The world has a growing attention on moving towards universal health coverage, and health insurance is instrumental in that endeavor. As a prepaid financing system, health insurance ensures collective pooling of risks and the redistribution of financial resources in a way that guarantees financial protection against the cost of illnesses. The main aim of the study was to determine the factors associated with Non enrollment into Community based health insurance schemes in the BHD. A community based cross-sectional study was carried-out among Parents in BHD. Multistage sampling technique was used to select participants and data collected using a structured interviewer administered questionnaire. Data collected was analysed using SPSS version 21. A total of 384 participants took part in the study. The rate of enrolment into CBHIS in BHD was 2.4% (95% CI: 0.9-3.9%). Salary employed individuals were 2.7 times more likely to be enrolled into CBHIS compared to those who were self-employed. (O.R: 2.70, 95%CI; 1.15-6.37: P = 0.023). Low level of education was also found to be significantly associated with non-enrollment into CBHIS (O.R: 0.455, CI: 0.212-0.976, P: 0.043). Unawareness of CBHIS (O.R: 0.025, CI: 0.006-0.113, P: <0.001), low income level (O.R: 0.305, CI: 0.134-0.697, P: 0.005) and age less than 40yrs (O.R: 0.255, CI: 0.103-0.631, P: 0.003) were found to be significantly associated with non-enrolment. There was low enrollment into CBHIS in the BHD (2.4%). Factors significantly associated with non-enrolment into CBHIS in BHD were; low level of education, low age group of less than 40yrs, non-salary employment, low income level and unawareness of existence of schemes.

1. Factors associated with Non Enrollment into Community Based Health Insurance Schemes in the Bamenda Health District, Cameroon
IJPHER
Factors associated with Non Enrollment into Community
Based Health Insurance Schemes in the Bamenda Health
District, Cameroon
Anye Che Jude1*, Sylvester Ndeso Atanga1,2, Doumta Charles Falang3, Eyong Herdis Nso4
1,3Department of Public Health and Hygiene, Faculty of Health Sciences, University of Buea, P.O. Box 63, Buea, Cameroon
2Department of Health Sciences, School of Health and Human Sciences, Saint Monica American International University,
Buea, Cameroon
4Department of Microbiology, Faculty of Science, University of Buea, P.O. Box 63, Buea, Cameroon
The world has a growing attention on moving towards universal health coverage, and health
insurance is instrumental in that endeavor. As a prepaid financing system, health insurance
ensures collective pooling of risks and the redistribution of financial resources in a way that
guarantees financial protection against the cost of illnesses. The main aim of the study was to
determine the factors associated with Non enrollment into Community based health insurance
schemes in the BHD. A community based cross-sectional study was carried-out among Parents
in BHD. Multistage sampling technique was used to select participants and data collected using
a structured interviewer administered questionnaire. Data collected was analysed using SPSS
version 21. A total of 384 participants took part in the study. The rate of enrolment into CBHIS in
BHD was 2.4% (95% CI: 0.9-3.9%). Salary employed individuals were 2.7 times more likely to be
enrolled into CBHIS compared to those who were self-employed. (O.R: 2.70, 95%CI; 1.15-6.37: P
= 0.023). Low level of education was also found to be significantly associated with non-enrollment
into CBHIS (O.R: 0.455, CI: 0.212-0.976, P: 0.043). Unawareness of CBHIS (O.R: 0.025, CI: 0.006-
0.113, P: <0.001), low income level (O.R: 0.305, CI: 0.134-0.697, P: 0.005) and age less than 40yrs
(O.R: 0.255, CI: 0.103-0.631, P: 0.003) were found to be significantly associated with non-
enrolment. There was low enrollment into CBHIS in the BHD (2.4%). Factors significantly
associated with non-enrolment into CBHIS in BHD were; low level of education, low age group of
less than 40yrs, non-salary employment, low income level and unawareness of existence of
schemes.
Keywords: Health Insurance, Socio-demographic/cultural/Economic factors, Unwareness, Bamenda Health District.
BACKGROUND
The world has a growing attention on moving towards
universal health coverage, and health insurance is
instrumental in that endeavor. As a prepaid financing
system, health insurance ensures collective pooling of
risks and the redistribution of financial resources in a way
that guarantees financial protection against the cost of
illnesses [Ataguba et al, 2010]. Health insurance also
seeks to promote equitable access to health care for all
people [De Alligri et al, 2006]. However, in low- and middle-
income countries (LMICs), the majority of health insurance
schemes are unable to extend coverage to every segment
of the population [Preker A et al, 2004].
*Corresponding Author: Anye Che Jude, Department of
Public Health and Hygiene, Faculty of Health Sciences,
University of Buea, P.O. Box 63, Buea, Cameroon. Email:
anyechejude@gmail.com; Tel: +237677233680
International Journal of Public Health and Epidemiology Research
Vol. 4(2), pp. 060-070, December, 2018. © www.premierpublishers.org. ISSN: 1406-089X
Research Article

2. Factors associated with Non Enrollment into Community Based Health Insurance Schemes in the Bamenda Health District, Cameroon
Jude et al. 061
Globally, Health care financing is under severe strain and
particularly in Africa and other developing Countries where
health care cost is ever increasing. For over three
decades, calls have been made for communities in
developing Countries to plan, finance, organize and
operate health care services. The question that often
arises is how and how much should the poor from poor
Countries contribute towards this [Atim CB et al, 1998].
