Psychosocial and environmental determinants of child cognitive development in rural south africa and tanzania: findings from the mal-ed cohort

Background Approximately 66% of children under the age of 5 in Sub-Saharan African countries do not reach their full cognitive potential, the highest percentage in the world. Because the majority of studies investigating child cognitive development have been conducted in high-income countries (HICs), there is limited knowledge regarding the determinants of child development in low- and middle-income countries (LMICs). Methods This analysis includes 401 mother-child dyads from the South Africa and Tanzania sites of the Etiology, Risk Factors, and Interactions of Enteric Infections and Malnutrition and the Consequences for Child Health and Development (MAL-ED) longitudinal birth cohort study. We investigated the effect of psychosocial and environmental determinants on child cognitive development measured by the Wechsler Preschool Primary Scales of Intelligence (WPPSI) at 5 years of age using multivariable linear regression. Results Socioeconomic status was most strongly associated with child cognitive development (WPSSI Score Difference (SD):14.27, 95% CI:1.96, 26.59). Modest associations between the organization of the home environment and its opportunities for cognitive stimulation and child cognitive development were also found (SD: 3.08, 95% CI: 0.65, 5.52 and SD: 3.18, 95% CI: 0.59, 5.76, respectively). Conclusion This study shows a stronger association with child cognitive development at 5 years of age for socioeconomic status compared to more proximal measures of psychosocial and environmental determinants. A better understanding of the role of these factors is needed to inform interventions aiming to alleviate the burden of compromised cognitive development for children in LMICs.publishedVersio

Full breastfeeding protection against common enteric bacteria and viruses: Results from the MAL-ED cohort study

Background: Breastfeeding is known to reduce risk of enteropathogen infections, but protection from specific enteropathogens is not well characterized.Objective: To estimate the association between full breastfeeding (days fed breast milk exclusively or with non-nutritive liquids) and enteropathogen detection.Design: 2,145 newborns were enrolled in eight sites, of whom 1,712 had breastfeeding and key enteropathogen data through 6 months. We focused on eleven enteropathogens: adenovirus 40/41, norovirus, sapovirus, astrovirus, and rotavirus, enterotoxigenic Escherichia coli (ETEC), Campylobacter spp, and typical enteropathogenic E. coli as well as entero-aggregative E. coli, Shigella and Cryptosporidium. Logistic regression was used to estimate the risk of enteropathogen detection in stools and survival analysis to estimate the timing of first detection of an enteropathogen.Results: Infants with 10% more days of full breastfeeding within the preceding 30 days of a stool sample were less likely to have the three E. Coli and Campylobacter spp detected in their stool (mean odds 0.92-0.99) but equally likely (0.99-1.02) to have the viral pathogens detected in their stool. A 10% longer period of full breastfeeding from birth was associated with later first detection of the three E. Coli, Campylobacter, adenovirus, astrovirus, and rotavirus (mean hazard ratios of 0.52-0.75). The hazards declined and point estimates were not statistically significant at 3 months.Conclusions: In this large multi-center cohort study, full breastfeeding was associated with lower likelihood of detecting four important enteric pathogens in the first six months of life. These results also show that full breastfeeding is related to delays in the first detection of some bacterial and viral pathogens in the stool. As several of these pathogens are risk factors for poor growth during childhood, this work underscores the importance of exclusive or full breastfeeding during the first six months of life to optimize early health

Full breastfeeding protection against common enteric bacteria and viruses : results from the MAL-ED cohort study

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World Health Organization Expert Working Group: Recommendations for assessing morbidity associated with enteric pathogens

