Determinants of Campylobacter infection and association with growth and enteric inflammation in children under 2 years of age in low-resource settings

listen audio

Study Justification:
– Campylobacter species infections have been associated with malnutrition and intestinal inflammation in children in low-resource settings.
– It is unclear whether this association is specific to Campylobacter jejuni/coli.
– This study aims to assess the association between all Campylobacter species infections and Campylobacter jejuni/coli infections on growth and enteric inflammation in children aged 1-24 months.
Highlights:
– Data from 1715 children followed from birth until 24 months of age in the MAL-ED birth cohort study were analyzed.
– Incidence rates of Campylobacter jejuni/coli and Campylobacter species infections were calculated.
– Factors associated with Campylobacter jejuni/coli infection were identified, including female sex of child, shorter duration of exclusive breastfeeding, lower maternal age, mother having less than 3 living children, maternal educational level of

Campylobacter species infections have been associated with malnutrition and intestinal inflammation among children in low-resource settings. However, it remains unclear whether that association is specific to Campylobacter jejuni/coli. The aim of this study was to assess the association between both all Campylobacter species infections and Campylobacter jejuni/coli infections on growth and enteric inflammation in children aged 1–24 months. We analyzed data from 1715 children followed from birth until 24 months of age in the MAL-ED birth cohort study, including detection of Campylobacter species by enzyme immunoassay and Campylobacter jejuni/coli by quantitative PCR in stool samples. Myeloperoxidase (MPO) concentration in stool, used as a quantitative index of enteric inflammation, was measured. The incidence rate per 100 child-months of infections with Campylobacter jejuni/coli and Campylobacter species during 1–24 month follow up were 17.7 and 29.6 respectively. Female sex of child, shorter duration of exclusive breastfeeding, lower maternal age, mother having less than 3 living children, maternal educational level of <6 years, lack of routine treatment of drinking water, and unimproved sanitation were associated with Campylobacter jejuni/coli infection. The cumulative burden of both Campylobacter jejuni/coli infections and Campylobacter species were associated with poor growth and increased intestinal inflammation.