Increasing the access of African populations to health care
is one of the biggest challenge facing Africa and the global
community.
Many low-and middle-income countries rely heavily on
patients’ out-of-pocket health payments to finance their
health care systems [Xu ke et al, 2007]. According to the
World Health Organization (WHO), empirical evidence
indicates that out-of-pocket health payment is the least
efficient and most inequitable means of financing health
care and prevents people from seeking medical care and
may exacerbate poverty [WHO, 2000].
The need to pay out-of pocket also mean that households
do not seek care when they need it. According to a study
carried out in Africa, the system of financing health
expenditure in Africa is too weak to protect households
against catastrophic expenses and for this reason, the
borrowing or selling assets to finance health care is a
common practice as the proportion of households who
have paid their health spending by borrowing or selling
assets ranged from 23% in Zambia to 68% in Burkina Faso
and so on [Adams L et al, 2008]. Health system financing
in Cameroon is carried out by both the public and the
private sectors. The public financing mechanism involves
Social Health Insurance (SHI), and Taxes (direct, indirect,
general and earmarked). On the other hand, apart from
user charges, private health is finance by Community
Based Health Insurance (CBHI), Private Health Insurance
(PHI), Mutual Health Organizations (MHO) and Medical
Saving Account (MSAs) [Xu ke et al, 2003].
Household health financing in Cameroon is mostly done
through out-of pocket payment. Out-of-pocket payments
for health services have caused households to incur
catastrophic expenditures (catastrophic when a household
must reduce its basic expenditure over a period of time to
cope with health cost), which in turn push them into poverty
[Xu Ke et al, 2003].
According to WHO (2010), out-of-pocket expenditure as a
percentage of private health expenditure in Cameroon is
approximately 94%. Meanwhile, social security funds as a
percentage of general government expenditure on health
for the same period (2009) was 4.7%.
Based on activity report of the North west Regional Fund
for Health Promotion (2017),Some mutual health
cooperatives societies (MUHCOOPS) of Kumbo, Boyo
and Bamenda in the North West region hold agreements
of collaboration with the North West Regional Fund for
Health Promotion (NWRFHP) as technical partner. In an
evaluation of the evolution of membership between 2015-
2017, the enrolment were approximately 7100 to 5500 in
Kumbo, 2300 to 2700 in Boyo and 300 to 250 in Bamenda.
This indicates that Bamenda has the lowest rate of
enrolment into community based health insurance
scheme.
In the absence of risk protection, cost becomes a barrier
to seeking and obtaining quality health care. These
financial barriers from the formal health care systems often
lead would-be patients to resort to self-medication and
other practices that sometimes injure their health [Arhin-
Tenkorang, 2004]. CHI will thus act as a response to
obstacles to the implementation of universal coverage. As
at November 2017 Kumbo and Boyo MUHCOOPS
showed signs of sustainability as they had bank reserves
but the situation was not a good one in Bamenda as cost
of service/functioning exceeded contributions made and
this can be attributed to low enrolment into the schemes
[Activity report NWRFHP, 2017]. Thus identifying and
tackling factors associated with non-enrolment will go a
long way in improving on enrolment rate and promoting
universal health coverage.
METHODS
Study design and setting: The study was a community
based cross-sectional study conducted among parents in
the Bamenda Health District (BHD).
The BHD is one of the nineteen health districts found in the
North West Region of Cameroon. It has an estimated
population of 422982 inhabitants as of 2017. The district
consists of seventeen health areas namely; Akumlam,
Alabukam, Alakuma, Alamandom, Atuakom, Azire,
Mankon, Mbachogwa, Mendankwe, Mulang, Ndzah,
Nkwen Baptist, Nkwen rural, Nkwen urban, Ntambag,
Ntamulung, Ntankah.
Study population, participants and sampling: The
study population was made up of Parents (Males or
Females) in the BHD. To be eligible for the study, a
participant had to be of aged 18 or above, a resident of the
BHD and in health areas covered by the schemes and or
must have been living permanently in the district for the
past six months. Participants who had hearing problems,
who were severely sick, suffering from mental health
problems and who refused to give consent to participate
were excluded from the study.
The sample size was calculated using the Lorenz formula
for sample size determination. We assumed the proportion
of persons non enrolled into schemes to be 0.5 which is a
standard provided a previous study was not available
giving such proportion as was the case of the study We
then used a margin of error of 5%, a 95% level of
confidence to calculate the required sample size of 384
participants. Therefore the formula used was;

3. Factors associated with Non Enrollment into Community Based Health Insurance Schemes in the Bamenda Health District, Cameroon
Int. J. Public Health Epidemiol. Res. 062
n= Z2P (1-P)/e2
Where
Z= 1.96 (at 95% CI)
P= Proportion of persons not enrolled into CBHIS was
assumed to be (0.5) due to absence of a past study.
e = Margin of error (5%, i.e. 0.05)
n= Minimum sample size?
n= 1.962 x 0.5 (1-0.5)/ 0.052
n= 384 participants
A multistage sampling method was used to select
participants. In the first stage, 3 health areas out of the 17
in the district were selected randomly by writing all the
health areas on pieces of papers and after balloting, 3
were chosen (Azire, Mulang and Nkwen Urban health
areas). Then we took the total population of each of the
health areas and divided by the total of all the three health
areas to get a proportion which was multiplied by the
calculated sample size of 384 to get the number of persons
in each health area to be used for the study. (Table 1). In
the second stage, a list of all communities in each health
area was gotten and balloting done to select two
communities from each health area-giving a total of six
communities for all 3 health areas chosen from the district.
