Association between health insurance membership and anaemia among children under-five years. Evidence from Ghana

Anaba, Emmanuel Anongeba; Abuosi, Aaron Asibi; Azilaku, Joshua Cobby; Nkrumah, Jacqueline

doi:10.1371/journal.pone.0238792

Cited by 8 publications

(5 citation statements)

References 32 publications

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“…Mothers who are not aware of NHIS coverage on malaria at the health facility are more likely to have their children suffer severe and moderate anaemia compared to those who are aware. Similar findings were reported by previous studies [ 47 – 49 ]. These studies reported that health insurance coverage serves as a protective factor against childhood anaemia and improves child health outcomes.…”

Section: Discussionsupporting

confidence: 93%

Multinomial logistic regression analysis of the determinants of anaemia severity among children aged 6–59 months in Ghana: new evidence from the 2019 Malaria Indicator Survey

2023

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Background Anaemia among children under age five is a major public health issue. Although anaemia prevalence is declining in Ghana, the severity among anaemic children is worsening. This study aims to investigate the determinants of anaemia severity among children aged 6 to 59 months in Ghana. Method The study utilized a weighted sample of 1,258 children with anaemia with data obtained from the 2019 Ghana Malaria Indicator Survey. The predictor variables included maternal, household child and health system characteristics. SPSS version. At the multivariate level, three different multinomial logistic models were run with selected predictor variables. All tests were conducted at the 95% confidence level. Results The overall anaemia prevalence among children under age five was 43.5%. Of these, 2.6% were severely anaemic, 48.5% were moderately anaemic, and 48.9% had mild anaemia. The multinomial analysis showed that maternal, household, child and health system factors significantly predicted anaemia levels among anaemic children. The results indicate that a lower likelihood of anaemia severity is likely to be found among children whose mothers belong to Pentecostal/Charismatic faith (AOR = 0.18-model I; AOR = 0.15-model III) and children who tested negative for malaria (AOR = 0.28-model II and III). Again, a higher probability of anaemia severity was found among anaemic children whose mothers were not aware of NHIS coverage of malaria (AOR = 2.41-model II, AOR = 2.60-model III). With regard to moderate anaemia level, children who belong to the poorest, poorer and middle household wealth index had a higher likelihood of being moderately anaemic compared to those in rich households. Similarly, anaemic children who were less than 12 months old (AOR = 2.21-model II, AOR = 2.29-model III) and those between the ages of 1–2 years (AOR = 1.84-model II, AOR = 1.83-model III) were more likely to have moderate anaemia levels. Conclusion The study findings show the importance of understanding the interrelation among different factors that influence anaemia severity among children under age five as critical in developing strategies and programmes aimed at addressing childhood anaemia.

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Section: Discussionsupporting

confidence: 93%

Multinomial logistic regression analysis of the determinants of anaemia severity among children aged 6–59 months in Ghana: new evidence from the 2019 Malaria Indicator Survey

2023

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“…In agreement with previous studies on the significant association between maternal health insurance coverage and child’s health outcome in Ghana [ 50 , 51 ] and other SSA countries [ 52 ], our findings further showed that the risk of under-five death was significantly lower among the children of mothers who were covered by health insurance and explained the importance of universal access to health insurance schemes in reducing the risks of U-5 M. As observed in previous studies [ 53 , 54 ], this plausibly revealed the negative implications of mothers’ financial constraints in seeking healthcare, especially on their children’s health outcomes. This suggests the need for the expansion of health insurance schemes to every child under the age of 5 years, as well as accrediting health insurance schemes at the primary and private healthcare facilities to ensure the enrolment of disadvantaged people.…”

Section: Discussionsupporting

confidence: 93%

The impact of maternal health insurance coverage and adequate healthcare services utilisation on the risk of under-five mortality in Nigeria: a cross-sectional study

