Impact of childhood nutritional status on pathogen prevalence and severity of acute diarrhea

American Journal of Tropical Medicine and Hygiene, Volume 97, No. 5, Year 2017

Interpretation

Children with acute and chronic malnutrition are at increased risk of morbidity and mortality following a diarrheal episode. To compare diarrheal disease severity and pathogen prevalence among children with and without acute and chronic malnutrition, we conducted a cross-sectional study of human immunodeficiency virus-uninfected Kenyan children aged 6–59 months, who presented with acute diarrhea. Children underwent clinical and anthropometric assessments and provided stool for bacterial and protozoal pathogen detection. Clinical and microbiological features were compared using log binomial regression among children with and without wasting (mid-upper arm circumference ≤ 125 mm) or stunting (height-for-age z score ≤ _2). Among 1,363 children, 7.0% were wasted and 16.9% were stunted. After adjustment for potential confounders, children with wasting were more likely than nonwasted children to present with at least one Integrated Management of Childhood Illness danger sign (adjusted prevalence ratio [aPR]: 1.3, 95% confidence interval [CI]: 1.0 to 1.5, P = 0.05), severe dehydration (aPR: 2.4, 95% CI: 1.5 to 3.8, P < 0.01), and enteroaggregative Escherichia coli recovered from their stool (aPR: 1.8, 1.1–2.8, P = 0.02). There were no differences in the prevalence of other pathogens by wasting status after confounder adjustment. Stunting was not associated with clinical severity or the presence of specific pathogens. Wasted children with diarrhea presented with more severe disease than children without malnutrition which may be explained by a delay in care-seeking or diminished immune response to infection. Combating social determinants and host risk factors associated with severe disease, rather than specific pathogens, may reduce the disparities in poor diarrhea-associated outcomes experienced by malnourished children. This analysis used data collected from children under 5 years of age presenting with acute diarrhea to the outpatient and inpatient units at Kisii Provincial Hospital, Migori District Hospital, and Homa Bay District Hospital between November 2011 and June 2014. A description of this study has been published previously.13,14 Briefly, the parent study recruited children aged 6 months to 15 years presenting to the health facility with acute diarrhea (≥ 3 loose stools in the previous 24 hours and lasting less than 14 days). Eligible participants were excluded if they were not accompanied by a legal guardian or biological parent, if study staff were unable to collect a stool sample or rectal swab or if the primary caregiver refused human immunodeficiency virus (HIV) testing on behalf of the child. Written informed consent was obtained from the child’s caregiver. For this analysis, we included HIV-uninfected children 6 months to 5 years of age recruited at Homa Bay or Kisii hospitals. Migori Hospital patients were excluded as the low numbers recruited would be challenging to appropriately include in statistical models. The study was approved by the Kenya Medical Research Institute and University of Washington ethical review boards. At enrollment the primary caregiver completed a standardized clinical and sociodemographic questionnaire. All children were examined by clinical staff who recorded the presence of World Health Organization (WHO) Integrated Management of Childhood Illness (IMCI) danger signs (unable to drink or feed, vomiting everything, convulsions, lethargic, or unconscious) and hydration status (severe dehydration defined as at least two of the following: lethargic or unconscious, sunken eyes, not able to drink, reduced skin turgor). Weight, mid-upper arm circumference (MUAC), and height (or length) were measured and HAZs, weight-for-age z-scores (WAZ), and weight-for-height z-scores (WHZ) were calculated using WHO ANTHRO software.15 Z-scores of less than −7 or greater than 7 were deemed implausible and set to missing. All children were tested for HIV using antibody testing (Abbott Determine™ rapid test kit [Abbott Park, IL] and confirmed using Uni-Gold™ [Trinity Biotech, Bray, Ireland]) or HIV polymerase chain reaction (PCR) if under 18 months of age. Maternal HIV status was determined by antibody rapid testing or self-report. Malaria status was determined by a combination of rapid test (Paracheck Pf® Orchid Biomedical Services, Verna, Goa, India) and microscopy. Stool samples were collected in stool collection containers by caregivers or study staff. When a child was not able to produce stool, three rectal swabs were obtained. Fecal samples were collected prior to antibiotic administration, if indicated. Samples were received in the nearby U.S. Army Medical Research Directorate—Kenya (USAMD-K) Microbiology Hub in Kericho within 24 hours of collection after being placed in transport media (Cary–Blair for bacterial culture and 10% formalin for protozoal testing) and maintained at 2–8°C. Bacterial pathogens (E. coli, Shigella spp., Campylobacter spp., Salmonella spp.) were identified using traditional culture and serotyping methods confirmed using the MicroScan WalkAway 40 Plus (Beckman Coulter, Brea, CA) automated platform. Escherichia coli isolates were further tested for virulence factors using multiplex PCR and classified by pathotype: ETEC (heat labile or heat stable enterotoxin), EPEC (bundle forming pilus and, after March 2013, intimin), enteroaggregrative E.coli (EAEC) (aatA and, after March 2013, aaiC), enteroinvasive E.coli (invasion plasmid antigen H), or enterohemmorhagic E.coli (Shiga toxin 1,2 and variant). Protozoal infections were identified from whole stool samples using microscopy after stool concentration using Mini Parasep® Solvent Free concentration kit (DiaSys, Berkshire, England). No viral testing was performed. Analyses were conducted to examine whether children with acute malnutrition (wasting, MUAC < 12.5 cm) or chronic malnutrition (stunted HAZ < −2) had a higher prevalence of detectable enteric pathogens at presentation or presented with more severe disease (defined as the presence of at least one IMCI danger sign and/or severe dehydration). WHZ was not used to define acute malnutrition because it is influenced by fluid status and children with diarrhea often have some degree of dehydration. All prevalences were compared using log-binomial regression and associated χ2 tests.16 Pathogens and danger signs that were significantly associated with nutritional status in univariate regression at an alpha of 0.05 were further assessed in multivariable models. Potential confounders were evaluated for inclusion in each model in a stepwise manner and maintained in the model if the prevalence ratio changed by more than 10%. The following potential confounding variables were considered: age, gender, hospital site, currently receiving any breast milk (yes/no), maternal HIV status, family income (dichotomized at above or below 5,000 Kenyan Shillings), caregiver education (primary education or less, some secondary education, or secondary or greater educational level), persons per room, and access to improved sanitation (as defined by WHO/United Nations Children's Fund Joint Monitoring Program).17 Finally, the linearity of significant univariate associations with acute malnutrition were examined graphically by further categorizing MUACs into: < 11.5 (SAM), ≥ 11.5 to < 12.5 (moderate acute malnutrition), ≥ 12.5 to < 13.5, ≥ 13.5 to < 14.5 and ≥ 14.5. No similar descriptive analysis was done for stunting as the initial results were not significant. All analyzes were conducted using Stata 13.1 (Statacorp; College Station, TX).

