Result
Of 845 sampled households, 808 participated in the study which yielded a response rate of 95.6%. The median age of respondents was 32, ranging 18–87 years. Among them, 574 (71%) were male, 550 (68.1%) Protestant Christians, 519 (64.2%) Bench ethnic groups, 675 (83.5%) married (574 monogamous/monandrous and 101 polygamous), 615 (76.1%) farmers, 388 (48%) were illiterate and 654 (80.9%) were head of the household. The median number of the household members was 5 with range of 1–13. The median annual household income, as estimated from the amount earned from sales of coffee, khat, maize cassava and other local products such as fruits, honey dairy products, etc., in one year time, was 2475 ETB (143 USD), ranging between 100–18,600 ETB (5.8-1075.1 USD). From the analysis of the wealth index, 31.6% of the households were found in the second and 24.0% in the highest wealth quintiles (Table
1).
Table 1
Demographic and socioeconomic characteristics of the study participants in Debub Bench District, Southwest Ethiopia, 2013 (n = 808)
Sex of the respondent | Female | 234 (29.0) |
| Male | 574 (71.0) |
Relationship | Head | 654 (80.9) |
| Spouse | 132 (16.3) |
| Others (Child, parent) | 22 (2.7) |
Religion of the respondent | Protestant | 550 (68.1) |
| Orthodox | 199 (24.6) |
| Muslim | 41 (5.1) |
| Others | 18 (2.2) |
Marital status of the respondent | Monogamous/monandrous | 573 (70.9) |
| Polygamous/polyandrous | 101 (12.5) |
| Single | 55 (6.8) |
| Widowed | 24 (3.0) |
| Divorced | 55 (6.8) |
Occupation of the respondent | Farmer | 615 (76.1) |
| Housewife | 113 (14.0) |
| Merchant | 36 (4.5) |
| Student | 30 (3.7) |
| Others | 14 (1.7) |
Ethnicity of the respondent | Bench | 519 (64.2) |
| Amhara | 116 (14.4) |
| Kaffa | 64 (7.9) |
| Others | 109 (13.5) |
Educational status of the respondent | Illiterate | 388 (48.0) |
| Read and write | 221 (27.4) |
| Grade 1-8 | 178 (22.0) |
| > = Secondary school | 21 (2.6) |
Wealth quintile of the household | Lowest wealth quintile | 70 (8.7) |
| Second wealth quintile | 255 (31.6) |
| Middle wealth quintile | 164 (20.3) |
| Fourth wealth quintile | 125 (15.5) |
| Highest wealth quintile | 194 (24.0) |
Category of annual income | Lower than 1100 birr | 198 (24.5) |
| 1100-4300 birr | 409 (50.6) |
| More than 4300 birr | 201 (24.9) |
Seven hundred and forty seven (92.5%) of the households were participating in iddirs. Out of them 635 (85 were participating in one iddir) and the remaining 112 households in more than one iddirs. The median contribution of the households to iddirs was 1 ETB per month with range of 1–4 ETB.
Regarding individual level social capital, 233 (28.8%), 545 (56.4%) and 119 (14.7%) of the households were of low (lower than the 25th percentile), middle (between 25th and 75th percentiles) and high (above 75th percentiles of horizontal trust index) individual level horizontal trust respectively. Also, 222 (27.5%), 451 (55.8%) and 135 (16.7%) of the households were of low, middle and high individual level reciprocity respectively.
With respect to health status and health related variables, 50 (6.2%) of the respondents evaluated their family’s health status to be very poor and 98 (12.1%) very high. Sixty one (7.5%) of the participants had at least one member with chronic disease or disability; and 250 (30.9%) of the households had at least one member who had encountered illnesses 3 months prior to data collection. Among the ill 231 (92.4%) had sought treatment for the illnesses they experienced, and 219 (94.8%) got treatment. The remaining 12 did not get treatment because, mainly, lack of money (Table
2).