The MAL-ED study design and methodology have been previously described19. Briefly, children were enrolled November, 2009 to February, 2012 from the community within 17 days of birth at eight locations: Dhaka, Bangladesh; Vellore, India; Bhaktapur, Nepal; Naushero Feroze, Pakistan; Venda, South Africa; Haydom, Tanzania; Fortaleza, Brazil; and Loreto, Peru. Children were included if the maternal age was 16 years or older, their family intended to remain in the study area for at least 6 months from enrolment, they were from a singleton pregnancy, and they had no other siblings enrolled in the study. Children with a birthweight or enrolment weight of less than 1500 gm and children diagnosed with congenital disease or severe neonatal disease were excluded. The study was approved by the Research Review Committee and the Ethical Review Committee of icddr,b (Bangladesh), the Local Institutional Review Board at the Federal Universisty of Ceará and the national IRB Conselho Nacional de Ética em Pesquisa (Brazil), the Christian Medical College Institutional Review Board and the Emory University Institutional Review Board (India), the Nepal Health Research Council and Walter Reed Institute of Research (Nepal), the Ethics Committee of Asociacion Benefica PRISMA, the Regional Health Directorate of Loreto and the IRB of Johns Hopkins Bloomberg School of Public Health (Peru), the Ethical Review Committee of Aga Khan University (Pakistan), the Institutional Review Boards at the University of Venda (South Africa), the National Institute for Medical Research (Tanzania), and the Institutional Review Board of the University of Virginia (UAS). Written informed consent was obtained from the parents or legal guardian of every child19,22. All methods were performed in accordance with the relevant guidelines and regulations. Household demographics, presence of siblings, maternal characteristics, and other data on the child’s birth and anthropometry were obtained at enrollment19. The socioeconomic status (SES) of families was assessed at 6, 12, 18, and 24 months. SES score, the water/sanitation, assets, maternal education and income (WAMI) index was developed using composite indicators including the variables such as access to improved water and sanitation, eight selected assets, maternal education, and household income23. Improved water and sanitation were defined following World Health Organization guidelines24. Treatment of drinking water was defined as filtering, boiling, or adding bleach1. Anthropometric measurements and vaccination history were collected monthly. Details of illness and child feeding practices were collected during twice-weekly household visits25. Stool samples were collected monthly and were preserved, transported, and processed at all sites using harmonized protocols26. Child anthropometry was measured using standard scales (seca gmbh & co. kg., Hamburg, Germany). Length-for-age Z score (LAZ) was calculated through the use of the 2006 WHO standards for children27. The Z-score scale, calculated as (observed value – average value of the reference population)/standard deviation value of reference population, is linear and therefore a fixed interval of Z-scores has a fixed length difference in cm for all children of the same age. Z-scores are also sex-independent, thus permitting the evaluation of children’s growth status by combining sex and age groups28. Stool samples were collected without fixative by field workers and raw stool aliquots were kept at −80 °C before nucleic acid extraction. All lab testing was done at the site specific laboratories11,14. Stool samples were assayed for Campylobacter species by enzyme immunoassay (ProSpecT, Remel, Lenexa, KS, USA). In addition, myeloperoxidase (MPO) (Alpco, Salem, New Hampshire) was measured using commercially-available Enzyme Linked Immunosorbent Assay (ELISA) kits following the instructions of the manufacturers1,8. Campylobacter jejuni/coli were detected in the stool samples by quantitative PCR targeting the cadF gene using the TaqMan Array Card (TAC) platform, a compartmentalized probe-based real-time PCR assays for detecting enteropathogens in fecal samples, as previously described22,29. The analytic cutoff of each pathogen was a quantification cycle (Cq) of 35; thus, a Cq < 35 was considered positive20,30. All statistical tests were performed in STATA 14 (Stata Corporation, College Station, TX). Campylobacter burden was defined as the number of pathogens detected divided by the number of stools collected and was scaled divided by (10th vs 90th percentile). Descriptive statistics such as proportion, mean and standard deviation for symmetric data, and median with inter‐quartile range (IQR) for asymmetric quantitative variables were used to summarize the data. Chi-square and proportion test was used to see the association between two categorical variables and t-test was used to see the mean difference between two groups for symmetric distribution. Cumulative incidence of Campylobacter jejuni/coli and Campylobacter species was defined as the proportion of subjects who were infected at least once during the study period. Incidence rates and risk factors associated with Campylobacter detection in surveillance stool samples were calculated using negative binomial regression models due to over dispersion. In the final multiple negative binomial regression model, the following variables were considered for inclusion using stepwise forward selection: child sex, duration of exclusive breastfeeding in months, enrollment weight for age z-score, maternal age in years, maternal education greater than or equal to 6 years, mother having less than 3 living children, routine treatment of drinking water, improved sanitation, and household ownership of cattle/poultry. The MPO values were log‐transformed before the analysis. We excluded children from the Pakistan site for growth analysis, owing to bias noted in a subset of length measurements at this site. Seasonality was calculated via the terms sin(2mπ/12) + cos(2mπ/12), where “m” is the calendar month1,31. Associations between Campylobacter infection and inflammation was estimated using generalized estimating equations to fit regression models after adjusting for seasonality, sex, age, water/sanitation, assets, maternal education, and income (WAMI) index; enrollment length-for-age; maternal height; poultry/cattle in house, some alternative pathogens which were significantly associated with log(MPO) such as enteroaggregative E. coli (EAEC), heat-labile enterotoxin-producing E. coli (LT-ETEC), heat-stable enterotoxin-producing E. coli (ST-ETEC), Shigella/enteroinvasive E. coli (Shigella/EIEC), and site for overall estimate and age in month as time variable32. The Gaussian family with identity link was used for the continuous outcome of log(MPO). To access and compare the associations of Campylobacter jejuni/coli and Campylobacter species infection burden on growth at 24 months of age, we used multi-variable linear regression after adjusting for site and the necessary covariates.

N/A

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

1. Telemedicine: Implementing telemedicine services can improve access to maternal health by allowing pregnant women in low-resource settings to consult with healthcare professionals remotely. This can help address barriers such as distance and transportation.

2. Mobile health (mHealth) applications: Developing mobile applications that provide information and resources on maternal health can empower women to take control of their own health. These apps can provide guidance on prenatal care, nutrition, and postpartum care, among other topics.

3. Community health workers: Training and deploying community health workers can help improve access to maternal health services in low-resource settings. These workers can provide education, support, and referrals to pregnant women, ensuring they receive the care they need.

4. Maternal health clinics: Establishing dedicated maternal health clinics in underserved areas can provide comprehensive care for pregnant women. These clinics can offer prenatal check-ups, vaccinations, and counseling services, all in one location.

5. Mobile clinics: Utilizing mobile clinics can bring maternal health services directly to remote communities. These clinics can travel to different locations, providing prenatal care, screenings, and vaccinations to pregnant women who may not have access to a nearby healthcare facility.

6. Health education programs: Implementing health education programs that specifically target maternal health can help raise awareness and improve knowledge among pregnant women. These programs can cover topics such as nutrition, hygiene, and the importance of prenatal care.

7. Financial incentives: Providing financial incentives, such as cash transfers or vouchers, to pregnant women in low-resource settings can encourage them to seek and utilize maternal health services. This can help overcome financial barriers that may prevent women from accessing care.

