Effects of school nurse led health education to re

Original Article Effects of school nurse‑led health education to reduce malnutrition among primary school children in Bangladesh: Cluster nonrandomized controlled trial Sadia A. Aivey1, Yasuko Fukushima1, Md Moshiur Rahman1, Niru S. Nahar2, Ashir Ahmed3, Junaidi B. Prihanto1,4, Mohammad D. H. Hawlader5, Michiko Moriyama1 1 Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan, 2Department of Nursing Science, Grameen Caledonian College of Nursing, Dhaka, Bangladesh, 3Faculty of Information Science and Electrical Engineering, Kyushu University, Fukuoka, Japan, 4Department of Physical Education, Universitas Negeri Surabaya (State University of Surabaya), Surabaya, East Java, Indonesia, 5Department of Public Health, North South University, Dhaka, Bangladesh A bstrAct Background: Malnutrition is a major health concern among children especially in low and middle‑income countries. However, there are limited studies on school health in Bangladesh. This study aimed to reduce malnutrition among primary school children in Bangladesh by increasing awareness and knowledge through school nurse‑led health education. Methods and Materials: A prospective, open‑label, parallel‑group (1:1), cluster nonrandomized controlled trial on primary school children conducted in rural Bangladesh. The study lasted 13 months between September 2021 and September 2022. Four schools were selected and assigned to the intervention and control groups (CGs). Next, school nurses provided evidence‑based health education to the children in the intervention group (IG) for 9 months to improve awareness and knowledge of malnutrition. Data were collected at baseline, midline, and endline. Results: Overall, 604 children were enrolled at the baseline; among them, 455 (CG, n = 220; IG, n = 235) completed the study. Changes in the malnutrition rate—the primary outcome—were not significant (P = 0.225). However, after adjusting the endline data with baseline and sociodemographic data, the children’s body mass index improved significantly in the IG than in the CG (P < 0.05). Changes in eating behavior, and awareness and knowledge of malnutrition—the secondary outcomes—significantly differed between the groups (P < 0.001). Conclusion: The school nurse‑led health education program significantly improved primary school children’s awareness and knowledge of malnutrition. This study revealed the effectiveness of school nurses in reducing malnutrition among children, which may decrease future morbidity and mortality rates in children. Keywords: Health education, health‑related behaviour, malnutrition, nutritional deficiency, primary school children, school nurse Introduction Address for correspondence: Dr. Sadia A. Aivey, Graduate School of Biomedical and Health Sciences, Hiroshima University, Kasumi 1‑2‑3 Minami‑Ku, Hiroshima 734‑8553, Japan. E‑mail: gccn.aivey@gmail.com Received: 19‑09‑2023 Accepted: 04‑12‑2023 Revised: 30‑11‑2023 Published: 04‑04‑2024 Access this article online Malnutrition is a major health concern with children being the most vulnerable population worldwide.[1] Malnutrition is a leading cause of death associated with several communicable and noncommunicable diseases namely pneumonia, anemia, This is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution‑NonCommercial‑ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non‑commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms. Quick Response Code: Website: http://journals.lww.com/JFMPC DOI: 10.4103/jfmpc.jfmpc_1560_23 For reprints contact: WKHLRPMedknow_reprints@wolterskluwer.com How to cite this article: Aivey SA, Fukushima Y, Rahman MM, Nahar NS, Ahmed A, Prihanto JB, et al. Effects of school nurse‑led health education to reduce malnutrition among primary school children in Bangladesh: Cluster nonrandomized controlled trial. J Family Med Prim Care 2024;13:1024‑36. © 2024 Journal of Family Medicine and Primary Care | Published by Wolters Kluwer - Medknow 1024 Aivey, et al.: School nurse trial on child malnutrition health education would significantly increase health awareness and knowledge among primary school children to prevent malnutrition. and infectious diseases.[1‑6] In higher‑income countries, although the undernutrition rate was lower compared with overnutrition, however, low‑ and middle‑income countries (LMICs) had higher prevalence for both under‑ and overnutrition.[7,8] Malnutrition affects children’s physical growth and mental development which may last for a lifetime.[9,10] Materials and Methods Study design and duration In Bangladesh, malnutrition rate is high among 5–12 years school‑going children[11] due to low case detection, limited health education, poor health assessment, and access to primary care providers.[12] Furthermore, malnutrition is firmly related to children’s eating behavior,[13] dietary literacy[14] and diversity,[15] awareness and knowledge regarding malnutrition, and their parents as well.[16,17] This was a prospective, open‑label, parallel‑group (1:1), cluster nonrandomized controlled trial with a pre‑and post‑test design. The study duration was 13 months, between September 2021 and September 2022. In Figure 2, the study was reported following the consolidated standards of reporting trials[38] and registered by the Clinical Trial Registry (NCT05012592). We considered changes in malnutrition as the main primary outcome and changes in children’s eating and drinking behavior and awareness and knowledge of malnutrition as the secondary outcomes. Results related to other secondary outcomes will be reported in future studies. Health education is a significant requirement for the children’s nutritional status improvement. [17‑22] In many developed countries, school nurses have a significant role in children’s health development through school health services,[23,24] and contribute to reducing communicable and noncommunicable diseases.[25‑29] Additionally, appropriate skilled and evidence‑based health education for children is the foremost intervention for sustainable positive changes in health behavior, awareness development, and knowledge acquisition.