Table 2
Health and health related situations in Debub Bench District, Southwest Ethiopia, 2013
Self-reported health status of the household (n = 808) | Very poor | 50 (6.2) |
| Poor | 166 (20.5) |
| Medium | 270 (33.4) |
| High | 224 (27.7) |
| Very high | 98 (12.1) |
Persons with chronic illness and/or disability in the household (n = 808) | No | 747 (92.5) |
Yes | 61 (7.5) |
Any illness encountered during the past 3 mths (n = 808) | No | 558 (69.1) |
Yes | 250 (30.9) |
Seek of medical treatment for the recent episode (n = 250) | No | 19 (7.6) |
Yes | 231 (92.4) |
Get treatment (n = 231) | No | 12 (5.2) |
| Yes | 219 (94.8) |
Place of treatment (n = 219) | Private Heath Facility | 90 (41.1) |
| Public health center | 65 (29.7) |
| Public hospital | 49 (22.4) |
| Other (self-treatment, traditional healer and local drug vendor) | 15 (6.8) |
Reasons for going there (n = 219) | The HF was physically accessible | 104 (47.5) |
| The HF was not expensive | 18 (8.2) |
| The health facility not too crowded | 19 (8.7) |
| The health service was effective | 66 (30.1) |
| Other (specify) | 12 (5.5) |
Reasons for not getting treatment (n = 12) | No enough money | 9 (75.0) |
Others (too far, self limiting) | 3 (25.0) |
Coverage of the health care cost (n = 219) | Self | 204 (93.2) |
Others (free, community) | 15 (6.8) |
Satisfaction with health care service and costs (n = 219) | Very dissatisfied | 23 (10.5) |
Dissatisfied | 61 (27.9) |
Neutral | 8 (3.7) |
Satisfied | 111 (50.7) |
Very satisfied | 16 (7.3) |
Perceived quality of the health care service in the district (n = 219) | Very low | 20 (9.1) |
Low | 76 (34.7) |
Neutral | 24 (11.0) |
High | 87 (39.7) |
Very high | 12 (5.5) |
Concern of the household for covering health care costs (n = 219) | Very difficult | 77 (35.2) |
Difficult | 110 (50.2) |
Not difficult | 32 (14.6) |
Means of getting money for health care payment (n = 187) | Drew from the savings | 38 (20.3) |
Borrow from someone | 27 (14.4) |
Assisted by relatives | 68 (36.4) |
Undertaken extra work | 2 (1.1) |
Sell capital assets such as cows | 33 (17.6) |
Cut back on other things, food, etc. | 19 (10.2) |
Borrow money for medical costs within last year (n = 808) | No | 530 (65.6) |
Yes | 278 (34.4) |
The nearest conventional health institution to the respondents’ home (n = 808) | Health center | 373 (46.2) |
Clinic (Private) | 367 (45.4) |
Hospital (Gov) | 68 (8.4) |
Of 219 who got treatment, 41.1% preferred to go to private clinics. They preferred the specified institutions because of its physical accessibility (47.5%), effective service (30.1%), not too crowded (8.7%), not expensive services (8.2%), or other reasons (5.5%) (Table
2).
The median expenditure of the 219 households which sought treatments was 170 ETB with range of 18 to 2000 ETB. Two hundred and four (93.2%) of the households covered the medical expenses by themselves. One hundred and eighty seven (85.4%) of these households reported that it was (very) difficult to cover payments for treatments. As a result, 68 (36.4%) of them were assisted by relatives to cover the medical costs; 38 (20.3%) drew from their savings, and 27 (14.4%) borrowed from someone. The remaining had to sell capital assets such as cows (17.6%), cut back on other things, food, drink, cloth etc. (9.1%), undertook extra works and search for other means (2.2%) to cover the payments for treatment (Table
2).
Of 808 respondents, 278 (34.4%) reported that they had borrowed money for covering health care expenses within one year before the data were collected. The median amount that these households borrowed was 200 ETB (11.6 USD), ranging 30–2000 ETB (1.7-115.6 USD) (Table
2).
Regarding the distance of home of the household to the nearby health facility (private clinics, health centre or public hospital), it was reported that the median time it takes to reach the nearby health facility was 50 minutes, range between 3 minutes to 180 minutes (Table
2).
