Poverty Index Research Articles

Digital Health Literacy and Social Determinants of Health Affecting Telehealth Use by Athletic Trainers.

While increasing telehealth use throughout sports medicine has improved patients' access to health care, some communities may not have the same opportunities to connect with a provider. Barriers to telehealth implementation can be influenced by internal (eg,provider's digital health literacy and resources) and external (eg,community's social determinants of health or "SDOH") factors. This study aimed to assess the impact of internal and external factors on telehealth use by athletic trainers (ATs). Cross-sectional survey. In total, 767 ATs participated in the study. Participants (age = 39 [13]y) completed a survey containing the electronic health literacy scale and digital health literacy instrument, reported professional use of telehealth as a provider (yes/no), provided resources at their clinical site, and provided the zip code for the community they served. After data collection, the researchers extracted SDOH information using the zip code data from 2 US databases, including population density, median household income, poverty index, education level, and technology access. Chi-square or independent samples t tests were conducted to compare telehealth use by each SDOH factor. In total, 62.3% (n = 478/767) of ATs reported using telehealth, and 81.6% of ATs (n = 626) had a dedicated facility to offer health care services. We identified a significant difference in digital health literacy scores between users and nonusers of telehealth (P = .013). We did not identify any significant differences between telehealth users by community type (P = .957), population density (P = .053), income (P = .462), poverty index (P = .073), and computer (P = .211) or broadband internet access (P = .295). Our data suggest that internal factors such as digital health literacy and clinical site resources may have contributed to an AT's previous telehealth use in clinical practice. However, the SDOH data extracted from the community zip code where the AT provided clinical services were similar for those with and without previous telehealth use.

Transición sociotécnica en el sector de la palma aceitera: análisis desde una perspectiva multinivel en el municipio Colombiano de Tibú

Abstract Changes in the interactions between agents involved in the value chain of the palm oil sector in the municipality of Tibú (Colombia) over the period 1985-2020 have resulted in a reduction in the indices of poverty, social inequality, and unemployment for the inhabitants of the region, which can be explained by a process of socio-technical transition. The main objective of this study is to analyze the factors that determined the success of this process from a multilevel perspective. Exploratory research was developed based on a case study analysis using semi-structured interviews of commercial and non-commercial agents in the sector and information collected from secondary sources. The results show that changes in the legal and regulatory framework established by the government, landscape transformation, and the transition from small farmers to medium entrepreneurs of the farms in the region were important factors revolutionizing the system and are encouraging the emergence of new alternative practices in the palm oil sector.

POVERTY AND INEQUALITY IN NIGERIA: A HOUSEHOLD-LEVEL FOUR-WAVE COMPARATIVE STUDY

Poverty and income inequality have been a recurring challenge in the global space for more than five decades. While these challenges have been declining globally, they have remained unabated and rising in Nigeria; thus, making Nigeria tagged as their destination. Thus, the research set out to evaluate the poverty and inequality in Nigeria using a household four-wave of secondary panel data of 4,000 nationally representative households of the Nigeria General Household Survey GHS - Panel collected by the National Bureau of Statistics from 2010 to 2019. Analytical tools used were descriptive statistics, the Foster-Greer-Thorbecke (FGT) poverty index, Lorenz’s curve, and the Gini coefficient. The results of the Foster-Greer-Thorbecke poverty headcount showed that over 50% of all the respondents remained under the poverty line throughout the four waves, thus indicating the prevalence of chronic poverty rather than transient poverty during the period. The general poverty depth ranged from 0.21 to 0.23 and the poverty severity ranged from 0.11 to 0.12. The Gini coefficient of inequality for total expenditure ranged from 0.39 to 0.44 with higher sectoral inequality. The results showed that Nigeria had chronic poverty, moderate poverty depth, and severity; and moderate inequality. Therefore, with strong political will and consistently right policies, Nigeria can exit extreme poverty. This work unraveled the reason behind the persistently high poverty status and inequality of Nigeria and has revealed the path not taken, which if done would enable Nigeria to exit extreme poverty and hunger.

