Determinants of health insurance ownership among women in Kenya: evidence from the 2008–09 Kenya demographic and health survey

Kimani, James; Ettarh, Remare; Warren, Charlotte E.; Bellows, Benjamin

doi:10.1186/1475-9276-13-27

Cited by 84 publications

(142 citation statements)

References 30 publications

(34 reference statements)

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“…Several explanations have been offered. These disparities may be associated with gender inequalities in access to health insurance coverage (29,30). Our findings are consistent with the results of the 2013 Kenya Household Healthcare Expenditure and Utilization Survey (KHEUS) which suggest that women are more likely to have poor access to primary healthcare services due to low health insurance coverage (31).…”

Section: Discussionsupporting

confidence: 88%

“…Our findings are consistent with the results of the 2013 Kenya Household Healthcare Expenditure and Utilization Survey (KHEUS) which suggest that women are more likely to have poor access to primary healthcare services due to low health insurance coverage (31). In general, the most important determinants of health insurance coverage are employment-related factors and income (29,32,33). A possible explanation for these results could be the existence of gender differences in job opportunities with women more likely to engage in informal employment with lack of entitlements such as health insurance than men (28).…”

Section: Discussionmentioning

confidence: 99%

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Access to primary healthcare services and associated factors in urban slums in Nairobi-Kenya

Otieno

Wambiya

Mohamed

et al. 2019

Preprint

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Background: Access to primary healthcare is crucial for the delivery of Kenya’s universal health coverage policy. However, disparities in healthcare have proved to be the biggest challenge for implementing primary care in poor-urban resource settings. In this study, we assessed the level of access to primary healthcare services and associated factors in urban slums in Nairobi-Kenya. Methods: The data were drawn from the Lown scholars’ study of 300 randomly selected households in Viwandani slums (Nairobi, Kenya), between June and July 2018. Access to primary care was measured using Penchansky and Thomas’ model. Access index was constructed using principal component analysis and recoded into tertiles with categories labeled as poor, moderate and highest. Generalized ordinal logistic regression analysis was used to determine the factors associated with access to primary care. The adjusted odds ratios and 95 percent confident intervals were used to interpret the strength of associations. Results : The odds of being in the lowest versus combined moderate and highest access tertile were significantly higher for female than male-headed households (AOR 1.91 [95% CI 1.03-3.54]; p < .05). Households with an average quarterly out-of-pocket healthcare expenditure of ≥$30 had significantly lower odds of being in the lowest versus combined moderate and highest access tertile compared to those spending ≤ $5 quarterly (AOR 0.33 [95% CI 0.50-1.90]; p< .001). Households that sought care from private facilities had significantly higher odds of being in the lowest versus combined moderate and highest access compared to the public facilities (AOR 3.77 [95% CI 2.16-6.56]; p < .05). Conclusion : In Nairobi slums in Kenya, the gender of the household head, out of pocket healthcare expenditure, and source of primary care are significantly associated with access to primary care. Therefore, the universal health coverage program in this setting should be designed with an equity lens so that the most vulnerable groups within the community can have access.

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Section: Discussionsupporting

confidence: 88%

Section: Discussionmentioning

confidence: 99%

Access to primary healthcare services and associated factors in urban slums in Nairobi-Kenya

Otieno

Wambiya

Mohamed

et al. 2019

Preprint

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“…Changes in the characteristics of women who had different levels of education, number of ANC visits and places of residence contributed to an observable change in the uptake of HIV testing. These factors have also been associated with an increased uptake of HIV testing in previous studies [17, 33, 37]. For example, during phase 1, a decrease in the proportion of women with primary education or an increase in the proportion of women residing in rural areas would have resulted in a decrease in the uptake of HIV testing in the absence of the coefficient.…”

Section: Discussionmentioning

confidence: 78%

Factors associated with changes in uptake of HIV testing among young women (aged 15–24) in Tanzania from 2003 to 2012