8. Partnerships with local organizations: Collaborating with local organizations, such as non-governmental organizations (NGOs) or community-based groups, can help improve access to maternal health services. These partnerships can leverage existing networks and resources to reach pregnant women in underserved areas.

9. Maternal health awareness campaigns: Conducting targeted awareness campaigns can help educate communities about the importance of maternal health and encourage women to seek care. These campaigns can use various mediums, such as radio, television, and community events, to reach a wide audience.

10. Strengthening healthcare infrastructure: Investing in and improving healthcare infrastructure in low-resource settings is crucial for ensuring access to maternal health services. This includes building and equipping healthcare facilities, training healthcare professionals, and ensuring the availability of essential supplies and medications.
AI Innovations Description
Based on the provided description, the recommendation to improve access to maternal health would be to conduct further research and studies to determine the specific interventions and strategies that can effectively reduce the incidence of Campylobacter infections in low-resource settings. This can include:

1. Developing targeted interventions: Based on the identified risk factors associated with Campylobacter infections, such as lack of routine treatment of drinking water and unimproved sanitation, interventions can be developed to improve access to clean and safe drinking water and sanitation facilities in these settings.

2. Promoting exclusive breastfeeding: The study found that shorter duration of exclusive breastfeeding was associated with Campylobacter infections. Therefore, promoting and supporting exclusive breastfeeding practices can be an effective strategy to reduce the risk of infections in children.

3. Enhancing maternal education and awareness: The study identified lower maternal education as a risk factor for Campylobacter infections. Therefore, efforts should be made to improve maternal education and awareness about hygiene practices, safe food handling, and prevention of infections.

4. Strengthening healthcare systems: Improving access to quality healthcare services, including antenatal care, skilled birth attendance, and postnatal care, can contribute to early detection and management of maternal and child health issues, including Campylobacter infections.

5. Implementing vaccination programs: If specific Campylobacter vaccines become available in the future, implementing vaccination programs targeting high-risk populations, such as pregnant women and young children, can help prevent infections and reduce the burden of Campylobacter-related complications.

It is important to note that these recommendations are based on the information provided and further research and evaluation would be needed to determine their effectiveness and feasibility in specific low-resource settings.
AI Innovations Methodology
To improve access to maternal health, here are some potential recommendations:

1. Mobile Health (mHealth) Solutions: Develop and implement mobile health applications that provide pregnant women with access to information, resources, and support. These apps can provide prenatal care reminders, educational materials, appointment scheduling, and telemedicine consultations.

2. Community Health Workers: Train and deploy community health workers to provide maternal health services in remote or underserved areas. These workers can conduct prenatal visits, provide health education, and facilitate referrals to healthcare facilities.

3. Telemedicine: Establish telemedicine programs that allow pregnant women to consult with healthcare providers remotely. This can help overcome geographical barriers and provide timely access to medical advice and support.

4. Transportation Support: Improve transportation infrastructure and provide transportation subsidies or vouchers for pregnant women to ensure they can easily access healthcare facilities for prenatal care, delivery, and postnatal care.

5. Maternal Health Clinics: Establish dedicated maternal health clinics in underserved areas, staffed with skilled healthcare professionals who can provide comprehensive prenatal, delivery, and postnatal care.

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

1. Define the target population: Identify the specific population that will benefit from the recommendations, such as pregnant women in low-resource settings.

2. Collect baseline data: Gather data on the current state of access to maternal health services in the target population. This can include information on healthcare facilities, transportation infrastructure, availability of healthcare providers, and utilization of maternal health services.

3. Develop a simulation model: Create a simulation model that incorporates the recommendations and their potential impact on improving access to maternal health. This model should consider factors such as the number of mobile health app users, the number of community health workers deployed, the utilization of telemedicine services, the availability of transportation support, and the establishment of maternal health clinics.

4. Input data and parameters: Input the baseline data and parameters into the simulation model. This includes information on the target population, the implementation of the recommendations, and any assumptions or constraints.

5. Run simulations: Run multiple simulations using different scenarios and assumptions to assess the potential impact of the recommendations on improving access to maternal health. This can include variations in the number of mobile health app users, the coverage of community health workers, the utilization of telemedicine services, and the availability of transportation support.

6. Analyze results: Analyze the simulation results to determine the potential impact of the recommendations on improving access to maternal health. This can include metrics such as the increase in the number of pregnant women accessing prenatal care, the reduction in travel time to healthcare facilities, and the improvement in health outcomes for mothers and infants.

7. Refine and iterate: Based on the simulation results, refine the recommendations and the simulation model as needed. Iterate the process to further optimize the impact of the recommendations on improving access to maternal health.

By using this methodology, stakeholders can assess the potential benefits and challenges of implementing these recommendations and make informed decisions on how to improve access to maternal health in low-resource settings.

Partilhar isto:
Facebook
Twitter
LinkedIn
WhatsApp
Email