Study Design, Study Setting, and Period
Community based cross-sectional study design was conducted from March 3/2020 to March 30/ 2020. The study was conducted in Motta district, Northwest Ethiopia called Hulet Ejju Enesse Woreda, 371 km away from Addis Ababa, capital city of Ethiopia. The woreda has total of 36 Kebeles. Among those, six were from Motta town, and the rest 30 were from a rural part. The district has one governmental hospital, 9 health centers, twelve nongovernmental clinics, five pharmacies, and 11 drug stores. According to the 2005 census and projected to the current population and from the Motta health bureau. The current estimated total population of the district was about 190,260. Of those, 94,436, and 95, 278 were males and females respectively. From the total number of females 36,898 were in reproductive age group, and 15,512 women were found in the age group of 30-49 .
All women in Motta district.
All women aged 40 -65 years old in Motta district in selected kebeles during the data collection period
Inclusion and Exclusion criteria
All Women aged 40-65 years old.
- Women who have stayed less than six months
- Critically ill and unable to communicate at the time of data collection
Sample size determination and sampling procedure
Sample size determination
The sample size was determined for the two objectives and the largest sample size was taken. A single population proportion formula was used with the following assumption, 95% confidence level, and margin of error (0.05) to calculate sample size for the first objective.
Where n=required sample size
Z= 1.96(z value at α=0.05).
P=proportion of knowledgeable women (22%) at Addis Ababa.
d= 0.05 (5% margin of error) and 10 % non-response rate.
n = 290 with 10% of non-response rate which gives 435.
Sample size determination for the second objective was calculated by using the double population formula with Epi-info version 7.2 by considering the following assumptions: 95%CI, power 80%,a non-response rate of 10%, and the factors are taken from a study conducted in Addis Ababa . By taking the largest sample size 488 was the final calculated sample size.
Sampling techniques and procedures
There are 36 kebeles in the woreda, and 12 kebeles were selected by the lottery method. Then, the calculated sample size was proportionally allocated for each kebeles based on the number of households. Since the number of house hold in each kebele is not equal, the calculated sample size allocated for each health kebele was proportionally allocated to determine the number of households included in the study from each kebeles. Finally, all randomly selected households were included in the study.
Data Collection tool
An interviewer administered questionnaire was used to collect the data. First, the tool was prepared in English, and then it were translated to the local language (Amharic), and then retranslated to English. Twelve health extension workers and four BSC midwives were recruited for data collection and supervisor, respectively. Two days training was given to all data collectors for proper filling of the questionnaire.
The questionnaires were including information on socio-demographic characteristics, knowledge assessing questions, reproductive health related factors, and other factors. The Knowledge level was assessed by using the 15 items provided to assess the knowledge level of the women in which each correct response was given a score of 1 and a wrong response score of 0. Severity of menopausal symptoms was assessed by Menopause Rating Scale (MRS) .
Data quality control
Translation, retranslation, and pretesting of the instrument and pretest were done before the actual data collection with 5% of the sample population in non-selected Kebeles for accuracy of responses and to estimate the time needed and the whole process of data collection under close supervision. Data were collected by trained data collectors and the collected data was checked and reviewed daily by the supervisors and principal investigator for its completeness Feedback on previous day activities was given, and necessary correction was done on daily bases.
The collected data was entered and cleaned by using epi data version 3.1, then exported to SPSS version 25 for analysis. Descriptive analysis was conducted to summarize the data and the final result of the study was interpreted in the form of text, figures, and tables. Binary logistic regression analysis was executed to see the association between independent and dependent variables. All explanatory variables with p≤0.2 in bivariable logistic regression were entered into multivariable logistic regression analysis and a significant association was identified based on p<0.05 and odds ratio with 95% CI in multivariable logistic regression. The final model fitness was checked using the Hosmer-Lemeshow Goodness of Fit test (0.11).
The principal component analysis was computed by the wealth status of the respondents. First, urban and rural wealth was separated and then all variables were subjected to the principal component analysis. In the first analysis, both urban and rural wealth components with Eigenvalues (variance) greater than one were extracted. According to “Kaiser’s rule” only those components with Eigenvalues greater than one should be retained . Based on Kaiser’s rule, the study decided to retain the first component because it had greater Eigen values (variance) than the other components. In the first component, the variables that had a correlation coefficients score of less than 0.3 were excluded in the second analysis. The correlation coefficient (𝑟) must be 0.30 or greater since anything lower would suggest a really weak relationship between the variables. The variables that had a weak relationship were excluded in the second -factor analysis. The second-factor analysis was performed with the remaining variables. Two components with Eigen values greater than one were extracted. Based on the same rule “Kaiser’s rule” the first component was retained because it had greater Eigen values than the second component and this first component was the one used to obtain the wealth index score. Then the reduced urban and rural wealth is coded to poor, medium, and rich and then merged by residence.
Premenopause: women experienced a regular menstrual cycle for the last three months with no or minimal complaint of related symptoms.
Peri-menopause: Refers women found around menopause, marked with the occurrence of the irregular menstrual period or amenorrhea for at least four months, but for less than 12 months and complain some symptoms related to menopause.
Post-menopause: Refers to women experiencing amenorrhea for at least12 months with menopausal symptoms which is not attributed due to other reasons.
Knowledgeable: For women with a score of a mean and above of knowledge assessing questions were considered as knowledgeable, whereas women who scored less than a mean of knowledge questions were considered as poor knowledge.
The severity of menopausal symptoms: Non/minimal (with a score of 0-4), mild (with a score of 5-8), moderate (with a score of 9-15), and sever (with a score of 16-44).
Ethical clearance was obtained from the Institutional Review Board (IRB) office of Bahir Dar University College of Medicine and Health sciences. A formal letter was taken to Motta health bureau, Motta town, and to each kebeles administration. Before the actual data collection, each participant was fully informed about the research objectives and a form for written informed consent that was placed at the front page of each questionnaire. Thus, written informed consent was obtained with the sign of the study participant and the actual data collection time. Finally the data collectors attached the consent form with each respondent’s questioner. Confidentiality was maintained throughout the study period, and the collected data was anonymous.