Effects of sanitary pad distribution and reproductive health education on primary school attendance and reproductive health knowledge and attitudes in Kenya: a cluster randomized controlled trial

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Muthengi, Erica Soler-Hampejsek This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-105989/v2 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 30 Aug, 2021 Read the published version in Reproductive Health → Version 2 posted 12 You are reading this latest preprint version Show more versions Abstract Background: Adolescent girls’ risk of school dropout and reproductive health (RH) challenges may be exacerbated by girls’ attitudes toward their bodies and inability to manage their menstruation. We assessed effects of sanitary pad distribution and RH education on girls in primary grade 7 in Kilifi, Kenya in 2017-18. Methods: A cluster randomized controlled trial design was used. Eligible clusters were all non-boarding schools in three sub-counties in Kilifi County that had a minimum of 25 girls enrolled in primary grade 7. 140 primary schools, 35 per arm, were randomly assigned to one of four study arms: 1) control (standard government provision of pads and health education); 2) sanitary pad distribution; 3) RH education; or 4) both sanitary pad distribution and RH education. Outcomes were school attendance, school engagement, RH knowledge and attitudes, gender norms, and self-efficacy. For outcomes measured both at baseline and endline, difference-in-differences (DID) models were estimated and for outcomes without baseline data available, analysis of covariance models were used. Results: The study enrolled 3,489 randomly selected girls in primary grade 7. Girls in arms 2 and 4 received on average 17.5 out of 20 packets of sanitary pads and girls in arms 3 and 4 participated on average in 21 out of 25 RH sessions. Ninety-four percent of the baseline sample was interviewed at the end of the intervention with no differential attrition by arm. There was no evidence of an effect on primary school attendance on arm 2 (coefficient [coef] 0.37, 95% CI -0.73, 1.46), arm 3 (coef 0.14, 95% CI -0.99, 1.26) or arm 4 (coef 0.58, 95% CI -.37, 1.52). There was increased positive RH attitudes for girls in arm 3 (DID coef. 0.63, 95% CI 0.40, 0.86) and arm 4 (DID coef. 0.85, 95% CI 0.64, -1.07). There was also an increase in RH knowledge, gender norms and self-efficacy in arms 3 and 4. Conclusions: The findings suggest that neither sanitary pad distribution nor RH education, on their own or together, were sufficient to improve primary school attendance. However, as the RH education intervention improved RH outcomes, the evidence suggests that sanitary pad distribution and RH education can be positioned in broader RH programming for girls. Trial Registration: ISRCTN, ISRCTN10894523. Registered 22 August 2017 - Retrospectively registered, http://www.isrctn.com/ISRCTN10894523 Sexual & Reproductive Medicine adolescent girls randomized controlled trial Kenya menstrual health sexual and reproductive health Figures Figure 1 Figure 2 Plain English Summary Adolescent girls face a range of challenges that may compromise their chances of completing school or their sexual and reproductive health. These challenges can be even further complicated by girls’ feelings of shame about their bodies, in particular about menstruation, or their lack of sanitary products to help them manage menstruation. This study sought out to assess if providing girls in grade 7 in a rural, coastal area of Kenya with sanitary pads and sex education would alleviate some of those challenges. One hundred and forty schools were included in the study and 35 each were randomly assigned to one of the following program packages: 1) control (standard government provision of pads and health education); 2) provision of sanitary pads; 3) sex education; or 4) both provision of sanitary pads and sex education. The study found that none of the three program packages had an impact on school attendance, however those that participated in the sex education felt more positively about menstruation, knew more about sexual and reproductive health, had more equitable gender norms and were more self-confident at the end of the program. The study results show that addressing girls’ menstrual health challenges are important, but are better positioned as part of comprehensive sexuality education programs addressing stigma and shame associated with menstruation, access to menstrual products, inequitable gender norms and sexual and reproductive health knowledge gaps, as opposed to a girls education intervention. Background As girls enter puberty their experience of sexual and gender based violence, school dropout, and early marriage starts to increase [ 1 ]. According to several qualitative studies in Africa, these vulnerabilities are exacerbated by girls’ lack of knowledge of their bodies and rights, and their inability to safely and comfortably manage their menstruation [ 2 – 5 ]. Qualitative studies conducted in Kenya, and other countries in sub-Saharan Africa, have identified several challenges girls face in managing their menstruation, including lack of access to menstrual products and lack of accurate information about menstruation. The studies also clarified that neither teachers [ 6 ] nor mothers [ 2 , 7 ] felt well placed to deliver information on menstruation, let alone a wider range of sexual and reproductive health topics. In additional qualitative studies, girls expressed that they missed school during their menses due to lack of menstrual products, fear of leaking blood on their uniforms and pain from menstrual cramps [ 3 , 5 , 8 ]. A sense of shame, discomfort and need for secrecy around the topic of menstruation was also a common theme [ 2 , 4 – 6 ]. Finally, girls expressed that when they were menstruating they experienced anxiety and stress about staining their uniforms, giving off an odor or in general being found out to be menstruating that made it difficult for them to concentrate or participate fully in class [ 2 , 5 , 9 ]. The literature on the challenges linked to a lack of menstrual hygiene products and knowledge has been largely qualitative. While several programs have previously been developed to address girls’ menstrual health management (MHM) needs in Kenya, as well as globally, few have been rigorously evaluated, and where evidence does exist on the effect of such programs on reproductive health (RH) and schooling outcomes, the results have been mixed. A 2013 systematic review of the literature on the effects of MHM programs concluded that while there was some evidence on the effect of MHM on psycho-social outcomes, the impact on RH outcomes was unclear. They also noted that quantitative evidence was lacking on the effects of MHM on reducing school absenteeism and that there was an absence of rigorous studies showing the impact of MHM on girls’ general health and well-being [ 10 ]. In 2016, Hennegan and Montgomery published an MHM-related systematic review that assessed the risk of bias in eight studies and synthesized the evidence on the effects of MHM interventions on educational and psychosocial outcomes for women and girls in low and middle income countries [ 11 ]. The authors outlined two dominant types of MHM intervention approaches: hardware, or the provision of physical objects useful for MHM, such as menstrual cups or sanitary pads; and software, or the provision of human and social capital through education and non-tangible benefits. The review found considerable risk of bias in these studies and overall weaknesses in study designs such as small sample sizes, inability to determine causation, non-random assignment to study arms and short follow-up periods. Therefore, the review concluded that while there are some indications of positive results, insufficient evidence existed for the effectiveness of MHM interventions. Since that review, the evidence base on the link between menstruation, menstrual products and education and RH outcomes has increased. A cluster RCT in rural Western Kenya found that while provision of menstrual cups or sanitary pads was associated with reduced sexually transmitted infection (STI) risk, there was no association with school dropout [ 12 ]. An analysis of school attendance data from this study showed a positive impact on attendance due to sanitary pad distribution, however, that effect washed out in models that accounted for absence due to school transfer [ 13 ]. A quasi-randomized controlled trial implemented in Uganda found positive effects from distribution of reusable sanitary pads and puberty education, both alone and combined; however the results should be interpreted with caution as the study had poor participant retention and a lack of fidelity to the intervention [ 14 ]. A cross sectional study of girls aged 14–18 years in a rural area of Uganda showed associations between menstruation and school attendance [ 8 ]. Finally, an analysis of longitudinal data on adolescent health in India showed that, conditional on school enrollment, menstruation is not a significant predictor of school attendance [ 15 ], which is a similar finding to an earlier study in Malawi that did not find an effect of menstruation on school attendance [ 16 ]. Despite the increase in quantitative evidence on the impact of menstrual products on education outcomes, studies assessing the effect of combined hardware and software interventions are lacking. In addition, MHM interventions are often embedded within the education or water, sanitation and hygiene (WASH) fields, yet the case has more recently been made that MHM and puberty education should be seen as an entry into girls discussing their bodies, and from which more comprehensive conversations on RH could then take place [ 17 ]. Evidence on the combined effect of an MHM and RH intervention has the potential to move that case forward. Therefore, this study aims to assess the effects of a combined hardware and software intervention, integrating both MHM and broader RH content, on education and RH outcomes. Methods Setting This study took place in Kilifi County, Kenya in 2017–2018. Kilifi was selected for the study as it ranked low in both education and RH indicators: for example, the transition rate from primary to secondary was 40% in 2010 compared to the national rate of 72% [ 18 ]; further, around 22% of girls ages 15–19 have begun childbearing, as compared to the national average of 18% [ 19 ]. In Kenya, the school year starts in January and consists of three academic terms per year. Primary school is from grade 1 through grade 8, and secondary school is from grade 9 to grade 12. While universal primary education for girls has nearly been achieved, there remains significant variation at the county level, gaps in the transition to secondary school and challenges with pupil absenteeism [ 19 , 20 ]. The Government of Kenya has committed to sanitary pad distribution in schools; however, evaluations have shown that supply chains of sanitary pads to schools were not reliable, and girls were not assured of equitable pad provision [ 21 ]. Data and Study Design This study assessed the impact of the Nia Project via a longitudinal, cluster-randomized controlled trial in 140 public primary schools in three rural sub-counties (Magarini, Kaloleni and Ganze) of Kilifi County, Kenya. Study schools were randomly assigned to one of the following four study arms: Control group Sanitary pads distribution (pads only) Reproductive health education (RH only) Sanitary pads distribution + reproductive health education (combined) The sub-counties and schools were selected in collaboration with the Kilifi County Department of Education. Eligible clusters included all non-boarding schools in the three sub-counties with at least 25 girls enrolled in primary grade 7. A total of 215 schools were mapped, and a one kilometer buffer was created around each school. For schools with overlapping boundaries, one school was randomly selected resulting in a list of 173 schools. Enrollment and school type were verified for each school in the first quarter of 2017. Based on this exercise, 33 schools were excluded leaving a sample of 140 schools: 44 in Magarini, 50 in Kaloleni, and 46 in Ganze (see Fig. 1 ). All eligible schools (n = 140) were included in the study. All girls enrolled in grade 7 in a randomly selected school were eligible for inclusion in the study sample. In schools with only 25 girls in grade 7, all girls were included in the research sample. In schools with a larger number of girls, 25 girls were randomly selected for the research sample and five additional girls were selected as alternates. A total of 3,489 girls were interviewed as part of the baseline survey. All grade 7 girls, including those who were not in the research sample and those who had not yet started menstruating, were eligible to receive interventions in order to streamline program delivery. Grade 7 was selected as it would allow for observation of the transition to secondary school within the study timeframe. The Nia Project included the following two components: 1) Sanitary pads: girls received, on a monthly basis for the entire duration of the project, one packet of ten disposable sanitary pads of ZanaAfrica’s Nia Teen brand. In addition, girls received two pairs of underwear at the start of the intervention, and an additional pair at the end of each subsequent school term. 2) RH education: a 25-session curriculum, Nia Yetu , was delivered by trained facilitators during girls-only health clubs held during time allocated for extra-curricular activities in schools. The curriculum covered a variety of topics including puberty, menstrual health management, reproductive systems, self-esteem, gender, human rights, power dynamics, sexual violence, assertiveness, decision making, relationships, teen pregnancy, STIs and HIV, peer pressure, drug use and conflict management. Girls also received a health magazine developed by ZanaAfrica, Nia Teen , designed to appeal to adolescent girls and convey core RH messaging through storytelling using aspirational personal stories, a relatable comic-style story, and activities. The magazine was distributed at the start of each school term for a five-term period. Each issue corresponded to the topics covered in the Nia Yetu curriculum that term. Table 1 shows take-up of the two Nia Project components by study arms: girls in the pads only and combined arms received on average 17.5 out of 20 packets of sanitary pads and girls in the RH only and combined arms participated on average in 21 out of 25 RH sessions. Additional details on the Nia Project, theory of change, and study design have been published elsewhere [ 22 ]. Table 1 Nia Project uptake Among Girls Menstruating at Baseline and Interviewed at Endline Arm 1 Control n = 627 (mean (SD)) Arm 2 Pads Only n = 632 (mean (SD)) Arm 3 RH Only n = 629 (mean (SD)) Arm 4 Pads & RH n = 656 (mean (SD)) Mean no. of pads received (target = 20) 0 17.5 (4.2) 0 17.5 (4.2) Mean no. of underwear received (target = 6) 5.5 (1.3) 5.6 (1.3) Mean no. of NIA magazines received (target = 5) 0 0.03 (0.2) 4.5 (1.2) 4.7 (1.1) Mean no. of safe space sessions attended (target = 25) 0 0 20.7 (5.8) 21.2 (5.4) Note: Numbers shown in all columns to show potential for direct contamination in program implementation or through girls moving schools after program assignment A baseline survey was conducted between January to April 2017, prior to the start of the intervention. Face-to-face interviews were carried out by a trained research assistant in Swahili and data was entered directly onto a tablet. Interviews were held in a private location to assure confidentiality, most commonly in the girls’ homestead or school (after school hours). School attendance tracking was carried out in two phases. First, an initial enrollment exercise took place in June 2017 where all students who were present in school were registered. Second, this registration list was updated at the start of each data collection term. Daily attendance was taken by community-based data collectors for a period of four weeks (20 consecutive school days) per term, starting in September 2017 through July 2018, for a total of 60 days of observation across three school terms. Girls who were registered during the enrollment period were entered as absent if they were absent on that particular day, or dropped out of school/transferred to another school during the observation period. Attendance data was entered as missing for girls who were not registered during the enrollment exercise. The intervention was completed in October 2018 and endline data was collected in November and December 2018 using the same technique as the baseline survey. All girls from the baseline sample were eligible for interview, regardless of schooling status. Figure 1 shows the sample flow by arm and Fig. 2 shows the study timeline. Randomization and Masking The unit of randomization was the school. At the completion of baseline data collection in each sub-county, prior to the start of the intervention, public lotteries were held and schools within that sub-county were randomly assigned to one of the four study arms. Interviewers and respondents were blinded to study arm at baseline but not at endline. Outcomes Outcomes of interest related to education are: (i) school attendance, which was measured as the number of days a girl was attending school out of a total of 60 days. School attendance was measured only for girls who remained in the same school from baseline to the end of the survey; and, (ii) school engagement measured with a 0–8 score constructed as the number of responses reflecting higher school engagement to eight agree/disagree survey items (e.g., “You are attentive in class”). Menstruation management outcomes were binary measures including reporting having enough sanitary pads to comfortably manage menstruation and having leaked blood at school during menstruation. Outcomes of interest related to the RH education intervention include: (i) RH attitudes among girls who had started menstruating with a 0–12 score constructed as the number of responses reflecting a positive attitude to twelve agree/disagree survey items which captured girls’ feelings of shame, pride and comfort vis-à-vis menstruation (e.g., “I feel ashamed of my body when I have my period”); (ii) a pregnancy knowledge score with range 0–4 constructed as the number of correct answers to four pregnancy related items; (iii) whether a girl could spontaneously name a modern method of contraception; (iv) STI knowledge score with range 0–4 constructed as the number of correct answers to four STI related items; and (v) a HIV knowledge score with range 0–11 constructed as the number of correct answers to eleven HIV related items; (vi) gender norms in marriage with a 0–5 score constructed as the number of responses reflecting an equitable gender norm to five agree/disagree survey items (e.g., “If a husband and wife disagree on using family planning, the husband’s opinion should come first”); (vii) equitable adolescent gender norms with a 0–12 score constructed as the number of responses reflecting an equitable adolescent gender norm to twelve agree/disagree survey items (e.g., “Girls should be as independent as boys”); (viii) gendered sexual norms with a 0–5 score constructed as the number of responses reflecting an equitable sexual norm to five agree/disagree survey items (e.g., “Girls should cover up or they will attract unwanted sexual attention”); (ix) acceptability of intimate partner violence (IPV) was measured with an indicator on whether a girl finds IPV acceptable in any of five situations; and (x) general self-efficacy with a 0–10 score constructed as the number of responses reflecting self-efficacy to ten agree/disagree survey items (e.g., “You always manage to solve difficult problems if you try hard enough”). See Additional Table 1 for the list of survey items included in each outcome. The following covariates were measured at baseline to assess balance across study arms: girls’ age, cognitive score with range 0–16 measured from a subset of Raven’s Coloured Progressive Matrices, math test score with a range 0–37 derived from a test including progressively harder problems, literacy score with a range 0–4 derived from reading sentences, using excerpts from the Uwezo Kenya National Learning Assessment [ 23 ], household wealth quintile, parental living status, and sub-county. Sample Size and Analytical Sample Based on findings of levels of detected differences in school attendance from previous studies conducted in Kenya and Ghana [ 24 , 25 ], sample size calculations were conducted using Stata 14.1 to detect a minimum difference between study arms of 1.18 mean days of school missed over a 4-week period and a 10 percentage points increase in RH attitudes, assuming power of 0.80, significance level of 0.05, intra-cluster correlation (ICC) of 0.173 and a standard deviation (SD) of 3.57. A sample size of 35 clusters per arm and 20 girls per cluster at endline (25 girls per cluster at baseline, assuming a loss of 20% by endline) was needed. Therefore, 25 girls per school were included in the research sample. There was no oversampling to account for girls who had not started menstruating at baseline. The analytical sample for this paper focuses on the sample of girls who had started menstruating at baseline and were re-interviewed at endline. Estimates including both menstruating and non-menstruating girls at baseline are presented in Additional Tables 3 –6. Statistical Analysis To assess baseline balance across study arms among girls interviewed at endline, means and 95% confidence intervals (CIs) were estimated for the set of covariates described above as well as for outcome variables measured at baseline. An analysis was also conducted to assess bias due to potential differential