Among the participants, 629 (77.8%) were willing to join the proposed community based health insurance. Four hundred and seventy five (75.5%) of the respondents wanted to join the scheme to get free access to health care. And, 59 (33%) of 179 respondents did not want to join the scheme because they do not need health insurance (Table
3).
Table 3
Willingness to join community based health insurance, reasons for joining and not willing to join the scheme in Debub Bench District, Southwest Ethiopia, 2013
Willingness to join community based health insurance scheme (n = 808) |
Yes | 729 (77.8) |
No | 179 (22.2) |
Reasons for joining the schemes (n = 629) |
It provides free access to medical care | 475 (75.5) |
To help others | 29 (4.6) |
For security and peace of mind in times of ill-health | 79 (12.6) |
Facing health problem frequently | 45 (7.2) |
Other (specify) | 1 (0.2) |
Reasons for not joining the scheme (n = 179) |
I do not have enough money to pay | 44 (24.6) |
Do not need health insurance | 59 (33.0) |
Out-of pocket charge is better | 17 (9.5) |
Lack of trust in government programmes | 8 (4.5) |
Lack of functional HF in my village | 24 (13.4) |
H/insurance is a confusing scheme | 14 (7.8) |
Others | 13 (7.3) |
The study revealed that a number of variables affect the households’ decision in willingness to join the proposed community based health insurance scheme. In multivariate analyses, most of the demographic variables (age, relationship of the respondent to the household head, marital status, occupation and ethnicity of the respondent, as well as the household’s family size) were significantly associated with WTJ the CBHIS.
Age had negative associations with the probability of WTJ the CBHIS. The younger were 6% more likely to join the scheme than the older (95% CI of AOR: .914, .974). Spouses were 59% less likely to join the scheme, in comparison with heads of the households (95% CI of AOR: .174, .967). In comparison to monogamous/monandrous, the single were 87.7% less likely to join the scheme (95% CI of AOR: .032, .474). Occupationally, housewives were more likely to join the scheme than farmers (AOR = 11.917; 95% CI AOR: [4.017, 35.357]). Ethnically, households which belong to Kaffa ethnicity were 81.6% less likely to join the scheme than Bench (95% CI of AOR: .072, .468). Size of the family was positively associated with WTJ decisions of the households. As the number of the household members increase, the probability of WTJ increased by 69% (95% CI AOR: 1.363, 2.099) (Table
4).
Table 4
Factors which are associated with willingness to join community based health insurances in Debub Bench, 2013
Demographic variables | |
Age | | 629 (78) | 179 (22) | .000 | 1.035 | .943 [.914, .974] |
Relationship
| 808 (100) | 629 (78) | 179 (22) | .007 | | |
Head* | 654 (80.9) | 519 (79) | 135 (21) | | | |
Spouse | 132 (16.3) | 97 (73) | 35 (27) | .042 | .721 | .410 [.174, .967] |
Others | 22 (2.7) | 13 (59) | 9 (41) | .015 | .376 | 18.523 [1.762, 194.6] |
Religion†
| 808 (100) | 629 (78) | 179 (22) | .869 | | |
Protestant* | 550 (68.1) | 431 (78) | 119 (22) | | | |
Orthodox | 199 (24.6) | 160 (80) | 39 (20) | .936 | 1.133 | .965 [.410, 2.275] |
Muslim | 41 (5.1) | 24 (58) | 17 (42) | .957 | .390 | 1.042 [.233, 4.650] |