A probability proportionate to size method was also used
to determine number of persons needed from each
community in the health areas from which data was
collected based on the total number of persons needed in
each health area (Tables 2, 3 and 4). Finally, in the third
stage at community level, we located a center in the
community, spun a bottle and visited all households to the
right of the head of the bottle. We interviewed only one of
the parent from each open household provided they met
the inclusion criteria. This procedure continued until the
required sample was reached for each health area. Where
both parents were present at home, a simple random
method was used to select either the male or female to
partake in the study provided he/she could give
information about enrollment of households.
Data collection and management
Data was collected by trained data collectors using a
structured interviewer administered questionnaire
designed by the investigators. The adopted questionnaire
was first pretested in one community of the Tubah Health
District which was not a study community and then
modified before being used to collect data. The
questionnaire was divided into four sections as follows:
Section A; socio-demographic/cultural characteristics
(age, gender, marital status, education level, household
size, health area and religious status), Section B; socio-
economic characteristic such as occupation and income
level, Sections C comprised of awareness and knowledge
on CBHIS. To control data quality, researchers supervised
daily collection of data. The data collected on the printed
questionnaire was checked daily for completeness and
entered into an Excel sheet for analysis. The data entered
was saved in a folder in the computer with a password
known only to the researchers and hard copies of the
questionnaires were securely kept in a cupboard
accessible only to the researchers.
Data analysis
Data was analysed using the statistical software program
(Statistical Package for Social Sciences version 21. The
socio-demographic characteristics were described using
frequencies and percentages for categorical variables and
means, standard deviation for continuous variables.
To determine the rate of enrollment into schemes which
was reflective of the entire health district, a review of
record was done where the total enrollment for 2017 in
both schemes [Mutual Health Organization (MHO) and
Bamenda Ecclesiastical Province for Health Assistance
(BEPHA)] in the BHD was gotten and the denominator was
the total population of the Health District for 2017. To
determine factors associated with non enrollment into the
schemes, we grouped items in the questionnaire under
enrollment status, socio-demographic/cultural, economic
related factors and awareness level of existence of
schemes and computed the frequencies and percentages
of each item.
Probability Proportionate to size method to determine
number of participants to sample in each health area
and communities within the health areas
Table 1: Sample size determination in three health areas
of BHD according to Probability proportionate to size
Health areas 2017
population
proportion Sample
Azire 74087 0.38 146
Nkwen Urban 83681 0.43 165
Mulang 35900 0.19 73
Total 193688 1.0 384
Sample size determination in health area communities
according to probability Proportionate to size Azire
Health Area
Table 2: Sample size determination in two communities in
Azire health area
Communities Population Proportion Sample
Azire 10895 0.51 74
Nitop II 10290 0.49 72
Total 21185 1.0 146
Nkwen Urban Health Area
Table 3: Sample size determination in two communities in
Nkwen urban health area
Communities Population Proportion Sample
Bayelle 20920 0.52 86
Ndamukong 19247 0.48 79
Total 40167 1.0 165

4. Factors associated with Non Enrollment into Community Based Health Insurance Schemes in the Bamenda Health District, Cameroon
Jude et al. 063
Mulang Health Area
Table 4: Sample size determination in two communities in
Mulang health area
Communities Population Proportion Sample
Ngomgham 10950 0.53 39
Mulang 9873 0.47 34
Total 20823 1.0 73
*Health area and communities population figures
obtained from the District Health service Bamenda,
North West Region, Bamenda-Cameroon.
To assess the relationship between non enrollment into
CBHIS and participant’s socio-demographic/Cultural
characteristics, economic related factors, unawareness of
existence of schemes, bivariate and multivariate analysis
was done. The bivariate analysis comprised of using state
of enrollment from questionaires as a binary outcome
variable and parents’s socio-demographic/cultural,
economic related characteristics, awareness level of
existence of schemes as predictors. Unadjusted odds
ratios, 95% confidence intervals and P-values were
computed and all variables having P-values of <0.05 in the
bivariate analysis were considered as appearing to have
an association with non-enrollment into CBHIS and were
included in the multivariate logistic model. The multivariate
analysis considered state of enrollment from questionaires
as a binary outcome variable and all the variables with P-
values ≤ 0.05 in the bivariate analysis as predictors.
Adjusted odds ratios, 95% confidence intervals and p-
values were computed. Variables with p-values < 0.05
were considered to have a statistically significant
association with non-enrollment into CBHIS in the BHD.
