Dynamic reflections of multidimensional health poverty in Pakistan
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ABSTRACT:
SUBMITTER: Mustafa K
PROVIDER: S-EPMC8570466 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:ObjectivesTo identify the chronic health conditions associated with multidimensional poverty.DesignCross-sectional study of the nationally representative Survey of Disability, Ageing and Carers, conducted by the Australian Bureau of Statistics.SettingAustralian population in 2003.Participants35 704 individuals randomly selected from the Australian population by the Australian Bureau of Statistics.Outcome measuresMultidimensional poverty status, costs of disability, short form 6D health utility score, income, education attainment.ResultsAmong those who were multidimensionally poor, 75% had a chronic health condition and the most common health conditions were back problems (11% of those in multidimensional poverty had back problems) and arthritis (11%). The conditions with the highest proportion of individuals in multidimensional poverty were depression/mood affecting disorders (26% in multidimensional poverty) and mental and behavioural disorders (22%). Those with depression/mood affecting disorders were nearly seven times (OR 6.60, 95% CI 5.09 to 8.55, p<0.0001) more likely to be multidimensionally poor than those with no health condition. Equivalising for the additional costs of disability increased the proportion of individuals in multidimensional poverty for all conditions and the conditions with the highest proportion of individuals in multidimensional poverty changed.ConclusionsOwing to the influence of certain health conditions on poverty status, health interventions have the potential to improve national living standards and poverty rates in a similar way that 'traditional' policy responses such as changes to welfare payment currently do. Using a multidimensional poverty measure reveals the health conditions that should be the focus of such efforts.
| S-EPMC3845066 | biostudies-literature
Project description:Though the concept of multidimensional poverty has been acknowledged cutting across the disciplines (among economists, public health professionals, development thinkers, social scientists, policy makers and international organizations) and included in the development agenda, its measurement and application are still limited. OBJECTIVES AND METHODOLOGY: Using unit data from the National Family and Health Survey 3, India, this paper measures poverty in multidimensional space and examine the linkages of multidimensional poverty with child survival. The multidimensional poverty is measured in the dimension of knowledge, health and wealth and the child survival is measured with respect to infant mortality and under-five mortality. Descriptive statistics, principal component analyses and the life table methods are used in the analyses.The estimates of multidimensional poverty are robust and the inter-state differentials are large. While infant mortality rate and under-five mortality rate are disproportionately higher among the abject poor compared to the non-poor, there are no significant differences in child survival among educationally, economically and health poor at the national level. State pattern in child survival among the education, economical and health poor are mixed.Use of multidimensional poverty measures help to identify abject poor who are unlikely to come out of poverty trap. The child survival is significantly lower among abject poor compared to moderate poor and non-poor. We urge to popularize the concept of multiple deprivations in research and program so as to reduce poverty and inequality in the population.
| S-EPMC3203176 | biostudies-other
Project description:The Multidimensional Poverty Index is used increasingly to measure poverty in developing countries. The index is constructed using selected indicators that cover health, education, and living standards dimensions. The accuracy of this tool, however, depends on how each indicator is measured. This study explores the effect of accounting for water quality in multidimensional poverty measurement. Access to drinking water is traditionally measured by water source types. The study uses a more comprehensive measure, access to safely managed drinking water services, which are free from E. coli contamination, available when needed and accessible on premises in line with Sustainable Development Goal target 6.1. The study finds that the new measure increases national multidimensional headcount poverty by 5-13 percentage points, which would mean that 5-13 million more people are multidimensionally poor. It also increases the poverty level in urban areas to a greater extent than in rural areas. The finding is robust to changes in water contamination risk levels and Multidimensional Poverty Index aggregation approaches and weighting structures.
| S-EPMC7737968 | biostudies-literature
Project description:According to the global Multidimensional Poverty Index (MPI), an internationally comparable measure, poverty in developing countries has fallen substantially over the last 15 years. The COVID-19 pandemic and associated economic contraction are negatively impacting multiple dimensions of poverty and jeopardising this progress. This paper uses recent assessments of food insecurity and school closures made by UN agencies to inform microsimulations of potential short-term impacts of the pandemic under alternative scenarios. These simulations use the nationally representative datasets underlying the 2020 update of the global MPI. Because these datasets were collected in various years before the pandemic, we develop models to translate the simulated impacts to 2020. Our approach accounts for the country-specific joint distribution of deprivations in the simulations, recent poverty reduction trends, and resulting differences in the responsiveness of the global MPI to the scenarios. Aggregating results across 70 countries that account for 89% of the global poor according to the 2020 global MPI, we find that the potential setback to multidimensional poverty reduction is between 3.6 and 9.9 years under the alternative scenarios. We argue that the extent to which such disruptions result in persistent increases of poverty and deprivations may be attenuated by appropriate policy responses.
