Malnutrition, morbidity and infection in the informal settlements of Nairobi, Kenya: An epidemiological study

Italian Journal of Pediatrics, Volume 45, No. 1, Year 2019

Interpretation

Background: Malnutrition constitutes one of the major public health challenges throughout the developing world. Urban poverty and malnutrition have been on the rise, with an increased rate of morbidity. We herein explore the relationship between infections and nutritional status and the related association with hygienic conditions as risk of infection in children residing in the slums of Nairobi. Methods: Case-control study based on a secondary analysis of quantitative data collected from a cluster randomized trial carried out in two slums of Nairobi. The following information about resident children were selected: babies’ anthropometric measurements, related life conditions, data on infant-feeding practices, food security, hygiene, immunization coverage and morbidity were collected and updated with structured questionnaires until 12 months of life. Prevalence of malnutrition was calculated, then both bivariate and multivariate analysis were used to explore the relationship between malnutrition and its determinants. Results: The study involved a total of 1119 babies registered at birth (51.28% male and 48.03% female infants). Overall the prevalence of malnutrition was high, with 26.3% of the children being stunted, 6.3% wasted and 13.16% underweight. Prevalence of wasting was higher in the first months of life, while in older children more case of stunting and underweight were captured. Wasted infants were significantly associated with common childhood illnesses: with cough and rapid breathing as well as with diarrhea (p-value< 0.05). Stunting was associated with hygienic conditions (p-value< 0.05 in households that did not perform any water treatment and for children that had a toilet within the house compound), immunization program and low-birth-weight. Moreover, regression analysis showed that significant determinants of stunting were sex and feeding practices. Underweight was significantly associated with socio-demographic factors. Conclusions: In the specific environment where the study was conducted acute malnutrition is correlated with acute infections, while chronic malnutrition is more influenced by WASH conditions. Therefore, our findings suggest that one cannot separate infection and its risk factors as determinants of the whole malnutrition burden. We herein explore the relationship between infections and nutritional status and the related association with hygienic conditions as risk of infection in children residing in above-mentioned slums. The MYICN (Maternal Infant and Young Child Nutrition) Intervention study, a cluster randomized controlled trial, was carried out in two slums of Nairobi, Kenya, i.e. Korogocho and Viwandani; here the African Population and Health Research Center (APHRC) runs the Nairobi Urban Health and Demographic Surveillance System (NUHDSS), covering close to 70,000 residents. The two slums are located about 7 km from each other and are densely populated with 63,318 and 52,583 inhabitants per square kilometer respectively [16]. The NUHDSS involves a systematic quarterly recording of vital demographic events, including births, deaths and migrations occurring among residents of all households in the area since 2003. Other data are also collected and updated regularly [17]. The informal settlements of Viwandani and Korogocho were selected as study sites, since data from available literature showed high malnutrition prevalence in these areas; with 45% of children aged < 5 years stunted and high under-five children mortality (79 deaths/1000 live births) [18] these settlements performed worse than other populations in Kenya, including those residing in rural settings and other areas of Nairobi, considering mortality, rate of infections and life conditions [9]. Case-control study based on a secondary analysis of quantitative data collected by the antecedent MIYCN intervention study. The latter’s protocol has already been published [19, 20] together with the results of the intervention [21]. Therefore we herein only detail methods relevant to the specific research question of this paper. The source population consisted in all pregnant women and their offspring living in the randomized Community Health Units (CUs, defined by the Kenya National Community Health Strategy) in Korogocho and Viwandani slums that fall within the NUHDSS area. The inclusion criteria were as follows: all pregnant women aged between 12 and 49 years and their children,born between December 2012 and July 2014. Exclusion criteria were as follows: women with a disability that made the administration of the questionnaires challenging (e.g. hearing, sight or mental impairment); women of reproductive age who had given birth before the recruitment started; disability in both mother and child that would significantly affect infant feeding (e.g. developmental problems); women who had a miscarriage or a still-birth; women who were lost to follow-up during pregnancy. Recruitment of participants was conducted through routine NUHDSS rounds, whereby pregnancy registration is done for female residents in each household. This was complemented by case finding carried out by Community Health volunteers (CHVs) and informants to ensure high coverage. While the reproductive age in most studies is usually defined as 15 to 49 years, girls aged 12 to 14 years were included because a substantial proportion (close to 10%) of adolescents in the study areas is sexually active before the age of 15 years [22]. Within the design of the MIYCN trial, which had focused on optimal maternal and infant feeding practices (as recommended by the WHO - World Health Organization), the population had been randomly divided into two groups: the intervention group and the control group. Both groups were involved in regular visits by CHVs, according to the specific needs of every age group [21]. In the intervention group, mothers were provided with age specific counseling and support on optimal child feeding and health, including breastfeeding initiation, exclusive breastfeeding (EBF), extended breastfeeding, complementary feeding, maternal nutrition, antenatal care including birth planning, health care seeking for delivery and post-natal services including immunization and general hygiene and child care. They also received information materials on MIYCN. The mothers in the intervention arm were visited at least monthly during pregnancy until gestation week