Age at menarche in relation to nutritional status and critical life events among rural and urban secondary school girls in post-conflict Northern Uganda

BMC Women's Health, Volume 14, No. 1, Year 2014

Ukuhunyushwa

Background: Menarche age is an important indicator of reproductive health of a woman or a community. In industrial societies, age at menarche has been declining over the last 150 years with a secular trend, and similar trends have been reported in some developing countries. Menarche age is affected by genetic and environmental cues, including nutrition. The study was designed to determine the age at menarche and its relation to childhood critical life events and nutritional status in post-conflict northern Uganda.Methods: This was a comparative cross-sectional study of rural and urban secondary school girls in northern Uganda. Structured questionnaires were administered to 274 secondary school girls, aged 12 – 18 years to determine the age at menarche in relation to home location, nutritional status, body composition and critical life events.Results: The mean age at menarche was 13.6 ± 1.3 for rural and 13.3 ± 1.4 years for urban dwelling girls (t = -1.996, p = 0.047). Among the body composition measures, hip circumference was negatively correlated with the age at menarche (r = -0.109, p = 0.036), whereas height, BMI and waist circumference did not correlate with menarche. Paternal (but not maternal) education was associated with earlier menarche (F = 2.959, p = 0.033). Childhood critical life events were not associated with age at menarche.Conclusions: Age at menarche differed among urban and rural dwelling school girls and dependent on current nutritional status, as manifested by the hip circumference. It was not associated with extreme stressful childhood critical life events. © 2014 Odongkara Mpora et al.; licensee BioMed Central Ltd. Gulu District, located 332 km north of the capital Kampala, has an area of 12,000 km2 and a population of 354,000, with a male/female ratio of 0.96. The main economic activity is farming, and poverty is widespread and severe; most families survive on either external aid or less than a dollar a day. The region was involved in a war for over 20 years from 1985 to 2006. The study subjects were born and raised during the war and were between 6 and12 years of age at the end of the war. The study subjects were selected from 11 rural and 11 urban secondary schools, which were randomly sampled. Rural girls live in villages without access to electricity, running water or roads, while urban girls live in areas with electricity, water, roads and healthcare facilities within a 5-kilometer radius from town centers. The design criteria included all the girls in the selected schools, except those suffering from chronic illnesses. A systematic sampling method was employed to ensure equal chance to participate in the study. Sample size was calculated comparing two means, assuming the power of 80% to detect any significant difference between the two groups [10], and required a total of 274 subjects. A total of 274 students, aged 12 – 18 years were studied with 137 subjects in the rural and 137 in the urban group. Three girls were excluded because they had not had their menarche and 271 were subjected to the final analysis. A set of standardized pre-coded questionnaires were used to obtain menarche data and demographic characteristics. The questionnaires were self-administered to the girls while at school. The dependent variable was age at menarche and independent variables included demographic characteristics: place of residence, family size, the presence of siblings and parents in the household, maternal and paternal education, maternal and paternal occupation, parents’ marital status, BMI, as well as a list of stressful life events that occurred during the war. Such stressful events include abduction into rebel captivity, loss of close first-degree relatives during the war, living in displacement camps and not living with both parents in the same household. Place of residence was defined as where the girls lived with the rest of the family members at the time of the interview. Family size was defined as the number of persons in the family, while paternal and maternal education implied the level of academic achievements of the parents specified as no education, primary, secondary and tertiary education. Parental occupation was defined according to the job or work each parent did to earn a living and take care of the family and it was specified as peasant farmer, employed, housewife or unemployed. The parents were considered married if they were in a matrimonial relationship and living together in the same household. Data entry was done using EPI Data 3.1 and analysis was done by SPSS version 17.1. A bivariate analysis was done to compare the characteristics of secondary school girls in urban and rural schools with respective p values for chi-square. An independent sample t-test was done for two independent groups to compare age at menarche among rural and urban school girls in relation to various critical life events. Nutritional status for rural and urban school girls was compared using the independent samples t-test. One-way ANOVA was used to compare menarche age with parental parameters. Each stressful life event was analyzed independently for association with age at menarche. Pearson’s correlation analysis was conducted on the combined analysis for the relationship between age at menarche and independent variables as listed above. Statistical significance was defined as p-value <0.05. Ethical approval was obtained from the Ethics Committee of Gulu University Faculty of Medicine. Parents were informed in writing about the study and agreed verbally for their daughters to be interviewed. Informed consent was obtained from the school administration and verbal assent was obtained from participating students. Girls with menarche problems and other pubertal problems were further investigated and treated by an endocrinologist.