[30‑32] These prerequisite activities have not yet been addressed in Bangladesh schools, although a limited number of nongovernmental organizations address this issue through school health programs.[33] However, in Bangladesh, there is no health checkup system in schools for children which leads to undesirable effects on primary care providers. Therefore, this study aimed to reduce malnutrition by increasing awareness and knowledge through school nurse‑led health education among primary school children in Bangladesh. Study area, recruitment, and eligibility criteria This study was conducted in two rural unions of North Matlab, Chandpur District, Bangladesh. The study participants were children of both sexes who were studied in grades 1–5 from four primary schools. The CHWs visited the children’s houses and explained the study’s purpose to them including their parents. Next, CHWs checked the children’s eligibility criteria, enrolled them in the study with their consent. The inclusion criteria were as follows: those (children and their parents) who agreed to give consent and were willing to participate, receive health checkups and laboratory investigation, respond to the questionnaire, and stay in the same school and area until study completion. Children who did not meet the eligibility criteria were excluded. Additionally, we excluded children in grade 5 who completed primary school after baseline data collection and had to be transferred to another school or area. Study Framework According to this study framework [Figure 1], school nurses are the most vital determining factors and outcomes as predictors are the fundamental elements. We developed a Health Awareness Program for Primary School Children (HAPSC) and implemented an interventional study involving the pilot placement of trained school nurses in a school setting in Bangladesh to provide evidence‑based health education to primary school children and their parents. School nurses collaborated with schools,[34] children including their parents,[35] and community health workers (CHWs) as an assistant. [36] The school nurses focused on child engagement including their parents to boost the effectiveness of health education. These experimental connections create a community obligation aimed at positive changes in outcomes through HAPSC.[37] School nurses provided health assessments, checkups, and evidence‑based health education to the children as a study intervention. Notably, health assessments, checkups, and evidence‑based health education are interrelated concepts. Evaluation and feedback, such as sharing a children’s baseline health report with their parents, motivated them to be more concerned about their children’s health‑related factors. We hypothesized that school nurse placement and evidence‑based Journal of Family Medicine and Primary Care Allocation and study procedure Two schools from each union were purposively allocated into the intervention group (IG) and control group (CG).[39] After enrollment, survey and health assessment data, such as height, weight, and BMI, were collected at baseline (T0). Next, we prepared and trained school nurses to conduct health educational interventions. Afterward, similar data were collected in both groups at midline (T1, 5 months after T0) and endline (T2, 12 months from T0). Baseline health reports of children in both groups were provided to their parents as study feedback. The report was made in Bengali (the local language) and English, which included normal ranges and WHO‑recommended growth curves, and recommended re‑examination of children later based on irregular results. Training of school nurses and assistants We recruited three nursing faculty members (registered nurses) from a reputed nursing college in Dhaka, Bangladesh, who had studied school nursing. They trained 10 undergraduate nursing 1025 Volume 13 : Issue 3 : March 2024 Aivey, et al.: School nurse trial on child malnutrition Figure 1: Study framework Assess for eligibility (n = 757) Exclude (n = 153) • Not meeting the inclusion criteria (n = 65) • Refused to participate (n = 54) • Other reason (n = 34) Enrolment Allocate to intervention group (2 schools) (n = 314) grades 1-5 • Health assessment (Health checkups) • School-based health awareness intervention • Loss to follow-up after baseline data collection (Grade 5, n = 70) Allocation Allocate to control group (2 schools) (n = 290) grades 1-5 • Health assessment (Health checkups) • No intervention • Loss to follow-up after baseline data collection (Grade 5, n = 63) Intervention group (n = 244) 5th months intervention follow-up (n = 237) Lost to follow-up (n = 2) Decline intervention (n = 5) 12th months intervention follow-up (n = 235) Collect post intervention data • Lost to follow-up (n = 2) • Decline intervention (n = 0) Analyzed (n = 235) Control group (n = 227) Midline follow-up Endline follow-up 5th months intervention follow-up (n = 222) • Lost to follow-up (n = 3) • Decline to continue (n = 2) 12th months intervention follow-up (n = 220) Collect post intervention data • Lost to follow-up (n = 1) • Decline to continue (n = 1) Study period (September 2021 to September 2022) Non-randomized controlled trials (n = 604) Analysis Analyzed (n = 220) Figure 2: Study flow chart students to assist the school nurse. The sessions were conducted for 1 month (total 36 h) in three modes: face‑to‑face, online, and group discussions including practice. Additionally, the CHWs Journal of Family Medicine and Primary Care received brief sessions on this study, administration, and data collection, including health assessment methods and educational materials. 1026 Volume 13 : Issue 3 : March 2024 Aivey, et al.: School nurse trial on child malnutrition the responses were classified into two categories: 0= “do not know”” or “no,” and 1= “yes”. The range of scores was from 0 to 10 with higher scores indicating a greater level of awareness and knowledge, and Cronbach’s alpha was 0.861. Health education for intervention group Children of IG received health education at school through HAPSC for 9 months. Specifically, they received 45‑min educational sessions every week of the month, except when school was closed due to holidays or unavoidable circumstances (COVID‑19 outbreak). During schools’ holiday, school nurses provided health education through telephone calls. All sessions were organized with fun play‑based, and conducted face‑to‑face, asking questions, small group discussions, roleplay, group work, and hands‑on practices.