no. 34, after which they were visited every week until they gave birth, and more frequently (as necessary) in the 1st month after giving birth (for support in initiating breastfeeding and sustaining EBF). They were then visited once a month until the 5th month, when they were visited fortnightly (to prepare them for introduction of complementary feeding) and monthly in the subsequent months until one year of age of the child. The control arm received standard care involving CHVs visits providing counselling on antenatal care, postnatal care including immunization and general hygiene in accordance with the guidance set forth by the community health strategy. The frequency of visits was defined by need, but generally about once a month per household, and usually more frequent around the time of birth. No specific schedule was given to them and CHVs in the control arm did not undergo any specific training on child feeding. However, mothers in the control arm also received information materials on MIYCN. In the MIYCN Intervention study, babies’ anthropometric measurements, data on infant feeding practices, household characteristics, demographic factors, food security and hygiene, immunization coverage and morbidity were collected and updated (where relevant) every two months during follow-up visits in both groups (intervention and control). Data were captured using various researcher-administered questionnaires. With regards to the present study specific data have been selected from the data dictionary (where all information had been stored). Malnutrition, indicated by wasted, stunted and underweight children. Anthropometric measurements (weight, length) were taken according to standard procedures [23]. Prevalence of malnutrition in the population was generated and the related prevalence of stunting, underweight and wasting at different ages was also considered. For determination of underweight, stunting, and wasting, we calculated weight-for-age z-scores (WAZ), height-for-age z-scores (HAZ) and weight-for-height z-scores (WHZ), using the WHO 2007 growth standards [23, 24]. Stunting was determined as HAZ < − 2, underweight as WAZ < − 2 and wasting as WHZ < − 2 [25]. Independent variables were categorized into three groups. Concerning child health status, common childhood symptoms of illnesses occurring two weeks before the interview date were considered. These included: fever, cough, cough with rapid breathing, diarrhea and seizures. The five common childhood illnesses’ symptoms were counted as separate variables in the analysis, but also collectively as morbidity (general morbidity), when a child had at least a single episode of illness - regardless of the type - two weeks before the interview date. Household Water, Sanitation and Hygiene (WASH) conditions were measured using data from a structured questionnaire addressing water, food and personal hygiene. One of the considered variables was whether any kind of water treatment had been in use at home; possible answers were: no treatment; filtered water; boiled water; water guard/aquatabs/other chemical treatment; sedimentation; UV rays or solar disinfection; sieved through cloth; others. Variables about habits of washing utensils for feeding babies, hand washing practice with soap (with specified frequency), presence of a toilet facility in or near the household were also investigated. With regards to sanitation, type of toilet facility used during the day and at night was categorized into two groups: own (own flush, traditional pit, Ventilated Improved Pit) and shared (shared flush, traditional pit, shared Ventilated Improved Pit; flush trench toilet; toilet without pit, working flush; no facility or bush and field, or flying toilet, and other toilet facility). Socio-economic and demographic variables: the following were included: sex of the child; mother’s age, parity and occupation; marital status; religion; attained level of mother’s education. Birth Weight (BW): BW was categorized into three groups: Low Birth Weight (LBW, less than 2.5 Kg), normal weight at birth (between 2.5 and 4.2 Kg) and overweight (more than 4.2 Kg at birth). Immunization coverage: The variable on full vaccination among children according to the Kenyan Immunization Program was considered [26]. Exclusive breastfeeding until six months: Data were collected through the interviewer-administered questionnaire to the mother to determine if the child was still breastfeeding, and, if so, whether they had started feeding on other foods or fluids other than breast milk; when they were introduced to the other foods or fluids; and if they stopped breastfeeding, when they stopped [21]. Complementary feeding practices: this focused on complementary feeding practices with regard to WHO recommendations [27]. In the present study we focused only on: timely introduction of solid/semi-solid/soft foods; number of food groups consumed (at least four food groups consumed and less than four); minimum meal babies’ frequency and household food security situation. Household Food Security: Household food security was defined using a modified Household Food Insecurity Access Scale (HFIAS) [28] . The WHO growth reference 2007 for children was used to generate anthropometric indices to assess the nutritional status of children [23, 25, 29]. The indices were expressed as standard deviation units from the median of the WHO child growth standards adopted in 2007. Bivariate analysis was conducted to evaluate the association between dependent and independent variables and to identify determinants of malnutrition in the study population. Odds Ratio (OR) and their 95% confidence intervals (CI) were estimated in order to show the magnitude of the association between independent variables and malnutrition. P-values of less than 0.05 were considered statistically significant. All independent variables were analyzed initially in bivariate models and the variables that were significantly associated with the dependent variable were included in logistic regression models. Subsequent selection of variables fitted into the final models was based on statistical significance of p-value ≤0.25, as proposed by Hosmer and Lameshow [30], upon running univariable logistic regression with all the exploratory variables considered in the study. Adjustment for confounding factors were made for the associations observed between independent variables and dependent variables. Details on data collection procedures and other data collected are published [19]. Data management and analysis were carried out using STATA Version 13.

