Menu
Menu
Menu
Menu
Poor knowledge and management of menstruation impacts girls’ school attendance and academic performance. This paper aims to explore how menstrual hygiene management practices and related factors influence school absenteeism and drop-out among primary and secondary school girls in rural Gambia. Mixed-method studies were conducted among students and key informants from 19 schools from July 2015–December 2017. Focus group discussions, in-depth interviews, cross-sectional surveys, menstrual diaries, and school water, sanitation and hygiene (WASH) facility observations were used. Key findings from the interviews were that menstrual pain, cultural beliefs, fear of peers knowing menstrual status, and poor school WASH facilities led to school absenteeism, however, they had no impact on school drop-out. Of the 561 girls surveyed, 27% reported missing at least one school day per month due to menses. Missing school during the most recent menstrual period was strongly associated with menstrual pain (extreme pain adjusted odds ratio (AOR) = 16.8 (95% CI: 7.29–38.74)), as was having at least one symptom suggestive of urinary tract infection (AOR = 1.71 (95% CI: 1.16–2.52)) or reproductive tract infection (AOR = 1.99 (95% CI: 1.34– 2.94)). Clean toilets (AOR = 0.44 (95% CI: 0.26–75)), being happy using school latrines while menstruating (AOR = 0.59 (95% CI: 0.37–0.93)), and soap availability (AOR = 0.46 (95% CI: 0.3–0.73)) were associated with reduced odds of school absenteeism. This study suggests menstrual pain, school WASH facilities, urogenital infections, and cultural beliefs affected school attendance among menstruating girls in rural Gambia.
This study was conducted in 19 rural primary and secondary schools located in 13 villages in the rural Kiang districts, in the Lower River Region of The Gambia (Bajana, Jali, Janneh Kunda, Jiffarong, Kaiaf, KantongKunda, Karantaba, Keneba, Kwinella, Manduar, Nema Kuta, Niorro Jattaba, and Sibito) between July 2015 and December 2017. Schools were selected through recommendation of the MoBSE. Of the 19 schools, twelve were English schools and seven were Arabic schools. The Gambia has two formal education systems: Arabic-based and English-based. The English-based schools are free public schools, and the Arabic schools are private schools that focus on Quranic education. Schools in The Gambia also run a double shifting programme, where some grades attend school in the mornings, while other grades attend schools in the afternoon. This is partly due to teacher and resource constraints, but also to allow students to carry out domestic duties [34]. The population in the Kiang district is predominantly from the Mandinka ethnic group, the majority are Muslims and most families are polygamous [35]. The majority of the population live below the moderate poverty line of less than USD 2/day [36,37]. Before enrolment, informed consent was obtained from students over 18. Assent was sought from younger students and consent was given by their carers. It was made clear to all participants that their participation was voluntary and would not affect any other services they receive [38]. Data presented in this paper are part of mixed method studies that involved two cross-sectional surveys, qualitative interviews (focus group discussions (FGDs) and in-depth interviews (IDIs)), daily diaries, and unannounced WASH spot checks. A mixed methods approach was used so as to benefit from both the detailed contextualized insight from the qualitative data and the generalizable externally valid insights from the quantitative data. The study started with the qualitative interviews to be able to set the scene and have a better understanding of the MHM context in The Gambia, as not much was known about it; qualitative methods were also seen to be useful to explore some of the aspects related to menstruation due to the taboo nature of the topic. The qualitative interview guides were developed through systematic reviews on MHM and through discussions with the local study team and local clinicians to explore what challenges needed to be addressed. The points raised in the interviews and existing tools used to evaluate MHM outcomes were used to develop the cross-sectional survey tools. Supplementary Materials show the qualitative interview guides and cross-sectional survey tools. The qualitative results were also used to triangulate findings with the quantitative data and explore issues that are not possible to address through a survey. Triangulation of methods can provide opportunities for testing alternative interpretations of data and for examining the extent to which the context helped to shape the quantitative results. A subset of six schools were selected to conduct the qualitative interviews in. Selected schools were a representative of the other schools in the region. We aimed to conduct at least one FGD with each of the following groups, pre-menarche girls, post-menarche girls, and boys in each of the six schools. For the IDIs, we aimed to