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      ‘Fit for school’ – a school-based water, sanitation and hygiene programme to improve child health: Results from a longitudinal study in Cambodia, Indonesia and Lao PDR


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          The Fit for School (FIT) programme integrates school health and Water, Sanitation and Hygiene interventions, which are implemented by the Ministries of Education in four Southeast Asian countries. This paper describes the findings of a Health Outcome Study, which aimed to assess the two-year effect of the FIT programme on the parasitological, weight, and oral health status of children attending schools implementing the programme in Cambodia, Indonesia and Lao PDR.


          The study was a non-randomized clustered controlled trial with a follow-up period of two years. The intervention group consisted of children attending public elementary schools implementing the FIT programme, including daily group handwashing with soap and toothbrushing with fluoride toothpaste, biannual school-based deworming; as well as construction of group handwashing facilities. Control schools implemented the regular government health education curriculum and biannual deworming. Per school, a random selection of six to seven-year-old grade-one students was drawn. Data on parasitological infections, anthropometric measurements, dental caries, odontogenic infections and sociodemographic characteristics were collected at baseline and at follow-up (24 months later). Data were analysed using the χ 2-test, Mann Whitney U-test and multilevel logistic and linear regression.


          A total of 1847 children (mean age = 6.7 years, range 6.0–8.0 years) participated in the baseline survey. Of these, 1499 children were available for follow-up examination – 478, 486 and 535 children in Cambodia, Indonesia and Lao PDR, respectively. In all three countries, children in intervention schools had a lower increment in the number of decayed, missing and filled permanent teeth between baseline and follow-up, in comparison to children in controls schools. The preventive fraction was 24% at average. The prevalence of soil-transmitted helminth infection (which was unexpectedly low at baseline), the prevalence of thinness and the prevalence of odontogenic infections did not significantly differ between baseline and follow-up, nor between intervention and control schools.


          The study found that the FIT programme significantly contributed to the prevention of dental caries in children. This study describes the challenges, learnings and, moreover, the importance of conducting real-life implementation research to evaluate health programmes to transform school settings into healthy learning environments for children.

          The study is retrospectively registered with the German Clinical Trials Register, University of Freiburg (Trial registration number: DRKS00004485, date of registration: 26th of February, 2013).

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          Most cited references39

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          Development of a WHO growth reference for school-aged children and adolescents

          OBJECTIVE: To construct growth curves for school-aged children and adolescents that accord with the WHO Child Growth Standards for preschool children and the body mass index (BMI) cut-offs for adults. METHODS: Data from the 1977 National Center for Health Statistics (NCHS)/WHO growth reference (1-24 years) were merged with data from the under-fives growth standards' cross-sectional sample (18-71 months) to smooth the transition between the two samples. State-of-the-art statistical methods used to construct the WHO Child Growth Standards (0-5 years), i.e. the Box-Cox power exponential (BCPE) method with appropriate diagnostic tools for the selection of best models, were applied to this combined sample. FINDINGS: The merged data sets resulted in a smooth transition at 5 years for height-for-age, weight-for-age and BMI-for-age. For BMI-for-age across all centiles the magnitude of the difference between the two curves at age 5 years is mostly 0.0 kg/m² to 0.1 kg/m². At 19 years, the new BMI values at +1 standard deviation (SD) are 25.4 kg/m² for boys and 25.0 kg/m² for girls. These values are equivalent to the overweight cut-off for adults (> 25.0 kg/m²). Similarly, the +2 SD value (29.7 kg/m² for both sexes) compares closely with the cut-off for obesity (> 30.0 kg/m²). CONCLUSION: The new curves are closely aligned with the WHO Child Growth Standards at 5 years, and the recommended adult cut-offs for overweight and obesity at 19 years. They fill the gap in growth curves and provide an appropriate reference for the 5 to 19 years age group.
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            Global burden of childhood pneumonia and diarrhoea

            Summary Diarrhoea and pneumonia are the leading infectious causes of childhood morbidity and mortality. We comprehensively reviewed the epidemiology of childhood diarrhoea and pneumonia in 2010–11 to inform the planning of integrated control programmes for both illnesses. We estimated that, in 2010, there were 1·731 billion episodes of diarrhoea (36 million of which progressed to severe episodes) and 120 million episodes of pneumonia (14 million of which progressed to severe episodes) in children younger than 5 years. We estimated that, in 2011, 700 000 episodes of diarrhoea and 1·3 million of pneumonia led to death. A high proportion of deaths occurs in the first 2 years of life in both diseases—72% for diarrhoea and 81% for pneumonia. The epidemiology of childhood diarrhoea and that of pneumonia overlap, which might be partly because of shared risk factors, such as undernutrition, suboptimum breastfeeding, and zinc deficiency. Rotavirus is the most common cause of vaccine-preventable severe diarrhoea (associated with 28% of cases), and Streptococcus pneumoniae (18·3%) of vaccine-preventable severe pneumonia. Morbidity and mortality from childhood pneumonia and diarrhoea are falling, but action is needed globally and at country level to accelerate the reduction.
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              Water, Sanitation, Hygiene, and Soil-Transmitted Helminth Infection: A Systematic Review and Meta-Analysis

              Introduction More than a billion people are infected with soil-transmitted helminths (STHs) and many more live in high risk areas [1]. The global burden of STH infection is estimated at between 5 and 39 million disability-adjusted life years, largely attributable to anemia, stunting, and reduced cognitive development [2]–[4]. Humans are infected after ingesting eggs (A. lumbricoides and T. trichiura) or through penetration of the skin by infective larvae in the soil (hookworm [A. duodenale and N. americanus] and S. stercoralis) [1]. Current control strategies have focused on preventive chemotherapy through mass drug administration (MDA), in which at-risk populations are treated once or twice per year with benzimidazoles, primarily albendazole (usually given as a single oral dose of 400 mg) or mebendazole (500 mg) [5]. While preventive chemotherapy can greatly reduce morbidity from helminth infection, reinfection typically occurs rapidly after treatment [6]. Long-term STH control and eventual elimination require improvements to water, sanitation, and hygiene (WASH) access and practices [7]. The history of STH in the United States of America, South Korea, and Japan—where WASH improvements acted in concert with deworming to eliminate STH as a public health problem—supports the need for an integrated control paradigm [8]–[10]. WASH interventions are diverse, potentially including improvements in water access (e.g., water quality, water quantity, and distance to water), sanitation access (e.g., access to improved latrines, latrine maintenance, and fecal sludge management), and hygiene practices (e.g., handwashing before eating and/or after defecation, water treatment, soap use, wearing shoes, and water storage practices) [11]–[20]. Interventions often include multiple components, e.g., building ventilated-improved pit latrines while also providing hygiene education. Work in the WASH sector is often motivated by the view that access to clean water and adequate sanitation is a human right, but health outcomes are also broadly considered, with diarrheal disease burden representing a common measure of impact [21]–[23]. The successful integration of WASH into a disease control program has already been demonstrated for trachoma, which—like STH—is also considered a neglected tropical disease (NTD). The World Health Organization (WHO) endorses the “SAFE” strategy for trachoma control: surgery to correct advanced stages of trachoma, antibiotics to treat active infection, facial cleanliness to reduce disease transmission, and environmental change (including increased access to water and improved sanitation) [24]. The SAFE strategy explicitly calls for the implementation of improved access to, and use of, water, sanitation, and hygiene through improvements in delivery and/or specific interventions. Such a fully integrated strategy—including guidelines and targets—does not yet exist for STH control, in part because evidence examining the relationship between WASH and STH is limited. A seminal review by Esrey and colleagues found few investigations that evaluated the association between WASH and STH infection [25]. A recent systematic review and meta-analysis by Ziegelbauer and colleagues found that individuals who have access to and use of sanitation facilities were at lower odds of infection with STH compared to individuals without sanitation [26]. Additional empirical evidence that links WASH improvements to reductions in STH infection is scarce, and an improved evidence-base may lead to better coordination between the NTD and WASH sectors [27],[28]. To fill this gap, we conducted a systematic review and set of meta-analyses to examine evidence of association between STH infection and WASH. We expanded the study's focus to include up-to-date meta-analyses for water and hygiene components, in addition to sanitation. We only used adjusted effect estimates in meta-analyses to help account for potential confounding and followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for systematic reviews. Our use of the Grades of Recommendation, Assessment, Development and Evaluation (GRADE) approach for quality assessment also provides a comprehensive accounting of the limitations of available evidence. We hypothesized that improvements in WASH would be associated with reductions in odds of STH infection. Thus, the purpose of this study was to quantitatively summarize the relationship between WASH access or practices on STH infection, while also synthesizing available data that did not qualify for meta-analysis. Methods Search Strategy, Inclusion Criteria, and Data Extraction Our review adheres to the PRISMA and Meta-analysis of Observational Studies in Epidemiology (MOOSE) reporting guidelines (see Texts S1 and S2) [29]–[31]. The methods protocol is available in Text S3. A study investigator (ECS) and two research assistants (Rachel Stelmach [RS] and Claire Still [CS]) systematically searched PubMed, Embase, Web of Science, and LILACS for relevant articles from inception to October 28, 2013. We also indexed relevant studies from the bibliography of reviews by Ziegelbauer and colleagues [26] and Asaolu and Ofoezie [32]. Abstracts without published articles were considered eligible for inclusion. Additionally, we requested available unpublished research from the US Centers for Disease Control and Prevention, The Carter Center, The Task Force for Global Health, the WHO regional offices, and the authors' personal collections. The native search engines within PubMed, Embase, Web of Knowledge, and LILACS were used to search each respective database using Boolean operators. The search included two clusters of terms: one for STH (i.e., helminth, soil-transmitted helminth, geohelminth, ascaris, lumbricoides, trichuris, trichiura, hookworm, ancylostoma, duodenale, necator, americanus, strongyloid*, stercoralis) and one for WASH (i.e., sanitation, sanitary engineering, water supply, waste management, environment*, excre*, faec*, fecal, feces, hand washing, handwashing, hygiene, latrine*, toilet*, water, soap). Results had to contain at least one term from both clusters. “Extensive search” was enabled when searching with Embase. Because Embase only allowed for exporting up to 5,000 records, results were stratified by date in order to screen and export all results in smaller segments. All search records were exported to bibliographic files and imported into Endnote X5 (Thomson Reuters), which was used to manage and screen search results. Titles, and when available, abstracts were scanned by an investigator (ECS) and also independently by research assistants (RS and CS) to determine possible relevance. Final selection was based on the full text of all potentially applicable articles. Ambiguous articles were examined by a senior reviewer (MCF). Publications in all languages were considered. Studies in English, Spanish, Portuguese, and French were screened by investigators directly. Chinese-language articles were reviewed by a study