AI Digest

Study Justification:

– Malnutrition is a significant public health challenge in developing countries, including Nairobi, Kenya.
– Urban poverty and malnutrition rates are increasing, leading to higher morbidity rates.
– This study aims to explore the relationship between infections, nutritional status, and hygienic conditions as risk factors for malnutrition in children living in the slums of Nairobi.

Study Highlights:

– The study involved 1119 babies registered at birth in two slums of Nairobi.
– The prevalence of malnutrition was high, with 26.3% of children being stunted, 6.3% wasted, and 13.16% underweight.
– Wasting was more prevalent in the first months of life, while stunting and underweight were more common in older children.
– Wasted infants were significantly associated with cough, rapid breathing, and diarrhea.
– Stunting was associated with poor hygienic conditions, lack of water treatment, immunization coverage, and low birth weight.
– Underweight was significantly associated with socio-demographic factors.

Recommendations for Lay Reader and Policy Maker:

– Improve access to clean water and promote water treatment practices in households.
– Enhance immunization coverage to reduce the risk of malnutrition.
– Promote proper hygiene practices, including handwashing and sanitation, to prevent infections and reduce the burden of malnutrition.
– Address socio-demographic factors that contribute to underweight in children.
– Provide targeted interventions for infants and young children to improve feeding practices and nutrition.

Key Role Players:

– Ministry of Health, Kenya
– Nairobi County Government
– African Population and Health Research Center (APHRC)
– Community Health Volunteers (CHVs)
– Non-governmental organizations (NGOs) working in nutrition and child health

Cost Items for Planning Recommendations:

– Water treatment supplies and equipment
– Immunization program resources
– Hygiene promotion materials and campaigns
– Training and capacity building for healthcare workers and community health volunteers
– Monitoring and evaluation activities to assess the impact of interventions

Strength of Evidence

The strength of evidence for this abstract is 8 out of 10.
The evidence in the abstract is strong because it is based on a case-control study with a large sample size (1119 babies) and includes both bivariate and multivariate analysis. The study provides prevalence rates of malnutrition and explores the relationship between malnutrition and its determinants. To improve the evidence, the abstract could include more information about the study design, such as the sampling method and inclusion/exclusion criteria. Additionally, it would be helpful to provide more details about the statistical methods used in the analysis.