2022

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Background Despite the progress in reducing under-five mortality (U-5 M) in recent years, these deaths remain considerably high in Nigeria. This could be attributed to poor health policies including inequality of health insurance coverage and access to adequate healthcare services utilisations which has remained inimical to achieving sustainable development goals (SDGs). Therefore, this study examined the impact of maternal health insurance coverage and adequate healthcare services utilisation on the risk of U-5 M in Nigeria. Methods The data for the study were derived from the 2018 Nigeria Demographic and Health Survey and comprised a weighted sample of 127,545 birth histories of childbearing women. Descriptive and analytical analyses were carried out, including frequency tables and multivariate using Cox proportional regression. The results were presented as hazard ratios (HR) with 95% confidence intervals (CIs). Data were analyzed using Stata software version 15.1. Results The results showed that 14.3% of the sampled birth histories of the childbearing women were children who died before age 5. The results further showed that 97.7% of the children were of mothers who have health insurance and over one-half (56.5%) were children whose mothers had adequate healthcare services utilisation. The risk of under-five death was significantly lower among the children of mothers who were covered by health insurance (HR: 0.66, CI: 0.42–1.02) and those whose mothers utilised adequate healthcare services (HR: 0.78, CI: 0.68–0.90). A similar result was observed among children whose mothers reported that distance to the health facility was not a problem (HR: 0.81, CI: 0.72–0.86). Some mothers’ characteristics including educational attainment, wealth quintile and region of residence significantly influenced the risk of U-5 M. Conclusions The study established that maternal health insurance coverage and adequate healthcare services utilisation were found to be protective factors against the risk of U-5 M. Also, the revealed low health insurance coverage of mothers calls for more pragmatic policy and intervention programmes through health insurance to achieve SDGs targets of ending preventable deaths of children under 5 years of age and ensuring quality, as well as universal access to maternal and child healthcare services.

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“…Prior studies among the adult population showed that health insurance enrolment was associated with educational status, wealth, age, marital status, gender, type of occupation and place of residence [ 23 – 25 ]. In addition, an analysis of the 2011 Ghana Multiple Indicator Cluster Survey (MICS) revealed that a majority (73%) of children under five years were non-insured [ 26 ]. However, there is a paucity of literature on determinants of health insurance enrolment among children under five years.…”

Section: Introductionmentioning

confidence: 99%

Factors associated with health insurance enrolment among Ghanaian children under the five years: analysis of secondary data from a national survey

Anaba

Tandoh

Sesay

et al. 2022

BMC Health Serv Res

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Background Health insurance enrolment provides financial access to health care and reduces the risk of catastrophic healthcare expenditure. Therefore, the objective of this study was to assess the prevalence and correlates of health insurance enrolment among Ghanaian children under five years. Methods We analysed secondary data from the 2017/18 Ghana Multiple Indicator Cluster Survey. The survey was a nationally representative weighted sample comprising 8,874 children under five years and employed Computer Assisted Personal Interviewing to collect data from the participants. In addition, Chi-square and Logistic Regression analyses were conducted to determine factors associated with health insurance enrolment. Results The results showed that a majority (58.4%) of the participants were insured. Health insurance enrollment was associated with child age, maternal educational status, wealth index, place of residence and geographical region (p < 0.05). Children born to mothers with higher educational status (AOR = 2.14; 95% CI: 1.39–3.30) and mothers in the richest wealth quintile (AOR = 2.82; 95% CI: 2.00–3.98) had a higher likelihood of being insured compared with their counterparts. Also, children residing in rural areas (AOR = 0.75; 95% CI: 0.61–0.91) were less likely to be insured than children in urban areas. Conclusion This study revealed that more than half of the participants were insured. Health insurance enrolment was influenced by the child's age, mother's educational status, wealth index, residence, ethnicity and geographical region. Therefore, interventions aimed at increasing health insurance coverage among children should focus on children from low socio-economic backgrounds. Stakeholders can leverage these findings to help improve health insurance coverage among Ghanaian children under five years.

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Association between health insurance membership and anaemia among children under-five years. Evidence from Ghana

Cited by 8 publications

References 32 publications

Multinomial logistic regression analysis of the determinants of anaemia severity among children aged 6–59 months in Ghana: new evidence from the 2019 Malaria Indicator Survey

Multinomial logistic regression analysis of the determinants of anaemia severity among children aged 6–59 months in Ghana: new evidence from the 2019 Malaria Indicator Survey

The impact of maternal health insurance coverage and adequate healthcare services utilisation on the risk of under-five mortality in Nigeria: a cross-sectional study

Factors associated with health insurance enrolment among Ghanaian children under the five years: analysis of secondary data from a national survey

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