| S-EPMC8500841 | biostudies-literature
Project description:IntroductionNarrow, unidimensional measures of poverty often fail to measure true poverty and inadequately capture its drivers. Multidimensional indices of poverty more accurately capture the diversity of poverty. There is little research regarding the association between multidimensional poverty and depression.MethodsA cross-sectional survey was administered in five sub-locations in Migori County, Kenya. A total of 4,765 heads of household were surveyed. Multidimensional poverty indices were used to determine the association of poverty with depression using the Patient Health Questionnaire (PHQ-8) depression screening tool.ResultsAcross the geographic areas surveyed, the overall prevalence of household poverty (deprivation headcount) was 19.4%, ranging from a low of 13.6% in Central Kamagambo to a high of 24.6% in North Kamagambo. Overall multidimensional poverty index varied from 0.053 in Central Kamagambo to 0.098 in North Kamagambo. Of the 3,939 participants with depression data available, 481 (12.2%) met the criteria for depression based on a PHQ-8 depression score ≥10. Poverty showed a dose-response association with depression.ConclusionsMultidimensional poverty indices can be used to accurately capture poverty in rural Kenya and to characterize differences in poverty across areas. There is a clear association between multidimensional poverty and depressive symptoms, including a dose effect with increasing poverty intensity. This supports the importance of multifaceted poverty policies and interventions to improve wellbeing and reduce depression.
| S-EPMC8594838 | biostudies-literature
Project description:One in three Cambodian children under 5 years of age are stunted. This study adopted a multidimensional approach to understand the influence of a series of contextual factors on the nutritional status of Cambodian children. In this study, we use a multidimensional poverty framework to identify a combination of interventions likely to achieve reductions in child stunting, in Cambodia. We used the UNICEF Multiple Overlapping Deprivation Analysis tool and data from the Cambodia Demographic and Health Survey 2014 to assess children's multidimensional poverty across nutrition, health, early childhood development, water, sanitation, and housing dimensions. We found that 80% of children under age five were deprived in at least two poverty dimensions. Multivariate logistic regression analysis revealed that reducing the likelihood of being deprived in three or more poverty dimensions was associated with a significant reduction of the probability of being stunted, after controlling for potential confounders. The combined probability of nondeprivation in nutrition, sanitation, and health dimensions had the largest effect on reducing the probability of stunting. The results of this study highlight the multiple, intersecting needs of children and their associated explanatory factors. Targeted and integrated cross-sectoral policies that reinforce comprehensive early childhood interventions are needed for improving nutritional status as part of a wider set of child poverty reduction measures in Cambodia.
| S-EPMC7591312 | biostudies-literature
Project description:Quantifying eye movement is important for diagnosing various neurological and ocular diseases as well as AR/VR displays. We developed a simple setup for real-time dynamic gaze tracking and accommodation measurements based on Purkinje reflections, which are the reflections from front and back surfaces of the cornea and the eye lens. We used an accurate eye model in ZEMAX to simulate the Purkinje reflection positions at different focus distances of the eye, which matched the experimental data. A neural network was trained to simultaneously predict vergence and accommodation using data collected from 9 subjects. We demonstrated that the use of Purkinje reflection coordinates in machine learning resulted in precise estimation. The proposed system accurately predicted the accommodation with an accuracy better than 0.22 D using subject's own data and 0.40 D using other subjects' data with two-point calibration in tests performed with 9 subjects in our setup.