Abstract

We herein explore the relationship between infections and nutritional status and the related association with hygienic conditions as risk of infection in children residing in above-mentioned slums. The MYICN (Maternal Infant and Young Child Nutrition) Intervention study, a cluster randomized controlled trial, was carried out in two slums of Nairobi, Kenya, i.e. Korogocho and Viwandani; here the African Population and Health Research Center (APHRC) runs the Nairobi Urban Health and Demographic Surveillance System (NUHDSS), covering close to 70,000 residents. The two slums are located about 7 km from each other and are densely populated with 63,318 and 52,583 inhabitants per square kilometer respectively [16]. The NUHDSS involves a systematic quarterly recording of vital demographic events, including births, deaths and migrations occurring among residents of all households in the area since 2003. Other data are also collected and updated regularly [17]. The informal settlements of Viwandani and Korogocho were selected as study sites, since data from available literature showed high malnutrition prevalence in these areas; with 45% of children aged < 5 years stunted and high under-five children mortality (79 deaths/1000 live births) [18] these settlements performed worse than other populations in Kenya, including those residing in rural settings and other areas of Nairobi, considering mortality, rate of infections and life conditions [9]. Case-control study based on a secondary analysis of quantitative data collected by the antecedent MIYCN intervention study. The latter’s protocol has already been published [19, 20] together with the results of the intervention [21]. Therefore we herein only detail methods relevant to the specific research question of this paper. The source population consisted in all pregnant women and their offspring living in the randomized Community Health Units (CUs, defined by the Kenya National Community Health Strategy) in Korogocho and Viwandani slums that fall within the NUHDSS area. The inclusion criteria were as follows: all pregnant women aged between 12 and 49 years and their children,born between December 2012 and July 2014. Exclusion criteria were as follows: women with a disability that made the administration of the questionnaires challenging (e.g. hearing, sight or mental impairment); women of reproductive age who had given birth before the recruitment started; disability in both mother and child that would significantly affect infant feeding (e.g. developmental problems); women who had a miscarriage or a still-birth; women who were lost to follow-up during pregnancy. Recruitment of participants was conducted through routine NUHDSS rounds, whereby pregnancy registration is done for female residents in each household. This was complemented by case finding carried out by Community Health volunteers (CHVs) and informants to ensure high coverage. While the reproductive age in most studies is usually defined as 15 to 49 years, girls aged 12 to 14 years were included because a substantial proportion (close to 10%) of adolescents in the study areas is sexually active before the age of 15 years [22]. Within the design of the MIYCN trial, which had focused on optimal maternal and infant feeding practices (as recommended by the WHO – World Health Organization), the population had been randomly divided into two groups: the intervention group and the control group. Both groups were involved in regular visits by CHVs, according to the specific needs of every age group [21]. In the intervention group, mothers were provided with age specific counseling and support on optimal child feeding and health, including breastfeeding initiation, exclusive breastfeeding (EBF), extended breastfeeding, complementary feeding, maternal nutrition, antenatal care including birth planning, health care seeking for delivery and post-natal services including immunization and general hygiene and child care. They also received information materials on MIYCN. The mothers in the intervention arm were visited at least monthly during pregnancy until gestation week no. 34, after which they were visited every week until they gave birth, and more frequently (as necessary) in the 1st month after giving birth (for support in initiating breastfeeding and sustaining EBF). They were then visited once a month until the 5th month, when they were visited fortnightly (to prepare them for introduction of complementary feeding) and monthly in the subsequent months until one year of age of the child. The control arm received standard care involving CHVs visits providing counselling on antenatal care, postnatal care including immunization and general hygiene in accordance with the guidance set forth by the community health strategy. The frequency of visits was defined by need, but generally about once a month per household, and usually more frequent around the time of birth. No specific schedule was given to them and CHVs in the control arm did not undergo any specific training on child feeding. However, mothers in the control arm also received information materials on MIYCN. In the MIYCN Intervention study, babies’ anthropometric measurements, data on infant feeding practices, household characteristics, demographic factors, food security and hygiene, immunization coverage and morbidity were collected and updated (where relevant) every two months during follow-up visits in both groups (intervention and control). Data were captured using various researcher-administered questionnaires. With regards to the present study specific data have been selected from the data dictionary (where all information had been stored). Malnutrition, indicated by wasted, stunted and underweight children. Anthropometric measurements (weight, length) were taken according to standard procedures [23]. Prevalence of malnutrition in the population was generated and the related prevalence of stunting, underweight and wasting at different ages was also considered. For determination of underweight, stunting, and wasting, we calculated weight-for-age z-scores (WAZ), height-for-age z-scores (HAZ) and weight-for-height z-scores (WHZ), using the WHO 2007 growth standards [23, 24]. Stunting was determined as HAZ < − 2, underweight as WAZ < − 2 and wasting as WHZ < − 2 [25]. Independent variables were categorized into three groups. Concerning child health status, common childhood symptoms of illnesses occurring two weeks before the interview date were considered. These included: fever, cough, cough with rapid breathing, diarrhea and seizures. The five common childhood illnesses’ symptoms were counted as separate variables in the analysis, but also collectively as morbidity (general morbidity), when a child had at least a single episode of illness – regardless of the type – two weeks before the interview date. Household Water, Sanitation and Hygiene (WASH) conditions were measured using data from a structured questionnaire addressing water, food and personal hygiene. One of the considered variables was whether any kind of water treatment had been in use at home; possible answers were: no treatment; filtered water; boiled water; water guard/aquatabs/other chemical treatment; sedimentation; UV rays or solar disinfection; sieved through cloth; others. Variables about habits of washing utensils for feeding babies, hand washing practice with soap (with specified frequency), presence of a toilet facility in or near the household were also investigated. With regards to sanitation, type of toilet facility used during the day and at night was categorized into two groups: own (own flush, traditional pit, Ventilated Improved Pit) and shared (shared flush, traditional pit, shared Ventilated Improved Pit; flush trench toilet; toilet without pit, working flush; no facility or bush and field, or flying toilet, and other toilet facility). Socio-economic and demographic variables: the following were included: sex of the child; mother’s age, parity and occupation; marital status; religion; attained level of mother’s education. Birth Weight (BW): BW was categorized into three groups: Low Birth Weight (LBW, less than 2.5 Kg), normal weight at birth (between 2.5 and 4.2 Kg) and overweight (more than 4.2 Kg at birth). Immunization coverage: The variable on full vaccination among children according to the Kenyan Immunization Program was considered [26]. Exclusive breastfeeding until six months: Data were collected through the interviewer-administered questionnaire to the mother to determine if the child was still breastfeeding, and, if so, whether they had started feeding on other foods or fluids other than breast milk; when they were introduced to the other foods or fluids; and if they stopped breastfeeding, when they stopped [21]. Complementary feeding practices: this focused on complementary feeding practices with regard to WHO recommendations [27]. In the present study we focused only on: timely introduction of solid/semi-solid/soft foods; number of food groups consumed (at least four food groups consumed and less than four); minimum meal babies’ frequency and household food security situation. Household Food Security: Household food security was defined using a modified Household Food Insecurity Access Scale (HFIAS) [28] . The WHO growth reference 2007 for children was used to generate anthropometric indices to assess the nutritional status of children [23, 25, 29]. The indices were expressed as standard deviation units from the median of the WHO child growth standards adopted in 2007. Bivariate analysis was conducted to evaluate the association between dependent and independent variables and to identify determinants of malnutrition in the study population. Odds Ratio (OR) and their 95% confidence intervals (CI) were estimated in order to show the magnitude of the association between independent variables and malnutrition. P-values of less than 0.05 were considered statistically significant. All independent variables were analyzed initially in bivariate models and the variables that were significantly associated with the dependent variable were included in logistic regression models. Subsequent selection of variables fitted into the final models was based on statistical significance of p-value ≤0.25, as proposed by Hosmer and Lameshow [30], upon running univariable logistic regression with all the exploratory variables considered in the study. Adjustment for confounding factors were made for the associations observed between independent variables and dependent variables. Details on data collection procedures and other data collected are published [19]. Data management and analysis were carried out using STATA Version 13.