attrition by study arms. An intent-to-treat (ITT) approach was used to estimate the effect of each intervention arm relative to the control group. For outcomes measured both at baseline and endline, difference-in-differences (DID) models with girl-level fixed-effects were estimated to compare the change between baseline and endline for each intervention arm relative to the control group [ 26 ]. Formally, the following linear regression model was estimated for each outcome: Y ijt = α 0 + α 1 S 2 ij + α 2 S 3 ij + α 3 S 4 ij + α 4 t + α 5 S 2 ij t + α 6 S 3 ij t + α 7 S 4 ij t + a ij + e ijt where Y ijt is the outcome of interest for girl i in school j at time t (t = 0 is baseline), S 2 is a dichotomous variable for a girl enrolled in a school assigned to Arm 2, S 3 is a dichotomous variable for a girl enrolled in a school assigned to Arm 3, S 4 is a dichotomous variable for a girl enrolled in a school assigned to Arm 4, a is a time-invariant individual effect and e is a random error. The coefficients related to the interactions between arms and time, α 5, α 6 and α 7 , provide the DID estimates for each treatment arm relative to the control. For outcomes with no comparable baseline data available, ANCOVA models were used to compare endline outcomes for each intervention arm relative to the control group while controlling for the following covariates measured at baseline: girls’ age, cognitive score, math and literacy scores, household wealth quintile, parental living status, and sub-county. Formally, the following linear regression model was estimated for each outcome: Y ijt = β 0 + β 1 S 2 ij + β 2 S 3 ij + β 3 S 4 ij + β 4 X ij0 + e ijt where X is a vector of the control variables measured at baseline. The coefficients related to the treatment arms, β 1, β 2 and β 3 , provide the estimates of the treatment effects for each treatment arm relative to the control. All regressions were estimated with robust standard errors accounting for clustering at the school level. Statistical analysis was conducted using Stata 14.1. Results Of the 3,489 girls interviewed at baseline, 2,725 (79%) had started menstruating. Of these, 2,544 (93%) were successfully interviewed at endline. There was no differential attrition across arms. The majority of girls lost to follow up could not be physically located and therefore were not interviewed. Girls in the analytical sample had a mean baseline age of 14.8 (SD:1.2). Girls’ skills were measured by their cognitive, math and literacy ability, and on average achieved scores of 55% (8.8/16 (SD:3.1)), 79% (29.4/37 (SD:4.0)) and 95% (mean 3.8/4 (SD:0.7)), respectively. At baseline, the majority of girls (82%) reported that both parents were alive (Table 2 ). Girls had moderately positive menstruation attitudes (mean score across arm: 7.6/12 (63.3%)). Girls were familiar with HIV (mean score across arms: 8.1/11 (74%)) and displayed lower levels of knowledge regarding when pregnancy is most likely to occur (mean score across arms: 1.9/4 (48%)), measures on norms and attitudes showed that equitable gender norms in marriage (mean score across arms: 3.2/5), equitable adolescent gender norms (mean score across arms 5.6/12), and gendered sexual norms (mean score across arms: 1.8/4). Girls general self-efficacy mean score across arms was 5.3/10, and the mean score across arms of how they perceived their engagement in school was 6.5 out of 8 (Table 4 ). Table 2 Baseline Characteristics Among Girls Menstruating at Baseline and Interviewed at Endline Arm 1 Control (n (%)) Arm 2 Pads Only (n (%)) Arm 3 RH Only (n (%)) Arm 4 Pads & RH (n (%)) Total n (%) Sample of girls menstruating at baseline 669 682 677 697 2,725 Sample of girls menstruating at baseline interviewed at endline N(%) 627 (93.7) 632 (92.7) 629 (92.9) 656 (94.1) 2,544 (93.4) Age (mean, SD) 14.8 (1.2) 14.7 (1.3) 14.8 (1.3) 14.8 (1.2) 14.8 (1.2) Skills Cognitive (max score = 16) (mean (SD)) 8.7 (3.1) 8.8 (3.1) 8.8 (3.2) 8.8 (3.1) 8.8 (3.1) Math (max score = 37) (mean (SD)) 29.4 (3.8) 29.2 (3.7) 29.3 (4.1) 29.7 (4.2) 29.4 (4.0) Literacy (max score = 4) (mean (SD)) 3.9 (0.5) 3.8 (0.7) 3.7 (0.8) 3.8 (0.6) 3.8 (0.7) SES quintiles n(% in each quintile) quintile 1 (most poor) 138 (22.0) 156 (24.7) 128 (20.4) 132 (20.1) 554 (21.8) quintile 2 141 (22.5) 131 (20.7) 135 (21.5) 137 (20.9) 544 (21.4) quintile 3 131 (20.9) 144 (22.8) 130 (20.7) 116 (17.7) 521 (20.5) quintile 4 106 (16.9) 107 (16.9) 112 (17.8) 139 (21.2) 464 (18.2) quintile 5 (least poor) 111 (17.7) 94 (14.9) 124 (19.7) 132 (20.1) 461 (18.1) Parents living status n(%) Knows both parents alive 512 (81.7) 512 (81.0) 521 (82.8) 531 (81.0) 2,076 (81.6) Knows mother only alive 97 (15.5) 89 (14.1) 80 (12.7) 91 (13.9) 357 (14.0) Knows father only alive 14 (2.2) 19 (3.0) 15 (2.4) 17 (2.6) 65 (2.6) Knows no parent alive 4 (0.6) 12 (1.9) 13 (2.1) 17 (2.6) 46 (1.8) Subcounty n(% in each subcounty) Ganze 204 (32.5) 212 (33.5) 220 (35.0) 211 (32.2) 847 (33.3) Magarini 211 (33.7) 223 (35.3) 222 (35.3 232 (35.4) 888 (34.9) Kaloleni 212 (33.8) 197 (31.2) 187 (29.7) 213 (32.5) 809 (31.8) Table 4 Baseline and Post Intervention Outcomes from Survey among Girls Menstruating at Baseline and Interviewed at Endline Arm 1 Control Arm 2 Pads Only Arm 3 RH Only Arm 4 Pads & RH School Engagement School engagement α (score 0–8): Baseline (N = 2,544) (mean(SD)n) 6.5 (1.4) n = 627 6.6 (1.4) n = 632 6.5 (1.4) n = 629 6.5 (1.3) n = 656 Endline (N = 2,432) (mean(SD)n) 6.8 (1.4) n = 593 6.8 (1.3) n = 606 6.8 (1.3) n = 600 6.9 (1.3) n = 633 Intra-cluster correlation coefficient 0.0214 Coefficient (95% CI) Reference -0.05 (-0.33, 0.22) 0.14 (-0.14, 0.42) 0.16 (-0.14, 0.47) P-value 0.703 0.329 0.294 Menstruation Management Has enough pads (= 1): Baseline (N = 2,544) (n(%)N) 136 (21.7), N = 627 126 (19.9), N = 632 119 (18.9), N = 629 155 (23.6), N = 656 Endline (N = 2,541) (n(%)N) 350 (55.9), N = 626 521 (82.4), N = 632 371 (59.1), N = 628 543 (82.9), N = 655 Intra-cluster correlation coefficient 0.102 Coefficient (95% CI) Reference 0.28 (0.20, 0.36) 0.06 (-0.03, 0.14) 0.25 (0.17, 0.33) P-value < 0.001 0.175 < 0.001 Reporting leaking (= 1): Baseline (N = 2,544) (n(%)N) 213 (34.0), N = 627 240 (38.0), N = 632 235 (37.4), N = 629 263 (40.1), N = 656 Endline (N = 2,432) (n(%)N) 161 (27.2), N = 593 125 (20.6), N = 606 143 (23.8), N = 600 138 (21.8), N = 633 Intra-cluster correlation coefficient 0.0139 Coefficient (95% CI) Reference -0.10 (-0.18, -0.03) -0.06 (-0.13, 0.01) -0.11 (-0.20, -0.02) P-value 0.005 0.118 0.014 Reproductive health attitudes Menstruation attitudes # (score:0–12): Baseline (N = 2,544) (mean(SD)n) 7.7 (1.7) n = 627 7.6 (1.8) n = 632 7.5 (1.8) n = 629 7.6 (1.7) n = 656 Endline (N = 2,432) (mean(SD)n) 8.1 (1.6) n = 593 8.2 (1.6) n = 606 8.6 (1.6) n = 600 8.9 (1.6) n = 633 Intra-cluster correlation coefficient 0.0714 Coefficient (95% CI) Reference 0.16 (-0.10, 0.41) 0.63 (0.40, 0.86) 0.85 (0.64, 1.07) P-value 0.230 < 0.001 < 0.001 Reproductive health knowledge Pregnancy knowledge (score:0–4): Baseline (N = 2,544) (mean(SD)n) 1.9 (0.9) n = 627 2.0 (0.8) n = 632 1.9 (0.9) n = 629 1.8 (0.9) n = 656 Endline (N = 2,544) (mean(SD)n) 2.2 (0.9) n = 627 2.1 (0.9) n = 632 2.2 (0.9) n = 629 2.3 (0.9) n = 656 Intra-cluster correlation coefficient 0.0412 Coefficient (95% CI) Reference -0.15 (-0.31, 0.01) 0.01 (-0.16, 0.17) 0.18 (0.02, 0.34) P-value 0.067 0.949 0.028 Can spontaneously name a method of modern contraception (= 1): Baseline (N = 2,544) (n(%)N) 321 (51.2), n = 321 357 (56.5), n = 357 326 (51.8), n = 326 349 (53.2), n = 349 Endline (N = 2,544) (n(%)N) 404 (64.4), n = 404 425 (67.2), n = 425 463 (73.6), n = 463 465 (70.9), n = 465 Intra-cluster correlation coefficient 0.0150 Coefficient (95% CI) Reference -0.03 (-0.11, 0.06) 0.09 (0.01, 0.17) 0.04 (-0.03, 0.12) P-value 0.524 0.036 0.275 STI knowledge score (score:0–4): Baseline (N = 2,544) (mean(SD)n) 0.4 (0.9) n = 627 0.5 (0.9) n = 632 0.4 (0.9) n = 629 0.4 (1.0) n = 656 Endline (N = 2,544) (mean(SD)n) 1.2 (1.2) n = 627 1.2 (1.2) n = 632 1.5 (1.2) n = 629 1.5 (1.2) n = 656 Intra-cluster correlation coefficient 0.0536 Coefficient (95% CI) Reference -0.01 (-0.19, 0.16) 0.31 (0.12, 0.49) 0.28 (0.10, 0.45) P-value 0.873 0.002 0.002 HIV knowledge score (score:0–11): Baseline (N = 2,544) (mean(SD)n) 7.8 (1.8) n = 627 8.0 (1.8) n = 632 8.0 (1.8) n = 629 8.0 (1.7) n = 656 Endline (N = 2,544) (mean(SD)n) 8.4 (1.7) n = 627 8.3 (1.8) n = 632 8.5 (1.7) n = 629 8.4 (1.6) n = 656 Intra-cluster correlation coefficient 0.0215 Coefficient (95% CI) Reference -0.30 (-0.61, 0.01) -0.05 (-0.34. 0.24) -0.18 (-0.43, 0 .08) P-value 0.058 0.728 0.170 Gender norms Gender norms in marriage (score:0–5): Baseline (N = 2,544) (mean(SD)n) 3.3 (1.1) n = 627 3.3 (1.2) n = 632 3.2 (1.2) n = 629 3.2 (1.1) n = 656 Endline (N = 2,544) (mean(SD)n) 3.0 (1.2) n = 627 3.0 (1.2) n = 632 2.9 (1.2) n = 629 3.0 (1.2) n = 656 Intra-cluster correlation coefficient 0.0283 Coefficient (95% CI) Reference 0.01 (-0.20, 0.22) 0.08 (-0.13, 0.29) 0.10 (-0.12, 0.31) P-value 0.921 0.455 0.374 Equitable adolescent gender norms (score:0–12): Baseline (N = 2,544) (mean(SD)n) 5.7 (1.9) n = 627 5.5 (2.0) n = 632 5.6 (1.9) n = 629 5.5 (2.0) n = 656 Endline (N = 2,544) (mean(SD)n) 6.2 (1.8) n = 627 6.1 (1.8) n = 632 6.6 (1.9) n = 629 6.6 (1.8) n = 656 Intra-cluster correlation coefficient 0.0507 Coefficient (95% CI) Reference 0.08 (-0.25, 0.40) 0.45 (0.15, 0.74) 0.57 (0.30, 0.85) P-value 0.640 0.003 < 0.001 Gendered sexual norms (score:0–5): Baseline (N = 2,544) (mean(SD)n) 1.8 (1.2) n = 627 1.8 (1.1) n = 632 1.7 (1.2) n = 629 1.8 (1.2) n = 656 Endline (N = 2,544) (mean(SD)n) 1.9 (1.2) n = 627 1.9 (1.2) n = 632 2.2 (1.3) n = 629 2.2 (1.3) n = 656 Intra-cluster correlation coefficient 0.0640 Coefficient (95% CI) Reference 0.02 (-0.18, 0.21) 0.46 (0.26, 0.65) 0.36 (0.15, 0.57) P-value 0.878 < 0.001 0.001 Agrees with IPV (= 1): Baseline (N = 2,544) (n(%)N) 458 (73.0), n = 458 458 (72.5), n = 458 456 (72.5), n = 456 465 (70.9), n = 465 Endline (N = 2,544) (n(%)N) 454 (72.4), n = 454 461 (72.9), n = 461 477 (75.8), n = 477 470 (71.6), n = 470 Intra-cluster correlation coefficient 0.0344 Coefficient (95% CI) Reference 0.01 (-0.06, 0.09) 0.04 (-0.04, 0.12) 0.01 (-0.05, 0.08) P-value 0.772 0.323 0.687 Self-efficacy General self-efficacy (score:0–10): Baseline (N = 2,544) (mean(SD)n) 5.1 (2.6) n = 627 5.2 (2.5) n = 632 5.2 (2.6) n = 629 5.5 (2.6) n = 656 Endline (N = 2,544) (mean(SD)n) 5.7 (2.4) n = 627 5.6 (2.5) n = 632 6.6 (2.3) n = 629 6.3 (2.5) n = 656 Intra-cluster correlation coefficient 0.0444 Coefficient (95% CI) Reference -0.16 (-0.54, 0.23) 0.80 (0.37, 1.24) 0.22 (-0.20, 0.64) P-value 0.420 < 0.001 0.301 Notes: The table reports post-intervention means for the control arm, and the estimated effect of the intent-to-treat for each study arm relative to the control arm. Difference-in-differences were estimated from regressions with girl-level fixed effects and robust standard errors accounting for clustering at the school level. Higher scores equate to higher knowledge and more positive/equitable norms and attitudes. + Differences at endline were estimated using ANCOVA. Regressions controlled for the following covariates measured at baseline: cognitive, math and literacy test scores, socio-economic quintile, age, parental living status, subcounty, and were estimated with robust standard errors accounting for clustering at the school level. α School engagement was only measured among respondents who were in school; at baseline all menstruating girls were in school, at endline 2,432 girls were still in school. Table 3 shows results from the school attendance tracking instrument. Attendance was observed for the full 60 days for 2,265 (89%) of girls in the analytical sample (no statistically significant difference by arm). On average, girls attended 56 days out of the 60 (SD: 7.6), and there was no difference between arms. Table 3 School Attendance Outcomes from School Attendance Tracking Instrument among Girls Menstruating at Baseline and Interviewed at Endline Arm 1 Control Arm 2 Pads Only Arm 3 RH Only Arm 4 Pads & RH Respondents in analytical sample (N) 627 632 629 656 Attendance was taken for all 60 days (% (N)) £ 84.7 (531) 87.3 (552) 86.5 (544) 85.7 (562) Intra-cluster correlation coefficient 0.000 Coefficient (95% CI) Reference 0.022 (-0.047, 0.092) 0.015(-0.049, 0.079) 0.007 (-0.069, 0.083) P-value 0.524 0.431 0.862 Mean # of days attended (mean (SD)) £ 55.6 (6.5) 56.0 (6.3) 55.8 (6.8) 56.2 (6.1) Intra-cluster correlation coefficient 0.059 Coefficient (95% CI) Reference 0.37 (-0.73, 1.46) 0.14 (-0.99, 1.26) 0.58 (-0.37, 1.52) P-value 0.507 0.812 0.230 Observed attendance + (% (N)): 91.4 (619) 91.8 (625) 91.6 (622) 92.2 (647) Intra-cluster correlation coefficient 0.056 Coefficient (95% CI) Reference 0.42 (-1.94, 2.78) 0.28 (-2.00, 2.57) 0.75 (-0.97, 2.48) P-value 0.725 0.806 0.389 Notes: The table reports post-intervention means for the control arm, and the estimated effect of the intent-to-treat for each study arm relative to the control arm. Difference-in-differences were estimated from regressions with girl-level fixed effects and robust standard errors accounting for clustering at the school level. Higher scores equate to higher knowledge and more positive/equitable norms and attitudes. £ Attendance data only includes those who remained in the same school throughout the 60 days. + Differences at endline were estimated using ANCOVA. Regressions controlled for the following covariates measured at baseline: cognitive, math and literacy test scores, socio-economic quintile, age, parental living status, subcounty, and were estimated with robust standard errors accounting for clustering at the school level. Table 4 shows results from outcomes measured in the girl survey instrument. A positive increase was observed in girls reporting having enough pads in the pads only (DID coeff: 0.28 (95%CI:0.20, 0.36)) and combined arms (DID coeff: 0.25 (95%CI:0.17, 0.33)), compared to the control. However, because girls in the control and RH only arms also had a significant increase in reporting having enough pads relative to baseline (36.5 and 43.3 percentage point increase for the control and RH only arms respectively), we carried out a post-hoc regression analysis to test if those increases explained the null attendance results. The post-hoc analysis showed no association between having enough pads and school attendance in girls who had started menstruating at baseline (coeff: 0.0004, 95% CI: -0.000585, 0.001; p value = 0.457). Girls also reported less leaking in both the pads only (DID coeff: -0.10 (95%CI:-0.18, -0.03)) and combined arms (DID coeff: -0.11 (95%CI:-0.20, -0.02)). A positive increase was observed in menstruation attitudes in both the RH only (DID coefficient (coeff):0.63 (95%CI:0.40,0.86)) and combined arms (DID coeff: 0.85 (95%CI:0.64,1.07)). A comparison of estimates between intervention arms (combined v. pads only for menstruation outcomes; combined v. RH only for RH and norms outcomes) showed a larger effect size on RH attitudes in the combined arm as compared to the RH only arm (see Additional Table 2 ). For the indicators measuring RH knowledge, an increase was observed in pregnancy knowledge in the combined arm (difference-in-difference (DID) coefficient: 0.18 (95% CI:0.02, 0.34)). An increase was also observed in the percentage of girls who could spontaneously mention a modern method of contraception in the RH only arm (DID coefficient: 0.09 (95% CI: 0.01, 0.17)) and in STI knowledge in the RH only arm (DID coefficient: 0.31 (95%CI: 0.12, 0.49)) and combined arm (DID coefficient: 0.28 (95%CI: 0.10, 0.45)). For the indicators measuring norms and attitudes, positive increases were observed in gender norms measuring equitable adolescent gender norms in adolescents in both the RH only (DID coefficient:0.45 (95%CI:0.15,0.74)) and combined arms (DID coefficient: 0.57 (95%CI: 0.30, 0.85)), as well as in norms on gendered sexual norms similarly in both the RH only (DID coefficient: 0.46 (95%CI:0.26,0.65)) and combined arms (DID coefficient: 0.36 (95%CI:0.15, 0.57)). Finally, there was an increase observed in general self-efficacy in the RH only arm (DID coefficient:0.80 (95%CI:0.37, 1.24)). A comparison between intervention arms showed a larger effect size on general self-efficacy in the RH only arm as compare to the combined arm (Additional Table 2 ). Supplementary tables show the impact of the intervention on the whole sample which includes menstruating and non-menstruating girls (Additional Tables 4 –6). There were no significant differences as compared to the restricted analytical sample. Discussion In this cluster randomized trial of evaluating sanitary pad distribution and RH education in Kenya we see that neither intervention component, alone or in combination, improved school attendance among girls in primary grade 7. This finding is consistent with several recent quantitative studies rigorously examining the relationship between sanitary pad distribution and/or RH education on attendance [ 13 , 15 ]. There are a few hypotheses as to why the intervention did not translate into improved school attendance, mainly related to alternative reasons for why girls miss school. While it is likely, and supported in the qualitative literature, that girls experience physical and emotional discomfort during menstruation, it is possible that it is not a direct cause of absenteeism. Quantitative studies assessing reasons girls miss school mention poverty and lack of ability to pay school fees, low value placed on girls’ education and instability in households as the most common causes of absenteeism [ 27 , 28 ], none of which are addressed via access to sanitary pads or RH education. Therefore, interventions addressing these causes might be better placed to have an effect on girls’ school attendance. In addition, this paper supports the recent push to move away from a central focus on school attendance as the central outcome of MHM programs [ 29 ]. This trial did show that the RH education improved girls’ RH attitudes, in particular increasing the pride and comfort they feel vis-à-vis menstruation, as well as RH knowledge, endorsement of equitable gender norms and general self-efficacy. This is also consistent with the literature on comprehensive sexuality education and its ability, when implemented well and addressing gender and power, to improve RH outcomes [ 30 ]. Furthermore, regardless of whether sanitary pads or RH education translate into improved attendance at school, it is recognized that girls have the right to manage their menstruation safely and with dignity [ 31 ] and have the right to adequate sexual and reproductive health information [ 32 ]. There are a few limitations of the study that affect the external validity of the findings. First, the study was implemented in one rural setting – three sub-counties within one county. Therefore, while the findings could be relevant to other rural areas in the country and region, the findings cannot be generalized to urban areas. Second, the intervention was implemented with girls in primary grade 7 at the start of the study, which means that the findings cannot be generalized to girls earlier in primary school or in secondary school. Third, it is possible that the attendance taking activities heightened students’ and schools’ attention to attendance and inadvertently stimulated attendance. Fourth, the gender norms scales, although a significant effect was detected, had low internal consistency as indicated by the alphas, suggesting low scale reliability. Fifth, the study did not oversample for girls who had not yet started menstruating at baseline, resulting in a slightly smaller number of girls per cluster in the analytical sample than calculated for in the power estimates; however, given the number of clusters per arm, the loss of power is minimal. Finally, the government pad distribution program in schools or other market factors such as a general reduction in the price of pads over time, although evenly distributed across arms, may have increased the access to pads in Kilifi, beyond a threshold that would show differences between arms. However, the post-hoc analysis conducted indicates that there was no association between access to pads and school attendance, independent of random assignment to study arm. This study also has several strengths which allow it to make a significant contribution to the literature on the impact of MHM interventions on education and health outcomes. Key study design features – random assignment, a large sample size, 18-month follow up period and strong fidelity to the design during implementation – address key limitations of previous research, which include small sample sizes, inability to determine causation, non-random assignment to study arms, and shorter follow-up periods. This increases the relevance of the results as it contradicts previous, less rigorous studies assessing the same outcomes [ 8 , 9 , 14 , 24 ]. Conclusions The results of this study suggest that in this specific context, neither sanitary pad distribution nor RH education, on their own or together, are sufficient to improve girls’ school attendance or engagement in class and therefore would caution again positioning MHM activities as girls education interventions. These activities would be better framed as part of comprehensive sexuality education programs aiming to address girls’ stigma and shame associated with menstruation, access to menstrual management products, inequitable gender norms and lack of knowledge key RH issues. List Of Abbreviations CI – Confidence Interval DID – Difference in Differences ICC – Intra-Cluster Correlation IPV – Intimate Partner Violence IRB – Institutional Review Board ITT – Intent-to-Treat MHM – Menstrual Health Management RCT – Randomized Controlled Trial RH – Reproductive Health SD – Standard Deviation STI – Sexually Transmitted Infection WASH – Water, Sanitation