# Effect of Maternal Employment on the Practice of Exclusive Breastfeeding Among Mothers of Infants Aged 6-12 Months in Wolkite City, Ethiopia: A Comparative Cross-Sectional Study | BMC Women’s Health

### Design, period and framework of the study

A community-based comparative cross-sectional study design was conducted from February 20 to March 28, 2020 in the town of Wolkite which is 158 km from Addis Ababa, the capital of Ethiopia, in the south- west along the main road from Addis Ababa. at Jimma. The administration of the town of Wolkite is organized into 3 sub-towns and 7 kebeles. According to the Wolkite Municipal Government Health Bureau report of 2019, the population size of the town is estimated at 72,929, of which 15,413 are women between the ages of 15 and 49 and 1,106 are infants aged from 6 to 12 months. [20].

### Population and sample

All mothers who had babies aged 6 to 12 months (employed and unemployed mothers) and who had lived in the study area for at least six months constituted the source population. Mothers who had children aged 6 to 12 months in randomly selected single households constituted the study population. Mothers of babies with cleft lip and/or palate and seriously ill mothers were excluded.

Sample size was determined for both purposes (prevalence and associated factors).

The sample size for the first objective.

According to a previous study conducted in Fafan Zone, Somali Regional State of Ethiopia in 2019, the prevalence of EBF among employed mothers was 25% and the prevalence of EBF among unemployed mothers was 83%. [17]. Next, the sample size is determined using the following statistical formula.

$$n = left( {p1q1 + p2q2} right) left( {fleft( , right)} right) / (left( {p1 – p2} right)^{2}$$

$${text{n}} = frac{{left( {0.25 times 0.75 + 0.83 times 0.17} right) times 7.84 , }}{{ left( {0.25 – 0.83} right )^{2} }} = 8,;{text{for}};{text{each}};{text{employed} };{text{and}};{text{unemployed}};{text{mothers}}$$

where P1 = 0.25 (prevalence of EBF among employees), q1 = 1 − p1, P2 = 0.83 (prevalence of EBF among unemployed), q2 = 1 − p2 and f (α, β ) = 7.84; when power = 80% and α = 5%.

The sample size for the associated factors is calculated using a comparative study carried out in the city of Gonder with the assumptions of a confidence interval of 95%, 80% power using OpenEpi version 3.01 [19] presented as follows (Table 1).

Finally, the sample sizes calculated using the first objective and the associated factors were compared. Then the largest sample size was taken. Therefore, the largest sample size of 239 in each group was taken, and after accounting for the 5% nonresponse rates, the total sample size for each group was 251,

Regarding the sampling procedure, the sample size was allocated proportionally to each kebele based on the total number of targeted woman-child pairs in each kebele. Then, a household survey was conducted prior to data collection to identify the employment status of the mother and provide an identity code for each eligible household in all kebeles. After obtaining the number of employed and unemployed mothers, the total sample size was again allocated proportionally by employment status in each kebele. Next, a simple computer-generated random sampling technique was used to select study participants.

### Data collection instrument and procedure

Data was collected through face-to-face interviews using pre-tested structured questionnaires which were prepared after reviewing different publications such as EDHS, 2016 questionnaires and other publications on related topics . [17,18,19, 21,22,23,24]. The questionnaire consists of five parts; socio-demographic characteristics, maternal health services and infant factors, breastfeeding and related elements, maternal breastfeeding knowledge and other barriers to exclusive breastfeeding. Data were collected by four clinical nurse professionals under the supervision of two public health professionals.

### Study variables

The practice of exclusive breastfeeding was the dependent variable. The independent variables include; socio-demographic factors such as mother’s age, education level, employment status, knowledge, working hours, father’s education level, father’s occupation, family size, household income and social support. Maternal health factors, including parity, number of antenatal visits, breastfeeding counseling during pregnancy, place and mode of delivery, postnatal care, maternal illness, and perceived adequacy breast milk were predictive variables. Similarly, infant-related factors such as birth order and interval, infant sex and health status, and bottle-feeding practice were independent variables.

### Operational definitions

An employed mother is a mother who has been employed in a government or private organization or a day laborer who works more than eight hours a day for at least five days a week, and who has worked from birth to six months of qualifying age of the child.

unemployed mother: a mother, who works at home as a housewife,

Welfare: a woman who has received economic, psychological support and/or breastfeeding advice from the company or organization.

Knowledge of breastfeeding: There are ten questions related to maternal knowledge, and if a study participant answers five or more correct answers, she has good knowledge and if she answers less than five, she has poor knowledge [22, 25].

### Data quality assurance

To ensure data quality, three days of training were provided to data collectors and supervisors.

To assess the relevance of the wording, the clarity of the questions and the reaction of the respondents to the questions and to the interviewer, a pre-test was carried out on 5% of the calculated sample size in the city of Emdibir which presents socio-demographic similarities with our study population. Regular supervisions were made during data collection. The completeness, consistency and clarity of the data collected were checked daily.

### Data analysis

Data were coded and entered into the statistical software EpiData version 3.12, then exported to SPSS version 21 for further analysis. Descriptive statistics such as frequencies, mean, median and proportions were calculated to know the prevalence of exclusive breastfeeding (EBF) and other indices. Bivariate logistic regression was used to check for variables having an association with the dependent variable, then variables with a p-value ≤ 0.2 were fitted to multivariate logistic regression to control for the effects of confounding factors. Adjusted odds ratios with 95% CI and a P-value