Ethical considerations
Ethical approval to conduct the study was obtained from
the IRB of the Faculty of Health Sciences of the University
of Buea and administrative authorization was obtained
from the Dean of the Faculty of Health Sciences of the
University of Buea, the Regional Delegate of Public Health
for the North West Region and the District Medical Officer
(DMO) of the Bamenda health district. All participants
provided written informed consent and apart from the
inconvenience of taking time to answer the questionnaire,
participants were not exposed to any undue risk. All
information collected from participants was used only for
the purpose of this study.
RESULTS
Demographic characteristics
Table 5 shows the socio-demographic characteristics of
the 384 study participants who were included in this study.
The mean age of participants was 32.2 years (SD: 9.7) and
a greater proportion of the participants (51.8%) were
single. Two hunderd and sixty six (69.3%) of the
participants had earned only the primary/secondary level
of education (less educated). Majority of the participants
(77.9%) were Christians most of whom (54.4%) were
males.
Table 5: Socio-demographic characteristics of the study population
Characteristics Azire
No (%)
Mulang
No (%)
Nkwen Urban No
(%)
Total
No (%)
Gender Male 73(19.0%) 38(9.9%) 98(25.5%) 209(54.4%)
Female 73(19.0%) 35(9.1%) 67(17.4%) 175(45.6%)
Marital status Married 69 (18.0%) 41(10.7%) 75 (19.5%) 185(48.2%)
Single 77 (20.1%) 32(8.3%) 90(23.4%) 199(51.8%)
Education Lower level 99(25.8%) 59(15.4%) 108(28.1%) 266(69.3%)
Higher level 47(12.2%) 14(3.6) 57(14.8%) 118(30.7%)
Occupation Salary employed 36(9.4%) 16(4.2%) 35(9.1%) 87(22.7%)
Non salary
employed
110(28.6%) 57(14.8%) 130(33.9%) 297(77.3%)
Religion Christians 124(32.3%) 62(16.1%) 113(29.4%) 299(77.9%)
Non-Christians 22(5.7%) 11(2.9%) 52(13.5%) 85(22.1%)
Income <50000frs 103(26.8%) 58(15.1%) 120(31.3%) 281(73.2%)
>50000frs 43(11.2%) 15(3.9%) 45(11.7%) 103(26.8%)
Age(years) Mean±SD 32.2±9.7
18-25 47(12.2%) 30(7.8%) 65(16.9%) 142(37.0%)
26-35 57(14.8%) 29(7.6%) 47(12.2%) 133(34.6%)
36-45 29(7.6%) 10(2.6%) 29(7.6%) 68(17.7%)
≥46 13(3.4%) 4(1.0%) 24(6.3%) 41(10.7%)

5. Factors associated with Non Enrollment into Community Based Health Insurance Schemes in the Bamenda Health District, Cameroon
Int. J. Public Health Epidemiol. Res. 064
Overall 2017 Enrollment rate into CBHIS in BHD from
review of records of schemes
Table 6 below shows the overall rate of enrollment into
CBHIS in the BHD in 2017
Table 6: 2017 Enrollment rate
Factors Overall Proportion
enrolled
Enrollment
rate
95%
C.I.
Total
enrollment of
2017
10250 0.024 2.4% 0.9-
3.9%
Population of
BHD in 2017
422982
The overall enrollment of the two Community based health
insurance schemes of the Bamenda health district in 2017
was 10250 and with the population of the health district
(422982) as the denominator, the rate of enrollment was
found to be 2.4%
Socio-demographic/cultural factors associated with
non-enrollment into community based health
insurance schemes in BHD
Association of socio-demographic/cultural factors with
non-enrolment into CBHIS is presented in table 7 and 8.
The main aim here was to identify if cultural factors which
can be reflected in the health areas of parents as
presented in table 7 and socio demographic factors such
as; Age, gender, marital status, educational level and
household size as seen in table 8 are associated with or
have any influence on non-enrolment into CBHIS.
Association of non-enrolment into CBHIS with health
area
Table 7 below shows association between non-enrolment
into CBHIS with respect to the health areas of the study
participants
Table 7: Association of non-enrolment into CBHIS with
health area
Health
areas
Enrolled
No (%)
Non
enrolled
No (%)
Total
No (%)
X2
P-
value
Azire 21(5.5%) 125(32.6%) 146(38.0%) 3.092 0.213
Mulang 8(2.1%) 65(16.9%) 73(19.0%)
Nkwen
Urban
32(8.3%) 133(34.6%) 165(43.0%)
Majority of non-enrolled, [133(34.6%)] were found in the
Nkwen Urban Health area with the least non-enrolled
persons 65(16.9%) found in the Mulang Health Area.
However there was no statistically significant association
between Health areas with non-enrolment into CBHIS
(p=0.213) (Table 7).
