Estimating the potential of beekeeping to alleviate household poverty in rural Uganda.
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ABSTRACT:
SUBMITTER: Amulen DR
PROVIDER: S-EPMC6436742 | biostudies-literature | 2019
REPOSITORIES: biostudies-literature
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Project description:This paper investigates the impact of financial Inclusion on household poverty and vulnerability by constructing a household financial inclusion index using the China Household Finance Survey 2015. It is found that financial Inclusion significantly reduces the probability of poverty and vulnerability of households and has a more significant impact on vulnerable groups such as rural and urban low-income people. Further, financial Inclusion has a more significant effect on poor families that do not receive government support for poverty alleviation and can complement co-insurance mechanisms to help families better cope with vulnerabilities caused by synergistic community shocks. Finally, promoting entrepreneurship and improving risk management capabilities are the main channels of financial Inclusion.
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Project description:In recent years, entrepreneurship has been gaining more prominence as a potential tool for solving poverty in developing countries. This paper mainly examines the relationship between farmer entrepreneurship and rural poverty alleviation in China by assessing the contribution of farm entrepreneurs towards overcoming poverty. Data were collected from 309 employees of farmer entrepreneurships in Guangxi Province through survey questionnaires. Structural equation modeling was used to conduct an analysis of the effects of three identified capabilities of farm entrepreneurs-economic, educational and knowledge, and socio-cultural capabilities-on attitude towards farmer entrepreneurship growth and the qualitative growth of farmer entrepreneurship and how these in turn affect rural poverty, using AMOS 21. The findings show that socio-cultural capability has the greatest influence on farmer entrepreneurship growth (β = 0.50, p<0.001). The qualitative growth of farmer entrepreneurship also more significantly impacts rural poverty (β = 0.69, p<0.001) than attitude towards farmer entrepreneurship growth. This study suggests that policy makers in China should involve more rural farmers in the targeted poverty alleviation strategies of the government by equipping rural farmers with entrepreneurial skills. This can serve as a sustainable, bottom-up approach to alleviating rural poverty in remote areas of the country. The study also extends the literature on the farmer entrepreneurship-rural poverty alleviation nexus in China, and this can serve as a lesson for other developing countries in the fight against rural poverty.
| S-EPMC5875809 | biostudies-literature
Project description:Tracking the progress of the Sustainable Development Goals (SDGs) and targeting interventions requires frequent, up-to-date data on social, economic, and ecosystem conditions. Monitoring socioeconomic targets using household survey data would require census enumeration combined with annual sample surveys on consumption and socioeconomic trends. Such surveys could cost up to $253 billion globally during the lifetime of the SDGs, almost double the global development assistance budget for 2013. We examine the role that satellite data could have in monitoring progress toward reducing poverty in rural areas by asking two questions: (i) Can household wealth be predicted from satellite data? (ii) Can a socioecologically informed multilevel treatment of the satellite data increase the ability to explain variance in household wealth? We found that satellite data explained up to 62% of the variation in household level wealth in a rural area of western Kenya when using a multilevel approach. This was a 10% increase compared with previously used single-level methods, which do not consider details of spatial landscape use. The size of buildings within a family compound (homestead), amount of bare agricultural land surrounding a homestead, amount of bare ground inside the homestead, and the length of growing season were important predictor variables. Our results show that a multilevel approach linking satellite and household data allows improved mapping of homestead characteristics, local land uses, and agricultural productivity, illustrating that satellite data can support the data revolution required for monitoring SDGs, especially those related to poverty and leaving no one behind.
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Project description:BackgroundLittle is known about poverty trends in people with severe mental illness (SMI) over a long time span, especially under conditions of fast socioeconomic development.AimsThis study aims to unravel changes in household poverty levels among people with SMI in a fast-changing rural community in China.MethodTwo mental health surveys, using ICD-10, were conducted in the same six townships of Xinjin county, Chengdu, China. A total of 711 and 1042 people with SMI identified in 1994 and 2015, respectively, participated in the study. The Foster-Greer-Thorbecke poverty index was adopted to measure the changes in household poverty. These changes were decomposed into effects of growth and equity using a static decomposition method. Factors associated with household poverty in 1994 and 2015 were examined and compared by regression analyses.ResultsThe proportion of poor households, as measured by the headcount ratio, increased significantly from 29.8% in 1994 to 39.5% in 2015. Decomposition showed that poverty in households containing people with SMI had worsened because of a redistribution effect. Factors associated with household poverty had also changed during the study period. The patient's age, ability to work and family size were of paramount significance in 2015.ConclusionsThis study shows that the levels of poverty faced by households containing people with SMI has become more pressing with China's fast socioeconomic development. It calls for further integration of mental health recovery and targeted antipoverty interventions for people with SMI as a development priority.