Materials

N/A

Innovations

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

1. Mobile Health (mHealth) Applications: Develop mobile applications that provide pregnant women and new mothers with information on optimal maternal and infant feeding practices, immunization schedules, and general hygiene and child care. These apps can also send reminders and alerts for important health appointments and provide access to teleconsultations with healthcare providers.

2. Community Health Volunteers (CHVs) Training: Provide specialized training to CHVs on maternal and infant nutrition, hygiene practices, and common childhood illnesses. This will empower them to provide accurate information and support to pregnant women and new mothers in the community.

3. Water Treatment and Sanitation Interventions: Implement interventions to improve access to clean water and sanitation facilities in the slums. This can include promoting water treatment methods, such as filtration or chemical treatment, and improving toilet facilities to ensure proper hygiene practices.

4. Targeted Nutrition Programs: Develop targeted nutrition programs that address the specific nutritional needs of pregnant women and young children in the slums. These programs can provide access to nutrient-rich foods, nutritional supplements, and counseling on optimal feeding practices.

5. Integrated Healthcare Services: Establish integrated healthcare services that combine maternal health, child health, and nutrition services in one location. This can improve access to comprehensive care and ensure continuity of care for pregnant women and their children.

6. Public Awareness Campaigns: Launch public awareness campaigns to educate the community about the importance of maternal health, nutrition, and hygiene practices. These campaigns can use various media channels, such as radio, television, and community events, to reach a wide audience.

7. Strengthening Health Systems: Invest in strengthening the overall health system in the slums, including improving healthcare infrastructure, training healthcare providers, and ensuring the availability of essential medicines and supplies.

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 slums in Nairobi, Kenya.