have at least two IDIs among each of the following categories: girls who had dropped out of school, boys, mothers, and teachers, across all six schools. Additional discussions were conducted if new themes continued to immerge through the discussions. Participants for the FGDs and IDIs were purposively selected. A group size of between 5–8 participants was considered adequate for the FGDs, discussions with fewer than five people were not conducted to ensure the anonymity of participants was not risked. The school teachers were asked to provide a list of different groups listed below that they considered able to discuss sensitive topics and were engaged during discussions: girls between 13–20 years, boys between 15–20 years, mothers who had adolescent children in the school, and drop-out female students whose age at drop-out was 15 years or older. Participants were randomly chosen from these lists. Teachers who were interested in the study topic and worked closely with students on topics related to reproductive health were invited to participate in the IDIs. Participants who were considered open, and had a lot of information to share that could not be captured during the FGDs, were invited to continue the discussion during an IDI. All participating schools (n = 19) were asked to create lists of female students that were 13 years and older from grades 5–12, all girls from this list were asked their menstrual status, and those that had started menstruating were included in the survey. Sample size calculations for the individual cross-sectional studies are described elsewhere [6,26]. In order to compare different methods of measuring school attendance related to menstrual status, daily diaries were given to a subset of participants. Participants for the daily diaries were randomly selected. Study IDs of all girls consenting from four schools (2 English and 2 Arabic) were split by age into three categories: 11–14 years, 15–17 years, and 18–25 years. IDs from each category were entered into a separate random number selector, 10 numbers were selected from each category to have a total of 30 numbers selected. The categories were created to ensure there was representation from each age category. All schools enrolled in the study (n = 19) received unannounced WASH spot checks. Interviews were conducted in the local language, using semi-structured interview guides, which contained open-ended questions and suggested probing questions. Interviewers were of the same gender as participants to ensure comfort and openness of participants. Girls were asked their menarcheal status on a one-to-one basis prior to the FGDs, and then split into groups of pre- and post-menarche girls. FGDs consisted of participants, a moderator, and a note taker; the moderator led the discussions, the note taker was there to note any non-verbal cues, highlight important topics that came up in the discussion, and assist the moderator. IDIs included the participant and moderator. The discussions explored knowledge and attitudes towards menstruation, cultural norms associated with menstruation, MHM practices at home and school, challenges faced managing menses, opinions on school WASH facilities, reasons for school absenteeism when menstruating or dropping out of school, role of parents and teachers on menstrual support for adolescents, and potential solutions to supporting girls while they menstruate. FGDs and IDIs were conducted in a private room and recorded using a digital voice recorder. The IDI lasted about 25–40 min and the FGDs lasted about 30–70 min. Due to the sensitive nature of the topic, moderators spent some time at the start of the discussions creating a rapport with the participants. Data saturation was the marker of adequate sampling [39]. Enumerator-administered pre-tested questionnaires were used due to low literacy levels and the local language (Mandinka) not being a written language. Data on socio-demographics, knowledge and practices of menstruation (including age of menarche; knowledge and attitudes about menstruation; MHM practices such as type of menstrual absorbent used, change frequency, washing and drying practices of reusable material; access to WASH at home), school absenteeism, reasons for absenteeism, and symptoms of urogenital infections were collected. Questions about school absenteeism referred to the last 30 days, and the questions were subdivided to ask about all frequently reported reasons for absenteeism. To assess school attendance related to menstruation, the question “in the last 30 days, how many days did you miss of school because of your period?” was used. Data completeness and consistency were reviewed at the end of each data collection day by the team’s supervisor (VS). The daily diaries given to the subset of 30 random girls were to be completed daily by the girls over an 8-week period, indicating if they attended school or not and if they were menstruating or not that day (Supplementary Materials—soft copy of diary distributed). The enumerators indicated the