Incidence of EAEC.

<p>Cumulative incidence of first EAEC detection in A) surveillance and diarrheal stools at all sites and B) surveillance stools by site among 2,092 children with at least one stool sample in the MAL-ED birth cohort. BGD–Dhaka, Bangladesh; BRF–Fortaleza, Brazil; INV–Vellore, India; NEB–Bhaktapur, Nepal; PEL–Loreto, Peru; PKN–Naushahro Feroze, Pakistan; SAV–Venda, South Africa; TZH–Haydom, Tanzania.</p

Effects of EAEC detection in monthly surveillance stools on weight (WAZ) and length (LAZ) attainment at 2 years of age among 1,727 children in the MAL-ED cohort with anthropometric measurements at 2 years.

<p>Effects of EAEC detection in monthly surveillance stools on weight (WAZ) and length (LAZ) attainment at 2 years of age among 1,727 children in the MAL-ED cohort with anthropometric measurements at 2 years.</p

Long-term growth.

<p>Adjusted site-specific association between EAEC detection in monthly surveillance stools and A: weight-for-age z-score (WAZ) and B: length-for-age z-score (LAZ) at two years of age among 1,727 children in the MAL-ED cohort who had anthropometric measurements at two years. Estimates are the z-score difference associated with a high frequency of EAEC detection compared to a low frequency of EAEC detection. Definitions for high and low frequency are based on the 10^th and 90^th percentiles of stool positivity in the cohort. Low: ≤11% of surveillance stools positive for EAEC; high: ≥50% of surveillance stools positive for EAEC.</p

Associations between EAEC detection and markers of inflammation and gut permeability in surveillance and diarrheal stools among 2,076 children in the MAL-ED cohort with at least one biomarker measurement.

<p>Associations between EAEC detection and markers of inflammation and gut permeability in surveillance and diarrheal stools among 2,076 children in the MAL-ED cohort with at least one biomarker measurement.</p

Risk factors for EAEC detection in monthly surveillance stools among 2,091 children in the MAL-ED cohort with at least one surveillance stool.

<p>Risk factors for EAEC detection in monthly surveillance stools among 2,091 children in the MAL-ED cohort with at least one surveillance stool.</p

Short-term growth.

<p>Adjusted site-specific associations between EAEC detection in monthly surveillance stools and A) weight-for-age z-score (WAZ) velocity and B) length-for-age z-score (LAZ) velocity over the subsequent month among 2,050 children in the MAL-ED cohort with at least one surveillance stool and at least one month of complete anthropometric measurements and testing for EAEC and <i>Campylobacter</i>.</p

Fecal MPO, Fecal alpha-1-antitrypsin (A1AT), and plasma LPS, FABP and SAA each predicts subsequent growth impairment.

<p>a: For MPO, <i>p</i> = 0.028; n = 266 when correcting for age and gender, and independent of breastfeeding status (that showed no correlation in these 6-26m old children) and of age. b: For A1AT, n = 237; <i>p</i> = 0.042; and A1AT also correlates with “catchup WAZ” as well, <i>p</i> = 0.035 after correcting for age and gender. c: For urine L/M, higher values correlated (controlling for age and gender) with impaired growth (delta HAZ) (<i>r</i> = -0.173; <i>p</i> = 0.009; n = 230). d: For plasma LPS (ie lower LUM), higher values correlated with impaired growth (delta HAZ) (<i>r</i> = 0.151; <i>p</i> = 0.017; n = 251). e: For plasma FABP, higher values correlated with impaired growth (delta HAZ) (r = -0.134; <i>p</i> = 0.042; n = 231). f: For plasma SAA, higher values correlated with impaired growth (delta HAZ) (r = -0.132; p = 0.046; n = 231).</p

Frequencies of biomarker testing, including 13 tests on plasma, 4 on fecal and L/M absorption testing on urine as shown.

<p>*Of 326 children with samples obtained within 1 month of study start.</p

Heat map showing all significant partial Pearson correlations of barrier and systemic biomarkers with HAZ or WAZ at enrollment (ie. study start, ss) or with changes in (Δ) HAZ or WAZ.

<p>Significant correlations (at p<0.05; * = p<0.01) between biomarkers and growth, controlling for child age and gender. HAZ = height for age Z score; WAZ = weight for age z score; ss = study start; Δ = change in HAZ or WAZ at 2-6m followup; numbers range from 230 to 292 except for zonulin at age >12m where n = 172. Full r, p and df values are provided in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0158772#pone.0158772.s002" target="_blank">S1 Table</a>.</p

Path model, using Principle Components Analyses (Equamax rotation solution maximizing independence of groups) showing associations among 1) Barrier (green), 2) Local Gut (orange) and 3) Systemic (pink) sets of biomarkers, as well as their predictive utility regarding linear growth.

<p>Path model, using Principle Components Analyses (Equamax rotation solution maximizing independence of groups) showing associations among 1) Barrier (green), 2) Local Gut (orange) and 3) Systemic (pink) sets of biomarkers, as well as their predictive utility regarding linear growth.</p