Sanitation and Hygiene-Specific Risk Factors for Moderate-to-Severe Diarrhea in Young Children in the Global Enteric Multicenter Study, 2007–2011: Case-Control Study

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Study Justification:
This study aimed to investigate the sanitation and hygiene-specific risk factors for moderate-to-severe diarrhea (MSD) in young children. Diarrheal disease is a major cause of illness and death in children under 5 years old, and poor water, sanitation, and hygiene conditions are the primary routes of exposure and infection. Understanding the specific risk factors associated with MSD can help inform interventions and policies to reduce the burden of diarrheal disease in children.
Study Highlights:
– The study was conducted across seven sites in Africa and South Asia, including The Gambia, Kenya, Mali, Mozambique, Bangladesh, India, and Pakistan.
– Data was collected for over 8,500 case children with MSD and over 12,000 asymptomatic controls.
– The study found that sharing a sanitation facility with 1-2 or more households was a significant risk factor for MSD in several countries.
– The presence of soap or ash in designated handwashing areas was protective against MSD in Mozambique and India.
– The study suggests that increasing access to private household sanitation facilities can reduce the burden of MSD in children.
Recommendations:
Based on the findings of this study, the following recommendations can be made:
1. Increase access to private household sanitation facilities to reduce the risk of MSD in young children.
2. Promote the use of soap or ash in designated handwashing areas to prevent diarrheal disease.
3. Implement interventions to discourage open defecation, particularly in rural areas.
4. Improve sanitation and hygiene education and awareness among caregivers and communities.
Key Role Players:
To address the recommendations, the following key role players are needed:
1. Government agencies responsible for water and sanitation policies and programs.
2. Non-governmental organizations (NGOs) working in the field of water, sanitation, and hygiene.
3. Health departments and healthcare providers.
4. Community leaders and local authorities.
5. Researchers and academics specializing in public health and sanitation.
Cost Items for Planning Recommendations:
While the actual cost will vary depending on the specific context and interventions implemented, the following cost items should be considered in planning the recommendations:
1. Construction and maintenance of private household sanitation facilities.
2. Distribution of soap or ash for handwashing.
3. Development and implementation of sanitation and hygiene education programs.
4. Training of healthcare providers and community health workers.
5. Monitoring and evaluation of interventions.
6. Advocacy and awareness campaigns.
Please note that the above cost items are general categories and the actual cost will depend on factors such as the scale of interventions, local labor and material costs, and the duration of programs.

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 large case-control study conducted at multiple sites. The study collected data from over 8,500 case children and over 12,000 controls, which provides a robust sample size. The study also used site-specific conditional logistic regression models to explore the association between sanitation and hygiene exposures and moderate-to-severe diarrhea (MSD) in children. The findings suggest that sharing a sanitation facility with one to two other households can increase the risk of MSD in young children. To improve the evidence, future studies could consider conducting a systematic review and meta-analysis to combine the findings from multiple studies and provide a more comprehensive assessment of the association between sanitation and hygiene exposures and MSD in children.

Background: Diarrheal disease is the second leading cause of disease in children less than 5 y of age. Poor water, sanitation, and hygiene conditions are the primary routes of exposure and infection. Sanitation and hygiene interventions are estimated to generate a 36% and 48% reduction in diarrheal risk in young children, respectively. Little is known about whether the number of households sharing a sanitation facility affects a child’s risk of diarrhea. The objective of this study was to describe sanitation and hygiene access across the Global Enteric Multicenter Study (GEMS) sites in Africa and South Asia and to assess sanitation and hygiene exposures, including shared sanitation access, as risk factors for moderate-to-severe diarrhea (MSD) in children less than 5 y of age. Methods/Findings: The GEMS matched case-control study was conducted between December 1, 2007, and March 3, 2011, at seven sites in Basse, The Gambia; Nyanza Province, Kenya; Bamako, Mali; Manhiça, Mozambique; Mirzapur, Bangladesh; Kolkata, India; and Karachi, Pakistan. Data was collected for 8,592 case children aged <5 y old experiencing MSD and for 12,390 asymptomatic age, gender, and neighborhood-matched controls. An MSD case was defined as a child with a diarrheal illness 93%) had access to a sanitation facility, while 70% of households in rural Kenya had access to a facility. Practicing open defecation was a risk factor for MSD in children <5 y old in Kenya. Sharing sanitation facilities with 1–2 or ≥3 other households was a statistically significant risk factor for MSD in Kenya, Mali, Mozambique, and Pakistan. Among those with a designated handwashing area near the home, soap or ash were more frequently observed at control households and were significantly protective against MSD in Mozambique and India. Conclusions: This study suggests that sharing a sanitation facility with just one to two other households can increase the risk of MSD in young children, compared to using a private facility. Interventions aimed at increasing access to private household sanitation facilities may reduce the burden of MSD in children. These findings support the current World Health Organization/ United Nations Children's Emergency Fund (UNICEF) system that categorizes shared sanitation as unimproved.

Written informed consent was obtained from caretakers of enrolled children. The scientific and ethical review committees of each participating organization, including in-country ethics approval, and the Institutional Review Board of the University of Maryland, Baltimore, approved the protocol and consent forms (S1 Table). The seven GEMS sites included Basse Sante Su, The Gambia; Nyanza Province, Kenya; Bamako, Mali; Manhiça, Mozambique; Mirzapur, Bangladesh; Kolkata, India; and Karachi (Bin Qasim Town), Pakistan [33]. Two sites are located in urban centers (Mali and India), and four sites are in rural settings (The Gambia, Mozambique, Kenya, and Bangladesh), whereas the study villages in Pakistan, located on the coast approximately 20 km outside Karachi, are considered periurban. Each GEMS site was linked to a defined population under a demographic surveillance system (DSS) that visited every household 2–3 times per year to record births, deaths, and migrations. The GEMS is a matched case-control study in which cases were children <5 y old seeking care for MSD at one of the sentinel health centers serving the DSS at each site (S2 Table). MSD was defined as passing three or more loose stools within 24 h, in conjunction with clinical signs of moderate-to-severe dehydration (sunken eyes, loss of skin turgor, or administration of IV fluids), dysentery, or admission to a health facility. Stool specimens were collected from all children at enrollment. Control children without diarrhea were randomly selected from the DSS population within 14 d of presentation of the case and matched to the case by age, sex, and neighborhood. Detailed GEMS clinical and epidemiologic methods have been published [33,34]. Case and control enrollment into GEMS took place over 36 mo from December 1, 2007, to March 3, 2011. Demographic information collected about the case or control and his/her household (defined as a group of people who share a cooking fire) included maternal education and household size (including the number of children <5 y old). Building materials and household possessions were documented as potential indicators for constructing a wealth index for each site [33]. WASH data were collected at enrollment from the caretakers of case children presenting at health facilities and at home for matched control children by means of a standardized questionnaire. Approximately 60 (range: 50–90) days after enrollment, a trained field worker visited the household of each case and control to collect follow-up health information and record WASH observations. Information on water sources, facilities to dispose of human fecal waste, and handwashing and other hygiene practices was collected at enrollment, with additional information (including direct observation of hygiene practices, latrines, and toilet facilities) recorded at the 60-d follow-up home visit. Five sociodemographic variables were considered in this analysis as potential confounders (Table 1). A wealth index quintile (WIQ) variable was generated by principal component analysis of 13 household assets. This method has been described elsewhere [33,35]. Access to an improved water source was defined as the main source of drinking water for the household at follow-up as a public or private piped water tap, tube well, borehole, protected dug well, protected spring, or rainwater that was available every day, with a round trip time of 30 min or less to fetch water [16]. Abbreviations: GEMS, Global Enteric Multicenter Study; VIP, ventilated improved pit. *Denotes five wealth index quintiles, with 1 representing the poorest households and 5 representing the wealthiest households. Eight sanitation and hygiene variables were explored in this paper (Table 1), including three self-reported or observed sanitation variables, two directly observed fecal contamination variables, and two directly observed handwashing variables. Sanitation variables included facility type, facility access and sharing, and disposal of child’s feces as reported by respondent. Because of the skewed distribution of the number of households sharing facilities and for comparison across sites, the highest category for numbers of households sharing a sanitation facility was categorized based on the overall median of 3. Data analysis was limited to subjects for whom complete data were available on sanitation access at enrollment and follow-up. Data were analyzed using SAS version 9.3 (SAS Institute, Cary, NC). Descriptive statistics for sociodemographic and exposure variables were reported as proportions, medians, and ranges. We aimed to describe site-to-site variability in effects; therefore, we present all results stratified by site. The modeling strategy involved estimating unadjusted effects of association between sanitation and hygiene exposures and MSD and assessing two-way interactions between exposures and age, followed by selecting and including consistent sociodemographic confounders across all sites for reporting adjusted estimates of sanitation and hygiene exposures. Site-specific univariable conditional logistic regression models were used to evaluate the relationship between sanitation exposure variables and MSD. Unadjusted matched odds ratios (mORs) and 95% confidence intervals (CIs) are reported. Since risk factors are likely to be different for infants, we assessed two-way interactions between risk factors and age. There were no significant interactions with age; thus, only main effects are reported, and all models still account for the age-, sex-, and geography-matched case-control design. For many of the primary sanitation variables of interest, there were low exposure frequencies, which limited the number of variables that could be included in multivariable conditional logistic models. Therefore, we ran separate multivariable conditional logistic models for each sanitation and hygiene exposure of interest. We considered the following variables as potential confounders: WIQs, caretaker education, parental residence in the household, other young children in the household, and access to an improved water source. We assessed for confounding one at a time in each of the models by identifying significant associations with MSD and effect size changes in our estimates of sanitation and hygiene variables. Based on previous research, we considered a priori that wealth was an important epidemiological factor associated with MSD and should be included in the multivariable models to produce adjusted estimates of sanitation and hygiene exposures [22]. We aimed to present consistent results across sites, so we adjusted for these same parameters in all site-specific multivariable conditional logistic regression models. Multivariable models were assessed for collinearity using condition index diagnostics.

