Key Study Measures

Household Water Quality: Escherichia coli levels are a highly reliable of measures of fecal contamination of water sources and are an indicator of inadequate sanitation (Edberg et al. 2000). Household water samples were tested for the presence and most probable number (MPN) of E. coli and total coliforms using the culture-based IDEXX Colilert test (IDEXX Laboratories, Inc. Westbrook, Maine) at the Galápagos Science Center (Cochran 1950; Eckner 1998).

Reagents were added to each sample and sealed in the IDEXX counting tray. After incubation, the sample was fluoresced to obtain the upper and lower bacterial concentrations using the Quanti-tray 2000’s most probable number methodology (IDEXX Laboratories, Inc. Westbrook, MA). Based on the WHO’s recommendations, household water samples were categorized based on potential health risk (Havelaar et al. 2001; WHO 2011b) and were used as the primary pathogenic predictor variable in Pilot Aim 2 and Dissertation Papers 2 and 3.

Blood Immune Biomarkers: Three rounds of blood spots were assayed for CRP and

EndoCAb levels using double sandwich enzyme-linked immunosorbent assay (ELISA)

technique at the Galápagos Science Center’s microbiology laboratory. Eluted blood spots were analyzed using Quantikine’s Human High Sensitivity C-Reactive Protein ELISA (R&D Systems,

Inc. Minneapolis, MN) (McDade et al. 2004) and Hycult’s EndoCAb IgG ELISA kit (Hycult Biotech Inc. Plymouth, PA) (Barclay 1995). CRP cut-points for low (<1 mg/L), moderate (1 to 3 mg/L) and elevated inflammation (3 to 10 mg/L) are taken from clinical practice (Pearson et al. 2003; Ridker 2003). Children with acute levels (>10 mg/L) are considered to have infections. Since there are no standardized cut-points for endotoxemia using EndoCAb IgG levels, the 75th percentile expressed as median unit (MU) per mL was used as the reference point for high microbial translocation (Barclay 1995). These blood immune function measures were examined as indicators of immunodysregulation for both the Pilot and Dissertation Aims, along with the primary outcomes in all three Dissertation Papers.

Iron Status: Hemoglobin status indicating iron deficiency was determined using the WHO age-specific cut-points for children women (WHO 2011a). Iron deficiency was used as a dietary predictor of nutritional deficiency for Pilot Aim 2.

Gut Microbial Composition: DNA was isolated using protocols from the Qiagen BioRobot Universal (Qiagen, Valencia, CA) and was quantified using Quant-iTTM PicoGreen® dsRNA Reagent (Molecular Probes, Life Technologies division of Thermo Fisher Scientific, Waltham, MA). A Roche GS FLX Titanium instrument was used to perform 16S rDNA bacterial amplicon pyrosequencing (Microbiome Core Facility, UNC). The QIIME pipeline (Caporaso et al. 2010) was used to analyze sequencing data and assign operational taxonomic units (OTUs). Gut health was assessed by exploring each taxonomic level to identify relevant microbial compositions related to pathogenic and obesogenic risk factors, as well as influence on immune function in both Pilot Aims and Dissertation Papers. We chose to analyze microbial

being too extensive, and is the primary outcome used in Paper 3- Gut Microbiota Mediate Immunostimulation.

Urine Immune Biomarker: Urinalysis was performed on the urine samples at the Galápagos Science Center using URS-11 reagent strips (Cortez Diagnostics, Inc., Calabasas, CA) to determine levels of leukocytes, nitrates and blood indicative of urinary tract infections. These urinary immune function measures were used to complement blood immune function measures for outcomes and to adjust for infection in the Pilot and Dissertation Aims.

Adiposity and Growth: Body mass index (BMI) was calculated using

mass(kg)/height(m)². Sex- and age- specific z-scores were calculated using the WHO reference data and cut-points for comparison across sex and age (de Onis and Lobstein 2010; de Onis et al. 2006; WHO 2006). Height-for-age z-scores were used to assess linear growth restrictions. BMI- for-age, skinfold and waist circumference z-scores were used to assess adiposity. These variables were examined as the main adiposity and linear growth outcomes for Pilot Aims and Dissertation Aim 2. Obesity was defined by a BMI z-score over 2 and used to adjust models in Papers 2 and 3, and used as the sensitivity and specificity predictor in Paper 1- Measuring Chronic Low-Grade Inflammation.

Blood Pressure: Diastolic and systolic blood pressure was determined for each mother and risk of hypertension was evaluated using American Heart Association’s cut-points (AHA 2017). These measures were explored to determine chronic disease risk associated with obesogenic factors among women in the Pilot Aims.

Household Sanitation: Using data from mothers’ interviews, household sanitation measures were created, including housing type, drinking water source, household water use,

water treatment, bathroom type, trash disposal and the presence of domesticated animals near the household. These variables were explored and used as pathogenic predictors in Pilot Aim 2.

Household Socio-Demographics: Data from mothers’ interviews were used to create household socio-demographics variables, including parental marital status, family size, mother’s education, parental employment, home ownership, land ownership elsewhere on the island, household assets, co-residence of grandparents, and smoking in the household. These measures were used as social predictors in Pilot Aim 2.

Child’s Demographics: Age, sex, ethnicity, birth weight, delivery mode, birth place, breastfeeding practices, formula use, introduction to solid foods, and school attendance were created from mothers’ interviews and used as the demographic predictors in Pilot Aim 2. Age

and sex variables were used to adjust all aims and papers.

Child’s Hygiene: Data from mothers’ interviews were used to create hygiene variables, including the toilet use, diaper use, bathing water source, oral hygiene practices, hand washing practices, frequency of swimming in the ocean, last deworming and interactions with animals. These variables were used as pathogenic predictors in Pilot Aim 2.

Infectious Symptoms: Infectious symptom measures were created using data from the two one-week symptom histories taken during visits one and three. The presence of diarrhea, fever, vomiting, cough, cold, urinary tract infection, skin rash, allergies and asthma were used as pathogenic predictors in Pilot Aim 2. If mothers reported that a child experienced diarrhea, vomiting and fever during either visits one or three, the child was considered to have infectious symptoms used to adjust and stratify models in Papers 2 and 3.

Dietary Composition: Data from food frequency questionnaires administered during field season two were used to calculate reported average consumption of high-fiber foods, sugary

drinks, dairy products, fried foods and other local unhealthy food items. Consumption was categorized into high and low quantities and used as the main dietary predictor for Pilot Aim 2. Alternative to dietary intake, food preferences for field season two and household staple food items for the entire sample were explored as dietary predictors.