Causes and consequences of child growth faltering in low-resource settings.

Growth faltering in children (low length for age or low weight for length) during the first 1,000 days of life (from conception to 2 years of age) influences short-term and long-term health and survival1,2. Interventions such as nutritional supplementation during pregnancy and the postnatal period could help prevent growth faltering, but programmatic action has been insufficient to eliminate the high burden of stunting and wasting in low- and middle-income countries. Identification of age windows and population subgroups on which to focus will benefit future preventive efforts. Here we use a population intervention effects analysis of 33 longitudinal cohorts (83,671 children, 662,763 measurements) and 30 separate exposures to show that improving maternal anthropometry and child condition at birth accounted for population increases in length-for-age z-scores of up to 0.40 and weight-for-length z-scores of up to 0.15 by 24 months of age. Boys had consistently higher risk of all forms of growth faltering than girls. Early postnatal growth faltering predisposed children to subsequent and persistent growth faltering. Children with multiple growth deficits exhibited higher mortality rates from birth to 2 years of age than children without growth deficits (hazard ratios 1.9 to 8.7). The importance of prenatal causes and severe consequences for children who experienced early growth faltering support a focus on pre-conception and pregnancy as a key opportunity for new preventive interventions.

Burden of disease attributable to unsafe drinking water, sanitation, and hygiene in domestic settings: a global analysis for selected adverse health outcomes.

BACKGROUND: Assessments of disease burden are important to inform national, regional, and global strategies and to guide investment. We aimed to estimate the drinking water, sanitation, and hygiene (WASH)-attributable burden of disease for diarrhoea, acute respiratory infections, undernutrition, and soil-transmitted helminthiasis, using the WASH service levels used to monitor the UN Sustainable Development Goals (SDGs) as counterfactual minimum risk-exposure levels. METHODS: We assessed the WASH-attributable disease burden of the four health outcomes overall and disaggregated by region, age, and sex for the year 2019. We calculated WASH-attributable fractions of diarrhoea and acute respiratory infections by country using modelled WASH exposures and exposure-response relationships from two updated meta-analyses. We used the WHO and UNICEF Joint Monitoring Programme for Water Supply, Sanitation and Hygiene public database to estimate population exposure to different WASH service levels. WASH-attributable undernutrition was estimated by combining the population attributable fractions (PAF) of diarrhoea caused by unsafe WASH and the PAF of undernutrition caused by diarrhoea. Soil-transmitted helminthiasis was fully attributed to unsafe WASH. FINDINGS: We estimate that 1·4 (95% CI 1·3-1·5) million deaths and 74 (68-80) million disability-adjusted life-years (DALYs) could have been prevented by safe WASH in 2019 across the four designated outcomes, representing 2·5% of global deaths and 2·9% of global DALYs from all causes. The proportion of diarrhoea that is attributable to unsafe WASH is 0·69 (0·65-0·72), 0·14 (0·13-0·17) for acute respiratory infections, and 0·10 (0·09-0·10) for undernutrition, and we assume that the entire disease burden from soil-transmitted helminthiasis was attributable to unsafe WASH. INTERPRETATION: WASH-attributable burden of disease estimates based on the levels of service established under the SDG framework show that progress towards the internationally agreed goal of safely managed WASH services for all would yield major public-health returns. FUNDING: WHO and Foreign, Commonwealth & Development Office.

Predictors of Drinking Water Boiling and Bottled Water Consumption in Rural China: A Hierarchical Modeling Approach.

Approximately two billion people drink unsafe water. Boiling is the most commonly used household water treatment (HWT) method globally and in China. HWT can make water safer, but sustained adoption is rare and bottled water consumption is growing. To successfully promote HWT, an understanding of associated socioeconomic factors is critical. We collected survey data and water samples from 450 rural households in Guangxi Province, China. Covariates were grouped into blocks to hierarchically construct modified Poisson models and estimate risk ratios (RR) associated with boiling methods, bottled water, and untreated water. Female-headed households were most likely to boil (RR = 1.36, p < 0.01), and among boilers those using electric kettles rather than pots had higher income proxies (e.g., per capita TV ownership RR = 1.42, p < 0.01). Higher-income households with younger, literate, and male heads were more likely to purchase (frequently contaminated) bottled water, or use electric kettles if they boiled. Our findings show that boiling is not an undifferentiated practice, but one with different methods of varying effectiveness, environmental impact, and adoption across socioeconomic strata. Our results can inform programs to promote safer and more efficient boiling using electric kettles, and suggest that if rural China's economy continues to grow then bottled water use will increase.