Examining approaches to material hardship classification: Cross-sectional and longitudinal perspectives

Material hardship is a significant indicator of poverty, offering direct insights into the inability to afford necessities. When examining material hardship, often a decision lies in determining the boundaries that distinguish those who experience hardship from those who do not. This decision holds significance given the threshold for differentiating hardship from non-hardship populations guides poverty identification, informs assessments of the impacts of material hardship, and directs poverty reduction initiatives. While there are several material hardship classification approaches, there is limited research investigating the effects of different approaches on outputted proportions of material hardship. This study examines three common methods for classifying families based on their material circumstances to assess the consistency and variability in who is classified as living in hardship. Data from four waves of the Growing Up in New Zealand longitudinal study (n = 6575), spanning early childhood through to early adolescence, were utilised to explore the outcomes of these classification approaches across the four waves. Findings reveal differences in the prevalence rates and interpretations of material hardship over time, depending on the adopted method. This research demonstrates the influence of a researcher's choice of classification method on the understanding of material hardship within a given population. Setting thresholds is not a ‘one-size-fits-all’ pursuit but a decision requiring careful consideration. Consequently, this study offers insights to equip researchers in selecting an appropriate method aligned with their specific research aims. Clear reporting of the chosen method is encouraged to ensure informative assessments.

Multidimensional Poverty: Complementary Measure to Absolute and Relative Poverty

Poverty is a complex issue that involves more than just income levels, affecting various aspects of life such as health, education, and living conditions. The ongoing discussion about how to measure poverty, whether through absolute or relative terms, reflects the challenges in assessing it. Absolute poverty is based on a set standard that focuses on meeting basic needs for survival, while relative poverty looks at income disparities within a society. This study explores existing research on multidimensional poverty and examines the debate between absolute and relative poverty measures, considering their respective advantages and disadvantages. A notable conclusion from the research is that multidimensional poverty indices (MPIs), like the Multidimensional Poverty Index, provide a broad view of deprivation by including multiple factors. MPIs help policymakers design more targeted interventions in areas such as education, healthcare, and living standards. However, absolute poverty measures, such as the World Bank’s $1.90-per-day threshold, are still essential for tracking extreme poverty in developing nations, offering a clear benchmark for international comparisons. In contrast, relative poverty measures are particularly relevant in wealthier nations, where inequality and social exclusion are more prominent factors in poverty. This study highlights gaps in how these different approaches are integrated and calls for further research to improve models that address both absolute and relative poverty. The findings suggest that combining multidimensional, absolute, and relative poverty measures is important for fully understanding poverty and creating effective strategies to reduce it, adapted to the needs of specific regions and contexts.

An Analytical Study of Multidimensional Poverty in Urban and Rural Areas of Iran

This study aims to measure and analyze multidimensional poverty in Iran using the Alkire-Foster (AF) index across five dimensions: education, employment, living standards, health, and housing. The study period covers the years 2017 to 2019. The results indicate that approximately 28% of individuals in rural areas and 25% in urban areas are poor. Additionally, about 51% of the poor live in rural areas, while 49% reside in urban areas. The highest deprivation in both regions pertains to employment, accounting for around 40%. In other dimensions, deprivation rates are 16% in education, 4% in living standards, 24.5% in health, and 15.5% in housing. The multidimensional poverty index (MPI) is calculated to be 10% for urban areas and 11.5% for rural areas. The findings show that women, particularly in the education dimension, experience higher levels of deprivation in both urban and rural areas. This study demonstrates that poverty is a multidimensional phenomenon, and effective policies for poverty reduction must address all its dimensions. Based on the results, improving employment conditions and enhancing living standards are primary priorities for reducing poverty. Additionally, special attention to improving health and education services, especially for women, is essential. The research indicates that targeted and precise policies can significantly reduce poverty and social inequalities.