2016

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BackgroundThis study explored the factors associated with changes in HIV testing uptake among young women in Tanzania, based on an analysis of data from the 2003–2004 Tanzania HIV/AIDS Indicator Survey, and the 2007–2008 and 2011–2012 Tanzania HIV/AIDS and Malaria Indicator Surveys.MethodsThe study population consisted of young women aged 15–24 years at the time of the survey. Multivariate decomposition analysis was used to assess factors associated with changes in HIV testing uptake between the 2003–2004 and 2007–2008 surveys, and between the 2007–2008 and 2011–2012 surveys.ResultsHIV testing uptake among the study population was 7 % in 2003–2004, 31 % in 2007–2008 and 40 % in 2011–2012. The time period of the survey had a substantial effect on the uptake of HIV testing independent of other covariates. The characteristics that were significantly associated with a higher chance of HIV testing uptake across the surveys were age (20–24), education level (primary and secondary), ever being married, having at least one lifetime sexual partner, having a sexually transmitted infection or associated symptoms, and receiving antenatal care.ConclusionsChanges in the study participants’ characteristics in the 2003–2004 survey compared with the 2007–2008 survey were associated with a decrease in HIV testing uptake. Comparing the 2007–2008 survey with the 2011–2012 survey shows that the changes in the participants’ characteristics contributed to 22 % of the changes in HIV testing uptake, while 78 % of the changes were attributed to coefficients.Electronic supplementary materialThe online version of this article (doi:10.1186/s40249-016-0180-3) contains supplementary material, which is available to authorized users.

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“…Households with an educated main earner were more likely to join MHI schemes compared to those where the main earner was illiterate. The influence of education on enrolment in MHI schemes has been documented elsewhere [25–29]. This could be due to better understanding of the concept of health insurance among the educated group.…”

Section: Discussionmentioning

confidence: 95%

Who enrols in voluntary micro health insurance schemes in low-resource settings? Experience from a rural area in Bangladesh

Mahmood

Hanifi

Mia

et al. 2018

Global Health Action

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Background: Micro health insurance (MHI) has proved to be a potential health-financing tool for many developing countries. Bangladesh also included MHI in its current health-financing strategy which aims to achieve universal health coverage. However, low uptake, low renewal and high dropouts have historically challenged financial sustainability of these schemes. Objective: This study aims to identify factors influencing people from low-resource settings, particularly those from Bangladesh, to enrol in MHI schemes. Methods: The study analyses the ‘Amader Shasthya’ MHI scheme operating in Chakaria, a sub-district under Cox’s Bazar district, Bangladesh. A household survey was carried out during May–June 2016 among 2,000 households from the scheme coverage area. The Outreville’s insurance-demand framework was used to identify enrolment influencing factors. Multivariate logistic regression analysis was carried out to identify significant influencing factors of enrolment. Results: Enrolment influencing factors were identified in four dimensions: economic, socio-cultural, demographic and structural. Households with the main income earner having 10+ years of schooling (odds 1.9 [CI 1.2–2.9] compared to illiterate), having financial literacy (odds 1.5 [CI 1.2–1.8] compared to financially illiterate) and being a public/private service holder (odds 1.6 [CI 1.1–2.4] compared to menial labour) were more likely to enrol. Membership in development programmes of NGOs also influenced enrolment decision significantly (odds 1.3 [CI 1.0–1.5]). The presence of chronic illness in household encouraged enrolment (odds 1.5 [CI 1.2–1.8]). Households living closer to health centres were more likely to enrol (odds 2.1 [CI 1.6–2.7]) compared to those living further away. Conclusion: The findings are expected to have significant implications in terms of designing similar health insurance schemes, particularly in terms of designing demand-driven and context adapted schemes that have greater potential to attract a larger client pool, ensure effective risk pooling and eventually expedite the achievement of universal health coverage in low-resource settings.

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Determinants of health insurance ownership among women in Kenya: evidence from the 2008–09 Kenya demographic and health survey

Cited by 84 publications

References 30 publications

Access to primary healthcare services and associated factors in urban slums in Nairobi-Kenya

Access to primary healthcare services and associated factors in urban slums in Nairobi-Kenya

Factors associated with changes in uptake of HIV testing among young women (aged 15–24) in Tanzania from 2003 to 2012

Who enrols in voluntary micro health insurance schemes in low-resource settings? Experience from a rural area in Bangladesh

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