and Hygiene Declarations Ethics approval and consent to participate The study was approved by the Population Council Institutional Review Board (IRB) (p768) and the AMREF Ethics and Scientific Review Committee (p292-2016). Written informed consent was obtained from respondents ages 18 and above. Written informed consent was obtained from a parent or guardian and then oral assent obtained for girls under age 18. Consent for publication Not applicable Availability of data and materials Study data in this paper, including de-identified individual data and data dictionary, will be made available open access upon publication. The data will be stored and available for downloading via the Adolescent Data Hub - http://popcouncil.org/girlcenter/adolescentdatahub/ Competing Interests The authors declare that they have no competing interest Funding The study was funded by a grant from the Bill & Melinda Gates Foundation (OPP1140962) via a sub-contract from ZanaAfrica. Representatives of the funder reviewed and approved the study design, but had no role in data collection, or analysis and interpretation reported here. Authors’ contributions EM and KA designed and conceptualized the study. BK and ESH conducted the data analysis. KA, BK and ESH drafted the manuscript. All authors reviewed and commented on the manuscript. Acknowledgements The authors would like to thank ZanaAfrica for providing leadership for the project implementation, including coordinating stakeholders and developing the intervention materials – Nia Teen sanitary pads, Nia Teen Magazine and the Nia Yetu curriculum. We also thank colleagues Barbara Mensch and Stephanie Psaki for reviewing and commenting on earlier drafts of the paper. We acknowledge the efforts of the members of the Nia Project Research Advisory Committee (RAC) – Caroline Kabiru, Cynthia Lloyd and Matthew Freeman throughout the study and in particular for providing feedback on the draft of the manuscript. Finally, we thank all of the adolescent girls who took the time to participate in the study. An earlier version of this paper was presented at the 8 th Africa Population Conference in Entebbe, Uganda held from November 18-22, 2019. References Sommer M: An overlooked priority: puberty in sub-Saharan Africa . American journal of public health 2011, 101 (6):979-981. Mason L, Nyothach E, Alexander K, Odhiambo FO, Eleveld A, Vulule J, Rheingans R, Laserson KF, Mohammed A, Phillips-Howard PA: ‘We Keep It Secret So No One Should Know’–A Qualitative Study to Explore Young Schoolgirls Attitudes and Experiences with Menstruation in Rural Western Kenya . PloS one 2013, 8 (11):e79132. Tegegne TK, Sisay MM: Menstrual hygiene management and school absenteeism among female adolescent students in Northeast Ethiopia . BMC public health 2014, 14 (1):1. Sommer M: Where the education system and women's bodies collide: The social and health impact of girls' experiences of menstruation and schooling in Tanzania . Journal of adolescence 2010, 33 (4):521-529. Lahme AM, Stern R, Cooper D: Factors impacting on menstrual hygiene and their implications for health promotion . Global health promotion 2018, 25 (1):54-62. McMahon SA, Winch PJ, Caruso BA, Obure AF, Ogutu EA, Ochari IA, Rheingans RD: 'The girl with her period is the one to hang her head'Reflections on menstrual management among schoolgirls in rural Kenya . BMC international health and human rights 2011, 11 (1):7. Crichton J, Ibisomi L, Gyimah SO: Mother–daughter communication about sexual maturation, abstinence and unintended pregnancy: Experiences from an informal settlement in Nairobi, Kenya . Journal of Adolescence 2012, 35 (1):21-30. Miiro G, Rutakumwa R, Nakiyingi-Miiro J, Nakuya K, Musoke S, Namakula J, Francis S, Torondel B, Gibson LJ, Ross DA: Menstrual health and school absenteeism among adolescent girls in Uganda (MENISCUS): a feasibility study . BMC women's health 2018, 18 (1):4. Dolan CS, Ryus CR, Dopson S, Montgomery P, Scott L: A Blind Spot in Girls' Education: Menarche and its Webs of Exclusion in Ghana . Journal of International Development 2014, 26 (5):643-657. Sumpter C, Torondel B: A systematic review of the health and social effects of menstrual hygiene management . PloS one 2013, 8 (4):e62004. Hennegan J, Montgomery P: Do Menstrual Hygiene Management Interventions Improve Education and Psychosocial Outcomes for Women and Girls in Low and Middle Income Countries? A Systematic Review . PloS one 2016, 11 (2):e0146985. Phillips-Howard PA, Nyothach E, ter Kuile FO, Omoto J, Wang D, Zeh C, Onyango C, Mason L, Alexander KT, Odhiambo FO: Menstrual cups and sanitary pads to reduce school attrition, and sexually transmitted and reproductive tract infections: a cluster randomised controlled feasibility study in rural western Kenya . BMJ open 2016, 6 (11):e013229. Benshaul-Tolonen A, Zulaika G, Nyothach E, Oduor C, Mason L, Obor D, Alexander KT, Laserson KF, Phillips-Howard PA: Pupil Absenteeism, Measurement, and Menstruation: Evidence from Western Kenya . 2019. Montgomery P, Hennegan J, Dolan C, Wu M, Steinfield L, Scott L: Menstruation and the Cycle of Poverty: A Cluster Quasi-Randomised Control Trial of Sanitary Pad and Puberty Education Provision in Uganda . PLOS ONE 2016, 11 (12):e0166122. Khanna M: The Precocious Period: The Impact of Early Menarche on Schooling in India . Available at SSRN 3419041 2019. Grant M, Lloyd C, Mensch B: Menstruation and school absenteeism: evidence from rural Malawi . Comparative education review 2013, 57 (2):260-284. Sommer M, Sutherland C, Chandra-Mouli V: Putting menarche and girls into the global population health agenda . Reproductive health 2015, 12 (1):24. Education Mo: Republic of Kenya: A Policy Framework: Aligning Education and Training to the Constitution of Kenya 2010 and Kenya Vision 2030 and Beyond . In . : Ministry of Education Nairobi; 2012. Kenya National Bureau of Statistics, ICF International: Kenya Demographic and Health Survey 2014 . In . Calverton, Maryland: KNBS and ICF International; 2015. Technology MoESa: A Policy Framework for Reforming Education and Training for Sustainable Development in Kenya . In . Kenya: Government of Kenya; 2019. Girod C, Ellis A, Andes KL, Freeman MC, Caruso BA: Physical, Social, and Political Inequities Constraining Girls’ Menstrual Management at Schools in Informal Settlements of Nairobi, Kenya . Journal of Urban Health 2017, 94 (6):835-846. Muthengi E, Austrian K: Cluster randomized evaluation of the Nia Project: study protocol . Reproductive health 2018, 15 (1):218. Kenya U: Are our children learning? Annual learning assessment report . In . : Uwezo Publications; 2014. Montgomery P, Ryus CR, Dolan CS, Dopson S, Scott LM: Sanitary pad interventions for girls' education in Ghana: a pilot study . PloS one 2012, 7 (10):e48274. Wilson E, Reeve J, Pitt A, Sully B, Julious S: INSPIRES: Investigating a reusable sanitary pad intervention in a rural educational setting-evaluating the acceptability and short term effect of teaching Kenyan school girls to make reusable sanitary towels on absenteeism and other daily activities: a partial preference parallel group, cluster randomised control trial . 2012. Khandker S, B. Koolwal G, Samad H: Handbook on impact evaluation: quantitative methods and practices : The World Bank; 2009. Prakash R, Beattie T, Javalkar P, Bhattacharjee P, Ramanaik S, Thalinja R, Murthy S, Davey C, Blanchard J, Watts C: Correlates of school dropout and absenteeism among adolescent girls from marginalized community in north Karnataka, south India . Journal of adolescence 2017, 61 :64-76. Roby JL, Erickson L, Nagaishi C: Education for children in sub-Saharan Africa: Predictors impacting school attendance . Children and Youth Services Review 2016, 64 :110-116. Benshaul-Tolonen A, Zulaika G, Sommer M, Phillips-Howard PA: Measuring Menstruation-Related Absenteeism Among Adolescents in Low-Income Countries . In: The Palgrave Handbook of Critical Menstruation Studies. edn. Edited by Bobel C, Winkler IT, Fahs B, Hasson KA, Kissling EA, Roberts T-A. Singapore: Springer Singapore; 2020: 705-723. Haberland NA: The case for addressing gender and power in sexuality and HIV education: A comprehensive review of evaluation studies . International Perspectives on Sexual and Reproductive Health 2015, 41 (1):31-42. Sommer M, Hirsch JS, Nathanson C, Parker RG: Comfortably, safely, and without shame: defining menstrual hygiene management as a public health issue . American Journal of Public Health 2015, 105 (7):1302-1311. Chandra-Mouli V, Svanemyr J, Amin A, Fogstad H, Say L, Girard F, Temmerman M: Twenty years after International Conference on Population and Development: where are we with adolescent sexual and reproductive health and rights? Journal of Adolescent Health 2015, 56 (1):S1-S6. Supplementary Files AdditionalTables20Apr2021.docx CONSORTChecklistNiaTrial20Apr2021.docx Cite Share Download PDF Status: Published Journal Publication published 30 Aug, 2021 Read the published version in Reproductive Health → Version 2 posted Editorial decision: Minor revision 02 Jun, 2021 Reviewer # 3 agreed at journal 23 May, 2021 Review # 2 received at journal 15 May, 2021 Reviews received at journal 10 May, 2021 Reviewer # 2 agreed at journal 10 May, 2021 Reviewers invited by journal 10 May, 2021 Reviewer # 1 agreed at journal 10 May, 2021 Review # 1 received at journal 10 May, 2021 Editor assigned by journal 21 Apr, 2021 Submission checks completed at journal 21 Apr, 2021 Editor invited by journal 21 Apr, 2021 First submitted to journal 20 Apr, 2021 You are reading this latest preprint version Show more versions Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Muthengi","email":"","orcid":"","institution":"Population Council","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Eunice","middleName":"N.","lastName":"Muthengi","suffix":""},{"id":25770547,"identity":"39d45c30-6804-4872-9e53-61819537d28f","order_by":3,"name":"Erica Soler-Hampejsek","email":"","orcid":"","institution":"Independent Consultant","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Erica","middleName":"","lastName":"Soler-Hampejsek","suffix":""}],"badges":[],"createdAt":"2020-11-10 21:34:02","currentVersionCode":2,"declarations":"","doi":"10.21203/rs.3.rs-105989/v2","doiUrl":"https://doi.org/10.21203/rs.3.rs-105989/v2","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12978-021-01223-7","type":"published","date":"2021-08-31T00:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":8930411,"identity":"c597f03c-09ce-488c-af98-9c1f110af154","added_by":"auto","created_at":"2021-05-07 19:10:26","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":94673,"visible":true,"origin":"","legend":"Sample Flow","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-105989/v2/afa90d8a23eb7fd9d4c798a8.png"},{"id":8929517,"identity":"698c496d-e1be-43a0-8118-0a5906ef22fc","added_by":"auto","created_at":"2021-05-07 19:04:26","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":98846,"visible":true,"origin":"","legend":"Study Design","description":"","filename":"Fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-105989/v2/2e1168fe2b4f37b71fd825ba.png"},{"id":13691766,"identity":"0a8f0f37-37c9-4db5-99fc-ad73ead9c201","added_by":"auto","created_at":"2021-09-17 12:40:05","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1480832,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-105989/v2/f38c572a-015e-475d-b9d6-bf466b6b60a9.pdf"},{"id":8930022,"identity":"39a255ed-7e26-45b1-97f3-28048a4e9c46","added_by":"auto","created_at":"2021-05-07 19:07:26","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":53138,"visible":true,"origin":"","legend":"","description":"","filename":"AdditionalTables20Apr2021.docx","url":"https://assets-eu.researchsquare.com/files/rs-105989/v2/c121a825ce45cdf078b30fd5.docx"},{"id":8930024,"identity":"9fbcf7a1-3b3b-4621-b3b4-76f2750d9b40","added_by":"auto","created_at":"2021-05-07 19:07:26","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":35607,"visible":true,"origin":"","legend":"","description":"","filename":"CONSORTChecklistNiaTrial20Apr2021.docx","url":"https://assets-eu.researchsquare.com/files/rs-105989/v2/212cc2213ff198f9a2c89421.docx"}],"financialInterests":"","formattedTitle":"Effects of sanitary pad distribution and reproductive health education on primary school attendance and reproductive health knowledge and attitudes in Kenya: a cluster randomized controlled trial","fulltext":[{"header":"Plain English Summary","content":" \u003cp\u003eAdolescent girls face a range of challenges that may compromise their chances of completing school or their sexual and reproductive health. These challenges can be even further complicated by girls\u0026rsquo; feelings of shame about their bodies, in particular about menstruation, or their lack of sanitary products to help them manage menstruation. This study sought out to assess if providing girls in grade 7 in a rural, coastal area of Kenya with sanitary pads and sex education would alleviate some of those challenges. One hundred and forty schools were included in the study and 35 each were randomly assigned to one of the following program packages: 1) control (standard government provision of pads and health education); 2) provision of sanitary pads; 3) sex education; or 4) both provision of sanitary pads and sex education. The study found that none of the three program packages had an impact on school attendance, however those that participated in the sex education felt more positively about menstruation, knew more about sexual and reproductive health, had more equitable gender norms and were more self-confident at the end of the program. The study results show that addressing girls\u0026rsquo; menstrual health challenges are important, but are better positioned as part of comprehensive sexuality education programs addressing stigma and shame associated with menstruation, access to menstrual products, inequitable gender norms and sexual and reproductive health knowledge gaps, as opposed to a girls education intervention.\u003c/p\u003e "},{"header":"Background","content":" \u003cp\u003eAs girls enter puberty their experience of sexual and gender based violence, school dropout, and early marriage starts to increase [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. According to several qualitative studies in Africa, these vulnerabilities are exacerbated by girls\u0026rsquo; lack of knowledge of their bodies and rights, and their inability to safely and comfortably manage their menstruation [\u003cspan additionalcitationids=\"CR3 CR4\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eQualitative studies conducted in Kenya, and other countries in sub-Saharan Africa, have identified several challenges girls face in managing their menstruation, including lack of access to menstrual products and lack of accurate information about menstruation. The studies also clarified that neither teachers [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] nor mothers [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] felt well placed to deliver information on menstruation, let alone a wider range of sexual and reproductive health topics. In additional qualitative studies, girls expressed that they missed school during their menses due to lack of menstrual products, fear of leaking blood on their uniforms and pain from menstrual cramps [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. A sense of shame, discomfort and need for secrecy around the topic of menstruation was also a common theme [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Finally, girls expressed that when they were menstruating they experienced anxiety and stress about staining their uniforms, giving off an odor or in general being found out to be menstruating that made it difficult for them to concentrate or participate fully in class [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. The literature on the challenges linked to a lack of menstrual hygiene products and knowledge has been largely qualitative.\u003c/p\u003e \u003cp\u003eWhile several programs have previously been developed to address girls\u0026rsquo; menstrual health management (MHM) needs in Kenya, as well as globally, few have been rigorously evaluated, and where evidence does exist on the effect of such programs on reproductive health (RH) and schooling outcomes, the results have been mixed. A 2013 systematic review of the literature on the effects of MHM programs concluded that while there was some evidence on the effect of MHM on psycho-social outcomes, the impact on RH outcomes was unclear. They also noted that quantitative evidence was lacking on the effects of MHM on reducing school absenteeism and that there was an absence of rigorous studies showing the impact of MHM on girls\u0026rsquo; general health and well-being [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn 2016, Hennegan and Montgomery published an MHM-related systematic review that assessed the risk of bias in eight studies and synthesized the evidence on the effects of MHM interventions on educational and psychosocial outcomes for women and girls in low and middle income countries [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. The authors outlined two dominant types of MHM intervention approaches: hardware, or the provision of physical objects useful for MHM, such as menstrual cups or sanitary pads; and software, or the provision of human and social capital through education and non-tangible benefits. The review found considerable risk of bias in these studies and overall weaknesses in study designs such as small sample sizes, inability to determine causation, non-random assignment to study arms and short follow-up periods. Therefore, the review concluded that while there are some indications of positive results, insufficient evidence existed for the effectiveness of MHM interventions.\u003c/p\u003e \u003cp\u003eSince that review, the evidence base on the link between menstruation, menstrual products and education and RH outcomes has increased. A cluster RCT in rural Western Kenya found that while provision of menstrual cups or sanitary pads was associated with reduced sexually transmitted infection (STI) risk, there was no association with school dropout [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. An analysis of school attendance data from this study showed a positive impact on attendance due to sanitary pad distribution, however, that effect washed out in models that accounted for absence due to school transfer [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. A quasi-randomized controlled trial implemented in Uganda found positive effects from distribution of reusable sanitary pads and puberty education, both alone and combined; however the results should be interpreted with caution as the study had poor participant retention and a lack of fidelity to the intervention [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. A cross sectional study of girls aged 14\u0026ndash;18 years in a rural area of Uganda showed associations between menstruation and school attendance [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Finally, an analysis of longitudinal data on adolescent health in India showed that, conditional on school enrollment, menstruation is not a significant predictor of school attendance [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], which is a similar finding to an earlier study in Malawi that did not find an effect of menstruation on school attendance [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite the increase in quantitative evidence on the impact of menstrual products on education outcomes, studies assessing the effect of combined hardware and software interventions are lacking. In addition, MHM interventions are often embedded within the education or water, sanitation and hygiene (WASH) fields, yet the case has more recently been made that MHM and puberty education should be seen as an entry into girls discussing their bodies, and from which more comprehensive conversations on RH could then take place [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Evidence on the combined effect of an MHM and RH intervention has the potential to move that case forward. Therefore, this study aims to assess the effects of a combined hardware and software intervention, integrating both MHM and broader RH content, on education and RH outcomes.\u003c/p\u003e "},{"header":"Methods","content":"\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n\u003ch2\u003eSetting\u003c/h2\u003e\n\u003cp\u003eThis study took place in Kilifi County, Kenya in 2017\u0026ndash;2018. Kilifi was selected for the study as it ranked low in both education and RH indicators: for example, the transition rate from primary to secondary was 40% in 2010 compared to the national rate of 72% [\u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e]; further, around 22% of girls ages 15\u0026ndash;19 have begun childbearing, as compared to the national average of 18% [\u003cspan class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e\n\u003cp\u003eIn Kenya, the school year starts in January and consists of three academic terms per year. Primary school is from grade 1 through grade 8, and secondary school is from grade 9 to grade 12. While universal primary education for girls has nearly been achieved, there remains significant variation at the county level, gaps in the transition to secondary school and challenges with pupil absenteeism [\u003cspan class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e20\u003c/span\u003e]. The Government of Kenya has committed to sanitary pad distribution in schools; however, evaluations have shown that supply chains of sanitary pads to schools were not reliable, and girls were not assured of equitable pad provision [\u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n\u003ch2\u003eData and Study Design\u003c/h2\u003e\n\u003cp\u003eThis study assessed the impact of the Nia Project via a longitudinal, cluster-randomized controlled trial in 140 public primary schools in three rural sub-counties (Magarini, Kaloleni and Ganze) of Kilifi County, Kenya.\u003c/p\u003e\n\u003cp\u003eStudy schools were randomly assigned to one of the following four study arms:\u003c/p\u003e\n\u003col\u003e\n\u003cli\u003e\n\u003cp\u003eControl group\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eSanitary pads distribution (pads only)\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eReproductive health education (RH only)\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eSanitary pads distribution\u0026thinsp;+\u0026thinsp;reproductive health education (combined)\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eThe sub-counties and schools were selected in collaboration with the Kilifi County Department of Education. Eligible clusters included all non-boarding schools in the three sub-counties with at least 25 girls enrolled in primary grade 7. A total of 215 schools were mapped, and a one kilometer buffer was created around each school. For schools with overlapping boundaries, one school was randomly selected resulting in a list of 173 schools. Enrollment and school type were verified for each school in the first quarter of 2017. Based on this exercise, 33 schools were excluded leaving a sample of 140 schools: 44 in Magarini, 50 in Kaloleni, and 46 in Ganze (see Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). All eligible schools (n\u0026thinsp;=\u0026thinsp;140) were included in the study.\u003c/p\u003e\n\u003cp\u003eAll girls enrolled in grade 7 in a randomly selected school were eligible for inclusion in the study sample. In schools with only 25 girls in grade 7, all girls were included in the research sample. In schools with a larger number of girls, 25 girls were randomly selected for the research sample and five additional girls were selected as alternates. A total of 3,489 girls were interviewed as part of the baseline survey. All grade 7 girls, including those who were not in the research sample and those who had not yet started menstruating, were eligible to receive interventions in order to streamline program delivery. Grade 7 was selected as it would allow for observation of the transition to secondary school within the study timeframe.\u003c/p\u003e\n\u003cp\u003eThe Nia Project included the following two components:\u003c/p\u003e\n\u003cp\u003e1) Sanitary pads: girls received, on a monthly basis for the entire duration of the project, one packet of ten disposable sanitary pads of ZanaAfrica\u0026rsquo;s Nia Teen brand. In addition, girls received two pairs of underwear at the start of the intervention, and an additional pair at the end of each subsequent school term.\u003c/p\u003e\n\u003cp\u003e2) RH education: a 25-session curriculum, \u003cem\u003eNia Yetu\u003c/em\u003e, was delivered by trained facilitators during girls-only health clubs held during time allocated for extra-curricular activities in schools. The curriculum covered a variety of topics including puberty, menstrual health management, reproductive systems, self-esteem, gender, human rights, power dynamics, sexual violence, assertiveness, decision making, relationships, teen pregnancy, STIs and HIV, peer pressure, drug use and conflict management. Girls also received a health magazine developed by ZanaAfrica, \u003cem\u003eNia Teen\u003c/em\u003e, designed to appeal to adolescent girls and convey core RH messaging through storytelling using aspirational personal stories, a relatable comic-style story, and activities. The magazine was distributed at the start of each school term for a five-term period. Each issue corresponded to the topics covered in the \u003cem\u003eNia Yetu\u003c/em\u003e curriculum that term.\u003c/p\u003e\n\u003cp\u003eTable\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e shows take-up of the two Nia Project components by study arms: girls in the pads only and combined arms received on average 17.5 out of 20 packets of sanitary pads and girls in the RH only and combined arms participated on average in 21 out of 25 RH sessions. Additional details on the Nia Project, theory of change, and study design have been published elsewhere [\u003cspan class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab1\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eNia Project uptake Among Girls Menstruating at Baseline and Interviewed at Endline\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eArm 1\u003c/p\u003e\n\u003cp\u003eControl\u003c/p\u003e\n\u003cp\u003en\u0026thinsp;=\u0026thinsp;627\u003c/p\u003e\n\u003cp\u003e(mean (SD))\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eArm 2\u003c/p\u003e\n\u003cp\u003ePads Only\u003c/p\u003e\n\u003cp\u003en\u0026thinsp;=\u0026thinsp;632\u003c/p\u003e\n\u003cp\u003e(mean (SD))\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eArm 3\u003c/p\u003e\n\u003cp\u003eRH Only\u003c/p\u003e\n\u003cp\u003en\u0026thinsp;=\u0026thinsp;629\u003c/p\u003e\n\u003cp\u003e(mean (SD))\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eArm 4\u003c/p\u003e\n\u003cp\u003ePads \u0026amp; RH\u003c/p\u003e\n\u003cp\u003en\u0026thinsp;=\u0026thinsp;656\u003c/p\u003e\n\u003cp\u003e(mean (SD))\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMean no. of pads received (target\u0026thinsp;=\u0026thinsp;20)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e17.5 (4.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e17.5 (4.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMean no. of underwear received\u003c/p\u003e\n\u003cp\u003e(target\u0026thinsp;=\u0026thinsp;6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.5 (1.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e5.6 (1.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMean no. of NIA magazines received (target\u0026thinsp;=\u0026thinsp;5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.03 (0.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.5 (1.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e4.7 (1.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMean no. of safe space sessions attended (target\u0026thinsp;=\u0026thinsp;25)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20.7 (5.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e21.2 (5.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"5\"\u003eNote: Numbers shown in all columns to show potential for direct contamination in program implementation or through girls moving schools after program assignment\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eA baseline survey was conducted between January to April 2017, prior to the start of the intervention. Face-to-face interviews were carried out by a trained research assistant in Swahili and data was entered directly onto a tablet. Interviews were held in a private location to assure confidentiality, most commonly in the girls\u0026rsquo; homestead or school (after school hours). School attendance tracking was carried out in two phases. First, an initial enrollment exercise took place in June 2017 where all students who were present in school were registered. Second, this registration list was updated at the start of each data collection term. Daily attendance was taken by community-based data collectors for a period of four weeks (20 consecutive school days) per term, starting in September 2017 through July 2018, for a total of 60 days of observation across three school terms. Girls who were registered during the enrollment period were entered as absent if they were absent on that particular day, or dropped out of school/transferred to another school during the observation period. Attendance data was entered as missing for girls who were not registered during the enrollment exercise. The intervention was completed in October 2018 and endline data was collected in November and December 2018 using the same technique as the baseline survey. All girls from the baseline sample were eligible for interview, regardless of schooling status. Figure\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e shows the sample flow by arm and Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e shows the study timeline.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n\u003ch2\u003eRandomization and Masking\u003c/h2\u003e\n\u003cp\u003eThe unit of randomization was the school. At the completion of baseline data collection in each sub-county, prior to the start of the intervention, public lotteries were held and schools within that sub-county were randomly assigned to one of the four study arms. Interviewers and respondents were blinded to study arm at baseline but not at endline.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n\u003ch2\u003eOutcomes\u003c/h2\u003e\n\u003cp\u003eOutcomes of interest related to education are: (i) school attendance, which was measured as the number of days a girl was attending school out of a total of 60 days. School attendance was measured only for girls who remained in the same school from baseline to the end of the survey; and, (ii) school engagement measured with a 0\u0026ndash;8 score constructed as the number of responses reflecting higher school engagement to eight agree/disagree survey items (e.g., \u0026ldquo;You are attentive in class\u0026rdquo;).\u003c/p\u003e\n\u003cp\u003eMenstruation management outcomes were binary measures including reporting having enough sanitary pads to comfortably manage menstruation and having leaked blood at school during menstruation. Outcomes of interest related to the RH education intervention include: (i) RH attitudes among girls who had started menstruating with a 0\u0026ndash;12 score constructed as the number of responses reflecting a positive attitude to twelve agree/disagree survey items which captured girls\u0026rsquo; feelings of shame, pride and comfort vis-\u0026agrave;-vis menstruation (e.g., \u0026ldquo;I feel ashamed of my body when I have my period\u0026rdquo;); (ii) a pregnancy knowledge score with range 0\u0026ndash;4 constructed as the number of correct answers to four pregnancy related items; (iii) whether a girl could spontaneously name a modern method of contraception; (iv) STI knowledge score with range 0\u0026ndash;4 constructed as the number of correct answers to four STI related items; and (v) a HIV knowledge score with range 0\u0026ndash;11 constructed as the number of correct answers to eleven HIV related items; (vi) gender norms in marriage with a 0\u0026ndash;5 score constructed as the number of responses reflecting an equitable gender norm to five agree/disagree survey items (e.g., \u0026ldquo;If a husband and wife disagree on using family planning, the husband\u0026rsquo;s opinion should come first\u0026rdquo;); (vii) equitable adolescent gender norms with a 0\u0026ndash;12 score constructed as the number of responses reflecting an equitable adolescent gender norm to twelve agree/disagree survey items (e.g., \u0026ldquo;Girls should be as independent as boys\u0026rdquo;); (viii) gendered sexual norms with a 0\u0026ndash;5 score constructed as the number of responses reflecting an equitable sexual norm to five agree/disagree survey items (e.g., \u0026ldquo;Girls should cover up or they will attract unwanted sexual attention\u0026rdquo;); (ix) acceptability of intimate partner violence (IPV) was measured with an indicator on whether a girl finds IPV acceptable in any of five situations; and (x) general self-efficacy with a 0\u0026ndash;10 score constructed as the number of responses reflecting self-efficacy to ten agree/disagree survey items (e.g., \u0026ldquo;You always manage to solve difficult problems if you try hard enough\u0026rdquo;). See Additional Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e for the list of survey items included in each outcome.\u003c/p\u003e\n\u003cp\u003eThe following covariates were measured at baseline to assess balance across study arms: girls\u0026rsquo; age, cognitive score with range 0\u0026ndash;16 measured from a subset of Raven\u0026rsquo;s Coloured Progressive Matrices, math test score with a range 0\u0026ndash;37 derived from a test including progressively harder problems, literacy score with a range 0\u0026ndash;4 derived from reading sentences, using excerpts from the Uwezo Kenya National Learning Assessment [\u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e], household wealth quintile, parental living status, and sub-county.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n\u003ch2\u003eSample Size and Analytical Sample\u003c/h2\u003e\n\u003cp\u003eBased on findings of levels of detected differences in school attendance from previous studies conducted in Kenya and Ghana [\u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e25\u003c/span\u003e], sample size calculations were conducted using Stata 14.1 to detect a minimum difference between study arms of 1.18 mean days of school missed over a 4-week period and a 10 percentage points increase in RH attitudes, assuming power of 0.80, significance level of 0.05, intra-cluster correlation (ICC) of 0.173 and a standard deviation (SD) of 3.57. A sample size of 35 clusters per arm and 20 girls per cluster at endline (25 girls per cluster at baseline, assuming a loss of 20% by endline) was needed. Therefore, 25 girls per school were included in the research sample. There was no oversampling to account for girls who had not started menstruating at baseline.\u003c/p\u003e\n\u003cp\u003eThe analytical sample for this paper focuses on the sample of girls who had started menstruating at baseline and were re-interviewed at endline. Estimates including both menstruating and non-menstruating girls at baseline are presented in Additional Tables\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e\u0026ndash;6.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\n\u003cp\u003eTo assess baseline balance across study arms among girls interviewed at endline, means and 95% confidence intervals (CIs) were estimated for the set of covariates described above as well as for outcome variables measured at baseline. An analysis was also conducted to assess bias due to potential differential attrition by study arms.\u003c/p\u003e\n\u003cp\u003eAn intent-to-treat (ITT) approach was used to estimate the effect of each intervention arm relative to the control group. For outcomes measured both at baseline and endline, difference-in-differences (DID) models with girl-level fixed-effects were estimated to compare the change between baseline and endline for each intervention arm relative to the control group [\u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e]. Formally, the following linear regression model was estimated for each outcome:\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eY\u003c/em\u003e \u003csub\u003e \u003cem\u003eijt\u003c/em\u003e \u003c/sub\u003e\u0026thinsp;=\u0026thinsp;\u0026alpha;\u003csub\u003e0\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;\u0026alpha;\u003csub\u003e1\u003c/sub\u003e\u003cem\u003eS\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003csub\u003e\u003cem\u003eij\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;\u0026alpha;\u003csub\u003e2\u003c/sub\u003e\u003cem\u003eS\u003c/em\u003e\u003csup\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sup\u003e\u003csub\u003e\u003cem\u003eij\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;\u0026alpha;\u003csub\u003e3\u003c/sub\u003e\u003cem\u003eS\u003c/em\u003e\u003csup\u003e\u003cem\u003e4\u003c/em\u003e\u003c/sup\u003e\u003csub\u003e\u003cem\u003eij\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;\u0026alpha;\u003csub\u003e4\u003c/sub\u003e\u003cem\u003et\u003c/em\u003e\u0026thinsp;+\u0026thinsp;\u0026alpha;\u003csub\u003e5\u003c/sub\u003e\u003cem\u003eS\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003csub\u003e\u003cem\u003eij\u003c/em\u003e\u003c/sub\u003e \u003cem\u003et\u003c/em\u003e\u0026thinsp;+\u0026thinsp;\u0026alpha;\u003csub\u003e6\u003c/sub\u003e\u003cem\u003eS\u003c/em\u003e\u003csup\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sup\u003e\u003csub\u003e\u003cem\u003eij\u003c/em\u003e\u003c/sub\u003e \u003cem\u003et\u003c/em\u003e\u0026thinsp;+\u0026thinsp;\u0026alpha;\u003csub\u003e7\u003c/sub\u003e\u003cem\u003eS\u003c/em\u003e\u003csup\u003e\u003cem\u003e4\u003c/em\u003e\u003c/sup\u003e\u003csub\u003e\u003cem\u003eij\u003c/em\u003e\u003c/sub\u003e \u003cem\u003et\u003c/em\u003e\u0026thinsp;+\u0026thinsp;a\u003csub\u003e\u003cem\u003eij\u003c/em\u003e\u003c/sub\u003e + e\u003csub\u003e\u003cem\u003eijt\u003c/em\u003e\u003c/sub\u003e\u003c/p\u003e\n\u003cp\u003ewhere \u003cem\u003eY\u003c/em\u003e\u003csub\u003e\u003cem\u003eijt\u003c/em\u003e\u003c/sub\u003e is the outcome of interest for girl \u003cem\u003ei\u003c/em\u003e in school \u003cem\u003ej\u003c/em\u003e at time \u003cem\u003et\u003c/em\u003e (t\u0026thinsp;=\u0026thinsp;0 is baseline), \u003cem\u003eS\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e is a dichotomous variable for a girl enrolled in a school assigned to Arm 2, \u003cem\u003eS\u003c/em\u003e\u003csup\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sup\u003e is a dichotomous variable for a girl enrolled in a school assigned to Arm 3, \u003cem\u003eS\u003c/em\u003e\u003csup\u003e\u003cem\u003e4\u003c/em\u003e\u003c/sup\u003e is a dichotomous variable for a girl enrolled in a school assigned to Arm 4, a is a time-invariant individual effect and e is a random error. The coefficients related to the interactions between arms and time, \u0026alpha;\u003csub\u003e5,\u003c/sub\u003e \u0026alpha;\u003csub\u003e6\u003c/sub\u003e and \u0026alpha;\u003csub\u003e7\u003c/sub\u003e, provide the DID estimates for each treatment arm relative to the control.\u003c/p\u003e\n\u003cp\u003eFor outcomes with no comparable baseline data available, ANCOVA models were used to compare endline outcomes for each intervention arm relative to the control group while controlling for the following covariates measured at baseline: girls\u0026rsquo; age, cognitive score, math and literacy scores, household wealth quintile, parental living status, and sub-county. Formally, the following linear regression model was estimated for each outcome:\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eY\u003c/em\u003e \u003csub\u003e \u003cem\u003eijt\u003c/em\u003e \u003c/sub\u003e\u0026thinsp;=\u0026thinsp;\u0026beta;\u003csub\u003e0\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;\u0026beta;\u003csub\u003e1\u003c/sub\u003e\u003cem\u003eS\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003csub\u003e\u003cem\u003eij\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;\u0026beta;\u003csub\u003e2\u003c/sub\u003e\u003cem\u003eS\u003c/em\u003e\u003csup\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sup\u003e\u003csub\u003e\u003cem\u003eij\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;\u0026beta;\u003csub\u003e3\u003c/sub\u003e\u003cem\u003eS\u003c/em\u003e\u003csup\u003e\u003cem\u003e4\u003c/em\u003e\u003c/sup\u003e\u003csub\u003e\u003cem\u003eij\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;\u0026beta;\u003csub\u003e4\u003c/sub\u003e\u003cem\u003eX\u003c/em\u003e\u003csub\u003e\u003cem\u003eij0\u003c/em\u003e\u003c/sub\u003e + e\u003csub\u003e\u003cem\u003eijt\u003c/em\u003e\u003c/sub\u003e\u003c/p\u003e\n\u003cp\u003ewhere \u003cem\u003eX\u003c/em\u003e is a vector of the control variables measured at baseline. The coefficients related to the treatment arms, \u0026beta;\u003csub\u003e1,\u003c/sub\u003e \u0026beta;\u003csub\u003e2\u003c/sub\u003e and \u0026beta;\u003csub\u003e3\u003c/sub\u003e, provide the estimates of the treatment effects for each treatment arm relative to the control.\u003c/p\u003e\n\u003cp\u003eAll regressions were estimated with robust standard errors accounting for clustering at the school level. Statistical analysis was conducted using Stata 14.1.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eOf the 3,489 girls interviewed at baseline, 2,725 (79%) had started menstruating. Of these, 2,544 (93%) were successfully interviewed at endline. There was no differential attrition across arms. The majority of girls lost to follow up could not be physically located and therefore were not interviewed.\u003c/p\u003e\n\u003cp\u003eGirls in the analytical sample had a mean baseline age of 14.8 (SD:1.2). Girls\u0026rsquo; skills were measured by their cognitive, math and literacy ability, and on average achieved scores of 55% (8.8/16 (SD:3.1)), 79% (29.4/37 (SD:4.0)) and 95% (mean 3.8/4 (SD:0.7)), respectively. At baseline, the majority of girls (82%) reported that both parents were alive (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). Girls had moderately positive menstruation attitudes (mean score across arm: 7.6/12 (63.3%)). Girls were familiar with HIV (mean score across arms: 8.1/11 (74%)) and displayed lower levels of knowledge regarding when pregnancy is most likely to occur (mean score across arms: 1.9/4 (48%)), measures on norms and attitudes showed that equitable gender norms in marriage (mean score across arms: 3.2/5), equitable adolescent gender norms (mean score across arms 5.6/12), and gendered sexual norms (mean score across arms: 1.8/4). Girls general self-efficacy mean score across arms was 5.3/10, and the mean score across arms of how they perceived their engagement in school was 6.5 out of 8 (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab2\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eBaseline Characteristics Among Girls Menstruating at Baseline and Interviewed at Endline\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eArm 1\u003c/p\u003e\n\u003cp\u003eControl\u003c/p\u003e\n\u003cp\u003e(n (%))\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eArm 2\u003c/p\u003e\n\u003cp\u003ePads Only\u003c/p\u003e\n\u003cp\u003e(n (%))\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eArm 3\u003c/p\u003e\n\u003cp\u003eRH Only\u003c/p\u003e\n\u003cp\u003e(n (%))\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eArm 4\u003c/p\u003e\n\u003cp\u003ePads \u0026amp; RH\u003c/p\u003e\n\u003cp\u003e(n (%))\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eTotal\u003c/p\u003e\n\u003cp\u003en (%)\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSample of girls menstruating at baseline\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e669\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e682\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e677\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e697\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2,725\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSample of girls menstruating at baseline interviewed at endline N(%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e627 (93.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e632 (92.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e629 (92.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e656 (94.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2,544 (93.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAge (mean, SD)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e14.8 (1.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e14.7 (1.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e14.8 (1.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e14.8 (1.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e14.8 (1.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eSkills\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCognitive (max score\u0026thinsp;=\u0026thinsp;16) (mean (SD))\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8.7 (3.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8.8 (3.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8.8 (3.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8.8 (3.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8.8 (3.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMath (max score\u0026thinsp;=\u0026thinsp;37) (mean (SD))\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e29.4 (3.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e29.2 (3.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e29.3 (4.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e29.7 (4.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e29.4 (4.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLiteracy (max score\u0026thinsp;=\u0026thinsp;4) (mean (SD))\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.9 (0.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.8 (0.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.7 (0.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.8 (0.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.8 (0.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eSES quintiles\u003c/strong\u003e n(% in each quintile)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003equintile 1 (most poor)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e138 (22.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e156 (24.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e128 (20.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e132 (20.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e554 (21.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003equintile 2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e141 (22.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e131 (20.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e135 (21.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e137 (20.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e544 (21.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003equintile 3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e131 (20.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e144 (22.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e130 (20.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e116 (17.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e521 (20.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003equintile 4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e106 (16.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e107 (16.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e112 (17.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e139 (21.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e464 (18.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003equintile 5 (least poor)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e111 (17.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e94 (14.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e124 (19.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e132 (20.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e461 (18.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eParents living status\u003c/strong\u003e n(%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eKnows both parents alive\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e512 (81.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e512 (81.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e521 (82.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e531 (81.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2,076 (81.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eKnows mother only alive\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e97 (15.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e89 (14.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e80 (12.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e91 (13.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e357 (14.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eKnows father only alive\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e14 (2.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e19 (3.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e15 (2.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e17 (2.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e65 (2.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eKnows no parent alive\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4 (0.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e12 (1.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e13 (2.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e17 (2.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e46 (1.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eSubcounty\u003c/strong\u003e n(% in each subcounty)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eGanze\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e204 (32.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e212 (33.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e220 (35.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e211 (32.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e847 (33.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMagarini\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e211 (33.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e223 (35.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e222 (35.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e232 (35.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e888 (34.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eKaloleni\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e212 (33.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e197 (31.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e187 (29.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e213 (32.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e809 (31.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable id=\"Tab3\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eBaseline and Post Intervention Outcomes from Survey among Girls Menstruating at Baseline and Interviewed at Endline\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eArm 1\u003c/p\u003e\n\u003cp\u003eControl\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eArm 2\u003c/p\u003e\n\u003cp\u003ePads Only\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eArm 3\u003c/p\u003e\n\u003cp\u003eRH Only\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eArm 4\u003c/p\u003e\n\u003cp\u003ePads \u0026amp; RH\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eSchool Engagement\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSchool engagement\u003csup\u003e\u0026alpha;\u003c/sup\u003e (score 0\u0026ndash;8):\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBaseline (N\u0026thinsp;=\u0026thinsp;2,544) (mean(SD)n)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6.5 (1.4) n\u0026thinsp;=\u0026thinsp;627\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6.6 (1.4) n\u0026thinsp;=\u0026thinsp;632\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6.5 (1.4) n\u0026thinsp;=\u0026thinsp;629\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6.5 (1.3) n\u0026thinsp;=\u0026thinsp;656\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eEndline (N\u0026thinsp;=\u0026thinsp;2,432) (mean(SD)n)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6.8 (1.4) n\u0026thinsp;=\u0026thinsp;593\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6.8 (1.3) n\u0026thinsp;=\u0026thinsp;606\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6.8 (1.3) n\u0026thinsp;=\u0026thinsp;600\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6.9 (1.3) n\u0026thinsp;=\u0026thinsp;633\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eIntra-cluster correlation coefficient\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" align=\"left\"\u003e\n\u003cp\u003e0.0214\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCoefficient (95% CI)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eReference\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.05 (-0.33, 0.22)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.14 (-0.14, 0.42)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.16 (-0.14, 0.47)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eP-value\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.703\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.329\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.294\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eMenstruation Management\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHas enough pads (=\u0026thinsp;1):\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBaseline (N\u0026thinsp;=\u0026thinsp;2,544) (n(%)N)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e136 (21.7), N\u0026thinsp;=\u0026thinsp;627\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e126 (19.9), N\u0026thinsp;=\u0026thinsp;632\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e119 (18.9), N\u0026thinsp;=\u0026thinsp;629\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e155 (23.6), N\u0026thinsp;=\u0026thinsp;656\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eEndline (N\u0026thinsp;=\u0026thinsp;2,541) (n(%)N)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e350 (55.9), N\u0026thinsp;=\u0026thinsp;626\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e521 (82.4), N\u0026thinsp;=\u0026thinsp;632\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e371 (59.1), N\u0026thinsp;=\u0026thinsp;628\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e543 (82.9), N\u0026thinsp;=\u0026thinsp;655\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eIntra-cluster correlation coefficient\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" align=\"left\"\u003e\n\u003cp\u003e0.102\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCoefficient (95% CI)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eReference\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.28 (0.20, 0.36)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.06 (-0.03, 0.14)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.25 (0.17, 0.33)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eP-value\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.175\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eReporting leaking (=\u0026thinsp;1):\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBaseline (N\u0026thinsp;=\u0026thinsp;2,544) (n(%)N)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e213 (34.0), N\u0026thinsp;=\u0026thinsp;627\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e240 (38.0), N\u0026thinsp;=\u0026thinsp;632\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e235 (37.4), N\u0026thinsp;=\u0026thinsp;629\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e263 (40.1), N\u0026thinsp;=\u0026thinsp;656\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eEndline (N\u0026thinsp;=\u0026thinsp;2,432) (n(%)N)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e161 (27.2), N\u0026thinsp;=\u0026thinsp;593\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e125 (20.6), N\u0026thinsp;=\u0026thinsp;606\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e143 (23.8), N\u0026thinsp;=\u0026thinsp;600\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e138 (21.8), N\u0026thinsp;=\u0026thinsp;633\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eIntra-cluster correlation coefficient\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" align=\"left\"\u003e\n\u003cp\u003e0.0139\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCoefficient (95% CI)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eReference\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.10 (-0.18, -0.03)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.06 (-0.13, 0.01)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.11 (-0.20, -0.02)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eP-value\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.005\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.118\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.014\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eReproductive health attitudes\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMenstruation attitudes\u003csup\u003e#\u003c/sup\u003e (score:0\u0026ndash;12):\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBaseline (N\u0026thinsp;=\u0026thinsp;2,544) (mean(SD)n)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7.7 (1.7) n\u0026thinsp;=\u0026thinsp;627\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7.6 (1.8) n\u0026thinsp;=\u0026thinsp;632\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7.5 (1.8) n\u0026thinsp;=\u0026thinsp;629\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7.6 (1.7) n\u0026thinsp;=\u0026thinsp;656\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eEndline (N\u0026thinsp;=\u0026thinsp;2,432) (mean(SD)n)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8.1 (1.6) n\u0026thinsp;=\u0026thinsp;593\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8.2 (1.6) n\u0026thinsp;=\u0026thinsp;606\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8.6 (1.6) n\u0026thinsp;=\u0026thinsp;600\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8.9 (1.6) n\u0026thinsp;=\u0026thinsp;633\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eIntra-cluster correlation coefficient\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" align=\"left\"\u003e\n\u003cp\u003e0.0714\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCoefficient (95% CI)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eReference\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.16 (-0.10, 0.41)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.63 (0.40, 0.86)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.85 (0.64, 1.07)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eP-value\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.230\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eReproductive health knowledge\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePregnancy knowledge (score:0\u0026ndash;4):\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBaseline (N\u0026thinsp;=\u0026thinsp;2,544) (mean(SD)n)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.9 (0.9) n\u0026thinsp;=\u0026thinsp;627\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.0 (0.8) n\u0026thinsp;=\u0026thinsp;632\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.9 (0.9) n\u0026thinsp;=\u0026thinsp;629\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.8 (0.9) n\u0026thinsp;=\u0026thinsp;656\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eEndline (N\u0026thinsp;=\u0026thinsp;2,544) (mean(SD)n)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.2 (0.9) n\u0026thinsp;=\u0026thinsp;627\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.1 (0.9) n\u0026thinsp;=\u0026thinsp;632\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.2 (0.9) n\u0026thinsp;=\u0026thinsp;629\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.3 (0.9) n\u0026thinsp;=\u0026thinsp;656\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eIntra-cluster correlation coefficient\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" align=\"left\"\u003e\n\u003cp\u003e0.0412\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCoefficient (95% CI)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eReference\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.15 (-0.31, 0.01)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.01 (-0.16, 0.17)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.18 (0.02, 0.34)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eP-value\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.067\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.949\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.028\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCan spontaneously name a method of modern contraception (=\u0026thinsp;1):\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBaseline (N\u0026thinsp;=\u0026thinsp;2,544) (n(%)N)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e321 (51.2), n\u0026thinsp;=\u0026thinsp;321\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e357 (56.5), n\u0026thinsp;=\u0026thinsp;357\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e326 (51.8), n\u0026thinsp;=\u0026thinsp;326\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e349 (53.2), n\u0026thinsp;=\u0026thinsp;349\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eEndline (N\u0026thinsp;=\u0026thinsp;2,544) (n(%)N)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e404 (64.4), n\u0026thinsp;=\u0026thinsp;404\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e425 (67.2), n\u0026thinsp;=\u0026thinsp;425\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e463 (73.6), n\u0026thinsp;=\u0026thinsp;463\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e465 (70.9), n\u0026thinsp;=\u0026thinsp;465\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eIntra-cluster correlation coefficient\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" align=\"left\"\u003e\n\u003cp\u003e0.0150\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCoefficient (95% CI)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eReference\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.03 (-0.11, 0.06)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.09 (0.01, 0.17)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.04 (-0.03, 0.12)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eP-value\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.524\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.036\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.275\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSTI knowledge score (score:0\u0026ndash;4):\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBaseline (N\u0026thinsp;=\u0026thinsp;2,544) (mean(SD)n)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.4 (0.9) n\u0026thinsp;=\u0026thinsp;627\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.5 (0.9) n\u0026thinsp;=\u0026thinsp;632\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.4 (0.9) n\u0026thinsp;=\u0026thinsp;629\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.4 (1.0) n\u0026thinsp;=\u0026thinsp;656\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eEndline (N\u0026thinsp;=\u0026thinsp;2,544) (mean(SD)n)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.2 (1.2) n\u0026thinsp;=\u0026thinsp;627\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.2 (1.2) n\u0026thinsp;=\u0026thinsp;632\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.5 (1.2) n\u0026thinsp;=\u0026thinsp;629\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.5 (1.2) n\u0026thinsp;=\u0026thinsp;656\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eIntra-cluster correlation coefficient\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" align=\"left\"\u003e\n\u003cp\u003e0.0536\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCoefficient (95% CI)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eReference\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.01 (-0.19, 0.16)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.31 (0.12, 0.49)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.28 (0.10, 0.45)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eP-value\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.873\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.002\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.002\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHIV knowledge score (score:0\u0026ndash;11):\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBaseline (N\u0026thinsp;=\u0026thinsp;2,544) (mean(SD)n)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7.8 (1.8) n\u0026thinsp;=\u0026thinsp;627\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8.0 (1.8) n\u0026thinsp;=\u0026thinsp;632\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8.0 (1.8) n\u0026thinsp;=\u0026thinsp;629\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8.0 (1.7) n\u0026thinsp;=\u0026thinsp;656\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eEndline (N\u0026thinsp;=\u0026thinsp;2,544) (mean(SD)n)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8.4 (1.7) n\u0026thinsp;=\u0026thinsp;627\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8.3 (1.8) n\u0026thinsp;=\u0026thinsp;632\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8.5 (1.7) n\u0026thinsp;=\u0026thinsp;629\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8.4 (1.6) n\u0026thinsp;=\u0026thinsp;656\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eIntra-cluster correlation coefficient\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" align=\"left\"\u003e\n\u003cp\u003e0.0215\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCoefficient (95% CI)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eReference\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.30 (-0.61, 0.01)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.05 (-0.34. 