The Impact of Poverty on Northern Nigeria’s Development: A Comprehensive Analysis

Poverty in Nigeria significantly hampers the nation’s developmental progress, with Northern Nigeria bearing the brunt of this socioeconomic issue. Despite the country’s rich agricultural and natural resources and a relatively significant industrial sector, Nigeria remains one of the world’s poorest countries, with up to 70% of its population living in poverty. This paper explores the multidimensional nature of poverty in Nigeria, utilizing data from the National Bureau of Statistics and other sources to provide an analysis and graphical representation of poverty rates. The 2022 National Multidimensional Poverty Index reveals that 63% of Nigerians, or over 133 million people, live in poverty, with a disproportionate impact on Northern Nigeria. Contributing factors include adverse economic policies, regional disparities, and demographic challenges. This analysis underscores the urgent need for targeted interventions to address the deep-rooted poverty in Northern Nigeria and foster sustainable development across the country. This paper examines the severe impact of poverty on Nigeria’s development, focusing on the acute disparities between Northern and Southern regions. Despite Nigeria’s abundant agricultural and natural resources and a relatively significant industrial sector, it remains one of the world’s poorest countries, with up to 70% of its population living in poverty. Using data from the National Bureau of Statistics and other sources, the paper provides a comprehensive analysis and graphical representation of poverty rates. The 2022 National Multidimensional Poverty Index reveals that 63% of Nigerians, or over 133 million people, live in poverty, with Northern Nigeria experiencing the highest rates. Factors contributing to this include adverse economic policies, regional disparities, and demographic challenges. By integrating multiple sociological theories—structural functionalism, conflict theory, dependency theory, social exclusion theory, and human capital theory—the paper offers a thorough understanding of poverty’s root causes in Northern Nigeria. It concludes with targeted recommendations for interventions to mitigate poverty and promote sustainable development across the country.

Pobreza multidimensional no Brasil: evidências para as áreas rurais e urbanas

Abstract This paper studied the behavior of multidimensional and income poverty, as well as its determinants in Brazil, in addition to rural and urban areas, based on information from the 2019 National Continuous Household Sample Survey (PNADC). The Alkire-Foster methodology was used in the construction of a Multidimensional Poverty Index (MPI), in addition to the logit model to estimate the impacts of determinants related to household characteristics on poverty. The health and sanitation dimension was the one that contributed the most to the MPI, followed by the education and housing dimensions. Unidimensional poverty was greater than multidimensional and rural poverty was also greater. Among the determinants of poverty, being in households with non-white heads, younger, unmarried, unemployed, less educated and in the North and Northeast regions increased the chances of poverty. In addition, while female heads reduced the chances of multidimensional poverty, it increased the chances of the unidimensional one.

Agricultural Water Poverty Index: A Tool for Agricultural Water Resources Management in District Dir Lower, Khyber Pakhtunkhwa, Pakistan

Agricultural Water Poverty Index: A Tool for Agricultural Water Resources Management in District Dir Lower, Khyber Pakhtunkhwa, Pakistan

Multi-dimensional poverty and health outcomes in Ghana

There is evidence on the social gradient in health in multiple settings. Recent research is increasingly focused on linkages between multidimensional poverty and health to capture and ascertain the role of non-monetary factors on individuals' health. In this paper, using the 2018/19 wave of the Ghana Socioeconomic Panel Survey (GSEPS) and the country's newly introduced multidimensional poverty index, bivariate correlations and regression analyses are carried out to explore associations between household multidimensional poverty and a series of health outcomes, including physical and mental health. There is evidence of significant subgroup differences across the country by gender, rural/urban residence, education, and region. Regression analyses consistently indicate that poorer mental and physical health outcomes are positively and significantly correlated with greater multidimensional poverty. Robustness tests indicate that deprivations in electricity access, safe sanitation and education are particularly relevant. Findings suggest the importance of a more equal geographical distribution of social amenities and infrastructure, as well as adequate targeting of policies to reduce health inequalities across the country and achieve a more equitable and inclusive distribution of resources within the country.