Association between socio-demographic
characteristics and non-enrollment into CBHIS
Table 8 shows association between socio-demographic
characteristics and non-enrolment into CBHIS
Table 8: Association of socio-demographic characteristics with non-enrollment into CBHIS
Factors Options Enrolled
No (%)
Unenrolled
No (%)
Overall
No (%)
O.R. 95% CI P-values
Age(years) <40 34(8.9%) 262(68.2%) 296(77.1%) 1.00 0.164-0.522 <0.001
≥40 27(7%) 61(15.9%) 88(22.9%) 0.293
Gender Male 36(9.4%) 173(45.1%) 209(54.4%) 1.00 0.716-2.175 0.433
Female 25(6.5%) 150(39.1%) 175(45.6%) 1.248
Marital status Married 36(9.4%) 110(28.6%) 146(38%) 1.00 1.59-4.88 <0.001
Unmarried 25(6.5%) 213(55.5%) 238(62%) 2.788
Educational level Less educated 17(4.4%) 249(64.8%) 266(69.3%) 1.00 0.062-0.213 <0.001
More Educated 44(11.5%) 74(19.3%) 118(30.7%) 0.114
Household size <4 persons 22(5.7%) 211(54.9%) 233(60.7%) 1.00 0.169-0.529 <0.001
>4 persons 39(10.2%) 112(29.2%) 151(39.3%) 0.299
Religion Christians 48(12.5%) 251(65.4%) 299(77.9%) 1.00 0.543-2.063 0.866
Non-Christians 13(3.4%) 72(18.8%) 85(22.1%) 1.059
Majority of non-enrolled individuals, [262(68.2%)] were
less than 40 years of age while just 61 (15.9%) of persons
greater than 40 years of age were unenrolled with a
statistically significant difference (O.R. = 0.293, CI=0.164-
0.522, p = < 0.001) (Table 8).
Non enrolment was found to be slightly higher among
males, 173(45.1%) when compared to females 150
(39.1%) with no statistical significant gender difference
(O.R.=1.24, CI=0.716-2.175, p=0.433) (Table 8).
Most of the parents who were unenrolled into schemes 213
(55.5%) were unmarried while 110 (28.6%) were married.
There existed a statistically significant association
between marital status and non-enrolment into CBHIS.
(OR 2.78; 95% CI 1.59-4.88; P= <0.001) (Table 8).

6. Factors associated with Non Enrollment into Community Based Health Insurance Schemes in the Bamenda Health District, Cameroon
Jude et al. 065
Most parents who were non-enrolled 249 (64.8%) were
those who had attended just primary or secondary level of
education while just 74 (19.3%) of those who had attended
university education were unenrolled. There was also a
statistically significant association existing between level
of education and non-enrolment into CBHIS (O.R. = 0.114;
CI = 0.062-0.213, P= <0.001) (Table 8).
Majority of parents who were not enrolled into CBHIS 211
(54.9%) had a household size of less than 4 persons while
just 112 (29.2%) of parents with household size greater
than 4 were unenrolled. There was a statistically significant
difference existing between size of a household and non-
enrolment into CBHIS. Those with household size less
than 4 had 0.17 less chance of enrolling compared to those
with household size of greater than 4. (OR 0.299; 95% CI
0.169-0.529; P= < 0.001) (Table 8).
Majority of those who were unenrolled into CBHIS 251
(65.4%) were Christians while 72 (18.8%) were non-
Christians. There was however no statistically significant
association existing between enrolment and religion (OR
1.059; 95% CI; 0.543-2.063; P = 0.866) (Table 8).
Economic factors associated to non-enrollment into
CBHIS in BHD
The main aim here was to determine if economic related
factors such as; economic activity or monthly income level
of parents is actually associated with or have any influence
on non-enrolment into CBHIS in Bamenda health district
as reported in Table 9.
The majority of parents who were non-enrolled in any
scheme 271 (70.6%) were not salary employed while just
52 (13.5%) were salary employed and those with salaries
were 7 times more likely to enroll into CBHIS compared to
those who were self-employed (O.R.=7.0). A statistical
significant association was found (O.R. =7.0, C.I=3.89-
12.628, P= < 0.001) (Table 9).
Non enrolment was high amongst parents with low income
level 260 (67.7%) compared to those who had a higher
income 63 (16.4%). There was a statistically significant
association existing between low income and non-
enrolment into CBHIS (OR 0.127; 95% CI 0.07-0.23; P=
<0.001) (Table 9).
Table 9: Association of Economic related factors with non-enrolment into CBHIS
Factors Option Enrolled
No (%)
Non enrolled No
(%)
Overall
No (%)
O.R. 95% CL P-values
Economic activitySalary employed 35(9.1%) 52(13.5%) 87(22.7%) 1.00 3.897-12.628 <0.001
Non-salary
employed
26(6.8%) 271(70.6%) 297(77.3%) 7.015
Monthly Income <50000frs 21(5.5%) 260(67.7%) 281(73.2%) 1.00 0.070-0.230 <0.001
>50000frs 40(10.4%) 63(16.4%) 103(26.8%) 0.127
Table 10: Association of awareness with non-enrolment into CBHIS
Factors Option Enrolled
No (%)
Non enrolled No (%) Overall
No (%)
O.R. 95%C.L P-value
Awareness of CBHIS Unaware 2(0.5%) 212(55.2%) 214(55.7%) 1.00 0.004-0.074 <0.001
Aware 59(15.4%) 111(28.9) 170(44.3%) 0.018
Influence of awareness on non-enrollment into CBHIS
in BHD
The main aim here was to determine if awareness of
parents on the different health insurance schemes have
any influence on non-enrolment into CBHIS in the
Bamenda health district as presented in table 10.