0.24)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.18 (-0.43, 0 .08)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eP-value\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.058\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.728\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.170\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eGender norms\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eGender norms in marriage (score:0\u0026ndash;5):\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBaseline (N\u0026thinsp;=\u0026thinsp;2,544) (mean(SD)n)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.3 (1.1) n\u0026thinsp;=\u0026thinsp;627\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.3 (1.2) n\u0026thinsp;=\u0026thinsp;632\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.2 (1.2) n\u0026thinsp;=\u0026thinsp;629\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.2 (1.1) n\u0026thinsp;=\u0026thinsp;656\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eEndline (N\u0026thinsp;=\u0026thinsp;2,544) (mean(SD)n)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.0 (1.2) n\u0026thinsp;=\u0026thinsp;627\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.0 (1.2) n\u0026thinsp;=\u0026thinsp;632\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.9 (1.2) n\u0026thinsp;=\u0026thinsp;629\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.0 (1.2) n\u0026thinsp;=\u0026thinsp;656\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eIntra-cluster correlation coefficient\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" align=\"left\"\u003e\n\u003cp\u003e0.0283\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCoefficient (95% CI)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eReference\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.01 (-0.20, 0.22)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.08 (-0.13, 0.29)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.10 (-0.12, 0.31)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eP-value\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.921\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.455\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.374\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eEquitable adolescent gender norms (score:0\u0026ndash;12):\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBaseline (N\u0026thinsp;=\u0026thinsp;2,544) (mean(SD)n)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.7 (1.9) n\u0026thinsp;=\u0026thinsp;627\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.5 (2.0) n\u0026thinsp;=\u0026thinsp;632\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.6 (1.9) n\u0026thinsp;=\u0026thinsp;629\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.5 (2.0) n\u0026thinsp;=\u0026thinsp;656\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eEndline (N\u0026thinsp;=\u0026thinsp;2,544) (mean(SD)n)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6.2 (1.8) n\u0026thinsp;=\u0026thinsp;627\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6.1 (1.8) n\u0026thinsp;=\u0026thinsp;632\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6.6 (1.9) n\u0026thinsp;=\u0026thinsp;629\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6.6 (1.8) n\u0026thinsp;=\u0026thinsp;656\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eIntra-cluster correlation coefficient\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" align=\"left\"\u003e\n\u003cp\u003e0.0507\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCoefficient (95% CI)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eReference\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.08 (-0.25, 0.40)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.45 (0.15, 0.74)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.57 (0.30, 0.85)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eP-value\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.640\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.003\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eGendered sexual norms (score:0\u0026ndash;5):\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBaseline (N\u0026thinsp;=\u0026thinsp;2,544) (mean(SD)n)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.8 (1.2) n\u0026thinsp;=\u0026thinsp;627\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.8 (1.1) n\u0026thinsp;=\u0026thinsp;632\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.7 (1.2) n\u0026thinsp;=\u0026thinsp;629\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.8 (1.2) n\u0026thinsp;=\u0026thinsp;656\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eEndline (N\u0026thinsp;=\u0026thinsp;2,544) (mean(SD)n)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.9 (1.2) n\u0026thinsp;=\u0026thinsp;627\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.9 (1.2) n\u0026thinsp;=\u0026thinsp;632\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.2 (1.3) n\u0026thinsp;=\u0026thinsp;629\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.2 (1.3) n\u0026thinsp;=\u0026thinsp;656\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eIntra-cluster correlation coefficient\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" align=\"left\"\u003e\n\u003cp\u003e0.0640\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCoefficient (95% CI)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eReference\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.02 (-0.18, 0.21)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.46 (0.26, 0.65)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.36 (0.15, 0.57)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eP-value\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.878\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAgrees with IPV (=\u0026thinsp;1):\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBaseline (N\u0026thinsp;=\u0026thinsp;2,544) (n(%)N)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e458 (73.0), n\u0026thinsp;=\u0026thinsp;458\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e458 (72.5), n\u0026thinsp;=\u0026thinsp;458\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e456 (72.5), n\u0026thinsp;=\u0026thinsp;456\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e465 (70.9), n\u0026thinsp;=\u0026thinsp;465\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eEndline (N\u0026thinsp;=\u0026thinsp;2,544) (n(%)N)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e454 (72.4), n\u0026thinsp;=\u0026thinsp;454\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e461 (72.9), n\u0026thinsp;=\u0026thinsp;461\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e477 (75.8), n\u0026thinsp;=\u0026thinsp;477\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e470 (71.6), n\u0026thinsp;=\u0026thinsp;470\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eIntra-cluster correlation coefficient\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" align=\"left\"\u003e\n\u003cp\u003e0.0344\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCoefficient (95% CI)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eReference\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.01 (-0.06, 0.09)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.04 (-0.04, 0.12)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.01 (-0.05, 0.08)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eP-value\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.772\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.323\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.687\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eSelf-efficacy\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eGeneral self-efficacy (score:0\u0026ndash;10):\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBaseline (N\u0026thinsp;=\u0026thinsp;2,544) (mean(SD)n)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.1 (2.6) n\u0026thinsp;=\u0026thinsp;627\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.2 (2.5) n\u0026thinsp;=\u0026thinsp;632\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.2 (2.6) n\u0026thinsp;=\u0026thinsp;629\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.5 (2.6) n\u0026thinsp;=\u0026thinsp;656\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eEndline (N\u0026thinsp;=\u0026thinsp;2,544) (mean(SD)n)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.7 (2.4) n\u0026thinsp;=\u0026thinsp;627\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.6 (2.5) n\u0026thinsp;=\u0026thinsp;632\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6.6 (2.3) n\u0026thinsp;=\u0026thinsp;629\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6.3 (2.5) n\u0026thinsp;=\u0026thinsp;656\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eIntra-cluster correlation coefficient\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" align=\"left\"\u003e\n\u003cp\u003e0.0444\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCoefficient (95% CI)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eReference\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.16 (-0.54, 0.23)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.80 (0.37, 1.24)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.22 (-0.20, 0.64)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eP-value\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.420\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.301\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"5\"\u003eNotes: The table reports post-intervention means for the control arm, and the estimated effect of the intent-to-treat for each study arm relative to the control arm. Difference-in-differences were estimated from regressions with girl-level fixed effects and robust standard errors accounting for clustering at the school level.\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"5\"\u003eHigher scores equate to higher knowledge and more positive/equitable norms and attitudes.\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"5\"\u003e\u003csup\u003e+\u003c/sup\u003eDifferences at endline were estimated using ANCOVA. Regressions controlled for the following covariates measured at baseline: cognitive, math and literacy test scores, socio-economic quintile, age, parental living status, subcounty, and were estimated with robust standard errors accounting for clustering at the school level.\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"5\"\u003e\u003csup\u003e\u0026alpha;\u003c/sup\u003eSchool engagement was only measured among respondents who were in school; at baseline all menstruating girls were in school, at endline 2,432 girls were still in school.\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eTable\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e shows results from the school attendance tracking instrument. Attendance was observed for the full 60 days for 2,265 (89%) of girls in the analytical sample (no statistically significant difference by arm). On average, girls attended 56 days out of the 60 (SD: 7.6), and there was no difference between arms.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab4\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eSchool Attendance Outcomes from School Attendance Tracking Instrument among Girls Menstruating at Baseline and Interviewed at Endline\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eArm 1\u003c/p\u003e\n\u003cp\u003eControl\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eArm 2\u003c/p\u003e\n\u003cp\u003ePads Only\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eArm 3\u003c/p\u003e\n\u003cp\u003eRH Only\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eArm 4\u003c/p\u003e\n\u003cp\u003ePads \u0026amp; RH\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRespondents in analytical sample (N)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e627\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e632\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e629\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e656\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eAttendance was taken for all 60 days\u003c/strong\u003e (% (N))\u003csup\u003e\u0026pound;\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e84.7 (531)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e87.3 (552)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e86.5 (544)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e85.7 (562)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eIntra-cluster correlation coefficient\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" align=\"left\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCoefficient (95% CI)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eReference\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.022 (-0.047, 0.092)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.015(-0.049, 0.079)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.007 (-0.069, 0.083)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eP-value\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.524\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.431\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.862\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eMean # of days attended\u003c/strong\u003e (mean (SD)) \u003csup\u003e\u0026pound;\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e55.6 (6.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e56.0 (6.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e55.8 (6.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e56.2 (6.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eIntra-cluster correlation coefficient\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" align=\"left\"\u003e\n\u003cp\u003e0.059\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCoefficient (95% CI)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eReference\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.37 (-0.73, 1.46)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.14 (-0.99, 1.26)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.58 (-0.37, 1.52)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eP-value\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.507\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.812\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.230\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eObserved attendance\u003c/strong\u003e\u003csup\u003e+\u003c/sup\u003e (% (N)):\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e91.4 (619)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e91.8 (625)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e91.6 (622)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e92.2 (647)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eIntra-cluster correlation coefficient\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" align=\"left\"\u003e\n\u003cp\u003e0.056\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCoefficient (95% CI)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eReference\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.42 (-1.94, 2.78)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.28 (-2.00, 2.57)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.75 (-0.97, 2.48)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eP-value\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.725\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.806\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.389\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"5\"\u003eNotes: The table reports post-intervention means for the control arm, and the estimated effect of the intent-to-treat for each study arm relative to the control arm. Difference-in-differences were estimated from regressions with girl-level fixed effects and robust standard errors accounting for clustering at the school level.\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eHigher scores equate to higher knowledge and more positive/equitable norms and attitudes.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e\u0026pound;\u003c/sup\u003eAttendance data only includes those who remained in the same school throughout the 60 days.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e+\u003c/sup\u003eDifferences at endline were estimated using ANCOVA. Regressions controlled for the following covariates measured at baseline: cognitive, math and literacy test scores, socio-economic quintile, age, parental living status, subcounty, and were estimated with robust standard errors accounting for clustering at the school level.\u003c/p\u003e\n\u003cp\u003eTable\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e shows results from outcomes measured in the girl survey instrument. A positive increase was observed in girls reporting having enough pads in the pads only (DID coeff: 0.28 (95%CI:0.20, 0.36)) and combined arms (DID coeff: 0.25 (95%CI:0.17, 0.33)), compared to the control. However, because girls in the control and RH only arms also had a significant increase in reporting having enough pads relative to baseline (36.5 and 43.3 percentage point increase for the control and RH only arms respectively), we carried out a post-hoc regression analysis to test if those increases explained the null attendance results. The post-hoc analysis showed no association between having enough pads and school attendance in girls who had started menstruating at baseline (coeff: 0.0004, 95% CI: -0.000585, 0.001; p value\u0026thinsp;=\u0026thinsp;0.457).\u003c/p\u003e\n\u003cp\u003eGirls also reported less leaking in both the pads only (DID coeff: -0.10 (95%CI:-0.18, -0.03)) and combined arms (DID coeff: -0.11 (95%CI:-0.20, -0.02)). A positive increase was observed in menstruation attitudes in both the RH only (DID coefficient (coeff):0.63 (95%CI:0.40,0.86)) and combined arms (DID coeff: 0.85 (95%CI:0.64,1.07)). A comparison of estimates between intervention arms (combined v. pads only for menstruation outcomes; combined v. RH only for RH and norms outcomes) showed a larger effect size on RH attitudes in the combined arm as compared to the RH only arm (see Additional Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eFor the indicators measuring RH knowledge, an increase was observed in pregnancy knowledge in the combined arm (difference-in-difference (DID) coefficient: 0.18 (95% CI:0.02, 0.34)). An increase was also observed in the percentage of girls who could spontaneously mention a modern method of contraception in the RH only arm (DID coefficient: 0.09 (95% CI: 0.01, 0.17)) and in STI knowledge in the RH only arm (DID coefficient: 0.31 (95%CI: 0.12, 0.49)) and combined arm (DID coefficient: 0.28 (95%CI: 0.10, 0.45)). For the indicators measuring norms and attitudes, positive increases were observed in gender norms measuring equitable adolescent gender norms in adolescents in both the RH only (DID coefficient:0.45 (95%CI:0.15,0.74)) and combined arms (DID coefficient: 0.57 (95%CI: 0.30, 0.85)), as well as in norms on gendered sexual norms similarly in both the RH only (DID coefficient: 0.46 (95%CI:0.26,0.65)) and combined arms (DID coefficient: 0.36 (95%CI:0.15, 0.57)). Finally, there was an increase observed in general self-efficacy in the RH only arm (DID coefficient:0.80 (95%CI:0.37, 1.24)).\u003c/p\u003e\n\u003cp\u003eA comparison between intervention arms showed a larger effect size on general self-efficacy in the RH only arm as compare to the combined arm (Additional Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). Supplementary tables show the impact of the intervention on the whole sample which includes menstruating and non-menstruating girls (Additional Tables\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e\u0026ndash;6). There were no significant differences as compared to the restricted analytical sample.