[31] The content was prepared using the dietary guidelines for Bangladesh.[34,40] Additionally, we prepared a few health education materials for the children, such as booklet, my health record notebook, poster, food models/pictures, and short message leaflet (Multimedia Appendix‑1). The contents focused on the food pyramid; benefits of food; eating breakfast and the ideal composition of a meal with nutritive and functional values; and effects of unhealthy food.[32,34] To facilitate the understanding of grades 1–2 children, we used hand‑made posters with many pictures and food models. However, the educational content for children grades 1–5 was similar. Lastly, the CHWs provided health education to the children’s parents twice during the first month and once a month throughout the intervention period. Study sample size The sample size was deter mined using the G Power software (Version 3.1.9.4) with an effect size of 0.70 for school‑based intervention[44] and a confidence level of 0.95.[45] The expected minimal sample size was 110, 55 for the IG and 55 for the CG. Nevertheless, we invited all the schools’ children to participate and enrolled all who expressed interest by providing consent. At T0, 604 children participated and completed all the surveys and health checkups. Quality control The study activities were monitored and the well‑trained staff were recruited. Additionally, to avoid possible contamination from the dissemination of information in the IG, we divided the schools into two areas based on different unions. Data analysis Regular follow‑up for control group A per‑protocol set analysis was conducted to explore this study’s efficacy. The continuous variables are expressed in mean and SD using the Mann–Whitney U test. Additionally, categorical variables are expressed as frequencies and percentages and were assessed using the Chi‑square test (χ2) performed in the SPSS for Windows version 26.0 (IBM Corp, Armonk, NY, USA). To observe the changes between both groups, covariance was analyzed using R software version 4.2 (R Foundation for Statistical Computing, Vienna, Austria).[46] The children in CG participated in all follow‑up activities; however, they received no health education throughout the intervention period. At the end of the study, the educational materials and the study findings were shared with them.[41] Outcome measurement Primary outcome The primary outcome of this study was the change in malnutrition rate among children as determined using BMI. The BMI was calculated using the WHO formula: BMI = weight (kg)/ height2 (m)2. Children’s nutritional status and BMI‑for‑age were measured by comparing the z‑scores against the 2007 WHO growth reference tables for children aged 5–19 years.[42,43] The cut‑off values for overweight and obesity are > +1 standard deviation (SD) and > +2SD, respectively, and the cut‑off value for thinness is < – 2SD. The BMI changes (BMI levels: −2SD, −1SD, +1SD, and + 2SD) categorized into three groups: 1 = decreased, 2 = no changed, and 3 = increased. Furthermore, Chi‑square and Wilcoxon rank‑sum tests were performed to compare the distribution between groups. To assess the changes in BMI between the groups, multivariate analysis was performed using a General Linear Model with a gamma‑log‑link distribution. BMI differences (from T2 to T0) were considered response variables, and age and BMI at T0 were adjusted variables. Some children showed abnormal changes; therefore, we removed 21 respondents who showed (±) 2SD as the outlier. Secondary outcomes We developed questionnaires that were pretested among 120 primary school children from different schools to ensure content validity and reliability. Eating and drinking‑related behavior data The questionnaire included children’s practices of eating meals thrice a day such as eating carbohydrate and protein‑containing foods and vegetables. The CHWs provided the survey form to the children’s parents with appropriate instructions and asked them to complete it based on their children’s 7‑day meal frequency. Regression analysis was used to compare the intervention effects, with both groups as independent variables, children’s awareness and knowledge and behavioral data at T2 as dependent variables, and the data at T0 as covariates. The gamma distribution was used to model non‑normally distributed data. During eating behavior analysis, the denominator value negative binomial model was used, and the general linear model (link = log) function in the MASS package of R was used to estimate a negative binomial distribution model. The significance level was set at P < 0.05. Awareness and knowledge of malnutrition We assessed the children’s awareness and knowledge of malnutrition using a quiz test questionnaire (10 questions) and Journal of Family Medicine and Primary Care 1027 Volume 13 : Issue 3 : March 2024 Aivey, et al.: School nurse trial on child malnutrition BDT (approximately <100 USD) per month, and approximately 50% of their fathers were employees in both groups. Results A total of 604 children were enrolled, allocated into CG (n = 290) and IG (n = 314) and participated in baseline data collection. During the intervention period, 70 children (24.1%) in CG and 79 (25.2%) in IG dropped out for unavoidable reasons. Therefore, 220 children in the CG and 235 in IG completed the study. The chronological changes in the children’s BMI categories according to WHO at each time point were revealed; the number of underweight children in each group increased [Figure 3]. The changes in BMI categories—the primary outcome of this study—were considered as “decreased,” “not changed,” and “increased” from T0 to T2. BMI “increased” in IG was 13 [Table 2], higher than the expected frequency of 9.41; however, BMI changes between the groups were not statistically