AI Innovations Description

Based on the description provided, the following recommendation can be developed into an innovation to improve access to maternal health:

1. Strengthening Maternal and Child Nutrition Programs: Implement comprehensive nutrition programs that focus on improving the nutritional status of pregnant women and children in the slums of Nairobi. This can include providing access to nutritious food, promoting breastfeeding and complementary feeding practices, and educating mothers on proper nutrition during pregnancy and early childhood.

2. Enhancing Hygiene and Sanitation Practices: Improve access to clean water, sanitation facilities, and hygiene practices in the slums. This can involve initiatives such as building community water sources, promoting handwashing with soap, and ensuring proper waste management. These efforts can help reduce the risk of infections and improve overall health outcomes for mothers and children.

3. Strengthening Immunization Coverage: Increase immunization coverage among children in the slums by implementing targeted immunization campaigns and ensuring access to vaccines. This can help prevent common childhood illnesses and reduce the burden of morbidity and malnutrition.

4. Empowering Community Health Workers: Train and empower community health workers (CHWs) to provide essential maternal and child health services in the slums. CHWs can play a crucial role in delivering healthcare services, promoting healthy behaviors, and providing education and support to mothers and families.

5. Strengthening Health Systems: Improve the overall health system in the slums by increasing the availability and accessibility of maternal health services. This can involve establishing and equipping health facilities, ensuring the availability of skilled healthcare providers, and strengthening referral systems for high-risk pregnancies and complications.

By implementing these recommendations, it is possible to develop innovative approaches to improve access to maternal health in the slums of Nairobi, Kenya. These interventions can address the underlying factors contributing to malnutrition, morbidity, and infection, and ultimately improve the health and well-being of mothers and children in these communities.

AI Innovations Methodology

Based on the provided description, here are two potential recommendations to improve access to maternal health:

1. Strengthening Hygiene Practices: Given the association between hygienic conditions and malnutrition, it is important to focus on improving hygiene practices in the slums of Nairobi. This can include promoting handwashing with soap, proper sanitation facilities, and safe water treatment methods. Implementing community-based hygiene education programs and providing access to affordable hygiene products can help improve hygiene practices and reduce the risk of infections.

2. Enhancing Maternal and Infant Nutrition: To address malnutrition, it is crucial to improve maternal and infant nutrition. This can be achieved through various interventions such as promoting exclusive breastfeeding for the first six months, providing nutritional counseling and support to mothers, and ensuring access to diverse and nutritious food options. Additionally, implementing programs that address food security issues and improve household food availability can also contribute to better maternal and infant nutrition.

Methodology to simulate the impact of these recommendations on improving access to maternal health:

1. Data Collection: Collect baseline data on key indicators related to access to maternal health, such as maternal and infant nutrition, hygiene practices, and healthcare utilization. This can be done through surveys, interviews, and observations in the target population.

2. Modeling: Develop a simulation model that incorporates the collected data and simulates the impact of the recommendations on improving access to maternal health. The model should consider various factors such as population size, demographic characteristics, and existing healthcare infrastructure.

3. Intervention Scenarios: Define different intervention scenarios based on the recommendations, such as increasing hygiene education, promoting exclusive breastfeeding, and improving food security. Each scenario should include specific targets and timelines for implementation.

4. Impact Assessment: Simulate the impact of each intervention scenario on key outcome measures, such as reduction in malnutrition rates, improvement in hygiene practices, and increase in healthcare utilization. Use statistical analysis and modeling techniques to estimate the potential impact of the interventions.

5. Sensitivity Analysis: Conduct sensitivity analysis to assess the robustness of the results and identify key factors that may influence the effectiveness of the interventions. This can help refine the recommendations and identify potential challenges or limitations.

6. Policy Recommendations: Based on the simulation results, provide evidence-based policy recommendations to stakeholders, policymakers, and healthcare providers. Highlight the potential benefits of implementing the recommended interventions and suggest strategies for their implementation and monitoring.

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

Author

Dima Health

Statistics:

Citations: 17

Identifiers:

DOI: 10.1186/s13052-019-0607-0

ISSN: 17208424

Research Areas:

Community Interventions, Disability, Disparities, Environmental, Food Security, Health System and Policy, Maternal Access, Maternal and Child Health, Quality of Care, Sexual and Reproductive Health, Social Determinants

Study Countries:

Kenya

Study Design:

Case-Control Study, Cohort Study, Cross Sectional Study, Exploratory Study, Grounded Theory, randomised-control-trial

Study Approach:

Quantitative

Participants Gender:

Male & Female