Campylobacter Colonization, Environmental Enteric Dysfunction, Stunting, and Associated Risk Factors Among Young Children in Rural Ethiopia: A Cross-Sectional Study From the Campylobacter Genomics and Environmental Enteric Dysfunction (CAGED) Project

Livestock farming provides a possible mechanism by which smallholder farmers can meet their household need for animal source foods (ASF), which may reduce the risk of stunting. However, direct/indirect contacts with domestic animals may increase colonization by Campylobacter spp., which has been associated with Environmental Enteric Dysfunction (EED) and stunting. A cross-sectional study involving 102 randomly selected children between 12 and 16 months of age was conducted in rural eastern Ethiopia to establish prevalence rates of Campylobacter colonization, EED, and stunting, and evaluate potential risk factors. Data were collected between September and December 2018. The prevalence of EED and stunting was 50% (95% CI: 40–60%) and 41% (95% CI: 32–51%), respectively. Among enrolled children, 56% had consumed some ASF in the previous 24 h; 47% had diarrhea and 50% had fever in the past 15 days. 54, 63, 71 or 43% of households owned at least one chicken, cow/bull, goat, or sheep; 54 (53%) households kept chickens indoors overnight and only half of these confined the animals. Sanitation was poor, with high levels of unimproved latrines and open defecation. Most households had access to an improved source of drinking water. The prevalence of Campylobacter colonization was 50% (95% CI: 41–60%) by PCR. In addition to the thermotolerant species Campylobacter jejuni, Campylobacter coli and Campylobacter upsaliensis, non-thermotolerant species related to Campylobacter hyointestinalis and Campylobacter fetus were frequently detected by Meta-total RNA sequencing (MeTRS). Current breastfeeding and ASF consumption increased the odds of Campylobacter detection by PCR, while improved drinking water supply decreased the odds of EED. No risk factors were significantly associated with stunting. Further studies are necessary to better understand reservoirs and transmission pathways of Campylobacter spp. and their potential impact on child health. A community-based cross-sectional study, including a questionnaire-based surveillance of the households and collection of child growth data, child urine, and fecal samples were performed in the Haramaya woreda (district), East Hararghe Zone, Oromia Region, Ethiopia. Beginning in 2018, Haramaya University (HU) initiated a full household enumeration of 12 kebeles (wards) within Haramaya woreda using methods developed for the Kersa Health and Demographic Surveillance System (26). For this cross-sectional study, five out of the 12 kebeles were selected in a way to capture the spatial heterogeneities in the landscape (e.g., land use, land cover, altitude, agricultural practices) that could influence risk factors contributing to health outcomes. Eligibility criteria of this study were designed to enroll children receiving traditional maternal care and without underlying health conditions that might affect the primary study outcomes. Previous studies (MAL-ED) have indicated that the prevalence of Campylobacter spp. in children in low- and middle-income countries (LMIC) increases linearly in the first year of life and then reaches a steady state or slow decline with peak levels occurring around 12 months of age (15). A child was included in the study if he/she was 11–13 months of age when consent was given, and if the child’s mother was the caretaker. The child was excluded from the study if he/she presented visible congenital abnormality or had serious medical illnesses, or the child or his/her mother required extended stay in hospital after birth. Households with at least three chickens within the homestead (defined as the small collection of households that are physically connected to one another), willing to participate and conform to the requirements of the study were included. Families not residing in Haramaya woreda for at least 3 months, currently participating in another study on animal husbandry, or with a mother who did not live in Haramaya woreda when the child was born were excluded. The sample size of this study considered estimation of the three primary outcomes: Campylobacter colonization, EED, and stunting. Based on a binomial distribution, a sample size of 100 for the whole study population allowed estimation of a 50% prevalence with precision of 10 at 95% confidence (R function binom:: binom.confint). While adjusting for population weight of kebeles, 102 children (one child from each household) were randomly selected from the sampling frame of the selected five kebeles. Field work started on October 16, 2018 and continued for 10 weeks until December 21, 2018. The enrolled children and their mothers were invited to come to a local health post or administration office for anthropometric measurements, administration of a sugar solution, and collection of a urine sample for each child for later measurement of lactulose excretion (a marker for EED in urine), as well as completion of interviews and providing a fecal sample for each child. Questionnaires were developed in collaboration with the Haramaya University (HU) field team using validated indices whenever possible, such as minimum dietary diversity of infant and young children (MDD-IYC). In consultation with social scientists and field workers, the study questionnaire was finalized so that it was culturally appropriate and locally adapted. In the local language (Afan Oromo), bilingual data collectors collected information on demographics, livelihoods, wealth, animal ownership, animal management and disease, water, sanitation and hygiene, health, and