| Literature DB >> 30316228 |
Bolaji Samson Aregbeshola1, Samina Mohsin Khan2.
Abstract
BACKGROUND: There is high reliance on out-of-pocket (OOP) health payments as a means of financing health system in Nigeria. OOP health payments can make households face catastrophe and become impoverished. The study aims to examine the financial burden of OOP health payments among households in Nigeria.Entities:
Keywords: Catastrophic Health Expenditure; Financial Risk Protection; Out-of-Pocket Payments; Poverty; Universal Health Coverag
Mesh:
Year: 2018 PMID: 30316228 PMCID: PMC6186489 DOI: 10.15171/ijhpm.2018.19
Source DB: PubMed Journal: Int J Health Policy Manag ISSN: 2322-5939
Financing Indicators in Nigeria
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| NHIS | 2 |
| OOP payment | 69 |
| FMoH | 7 |
| SMoH | 5 |
| HMBs | 4 |
| LGA health departments | 7 |
| NGOs | 0 |
| Firms health department | 1 |
| Other federal agencies | 5 |
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| Total health expenditure as a share of GDP | 4 |
| Public expenditure on health as a percentage of total health expenditure | 24 |
| Private expenditure on health as a percentage of total health expenditure | 76 |
| OOP expenditure as a percentage of total health expenditure | 73 |
| OOP health expenditure as a percentage of private expenditure on health | 95 |
Abbreviations: NHIS, National Health Insurance Scheme; OOP, out-of-pocket; FMoH, Federal Ministry of Health; SMoH, State Ministries of Health; HMBs, Health Management Boards; LGA, local government area; NGOs, non-governmental organizations; GDP, gross domestic product.
Source: Uzochukwu et al 2015[32] and WHO.[33]
Demographic and Socio-Economic Profile of the Study Population
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| Age | |
| 0-5 | 13.8 (42 015) |
| 6-14 | 24.8 (75 593) |
| 15-24 | 18.4 (56 239) |
| 25-54 | 33.3 (101 588) |
| 55-64 | 5.1 (15 409) |
| 65 and above | 4.6 (14 156) |
| Education of household head | |
| None | 46.6 (142 043) |
| Nursery | 0.1 (246) |
| Primary | 31.6 (96 381) |
| Secondary | 16.7 (50 873) |
| Post-secondary | 5.1 (15 457) |
| Gender of household head | |
| Male | 50.9 (155 206) |
| Female | 49.1 (149 794) |
| Household size | |
| Less than 5 members | 22.5 (68 724) |
| More than 5 members | 77.5 (236 276) |
| Location | |
| Urban | 25.9 (79 116) |
| Rural | 74.1 (225 884) |
| Geo-political zone | |
| North Central | 16.9 (51 693) |
| North East | 12.5 (38 263) |
| North West | 27.7 (84 502) |
| South East | 12.3 (37 663) |
| South South | 15.0 (45 755) |
| South West | 15.5 (47 124) |
| Socio-economic status | |
| Poorest | 0.1 (260) |
| Poorer | 64.1 (195 651) |
| Middle | 35.7 (108 786) |
| Richer | 0.1 (240) |
| Richest | 0 (63) |
| Work status of household head | |
| Employed | 62.8 (191 628) |
| Unemployed | 37.2 (113 372) |
| Health insurance status | |
| Lack health insurance | 77.9 (237 728) |
| Have health insurance | 22.1 (67 332) |
| Type of health facility visited | |
| Public health facility | 95.3 (290 531) |
| Private health facility | 4.7 (14 469) |
| Type of illness suffered | |
| Non-chronic illness | 99.2 (302 408) |
| Chronic illness | 0.8 (2592) |
Incidence and Distribution of Catastrophic OOP Health Payments
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| Headcount (H) | 18.2 | 16.4 | 15.3 | 13.6 | 13.2 | 12.3 |
| Concentration index, C_E | 0.202 | 0.221 | 0.233 | 0.251 | 0.259 | 0.269 |
| Concentration index, C_O | 0.261 | 0.266 | 0.270 | 0.276 | 0.279 | 0.282 |
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| Headcount (H) | 20.5 | 18.6 | 17.5 | 15.5 | 14.8 | 13.7 |
| Concentration index, C_E | 0.244 | 0.266 | 0.284 | 0.310 | 0.315 | 0.339 |
| Concentration index, C_O | 0.841 | 0.841 | 0.841 | 0.842 | 0.842 | 0.842 |
Abbreviation: OOP, out-of-pocket.
Source: Author’s estimates using ADePT and data from HNLSS 2009/2010.
Figure 1
Figure 2Impoverishment Impact of OOP Health Payments
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| Poverty line = PL1 ($1.25 per day) | ||||
| Poverty headcount (%) | 97.9 | 98.7 | 0.8 | 0.8 |
| Poverty gap (Naira) | 2492.2 | 2539.8 | 47.6 | 1.9 |
| Normalized poverty gap (%) | 92.8 | 94.6 | 1.8 | 1.9 |
| Normalized mean positive poverty gap (%) | 94.8 | 95.9 | 1.1 | 1.2 |
| Poverty line = PL2 ($2.00 per day) | ||||
| Poverty headcount (%) | 98.7 | 99.1 | 0.4 | 0.4 |
| Poverty gap (Naira) | 4077.3 | 4133.9 | 56.6 | 1.4 |
| Normalized poverty gap (%) | 94.9 | 96.2 | 1.3 | 1.4 |
| Normalized mean positive poverty gap (%) | 96.1 | 97.0 | 0.9 | 0.9 |
Abbreviation: OOP, out-of-pocket.
Note: Between 2009 and 2010 when the data was collected, the interbank exchange rate was 1US$ = 152 Naira.
Catastrophic and Impoverishing Effects of OOP Health Payments in African Countries
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| Tanzania (2014) | - | 18% | - | - |
| Burkina Faso (2006) | - | 10.8% | - | - |
| Ghana (2010) | 5.2%* | 2.4% | 1.6 | 9.4% |
| Kenya (2017) | - | 6.6% | 1.6 | 2.4% |
| Kenya (2016) | 14.3% | 9.8% | 3.1 | 6.3% |
| Kenya (2012) | 15.5% | 11.4% | 2.7 | 5% |
| Uganda (2015) | 22.8% | - | 4.1 | 18.1% |
| Malawi (2017) | - | 0.7% | 0.9 | 1.8% |
| Mongolia (2016) | 5.5% | 1.1% | 1.6 | 12.0% |
| Mongolia (2012) | 10% | 3.3% | 2.5 | 7.0% |
| Egypt (2015) | 22.4% | 7.1% | 0.4 | 66.6% |
| Senegal (2015) | 6.3% | - | - | - |
| Zambia (2016) | 9.3% | 11.2% | - | - |
| Swaziland (2015) | 9.6% | 2.7% | 1.6 | 7.7% |
Abbreviation: OOP, out-of-pocket.
Source: Brinda et al 2014[22]; Su et al 2006[25]; Akazili 2010[2]; Barasa et al 2017[21]; Kimani et al 2016[20]; Chuma and Maina[19]; Kwesiga et al 2015[24]; Mchenga 2017[47]; Dorjdagva et al 2016[16]; Bredenkamp et al 2012[15]; Rashad and Sharaf 2015[17]; Sene and Cisse 2015[23]; Masiye et al 2016[18]; Ngcamphalala 2015.[26]
* The values are rounded to 1 decimal.