significant. However, the mean (SD) of all children’s raw data of weight, height, and BMI was slightly increased for both sexes at each time point periodically [Supplementary Appendix 1]. The sociodemographic data of children in both groups were similar except for their academic grades (P = 0.011), religion (P = 0.008), and their mother’s educational level (P = 0.039) [Table 1]. Additionally, 263 (57.8%) were female, and each academic grade had >50 children, except for grade one. The family income of 168 respondents (36.90%) was <10,000 Table 1: Sociodemographic characteristics of the participants (n=455) Variables Gender Male Female Academic grades 1 2 3 4 Age 5 6 7 8 9 10 11 12 Religion Islam Hindu Family income (per month) Do not know <10,000 BDT 10,000‑20,000 BDT >20,000 BDT Occupation of the child’s father Employee Business Expatriate workers Others Occupation of the child’s mother Housewife Others Educational level of child’s father Primary level or lower Secondary level or above Educational level of child’s mother Primary level or lower Secondary level or above Control Group (n=220) Intervention Group (n=235) p 97 (44.1) 123 (55.9) 95 (40.4) 140 (59.6) 0.429 56 (25.5) 58 (26.4) 51 (23.2) 55 (25.0) 31 (13.2) 70 (29.8) 67 (28.5) 67 (28.5) 0.011** 1 (0.5) 33 (15.0) 43 (19.5) 51 (23.2) 48 (21.8) 31 (14.1) 9 (4.1) 4 (1.8) 0 (0.0) 15 (6.4) 50 (21.3) 57 (24.3) 53 (22.6) 47 (20.0) 10 (4.3) 3 (1.3) 0.105 214 (97.3) 6 (2.7) 215 (91.5) 20 (8.5) 0.008** 12 (5.5) 74 (33.6) 111 (50.5) 23 (10.5) 7 (3.0) 94 (40.0) 102 (43.4) 32 (13.6) 0.167 119 (54.1) 35 (15.9) 39 (17.7) 27 (12.3) 112 (47.7) 48 (20.4) 36 (15.3) 39 (16.6) 0.255 209 (95.0) 11 (5.0) 219 (93.2) 16 (6.8) 0.415 184 (83.6) 36 (16.4) 188 (80.0) 47 (20.0) 0.316 191 (86.8) 29 (13.2) 187 (79.6) 48 (20.4) 0.039* *<0.05, **<0.01, ***<0.001 Journal of Family Medicine and Primary Care 1028 Volume 13 : Issue 3 : March 2024 Aivey, et al.: School nurse trial on child malnutrition Figure 3: Frequency of BMI changes (according to World Health Organization cut‑off value, 2007) of both groups at each time point. Notes: IG = intervention group, CG = control group, BMI = body mass index, SD = standard deviation of malnutrition at T1 [Exp (β) =1.135, SE = 0.035, t = 3.678, P < 0.001] and T2 [Exp (β) =1.692, SE = 0.037, t = 14.358, P < 0.001] [Table 4]. Additionally, IG had a significantly higher mean score than that of CG. Table 2: Body mass index categorical change between groups after and before intervention (n=434) Categories Decreased No changed Increased Control Group (n=215) n (%) 28 (13.0) 181 (84.2) 6 (2.8) Intervention Group (n=219) n (%) 33 (15.1) 173 (78.9) 13 (5.9) The negative binomial regression analysis indicated that intervention significantly positively affected the eating behavior at T1 [Exp (β) =1.428, SE = 0.060, z = 3.388, P < 0.00] and T2 [Exp (β) =1.225, SE = 0.062, z = 5.742, P < 0.001] after adjusting for T0 [Table 5]. χ2=2.982, df=2, P=0.225 Gamma regression analysis was conducted on BMI changes after adjusting the T2 with T0; the intervention positively influenced BMI at T2 [Exp(β) =1.105, SE (standard error) =0.026, t = 3.869, P < 0.001], which was statistically significant between the groups [Table 3]. Moreover, the primary outcome was further adjusted with sociodemographic data, revealing significant intervention effects on BMI at T2 [Exp(β) =1.108, SE = 0.034, t = 2.984, P = 0.003]. The father’s educational qualifications as a covariate strongly influenced family income and higher educational qualifications significantly influenced the child’s BMI at T2 (P = 0.027). Discussion This is the first school nurse‑led study conducted to reduce child malnutrition and improve awareness and knowledge of malnutrition in Bangladesh. The results revealed that school nurse‑led health education had satisfactory effects on the groups at each time point (T1 and T2). The BMI categorical changes between the groups were not statistically significant. Although the raw data of the children’s height, weight and BMI were gradually increased at each time point. However, in this study, the pattern of Bangladeshi children’s growth is not adequate, which leads to an increasing number of poor BMI at T0 to T2 compared with WHO standard reference. The prior study explored similar findings such as high malnutrition, vitamin deficiency, poor growth pattern, and poor BMI compared with standard reference for the same‑aged group of children, and several studies failed to find out malnutrition for 5–15 years of children.[47‑49] Nevertheless, comparing the adjusted BMI changes, the number of malnourished children was reduced, and the changes in children’s BMI in IG were positively significant. Additionally, to assess intervention effects, we described the children’s BMI (mean ± SD) by all ages and divided the underweight children (lower than the WHO cut‑off value: −2SD to − 1SD) into − 2SD group as an underweight group and the rest (−1SD, +1SD, and + 2SD) into a nonunderweight group at T2 from T0 in both groups [Supplementary Appendix 2]. The children in the − 2SD group had more improvement (0.48) in BMI than the rest (0.20). In the − 2SD group, children in IG showed significantly greater improvement in BMI difference than those in CG (P = 0.008). Therefore, the intervention had favorable effects on the children. The malnutrition rate among the children was consistent with previous reports that 38% of school‑aged children are stunted, 41% are underweight, and 48% are wasted.[11] Moreover, the The gamma regression analysis revealed that the intervention significantly positively affected the awareness and knowledge Journal of Family Medicine and Primary Care 1029 Volume 13 : Issue 3 : March 2024 Aivey, et al.: School nurse trial on child malnutrition Table 3: Body mass index comparison (n=434) Variables Adjusted baseline model (Intercept) Group intervention BMI (baseline) Age (month) Adjusted T0 and sociodemographic model (Intercept) Group Intervention Control Gender Female Male BMI (baseline) School School (A) School (B) School © BMI categories (baseline) Age (month) Father’s educational qualification No education Primary level Secondary level Higher secondary level Graduate level or above Exp β (estimate) P High Std. Error t Low 95% CI 2.476 1.105 1.001 1.001 2.013 1.051 0.989 0.999 3.044 1.163 1.012 1.002 0.109 0.026 0.006 0.001 8.327 3.869 0.128 1.198 <0.001*** <0.001*** 0.898 0.231 2.275 1.793 2.884 0.125 6.600 <0.001*** 1.108 ref 1.036 1.186 0.034 2.984 0.003*** 1.029 ref 1.014 0.977 1.082 0.026 1.078 0.282 0.992 1.037 0.011 1.257 0.210 0.945 0.947 ref 0.935 1.001 0.877 0.881 1.019 1.018 0.038 0.037 ‑1.473 ‑1.474 0.142 0.141 0.862 0.999 1.014 1.002 0.042 0.001 ‑1.617 0.980 0.107 0.328 ref 1.001 1.022 1.043 0.843 0.945 0.939 0.919 0.727 1.061 1.114 1.188 0.983 0.030 0.044 0.065 0.077 0.030 0.509 0.649 ‑2.221 0.976 0.611 0.517 0.027* Multivariate general liner models gamma log‑link for the BMI difference (T2‑T0) with sociodemographic determinants. Note, BMI=body mass index, CI=confidence interval; Std. Error=standard error, *<0.05, **<0.01, ***<0.001 Table 4: Awareness and knowledge changes regarding malnutrition between groups (n=455) Outcome variable Coefficients Awareness & knowledge related to malnutrition T1 T2 Exp β (Estimate) 95% CI Low High Std. Error t P (Intercept) Group Baseline 5.514 1.135 1.009 4.468 1.574 0.991 5.134 1.818 1.016 0.033 0.035 0.006 51.119 3.678 1.556 <0.001*** <0.001*** 0.1203 (Intercept) Group Baseline 4.785 1.692 1.003 5.160 1.061 0.998 5.894 1.215 1.021 0.035 0.037 0.006 44.176 14.358 0.483 <0.001*** <0.001*** 0.63 General liner model: family=Gamma (link=log). Note, CI=confidence interval; Std. Error=standard error, *<0.05, **<0.01, ***<0.001 Table 5: Eating behavior changes between groups (n=455) Outcome variable Eating behavior T1 T2 Coefficients Exp β (Estimate) P High Std. Error Z Low 95% CI (Intercept) Group Baseline 6.977 1.428 1.023 6.253 1.089 1.000 7.925 1.377 1.024 0.059 0.060 0.006 32.988 3.388 2.05 <0.001*** <0.001*** <0.04 (Intercept) Group Baseline 7.036 1.225 1.012 6.159 1.265 1.011 7.908 1.613 1.037 0.062 0.062 0.006 31.467 5.742 3.725 <0.001*** <0.001*** <0.001*** Note, CI=confidence interval; Std. Error=standard error. Negative binomial model, *<0.05, **<0.01, ***<0.001 Journal of Family Medicine and Primary Care 1030 Volume 13 : Issue 3 : March 2024 Aivey, et al.: School nurse trial on child malnutrition significant at baseline, which might affect the study outcomes. Furthermore, the schools were from only rural unions. Thus, the efficacy of education is not conclusive as we did not cover urban areas in Bangladesh. Second, the study was conducted during the COVID‑19 pandemic; therefore, we could not extensively assess the intervention. Third, we did not include 5th‑grade children in the analysis, which may have affected the results. Lastly, a self‑reported questionnaire (dietary behavior) could be a possible source of bias. children’s BMI and malnutrition rates were closely associated with their sociodemographic status and parents’ educational level. A higher educational level of children’s fathers positively influenced children’s BMI improvement.[35,50,51] The factors for the high burden of malnutrition in Bangladesh can be broadly categorized as sociodemographic, access, health, physical, and low‑health literacy factors.[6,12,52] In this study, BMI was the only indicator used to assess malnutrition. Previous researchers used similar indicators among children of similar age groups[39,53,54] and acknowledged that uncontrolled BMI is associated with noncommunicable diseases in later stages of human life.[5] Therefore, regular BMI monitoring is essential for children to monitor health issues during early adulthood. Conclusion This study demonstrates the effectiveness of the first school nurse‑led evidence‑based health education through positive changes in the outcomes for primary school children. Overall, it provides evidence for further expansion of health educational interventions to accumulate evidence in Bangladesh, particularly in resource‑poor settings. We recommend for developing countries; it is obligatory to establish an authorized certified school nursing program and placement of school nurses in the school setting to improve the children’s health status in the future. Health education alone did not affect BMI changes; hence, we involved school authorities, CHWs, and parents. The CHWs continued periodic visits to the children’s home and encouraged the parents to positively change their daily lives based on health education. The intervention had positive effects, especially on underweight children, although a few showed improvements. Prior research explored the scope of improvement in child health status through school‑based[18,34,37] and community‑based health education involving their parents and primary care providers.[55,56] Therefore, individual approaches that consider the risk groups of children are vital in ensuring progressive changes. Ethical Policy and Institutional Review Board Statement This study followed the ethical standards of the 1975 Helsinki Declaration (revised version 2013) and was approved by the Institutional Review Board (2021/OR‑NSU/IRB/0701) from a University in Bangladesh. Before participating in the study, all the children provided verbal assent, and written informed consent was obtained from their parents (or legal guardian). We informed all the children and their parents about the research purpose, privacy, anonymity, no/minimal risk to participate in this study, and their right to withdraw from the study at any point without explanation. Data were recorded using a unique number for each participant to prevent duplication and identification. The secondary outcomes of this study significantly differed between the IG and CG, which provides robust evidence that school nurse‑led health education is effective for primary school children in school settings in Bangladesh, and may be relevant to other LMICs.[19,57,58] Therefore, increasing awareness and knowledge of health and preventive practices are key to minimizing malnutrition.[32,57] Health education from childhood is sustainable for a nation, and a school environment is a suitable place for children to learn healthy lifestyles and behaviors to prevent malnutrition.[59,60] Furthermore, longer intervention periods support the exploration of more findings.[61] As children’s parents repeatedly participated in health education, they became more concerned about their child’s health.[62] Thus, parents’ knowledge level could influence children’s health status.[16,63,64] Notably, we shared the children’s health report with their parents; hence, they became more concerned about their children’s health after acquiring health information.[65] Acknowledgements The authors sincerely acknowledge all the participants for their participation, all school staff, and study members who are involved in the study. The authors thank all the institutes including their staff for their support such as Grameen Caledonian College of Nursing, Grameen Communications, and Jadur Kathi, Bangladesh. The authors thank Mohammad Golam Nabi, Rokeya Akter Bristy, and Fatema Akter for their support. We also thank school nurses (Sanjida, Shashi, Sefa, Mitu, Israt, Lata, Akhi, Ambia, Munni, Sharmin, Susmita, Sheuly, Nadira, Puja, Hafeza, Tamalika, Kajol, Mithila, Farzana, Lucy, Ferdous) and CHWs (Foyas (supervisor of CHWs), Haowa, Reshma, Farzana, Habiba, Imran, Rima, Surma, Lucky, Shahnaj, Mehbuba, Moyna, Soniya, Halima). According to previous studies, school nurses are professionally unique, and their placement at school is vital in improving behavioral changes among children which is a way to make constructive rapport with primary care providers. [23,56,58] Additionally, school nurse placement creates a healthy and supportive environment and promotes child educational development. [18,66] However, reducing child malnutrition sustainably is still challenging in developing countries due to poor socioeconomic status. Financial support and sponsorship This study was funded by the Grants‑in‑Aid for Scientific Research Program (KAKENHI), Japan (Kiban B, N0. 21H03250). This study had some limitations. First, the schools were nonrandomly selected, and a few variables were statistically Journal of Family Medicine and Primary Care 1031 Volume 13 : Issue 3 : March 2024 Aivey, et al.: School nurse trial on child malnutrition of dietary diversity with undernutrition in school‑aged children. BMC Pediatr 2023;23:1‑10. doi: 10.1186/ s12887‑023‑04032‑y. Conflicts of interest There are no conflicts of interest. 16. Yabanci N, Kısaç İ, Karakuş SŞ. The effects of mother’s nutritional knowledge on attitudes and behaviors of children about nutrition. Procedia Soc Behav Sci 2014;116:4477‑81. References 1. Caulfield LE, de Onis M, Blössner M, Black RE. Undernutrition as an underlying cause of child deaths associated with diarrhea, pneumonia, malaria, and measles. Am J Clin Nutr 2004;80:193‑8. 2. Dey U, Bisai S. The prevalence of under‑nutrition among the tribal children in India: A systematic review. Anthropol Rev 2019;82:203‑17. 3. Chisti MJ, Tebruegge M, La Vincente S, Graham SM, Duke T. Pneumonia in severely malnourished children in developing countries‑mortality risk, aetiology and validity of WHO clinical signs: A systematic review. Trop Med Int Health 2009;14:1173‑89. 4. Liu L, Villavicencio F, Yeung D, Perin J, Lopez G, Strong KL, et al. National, regional, and global causes of mortality in 5‑19‑year‑olds from 2000 to 2019: A systematic analysis. Lancet Glob Heal 2022;10:e337‑47. 5. Baker JL, Olsen LW, Sørensen TIA, Sci M. Childhood body‑mass index and the risk of coronary heart disease in adulthood. N Engl J Med 2007;357:2329‑37. 6. Walson JL, Berkley JA. The impact of malnutrition on childhood infections. Curr Opin Infect Dis 2018;31:231‑6. 7. Peng W, Mu Y, Hu Y, Li B, Raman J, Sui Z. Double burden of malnutrition in the Asia‑Pacific region—A systematic review and meta‑analysis. J Epidemiol Glob Health 2020;10:16‑27. 8. Dukhi N. Global Prevalence of Malnutrition: Evidence from Literature. Intech Open 2020;10.5772/intechopen.92006. 9. Kirolos A, Goyheneix M, Kalmus Eliasz M, Chisala M, Lissauer S, Gladstone M, et al. Neurodevelopmental, cognitive, behavioural and mental health impairments following childhood malnutrition: A systematic review. BMJ Glob Heal 2022;7:e009330. doi: 10.1136/bmjgh‑2022‑009330. 17. Talib RA, Azdie W, Ismail MN. The effectiveness of nutrition education programme for primary school children. Malays J Nutr 2007;13:45‑54. 18. Pulimeno M, Piscitelli P, Colazzo S, Colao A, Miani A. School as ideal setting to promote health and wellbeing among young people. Heal Promot Perspect 2020;10:316‑24. 19. Teo CH, Chin YS, Lim PY, Masrom SAH, Shariff ZM. School‑based intervention that integrates nutrition education and supportive healthy school food environment among Malaysian primary school children: A study protocol. BMC Public Health 2019;19:1427. 20. Westerbotn M, Monfors F, Reusser J, Tyrrell M. Promoting health and preventing malnutrition among children in rural Bangladesh: A qualitative study. Nurs Open 2023;10:5693‑700. 21. Asakura K, Mori S, Sasaki S, Nishiwaki Y. A school‑based nutrition education program involving children and their guardians in Japan: Facilitation of guardian‑child communication and reduction of nutrition knowledge disparity. Nutr J 2021;20:1‑13. doi: 10.1186/ s12937‑021‑00751‑z. 22. Furukawa Y, Yokota F, Maruf RI, Nishikitani M, Kikuchi K, Ahmed A, et al. School‑based educational intervention to improve children’s oral health‑related behaviors in rural Bangladesh. South East Asia J Public Heal 2018;7:27‑33. 23. Turner G, Mackay S. The impact of school nurse interventions: Behaviour change and mental health. Br J Sch Nurs 2015;10:494‑506. 24. Bohnenkamp JH, Stephan SH, Bobo N. Sopporting student mental health: The role of the school nurse in coordinated school mental health care. Psychol Sch 2015;52:714‑27. 10. Galler JR, Bringas‑Vega ML, Tang Q, Rabinowitz AG, Musa KI, Chai WJ, et al. Neurodevelopmental effects of childhood malnutrition: A neuroimaging perspective. Neuroimage 2021;231:117828. doi: 10.1016/j.neuroimage. 2021.117828. 25. Harold M, Donna M. Role of the school nurse in providing school health services. American Academy of Pediatrics Council on School Health. Pediatrics 2008;121:1052‑6. 