Rivers State. 140 structured questionnaires were distributed across various business types in the local government out of which 120 were retrieved. The informal sector or grey economy is a business activity that falls outside the formally recognized enterprise engagement not accounted for in the National Gross Domestic Product. As result of the nature of the businesses, it becomes difficult for authorities to hold them for taxation. The study employed the primary data source for information which was a subject of combined descriptive and Ordinary Least Square analytical econometric technique. It employed the SPSS Package for the Management Sciences and Business. The analysis revealed a positive correlation between multidimensional poverty index and family size and monthly consumption among other variables employed in the survey. The findings established the necessity for infrastructural development in the rural areas, educational improvement and adequate finding or accessibility to capital among others. It, therefore, recommended the deliberate policy of government to improve the provision of basic amenities in rural areas, enhance the education facilities to cater for the needs of those in the rural areas and promote access to credit facilities.

Water infrastructure sustainability challenge in Nigeria: A detailed examination of infrastructure failures and potential solutions

ABSTRACT Achieving Sustainable Development Goal 6.1 – universal and equitable access to safe and affordable drinking water – is a critical global challenge. This study contributes to this aim by analyzing the functionality and sustainability of rural water boreholes in Nigeria. It employs GIS mapping, Spearman's rho correlation analysis, and interviews across 1,696 communities to investigate borehole failure dynamics, the impact of multidimensional poverty index (MPI) on water access, technical failure causes, and the influence of ownership on functionality. Findings show that while 49.8% of communities lack improved water sources, 25.5 benefit from functional boreholes, and 24.5 grapple with failures. This study reveals a complex relationship between MPI and water access, with community ownership associated with better functionality. Consequently, the study proposes holistic strategies, emphasizing community mapping and smart infrastructure, to enhance water system sustainability. Although the study is centered in Nigeria, its insights are applicable to regions with similar socio-economic conditions, contributing to the global pursuit of sustainable water access in alignment with SDG 6.1.

Geographic heterogeneity of SARS-CoV-2 circulation in Abidjan, Ivory Coast: a prospective study.

Few studies on SARS-CoV-2 seroprevalence in Ivory Coast have been conducted since the first case was reported on March 11, 2020. The main objective of this study was to observe and better understand the circulation of SARS-CoV-2 in Abidjan. This prospective study collected data concerning age, sex, vaccination status, municipality of origin, monthly income, frequency of malaria, and frequency of diarrheal diseases in persons who gave their informed consent. Venous blood samples were taken to test for anti-SARS-COV-2 antibodies (IgM and IgG) using the VIDAS automated system. A total of 1504 patients were recruited and tested for antibodies directed against SARS-COV-2. Data analysis revealed the presence of anti-SARS-CoV-2 in 53.5% of participants, 17.3% of the participants had a previous symptomatic infection, 31.4% had an asymptomatic infection, and 44.8% were never in contact with the virus. Seroprevalence of SARS-CoV-2 was higher in Marcory (70.9%) and Cocody (61.1%) than in the remaining townships (48.4%). Township rates of serologically confirmed SARS-CoV-2 infection correlated with poverty index (p = 0.025), children < 5 years' proportion in the township (p = 0.026), and levels of malaria (p = 0.034). In the city of Abidjan, COVID-19 is strongly modulated by poverty, the proportion of babies and toddlers in the community, or exposure to malaria.

SPATIAL MODELING OF POVERTY IN BENGKULU PROVINCE WITH MIXED GEOGRAPHICALLY WEIGHTED REGRESSION

The percentage of poor people in Bengkulu Province is high from year to year. The poverty rate in Bengkulu Province also tends to fluctuate. If there is a decrease in the poverty rate, the decrease is relatively small. Poverty in the regions of Bengkulu Province also varies from district to district, subdistrict, and village to village, because poverty data is spatial data that varies regionally. The diversity of poverty data in Bengkulu Province is influenced by spatial effects, namely spatial dependency and spatial heterogeneity. Spatial dependency occurs due to spatial error correlation in cross section data, while spatial heterogeneity occurs due to random area effects, which is the difference between one region and another. Therefore, classical methods are not qualified enough to analyze the resulting diversity. This research will model the poverty of each district/city in Bengkulu Province using Mixed Geographically Weighted Regression (MGWR), because this method is quite complex in modeling data that contains spatial heterogeneity and variations in geospatial data. This modeling aims to identify and analyze poverty indicators in Bengkulu Province spatially, namely based on poverty data in each district/city in Bengkulu Province. The results showed that by using the MGWR method, the variables that locally influence the percentage of extreme poor people in each district/city in Bengkulu Province are Female Household Head Gender and not having a waterheater . Meanwhile, the variable that has a global effect on the percentage of the extreme poor in each district/city in Bengkulu Province is not having a flat screen television ().