AI Digest

Study Justification:

The study aimed to investigate the impact of childhood nutritional status on the prevalence and severity of acute diarrhea. This is important because children with malnutrition are at a higher risk of morbidity and mortality following a diarrheal episode. Understanding the relationship between nutritional status and diarrhea can help inform interventions and policies to improve child health outcomes.

Highlights:

– The study found that children with wasting (mid-upper arm circumference ≤ 125 mm) were more likely to present with severe dehydration and enteroaggregative Escherichia coli in their stool compared to non-wasted children.
– Stunting (height-for-age z score ≤ -2) was not associated with clinical severity or the presence of specific pathogens.
– Wasted children with diarrhea had more severe disease, which may be due to a delay in care-seeking or diminished immune response to infection.
– The study suggests that addressing social determinants and host risk factors associated with severe disease, rather than specific pathogens, may reduce the disparities in poor diarrhea-associated outcomes experienced by malnourished children.

Recommendations:

– Interventions should focus on improving the nutritional status of children to reduce the severity of diarrhea and its associated complications.
– Caregivers and healthcare providers should be educated about the importance of early care-seeking for children with malnutrition and diarrhea.
– Policies should prioritize addressing social determinants of health, such as poverty and access to improved sanitation, to improve child health outcomes.

Key Role Players:

– Researchers and scientists to conduct further studies and gather more evidence on the relationship between nutritional status and diarrhea.
– Healthcare providers to implement interventions and provide appropriate care for malnourished children with diarrhea.
– Policy makers to develop and implement policies that address social determinants of health and prioritize child nutrition and diarrhea prevention.

Cost Items for Planning Recommendations:

– Research funding for further studies and data collection.
– Training and capacity building for healthcare providers on managing malnourished children with diarrhea.
– Educational materials and campaigns for caregivers on the importance of nutrition and early care-seeking.
– Investments in improving access to improved sanitation facilities.
– Monitoring and evaluation systems to assess the impact of interventions and track progress in reducing malnutrition-related diarrhea.

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 cross-sectional study with a large sample size. The study conducted clinical and microbiological assessments and used statistical analysis to compare the prevalence and severity of diarrhea among children with and without malnutrition. The study also adjusted for potential confounders. To improve the evidence, it would be beneficial to include information about the methodology used for data collection and analysis, as well as any limitations of the study.