26. Stefanowicz A, Stefanowicz J. The role of a school nurse in the care of a child with diabetes mellitus type 1‑The perspectives of patients and their parents: Literature review. Zdr Varst 2018;57:166‑74. 11. Khanam SJ, Haque MA. Prevalence and determinants of malnutrition among primary school going children in the haor areas of Kishoreganj district of Bangladesh. Heliyon 2021;7:eo8077. 27. Lee RL. The role of school nurses in delivering accessible health services for primary and secondary school students in Hong Kong. J Clin Nurs 2011;20‑:2968‑77. 12. Sujan MSH, Islam MS, Naher S, Banik R, Gozal D. Predictors associated with knowledge and practice of helminthic infection prevention among rural school‑aged children’s parents in Bangladesh: A cross‑sectional study. Front Public Heal 2020;8. doi: 10.3389/fpubh. 2020.00484. 28. Lineberry MJ, Ickes MJ. The role and impact of nurses in American elementary schools: A systematic review of the research. J Sch Nurs 2015;31:22‑33. 13. Tay CW, Chin YS, Lee ST, Khouw I, Poh BK. Association of eating behavior with nutritional status and body composition in primary school‑aged children. Asia Pacific J Public Heal 2016;28:47S‑58S. 29. Health COS. Role of the school nurse in providing school health services. Pediatrics 2016;137:e20160852. doi: 10.1542/peds.2016‑0852. 14. Chang JJ, Xu N, Song LL, Li YH, Yuan MY, Zhang TT, et al. Association between the dietary literacy of children’s daily diet providers and school‑age children’s nutritional status and eating behaviours: A cross‑sectional study. BMC Public Health 2022;22:1‑12. doi: 10.1186/s12889‑022‑14621‑8 30. Kaufman TK, Lynch BA, Wilkinson JM. Childhood obesity: An evidence‑based approach to family‑centered advice and support. J Prim Care Community Health 2020;11:2150132720926279. doi: 10.1177/2150132720926279. 15. Zeinalabedini M, Zamani B, Nasli‑Esfahani E, Azadbakht L. A systematic review and meta‑analysis of the association 31. Karki P, Prabandari YS, Probandari A, Banjara MR. Feasibility of school‑based health education intervention to improve Journal of Family Medicine and Primary Care 1032 Volume 13 : Issue 3 : March 2024 Aivey, et al.: School nurse trial on child malnutrition scirp.org/(S(lz5mqp453edsnp55rrgjct55))/reference/ ReferencesPapers.aspx?ReferenceID=2342186. [Last accessed on 2023 Mar 07]. the compliance to mass drug administration for lymphatic Filariasis in Lalitpur district, Nepal: A mixed methods among students, teachers and health program manager. PLoS One 2018;13:e0203547. doi: 10.1371/journal.pone. 0203547. 47. Ahsan S, Saleh Z, Sheikh SA, Fahim MF, Memon MS, Shakil S, et al. Nutritional status of school going children of 5‑15 years of age: Urban slums scenario in Karachi, Pakistan. Biostat Biometrics Open Access J 2020;10:24‑8. 32. Gorely T, Nevill ME, Morris JG, Stensel DJ, Nevill A. Effect of a school‑based intervention to promote healthy lifestyles in 7‑11 year old children. Int J Behav Nutr Phys Act 2009;6:5. doi: 10.1186/1479‑5868‑6‑5. 48. Rahman MH, Alam SS. Nutritional status of children in slums of Dhaka, Bangladesh. J Nutr Food Sci 2015;5:1. 33. Baser S, Hasnath SA. The Rise and Fall of the NGOs in Bangladesh: What Does the Future Hold? IntechOpen 2023;10.5772/intechopen.107855. 49. Moestue H, de Pee S, Hall A, Hye A, Sultana N, Ishtiaque MZ, et al. Conclusions about differences in linear growth between Bangladeshi boys and girls depend on the growth reference used. Eur J Clin Nutr 2004;58:725‑31. 34. Kebaili R, Harrabi I, Maatoug J, Ghammam R, Slim S, Ghannem H. School‑based intervention to promote healthy nutrition in Sousse, Tunisia. Int J Adolesc Med Health 2014;26:253‑8. 50. Agbozo F, Atito P, Abubakari A. Malnutrition and associated factors in children: A comparative study between public and private schools in Hohoe Municipality, Ghana. BMC Nutr 2016;2:32. 35. Col L, Kunwar R. Impact of education of parents on nutritional status of primary school children. Med J Armed Forces India 2002;58:38‑43. 51. Igbokwe O, Adimorah G, Ikefuna A, Ibeziako N, Ubesie A, Ekeh C, et al. Socio‑demographic determinants of malnutrition among primary school aged children in Enugu, Nigeria. Pan Afr Med J 2017;:28‑48. 36. Shrestha RM, Ghimire M, Shakya P, Ayer R, Dhital R, Jimba M. School health and nutrition program implementation, impact, and challenges in schools of Nepal: Stakeholders’ perceptions. Trop Med Health 2019;47:1‑11. 52. Assemie MA, Shitu Getahun D, Hune Y, Petrucka P, Abebe AM, Telayneh AT, et al. Prevalence of intestinal parasitic infection and its associated factors among primary school students in Ethiopia: A systematic review and meta‑analysis. PLoS Negl Trop Dis 2021;15:e0009379. doi: 10.1371/journal.pntd. 0009379. 37. Kim SJ, Baek SS, Kang KA. Development and exploratory testing of a school‑based educational program for healthy life behaviors among fifth grade children in South Korea. Japan J Nurs Sci 2017;14:13‑26. 53. Angelopoulos PD, Milionis HJ, Grammatikaki E, Moschonis G, Manios Y. Changes in BMI and blood pressure after a school based intervention: The CHILDREN study. Eur J Public Health 2009;19:319‑25. 38. Reeves BC, Gaus W. Guidelines for reporting non‑randomised studies. Forschende Komplementarmedizin und Klass Naturheilkd 2004;11:46‑52. 39. Li XH, Lin S, Guo H, Huang Y, Wu L, Zhang Z, et al. Effectiveness of a school‑based physical activity intervention on obesity in school children: A nonrandomized controlled trial. BMC Public Health 2014;14:1282. doi: 10.1186/1471‑2458‑14‑1282. 54. Fairclough SJ, Hackett AF, Davies IG, Gobbi R, Mackintosh KA, Warburton GL, et al. Promoting healthy weight in primary school children through physical activity and nutrition education: A pragmatic evaluation of the CHANGE! randomised intervention study. BMC Public Health 2013;13:1‑14. doi: 10.1186/1471‑2458‑13‑626. 40. Tengku Jamaluddin TZM, Mohamed NA, Mohd Rani MD, Ismail Z, Ramli S, Faroque H, et al. Assessment on hand hygiene knowledge and practices among pre‑school children in Klang Valley. Glob Pediatr Heal 2020;7:2333794X2097636. doi: 10.1177/2333794x20976369. 55. Kim HW, Park S, Kim Y. Effect of community‑based education to Korean mothers in relation to the prevention of cervical cancer in their daughters: A non‑randomized trial. Japan J Nurs Sci 2018;15:146‑55. 