Factors associated with recovery from stunting at 24 months of age among infants and young children enrolled in the Pediatric Development Clinic (PDC): A retrospective cohort study in rural Rwanda.

INTRODUCTION: Stunting (low height/length-for-age) in early life is associated with poor long-term health and developmental outcomes. Nutrition interventions provided during the first 1,000 days of life can result in improved catch-up growth and development outcomes. We assessed factors associated with stunting recovery at 24 months of age among infants and young Children enrolled in Pediatric Development Clinics (PDC) who were stunted at 11 months of age. METHODS: This retrospective cohort study included infants and young children who enrolled in PDCs in two rural districts in Rwanda between April 2014 and December 2018. Children were included in the study if their PDC enrollment happened within 2 months after birth, were stunted at 11 months of age (considered as baseline) and had a stunting status measured and analyzed at 24 months of age. We defined moderate stunting as length-for-age z-score (LAZ) < -2 and ≥-3 and severe stunting as LAZ <-3 based on the 2006 WHO child growth standards. Stunting recovery at 24 months of age was defined as the child's LAZ changing from <-2 to > -2. We used logistic regression analysis to investigate factors associated with stunting recovery. The factors analyzed included child and mother's socio-demographic and clinical characteristics. RESULTS: Of the 179 children who were eligible for this study, 100 (55.9%) were severely stunted at age 11 months. At 24 months of age, 37 (20.7%) children recovered from stunting, while 21 (21.0%) severely stunted children improved to moderate stunting and 20 (25.3%) moderately-stunted children worsened to severe stunting. Early stunting at 6 months of age was associated with lower odds of stunting recovery, with the odds of stunting recovery being reduced by 80% (aOR: 0.2; 95%CI: 0.07-0.81) for severely stunted children and by 60% (aOR: 0.4; 95% CI: 0.16-0.97) for moderately stunted children (p = 0.035). Lower odds of stunting recovery were also observed among children who were severely stunted at 11 months of age (aOR: 0.3; 95% CI: 0.1-0.6, p = 0.004). No other maternal or child factors were statistically significantly associated with recovery from stunting at 24 months in our final adjusted model. CONCLUSION: A substantial proportion of children who were enrolled in PDC within 2 months after birth and were stunted at 11 months of age recovered from stunting at 24 months of age. Children who were severely stunted at 11 months of age (baseline) and those who were stunted at 6 months of age were less likely to recover from stunting at 24 months of age compared to those with moderate stunting at 11 months and no stunting at 6 months of age, respectively. More focus on prevention and early identification of stunting during pregnancy and early life is important to the healthy growth of a child.

Evaluation of an mHealth tool to improve nutritional assessment among infants under 6 months in paediatric development clinics in rural Rwanda: Quasi-experimental study.

Infants born preterm, low birthweight or with other perinatal complications require frequent and accurate growth monitoring for optimal nutrition and growth. We implemented an mHealth tool to improve growth monitoring and nutritional status assessment of high risk infants. We conducted a pre-post quasi-experimental study with a concurrent control group among infants enrolled in paediatric development clinics in two rural Rwandan districts. During the pre-intervention period (August 2017-January 2018), all clinics used standard paper-based World Health Organization (WHO) growth charts. During the intervention period (August 2018-January 2019), Kirehe district adopted an mHealth tool for child growth monitoring and nutritional status assessment. Data on length/height; weight; length/height-for-age (L/HFA), weight-for-length/height (WFL/H) and weight-for-age (WFA) z-scores; and interval growth were tracked at each visit. We conducted a 'difference-in-difference' analysis to assess whether the mHealth tool was associated with greater improvements in completion and accuracy of nutritional assessments and nutritional status at 2 and 6 months of age. We observed 3529 visits. mHealth intervention clinics showed significantly greater improvements on completeness for corrected age (endline: 65% vs. 55%; p = 0.036), L/HFA (endline: 82% vs. 57%; p ≤ 0.001), WFA (endline: 93% vs. 67%; p ≤ 0.001) and WFL/H (endline: 90% vs. 59%; p ≤ 0.001) z-scores compared with control sites. Accuracy of growth monitoring did not improve. Prevalence of stunting, underweight and inadequate interval growth at 6-months corrected age decreased significantly more in the intervention clinics than in control clinics. Results suggest that integrating mHealth nutrition interventions is feasible and can improve child nutrition outcomes. Improved tool design may better promote accuracy.

