Study settings and context
During data collection Ethiopia was administratively divided into nine regional states (i.e. Tigray, Afar, Amhara, Oromia, Somali, Benishangul-Gumuz, Gambela, Harari, and SNNPR) and two city administrations (i.e. Addis Ababa and Dire Dewa). Each region is divided into woreda and then each woreda is divided into kebele which are the lowest government administrative structures. The study covered all the nine regional states where the livelihood is agrarian or pastoralist. There are three tiers of health delivery systems in Ethiopia, namely, primary, secondary and tertiary levels. The primary level consists of primary healthcare units (health posts and health centers) and primary hospitals. Health posts are staffed primarily with two HEWs who are recruited based on nationally agreed criteria that include residence in the village, capacity to speak local language, graduation from 10th grade, and willingness to remain in the village and serve communities. The HEWs go through a year of training with both theoretical and practical components. The HEP, which is implemented at a grassroots level by HEWs, was originally designed to enhance the primary health services in rural areas through an innovative community-based approach that focuses on prevention, healthy living and basic curative care. Family planning is one of the 18 packages of HEP that is expected to be delivered by HEWs at the health post level .
Data source and study participants
Data used in this paper was extracted from a national rural HEP assessment which was conducted by MERQ consultancy PLC from October 2018 to September 2019. The assessment collected field data from March to May 2019. The assessment used multistage stratified sampling to select 62 districts or woredas from strata created by combining region with livelihood categories, three kebeles nested within each study woreda, and 34 households in each study kebele. The data was collected electronically using Open Data Kit (ODK). To develop this paper we extracted the data from married, rural, and aged 15–49 years from the national rural HEP assessment data base .
The primary outcome variable is an unmet need for family planning. It is defined as “the proportion of women who (1) are not pregnant and not postpartum amenorrhoeic and are considered fecund and want to postpone their next birth for 2 or more years or stop childbearing altogether but are not using a contraceptive method, or (2) have a mistimed or unwanted current pregnancy, or (3) are postpartum amenorrhoeic and their last birth in the last 2 years was mistimed or unwanted.” [6, 21].
Primary exposure variable
Our primary variable of interest is exposure of women to FP services through HEP. It is a composite variable defined using five items, namely, whether a woman: (1) was aware of the presence of FP services in the health post, (2) received a home visit by a HEW in the last 1 year, (3) received FP education at home by the HEWs, (4) visited a health post in the last 1 year, and (5) received any counselling about FP. The response for each question was either yes or no. If a woman responded “yes” to at least one of the above five items, it was considered as “having exposure to FP service through HEP” and if a woman responded “no” to all of the five items then she was categorized as “not having exposure to FP service through HEP”.
Covariates include sociodemographic variables such as a woman’s age, number of children in the household, wealth index of the household (categorized into five categories as “Lowest quantile, lower quantile, middle quantile, higher quantile, and highest quantile”), maternal educational status (categorized into “no formal education” and “attend formal education”), a woman’s knowledge about FP, and livelihood (categorized as agrarian for a main livelihood of growing crops/farming or pastoralist for a main livelihood of livestock farming). Other covariates (further described below) were availability of health workers, the health post’s readiness for FP services, the qualifications of health workers at the health post, and women’s awareness about FPs.
Health post readiness for FP service
This variable was computed from the responses given to the following variables (a) availability of contraceptives supply and equipment in the health post and, (b) availability of FP services in the health post. The allowable response for each of the composite variables was yes or no. A health post was categorized as a “ready health post” for FP services if it had a response of “yes” for the two items. A health post was categorized as “not ready” if it received a “no” response for either item.
Qualification of health workers assigned to work at health post
This variable was measured by reviewing the professional qualifications of HEWs at the health post at the time of data collection. The response was categorized in to three levels, namely, level III HEWs (basic skills to provide services at a health post), level IV HEWs (1 year additional course after graduation of level III) and clinical nurse or midwife. We used the label “level III HEWs” for health posts who have level III HEWs as the maximum qualification. If the health post has at least one level IV HEW we categorized it as “level IV”. Health posts that have either clinical nurse/nurse or midwife were labelled as “clinical nurse or midwife”.
Women’s knowledge of modern FP
Knowledge of women about FP was collected by asking the woman if she had heard about a total of nine modern FP methods (male condom, female condom, implants, IUCD, female sterilization, male sterilization, injectable, pills and Lactational Amenorrhea Method (LAM)). The response categories for each question were either 0(no) or 1(yes). Finally, the responses on the nine questions were summed to create one continuous variable that measures knowledge of married women on modern FP.
Number of children
This variable document the number of living children the woman had during the data collection time. During data analysis it was coded in to three categories: ‘1–2’, ‘3–4’ and ‘5 or more’.
Data quality assurance
Intensive training that lasted for 10 days was given for data collectors and their supervisors. In addition, regular supervision at the field during data collection was done to ensure data completeness and consistency of data. All possible data checking rules and logical checks were also implemented in the electronic data capturing template.
Electronically collected data were exported to STATA version 15 for analysis. The complex nature of sampling and unequal probability of recruiting study participants were addressed by using weighting in every analysis. Descriptive statistics (frequencies and percentages) were used to summarize categorical variables, and mean with standard deviation was used to summarize continuous variables. Logistic regression was used to model the unmet need for FP and to investigate the effect of HEP. Unadjusted and adjusted odds ratios (OR) and a 95% confidence interval (CI) around the estimates were reported as measures of effect.