Predictive Modeling of Energy Poverty with Machine Learning Ensembles: Strategic Insights from Socioeconomic Determinants for Effective Policy Implementation

This study aims to identify the key predictors of the multidimensional energy poverty index (MEPI) by employing advanced machine learning (ML) ensemble methods. Traditional energy poverty research often relies on conventional statistical techniques, which limits the understanding of complex socioeconomic factors. To address this gap, we propose an approach using three distinct ML ensemble models: extreme gradient boosting (XGBoost)‐random forest (RF), XGBoost‐multiple linear regression (MLR), and XGBoost‐artificial neural network (ANN). These models are applied to a comprehensive dataset encompassing various socioeconomic indicators. The findings demonstrate that the XGBoost‐RF ensemble achieves exceptional accuracy and reliability, with a root mean squared error (RMSE) of 0.041, an R‐squared (R2) of 0.975, and a Pearson correlation coefficient of 0.992. The XGBoost‐MLR ensemble shows superior generalizability, maintaining a consistent R2 of 0.845 across both the testing and training phases. The XGBoost‐ANN model balances complexity with predictive capability, achieving an RMSE of 0.056, an R2 of 0.954 in the testing phase, and an R2 of 0.799 in training. Significantly, the study identifies “Education,” “Food Consumption Score (FCS),” “Household Food Insecurity Access Scale (HFIA),” and “Dietary Diversity Score (DDS)” as critical predictors of MEPI. These results highlight the intricate relationship between energy poverty and factors related to food security and education. By integrating the insights from these ML models with policy initiatives, this study offers a promising new approach to addressing energy poverty. It highlights the importance of education, food security, and socioeconomic factors in crafting effective policy interventions.

Poverty line and multidimensional poverty index through Sustainable Development Goals in Indonesia

Poverty line and multidimensional poverty index through Sustainable Development Goals in Indonesia

DETERMINANTS OF BROILER PRODUCTION AND ITS EFFECTS ON POVERTY STATUS AMONG CIVIL SERVANTS IN JOS METROPOLIS, PLATEAU STATE, NIGERIA

The research was carried out to analyze broiler production as a sustainable tool in reducing poverty among civil servants in Plateau State, Nigeria. The specific objectives were to: determine the profitability of broiler production; evaluate the poverty status and the effect of broiler income on the poverty status of the civil servants; identify the socio-economic factors influencing the level of broiler production; and describe the constraints of broiler production. Data from 120 members of Poultry Association of Nigeria (PAN) who are civil servants, were analysed using descriptive and inferential statistics. Majority of the civil servants that engaged in broiler farmers were women. Findings revealed that the influx of new entrants into broiler production in recent times was due to the ban on importation of frozen poultry product by the Federal Government of Nigeria which create high demand-supply gap. The civil servants’ broiler producers earned a profit margin of 58% and return on investment of ₦1.67 per Naira invested. This resulted into reduced FGT poverty indices. The level of broiler production were significantly determined by sex, level of education and experience at different level of probability. Likewise, the poverty status of the civil servants were significantly affected by salary and income from broiler production at 1 and 5 % levels of probability. Major constraints in broiler production were high cost of feed and vaccines. Government ban on importation of poultry meat is plausible and should be further imbibed by the Nigerian citizens to consume home grown poultry meat.

Indoor Air Pollution: A Review on the Challenges in Third World Countries

Background: The challenges of third-world countries toward curbing indoor air pollution seem insurmountable as its solution is closely linked to their economic incapacities, lifestyle, and existing outdoor air quality. The economic incapacities include types of the cookstove, fuel sources, types of insecticides and pesticides, building patterns, indoor fermentation activities (such as leaving dirty plates and biological waste in the house for a long time), and regulation on the use of deodorants. Aside from the common pollutants from these sources, the reactive chemistry of pollutants leads to other kinds of pollutants which have been reported to be short-lived but dangerous. Objectives: The objectives of the study are to: profile emerging indoor pollutants; examine the pollutant dynamics and their impact on unplanned regions of developing countries; offer solutions to curb indoor pollution in the identified region; elaborate on the cost analysis of existing solutions and how irrelevant they may be due to the rising poverty index; and project how government policies could help in reducing indoor pollution. Design: This paper is a review that wholistically examined indoor pollution. A total of fifty-six articles was reviewed in addition to the data obtained from MERRA-2. Results: The study observed that indoor air pollution dynamics are more complex—compared to outdoor air pollution. It was observed that the possibility to control indoor air pollution is based on the type of pollutants, the reactive chemistry of the pollutants, and ventilation in the building. This review shows that poverty is one of the many reasons why indoor air pollution would be a source of menace for a long time in third-world countries. Several solutions to curbing indoor air pollution were considered with a principal focus on cost and availability. Limitations: Most experimental results that were used to corroborate postulates were obtained from the literature. The accuracy of those experiments and the sensitivity of the equipment used cannot be verified. Conclusion: The plant-based technique was identified as a perfect solution to indoor air pollution control in third-world countries but the local architecture and lifestyle of most third-world countries constitute a threat to its adoption. It was observed that less than 8% of third-world countries have specific Air Quality Acts which have not been amended for decades. Most third-world countries have a general Environmental Act with air quality as a sub-section in the Act with very low fines for violators. The inclusion of indoor air quality as a vital public health issue in third-world countries is necessary for the preservation of lives and posterity.