Spillover effects on health outcomes in low- and middle-income countries: a systematic review.

Background: Many interventions delivered to improve health may benefit not only direct recipients but also people in close physical or social proximity. Our objective was to review all published literature about the spillover effects of interventions on health outcomes in low-middle income countries and to identify methods used in estimating these effects. Methods: We searched 19 electronic databases for articles published before 2014 and hand-searched titles from 2010 to 2013 in five relevant journals. We adapted the Cochrane Collaboration's quality grading tool for spillover estimation and rated the quality of evidence. Results: A total of 54 studies met inclusion criteria. We found a wide range of terminology used to describe spillovers, a lack of standardization among spillover methods and poor reporting of spillovers in many studies. We identified three primary mechanisms of spillovers: reduced disease transmission, social proximity and substitution of resources within households. We found the strongest evidence for spillovers through reduced disease transmission, particularly vaccines and mass drug administration. In general, the proportion of a population receiving an intervention was associated with improved health. Most studies were of moderate or low quality. We found evidence of publication bias for certain spillover estimates but not for total or direct effects. To facilitate improved reporting and standardization in future studies, we developed a reporting checklist adapted from the CONSORT framework specific to reporting spillover effects. Conclusions: We found the strongest evidence for spillovers from vaccines and mass drug administration to control infectious disease. There was little high quality evidence of spillovers for other interventions.

Climate and Health Co-Benefits in Low-Income Countries: A Case Study of Carbon Financed Water Filters in Kenya and a Call for Independent Monitoring.

BACKGROUND: The recent global climate agreement in Paris aims to mitigate greenhouse gas emissions while fostering sustainable development and establishes an international trading mechanism to meet this goal. Currently, carbon offset program implementers are allowed to collect their own monitoring data to determine the number of carbon credits to be awarded. OBJECTIVES: We summarize reasons for mandating independent monitoring of greenhouse gas emission reduction projects. In support of our policy recommendations, we describe a case study of a program designed to earn carbon credits by distributing almost one million drinking water filters in rural Kenya to avert the use of fuel for boiling water. We compare results from an assessment conducted by our research team in the program area among households with pregnant women or caregivers in rural villages with low piped water access with the reported program monitoring data and discuss the implications. DISCUSSION: Our assessment in Kenya found lower levels of household water filter usage than the internal program monitoring reported estimates used to determine carbon credits; we found 19% (n = 4,041) of households reported filter usage 2-3 years after filter distribution compared to the program stated usage rate of 81% (n = 14,988) 2.7 years after filter distribution. Although carbon financing could be a financially sustainable approach to scale up water treatment and improve health in low-income settings, these results suggest program effectiveness will remain uncertain in the absence of requiring monitoring data be collected by third-party organizations. CONCLUSION: Independent monitoring should be a key requirement for carbon credit verification in future international carbon trading mechanisms to ensure programs achieve benefits in line with sustainable development goals. Citation: Pickering AJ, Arnold BF, Dentz HN, Colford JM Jr., Null C. 2017. Climate and health co-benefits in low-income countries: a case study of carbon financed water filters in Kenya and a call for independent monitoring. Environ Health Perspect 125:278-283; http://dx.doi.org/10.1289/EHP342.

Epidemiologic evaluation of multiple alternate microbial water quality monitoring indicators at three California beaches.