\u003c/p\u003e"},{"header":"Discussion","content":" \u003cp\u003eIn this cluster randomized trial of evaluating sanitary pad distribution and RH education in Kenya we see that neither intervention component, alone or in combination, improved school attendance among girls in primary grade 7. This finding is consistent with several recent quantitative studies rigorously examining the relationship between sanitary pad distribution and/or RH education on attendance [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThere are a few hypotheses as to why the intervention did not translate into improved school attendance, mainly related to alternative reasons for why girls miss school. While it is likely, and supported in the qualitative literature, that girls experience physical and emotional discomfort during menstruation, it is possible that it is not a direct cause of absenteeism. Quantitative studies assessing reasons girls miss school mention poverty and lack of ability to pay school fees, low value placed on girls\u0026rsquo; education and instability in households as the most common causes of absenteeism [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], none of which are addressed via access to sanitary pads or RH education. Therefore, interventions addressing these causes might be better placed to have an effect on girls\u0026rsquo; school attendance. In addition, this paper supports the recent push to move away from a central focus on school attendance as the central outcome of MHM programs [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThis trial did show that the RH education improved girls\u0026rsquo; RH attitudes, in particular increasing the pride and comfort they feel vis-\u0026agrave;-vis menstruation, as well as RH knowledge, endorsement of equitable gender norms and general self-efficacy. This is also consistent with the literature on comprehensive sexuality education and its ability, when implemented well and addressing gender and power, to improve RH outcomes [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Furthermore, regardless of whether sanitary pads or RH education translate into improved attendance at school, it is recognized that girls have the right to manage their menstruation safely and with dignity [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e] and have the right to adequate sexual and reproductive health information [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThere are a few limitations of the study that affect the external validity of the findings. First, the study was implemented in one rural setting \u0026ndash; three sub-counties within one county. Therefore, while the findings could be relevant to other rural areas in the country and region, the findings cannot be generalized to urban areas. Second, the intervention was implemented with girls in primary grade 7 at the start of the study, which means that the findings cannot be generalized to girls earlier in primary school or in secondary school. Third, it is possible that the attendance taking activities heightened students\u0026rsquo; and schools\u0026rsquo; attention to attendance and inadvertently stimulated attendance. Fourth, the gender norms scales, although a significant effect was detected, had low internal consistency as indicated by the alphas, suggesting low scale reliability. Fifth, the study did not oversample for girls who had not yet started menstruating at baseline, resulting in a slightly smaller number of girls per cluster in the analytical sample than calculated for in the power estimates; however, given the number of clusters per arm, the loss of power is minimal. Finally, the government pad distribution program in schools or other market factors such as a general reduction in the price of pads over time, although evenly distributed across arms, may have increased the access to pads in Kilifi, beyond a threshold that would show differences between arms. However, the post-hoc analysis conducted indicates that there was no association between access to pads and school attendance, independent of random assignment to study arm.\u003c/p\u003e \u003cp\u003eThis study also has several strengths which allow it to make a significant contribution to the literature on the impact of MHM interventions on education and health outcomes. Key study design features \u0026ndash; random assignment, a large sample size, 18-month follow up period and strong fidelity to the design during implementation \u0026ndash; address key limitations of previous research, which include small sample sizes, inability to determine causation, non-random assignment to study arms, and shorter follow-up periods. This increases the relevance of the results as it contradicts previous, less rigorous studies assessing the same outcomes [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e "},{"header":"Conclusions","content":" \u003cp\u003eThe results of this study suggest that in this specific context, neither sanitary pad distribution nor RH education, on their own or together, are sufficient to improve girls\u0026rsquo; school attendance or engagement in class and therefore would caution again positioning MHM activities as girls education interventions. These activities would be better framed as part of comprehensive sexuality education programs aiming to address girls\u0026rsquo; stigma and shame associated with menstruation, access to menstrual management products, inequitable gender norms and lack of knowledge key RH issues.\u003c/p\u003e "},{"header":"List Of Abbreviations","content":"\u003cp\u003eCI \u0026ndash; Confidence Interval\u003c/p\u003e\n\u003cp\u003eDID \u0026ndash; Difference in Differences\u003c/p\u003e\n\u003cp\u003eICC \u0026ndash; Intra-Cluster Correlation\u003c/p\u003e\n\u003cp\u003eIPV \u0026ndash; Intimate Partner Violence\u003c/p\u003e\n\u003cp\u003eIRB \u0026ndash; Institutional Review Board\u003c/p\u003e\n\u003cp\u003eITT \u0026ndash; Intent-to-Treat\u003c/p\u003e\n\u003cp\u003eMHM \u0026ndash; Menstrual Health Management\u003c/p\u003e\n\u003cp\u003eRCT \u0026ndash; Randomized Controlled Trial\u003c/p\u003e\n\u003cp\u003eRH \u0026ndash; Reproductive Health\u003c/p\u003e\n\u003cp\u003eSD \u0026ndash; Standard Deviation\u003c/p\u003e\n\u003cp\u003eSTI \u0026ndash; Sexually Transmitted Infection\u003c/p\u003e\n\u003cp\u003eWASH \u0026ndash; Water, Sanitation and Hygiene\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by the Population Council Institutional Review Board (IRB) (p768) and the AMREF Ethics and Scientific Review Committee (p292-2016). Written informed consent was obtained from respondents ages 18 and above. Written informed consent was obtained from a parent or guardian and then oral assent obtained for girls under age 18.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStudy data in this paper, including de-identified individual data and data dictionary, will be made available open access upon publication. The data will be stored and available for downloading via the Adolescent Data Hub - http://popcouncil.org/girlcenter/adolescentdatahub/\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interest\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was funded by a grant from the Bill \u0026amp; Melinda Gates Foundation (OPP1140962) via a sub-contract from ZanaAfrica. Representatives of the funder reviewed and approved the study design, but had no role in data collection, or analysis and interpretation reported here.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEM and KA designed and conceptualized the study. BK and ESH conducted the data analysis. KA, BK and ESH drafted the manuscript. All authors reviewed and commented on the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank ZanaAfrica for providing leadership for the project implementation, including coordinating stakeholders and developing the intervention materials \u0026ndash; Nia Teen sanitary pads, Nia Teen Magazine and the Nia Yetu curriculum. We also thank colleagues Barbara Mensch and Stephanie Psaki for reviewing and commenting on earlier drafts of the paper. We acknowledge the efforts of the members of the Nia Project Research Advisory Committee (RAC) \u0026ndash; Caroline Kabiru, Cynthia Lloyd and Matthew Freeman throughout the study and in particular for providing feedback on the draft of the manuscript. Finally, we thank all of the adolescent girls who took the time to participate in the study. An earlier version of this paper was presented at the 8\u003csup\u003eth\u003c/sup\u003e Africa Population Conference in Entebbe, Uganda held from November 18-22, 2019.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSommer M: \u003cstrong\u003eAn overlooked priority: puberty in sub-Saharan Africa\u003c/strong\u003e. \u003cem\u003eAmerican journal of public health \u003c/em\u003e2011, \u003cstrong\u003e101\u003c/strong\u003e(6):979-981.\u003c/li\u003e\n\u003cli\u003eMason L, Nyothach E, Alexander K, Odhiambo FO, Eleveld A, Vulule J, Rheingans R, Laserson KF, Mohammed A, Phillips-Howard PA: \u003cstrong\u003e\u0026lsquo;We Keep It Secret So No One Should Know\u0026rsquo;\u0026ndash;A Qualitative Study to Explore Young Schoolgirls Attitudes and Experiences with Menstruation in Rural Western Kenya\u003c/strong\u003e. \u003cem\u003ePloS one \u003c/em\u003e2013, \u003cstrong\u003e8\u003c/strong\u003e(11):e79132.\u003c/li\u003e\n\u003cli\u003eTegegne TK, Sisay MM: \u003cstrong\u003eMenstrual hygiene management and school absenteeism among female adolescent students in Northeast Ethiopia\u003c/strong\u003e. \u003cem\u003eBMC public health \u003c/em\u003e2014, \u003cstrong\u003e14\u003c/strong\u003e(1):1.\u003c/li\u003e\n\u003cli\u003eSommer M: \u003cstrong\u003eWhere the education system and women's bodies collide: The social and health impact of girls' experiences of menstruation and schooling in Tanzania\u003c/strong\u003e. \u003cem\u003eJournal of adolescence \u003c/em\u003e2010, \u003cstrong\u003e33\u003c/strong\u003e(4):521-529.\u003c/li\u003e\n\u003cli\u003eLahme AM, Stern R, Cooper D: \u003cstrong\u003eFactors impacting on menstrual hygiene and their implications for health promotion\u003c/strong\u003e. \u003cem\u003eGlobal health promotion \u003c/em\u003e2018, \u003cstrong\u003e25\u003c/strong\u003e(1):54-62.\u003c/li\u003e\n\u003cli\u003eMcMahon SA, Winch PJ, Caruso BA, Obure AF, Ogutu EA, Ochari IA, Rheingans RD: \u003cstrong\u003e'The girl with her period is the one to hang her head'Reflections on menstrual management among schoolgirls in rural Kenya\u003c/strong\u003e. \u003cem\u003eBMC international health and human rights \u003c/em\u003e2011, \u003cstrong\u003e11\u003c/strong\u003e(1):7.\u003c/li\u003e\n\u003cli\u003eCrichton J, Ibisomi L, Gyimah SO: \u003cstrong\u003eMother\u0026ndash;daughter communication about sexual maturation, abstinence and unintended pregnancy: Experiences from an informal settlement in Nairobi, Kenya\u003c/strong\u003e. \u003cem\u003eJournal of Adolescence \u003c/em\u003e2012, \u003cstrong\u003e35\u003c/strong\u003e(1):21-30.\u003c/li\u003e\n\u003cli\u003eMiiro G, Rutakumwa R, Nakiyingi-Miiro J, Nakuya K, Musoke S, Namakula J, Francis S, Torondel B, Gibson LJ, Ross DA: \u003cstrong\u003eMenstrual health and school absenteeism among adolescent girls in Uganda (MENISCUS): a feasibility study\u003c/strong\u003e. \u003cem\u003eBMC women's health \u003c/em\u003e2018, \u003cstrong\u003e18\u003c/strong\u003e(1):4.\u003c/li\u003e\n\u003cli\u003eDolan CS, Ryus CR, Dopson S, Montgomery P, Scott L: \u003cstrong\u003eA Blind Spot in Girls' Education: Menarche and its Webs of Exclusion in Ghana\u003c/strong\u003e. \u003cem\u003eJournal of International Development \u003c/em\u003e2014, \u003cstrong\u003e26\u003c/strong\u003e(5):643-657.\u003c/li\u003e\n\u003cli\u003eSumpter C, Torondel B: \u003cstrong\u003eA systematic review of the health and social effects of menstrual hygiene management\u003c/strong\u003e. \u003cem\u003ePloS one \u003c/em\u003e2013, \u003cstrong\u003e8\u003c/strong\u003e(4):e62004.\u003c/li\u003e\n\u003cli\u003eHennegan J, Montgomery P: \u003cstrong\u003eDo Menstrual Hygiene Management Interventions Improve Education and Psychosocial Outcomes for Women and Girls in Low and Middle Income Countries? A Systematic Review\u003c/strong\u003e. \u003cem\u003ePloS one \u003c/em\u003e2016, \u003cstrong\u003e11\u003c/strong\u003e(2):e0146985.\u003c/li\u003e\n\u003cli\u003ePhillips-Howard PA, Nyothach E, ter Kuile FO, Omoto J, Wang D, Zeh C, Onyango C, Mason L, Alexander KT, Odhiambo FO: \u003cstrong\u003eMenstrual cups and sanitary pads to reduce school attrition, and sexually transmitted and reproductive tract infections: a cluster randomised controlled feasibility study in rural western Kenya\u003c/strong\u003e. \u003cem\u003eBMJ open \u003c/em\u003e2016, \u003cstrong\u003e6\u003c/strong\u003e(11):e013229.\u003c/li\u003e\n\u003cli\u003eBenshaul-Tolonen A, Zulaika G, Nyothach E, Oduor C, Mason L, Obor D, Alexander KT, Laserson KF, Phillips-Howard PA: \u003cstrong\u003ePupil Absenteeism, Measurement, and Menstruation: Evidence from Western Kenya\u003c/strong\u003e. 2019.\u003c/li\u003e\n\u003cli\u003eMontgomery P, Hennegan J, Dolan C, Wu M, Steinfield L, Scott L: \u003cstrong\u003eMenstruation and the Cycle of Poverty: A Cluster Quasi-Randomised Control Trial of Sanitary Pad and Puberty Education Provision in Uganda\u003c/strong\u003e. \u003cem\u003ePLOS ONE \u003c/em\u003e2016, \u003cstrong\u003e11\u003c/strong\u003e(12):e0166122.\u003c/li\u003e\n\u003cli\u003eKhanna M: \u003cstrong\u003eThe Precocious Period: The Impact of Early Menarche on Schooling in India\u003c/strong\u003e. \u003cem\u003eAvailable at SSRN 3419041 \u003c/em\u003e2019.\u003c/li\u003e\n\u003cli\u003eGrant M, Lloyd C, Mensch B: \u003cstrong\u003eMenstruation and school absenteeism: evidence from rural Malawi\u003c/strong\u003e. \u003cem\u003eComparative education review \u003c/em\u003e2013, \u003cstrong\u003e57\u003c/strong\u003e(2):260-284.\u003c/li\u003e\n\u003cli\u003eSommer M, Sutherland C, Chandra-Mouli V: \u003cstrong\u003ePutting menarche and girls into the global population health agenda\u003c/strong\u003e. \u003cem\u003eReproductive health \u003c/em\u003e2015, \u003cstrong\u003e12\u003c/strong\u003e(1):24.\u003c/li\u003e\n\u003cli\u003eEducation Mo: \u003cstrong\u003eRepublic of Kenya: A Policy Framework: Aligning Education and Training to the Constitution of Kenya 2010 and Kenya Vision 2030 and Beyond\u003c/strong\u003e. In\u003cem\u003e.\u003c/em\u003e: Ministry of Education Nairobi; 2012.\u003c/li\u003e\n\u003cli\u003eKenya National Bureau of Statistics, ICF International: \u003cstrong\u003eKenya Demographic and Health Survey 2014\u003c/strong\u003e. In\u003cem\u003e.\u003c/em\u003e Calverton, Maryland: KNBS and ICF International; 2015.\u003c/li\u003e\n\u003cli\u003eTechnology MoESa: \u003cstrong\u003eA Policy Framework for Reforming Education and Training for Sustainable Development in Kenya\u003c/strong\u003e. In\u003cem\u003e.\u003c/em\u003e Kenya: Government of Kenya; 2019.\u003c/li\u003e\n\u003cli\u003eGirod C, Ellis A, Andes KL, Freeman MC, Caruso BA: \u003cstrong\u003ePhysical, Social, and Political Inequities Constraining Girls\u0026rsquo; Menstrual Management at Schools in Informal Settlements of Nairobi, Kenya\u003c/strong\u003e. \u003cem\u003eJournal of Urban Health \u003c/em\u003e2017, \u003cstrong\u003e94\u003c/strong\u003e(6):835-846.\u003c/li\u003e\n\u003cli\u003eMuthengi E, Austrian K: \u003cstrong\u003eCluster randomized evaluation of the Nia Project: study protocol\u003c/strong\u003e. \u003cem\u003eReproductive health \u003c/em\u003e2018, \u003cstrong\u003e15\u003c/strong\u003e(1):218.\u003c/li\u003e\n\u003cli\u003eKenya U: \u003cstrong\u003eAre our children learning? Annual learning assessment report\u003c/strong\u003e. In\u003cem\u003e.\u003c/em\u003e: Uwezo Publications; 2014.\u003c/li\u003e\n\u003cli\u003eMontgomery P, Ryus CR, Dolan CS, Dopson S, Scott LM: \u003cstrong\u003eSanitary pad interventions for girls' education in Ghana: a pilot study\u003c/strong\u003e. \u003cem\u003ePloS one \u003c/em\u003e2012, \u003cstrong\u003e7\u003c/strong\u003e(10):e48274.\u003c/li\u003e\n\u003cli\u003eWilson E, Reeve J, Pitt A, Sully B, Julious S: \u003cstrong\u003eINSPIRES: Investigating a reusable sanitary pad intervention in a rural educational setting-evaluating the acceptability and short term effect of teaching Kenyan school girls to make reusable sanitary towels on absenteeism and other daily activities: a partial preference parallel group, cluster randomised control trial\u003c/strong\u003e. 2012.\u003c/li\u003e\n\u003cli\u003eKhandker S, B. Koolwal G, Samad H: \u003cstrong\u003eHandbook on impact evaluation: quantitative methods and practices\u003c/strong\u003e: The World Bank; 2009.\u003c/li\u003e\n\u003cli\u003ePrakash R, Beattie T, Javalkar P, Bhattacharjee P, Ramanaik S, Thalinja R, Murthy S, Davey C, Blanchard J, Watts C: \u003cstrong\u003eCorrelates of school dropout and absenteeism among adolescent girls from marginalized community in north Karnataka, south India\u003c/strong\u003e. \u003cem\u003eJournal of adolescence \u003c/em\u003e2017, \u003cstrong\u003e61\u003c/strong\u003e:64-76.\u003c/li\u003e\n\u003cli\u003eRoby JL, Erickson L, Nagaishi C: \u003cstrong\u003eEducation for children in sub-Saharan Africa: Predictors impacting school attendance\u003c/strong\u003e. \u003cem\u003eChildren and Youth Services Review \u003c/em\u003e2016, \u003cstrong\u003e64\u003c/strong\u003e:110-116.\u003c/li\u003e\n\u003cli\u003eBenshaul-Tolonen A, Zulaika G, Sommer M, Phillips-Howard PA: \u003cstrong\u003eMeasuring Menstruation-Related Absenteeism Among Adolescents in Low-Income Countries\u003c/strong\u003e. In: \u003cem\u003eThe Palgrave Handbook of Critical Menstruation Studies.\u003c/em\u003e edn. Edited by Bobel C, Winkler IT, Fahs B, Hasson KA, Kissling EA, Roberts T-A. Singapore: Springer Singapore; 2020: 705-723.\u003c/li\u003e\n\u003cli\u003eHaberland NA: \u003cstrong\u003eThe case for addressing gender and power in sexuality and HIV education: A comprehensive review of evaluation studies\u003c/strong\u003e. \u003cem\u003eInternational Perspectives on Sexual and Reproductive Health \u003c/em\u003e2015, \u003cstrong\u003e41\u003c/strong\u003e(1):31-42.\u003c/li\u003e\n\u003cli\u003eSommer M, Hirsch JS, Nathanson C, Parker RG: \u003cstrong\u003eComfortably, safely, and without shame: defining menstrual hygiene management as a public health issue\u003c/strong\u003e. \u003cem\u003eAmerican Journal of Public Health \u003c/em\u003e2015, \u003cstrong\u003e105\u003c/strong\u003e(7):1302-1311.\u003c/li\u003e\n\u003cli\u003eChandra-Mouli V, Svanemyr J, Amin A, Fogstad H, Say L, Girard F, Temmerman M: \u003cstrong\u003eTwenty years after International Conference on Population and Development: where are we with adolescent sexual and reproductive health and rights?\u003c/strong\u003e \u003cem\u003eJournal of Adolescent Health \u003c/em\u003e2015, \u003cstrong\u003e56\u003c/strong\u003e(1):S1-S6.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"reproductive-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"reph","sideBox":"Learn more about [Reproductive Health](http://reproductive-health-journal.biomedcentral.com)","snPcode":"12978","submissionUrl":"https://submission.nature.com/new-submission/12978/3","title":"Reproductive Health","twitterHandle":"@Reprod_Health","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"adolescent girls, randomized controlled trial, Kenya, menstrual health, sexual and reproductive health","lastPublishedDoi":"10.21203/rs.3.rs-105989/v2","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-105989/v2","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cem\u003eBackground:\u003c/em\u003e Adolescent girls’ risk of school dropout and reproductive health (RH) challenges may be exacerbated by girls’ attitudes toward their bodies and inability to manage their menstruation. We assessed effects of sanitary pad distribution and RH education on girls in primary grade 7 in Kilifi, Kenya in 2017-18.\u003c/p\u003e\u003cp\u003e\u003cem\u003eMethods: \u003c/em\u003eA cluster randomized controlled trial design was used. Eligible clusters were all non-boarding schools in three sub-counties in Kilifi County that had a minimum of 25 girls enrolled in primary grade 7. 140 primary schools, 35 per arm, were randomly assigned to one of four study arms: 1) control (standard government provision of pads and health education); 2) sanitary pad distribution; 3) RH education; or 4) both sanitary pad distribution and RH education. Outcomes were school attendance, school engagement, RH knowledge and attitudes, gender norms, and self-efficacy. For outcomes measured both at baseline and endline, difference-in-differences (DID) models were estimated and for outcomes without baseline data available, analysis of covariance models were used. \u003c/p\u003e\u003cp\u003e\u003cem\u003eResults: \u003c/em\u003eThe study enrolled 3,489 randomly selected girls in primary grade 7. Girls in arms 2 and 4 received on average 17.5 out of 20 packets of sanitary pads and girls in arms 3 and 4 participated on average in 21 out of 25 RH sessions. Ninety-four percent of the baseline sample was interviewed at the end of the intervention with no differential attrition by arm. There was no evidence of an effect on primary school attendance on arm 2 (coefficient [coef] 0.37, 95% CI -0.73, 1.46), arm 3 (coef 0.14, 95% CI -0.99, 1.26) or arm 4 (coef 0.58, 95% CI -.37, 1.52). There was increased positive RH attitudes for girls in arm 3 (DID coef. 0.63, 95% CI 0.40, 0.86) and arm 4 (DID coef. 0.85, 95% CI 0.64, -1.07). There was also an increase in RH knowledge, gender norms and self-efficacy in arms 3 and 4.\u003c/p\u003e\u003cp\u003e\u003cem\u003eConclusions:\u0026nbsp;\u003c/em\u003eThe findings suggest that neither sanitary pad distribution nor RH education, on their own or together, were sufficient to improve primary school attendance. However, as the RH education intervention improved RH outcomes, the evidence suggests that sanitary pad distribution and RH education can be positioned in broader RH programming for girls.\u003cem\u003e \u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eTrial Registration: \u003c/em\u003eISRCTN, ISRCTN10894523. Registered 22 August 2017 - Retrospectively registered, \u003ca href=\"http://www.isrctn.com/ISRCTN10894523\" rel=\"noopener noreferrer\" target=\"_blank\"\u003ehttp://www.isrctn.com/ISRCTN10894523\u003c/a\u003e\u003c/p\u003e","manuscriptTitle":"Effects of sanitary pad distribution and reproductive health education on primary school attendance and reproductive health knowledge and attitudes in Kenya: a cluster randomized controlled trial","msid":"","msnumber":"","nonDraftVersions":[{"code":2,"date":"2021-05-07 19:04:24","doi":"10.21203/rs.3.rs-105989/v2","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Minor revision","date":"2021-06-03T00:00:00+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2021-05-24T00:00:00+00:00","index":3,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2021-05-16T00:00:00+00:00","index":2,"fulltext":"Recommendation: Minor Revision\nForm responses:\n---\n\nComments to Author:\n---\nThank you for reporting your research, which I can see has been constructed and conducted with care.