| S-EPMC10703819 | biostudies-literature
Project description:Although the association between disability and multidimensional poverty has been consistently found in several studies in Low- and Middle-Income Countries. None of these studies so far has used an extended and internationally comparable questionnaire (extended Washington Group Questionnaire) and a clinical screening of disability. The purpose of this article is to calculate, compare and analyse the levels of multidimensional poverty of people with and without disabilities in Guatemala (national), in one district of Cameroon (Fundong Health District, North West Cameroon) and in one district in India (Mahbubnagar District, Telangana State). We used a case-control study approach; adults with disabilities identified in a population-based disability survey using the Washington Group Extended Questionnaire were matched to age-sex matched controls without disabilities and interviewed about their levels of access and use of different social services. Following the Alkire-Foster method, the levels of multidimensional poverty between cases and control were computed and compared. Additionally, we analysed how disability and other individual characteristics are associated with being poor in each country. The results showed that people with disabilities in all three-study settings face significantly higher levels of poverty and the intensity of their poverty is higher. In the case of Cameroon, differences in the levels of deprivation between people with and without disabilities were smaller than those observed in India and Guatemala. This might suggest that in countries with higher levels of human, economic and social development people with disabilities are being left behind by public policies aiming to reduce poverty and deprivation in basic indicators. In addition, indicators related to health contributed the most to the levels of multidimensional poverty for people with disabilities. These findings provide important evidence about the association of multidimensional poverty and disability and underline the importance of including indicators capturing individual deprivations to analyse poverty for this group.
| S-EPMC7212179 | biostudies-literature
Project description:ObjectiveA focus on bacterial contamination has limited many studies of water service delivery in slums, with diarrheal illness being the presumed outcome of interest. We conducted a mixed methods study in a slum of 12,000 people in Mumbai, India to measure deficiencies in a broader array of water service delivery indicators and their adverse life impacts on the slum's residents.MethodsSix focus group discussions and 40 individual qualitative interviews were conducted using purposeful sampling. Quantitative data on water indicators-quantity, access, price, reliability, and equity-were collected via a structured survey of 521 households selected using population-based random sampling.ResultsIn addition to negatively affecting health, the qualitative findings reveal that water service delivery failures have a constellation of other adverse life impacts-on household economy, employment, education, quality of life, social cohesion, and people's sense of political inclusion. In a multivariate logistic regression analysis, price of water is the factor most strongly associated with use of inadequate water quantity (?20 liters per capita per day). Water service delivery failures and their adverse impacts vary based on whether households fetch water or have informal water vendors deliver it to their homes.ConclusionsDeficiencies in water service delivery are associated with many non-health-related adverse impacts on slum households. Failure to evaluate non-health outcomes may underestimate the deprivation resulting from inadequate water service delivery. Based on these findings, we outline a multidimensional definition of household "water poverty" that encourages policymakers and researchers to look beyond evaluation of water quality and health. Use of multidimensional water metrics by governments, slum communities, and researchers may help to ensure that water supplies are designed to advance a broad array of health, economic, and social outcomes for the urban poor.
| S-EPMC4511227 | biostudies-literature
Project description:Smallholder agriculture in developing countries is characterized by low productivity. Improving the productive efficiency of farm households is considered one of the paths to increase productivity and reduce poverty. This study analyzed the poverty reduction effects of improving the technical efficiency of cereal-producing farm households using plot-level data from rural Ethiopia. The effects were also evaluated whether they were heterogeneous relative to the level of crop diversification. Multidimensional Poverty Index (MPI) and stochastic meta-frontier approach were used to estimate the poverty status and the technical efficiency scores, respectively, and the Herfindahl Index (HI) was used to compute crop diversification. The instrumental Tobit Model was specified to estimate the poverty reduction effect of technical efficiency. Our results revealed that the mean technical efficiency of farm households was estimated to be 58%. The poverty estimate results showed that a higher proportion of farm households were multidimensional poor. The incidence of poverty and the mean deprivation score was found to be 57.9% and 44.1%, respectively. Overall, the value of MPI estimated was 31.2%, implying the farm households experienced 31.2% of the total deprivations across all indicators. The HI was 0.51, indicating a moderate degree of crop diversification among farm households. The model results showed that a 10% increase in technical efficiency significantly drives down the household multidimensional poverty by 15.3% at 1% level, keeping other things being constant. Furthermore, ceteris paribus, a 10% increase in technical efficiency significantly reduces household multidimensional poverty by 7.0% and 7.8% at 1% level among moderately diversified and least diversified farm households, respectively. In conclusion, technical efficiency has a higher effect on multidimensional poverty among moderately diversified and least diversified farm households. Therefore, enhancing the productive capacity of farm households among the lower degree of crop diversification to efficiently use production inputs may assist in poverty reduction.
| S-EPMC8723994 | biostudies-literature