I-AI Digest

Study Justification:

This study aimed to investigate the age at menarche (the onset of menstruation) and its relationship to nutritional status and critical life events among secondary school girls in post-conflict Northern Uganda. The study is important because age at menarche is an indicator of reproductive health and can provide insights into the overall well-being of women and communities. Understanding the factors that influence age at menarche can help inform interventions and policies related to reproductive health and nutrition.

Study Highlights:

– The study found that the mean age at menarche was 13.6 years for rural girls and 13.3 years for urban girls.
– Hip circumference was negatively correlated with age at menarche, indicating that current nutritional status, as reflected by hip circumference, may influence the timing of menarche.
– Paternal education was associated with earlier menarche, while childhood critical life events were not found to be associated with age at menarche.

Recommendations for Lay Readers and Policy Makers:

1. Improve access to nutrition: Given the association between hip circumference and age at menarche, efforts should be made to improve nutrition among adolescent girls, particularly in rural areas where access to nutritious food may be limited.
2. Enhance educational opportunities: The finding that paternal education was associated with earlier menarche suggests that education may play a role in reproductive health outcomes. Policies should focus on increasing educational opportunities for both girls and boys.
3. Address reproductive health needs: The study highlights the importance of addressing reproductive health needs among adolescent girls, including access to menstrual hygiene products and comprehensive sexual education.
4. Support post-conflict communities: Post-conflict communities may face unique challenges that can impact reproductive health. Policies should prioritize support for these communities, including access to healthcare facilities and psychosocial support services.

Key Role Players:

1. Ministry of Health: Responsible for implementing policies related to reproductive health and nutrition.
2. Ministry of Education: Involved in promoting educational opportunities for girls and boys.
3. Non-governmental organizations (NGOs): Can provide support in implementing interventions related to nutrition, reproductive health, and psychosocial support.
4. Community leaders: Play a crucial role in raising awareness and mobilizing resources to address the needs of adolescent girls.

Cost Items for Planning Recommendations:

1. Nutrition programs: Budget for implementing nutrition programs targeting adolescent girls, including initiatives to improve access to nutritious food and supplements.
2. Educational initiatives: Allocate funds for initiatives aimed at increasing educational opportunities for girls and boys, such as scholarships, school infrastructure improvements, and teacher training.
3. Reproductive health services: Include funding for reproductive health services, including access to menstrual hygiene products, sexual education programs, and healthcare facilities.
4. Psychosocial support services: Budget for providing psychosocial support services to address the unique needs of post-conflict communities, including counseling and trauma-informed care.
Please note that the cost items provided are general categories and would need to be further detailed and estimated based on the specific context and resources available.

Amandla Obufakazi

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is moderately strong, but there are some areas for improvement. The study design is a comparative cross-sectional study, which provides some evidence for a relationship between age at menarche and factors such as home location, nutritional status, body composition, and critical life events. The sample size of 274 secondary school girls is relatively large, which adds to the strength of the evidence. However, there are a few limitations to consider. First, the study relies on self-reported data, which may introduce bias. Second, the study does not provide information on the specific methods used to measure nutritional status and body composition, which could affect the validity of the findings. Third, the study only includes girls from rural and urban areas in post-conflict northern Uganda, so the findings may not be generalizable to other populations. To improve the strength of the evidence, future studies could consider using more objective measures of nutritional status and body composition, include a more diverse sample of participants, and use longitudinal designs to better understand the relationship between age at menarche and the factors examined.