A review of natural resource extraction industries and their influence on the occurrence of poverty

PurposeThis research paper takes a narrow approach to examining the apparent link between poverty and the resource extraction industries. However, it acknowledges that much more is to be explored about this relationship. Many complexities influence the occurrence and degree of poverty in a particular country, region, or community.Design/methodology/approachThe literature review identified proposed and operational poverty reduction actions and processes categorized under the broad concept of community development projects. The surveyed cases describe how various corporate strategies, work processes, labor requirements and efficient management and governance solutions are purported to improve poverty-reduction efforts potentially.FindingsNo causal linkages between poverty and hypothetically valuable and successful community development projects were found. No poverty monitoring evaluations and learning data (MEL) for these projects were proposed and published in most of the literature. However, associations were observed between some business practices implemented in these resource extraction community development projects and observations of indicators of lower poverty levels.Practical implicationsThe research improves our understanding of the requirements and opportunities for successful community development projects by highlighting processes, company strategy, human resource programs and enlightened governance that can contribute to reducing poverty.Originality/valueThe paper identifies the characteristics of community development projects that appear to span natural resource extraction industries and countries. Effective management strategies and representative and formally designated organisational governance boards are essential for these projects.

PER CAPITA CONSUMPTION ESTIMATION IN SURABAYA USING ENSEMBLE MODEL APPROACH

The categorization of the Low-Income Community category is based on the poverty indicators in the Multidimensional Poverty Index, including the dimensions of health, education, and living standards. The Proxy Means Test (PMT) can estimate household income or consumption by taking into account household conditions that are readily observable and cannot be manipulated. This method offers the advantage of being capable of determining both the poverty level of a household and the household's characteristics based on asset ownership and socio-demographic conditions. This study aims to estimate per capita consumption using OLS, Robust, Quantile, LASSO, and Ensemble methods. The application of these methods is intended to address various issues, including the presence of outlier data, multicollinearity, and uncertainties. The results indicate that none of the four methods used achieved the highest accuracy based on the MSE, MAE, and sMAPE criteria. Consequently, employing an ensemble model becomes essential to accommodate the element of uncertainty present in these four models. The application of the ensemble method is not only as a comparison between the models, but also as a means to capture the uncertainty contained in each model

Measurement and determinants of multidimensional urban poverty: Evidence from Shandong Province, China.

China eliminated rural poverty under current poverty standards in 2020. However, compared with rural poverty, urban poverty in China has been somewhat neglected. This paper aims to discover the changes and determinants of multidimensional urban poverty in Shandong Province, a representative province in Eastern China. Using a nationally representative panel dataset, the China Family Panel Studies, and the Dual Cutoff method, this study creates a multidimensional poverty index with four dimensions and 11 indicators to measure urban poverty in Shandong Province. This paper discovers that while the incidence of multidimensional urban poverty in Shandong Province decreased from 47.62% in 2010 to 36.45% in 2018, the intensity of multidimensional poverty only decreased from 41.27% to 37.25%, which indicates the inadequacy of urban anti-poverty efforts in Shandong Province. This paper also uses logistic regression to identify the determinants of multidimensional urban poverty. The findings suggest that income, health, drinking water, and durable goods are the main determinants of multidimensional urban poverty in Shandong Province. Based on these findings, this study provides targeted recommendations for future urban anti-poverty policies in Shandong Province.

How to quantify the regional effects of ocean temperature rise due to climate change: implications of Octopus maya ecophysiology on food security of the Yucatan shelf artisanal fishermen

The vital survival, maturation, and reproduction rates of Octopus maya were formulated according to the thermal preferences in each stage (juvenile and adult) and the bottom temperature of the Yucatan shelf projected from different shared socioeconomic pathways (SSPs): SSP1-5, to describe the species population growth in shallow waters. The dispersion of each individual in the population and the spread of the offshore population were incorporated with an integrodifference equation. For each SSP, the food security of the artisanal fishermen in the Western, Central, and Eastern Yucatan shelf region was analyzed based on the proposed availability, access, and utilization indices of Octopus maya as food. The analysis was complemented with an average monthly protein and income poverty indicators that this species’ shallow water fishery would have the capacity to supply by the year 2100. Although the proportion of the legally O. maya catchable population may be favored with the gradual increase in temperature in the coming years, this increase may not translate into greater food security for the artisanal fishermen who catch this species in shallow waters. Moreover, this fishery alone may not have the capacity to supply the average annual intake of 10.6 kg of protein per person recommended and maintain fishermen and their families above the income poverty line by 2100.

Effect of Covid-19 on Female-Headed Farming Household Food Security in Northern Bahr El Ghazal State, South Sudan

At the beginning of 2020, global food security was interrupted by the unprecedented occurrence of the COVID-19 pandemic and its associated restrictions to contain it. In South Sudan, women were among the most vulnerable groups due to restrictions and standard operating procedures (SoPs). This study was conducted to determine the effect of COVID-19 on the food security of female-headed households from three counties in Northern Bahr el Ghazal state, South Sudan. The analysis of the food security status was based on the Consolidated Approach for Reporting Indicators of Food Security (CARI) and food security was viewed in terms of availability of, and accessibility to food among households. Findings revealed that only 15.5% of the female-headed households sampled were food secure while 84.5% of them were food insecure on the 2-level scale. There was a significant reduction in average household income, size of land under agricultural production and crop harvest. Households lost access to produce markets, supermarkets, agro-input markets and produce stores, lowering their food production potential and farm output. Coping strategies included sale of household items, finding other work to supplement their agricultural activities, revision of household food consumption tendencies, new sales channels, while some of the households did nothing. These strategies are indicators of poverty, hunger and food insecurity which can lead to malnutrition. The study concluded that food security among female-headed households is low post-COVID, pushing women into life-threatening coping strategies in South Sudan. Development efforts in the country should be directed towards supporting recovery and resilience systems among these households in the country

Multidimensional Poverty and Risk of Atherosclerotic Cardiovascular Disease: A U.S. National Study

BackgroundPoverty is associated with atherosclerotic cardiovascular disease (ASCVD). While poverty can be evaluated using income, a unidimensional poverty metric inadequately captures socioeconomic adversity. ObjectivesThe aim of the study was to examine the association between a multidimensional poverty measure and ASCVD. MethodsSurvey data from the National Health Interview Survey was analyzed. Four poverty dimensions were used: income, education, self-reported health, and health insurance status. A weighted deprivation score (ci) was calculated for each person. The multidimensional poverty index was computed for various cutoffs, k, for total population, and by ASCVD status. The association between multidimensional poverty and ASCVD was examined using Poisson regression. Area under receiver operator characteristics curve analysis was performed to compare the multidimensional poverty measure with the income poverty measure as a classification tool for ASCVD. ResultsAmong the 328,164 participants, 55.0% were females, the mean age was 46.3 years, 63.1% were non-Hispanic Whites, and 14.1% were non-Hispanic Blacks. Participants with ASCVD (7.95%) experienced greater deprivation at each multidimensional poverty cutoff, k, compared to those without ASCVD. In adjusted models, higher burden of multidimensional poverty was associated with up to 2.4-fold increased prevalence of ASCVD (ci = 0.25, adjusted prevalence ratio [aPR] = 1.66, P < 0.001; ci = 0.50, aPR = 1.99; ci = 0.75, aPR = 2.29; P < 0.001; ci = 1.00, aPR = 2.38, P < 0.001). Multidimensional poverty exhibited modestly higher discriminant validity, compared to income poverty (area under receiver operator characteristics = 0.62 vs 0.58). ConclusionsThere is an association between the multidimensional poverty and ASCVD. Multidimensional poverty index demonstrates slightly better discriminatory power than income alone. Future validation studies are warranted to redefine poverty's role in health outcomes.