Skip to main content
Dryad logo

Data from: Socio-cultural factors influencing knowledge, attitudes and menstrual hygiene practices among Junior High School adolescent girls in the Kpando District of Ghana: A mixed method study


Kpodo, Lebene et al. (2020), Data from: Socio-cultural factors influencing knowledge, attitudes and menstrual hygiene practices among Junior High School adolescent girls in the Kpando District of Ghana: A mixed method study, Dryad, Dataset,


Background: Menstruation is scarcely discussed openly in Ghana due to social and religious beliefs concerning it. This has limited transfer of knowledge on menstruation to adolescents. In this study we examined socio-cultural factors affecting knowledge, attitudes and menstrual hygiene practices of Junior High School adolescent girls in the Kpando Municipality of Ghana.

Materials and Methods: A mixed method approach was employed with 480 respondents.  A survey was conducted among 390 adolescent girls using interviewer administered questionnaires whilst Focus Group Discussions using a discussion guide were conducted among 90 respondents in groups of 9 members. Descriptive, inferential statistics and content analysis were used to summarize quantitative and qualitative data respectively.

Results: Fifty nine percent of the respondents had good knowledge of menstruation. Most (84.6%) of the students practiced good menstrual hygiene. Attending a private (AOR=0.19, 95% CI=0.09-0.40) and rural (AOR= 0.42, 95% CI=0.22-0.83, p=0.012) schools were significantly associated with reduced odds of practicing good menstrual hygiene. Good knowledge on menstruation was associated with increased odds of good hygiene practices (AOR=2.61, 95% CI=1.46-4.67, p=0.001). Qualitative results showed respondents were not given in-depth information on menstruation at menarche. Social and religious beliefs concerning menstruation were prominent and they influenced attitudes and practices such as isolation of menstruating girls and perception that menstruation was dirty and evil.

Conclusion: Although, good menstrual hygiene practice was high, religious and social beliefs regarding menstruation were common. Most of these beliefs lead to menstrual related restrictions which limit desire to seek crucial menstrual information. It is necessary to expand the scope of menstrual health awareness beyond the school environment in both rural and urban areas to eradicate menstrual misconceptions and restrictions.


The quantitative data was collected using an interviewer-administered questionnaire which was digitized using CSPro software and transferred unto android devices. The questionnaire was divided into three sections namely; Section A: Socio-demographic characteristics of the respondents; Section B: Knowledge on menstruation and Section C: Menstrual hygiene practices. The questionnaires were administered through face to face interviews with each participant by six experienced and well-trained data collectors.

Data were transferred to Stata Version 14.1, cleaned and validated to ensure quality before being analyzed. Categorical variables were presented using frequencies and percentages. A scoring system similar to that of Fehintola and colleagues was used to measure Knowledge on menstruation and menstrual hygiene practices [7]. A score of 1 was assigned to correct responses and 0 was assigned to incorrect responses. Regarding knowledge on menstruation, five variables were considered and these were; cause of menstruation, source of menstrual blood, implication of onset of menarche, normal menstrual cycle and the particular sex that experiences menstruation. The highest possible score was thus five (5) and the lowest was zero (0). A total score of three (3) and above was classified as good knowledge and a total score of less than three(3) was considered poor knowledge on menstruation. A dichotomous variable called knowledge on menstruation was then developed out of the knowledge variables. Good knowledge was coded as 1 while poor knowledge was coded as 0.

Regarding menstrual hygiene practice, four (4) variables were taken into consideration and the variables were;  type of absorbent used; number of times absorbent was changed per day; genitalia cleaning during menstruation; and the material used for cleaning the genitalia. The highest possible score was thus four (4) and the lowest was zero (0). A total score of three (3) and above was classified as good menstrual hygiene and a total score of less than three (3) was considered poor menstrual hygiene practice.  A dichotomous variable called hygiene practice was then developed out of the practice variables. Good practice was coded as 1 while poor practice was coded as 0.

Multivariate logistic regression was used to determine the strength of association. Forward and backward logistic regression was used to adjust for confounding variables. In the logistic regression model, good hygienic practice was coded 1 and poor hygienic practice was coded 0. The principal dependent variable was hygienic practice and the outcome of interest was good hygiene practices. Strengths of association between the independent variables and good hygiene practices were determined using the crude odds ratio (Model 1). Variables with p-value of <0.05 in Model 1 were considered for inclusion in the multiple logistic regression analysis (Model 2). To test for goodness of fit of Model 2, we used the likelihood ratio test to examine the likelihood of data under the full model as against the likelihood of the data under a model with reduced number of independent variables. We obtained a p-value for the overall model to be less than 0.05. Thus, we concluded the model was good.


FGD was employed to collect qualitative data using an FGD guide. Each FGD was made up of nine participants, a moderator, note taker and an observer. All discussions were taped using a recorder. The audio recordings from the FGDs were transcribed verbatim after each session by the note taker and the transcripts were verified by the moderator.

All transcribed notes were typed in Microsoft Word 2016 and analyzed using content analysis.  Frequently used words by participants were identified and coded manually after thorough reading of transcripts. Statements containing same or similar words were coded and categorized into themes for interpretation and further analysis.