How do household living conditions and gender-related decision-making influence child stunting in Rwanda? A population-based study.

Child stunting (chronic undernutrition) is a major public health concern in low- and middle-income countries. In Rwanda, an estimated 33% of children are affected. This study investigated the household living conditions and the impact of gender-related decision-making on child stunting. The findings contribute to ongoing discussion on this critical public health issue. In December 2021, a population-based cross-sectional study was conducted in Rwanda's Northern Province; 601 women with children aged 1-36 months were included. Stunting was assessed using low height-for-age criteria. The Multidimensional Poverty Index (MPI) was used to determine household socioeconomic status. Researcher-designed questionnaires evaluated gender-related factors such as social support and household decision-making. Multivariable logistic regression analysis identified risk factor patterns. Six hundred and one children were included in the study; 27.1% (n = 163) were diagnosed as stunted; there was a higher prevalence of stunting in boys (60.1%) than girls (39.9%; p<0.001). The MPI was 0.265 with no significant difference between households with stunted children (MPI, 0.263; 95% confidence interval [CI], 0.216-0.310) and non-stunted children (MPI, 0.265; 95% CI, 0.237-0.293). Most households reported a lack of adequate housing (78.9%), electricity (63.0%), good water sources (58.7%), and proper toilets (57.1%). Male-headed households dominated (92% vs. 8.0%; p = 0.018), and women often shared decision-making with their partners. However, 26.4% of women reported forced sexual intercourse within marriage (Odds Ratio [OR] 1.81; 95% CI, 1.15-2.85). Lack of support during illness ([OR], 1.93; 95% CI, 1.13-3.28) and absence of personal guidance (OR, 2.44; 95% CI, 1.41-4.26) were significantly associated with child stunting. Poverty contributes to child stunting in the Northern Province of Rwanda. Limited social support and women's lack of decision-making power in the household increase stunting rates. Interventions should empower women and address the broader social and economic context to promote both women's and children's health.

СРАВНИТЕЛЬНЫЙ АНАЛИЗ ПОКАЗАТЕЛЕЙ БЕДНОСТИ И МЕР ПОЛИТИКИ ПО ЕЕ МИНИМИЗАЦИИ В РОССИИ И ОДНОЙ ИЗ РАЗВИТЫХ СТРАН (НА ПРИМЕРЕ США)

The article discusses the issues of poverty and policy measures to minimise it in Russia and compares them with the USA. The authors emphasise the specific impact of poverty on political processes, which slows down state action and delays the development of civil society. The link between poverty and demographics, employment, health, education, culture, upbringing, socialisation and morality is examined. The text also discusses the key economic factors affecting poverty in Russia, such as low income, declining social security and deteriorating equality in income distribution. An analysis of poverty indicators in Russia and the USA is presented, poverty minimisation policies are reviewed, policy shortcomings are identified and recommendations for improving the effectiveness of existing poverty minimisation policies are made. The authors emphasise the need to fight poverty to ensure sustainable development of society and to provide social protection to vulnerable groups.