Others | 18 (2.2) | 14 (78) | 4 (22) | .406 | .996 | 2.056 [.375, 11.262] |
Marital status
| 808 (100) | 629 (78) | 179 (22) | .019 | | |
Monogamous* | 573 (70.9) | 458 (80) | 115 (20) | | | |
Polygamous | 101(12.5) | 84 (83) | 17 (17) | .061 | 1.241 | .409 [.160, 1.043] |
Single | 55 (6.8) | 25 (45) | 30 (55) | .002 | .209 | .123 [.032, .474] |
Widowers | 24 (3.0) | 19 (79) | 5 (21) | .996 | .954 | .996 [.171, 5.814] |
Divorced | 55 (6.8) | 43 (78) | 12 (22) | .929 | .900 | .950 [.304, 2.971] |
Occupations
| 808 (100) | 629 (78) | 179 (22) | .000 | | |
Farmers* | 615 (76.1) | 501 (81) | 114 (19) | | | |
Housewives | 113 (14.0) | 87 (77) | 26 (23) | .000 | .761 | 11.917 [4.017, 35.357] |
Merchants | 36 (4.5) | 19 (53) | 17 (47) | .769 | .254 | .821 [.221, 3.046] |
Students | 30 (3.7) | 14 (47) | 16 (53) | .443 | .199 | .521 [.098, 2.760] |
Others | 14 (1.7) | 8 (57) | 6 (43) | .025 | .303 | .088 [.011, .738] |
Ethnicity
| 808 (100) | 629 (78) | 179 (22) | .000 | | |
Bench* | 519 (64.2) | 404 (78) | 115 (22) | | | |
Amhara | 116 (14.4) | 88 (76) | 28 (24) | .341 | .895 | 1.557 [.626, 3.875] |
Kaffa | 64 (8.0) | 41 (64) | 23 (36) | .000 | .507 | .184 [.072, .468] |
Others | 109 (13.5) | 96 (88) | 13 (12) | .004 | 2.102 | 5.306 [1.682, 16.733] |
Total family size | | | | .000 | | 1.691 [1.363, 2.099] |
Socioeconomic variables |
Educational-status
| 808 (100) | 629 (78) | 179 (22) | .001 | | |
No education* | 388 (48.0) | 316 (81) | 72 (19) | | | |
Read & write only | 221 (27.3) | 176 (80) | 45 (20) | .045 | .891 | 2.134 [1.017, 4.479] |
Grade 1-8 | 178 (22.0) | 124 (70) | 54 (30) | .007 | .523 | .321 [.140, .738] |
Sec and above | 21 (2.6) | 13 (62) | 8 (38) | .864 | .370 | 1.205 [.143, 10.161] |
Wealth quintile
| 808 (100) | 629 (78) | 179 (22) | .002 | | |
Low wealth quintile | 70 (8.7) | 48 (69) | 22 (31) | .451 | .778 | 1.559 [.492, 4.938] |
Second wealth quintile* | 255 (31.6) | 188 (74) | 67 (26) | | | |
Middle wealth quintile | 164 (20.3) | 124 (76) | 40 (24) | .082 | 1.105 | .481 [.211, 1.097] |
Fourth wealth quintile | 125 (15.5) | 94 (75) | 31 (25) | .375 | 1.081 | .672 [.279, 1.618] |
Highest wealth quintile | 194 (24.0) | 175 (90) | 19 (10) | .003 | 3.282 | 4.203 [1.616,10.931] |
Annual income
| 808 (100) | 629 (78) | 179 (22) | .003 | | |
Less than 1100 birr | 198 (24.5) | 133 (67) | 65 (33) | .008 | .470 | .475 [.274, .823] |
1100-4300 birr* | 409 (50.6) | 326 (80) | 83 (20) | | | |
More than 4300 birr | 201 (24.9) | 170 (85) | 31 (15) | .180 | 1.768 | 1.500 [.830, 2.712] |
Participation in risk sharing organizations |
No. of risky to become ill† | | | | .887 | 1.322 | .980 [.780, 1.300] |
Iddir participation
| 808 (100) | 629 (78) | 179 (22) | | | |
Yes* | 747 (92.5) | 603 (81) | 144 (19) | | | |
No | 61 (7.5) | 26 (43) | 35 (57) | .139 | | .427 [.138, 1.320] |
Social capital |
Indiv level hor trust
| 808 (100) | 629 (78) | 179 (22) | .000 | | |
Low | 233 (28.8) | 144 (62) | 89 (38) | .000 | .339 | .064 [.025, .165] |
Middle* | 456 (56.4) | 377 (83) | 79 (17) | | | |
High | 119 (14.7) | 108 (91) | 11 (9) | .238 | 2.057 | 2.284 [.580, 9.000] |
Indiv level reciprocity
| 808 (100) | 629 (78) | 179 (22) | .050 | | |
Low | 222 (27.5) | 136 (61) | 86 (39) | .952 | .341 | .975 [.435, 2.187] |