INTRODUCTION: Advances in molecular methods provide new opportunities for directly measuring pathogens or host-associated markers of fecal pollution instead of relying on fecal indicator bacteria (FIB) alone for beach water quality monitoring. Adoption of new indicators depends on identifying relationships between either the presence or concentration of the indicators and illness among swimmers. Here we present results from three epidemiologic studies in which a broad range of bacterial and viral indicators of fecal contamination were measured simultaneously by either culture or molecular methods along with Enterococcus to assess whether they provide better health risk prediction than current microbial indicators of recreational water quality. METHODS: We conducted prospective cohort studies at three California beaches -- Avalon Bay (Avalon), Doheny State Beach (Doheny), Surfrider State Beach (Malibu) -- during the summers of 2007, 2008 and 2009. The studies enrolled 10,785 swimmers across the beaches and recorded each swimmer's water exposure. Water and sand samples were collected several times per day at multiple locations at each beach and analyzed for up to 41 target indicators using 67 different methodologies. Interviewers contacted participants by phone 10-14 days later and recorded symptoms of gastrointestinal illness occurring after their beach visit. Regression models were used to evaluate the association between water quality indicators and gastrointestinal illness among swimmers at each beach. RESULTS: F+ coliphage (measured using EPA Method 1602) exhibited a stronger association with GI illness than did EPA Method 1600 at the two beaches where it was measured, while a molecular method, F+ RNA Coliphage Genotype II, was the only indicator significantly associated with GI illness at Malibu. MRSA, a known pathogen, had the strongest association with GI illness of any microbe measured at Avalon. There were two methods targeting human-associated fecal anaerobic bacteria that were more strongly associated with GI illness than EPA Method 1600, but only at Avalon. No indicator combinations consistently had a higher odds ratio than EPA Method 1600, but one composite indicator, based on the number of pathogens detected at a beach, was significantly associated with gastrointestinal illness at both Avalon and Doheny when freshwater flow was high. DISCUSSION: While EPA Method1600 performed adequately at two beaches based on its consistency of association with gastrointestinal illness and the precision of its estimated associations, F+ coliphage measured by EPA Method 1602 had a stronger association with GI illness under high risk conditions at the two beaches where it was measured. One indicator, F+ Coliphage Genotype II was the only indicator significantly associated with GI illness at Malibu. Several indicators, particularly those targeting human associated bacteria, exhibited relationships with GI illness that were equal to or greater than that of EPA Method 1600 at Avalon, which has a focused human fecal source. Our results suggest that site-specific conditions at each beach determine which indicator or indicators best predict GI illness.

Estimating the impact of unsafe water, sanitation and hygiene on the global burden of disease: evolving and alternative methods.

The 2010 global burden of disease (GBD) study represents the latest effort to estimate the global burden of disease and injuries and the associated risk factors. Like previous GBD studies, this latest iteration reflects a continuing evolution in methods, scope and evidence base. Since the first GBD Study in 1990, the burden of diarrhoeal disease and the burden attributable to inadequate water and sanitation have fallen dramatically. While this is consistent with trends in communicable disease and child mortality, the change in attributable risk is also due to new interpretations of the epidemiological evidence from studies of interventions to improve water quality. To provide context for a series of companion papers proposing alternative assumptions and methods concerning the disease burden and risks from inadequate water, sanitation and hygiene, we summarise evolving methods over previous GBD studies. We also describe an alternative approach using population intervention modelling. We conclude by emphasising the important role of GBD studies and the need to ensure that policy on interventions such as water and sanitation be grounded on methods that are transparent, peer-reviewed and widely accepted.

Burden of disease from inadequate water, sanitation and hygiene in low- and middle-income settings: a retrospective analysis of data from 145 countries.

OBJECTIVE: To estimate the burden of diarrhoeal diseases from exposure to inadequate water, sanitation and hand hygiene in low- and middle-income settings and provide an overview of the impact on other diseases. METHODS: For estimating the impact of water, sanitation and hygiene on diarrhoea, we selected exposure levels with both sufficient global exposure data and a matching exposure-risk relationship. Global exposure data were estimated for the year 2012, and risk estimates were taken from the most recent systematic analyses. We estimated attributable deaths and disability-adjusted life years (DALYs) by country, age and sex for inadequate water, sanitation and hand hygiene separately, and as a cluster of risk factors. Uncertainty estimates were computed on the basis of uncertainty surrounding exposure estimates and relative risks. RESULTS: In 2012, 502,000 diarrhoea deaths were estimated to be caused by inadequate drinking water and 280,000 deaths by inadequate sanitation. The most likely estimate of disease burden from inadequate hand hygiene amounts to 297,000 deaths. In total, 842,000 diarrhoea deaths are estimated to be caused by this cluster of risk factors, which amounts to 1.5% of the total disease burden and 58% of diarrhoeal diseases. In children under 5 years old, 361,000 deaths could be prevented, representing 5.5% of deaths in that age group. CONCLUSIONS: This estimate confirms the importance of improving water and sanitation in low- and middle-income settings for the prevention of diarrhoeal disease burden. It also underscores the need for better data on exposure and risk reductions that can be achieved with provision of reliable piped water, community sewage with treatment and hand hygiene.