Abstract

Gulu District, located 332 km north of the capital Kampala, has an area of 12,000 km2 and a population of 354,000, with a male/female ratio of 0.96. The main economic activity is farming, and poverty is widespread and severe; most families survive on either external aid or less than a dollar a day. The region was involved in a war for over 20 years from 1985 to 2006. The study subjects were born and raised during the war and were between 6 and12 years of age at the end of the war. The study subjects were selected from 11 rural and 11 urban secondary schools, which were randomly sampled. Rural girls live in villages without access to electricity, running water or roads, while urban girls live in areas with electricity, water, roads and healthcare facilities within a 5-kilometer radius from town centers. The design criteria included all the girls in the selected schools, except those suffering from chronic illnesses. A systematic sampling method was employed to ensure equal chance to participate in the study. Sample size was calculated comparing two means, assuming the power of 80% to detect any significant difference between the two groups [10], and required a total of 274 subjects. A total of 274 students, aged 12 – 18 years were studied with 137 subjects in the rural and 137 in the urban group. Three girls were excluded because they had not had their menarche and 271 were subjected to the final analysis. A set of standardized pre-coded questionnaires were used to obtain menarche data and demographic characteristics. The questionnaires were self-administered to the girls while at school. The dependent variable was age at menarche and independent variables included demographic characteristics: place of residence, family size, the presence of siblings and parents in the household, maternal and paternal education, maternal and paternal occupation, parents’ marital status, BMI, as well as a list of stressful life events that occurred during the war. Such stressful events include abduction into rebel captivity, loss of close first-degree relatives during the war, living in displacement camps and not living with both parents in the same household. Place of residence was defined as where the girls lived with the rest of the family members at the time of the interview. Family size was defined as the number of persons in the family, while paternal and maternal education implied the level of academic achievements of the parents specified as no education, primary, secondary and tertiary education. Parental occupation was defined according to the job or work each parent did to earn a living and take care of the family and it was specified as peasant farmer, employed, housewife or unemployed. The parents were considered married if they were in a matrimonial relationship and living together in the same household. Data entry was done using EPI Data 3.1 and analysis was done by SPSS version 17.1. A bivariate analysis was done to compare the characteristics of secondary school girls in urban and rural schools with respective p values for chi-square. An independent sample t-test was done for two independent groups to compare age at menarche among rural and urban school girls in relation to various critical life events. Nutritional status for rural and urban school girls was compared using the independent samples t-test. One-way ANOVA was used to compare menarche age with parental parameters. Each stressful life event was analyzed independently for association with age at menarche. Pearson’s correlation analysis was conducted on the combined analysis for the relationship between age at menarche and independent variables as listed above. Statistical significance was defined as p-value <0.05. Ethical approval was obtained from the Ethics Committee of Gulu University Faculty of Medicine. Parents were informed in writing about the study and agreed verbally for their daughters to be interviewed. Informed consent was obtained from the school administration and verbal assent was obtained from participating students. Girls with menarche problems and other pubertal problems were further investigated and treated by an endocrinologist.

Izinto zokwakha

N/A

Emisha

Based on the provided information, here are some potential innovations that could improve access to maternal health:

1. Mobile Health Clinics: Implementing mobile health clinics that can travel to rural areas without access to healthcare facilities. These clinics can provide prenatal care, postnatal care, and other maternal health services to women in remote areas.

2. Telemedicine: Introducing telemedicine services that allow pregnant women in rural areas to consult with healthcare professionals remotely. This can help address the lack of healthcare providers in these areas and provide timely advice and support to pregnant women.

3. Community Health Workers: Training and deploying community health workers in rural areas to provide basic maternal health services, education, and support to pregnant women. These workers can also help identify high-risk pregnancies and refer women to appropriate healthcare facilities.

4. Maternal Health Vouchers: Introducing a voucher system that provides financial assistance to pregnant women in low-income areas, enabling them to access quality maternal healthcare services. This can help overcome financial barriers and ensure that all women have access to essential maternal health services.

5. Health Education Programs: Implementing comprehensive health education programs in schools and communities to raise awareness about maternal health, reproductive rights, and the importance of prenatal and postnatal care. These programs can empower women with knowledge and encourage them to seek appropriate healthcare services.

6. Infrastructure Development: Investing in the development of healthcare infrastructure in rural areas, including the construction of healthcare facilities and improving road connectivity to ensure better access to maternal health services.

7. Maternal Health Information Systems: Implementing digital information systems to track and monitor maternal health indicators, such as age at menarche, nutritional status, and critical life events. This data can help identify trends, target interventions, and improve overall maternal health outcomes.