Out of the 214 parents who were unaware of CBHIS, 212
(55.2%) were unenrolled while just 2 (0.5%) were enrolled.
On the part of those parents aware of CBHIS, out of the
170 aware, 111 (28.9%) were unenrolled while 59 (15.4%)
of them were enrolled. There existed a statistically
significant association between unawareness and non-
enrolment into CBHIS. Those who are unaware of CBHIS
are 0.018 times less likely to be enrolled into CBHIS
compared to those who are aware. (O.R. =0.018, C.I.
=0.004-0.074, P= < 0.001).
Multivariate Analysis
Socio-demographic/cultural/economic/awareness
related factors associated with non-enrolment into
CBHIS in B.H.D
In order to control for confounders, multiple logistic
regression analysis was done as seen in the results
presented in Table 11.
All the factors presenting with statistical significant
association in the bivariate analysis were adjusted in the
multiple logistic regression analysis for the following
possible confounders; (Household size and marital status).
After the multivariate analysis, low age (less than
40years), low income level, low educational level, non-
salary employment and unawareness were still found to be
statistically significantly associated with non-enrollment
into CBHIS in the Bamenda health district. This indicated
that these confounders had an effect on the increased
likelihood of not enrolling into CBHIS. (Table 11).

7. Factors associated with Non Enrollment into Community Based Health Insurance Schemes in the Bamenda Health District, Cameroon
Int. J. Public Health Epidemiol. Res. 066
Table 11: Multiple logistic regression on factors significant on a bivariate analysis
Factors Options Enrolled
No (%)
Unenrolled
No (%)
Overall
No (%)
A.O.R. 95% CI P-values
Age(years) <40 34(8.9%) 262(68.2%) 296(77.1%) 1.00 0.104-0.636 0.003
≥40 27(7%) 61(15.9%) 88(22.9%) 0.257
Economic activity Salary employed 35(9.1%) 52(13.4%) 87(22.7%) 1.00 1.153-6.406 0.022
Non salary employed 26(6.8%) 271(70.6%) 297(77.3%) 2.717
Marital status Married 36(9.4%) 110(28.6%) 146(38%) 1.00 0.695-3.308 0.296
Single 25(6.5%) 213(55.5%) 238(62%) 1.516
Educational level Less educated 17(4.4%) 249(64.8%) 266(69.3%) 1.00 0.212-0.976 0.043
More Educated 44(11.5%) 74(19.3%) 118(30.7%) 0.455
Household size <4 persons 22(5.7%) 211(54.9%) 233(60.7%) 1.00 0.583-3.329 0.456
>4 persons 39(10.2%) 112(29.2%) 151(39.3%) 1.393
Monthly income <50000frs 21(5.5%) 260(67.7%) 281(73.2%) 1.00 0.134-0.697 0.005
>50000frs 40(10%) 63(16.4%) 103(26.8%) 0.305
Awareness of CBHIS Unaware 2(0.5%) 212(55.2%) 214(55.7%) 1.00 0.006-0.113 <0.001
Aware 59(15.4%) 111(28.9) 170(44.3%) 0.025
Distribution of respondents according to what they
think are the benefits of the CBHIS
Figure 1 below presents results of what parents think could
be the benefits of enrolling into CBHIS
Figure 1: Distribution of respondents according to what
they think are the benefits of the CBHIS
On what the benefits of the scheme are, 238 (62%) had no
response because they were unaware, majority 62
(16.1%) said pay 50% of hospital bills when sick, followed
by 52 (13.5%) who said pay 75% of hospital bills when sick
not exceeding some amount and 29 (7.6%) who said pay
75% of all hospital bills when sick.
Distribution of respondents’ according to reasons for
non-enrolment into CBHIS
Figure 2 presents results of reasons why some parents are
not enrolled into CBHIS in the BHD
Figure 2: Distribution of respondents’ according to
reasons for non-enrolment into CBHIS
On the reasons for non-enrolment into schemes, majority
152 (39.6%) said they didn’t know such exist, followed by
75 (19.5%) who said they were discouraged by
family/friends and 60 (15.6%) who said they have never
been sick. (Figure 2).

8. Factors associated with Non Enrollment into Community Based Health Insurance Schemes in the Bamenda Health District, Cameroon
Jude et al. 067
DISCUSSION OF RESULTS
Rate of enrollment into CBHIS in BHD
The total number of persons enrolled into CBHIS in 2017
from review of data was 10250 (2.4%) of the population as
seen in table 8. This goes in accordance with WHO report
of 2000 which says low and middle income countries rely
more on out of pocket payments for health care and which
is the least efficient and most inequitable means of
financing health care as well as prevent people from
seeking medical care and exacerbate poverty. It’s also in
line with WHO report of 2010 which says out of pocket
expenditure in Cameroon is staggering at 94% indicating
that majority of persons in Cameroon are not enrolled into
health insurance schemes .
Socio-demographic/Cultural factors associated with
non-enrollment into CBHIS in BHD
Despite the fact that majority of non-enrolled persons
133(34.6%) were found in Nkwen Urban health area with
the least 65(16.9%) at Mulang, there existed no significant
association between health area and non-enrolment into
CBHIS in BHD (P=0.213). Therefore non enrollment into
CBHIS is not influence by culture of persons living in a
particular community and sharing common
characteristics/ideas.
With regards to gender, non-enrollment was slightly higher
amongst males 173(45.1%) compared to females 150
(39.1%) and same was the case with enrollment with
36(9.4%) of males enrolling into schemes compared to
25(6.5%) of females. However there was no statistically
significant association existing between gender and non-
enrollment into CBHIS though with an O.R. of 1.24, males
were 1.24 times more likely to enroll into CBHIS compared
to females. This is similar with findings made by Sabine in
India which stated males are more likely to be enrolled into
insurance schemes compared to females. This was
attributed to the disadvantage position of women in
households since it was a man who takes pertinent
decisions.
The finding was contrary to that reported by Bsateng et al
in Ghana in 2012 who said there was a statistically
significant association between gender and non-
enrollment into insurance schemes.
In terms of age, most of the non-enrolled individuals
262(68.2%) were less than 40yrs of age while just 61
(15.9%) of persons greater than 40yrs of age were
unenrolled with a statistically significant difference. This is
in line with a study carried out in Ghana by Edward who
said persons with age greater than 40yrs were more likely
to enroll into health insurance schemes reason being as
age increases health stock depreciates at increasing rate
thus a need for inducing investment in health. The findings
are also in accordance with study carried out by Mhere in
2013 in Zimbabwe who reported age was a significant
determinant of enrollments with reasons being persons
with advance age have better experience and sense of
responsibility and as well must have acquired more
treasure .
Most of the parents who were not enrolled 249 (64.8%) are
those who had acquired just primary or secondary
education while just 74 (19.3%) of those who had acquired
university education were unenrolled and there existed a
significant association statistically between level of
education and non-enrollment into CBHIS in BHD which is
indicative that enrollment is influenced by educational level
of individuals. This study goes in agreement with that
carried out by Feinstein et al who said education is an
important link to health and its determinants including
healthy behavior (of which enrolment into CBHIS is part
of), use of preventive services and general attitude
towards risk and that those with many years of schooling
tend to have better health, wellbeing and healthier
behaviors.
Majority of parents who were unenrolled into CBHIS [211
(54.9%)] had a household size of less than 4 persons while
just 112 (29.2%) of parents with household size greater
than 4 were unenrolled and there was a statistically
significant difference between household size and non-
enrollment into CBHIS in BHD and those with household
size less than 4 had 0.17 less chance of enrolling into
CBHIS compared to those with household size greater
than 4. (O.R. = 0.169). These findings are contrary to that
to those carried out by Fang et al in Taiwan on health
insurance coverage who observed that coverage in both
public and private health insurance was dominated by
household with smaller family sizes.
However, the study is similar with that carried out by Doyle
et al in India which stated; larger household were more
likely to purchase Health insurance scheme compared to
smaller ones. This was attributed to more members of a
family living together in a single unit and sharing different
ideas thus making good decisions.
With regards to religious denominations, there was no
statistically significant difference (P= 0.866) existing
between religious status and non-enrollment into CBHIS in
BHD meaning religion had little or no influence on non-
enrollment into schemes. This can be due to the fact that
there are both faith based health insurance scheme such
as BEPHA and non-faith based schemes such as M.H.O.
thus individuals can make decisions to be part of any and
no complaints of it being owned by a particular faith based
organization.
Most of the parents who were unenrolled into CBHIS
213(55.5%) were unmarried while 110 (28.6%) were
married and there existed a statistically significant
difference ( P= <0.001) between marital status and non-
enrollment into CBHIS with married persons being 2.78
times more likely to be enrolled into CBHIS compared to

9. Factors associated with Non Enrollment into Community Based Health Insurance Schemes in the Bamenda Health District, Cameroon
Int. J. Public Health Epidemiol. Res. 068
those who are unmarried (O.R.= 2.78). The findings of this
study is in accordance with that carried out by Kirigia et al
in South Africa who found that marital status had a positive
effect on enrollment into health insurance schemes and
explained that it might be due to the need for them to
protect their children in future being more concerned about
high health expenditure .
Economic related factors associated with non-
enrollment into CBHIS in BHD
Majority of those who were not enrolled in any CBHIS 271
(70.6%) were non-salary employed while just 52 (13.5%)
were salary employed. Those with constant regular
monthly salaries were 7 times more likely to be enrolled
into CBHIS compared to that without a steady monthly
salary and there existed a statistically significant
association between employment status and non-
enrollment into CBHIS in BHD. (O.R. = 7.0, P = <0.001).
This is in agreement with a study carried out by Perry et al
who discovered that self-employed were significantly less
likely than wage earners to be enrolled in Health insurance
schemes. This can be due to the fact that wage earners
can predict and are sure of having a steady amount of
money at end of the month which is not the case for the
self-employed.
Based on economic factor such as income level, non-
enrollment was high amongst parents with low income
level [260 (67.7%)] compared to those with higher incomes
[63(16.4%)] and there existed a statistically significant
association between income level and non-enrollment into
CBHIS (P = <0.001) and those with income less than
50000frs or less income had a 0.12 less chance of
enrolling into CBHIS (O.R. = 0.127). This study is in line
with that carried out by Kirigia et al in South Africa who said
enrolling into Health insurance schemes is influenced by
income levels as those with higher income have a higher
coverage compared to those with lower income.