Caregiver delay in seeking healthcare during the acute phase of pediatric illness, Kigali, Rwanda.

INTRODUCTION: Delay in seeking healthcare contributes significantly to under-five mortality. Multiple socioeconomic and demographic factors have been reported as predictors of such delay. There is no published research in this area in Rwanda. Our aim was to describe the caregivers' delay in seeking healthcare during the acute phase of a childhood illness among under-five children admitted in a tertiary hospital, Rwanda. METHODS: This was an analytical, descriptive cross-sectional study conducted at University Teaching Hospital of Kigali. Bivariate analysis and logistic multivariate regression were used to analyze factors associated with delayed care-seeking behavior, defined as seeking care after the first 48 hours of illness onset. RESULTS: Among 275 admitted children under age five, care-seeking delay occurred in 35% (97/275) of cases. The most significant predictors of delay in seeking care were use of traditional healers (AOR = 14.87, 95% CI: 3.94-56.12), the recognition of illness as mild (AOR = 8.20, 95% CI: 4.08-16.47), use of un-prescribed medicine at home (AOR = 2.00, 95% CI: 1.01-3.91), use of special prayers provided by ministers of God before seeking healthcare (AOR = 6.42, 95% CI: 2.50, 16.48), and first consultation at public institutions (AOR = 4.00, 95% CI:1.54-10.39). CONCLUSION: Even though Rwanda has made tremendous achievements in strengthening the community-based health systems, delayed care-seeking is a reality. Health education and behavior change communication interventions are needed at the community level to address the factors that lead to delay in seeking healthcare.

Predictors of mortality in a paediatric intensive care unit in Kigali, Rwanda.

BACKGROUND: The enormous burden of critical illness in resource-limited settings has led to a growing interest in paediatric critical care in these regions. However, published data on the practice of critical care and patient outcomes in these settings are scant. OBJECTIVE: This study sought to identify risk factors associated with mortality in the newly established Paediatric Intensive Care Unit (PICU) at Kigali University Teaching Hospital (KUTH) in Rwanda and test the predictive ability of a newly devised mortality risk score, the modified PRISM (MP) score. METHODS: All admissions to the PICU at KUTH from October 2012 to October 2014 were included. Demographic and physiological data on each patient were gathered and each was assigned a MP score. This prospective cross-sectional study examined the association between the characteristics and physiological status of these patients and mortality. Using logistic regression, factors associated with mortality in the PICU were analysed. RESULTS: A total of 213 children were admitted to the PICU during the study period. Three patients were excluded because of missing data. Of this total, 59% were male, 25% were neonates and nearly 60% were moderately to severely malnourished. The overall mortality rate was 50%. On bivariate analysis, factors associated with increased mortality were male sex, use of vasoactive medications, a MP score ≥ 5, a discharge diagnosis of septic shock, and malnutrition on admission. On multivariate analysis, only the use of vasoactive drugs [odds ratio (OR) 12.24, 95% confidence interval (CI) 4.4-35.4, p < 0.001] and MP score ≥ 5 (OR 16.1, CI 6.3-40.8, p < 0.001) were associated with mortality. CONCLUSION: The observed mortality rate was in the range reported in other resource-limited settings. The initial attempt to create and implement a risk of mortality tool for this setting determined a score that could identify those patients at higher risk of mortality. In PICUs in resource-limited settings, the gathering of data and use of severity of illness tools could improve care in a number of ways.