It is important to note that these recommendations are based on the information provided and may need to be tailored to the specific context and needs of the community in question.

AI Innovations Description

Based on the provided information, a recommendation to improve access to maternal health in post-conflict Northern Uganda could be to implement targeted interventions aimed at improving nutritional status among adolescent girls. This recommendation is based on the finding that age at menarche, which is an important indicator of reproductive health, is influenced by nutrition.

To implement this recommendation, the following steps could be taken:

1. Conduct a comprehensive assessment of the nutritional status of adolescent girls in rural and urban areas of Northern Uganda. This assessment should include measurements of body composition, such as hip circumference, as well as other indicators of nutritional status.

2. Develop and implement targeted interventions to improve the nutritional status of adolescent girls. These interventions could include providing access to nutritious food, promoting healthy eating habits, and educating girls and their families about the importance of nutrition for reproductive health.

3. Collaborate with local communities, schools, and healthcare facilities to ensure the successful implementation of these interventions. This could involve training healthcare providers and educators on the importance of nutrition for maternal health and providing them with the necessary resources to support the interventions.

4. Monitor and evaluate the impact of the interventions on the nutritional status of adolescent girls and their age at menarche. This could be done through regular assessments and data collection.

By improving the nutritional status of adolescent girls, it is expected that their reproductive health, including maternal health, will also improve. This recommendation takes into account the specific context of post-conflict Northern Uganda, where poverty and limited access to basic services are prevalent.

AI Innovations Methodology

In order to improve access to maternal health in post-conflict Northern Uganda, the following innovations and recommendations can be considered:

1. Mobile Clinics: Implementing mobile clinics that can travel to rural areas without access to healthcare facilities. These clinics can provide prenatal care, postnatal care, and other essential maternal health services.

2. Telemedicine: Utilizing telemedicine technology to connect rural communities with healthcare professionals in urban areas. This would allow for remote consultations, diagnosis, and treatment, reducing the need for travel and improving access to specialized care.

3. Community Health Workers: Training and deploying community health workers in rural areas to provide basic maternal health services, education, and support. These workers can act as a bridge between the community and healthcare facilities, ensuring that women receive the care they need.

4. Health Education Programs: Implementing comprehensive health education programs that focus on maternal health, including topics such as prenatal care, nutrition, family planning, and safe delivery practices. These programs can be conducted in schools, community centers, and through mobile outreach initiatives.

To simulate the impact of these recommendations on improving access to maternal health, a methodology could be developed as follows:

1. Baseline Data Collection: Gather data on the current state of maternal health in the target area, including indicators such as maternal mortality rates, access to prenatal care, and availability of healthcare facilities.

2. Define Metrics: Identify specific metrics to measure the impact of the recommendations, such as the number of women receiving prenatal care, the number of safe deliveries, or the reduction in maternal mortality rates.

3. Simulation Modeling: Use simulation modeling techniques to estimate the potential impact of the recommendations on the defined metrics. This could involve creating a mathematical model that takes into account factors such as population size, geographic distribution, and healthcare resource allocation.

4. Sensitivity Analysis: Conduct sensitivity analysis to assess the robustness of the simulation model and evaluate the potential impact of different scenarios or variations in key parameters. This can help identify potential challenges or limitations of the recommendations.

5. Validation: Validate the simulation model by comparing the simulated results with real-world data or conducting pilot studies to measure the actual impact of implementing the recommendations.

6. Monitoring and Evaluation: Continuously monitor and evaluate the implementation of the recommendations, collecting data on the defined metrics to assess the progress and make any necessary adjustments.

By following this methodology, policymakers and healthcare professionals can gain insights into the potential impact of the recommendations on improving access to maternal health and make informed decisions on resource allocation and implementation strategies.

Ababhali & Co-Ababhali

Statistics:

Citations: 28

Authors: 7

Identifiers:

DOI: 10.1186/1472-6874-14-66

Research Areas:

Community Interventions, Environmental, Food Security, Genetics and Genomics, Health System and Policy, Maternal Access, Maternal and Child Health, Sexual and Reproductive Health, Social Determinants

Study Countries:

Uganda

Study Design:

Cross Sectional Study

Study Approach:

Quantitative

Participants Gender:

Male & Female

Yabelana ngalokhu: