The vast majority of research data, including systematic reviews, have focused on the impact of WASH interventions on diarrhea [2-4]. The link between WASH interventions and improvement in diarrheal infections has not translated into a demonstrable consistent improvement in other health parameters like child growth in various trials. Nutritional status of children is probably the best indicator of the health of a population, and more objective than historical recalls of diarrhea [5]. There is a paucity of systematic reviews evaluating the effect of WASH interventions on other health indicators, like malnutrition [6], mortality, and non-diarrheal morbidity; and additional trials have also now become available. We conducted this systematic review to evaluate the impact of WASH interventions on growth, non-diarrheal morbidity and mortality in children.

Individual- or cluster-randomized trials, and non-randomized and controlled before-after studies (CBA) from LMIC (individuals, families or communities) reporting outcomes in children (age <18 y) were eligible for inclusion in this review. Non-randomized trials were considered eligible for inclusion only if they had a concurrent comparison group (no WASH intervention) and adjustment for baseline characteristics and confounders. CBA studies were considered eligible for inclusion if allocation to the different comparison groups were not made by the investigators, and outcomes of interest were measured in both intervention and control groups before the WASH intervention was introduced, and again after a reasonable period of the intervention. We included non-randomized cluster trials, and CBA studies only with at least two intervention sites and two control sites.

We included studies that compared the provision of an improved source of water and/or improved distribution – such as piped water or standpipes, provided either at public (source) or household (point-of-use) levels; sanitation (‘hardware’) interventions that provide improved means of excreta disposal; hygiene interventions that focused on health and hygiene education and promotion of specific health behaviors like hand-washing; and various combinations of the above listed interventions by local government, research institutions, or other non-governmental organizations – with no intervention.

The outcomes evaluated were: (i) anthropometry: weight, height and weight-for-height (WFH), mid-arm circumference; (ii) prevalence of malnutrition [stunting (author defined), wasting (author defined), low weight-for-age or underweight (author defined) or low BMI (author defined)]; (iii) non-diarrheal morbidity (helminth infestation, dranculiasis, respiratory infections and others); and (iv) mortality.

We searched (August 2016) the following electronic databases: Medline, Web of Science, The Cochrane Controlled Trials Register, EMBASE, LILACS, Popline, and Graysource. Reference lists of all included papers and relevant reviews were scanned to identify citations that could have been missed in the primary search. We contacted authors of other relevant reviews in the field, relevant agencies and networks for the identification of ongoing or unpublished studies. The search results from the various databases and other sources were merged using reference management software (Endnote) to remove duplicate records. The title and abstract of the studies identified in the computerized search were scanned in duplicate to exclude references that were obviously irrelevant. In order to determine eligibility for inclusion of the remaining articles, their full texts were reviewed, and multiple reports of the same study were linked together. Two authors independently screened and assessed the eligibility of the studies, extracted relevant data and assessed the risk of bias for all included studies. Any dispute regarding these criteria was resolved among the investigators by mutual consultation.

We evaluated the risk of bias for each trial using the criteria outlined in the Cochrane Handbook for Systematic Reviews of Interventions [7]. Plots of ‘Risk of bias’ assessments were created in Review Manager (RevMan) [8].

Risk ratio (RR) estimates with 95% confidence intervals (CI) were used for binary outcomes; for continuous outcomes, mean differences (MD) were used. In order to maximize the data input for the pooled outcome measures, we utilized post-intervention values (means and standard deviations (SDs)) in preference to the changes from baseline [7]. In factorial trials and in multi-arm designs yielding two or more intervention groups (e.g., improved water supply and promotion of hand-washing) and a single control group, the data in the intervention groups were pooled and compared against the single control group to prevent unit-of-analysis error. For cluster-randomized trials, we used the stated cluster-adjusted RR or means and 95% CI, irrespective of the method employed for adjustment. In case of missing data, we contacted trial authors for information wherever possible; and where this could not be done, or the authors did not respond, we imputed the missing values with the help of a statistician, where feasible. In case any assumptions were made for such imputations, they were recorded, and are detailed in Web Appendix 1.

We performed statistical analysis using the Revman software [8]. In concordance with the current recommendations [7], we conducted the meta-analysis of included randomized controlled trials and observational studies separately. In view of variation in studies with respect to populations, interventions, comparators, outcome and settings, the pooled effects were computed by random effects model. If it was not possible to amalgamate the data from the included studies, we provided a narrative synthesis of the results. For each primary outcome, quality assessment of the results was carried out using the GRADE approach [9].

The search strategy for various databases is detailed in Web Appendix 2, and the results are summarized in Fig. 1. We screened 24258 records, of which 177 were potentially eligible. Of these 107 references were excluded and 62 publications (41 studies) were included in the final analyses [10-71]. Six studies (8 publications) were ongoing [72-79].

Fig. 1 The PRISMA flow chart.

The 41 included studies (Web Table I) reported data on 113055 children. Thirty-three trials were cluster randomized controlled trials, four were CBA studies, and the remaining four were cluster non-randomized controlled trials. Twenty trials were conducted in Africa, 17 in Asia and 4 in Latin America. Twenty-three trials included infants or preschool children (age <5 years), while the remaining included older children as well. The intervention was hygiene promotion and education in 15 trials, improvement in water supply, quality and storage in 10 trials, and improvement in sanitation in 7 trials. All three components of WASH intervention (water, sanitation and hygiene) were studied in 4 trials. Water and sanitation improvement was studied in one trial, and sanitation and hygiene in one study. Three trials had multiple comparison groups and yielded different combinations of interventions for analysis.

Web Fig. 1 and Web Fig. 2 summarize the Risk of Bias for the included studies. The risk of bias for random sequence generation was low for the 33 cluster randomized controlled trials, unclear or high for two non-randomized controlled trials, and high for the remaining six studies. The risk of bias for allocation concealment was judged to be low in six, unclear in eight and high in the remaining studies. Attrition was high or unequal in the intervention and the control groups in eleven trials (high risk of bias), unclear for two trials, and low for the remaining 28 trials. Four trials were considered to be at high risk of bias on account of baseline imbalance of clusters, whereas the risk of bias was unclear for three trials, and low for remaining 34 trials. The cluster effect was not taken into account while doing the statistical analyses in six trials, and these were considered to be at high risk of bias for unit of analysis error.

Comparison 1: Hygiene vs. No Intervention (17 trials; 82456 participants) (Table I and Web Appendix 3A)

TABLE I 	Effect of Hygiene Interventions (vs No Intervention) on Anthropometry, Nutritional Status, 
and Non-Diarrheal Morbidity and Mortality

For anthropometry, one trial [66] enrolling 1272 participants showed no evidence of difference (very low quality evidence) in the change in anthropometry (weight, height, Z scores) between intervention and control groups (Table I). Two studies [16,66] evaluated the weight-for-age after long-term follow-up. Pooled analyses (no significant heterogeneity; I²=0%, P=0.9) showed no difference (very low quality evidence) in weight-for-age or height-for-age. One trial [16] studied the impact of hygiene on BMI Z-score on follow-up and reported no change (very low quality evidence). The impact of hygiene interventions on other outcomes are also presented in Table I. The number of episodes of ARI were 24% lower in the hygiene intervention group (P=0.03; 6 trials, moderate quality evidence) (Fig. 2) [26,44, 50,63,65,70]. Similar benefits were also observed for cough (P=0.006; low quality evidence) [63], and laboratory confirmed influenza (P<0.001; very low quality evidence) [70]. Meta-analyses of data from four trials [50,54,58,70] showed that hygiene intervention reduced absence from school in children by 22% (P<0.001; moderate quality evidence). There was no evidence of any effect of hygiene intervention on mortality in children (P=0.38; low quality evidence).

Fig. 2 Forest plot of effect of Hygiene intervention versus no Intervention on incidence of acute respiratory infections (episodes/person-week).

TABLE II	Effect of Interventions Focusing on Improvement in Water Supply or Distribution (vs No Intervention) 
on Anthropometry, and Non-diarrheal Morbidity and Mortality 

Table II presents the results of the effect of improvement in water quality and supply on various outcomes in children. Limited data from individual studies indicated marginal improvement in anthropometry, but no evidence of any significant benefit in reduction of morbidities or school absenteeism. Five trials [25,27,29,32,53] with water intervention reported on mortality data, showing a reduction in mortality by more than 50% (P=0.007; very low quality of evidence) (Fig. 3 and Web Appendix 3B).

Fig. 3 Forest plot of effect of Water intervention on mortality.

TABLE III Effect of Sanitation Interventions (vs No Intervention) on Anthropometry, 
Nutritional Status, and Non-diarrheal Morbidity and Mortality

Table III presents the effect of improvement in sanitation on various outcomes. Data from individual studies did not show any significant positive effect of sanitation-related interventions on anthropometry of children, but there was a marginal benefit in terms of reduction of prevalence of underweight, wasting and stunting [13,56]. There was no evidence of significant effect on morbidity or mortality (Fig. 4 and Web Appendix 3C) [23,56,69].

Fig. 4 Forest plot of effect of Sanitation versus no intervention on mortality (<10 years).

TABLE IV	Effect of Combined (Water, Sanitation or Hygiene) Interventions (vs No Intervention) on 
Anthropometry, Nutritional Status, Non-diarrheal Morbidity and Mortality

TABLE V	Effect of Any (Water, Sanitation or Hygiene) Intervention (vs No Intervention) on 
Anthropometry and Nutritional Status of Children

Table IV shows the magnitude of the effect in studies where more than one WASH interventions were delivered. Data on two of the WASH interventions were available only from individual studies [16,28,33,36,37,60], which did not document any significant impact on anthropometry or morbidity. Table V compares the effect of any of the WASH intervention (in comparison to no intervention) on child health outcomes. There was no evidence of any significant difference in the anthropometry (weight, height, BMI, Z scores) between the intervention and control groups, but the prevalence of underweight (Fig. 5), wasting and stunting (Fig. 6) was significantly less in intervention group [11,13,56,60].

Fig. 5 Forest plot of effect of any WASH Intervention on risk of underweight (low weight-for-age).

Fig. 6 Forest plot of effect of any WASH Intervention on risk of stunting (low height-for-age).

In this systematic review of 41 trials with WASH interventions, incorporating data on 113055 children, there was no evidence of effect of hygiene intervention on anthropometry. However, hygiene intervention reduced the risk of developing acute respiratory infections by 24%, cough by 10%, laboratory-confirmed influenza by 50%, and conjunctivitis by 51%. There was low quality evidence to suggest no impact of intervention on mortality. Improvement in water supply and quality was associated with slightly higher weight-for-age Z-score without any evidence of impact on other anthropometric measures, non-diarrheal morbidity or school absenteeism. There was very low quality evidence to suggest about 55% reduction in mortality. Improvement in sanitation had a variable effect on the anthropometry in children; no positive effect on anthropometric measures but there was a reduction in risk of wasting, stunting and underweight. Individual studies on combination of two WASH interventions did not document any significant benefit in terms of child anthropometry or morbidity. Combined water, sanitation and hygiene intervention improved height-for-age Z-scores and decreased the risk of stunting. Any WASH intervention (considered together) resulted in lower prevalence of malnutrition (underweight, stunting and wasting).

Most studies in this review involved study populations from LMIC with high prevalence of malnutrition and infectious morbidities; these settings are expected to benefit from WASH interventions in case of a true effect. Although the nature of interventions under each heading varied among trials, control groups in most trials were comparable with intervention groups at baseline. Thus any observed effects in the intervention groups are more likely to be attributable to the WASH strategy than to spontaneous improvements noted over time. Evidence from these trials is largely applicable to real-life situations among populations in LMIC.

Most of the studies included in this review did not have good methodological quality on some criteria. WASH is a complex intervention, and conducting field trials to evaluate its impact is challenging. By its very nature, allocation concealment and blinding of participants and observers to the intervention are very tough to execute (although a couple of trials managed to do that). Of the included trials, most were carefully conducted cluster RCTs with low risk of recruitment bias, baseline comparability of clusters, no loss of clusters and appropriate analysis. Owing to the widely varying nature of interventions, we evaluated the impact of individual group of interventions separately. This also restricted the availability of studies available for quantitative synthesis for most of the outcomes, thus downgrading the certainty of evidence for some of them.

Dangour, et al. [6] assessed the effect of WASH interventions on weight-for-age, weight-for-height and height-for-age Z scores. The studies included in this review were different from ours. Few studies included in this review were excluded for various reasons from the present review. In addition, we included some additional studies. The results were however similar in both the reviews, with no to minimal effect on these indices. Cumming, et al. [80] reviewed the effect of WASH interventions on stunting. However, it was more of a qualitative review, which focused more on observational data, and on the data from an earlier systematic review [6]. The authors suggested that WASH interventions may be effective if introduced before the onset of growth faltering. Diarrheal morbidity and mortality and onset of stunting are more concentrated before two years, and it might be important to focus on this age group to make WASH interventions more effective. A meta-analysis of the effect of hand hygiene on infectious disease risk in the community setting reported a reduction in respiratory illness of 21% (95% CI 5% to 34%) [81]. Rabie, et al. [82] studied the effect of handwashing on respiratory infections. All eight eligible studies reported that handwashing lowered risks of respiratory infection, with risk reductions ranging from 6% to 44% (pooled value 24%). Though none of the studies included in the review by Rabie, et al. [82] were included in the present systematic review because all of these included participants from high-income countries (Australia, Denmark, USA), these estimates are similar to our review. Pruss, et al. [83] reviewed the impact of the various environmental interventions on trachoma reduction. However, this again was a qualitative review with bulk of the evidence emerging from observational studies, and the conclusions cannot be compared with this review.

Evidence from this review suggests that though there is little or no effect of WASH interventions on the anthropometric indices in children from LMIC, they may result in reduction in prevalence of wasting, stunting and underweight. Moreover, WASH interventions (especially hygiene intervention) are probably associated with lower risk of non-diarrheal morbidity. There are several ongoing trials on these interventions, which may alter the conclusions and improve the quality of evidence available till date. Nevertheless, these potential health benefits lend support to the ongoing efforts for provision of safe and adequate water supply, sanitation and hygiene. Future studies from varied settings need to focus on long-term benefits and other important outcomes necessary for decision-making, including the effect on micronutrient status, equity aspects and cost effectiveness.

Contributors: TG: conceptualized the review, literature search, data analysis and manuscript writing; DS: literature search data analysis and interpretation, and manuscript writing; HPS: conceptualized the review, data analysis and its interpretation, and critical inputs into manuscript writing.

Funding: Department of Health Research, Ministry of Health & Family Welfare, Government of India.

Competing interests: None stated.

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