BACKGROUND: Diarrhoeal infections are one of the leading causes of child's mortality and morbidity. Vaccines against Shigella, enterotoxigenic E. coli (ETEC), norovirus and invasive non-typhoidal Salmonella are in clinical development, however, their full value in terms of short and long-term health and socio-economic burden needs to be evaluated and communicated, to rationalise investment in vaccine development, and deployment. While estimates of mortality of enteric infections exist, the long-term morbidity estimates are scarce and have not been systematically collected. METHODS: The World Health Organization (WHO) has convened a Burden of Enteric Diseases Morbidity Working Group (BoED MWG) who identified key workstreams needed to characterise the morbidity burden of enteric infections. The group also identified four criteria for the prioritisation of pathogens of which impact on long-term morbidity needs to be assessed. RESULTS: The BoED MWG suggested to identify and analyse the individual level data from historical datasets to estimate the impact of enteric infections and confounders on long-term morbidity, including growth faltering and cognitive impairment in children (workstream 1); to conduct a systematic review of evidence on the association of aetiology specific diarrhoea with short- and long- term impact on growth, including stunting, and possibly cognitive impairment in children, while accounting for potential confounders (workstream 2); and to conduct a systematic review of evidence on the association of aetiology specific diarrhoea with short- and long- term impact on health outcomes in adults. The experts prioritised four pathogens for this work: Campylobacter jejuni, ETEC (LT or ST), norovirus (G1 or G2), and Shigella (dysenteriae, flexneri, sonnei). CONCLUSIONS: The proposed work will contribute to improving the understanding of the impact of enteric pathogens on long-term morbidity. The timing of this work is critical as all four pathogens have vaccine candidates in the clinical pipeline and decisions about investments in development, manufacturing or vaccine procurement and use are expected to be made soon

Aetiology and incidence of diarrhoea requiring hospitalisation in children under 5 years of age in 28 low-income and middle-income countries: findings from the Global Pediatric Diarrhea Surveillance network.

Introduction: Diarrhoea remains a leading cause of child morbidity and mortality. Systematically collected and analysed data on the aetiology of hospitalised diarrhoea in low-income and middle-income countries are needed to prioritise interventions. Methods: We established the Global Pediatric Diarrhea Surveillance network, in which children under 5 years hospitalised with diarrhoea were enrolled at 33 sentinel surveillance hospitals in 28 low-income and middle-income countries. Randomly selected stool specimens were tested by quantitative PCR for 16 causes of diarrhoea. We estimated pathogen-specific attributable burdens of diarrhoeal hospitalisations and deaths. We incorporated country-level incidence to estimate the number of pathogen-specific deaths on a global scale. Results: During 2017–2018, 29 502 diarrhoea hospitalisations were enrolled, of which 5465 were randomly selected and tested. Rotavirus was the leading cause of diarrhoea requiring hospitalisation (attributable fraction (AF) 33.3%; 95% CI 27.7 to 40.3), followed by Shigella (9.7%; 95% CI 7.7 to 11.6), norovirus (6.5%; 95% CI 5.4 to 7.6) and adenovirus 40/41 (5.5%; 95% CI 4.4 to 6.7). Rotavirus was the leading cause of hospitalised diarrhoea in all regions except the Americas, where the leading aetiologies were Shigella (19.2%; 95% CI 11.4 to 28.1) and norovirus (22.2%; 95% CI 17.5 to 27.9) in Central and South America, respectively. The proportion of hospitalisations attributable to rotavirus was approximately 50% lower in sites that had introduced rotavirus vaccine (AF 20.8%; 95% CI 18.0 to 24.1) compared with sites that had not (42.1%; 95% CI 33.2 to 53.4). Globally, we estimated 208 009 annual rotavirus-attributable deaths (95% CI 169 561 to 259 216), 62 853 Shigella-attributable deaths (95% CI 48 656 to 78 805), 36 922 adenovirus 40/41-attributable deaths (95% CI 28 469 to 46 672) and 35 914 norovirus-attributable deaths (95% CI 27 258 to 46 516). Conclusions: Despite the substantial impact of rotavirus vaccine introduction, rotavirus remained the leading cause of paediatric diarrhoea hospitalisations. Improving the efficacy and coverage of rotavirus vaccination and prioritising interventions against Shigella, norovirus and adenovirus could further reduce diarrhoea morbidity and mortality

Population Enumeration and Household Utilization Survey Methods in the Enterics for Global Health (EFGH): Shigella Surveillance Study

Background: Accurate estimation of diarrhea incidence from facility-based surveillance requires estimating the population at risk and accounting for case patients who do not seek care. The Enterics for Global Health (EFGH) Shigella surveillance study will characterize population denominators and healthcare-seeking behavior proportions to calculate incidence rates of Shigella diarrhea in children aged 6–35 months across 7 sites in Africa, Asia, and Latin America. Methods: The Enterics for Global Health (EFGH) Shigella surveillance study will use a hybrid surveillance design, supplementing facility-based surveillance with population-based surveys to estimate population size and the proportion of children with diarrhea brought for care at EFGH health facilities. Continuous data collection over a 24 month period captures seasonality and ensures representative sampling of the population at risk during the period of facility-based enrollments. Study catchment areas are broken into randomized clusters, each sized to be feasibly enumerated by individual field teams. Conclusions: The methods presented herein aim to minimize the challenges associated with hybrid surveillance, such as poor parity between survey area coverage and facility coverage, population fluctuations, seasonal variability, and adjustments to care-seeking behavior