Measuring non-monetary poverty via machine learning and neutrosophic method: Review

Poverty is an emerging problem that most economies are facing today. The study is aimed at exploring research conducted on measuring non-monetary poverty via machine learning. Non-monetary poverty is identified through the following factors: demographics, population, distribution of income, climate, culture, ethnics, and availability of natural and artificial resources. Today, one of the most important aspects of non-monetary poverty measurement is using machine learning for multiple data points other than wealth or income to assess the quality of life of an individual or community. The socioeconomic factors that contribute poverty in emerging nations have also been found using machine learning algorithms. To achieve our goal neutrosophic model and machine learning algorithms were applied. Neutrosophic model used for reviewing the poverty indicators along with ML algorithms. While exploring the utility of machine learning in our study to measure poverty we will find the answers for the following questions: (1) Why it is important to take into consideration of non-monetary approaches while calculating poverty rate? (2) Which machine learning algorithms were used in poverty measurement? (3) What is the future scope of machine learning applications in poverty prediction? In finding answers for those questions, we have analyzed overall 10 papers which were collected according to exclusion and inclusion criteria and the purpose of the selection according to the content of the paper. During the survey it was found out that machine learning gives sophisticated data for identifying non-monetary reasons of poverty and this survey is first that uses machine learning to non-monetary poverty factors.

Impact of Conditional Economic Transfers on Poverty: The case of Equator

This paper analyzes the impact of conditional cash transfers on poverty in the canton of Milagro, Ecuador. Several dimensions were postulated as possible factors influencing poverty rates and their reduction through the allocation of resources to beneficiaries, whose purpose is to improve their quality of life. The dimensions are framed within the scope of coverage, budget allocation, investment, economic characterization, poverty indices, level of improvement in the quality of life and allocation of the items received. The analysis is based on a review of the impact on the poverty of citizens, by conducting a focus group with personnel who work directly with beneficiary families. The study had a mixed approach and a descriptive-diagnostic and non-experimental cross-sectional or sectional design, since the data collection was determined in the period two thousand twenty-two. The findings found in the analysis suggest that poverty rates in the canton of Milagro have no relationship between access to the human development bond and the improvement in the quality of life of the beneficiaries.

Poverty reduction as a factor of ensuring food security in Kazakhstan

Object: One of the key factors of economic security is the economic availability of food. This directly affects the problem of poverty reduction. Today, in Kazakhstan, the decline in real incomes of the population threatens the possibility of meeting the need for high-quality nutrition of citizens. The purpose of the study is to assess the level of poverty in Kazakhstan and develop measures to reduce it.Methods: The research methods were: systematic, the method of economic and statistical data processing, expert evaluation, the method of multidimensional comparative analysis of the level of poverty in the context of the regions of Kazakhstan and the republic as a whole.Findings: It is revealed that Kazakhstan ranks 32nd in the ranking of 113 countries in the world on food security. This is largely determined by the decrease in the availability of food products as a result of the lagging income of the population from the increase in food prices. The decrease in the economic availability of food occurs as a result of the increase in poverty indicators. The methodology for assessing poverty based on the consumer basket does not reflect the real picture and needs to be adjusted. The underestimation of the subsistence minimum directly determines the amount of social payments from the state budget for vulnerable segments of the population, which further aggravates the growth of the number of poor.Conclusions: Based on the analysis, a number of recommendations aimed at combating poverty, including organizational, legislative and financial instruments, are presented. In particular, it is proposed to revise the methodology for assessing the consumer basket; set the poverty line by the subsistence minimum, as is customary in most countries and recommended by international experts; develop state programs to promote youth employment; increase the responsibility of local executive bodies for the implementation of employment programs and the development of regional employment centers.

Analisis Penerapan Standar Masyarakat Miskin di BPS Kota Binjai

Poverty is a condition in which a person or region is unable to improve quality of life or standard of living. Binjai cities are mentioned in a good category in the presentation of poverty compared to other cities in northern Sumatra. This study aims to find out the application of the standards of the poor society in the Central Statistical Authority (BPS) of Binjai City, using qualitative descriptive methods. The research finds that the concept used is that poverty is seen as an inability on the economic side to meet the food base not food measured on the expenditure side, and the concept is confined only to indicators of the poverty line, the presentation of the poor, the depth index of poverty, the index of misery.And there are two types of poverty data: micropoverty data and macro-poverty data.