Estimation of treatment efficacy with complier average causal effects (CACE) in a randomized stepped wedge trial.

Complier average causal effects (CACE) estimate the impact of an intervention among treatment compliers in randomized trials. Methods used to estimate CACE have been outlined for parallel-arm trials (e.g., using an instrumental variables (IV) estimator) but not for other randomized study designs. Here, we propose a method for estimating CACE in randomized stepped wedge trials, where experimental units cross over from control conditions to intervention conditions in a randomized sequence. We illustrate the approach with a cluster-randomized drinking water trial conducted in rural Mexico from 2009 to 2011. Additionally, we evaluated the plausibility of assumptions required to estimate CACE using the IV approach, which are testable in stepped wedge trials but not in parallel-arm trials. We observed small increases in the magnitude of CACE risk differences compared with intention-to-treat estimates for drinking water contamination (risk difference (RD) = -22% (95% confidence interval (CI): -33, -11) vs. RD = -19% (95% CI: -26, -12)) and diarrhea (RD = -0.8% (95% CI: -2.1, 0.4) vs. RD = -0.1% (95% CI: -1.1, 0.9)). Assumptions required for IV analysis were probably violated. Stepped wedge trials allow investigators to estimate CACE with an approach that avoids the stronger assumptions required for CACE estimation in parallel-arm trials. Inclusion of CACE estimates in stepped wedge trials with imperfect compliance could enhance reporting and interpretation of the results of such trials.

H2S as an indicator of water supply vulnerability and health risk in low-resource settings: a prospective cohort study.

In this large-scale longitudinal study conducted in rural Southern India, we compared a presence/absence hydrogen sulfide (H2S) test with quantitative assays for total coliforms and Escherichia coli as measures of water quality, health risk, and water supply vulnerability to microbial contamination. None of the three indicators showed a significant association with child diarrhea. The presence of H2S in a water sample was associated with higher levels of total coliform species that may have included E. coli but that were not restricted to E. coli. In addition, we observed a strong relationship between the percent positive H2S test results and total coliform levels among water source samples (R(2) = 0.87). The consistent relationships between H2S and total coliform levels indicate that presence/absence of H2S tests provide a cost-effective option for assessing both the vulnerability of water supplies to microbial contamination and the results of water quality management and risk mitigation efforts.

Dissemination of drinking water contamination data to consumers: a systematic review of impact on consumer behaviors.

BACKGROUND: Drinking water contaminated by chemicals or pathogens is a major public health threat in the developing world. Responses to this threat often require water consumers (households or communities) to improve their own management or treatment of water. One approach hypothesized to increase such positive behaviors is increasing knowledge of the risks of unsafe water through the dissemination of water contamination data. This paper reviews the evidence for this approach in changing behavior and subsequent health outcomes. METHODS/PRINCIPAL FINDINGS: A systematic review was conducted for studies where results of tests for contaminants in drinking water were disseminated to populations whose water supply posed a known health risk. Studies of any design were included where data were available from a contemporaneous comparison or control group. Using multiple sources >14,000 documents were located. Six studies met inclusion criteria (four of arsenic contamination and two of microbiological contamination). Meta-analysis was not possible in most cases due to heterogeneity of outcomes and study designs. Outcomes included water quality, change of water source, treatment of water, knowledge of contamination, and urinary arsenic. Source switching was most frequently reported: of 5 reporting studies 4 report significantly higher rates of switching (26-72%) among those who received a positive test result and a pooled risk difference was calculate for 2 studies (RD = 0.43 [CI0.4.0-0.46] 6-12 months post intervention) suggesting 43% more of those with unsafe wells switched source compared to those with safe wells. Strength of evidence is low since the comparison is between non-equivalent groups. Two studies concerning fecal contamination reported non-significant increases in point-of-use water treatment. CONCLUSION: Despite the publication of some large cohort studies and some encouraging results the evidence base to support dissemination of contamination data to improve water management is currently equivocal. Rigorous studies on this topic are needed, ideally using common outcome measures.

Performance of analytical methods for overdispersed counts in cluster randomized trials: sample size, degree of clustering and imbalance.