\n\nIt is in my view just as important to report serious research which does not find significant causal connections, as it is to tell others in the field about work which captures connection.\n\nA couple of thoughts, if I may?\n\nVery small point: in my part of the world 'primary' school ends at age 10-11. Might you be able to indicate the actual age of the children you have investigated, in the title? This would be helpful.\n\nAnother very small question: Do we need to look again at the sense of the last line of 'Randomization and Masking', p.12?\n\nSome suggestions: In the Abstract you refer to 'standard government provision of pads and health education', but nowhere is the practical application of this standard provision really explained, which makes for some difficulty in comparing it with the other 'arms' of your experimental approach. Is the '20 packets of sanitary protection' delivered by the schools? How and over what duration (I see you offer a couple of lines of explanation on p8 of the text...)? Do all Kenyan pupils, urban and rural, receive this provision in the same way; who is in charge? (These questions may not precisely focus the specifics of the situation, but I hope they point to some of the practicals which might be clarified?) And how does 'standard' health education vary from the bespoke provision in the programme? Is there more to be learned about how you see the 'menstrual health challenges' which routinely face these girls?\n\nI ask these questions because I think there are additional considerations we can bring to the 'software' aspects of your investigation. On p13 you list a lot of axes for investigation; I hope in a future paper you will explore these further. This is a very important part of the field you are investigating. Perhaps I've missed it, but my own research in a very different context suggests also that the age at first child of both parents is a significant influencer on the behaviour of their offspring...?\n\nI think too that more about what satisfactory attitudes to menstruation might be would be helpful. I fully understand that these matters are very private but does this in any way relate to the attitudes of boys and men (peers, brothers, fathers...)? Do boys / male family members need educating on these issues more specifically, too? Would that help re retaining older girls in school? Will there be any longitudinal follow up of the girls?\n\nYour concluding discussion of other factors which may influence school attendance / menstruation attitudes is valuable. Perhaps either now, or in a future paper, this discussion in the context of RH / sex education might be taken further? (It seems quite possible, as you say, that urban attitudes will be different from rural ones.)\n\nBut the important thing, which you may like to highlight a bit more, is that you have articulated a proposition frequently encountered - 'menstruation deters school attendance' - and found, in the context of significant research in a particular context, that this is not necessarily the case. It's vital that not only 'we found a big correlation' papers are published.\n\nThe next step is, as you say, to consider further the conjunctions of growing physical maturity and the socio-economic contexts in which girls at this impressionable and critical age find themselves. Thank you.\n\n\n\n\n\n* Publons Reviewer Recognition. Springer Nature can send verification of this review directly to Publons (a subsidiary of Clarivate Analytics). If you would like to take advantage of this service, please click on the “Yes” option below. Your name, email address, title of the reviewed manuscript, name of the journal, and date of your review submission (the “Review Data”) will then be transmitted to Publons after the final decision on the manuscript has been made. If you have already registered at Publons, they will notify you of the receipt of this review and update your profile as per your settings and their policy. If you are not registered with Publons, you will receive an email from them asking you to register in order for them to be able to recognize your review on your new profile page. Publons may use the Review Data to generate derivative metadata for the benefit of Publons and you as a reviewer, carefully considering the sensitivity of such information. For example, Publons may verify your record as a reviewer by updating your profile published on its webservice if you have registered for such service or help editors to identify candidate reviewers. Please find the details of processing in Publons’ privacy policy https://publons.com/about/terms: **Yes**\n* Level of interest: **An article whose findings are important to those with closely related research interests**\n* Quality of written English: **Acceptable**\n* Declaration of competing interests: **I declare I have no competing interests**\n* I agree to the open peer review policy of the journal. I understand that my name will be included on my report to the authors and, if the manuscript is accepted for publication, my named report including any attachments I upload will be posted on the website along with the authors' responses. I agree for my report to be made available under an Open Access Creative Commons CC-BY license (http://creativecommons.org/licenses/by/4.0/). I understand that any comments which I do not wish to be included in my named report can be included as confidential comments to the editors, which will not be published.: **\nI agree to the open peer review policy of the journal**\n"},{"type":"editorInvitedReview","content":"","date":"2021-05-11T01:10:00+00:00","index":0,"fulltext":""},{"type":"reviewerAgreed","content":"","date":"2021-05-11T01:00:00+00:00","index":2,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2021-05-11T00:30:00+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2021-05-11T00:00:00+00:00","index":1,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2021-05-11T00:00:00+00:00","index":1,"fulltext":"Recommendation: Accept\nForm responses:\n---\n\nComments to Author:\n---\nI recommend this article for publication without further revisions. The study design seems sound, and the finding are clearly presented and their implications appropriately discussed. Most of my initial concerns were brought up in the previous reviews and addressed in the revised document that I reviewed. While I am not entirely convinced that the null results were not due to contamination across study arms or the study being underpowered, I strongly agree with the authors' contention that MHM support should be thought of in a reproductive rights framework rather than as primarily a means to improve education outcomes. It would be interesting to follow these girls longer term to see if changes in attitudes and knowledge found influence behavior change in the longer term.* Publons Reviewer Recognition. Springer Nature can send verification of this review directly to Publons (a subsidiary of Clarivate Analytics). If you would like to take advantage of this service, please click on the “Yes” option below. Your name, email address, title of the reviewed manuscript, name of the journal, and date of your review submission (the “Review Data”) will then be transmitted to Publons after the final decision on the manuscript has been made. If you have already registered at Publons, they will notify you of the receipt of this review and update your profile as per your settings and their policy. If you are not registered with Publons, you will receive an email from them asking you to register in order for them to be able to recognize your review on your new profile page. Publons may use the Review Data to generate derivative metadata for the benefit of Publons and you as a reviewer, carefully considering the sensitivity of such information. For example, Publons may verify your record as a reviewer by updating your profile published on its webservice if you have registered for such service or help editors to identify candidate reviewers. Please find the details of processing in Publons’ privacy policy https://publons.com/about/terms: **No**\n* Level of interest: **An article of importance in its field**\n* Quality of written English: **Acceptable**\n* Declaration of competing interests: **I declare that I have no competing interests**\n* I agree to the open peer review policy of the journal. I understand that my name will be included on my report to the authors and, if the manuscript is accepted for publication, my named report including any attachments I upload will be posted on the website along with the authors' responses. I agree for my report to be made available under an Open Access Creative Commons CC-BY license (http://creativecommons.org/licenses/by/4.0/). I understand that any comments which I do not wish to be included in my named report can be included as confidential comments to the editors, which will not be published.: **\nI agree to the open peer review policy of the journal**\n"},{"type":"editorAssigned","content":"","date":"2021-04-22T00:00:00+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2021-04-21T23:00:00+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2021-04-21T23:00:00+00:00","index":"","fulltext":""},{"type":"submitted","content":"Reproductive Health","date":"2021-04-20T07:13:02+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"reproductive-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"reph","sideBox":"Learn more about [Reproductive Health](http://reproductive-health-journal.biomedcentral.com)","snPcode":"12978","submissionUrl":"https://submission.nature.com/new-submission/12978/3","title":"Reproductive Health","twitterHandle":"@Reprod_Health","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}},{"code":1,"date":"2020-11-18 14:38:50","doi":"10.21203/rs.3.rs-105989/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Reject after peer review","date":"2021-02-03T00:00:00+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2021-01-31T00:00:00+00:00","index":2,"fulltext":"Recommendation: Reject\nForm responses:\n---\n\nComments to Author:\n---\nWhile interesting, this article needs extensive editing. For example, inclusion and exclusion criteria for schools selected and girls selected are not included in the Methods section. In addition, the authors do not provide justification for the number of girls chosen to include in the study.* Publons Reviewer Recognition. Springer Nature can send verification of this review directly to Publons (a subsidiary of Clarivate Analytics). If you would like to take advantage of this service, please click on the “Yes” option below. Your name, email address, title of the reviewed manuscript, name of the journal, and date of your review submission (the “Review Data”) will then be transmitted to Publons upon publication of the manuscript. If you have already registered at Publons, they will notify you of the receipt of this review and update your profile as per your settings and their policy. If you are not registered with Publons, you will receive an email from them asking you to register in order for them to be able to recognize your review on your new profile page. Publons may use the Review Data to generate derivative metadata for the benefit of Publons and you as a reviewer, carefully considering the sensitivity of such information. For example, Publons may verify your record as a reviewer by updating your profile published on its webservice if you have registered for such service or help editors to identify candidate reviewers. Please find the details of processing in Publons’ privacy policy https://publons.com/about/terms: **No**\n* Level of interest: **An article whose findings are important to those with closely related research interests**\n* Quality of written English: **Not suitable for publication unless extensively edited**\n* Declaration of competing interests: **I declare that I have no competing interests**\n* I agree to the open peer review policy of the journal. I understand that my name will be included on my report to the authors and, if the manuscript is accepted for publication, my named report including any attachments I upload will be posted on the website along with the authors' responses. I agree for my report to be made available under an Open Access Creative Commons CC-BY license (http://creativecommons.org/licenses/by/4.0/). I understand that any comments which I do not wish to be included in my named report can be included as confidential comments to the editors, which will not be published.: **\nI agree to the open peer review policy of the journal**\n"},{"type":"reviewerAgreed","content":"","date":"2021-01-12T00:00:00+00:00","index":2,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2020-12-22T00:00:00+00:00","index":1,"fulltext":"Recommendation: Major Revision\nForm responses:\n---\n\nComments to Author:\n---\nThis is an important, four-arm, school-based, cluster randomized controlled trial, which tested the effectiveness of providing seventh grade schoolgirls with sanitary pad and reproductive health (RH) education over 18 months in Kilifi county, Kenya. Each of these interventions, alone and together, were compared with a non-placebo control group. The primary outcomes were to reduce the number of missing school days and improve RH knowledge and attitudes of girls. Drawing on the lessons learned from previous trials and studies, the authors took several steps to ensure finding of the true effects of these interventions. This study, therefore, might be a valuable addition to the literature, informing the future research, policies, and programs. To that end, I'm afraid that the manuscript needs to be far more informative and transparent.\n\nAlthough the authors have met many of the reporting requirements of the 'Consort 2010 statement: extension to cluster randomised trials,' I'll strongly suggest them to more closely follow this statement, especially the criteria that pertain to the 'extension to cluster' (Campbell et al. 2012). For example, in the abstract, the eligibility criteria for clusters, number of participants, and number of clusters analyzed in each arm/group are currently missing (see Table 2 and Figure 1 of Campbell et al. 2012 for details).\n\nSimilarly, Figure 1 on the sample flow by study phases did not include any information on the analytical sample that were included in the analysis (See Figure 2 of Campbell et al. 2012). This sample comprising of the menstruating girls is critical because the authors made their claims (and rightly so) on the effectiveness of their interventions based on this sample. However, comparing this analytical sample with the required sample size might show that the study was somewhat under-power. This problem was exacerbated by the fact that the Kenyan government improved the distribution of pads to both control and RH arms, which appears to be significantly higher than the baseline levels (See Table A5). At endline, the girls in Control and RH arms reported an almost 40% increase of having enough pads. Therefore, the authors attempt to show that no contamination of intervention activities occurred across arms in Table 1 is misleading.\n\nAs a result, the authors have missed analyzing the implications of these important aspects on their findings which might have implications for some girls not having materials that they desperately need. I'll suggest authors to address the above concerns. They might run a post-hoc analysis to examine if having enough pads, as reported by girls, had any effect on the outcome of reducing the no. of missing school days.\n\nI'll also suggest reporting the intra-cluster correlation coefficients (ICC) for each outcome across arms to understand their implications on the sample size. See an example in Table 4 in Campbell et al. 2012. \n\nFurther about the data analysis, I appreciate that Table 2 includes sub-county level baseline characteristics of the girls, but the \"cluster-level statistics\" are missing. As girls are nested in schools, cluster level data for each arm will be more informative.\n\nAlso, include the formula for the Difference-in-Differences models tested in this study either in the body of the text or in a supplementary file to enhance the reproducibility of research. Cite the statistical literature in sample size and data analysis sections. In addition, please clarify how the study derived at a minimum difference between study arms of \"1.18 mean days of school.\"\n\nLastly, please give references to the measures/scaled tested in this study. It will be informative to know if the low levels of alpha contributed to some of the findings.\n\nOf note, please check if the Global Early Adolescent Study (GEAS) used the term \"heteronormativity.\" According to Wikipedia, \"Heteronormativity is the belief that heterosexuality, predicated on the gender binary, is the default, preferred, or normal mode of sexual orientation.\" Looking at the items, it appears that the authors use of the term, equitable adolescent gender norm, is more appropriate than heteronormativity. By the way, alpha on attitude toward intimate partner violence seems to be missing.\n\nAbout the study design, I'll suggest including an extended version of Figure 1 that was published in the study protocol (Muthengi \u0026 Austrian, 2018). Adding the study phases and information on data collection to that figure will be informative for the readers.\n\n\nREFERENCES\n* Campbell Marion K, Piaggio Gilda, Elbourne Diana R, Altman Douglas G. Consort 2010 statement: extension to cluster randomised trials. BMJ. 2012; 345 :e5661.\n\n* Muthengi E, Austrian K. Cluster randomized evaluation of the Nia Project: study protocol. Reprod Health. 2018 Dec 29;15(1):218. doi: 10.1186/s12978-018-0586-4. PMID: 30594217; PMCID: PMC6310925.\n\n* Wikipedia. Heteronormativity. 2020. Retrieved from https://en.wikipedia.org/wiki/Heteronormativity#:~:text=Heteronormativity%20is%20the%20belief%20that,between%20people%20of%20opposite%20sex.\n* Publons Reviewer Recognition. Springer Nature can send verification of this review directly to Publons (a subsidiary of Clarivate Analytics). If you would like to take advantage of this service, please click on the “Yes” option below. Your name, email address, title of the reviewed manuscript, name of the journal, and date of your review submission (the “Review Data”) will then be transmitted to Publons upon publication of the manuscript. If you have already registered at Publons, they will notify you of the receipt of this review and update your profile as per your settings and their policy. If you are not registered with Publons, you will receive an email from them asking you to register in order for them to be able to recognize your review on your new profile page. Publons may use the Review Data to generate derivative metadata for the benefit of Publons and you as a reviewer, carefully considering the sensitivity of such information. For example, Publons may verify your record as a reviewer by updating your profile published on its webservice if you have registered for such service or help editors to identify candidate reviewers. Please find the details of processing in Publons’ privacy policy https://publons.com/about/terms: **Yes**\n* Level of interest: **An article of importance in its field**\n* Quality of written English: **Acceptable**\n* Declaration of competing interests: **I declare that I have no competing interests.**\n* I agree to the open peer review policy of the journal. I understand that my name will be included on my report to the authors and, if the manuscript is accepted for publication, my named report including any attachments I upload will be posted on the website along with the authors' responses. I agree for my report to be made available under an Open Access Creative Commons CC-BY license (http://creativecommons.org/licenses/by/4.0/). I understand that any comments which I do not wish to be included in my named report can be included as confidential comments to the editors, which will not be published.: **\nI agree to the open peer review policy of the journal**\n"},{"type":"reviewerAgreed","content":"","date":"2020-11-28T00:00:00+00:00","index":1,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2020-11-20T00:00:00+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2020-11-09T00:00:00+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2020-11-08T23:00:00+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2020-11-08T23:00:00+00:00","index":"","fulltext":""},{"type":"submitted","content":"","date":"2020-11-07T00:00:00+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"reproductive-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"reph","sideBox":"Learn more about [Reproductive Health](http://reproductive-health-journal.biomedcentral.com)","snPcode":"12978","submissionUrl":"https://submission.nature.com/new-submission/12978/3","title":"Reproductive Health","twitterHandle":"@Reprod_Health","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4b9ca517-818f-4f41-a4e8-2c822327027b","owner":[],"postedDate":"May 7th, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":4170196,"name":"Sexual \u0026 Reproductive Medicine"}],"tags":[],"updatedAt":"2021-09-10T17:53:33+00:00","versionOfRecord":{"articleIdentity":"rs-105989","link":"https://doi.org/10.1186/s12978-021-01223-7","journal":{"identity":"reproductive-health","isVorOnly":false,"title":"Reproductive Health"},"publishedOn":"2021-08-31 00:00:00","publishedOnDateReadable":"August 31st, 2021"},"versionCreatedAt":"2021-05-07 19:04:24","video":"","vorDoi":"10.1186/s12978-021-01223-7","vorDoiUrl":"https://doi.org/10.1186/s12978-021-01223-7","workflowStages":[]},"version":"v2","identity":"rs-105989","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-105989","identity":"rs-105989","version":["v2"]},"buildId":"GqpaHPwrfC8PjnIFayRh5","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}