girls study ID on the diary and explained how to fill in the diaries and completed one week retrospectively to give the girls an example of how to complete it. A month later, the team then went again to check if the girls needed any help and then again at the end to collect the diaries. Unannounced visits to conduct spot checks of WASH facilities were conducted in each school by the team’s supervisor. A pre-determined tool was used to assess the WASH hardware available: number and type of toilets, handwashing facilities, and disposal facilities. As well as access, the quality of these facilities, functionality, gender specificity, privacy, cleanliness, availability of water and soap, and location of water was assessed. Permissions to conduct unannounced visits were obtained from each school at the beginning of the study. One spot check was conducted in each school over the course of the study period. Spot checks were conducted during school hours to ensure the facilities could be observed in conditions that would be available for students. The study team also ensured there was a lag between obtaining consent for unannounced visits and the actual visit. Questions used in tools (interview guides and survey questionnaires) were put together from several different sources that had been validated, however, since the questions had not been tested/validated in the combination we used and in the Gambian context, we piloted the tools we developed for the study on 11 volunteers (3 medical practitioners, 4 field assistants from MRCG Keneba, 3 adolescent girls, and 1 adolescent boy). The tools were first piloted on the medical practitioners and field assistants and feedback from these groups was used to amend the tools; after these groups were satisfied with the tools, they were then piloted on the adolescents. The tools had final adjustments after feedback from the adolescents and were then considered valid for this context. The main aim of the piloting was testing the quality and acceptability of questions and their translation, and the feasibility of using the tools. Other benefits from the piloting were they supported enumerator training in using and administering the tools. The WASH spot check tool was adapted from the UNICEF international guidelines [40]; these guidelines set out questions and indicators to standardize monitoring WASH in schools in line with the sustainable development goals. The adapted tool was piloted to test if it worked well in the Gambian context. Data from the IDIs and FGDs were simultaneously translated and transcribed into English by the field team. Inductive content analysis was conducted [41]. VS analysed all the transcripts. Six randomly selected transcripts were assigned to the HN for analysis to test the inter-rater reliability regarding the codes and themes emerging from the transcripts. HN and VS independently read the transcribed data carefully and segmented the data. Each researcher assigned meaningful segments a code and the codes were then discussed and compared. Data collected on questionnaire forms were double entered into SQL (SQL server 2017 [42]) and analysed using Stata version 16.0, [43]. The cross-sectional data was presented by school type and comparisons made using chi-squared statistics for binary and categorical outcomes and t-test for continuous outcomes. Principal component analysis (PCA) was used to determine household socio-economic status using an asset-based index [44]. The adolescent girls’ households were classified into three quantiles (i.e., poorest/2nd quantile/least poor) based on Filmer and Pritchett’s method [45]. Knowledge of menstruation was assessed using five questions. Each question was scored on a scale of 0 (incorrect) to 1 (correct). The score for each respondent was totalled, with a maximum score of 5. A score of 0–1 was coded as poor knowledge and 2–5 was coded as good knowledge. Univariable and multivariable logistic regression analyses of outcome variables were applied to provide both unadjusted and adjusted odds ratios in exploring factors associated with school absenteeism due to menstruation. In the multivariable regression analysis, a model was run for each of the MHM health outcomes and WASH variables. The variables age, wealth, school type, and maternal education were included as a priori confounders in the models, as they were associated with the outcome. School level data were adjusted for clustering using robust standard errors. Missing data were not imputed. The study ID was used to link survey and diary data. From the diary, total number of days missed, and number of days missed due to menstruation in the 30-day prior to survey date were extracted and compared with survey data. Data was collected on forms and double entered into SQL [42] and analysed using Stata 16 [43]. Basic descriptive analysis was carried out to describe the quality of WASH facilities per school type, after which univariable analysis was carried out to see if the quality of WASH components affected attendance.