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Project description:ObjectiveTo examine the relationship between household wealth and HIV incidence in rural Uganda over time from 1994 to 2018. In research conducted early in the epidemic, greater wealth (i.e. higher socioeconomic status, SES) was associated with higher HIV prevalence in sub-Saharan Africa (SSA); this relationship reversed in some settings in later years.DesignAnalysis of associations over time in a population-based open cohort of persons 15-49 years from 17 survey-rounds in 28 continuously followed communities of the Rakai Community Cohort Study (RCCS).MethodsThe RCCS sample averaged 8622 individuals and 5387 households per round. Principal components analysis was used to create a nine-item asset-based measure of household wealth. Poisson regression with generalized estimating equation (GEE) and exchangeable correlation structure was used to estimate HIV incidence rate ratios (IRRs) by SES quartile, survey-round, sex, and age group.ResultsFrom 1994 to 2018, SES rose considerably, and HIV incidence declined from 1.45 to 0.40 per 100 person-years (IRR = 0.39, 95% CI = 0.32--0.47, P < 0.001). HIV incidence was similar by SES category in the initial survey intervals (1994-1997); however, higher SES groups showed greater declines in HIV incidence over time. Multivariable analyses showed significant associations between HIV incidence and SES (IRR = 0.55 for highest compared with lowest quartile, 95% CI = 0.45--0.66, P < 0.001) controlling for time, sex, and age group.ConclusionBeyond the early years of the RCCS, higher SES was associated with lower HIV incidence and SES gradients widened over time. The poor, like other key populations, should be targeted for HIV prevention, including treatment as prevention.
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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.
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Project description:Young children in low- and middle-income countries (LMICs) are vulnerable to adverse effects of household microenvironments. The UN Sustainable Development Goals (SDGs)-specifically SDG 3 through 7-urge for a comprehensive multi-sector approach to achieve the 2030 goals. This study addresses gaps in understanding the health effects of household microenvironments in resource-poor settings. It studies associations of household microenvironment variables with episodes of acute respiratory infection (ARI) and diarrhoea as well as with stunting among under-fives using logistic regression. Comprehensive data from a nationally representative, cross-sectional demographic and health survey (DHS) in Uganda were analysed. We constructed and applied the multidimensional energy poverty index (MEPI) and the three-dimensional women empowerment index in multi-variate regressions. The multidimensional energy poverty was associated with higher risk of ARI (OR = 1.32, 95% CI 1.10 to 1.58). Social independence of women was associated with lower risk of ARI (OR= 0.91, 95% CI 0.84 to 0.98), diarrhoea (OR = 0.93, 95% CI 0.88 to 0.99), and stunting (OR = 0.83, 95% CI 0.75 to 0.92). Women's attitude against domestic violence was also significantly associated with episodes of ARI (OR = 0.88, 95% CI 0.82 to 0.93) and diarrhoea (OR = 0.89, 95% CI 0.84 to 0.93) in children. Access to sanitation facilities was associated with lower risk of ARI (OR = 0.55, 95% CI 0.45 to 0.68), diarrhoea (OR = 0.83, 95% CI 0.71 to 0.96), and stunting (OR = 0.64, 95% CI 0.49 to 0.86). Investments targeting synergies in integrated energy and water, sanitation and hygiene, and women empowerment programmes are likely to contribute to the reduction of the burden from early childhood illnesses. Research and development actions in LMICs should address and include multi-sector synergies.
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Project description:Many policies attempt to help extremely poor households build sustainable sources of income. Although economic interventions have predominated historically1,2, psychosocial support has attracted substantial interest3-5, particularly for its potential cost-effectiveness. Recent evidence has shown that multi-faceted 'graduation' programmes can succeed in generating sustained changes6,7. Here we show that a multi-faceted intervention can open pathways out of extreme poverty by relaxing capital and psychosocial constraints. We conducted a four-arm randomized evaluation among extremely poor female beneficiaries already enrolled in a national cash transfer government programme in Niger. The three treatment arms included group savings promotion, coaching and entrepreneurship training, and then added either a lump-sum cash grant, psychosocial interventions, or both the cash grant and psychosocial interventions. All three arms generated positive effects on economic outcomes and psychosocial well-being, but there were notable differences in the pathways and the timing of effects. Overall, the arms with psychosocial interventions were the most cost-effective, highlighting the value of including well-designed psychosocial components in government-led multi-faceted interventions for the extreme poor.
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Project description:The study develops a theoretical framework of how irrigation and drainage infrastructure and rural transportation infrastructure influence poverty. Using panel data on 31 provinces in China from 2002 to 2017, this paper estimates basic and continuous difference-in-differences (DID) models to investigate the preliminary impact of irrigation and drainage infrastructure and rural transportation infrastructure on poverty and further explores the influence mechanisms of these rural infrastructures on poverty by using the mediating effect model. The results show that irrigation and drainage facilities infrastructure can directly reduce poverty. On the one hand, rural transportation infrastructure directly leads to rural hollowing out and aggravates rural poverty; on the other hand, it indirectly promotes poverty reduction by stimulating economic growth. Overall, the positive and negative effects of rural transportation infrastructure on poverty offset each other.
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