Introducing riskCommunicator: An R package to obtain interpretable effect estimates for public health

Common statistical modeling methods do not necessarily produce the most relevant or interpretable effect estimates to communicate risk. Overreliance on the odds ratio and relative effect measures limit the potential impact of epidemiologic and public health research. We created a straightforward R package, called riskCommunicator, to facilitate the presentation of a variety of effect measures, including risk differences and ratios, number needed to treat, incidence rate differences and ratios, and mean differences. The riskCommunicator package uses g-computation with parametric regression models and bootstrapping for confidence intervals to estimate effect measures in time-fixed data. We demonstrate the utility of the package using data from the Framingham Heart Study to estimate the effect of prevalent diabetes on the 24-year risk of cardiovascular disease or death. The package promotes the communication of public-health relevant effects and is accessible to a broad range of epidemiologists and health researchers with little to no expertise in causal inference methods or advanced coding

Minimizing error in estimates of the effect of interventions by accounting for baseline measurements: A simulation study analyzing effects on child growth

Abstract Interventions to reduce childhood stunting burden require clinical trials with a primary outcome of linear growth. When growth is measured longitudinally, there are several options for including baseline measurements in the analysis. This study compares the performance of several methods. Randomized controlled trials evaluating a hypothetical intervention to improve length‐for‐age z‐score (LAZ) from birth through 24 months of age were simulated. The intervention effect was evaluated using linear regression and five methods for handling baseline measurements: comparing final measurements only (FINAL), comparing final measurement adjusted for baseline (ADJUST), comparing the change in the measurement over time (DELTA), adjusting for baseline when comparing the changes over time (DELTA+ADJUST) and adjusting for baseline in two‐step residuals approach (RESIDUALS). We calculated bias, precision and power of each method for scenarios with and without a baseline imbalance in LAZ. Using a 0.15 effect size at 18 months, FINAL and DELTA required 1200 and 1500 enroled participants, respectively, to reach 80% power, whereas ADJUST, DELTA+ADJUST and RESIDUALS only required 900 participants. The adjusted models also produced unbiased estimates when there was a baseline imbalance, whereas the FINAL and DELTA methods produced biased estimates, as large as 0.07 lower and higher, respectively, than the true effect. Adjusted methods required smaller sample size and produced more precise results than both DELTA and FINAL methods in all test scenarios. If randomization fails, and there is an imbalance in LAZ at baseline, DELTA and FINAL methods can produce biased estimates, but adjusted models remain unbiased. These results warn against using the FINAL or DELTA methods

Population intervention effects in observational studies to emulate target trial results: reconciling the effects of improved sanitation on child growth.

BackgroundImproved sanitation has been associated with improved child growth in observational studies, but multiple randomized trials that delivered improved sanitation found no effect on child growth. We assessed to what extent differences in the effect estimated in the two study designs (the effect of treatment in observational studies and the effect of treatment assignment in trials) could explain the contradictory results.MethodsWe used parametric g-computation in five prospective studies (n = 21 524) and 59 cross-sectional Demographic and Health Surveys (DHS; n = 158 439). We compared the average treatment effect (ATE) for improved sanitation on mean length-for-age z-score (LAZ) among children aged <2 years to population intervention effects (PIEs), which are the observational analogue of the effect estimated in trials in which some participants are already exposed.ResultsThe ATE was >0.15 z-scores, a clinically meaningful difference, in most prospective studies but in <20% of DHS surveys. The PIE was always smaller than the ATE, and the magnitude of difference depended on the baseline prevalence of the improved sanitation. Interventions with suboptimal coverage and interventions delivered in populations with higher mean LAZ had a smaller effect on population-level LAZ.ConclusionsEstimates of PIEs corresponding to anticipated trial results were often smaller than clinically meaningful effects. Incongruence between observational associations and null trial results may in part be explained by expected differences between the effects estimated. Using observational ATEs to set expectations for trials may overestimate the impact that sanitation interventions can achieve. PIEs predict realistic effects and should be more routinely estimated