However, the findings are contrary to that of Bhat et al in
India who said that income level and non-enrollment into
CBHIS are not linear and that as income increases,
enrollment increases but as time unfolds the relationship
between income and enrollment becomes negative. This
might be due to the fact that as income increases more,
individuals think they have much money to provide
whatever care they need themselves and their family and
thus do not need any health insurance scheme for financial
protection.
Influence of awareness on non-enrollment into CBHIS
in BHD
There existed a statistically significant association
between unawareness and non-enrollment into CBHIS
(P= <0.001) and those who are unaware are 0.018 times
less likely to be enrolled into CBHIS compared to those
who are aware. (O.R. = 0.018). This is indicative of the fact
that more sensitization and education of the public on
CBHIS will need to be done to play a great role in boosting
up enrollment and striving towards attainment of national
health coverage. This is in line with a study carried out by
Plateau et al in India on the influence of awareness on non-
enrollment and renewal into health insurance scheme. He
found that low enrollment and renewal was influence by
deficient information on the functioning of the scheme and
poor understanding of insurance concept.
Based on what the benefits of the scheme were, most of
those who said they were aware of the benefits 62 (16.6%)
says it pays 50% of hospital bills when sick followed by 52
(13.5%) who said it pays 75% of hospital bills when sick
not exceeding some amount. This shows that majority who
said it pays 50% of all hospital bills when sick don’t know
the actual benefit of the scheme. Thus if they are more
educated that it can cover up to 75% of all hospital bills
when sick not exceeding some amount, then enrollment as
well as renewal will have a likelihood of increasing
drastically
On reasons why individuals were not enrolled into CBHIS
in the district, most of the parents 152 (39.6%) said they
didn’t know such exist followed by 75 (19.5%) who said
they were discouraged by friends and 60 (15.6%) who said
they have never been sick before. This shows that most of
the non-enrollment into CBHIS is as a result of not been
aware of the scheme at all and that workers of schemes
need to encourage parents to visit the schemes if they
have any worry or doubt for them to be clarified and not go
to friends who might not understand clearly how the
scheme functions. Also workers of scheme will also need
to educate the parents that they are unaware of the
happening of tomorrow and that even if not sick today, they
can as well be sick tomorrow and their contributions can
as well help a family member somewhere tomorrow in
need of help and enrolled in the scheme.
CONCLUSION
- The rate of enrollment into Community Based Health
Insurance Schemes in Bamenda Health District is 2.4%.
- Socio-demographic as well as economic related factors
factors such as; age less than 40yrs, low educational level,
non-salary employment and low income levels are
associated with non- enrolment into community based
health insurance schemes in the Bamenda Health District.
- Unawareness of the existence of schemes have a great
influence on Non enrollment into Community based Health
Insurance schemes in the Bamenda Health District.
Further studies need to be conducted for much longer
durations in other Health Districts and Regions of the
Country involving larger samples of participants to
determine other factors associated with non-enrollment
into Community based health insurance schemes.

10. Factors associated with Non Enrollment into Community Based Health Insurance Schemes in the Bamenda Health District, Cameroon
Jude et al. 069
Conflicts of Interests
The authors declare no conflict of interest.
Authors' Contributions
ACJ, SNA, DCF conceived, designed and revised the
article, ACJ designed the study protocol and collected
data; ACJ, EHN and DCF analysed data and assisted with
data interpretation; ACJ, SNA and DCF assisted with study
design. All authors wrote and or reviewed the manuscript.
ACKNOWLEDGEMENTS
We thank all study participants and our data collectors. We
also express our sincere gratitude to the Institutional
Review Board of the Faculty of Health Sciences of the
University of Buea which gave ethical clearance for this
study, the Dean of the Faculty of Health Sciences of the
University of Buea (Pr. Ngowe Ngowe Marcelin), Regional
Delegate of Public Health for the North West Region (Dr.
Kingsley Che Soh) and the District Medical Officer for the
Bamenda Health District, who gave administrative
authorizations for this work to be carried out.
FUNDING
Study had no funding.
ABBREVIATIONS
AOR: Adjusted Odds Ratio
BHD: Bamenda Health District
BEPHA; Bamenda Ecclesiastical Province Health
Assistance
CBHIS: Community Based Health Insurance Schemes
CI: Confience Interval
DMO: District Medical Officer
IRB: Institutional Review Board
No: Number
MHO: Mutual Health Organization
MUHCOOPS: Mutual Health Cooperatives
NWRSFHP: North West Regional Special Fund for Health
Promotion
OR: Unadjusted Odds Ratio
SD: Standard Deviation
WHO: World Health Organisation.
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Accepted 23 December 2018
Citation: Jude AC, Atanga SN, Falang DC, Nso EH
(2018). Factors associated with Non Enrollment into
Community Based Health Insurance Schemes in the
Bamenda Health District, Cameroon. International Journal
of Public Health and Epidemiology Research, 4(2): 060-
070.
Copyright: © 2018 Jude et al. This is an open-access
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