Many different methods have been proposed for the analysis of cluster randomized trials (CRTs) over the last 30 years. However, the evaluation of methods on overdispersed count data has been based mostly on the comparison of results using empiric data; i.e. when the true model parameters are not known. In this study, we assess via simulation the performance of five methods for the analysis of counts in situations similar to real community-intervention trials. We used the negative binomial distribution to simulate overdispersed counts of CRTs with two study arms, allowing the period of time under observation to vary among individuals. We assessed different sample sizes, degrees of clustering and degrees of cluster-size imbalance. The compared methods are: (i) the two-sample t-test of cluster-level rates, (ii) generalized estimating equations (GEE) with empirical covariance estimators, (iii) GEE with model-based covariance estimators, (iv) generalized linear mixed models (GLMM) and (v) Bayesian hierarchical models (Bayes-HM). Variation in sample size and clustering led to differences between the methods in terms of coverage, significance, power and random-effects estimation. GLMM and Bayes-HM performed better in general with Bayes-HM producing less dispersed results for random-effects estimates although upward biased when clustering was low. GEE showed higher power but anticonservative coverage and elevated type I error rates. Imbalance affected the overall performance of the cluster-level t-test and the GEE's coverage in small samples. Important effects arising from accounting for overdispersion are illustrated through the analysis of a community-intervention trial on Solar Water Disinfection in rural Bolivia.

Microbial risk assessment framework for exposure to amended sludge projects.

BACKGROUND: Although the U.S. Environmental Protection Agency has a long history of using risk-based approaches for regulatory purposes, pollutant limits for pathogens in biosolids are not currently based on quantitative risk assessments. OBJECTIVES: We developed and demonstrated a risk-based methodology for assessing the risk to human health from exposure to pathogens via biosolids. MATERIALS: Four models were developed, incorporating direct ingestion, groundwater, and aerosol exposure pathways. Three sources of environmental data were used to estimate risk: pathogen monitoring of sludge, efficacy of sludge treatment, and pathogen monitoring of biosolids. RESULTS: Risk estimates were obtainable even for Class A biosolids, where posttreatment monitoring data are below detectable levels, demonstrating that risk assessments for biosolids exposure are practical. Model analyses suggest that: a) a two-digester design decreases the probability of risks >10(-4) compared with one-digester designs, b) risks associated with exposures to groundwater and aerosol pathways were, in general, lower than exposures to the direct ingestion pathway, and c) secondary transmission can be an important factor in risk estimation. CONCLUSIONS: The risk-based approach presented here provides a tool to a) help biosolids producers interpret the results of biosolids monitoring data in terms of its health implications, b) help treatment plant engineers evaluate the risk-based benefits of operational changes to existing or projected treatment processes, and c) help environmental managers evaluate potential capital improvements and/or land application site placement issues. Regulation of pathogens can now be based on human health risk in a manner parallel to other water-related risks.

Inferences drawn from a risk assessment compared directly with a randomized trial of a home drinking water intervention.

Risk assessments and intervention trials have been used by the U.S. Environmental Protection Agency to estimate drinking water health risks. Seldom are both methods used concurrently. Between 2001 and 2003, illness data from a trial were collected simultaneously with exposure data, providing a unique opportunity to compare direct risk estimates of waterborne disease from the intervention trial with indirect estimates from a risk assessment. Comparing the group with water treatment (active) with that without water treatment (sham), the estimated annual attributable disease rate (cases per 10,000 persons per year) from the trial provided no evidence of a significantly elevated drinking water risk [attributable risk=-365 cases/year, sham minus active; 95% confidence interval (CI) , -2,555 to 1,825]. The predicted mean rate of disease per 10,000 persons per person-year from the risk assessment was 13.9 (2.5, 97.5 percentiles: 1.6, 37.7) assuming 4 log removal due to viral disinfection and 5.5 (2.5, 97.5 percentiles: 1.4, 19.2) assuming 6 log removal. Risk assessments are important under conditions of low risk when estimates are difficult to attain from trials. In particular, this assessment pointed toward the importance of attaining site-specific treatment data and the clear need for a better understanding of viral removal by disinfection. Trials provide direct risk estimates, and the upper confidence limit estimates, even if not statistically significant, are informative about possible upper estimates of likely risk. These differences suggest that conclusions about waterborne disease risk may be strengthened by the joint use of these two approaches. Key words: drinking water, gastrointestinal, intervention trial, microbial risk assessment, waterborne pathogens.