Middle* | 451 (55.8) | 371 (82) | 80 (18) | | | |
High | 135 (16.7) | 122 (90) | 13 (10) | .015 | 2.024 | 4.959 [1.362, 18.052] |
Commun level hor trust
| 808 (100) | 629 (78) | 179 (22) | | | |
High | 158 (19.6) | 146 (92) | 12 (8) | .000 | 4.207 | 25.233 [6.355, 100.195] |
Low* | 650 (80.4) | 483 (74) | 167 (26) | | | |
Health and health related variables |
Health status of the HH
| 808 (100) | 629 (78) | 179 (22) | .000 | . | |
Very poora
| 50 (6.2) | 48 (96) | 2 (4) | .996 | 4.546 | |
Poor | 166 (20.5) | 145 (87) | 21 (13) | .456 | 1.308 | 1.391 [.584, 3.315] |
Medium* | 270 (33.4) | 227 (84) | 43 (16) | | | |
High | 224 (27.8) | 159 (71) | 65 (29) | .012 | .463 | .381 [.179, .811] |
Very high | 98 (12.1) | 50 (51) | 48 (49) | .000 | .197 | .165 [.068, .402] |
Member with chronic illness† | 808 (100) | 629 (78) | 179 (22) | | | |
Yes | 61 (7.5) | 57 (93) | 4 (7) | .476 | 4.360 | 1.563 [.458, 5.337] |
No* | 747 (92.5) | 572 (77) | 175 (23) | | | |
Illness in prev 3 months† | 808 (100) | 629 (78) | 179 (22) | | | |
No* | 558 (69.0) | 404 (72) | 154 (28) | | | |
Yes | 250 (31.0) | 225 (90) | 25 (10) | .817 | 3.431 | 1.182 [.287, 4.869] |
Seeking medical treatment† | 808 (100) | 629 (78) | 179 (22) | | | |
Yes* | 231(28.6) | 212 (92) | 19 (8) | | | |
No | 577 (71.4) | 417 (72) | 160 (28) | .231 | 0.194 | 6.338 [.308, 130.434] |
Borrow for treatment | 808 (100) | 629 (78) | 179 (22) | | | |
No* | 530 (65.6) | 381 (72) | 149 (28) | | | |
Yes | 278 (34.4) | 248 (89) | 30 (11) | .004 | 3.233 | 2.836 [1.403, 5.730] |
Time to HF (in minutes) | 808 (100) | 629 (78) | 179 (22) | .001 | .991 | .983 [.973, .992] |
Constant | | | | .340 | | 2.355 |
Socioeconomic statuses of the respondents (educational status, wealth index and annual incomes) had also statistically significant associations with the households’ decision in WTJ the CBHIS. Respondents who had no education were about 3 times more likely to join the scheme than those who completed grade 1–8 (95% CI of AOR: 1.355, 7.143). Households who were in the highest wealth quintile were more than 4 times more likely to join the scheme than those who were in the second wealth quintile (95% CI of AOR: 1.626, 10.931). in the same manner, households with annual income 1100–4300 birrs were 2.105 times more likely to join the scheme than whose income was less than 4300 birrs [95% CI of AOR: 1.215, 3.650] (Table
4).
Participation in iddirs, number of iddirs the households participate in and amount of money the households contribute for iddir were not statistically significant in multivariate analyses. But the variables which measure both individual level and community level social capitals were positively associated with WTJ the CBHIS. Households with low individual level horizontal trust level were 93.6% less likely to join CBHIS than middle level ones (95% CI of AOR: .025, .165). Households of high individual level reciprocity were about 5 times more likely to join the scheme than those in middle level (95% CI AOR: 1.362, 18.052). Community level horizontal trust was strong positive predictor for WTJ community based health insurance (AOR = 25.2, 95% CI AOR: 6.355, 100.195). But community level reciprocity had no association in the decision of the household to join CBHIS (Table
4).