nutrition. Study data were collected and managed using REDCap electronic data capture tools hosted at the University of Florida Clinical and Translational Science Institute (27). During the implementation of household surveillance, stool samples from the selected children were also collected aseptically in a sterile plastic sheet for EED and PCR analyses, and meta-total RNA sequencing (MeTRS, a culture-independent sequencing method that profiles the presence and quantity of RNA transcripts in a sample). Samples were flash-frozen in the field using liquid nitrogen and stored at −80°C until further use. Genomic DNA and RNA were extracted for conventional PCR and MeTRS, respectively (25). Details of laboratory procedures on PCR and MeTRS were described in Terefe et al. (25). For the dual sugar absorption test, an oral solution consisting of 200 mg L-rhamnose and 1000 mg lactulose in 10 mL sterile water was prepared as previously described (28). Study personnel administered the entire solution to each child over a period of 5 min. A urine bag was then placed on the child 30 min after consuming the solution and all urine collected over the subsequent 60 min was returned to the data collector. Analysis of lactulose and rhamnose was conducted according to a previously described procedure (29, 30). In stool samples, myeloperoxidase (MPO) was measured using a commercially available enzyme-linked immunosorbent assay (MPO RUO, Alpco, Salem, NH). One child had severe diarrhea and difficulty in producing feces, we were unable to collect a fecal sample from him; another child produced a small amount of feces that was only sufficient for PCR testing. The samples sizes for PCR, MeTRS, and MPO analyses were therefore 101, 100, and 100, respectively. Threshold cutoffs for moderate and severe EED based on the dual sugar absorption test and fecal MPO were defined following previously described methods (31, 32). As reported by Ordiz et al. (31), urinary excretion of lactulose and rhamnose were highly correlated as illustrated in Supplementary Figure 1, and following these authors, we adopted the percentage of lactulose excretion as a biomarker for gut permeability associated with EED. Cutoff values for the percentage of lactulose (%L) were as suggested by Agapova et al. (33): 0.2 < %L ≤ 0.45% for moderate EED, and %L > 0.45 for severe EED. Following Kosek et al. (32), we defined a threshold for fecal MPO of 2,000 ng/ml for gut inflammation and the third quartile of the observed data (11,000 ng/ml in our cohort) as a threshold for severe inflammation. The child’s weight, recumbent length, and Mid-Upper Arm Circumference (MUAC) measurements were collected by trained caregivers using Seca 334 baby scales, Seca 417 length boards (Itin Scale Co., Inc., Brooklyn, NY), and MUAC tape precise to 0.01 kg, 0.1, and 0.2 cm, respectively. Length measurements were taken three times. The average length was calculated by taking the arithmetic mean of the data after outlier removal as described in Supplementary Appendix 1. Length-for-age, weight-for-age, and weight-for-length Z scores (LAZ, WAZ, and WLZ, respectively) were calculated according to WHO Child Growth Standards using R package anthro. Severe acute malnutrition was defined according to Ethiopian clinical standards (MUAC <110 mm and length >65 cm or a WLZ ≤ −3) (34). A total of 12 children with one (or more) of the following medical condition(s) were referred to a healthcare facility, including four cases of dehydration, five cases of diarrhea and fever, and six cases of diarrhea. Two children were referred to a health post for additional follow-up for severe acute malnutrition. Primary outcome variables of interest were Campylobacter colonization (by PCR), EED, and stunting. Descriptive analysis was undertaken to explore background features of the study population. 95% binomial proportion confidence intervals for prevalence were based on Wilson score. Explanatory variables potentially associated with the outcome variables were selected based on a priori knowledge (1–4, 7, 8, 10, 12, 13, 16). All data analyses were performed in the statistical language R version 3.5.1 (35). Composite variables were generated to assist in analyzing the sociodemographic data. We created Water, Sanitation, and Hygiene (WASH) ladder variables (i.e., drinking water, sanitation, and hygiene ladders) based on the Joint Monitoring Program (JMP) by WHO and UNICEF (22, 36). Tropical livestock unit (TLU), a composite metric for quantifying all farming animals in a household, was calculated following published literature (37). Bivariate and multivariate analyses were conducted to explore associations between the three outcome variables and potential explanatory variables using unadjusted and adjusted logistic regression models [controlling for child’s age (in days), sex, and kebele of residence]. To strengthen the robustness of the models, continuous [i.e., child’s and mother’s age, TLU, household wealth (asset and income)] and ordinal explanatory variables were, respectively dichotomized by medians or generally accepted cut-offs (i.e., minimum dietary diversity score of 5). We established multiple exposure models by including the three confounders (child’s age group, sex, and kebele of residence) and candidate variables with p-values < 0.20 from the adjusted single exposure models (Supplementary Tables 4–6), and backward stepwise selections were conducted to sort out the significant explanatory variables (38). Given the small sample size, all p-values and 95% confidence intervals (CIs) were estimated by likelihood-ratio (LR) test, and we did not include interaction between the explanatory variables in the models. Observations with missing values were excluded from the analyses.