Abstract

This analysis used data collected from children under 5 years of age presenting with acute diarrhea to the outpatient and inpatient units at Kisii Provincial Hospital, Migori District Hospital, and Homa Bay District Hospital between November 2011 and June 2014. A description of this study has been published previously.13,14 Briefly, the parent study recruited children aged 6 months to 15 years presenting to the health facility with acute diarrhea (≥ 3 loose stools in the previous 24 hours and lasting less than 14 days). Eligible participants were excluded if they were not accompanied by a legal guardian or biological parent, if study staff were unable to collect a stool sample or rectal swab or if the primary caregiver refused human immunodeficiency virus (HIV) testing on behalf of the child. Written informed consent was obtained from the child’s caregiver. For this analysis, we included HIV-uninfected children 6 months to 5 years of age recruited at Homa Bay or Kisii hospitals. Migori Hospital patients were excluded as the low numbers recruited would be challenging to appropriately include in statistical models. The study was approved by the Kenya Medical Research Institute and University of Washington ethical review boards. At enrollment the primary caregiver completed a standardized clinical and sociodemographic questionnaire. All children were examined by clinical staff who recorded the presence of World Health Organization (WHO) Integrated Management of Childhood Illness (IMCI) danger signs (unable to drink or feed, vomiting everything, convulsions, lethargic, or unconscious) and hydration status (severe dehydration defined as at least two of the following: lethargic or unconscious, sunken eyes, not able to drink, reduced skin turgor). Weight, mid-upper arm circumference (MUAC), and height (or length) were measured and HAZs, weight-for-age z-scores (WAZ), and weight-for-height z-scores (WHZ) were calculated using WHO ANTHRO software.15 Z-scores of less than −7 or greater than 7 were deemed implausible and set to missing. All children were tested for HIV using antibody testing (Abbott Determine™ rapid test kit [Abbott Park, IL] and confirmed using Uni-Gold™ [Trinity Biotech, Bray, Ireland]) or HIV polymerase chain reaction (PCR) if under 18 months of age. Maternal HIV status was determined by antibody rapid testing or self-report. Malaria status was determined by a combination of rapid test (Paracheck Pf® Orchid Biomedical Services, Verna, Goa, India) and microscopy. Stool samples were collected in stool collection containers by caregivers or study staff. When a child was not able to produce stool, three rectal swabs were obtained. Fecal samples were collected prior to antibiotic administration, if indicated. Samples were received in the nearby U.S. Army Medical Research Directorate—Kenya (USAMD-K) Microbiology Hub in Kericho within 24 hours of collection after being placed in transport media (Cary–Blair for bacterial culture and 10% formalin for protozoal testing) and maintained at 2–8°C. Bacterial pathogens (E. coli, Shigella spp., Campylobacter spp., Salmonella spp.) were identified using traditional culture and serotyping methods confirmed using the MicroScan WalkAway 40 Plus (Beckman Coulter, Brea, CA) automated platform. Escherichia coli isolates were further tested for virulence factors using multiplex PCR and classified by pathotype: ETEC (heat labile or heat stable enterotoxin), EPEC (bundle forming pilus and, after March 2013, intimin), enteroaggregrative E.coli (EAEC) (aatA and, after March 2013, aaiC), enteroinvasive E.coli (invasion plasmid antigen H), or enterohemmorhagic E.coli (Shiga toxin 1,2 and variant). Protozoal infections were identified from whole stool samples using microscopy after stool concentration using Mini Parasep® Solvent Free concentration kit (DiaSys, Berkshire, England). No viral testing was performed. Analyses were conducted to examine whether children with acute malnutrition (wasting, MUAC < 12.5 cm) or chronic malnutrition (stunted HAZ < −2) had a higher prevalence of detectable enteric pathogens at presentation or presented with more severe disease (defined as the presence of at least one IMCI danger sign and/or severe dehydration). WHZ was not used to define acute malnutrition because it is influenced by fluid status and children with diarrhea often have some degree of dehydration. All prevalences were compared using log-binomial regression and associated χ2 tests.16 Pathogens and danger signs that were significantly associated with nutritional status in univariate regression at an alpha of 0.05 were further assessed in multivariable models. Potential confounders were evaluated for inclusion in each model in a stepwise manner and maintained in the model if the prevalence ratio changed by more than 10%. The following potential confounding variables were considered: age, gender, hospital site, currently receiving any breast milk (yes/no), maternal HIV status, family income (dichotomized at above or below 5,000 Kenyan Shillings), caregiver education (primary education or less, some secondary education, or secondary or greater educational level), persons per room, and access to improved sanitation (as defined by WHO/United Nations Children's Fund Joint Monitoring Program).17 Finally, the linearity of significant univariate associations with acute malnutrition were examined graphically by further categorizing MUACs into: < 11.5 (SAM), ≥ 11.5 to < 12.5 (moderate acute malnutrition), ≥ 12.5 to < 13.5, ≥ 13.5 to < 14.5 and ≥ 14.5. No similar descriptive analysis was done for stunting as the initial results were not significant. All analyzes were conducted using Stata 13.1 (Statacorp; College Station, TX).