41. Hollis JL, Sutherland R, Campbell L, Morgan PJ, Lubans DR, Nathan N, et al. Effects of a “school‑based” physical activity intervention on adiposity in adolescents from economically disadvantaged communities: Secondary outcomes of the “Physical Activity 4 Everyone” RCT. Int J Obes 2016;40:1486‑93. 56. Goldberg L, Rankine J, Devlin B, Np CP, Miller E, Ray KN. School nurse perspectives on collaboration with primary care providers. J Sch Health 2023;93:717‑25. 57. Shariff ZM, Bukhari SS, Othman N, Hashim N, Ismail M, Jamil Z, et al. Nutrition education intervention improves nutrition of primary school children nutrition education intervention improves nutrition knowledge, attitude and practices of primary school children: A pilot study nutrition education intervention improves nutrit. Int Electron J Health Educ 2008;11:119‑32. 42. Yeasmin S, Islam K. Prevalence and determinants of undernutrition among school age slum children in Dhaka City, Bangladesh. J Nutr Heal Sci 2016;3:201. 43. World Health Organization. Growth reference data for 5‑19 years. 2007. Available from: https://www.who.int/toolkits/ growth‑reference‑data‑for‑5to19‑years. [Last accessed on 2021 May 24]. 58. Best NC, Oppewal S, Travers D. Exploring school nurse interventions and health and education outcomes: An integrative review. J Sch Nurs 2017;34:14‑27. 44. Lavelle H V., MacKay DF, Pell JP. Systematic review and meta‑analysis of school‑based interventions to reduce body mass index. J Public Health (Oxf) 2012;34:360‑9. 59. Wafa SW, Ghazalli R. Association between the school environment and children’s body mass index in Terengganu: A cross sectional study. PLoS One 2020;15:e0232000. doi: 10.1371/journal.pone. 0232000. 45. Faul F, Erdfelder E, Lang AG, Buchner A. G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav Res Methods 2007;39:175‑91. 60. Khatoon R, Sachan B, Khan M, Srivastava J. Impact of school health education program on personal hygiene among school children of Lucknow district. J Fam Med Prim Care 2017;6:97‑100. 46. R Core Team. R: A language and environment for statistical computing. R foundation for statistical computing, Vienna. Sci Res 2008. Available from: https://www. Journal of Family Medicine and Primary Care 61. Murimi MW, Moyeda‑Carabaza AF, Nguyen B, Saha S, Amin R, 1033 Volume 13 : Issue 3 : March 2024 Aivey, et al.: School nurse trial on child malnutrition Njike V. Factors that contribute to effective nutrition education interventions in children: A systematic review. Nutr Rev 2018;76:553‑80. healthy‑eating attitudes and nutritional knowledge on nutritional adequacy and diet quality among preschoolers: The SENDO project. Nutrients 2018;10:1875. doi: 10.3390/ nu10121875. 62. Sudo K, Hamamoto Y. Health behaviors of foreign mothers in Japan regarding their young children and the factors that affect these behaviors: A qualitative study. Jpn J Nurs Sci 2019;16:420‑32. 65. Eli K, Neovius C, Nordin K, Brissman M, Ek A. Parents’ experiences following conversations about their young child’s weight in the primary health care setting: A study within the STOP project. BMC Public Health 2022;22:1‑14. doi: 10.1186/s12889‑022‑13803‑8. 63. De Vlieger N, Van Rossum J, Riley N, Miller A, Collins C, Bucher T. Nutrition education in the australian new south wales primary school curriculum: Knowledge and attitudes of students and parents. Children (Basel) 2020;7:24. doi: 10.3390/children7040024. 66. Jamal F, Fletcher A, Harden A, Wells H, Thomas J, Bonell C. The school environment and student health: A systematic review and meta‑ethnography of qualitative research. BMC Public Health 2013;13:1‑11. doi: 10.1186/1471‑2458‑13‑798. 64. Romanos‑Nanclares A, Zazpe I, Santiago S, Marín L, Rico‑Campà A, Martín‑Calvo N. Influence of parental Journal of Family Medicine and Primary Care 1034 Volume 13 : Issue 3 : March 2024 Aivey, et al.: School nurse trial on child malnutrition Multimedia Appendix 1: Educational materials (booklet, leaflet and poster) Journal of Family Medicine and Primary Care 1035 Volume 13 : Issue 3 : March 2024 Aivey, et al.: School nurse trial on child malnutrition Supplementary Appendix 1 Supplementary Appendix 1: The mean (SD) values of height, weight, and body mass index among the children in terms of gender for both groups at each time points Variables Times Height (cm) Weight (kg) Body mass index T0 T1 T2 T0 T1 T2 T0 T1 T2 Boy (mean (SD)) Overall Control group (n=186) (n=95) 127.08 (9.92) 125.25 (8.99) 130.75 (10.03) 129.19 (9.08) 132.32 (10.00) 130.95 (9.11) 24.19 (6.09) 23.05 (4.51) 25.74 (6.63) 24.51 (4.90) 26.35 (6.86) 25.01 (4.77) 14.77 (2.02) 14.58 (1.65) 14.86 (2.13) 14.58 (1.77) 14.85 (2.15) 14.49 (1.67) Intervention group (n=91) 128.99 (10.52) 132.37 (10.74) 133.74 (10.71) 25.38 (7.23) 27.03 (7.88) 27.76 (8.32) 14.97 (2.33) 15.15 (2.42) 15.22 (2.51) Overall (n=248) 126.88 (9.33) 130.68 (9.46) 132.44 (9.50) 24.15 (6.43) 25.81 (6.86) 26.57 (7.29) 14.79 (2.31) 14.91 (2.39) 14.92 (2.50) Girl (mean (SD)) Control group (n=120) 125.20 (8.89) 129.16 (9.11) 131.16 (9.27) 22.95 (5.52) 24.60 (6.12) 25.21 (6.40) 14.47 (1.89) 14.56 (2.05) 14.46 (2.11) Intervention group (n=128) 128.45 (9.50) 132.09 (9.60) 133.64 (9.60) 25.26 (7.02) 26.94 (7.33) 27.85 (7.85) 15.09 (2.61) 15.23 (2.63) 15.35 (2.76) Note, T0=Baseline, T1=Midline, T2=Endline, and SD=Standard deviation Supplementary Appendix 2 Body mass index differences from T2 to T0 of both groups Note. The Wilcoxon rank sum test showed that (1) The increase in BMI of the underweight group was higher in the intervention group (BMI difference = 0.48) than the control group (BMI difference = 0.07) from T2 to T0, which was statistically significant (p = 0.008). (2) The increase in BMI in the non‑underweight group was higher in the intervention group (BMI difference = 0.20) than in the control group (BMI difference = 0.07) from T2 to T0, which was statistically significant (p = 0.001) Note. BMI = body mass index, WHO = World Health Organization, SD = standard deviation. Journal of Family Medicine and Primary Care 1036 Volume 13 : Issue 3 : March 2024