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

1. Improved Sanitation Facilities: Developing and implementing innovative sanitation facilities that are easily accessible, private, and hygienic can help reduce the risk of diarrheal diseases in young children and improve maternal health outcomes.

2. Hygiene Education and Promotion: Implementing innovative hygiene education programs that focus on promoting proper handwashing practices, use of soap or ash, and safe disposal of fecal waste can help prevent the spread of diseases and improve maternal health.

3. Mobile Health (mHealth) Solutions: Utilizing mobile technology to provide maternal health information, reminders, and access to healthcare services can improve access to essential maternal health services, especially in remote or underserved areas.

4. Telemedicine: Implementing telemedicine services that allow pregnant women to consult with healthcare providers remotely can improve access to prenatal care, reduce travel time and costs, and ensure timely medical advice and support.

5. Community Health Workers: Training and deploying community health workers who can provide essential maternal health services, education, and support at the community level can improve access to care, especially in areas with limited healthcare infrastructure.

6. Transportation Solutions: Developing innovative transportation solutions, such as ambulances or transport vouchers, to ensure timely and safe transportation for pregnant women to healthcare facilities can improve access to emergency obstetric care and reduce maternal mortality.

7. Financial Incentives: Implementing innovative financial incentive programs, such as conditional cash transfers or vouchers, to encourage pregnant women to seek and utilize maternal health services can help overcome financial barriers and improve access to care.

8. Public-Private Partnerships: Establishing partnerships between public and private sectors to improve access to maternal health services can leverage resources, expertise, and infrastructure to ensure quality care and reach underserved populations.

These are just a few potential innovations that can be explored to improve access to maternal health. It is important to assess the feasibility, effectiveness, and sustainability of these innovations in specific contexts before implementing them on a larger scale.
AI Innovations Description
Based on the description provided, the recommendation to improve access to maternal health is to focus on sanitation and hygiene interventions. The study found that poor water, sanitation, and hygiene conditions are the primary routes of exposure and infection for diarrheal diseases, which are a significant cause of illness in children under 5 years old. Sanitation and hygiene interventions have been shown to reduce the risk of diarrheal diseases in young children.

Specifically, the study found that sharing a sanitation facility with one to two other households increases the risk of moderate-to-severe diarrhea (MSD) in young children compared to using a private facility. Therefore, interventions aimed at increasing access to private household sanitation facilities may reduce the burden of MSD in children.

Additionally, the study found that the presence of soap or ash in designated handwashing areas near the home was significantly protective against MSD in certain locations. This suggests that promoting proper handwashing practices, including the availability of soap or ash, can also contribute to reducing the risk of diarrheal diseases in children.

Overall, the recommendation is to prioritize improving access to private household sanitation facilities and promoting proper handwashing practices, including the availability of soap or ash, to improve maternal health and reduce the burden of diarrheal diseases in young children.
AI Innovations Methodology
Based on the provided information, here are some potential recommendations for improving access to maternal health:

1. Improve sanitation facilities: Enhance access to private household sanitation facilities to reduce the burden of moderate-to-severe diarrhea (MSD) in children. This can be achieved by promoting the construction and maintenance of individual household toilets.

2. Increase hygiene practices: Encourage proper handwashing with soap or ash, especially in households with designated handwashing areas. This can be achieved through educational campaigns and the provision of affordable and accessible hygiene products.

3. Address shared sanitation challenges: Develop strategies to mitigate the risks associated with sharing sanitation facilities. This may involve implementing measures to ensure proper maintenance, hygiene, and privacy in shared facilities.

To simulate the impact of these recommendations on improving access to maternal health, a methodology could include the following steps:

1. Data collection: Gather information on the current state of sanitation and hygiene access in the target population. This can be done through surveys, interviews, or existing data sources.

2. Define indicators: Identify key indicators that reflect the level of access to maternal health services, such as the number of maternal deaths, maternal healthcare utilization rates, or access to prenatal and postnatal care.

3. Establish a baseline: Determine the current status of the selected indicators to establish a baseline against which the impact of the recommendations can be measured.

4. Model the impact: Use statistical modeling techniques to simulate the potential impact of the recommendations on the selected indicators. This can involve creating scenarios that reflect the implementation of the recommendations and estimating the resulting changes in the indicators.

5. Validate the model: Validate the model by comparing the simulated results with real-world data, if available. This will help ensure the accuracy and reliability of the simulation.

6. Analyze the results: Analyze the simulated results to assess the potential impact of the recommendations on improving access to maternal health. This can involve quantifying the expected changes in the selected indicators and evaluating the feasibility and effectiveness of the recommendations.

7. Refine and iterate: Based on the analysis of the simulated results, refine the recommendations and iterate the simulation process if necessary. This can involve adjusting the parameters of the model or incorporating additional factors that may influence the impact of the recommendations.

By following this methodology, policymakers and stakeholders can gain insights into the potential benefits of implementing the recommended innovations and make informed decisions to improve access to maternal health.

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