Materials

https://efashare.b-cdn.net/materials/6e514f1ae6adda8523981b26d6f0c9af4799721d13b8ac824458f8cad519c343/tpmd170139.SD1.pdf

Innovations

Based on the provided information, it is not clear what specific innovations or recommendations are being sought to improve access to maternal health. The information provided describes a study conducted on children with acute diarrhea and their nutritional status. If you have any specific questions or need assistance with a different topic related to maternal health, please provide more details and I will be happy to help.

AI Innovations Description

Based on the provided description, the recommendation to improve access to maternal health is to address and combat social determinants and host risk factors associated with severe disease, rather than specific pathogens. This approach may help reduce the disparities in poor diarrhea-associated outcomes experienced by malnourished children. Additionally, efforts should be made to promote early care-seeking and ensure timely access to healthcare services for malnourished children with diarrhea. This can be achieved through community education and awareness programs, improving healthcare infrastructure and availability of resources, and strengthening the overall healthcare system.

AI Innovations Methodology

The analysis described in the provided text aimed to investigate the impact of childhood nutritional status on the prevalence and severity of acute diarrhea in Kenyan children aged 6-59 months. The study collected data from children presenting with acute diarrhea at three hospitals in Kenya between November 2011 and June 2014.

The methodology used in this study involved the following steps:

1. Study population: The study included HIV-uninfected children aged 6 months to 5 years who presented with acute diarrhea at Homa Bay or Kisii hospitals. Children from Migori Hospital were excluded due to low recruitment numbers.

2. Data collection: At enrollment, the primary caregiver completed a standardized clinical and sociodemographic questionnaire. Clinical staff conducted examinations and recorded the presence of Integrated Management of Childhood Illness (IMCI) danger signs and hydration status. Anthropometric measurements (weight, mid-upper arm circumference, and height) were taken, and z-scores were calculated using WHO ANTHRO software. Stool samples were collected for pathogen detection.

3. Laboratory analysis: Stool samples were tested for bacterial pathogens (E. coli, Shigella spp., Campylobacter spp., Salmonella spp.) using traditional culture and serotyping methods. Escherichia coli isolates were further tested for virulence factors using multiplex PCR. Protozoal infections were identified using microscopy.

4. Statistical analysis: Log-binomial regression and chi-square tests were used to compare the prevalence of pathogens and clinical features between children with and without acute malnutrition (wasting) or chronic malnutrition (stunting). Multivariable models were used to assess the associations between nutritional status and pathogen prevalence or disease severity, adjusting for potential confounders.

5. Data interpretation: The results were analyzed to determine whether children with acute malnutrition had a higher prevalence of enteric pathogens at presentation or presented with more severe disease. The significance of associations was assessed, and potential confounding variables were considered.

6. Reporting: The findings were reported in a scientific publication, providing insights into the impact of childhood nutritional status on the severity and prevalence of acute diarrhea in Kenyan children.

To simulate the impact of recommendations on improving access to maternal health, a similar methodology could be applied:

1. Define the study population: Identify the target population for the study, such as pregnant women or women of reproductive age.

2. Data collection: Collect relevant data on maternal health, including demographic information, access to healthcare services, and health outcomes. This could involve surveys, interviews, or medical record reviews.

3. Analyze the data: Use appropriate statistical methods to analyze the data and identify factors associated with poor maternal health outcomes or limited access to healthcare services. This could involve regression analysis, chi-square tests, or other relevant statistical techniques.

4. Identify potential recommendations: Based on the analysis, identify potential recommendations to improve access to maternal health. These could include interventions to increase healthcare facility availability, improve transportation infrastructure, enhance health education programs, or address social determinants of health.

5. Simulate the impact: Use modeling techniques to simulate the potential impact of the identified recommendations on improving access to maternal health. This could involve creating scenarios and estimating the potential changes in health outcomes or access indicators based on the implementation of the recommendations.

6. Evaluate the results: Assess the simulated impact of the recommendations and evaluate their feasibility, cost-effectiveness, and potential barriers to implementation. This could involve conducting sensitivity analyses and consulting with relevant stakeholders.

7. Report and disseminate findings: Communicate the findings of the simulation study, including the potential impact of the recommendations on improving access to maternal health. This could be done through scientific publications, policy briefs, or presentations to relevant stakeholders.

By following a similar methodology, researchers and policymakers can gain insights into the potential impact of recommendations on improving access to maternal health and make informed decisions to address this important issue.

Authors & Co-Authors

Statistics:

Citations: 16

Authors: 10

Identifiers:

DOI: 10.4269/ajtmh.17-0139

ISSN: 00029637

Research Areas:

Disparities, Environmental, Food Security, Health System and Policy, Infectious Diseases, Maternal Access, Maternal and Child Health, Quality of Care, Social Determinants

Study Countries:

Kenya

Study Design:

Cross Sectional Study

Study Approach:

Quantitative