In case of health related variables, only self-reported health status of the household, borrowing money for covering treatments, and distance of the house to nearby health care facility were found to be significant predictors for the households’ WTJ decisions. Self-reported health status had negative association with the households’ WTJ. Borrowing money for health care payment was positively associated with WTJ. Households which borrowed money were about 3 times more likely to join the scheme than those who did not borrow (95% CI of AOR: 1.403, 5.730). Distance of the health facility to the home of the household, as measured by time taken to arrive at the nearby HF (HFs, here refer to hospital, public health center or private clinics), was negatively associated with WTJ. The probability of joining the scheme decreases by 1.6% as the time taken to reach the HFs increases by one minute. (95% CI of AOR: .973, .992) (Table
4).
Discussion
After presenting the scenario of community based health insurance scheme, the respondents were asked whether they were willing to join the scheme. Presenting scenarios simplifies understanding of hypothetical markets such as community- based health insurance schemes which is new concept in the district [
18].
Among 808 participants 629 (77.85%) responded that they would enroll in the scheme. Depending on the premium set, the actual enrollment could be lower. For example, if the premium is set to be 162.61 ETB (8.9 US$), only 50% of the households who are WTJ will enrol in the scheme. This translates the WTJ to be 38%. There are also other factors which may lower the actual WTJ [
21].
But, this initial figure is greater than findings from Edo state of Nigeria (60%) [
22]. The discrepancy may be attributed to the scenario employed in this study which was not used in the previous study. Various studies indicate that presenting scenarios about hypothetical markets such as health insurance schemes provides relatively accurate estimates. The difference may also be because of differences in the study areas. Obviously, people’s utilities in most aspects differ in different geographic regions.
In the current study, among the ill 231 (92.4%) had sought treatment for the illnesses they experienced, and 219 (94.8%) got treatment. This situation is not concurrence with the low access to health in Ethiopia [
2]. This indicates that the health seeking behavior of the people in the current study area is better than the broader national instance.
The potential WTJ in the current study area also exceeds that in Ecuador, which is 69% [
13]. This may be due to differences in study areas and demographic situations of the source population. The population in El Páramo Region of Ecuador, where the previous study was conducted, lacks official governance and the estimate number of the people is smaller than those in the current study. This situation led to small number of study participants which possibly yielded less precise estimate of WTJ in the El Páramo than the current findings.
The current finding is less than that found in 2004 in Ethiopia, in which the probability of WTJ the scheme was 94.7% [
23]. The reason may be attributed to differences in the study areas and time of study. The current finding is almost similar to that conducted in Jimma town in 2009, in which the probability to join iddir-based health insurances were 76.5% [
16].
The number of total family size, housewives (in comparison to farmers), participation in iddirs, amount contributed to iddirs monthly, individual social capital and community level horizontal trust had positive associations with the probability of WTJ the CBHIS. These findings are similar with those found in South Africa [
24], Lao PDR [
25], Nigeria [
22] and rural areas of China [
26,
27].
One interesting finding in this study is that age of the respondent is negatively associated with WTJ of the households. This finding is inconcurrent with other findings [
28‐
33]. The potential reason for such variation is pertinent to the benefit package of the proposed health insurance scheme in Ethiopia. Unlike health insurance schemes in many countries, the Ethiopian community-based health insurance scheme benefit package covers only the members of the households whose age is less than 18 years. As the age of the respondent in this study (mainly the head of the household) increases the probability of having family members who are eligible for the benefit package of the scheme is lower than the younger counterpart. Consequently the utility of joining the community-based health insurance scheme decreases. Such decision is in line with economic theories.
Few health related variables, such as seeking treatment during illnesses intrude, borrowing money for covering healthcare costs, which had no associations with probability of enrolling in iddir based health insurances in Jimma [
16], had positive and significant associations with the outcome variable in the current study area. This discrepancy may be attributed to the differences in the study areas.