collaborator (Shuyuan Huang [SH]) who assessed eligibility and extracted relevant data for the research team. Relevant data from all eligible studies was abstracted by a reviewer (ECS) and independently by assistants (RS and CS). Extracted data included study design, setting, year, population characteristics, WASH components measured, diagnostic approach, STH species, and relevant effect measures. Odds ratios (ORs) served as the primary effect measure in the reviewed literature. We collected both crude and adjusted estimates if available. Excel 2007 (Microsoft) was used to input and manage data using a long format to accommodate multiple effect estimates per study. An article was eligible for inclusion if it presented a measure of effect between WASH and STH (e.g., an OR). For studies that pooled multiple intestinal parasites (e.g., Giardia intestinalis and STH) into one outcome measure, we contacted authors to request disaggregated data. We did not exclude studies based on methodology or population characteristics. Studies that evaluated multiple WASH components were included, as long as the components could be assessed separately from deworming medications and other non-WASH interventions. There are few standard definitions for WASH access and practices, and it is difficult to measure WASH behaviors objectively [33]. We were unable to consistently connect water and sanitation variables reported in retrieved studies to the WHO and UNICEF Joint Monitoring Program's water and sanitation ladder definitions [34],[35]. For this review, “treated water” is defined as the use of any chemical or physical treatment of water to change its potability, whether conducted at the source or at the point of use. Two specific forms of treatment included boiling and filtering water at home. “Piped water” describes access to, or use of, water collected from a piped infrastructure, regardless of where the water is accessed (public/private) or how well maintained the infrastructure may be. “Sanitation access” was our primary sanitation exposure, defined as access to, or use of, any latrine. We did not exclude studies that lacked information about latrine quality, so access to sanitation could refer to anything from simple pit latrines to flush toilets. For hygiene, “washing after defecation” refers to the availability of handwashing resources (e.g., a wash basin) near sanitation facilities or reported handwashing behavior after defecation. “Soap use or availability” could refer to washing with water alone or no washing as the comparison group. Further, these definitions do not incorporate any criteria for compliance or consistency, since such details were rare in retrieved literature. Statistical Methods We conducted meta-analyses for groups of effect estimates that related similar WASH access or practices (e.g., latrine availability and/or use became “sanitation access”) to a common outcome. Potential outcomes included infection with a specific STH (i.e., A. lumbricoides, T. trichiura, hookworm, and S. stercoralis) or any STH generally. Note that “any STH” reflected infection with an individual species or co-infection with multiple species when authors reported aggregated STH infection results. Meta-analyses were performed for groups of independent effect estimates that numbered three or greater and shared a similar exposure and infection outcome. A study that measured several WASH components could contribute to multiple meta-analyses, but could only supply one effect estimate for any single meta-analysis. We employed random-effects models to account for the expected heterogeneity between studies [36]. Only adjusted estimates were utilized to limit the impact of confounding on pooled effect measures [37]. When necessary, we inverted estimates to reflect the effect of WASH, rather than the absence of WASH. This inversion was necessary in order to ensure enough study estimates were available for meta-analysis, but could have resulted in additional heterogeneity. For example, the inverse of “no sanitation access” may be similar to, but distinct from, “sanitation access” when assessed by questionnaire due to bias associated with socially desirable responses. Further, the presence of WASH access or practices may not necessarily be the same as the inverse effect of their absence, especially if important confounders or effect modifiers remain unexplored. Estimates of effect not included in meta-analyses were summarized in the text. The meta-analysis package MAIS for Stata version 12 (StataCorp) was used to perform the random-effects meta-analyses with the DerSimonian and Laird method [38]. The natural log of reported ORs was the dependent variable. CIs use the 95% level unless otherwise noted. Bias Assessment and Evidence Quality We used the GRADE framework to assess potential sources of bias within studies and determine overall strength of evidence for each meta-analysis [39]. The GRADE approach is used to contextualize or justify intervention recommendations with four levels of evidence quality, ranging from very low to high. These levels correspond to how likely it would be for further research to alter conclusions drawn from the current evidence. “High quality” suggests that it is very unlikely for conclusions about effect estimates to change, whereas “very low quality” suggests that any estimate of effect is highly uncertain [40]. We formed our key bias categories from the literature, GRADE recommendations [41], and two instruments highlighted by the Cochrane Collaboration [42]: the Downs and Black tool [43] and the Newcastle-Ottawa scale [44]. We focused on five potential sources of bias in our assessment of individual studies: (i) diagnostic approach for assessing STH infection; (ii) exposure assessment; (iii) confounding assessment; (iv) response rate; and (v) selective reporting. Each study received one of three rankings for each source of bias: low risk, unclear risk, or high risk. Detailed criteria for these categories are available in Table 1. Bias was assessed independently by ECS and one of the two research assistants (RS and CS), compared, and reviewed by a senior assessor (DGA or MCF) if necessary. 10.1371/journal.pmed.1001620.t001 Table 1 Criteria for study bias assessment. Criteria Description Infection diagnostics Is a diagnostic assay clearly mentioned? Is there any form of quality control in the diagnostic process (e.g., a senior technician doing spot-checks)? Exposure assessment Was exposure assessment (e.g., access to clean water, washing hands) ascertained via a self-reported survey response (unreliable) or observed directly by investigators (more reliable)? Is there any attempt to gauge proper use of water, hygiene, or some form of “quality control” for the exposures? Confounding assessment Are only crude estimates computed? Has matching and/or multiple logistic regression been undertaken to control for important potential confounders? Response rate Is the response rate (or loss-to-follow-up) similar for infected versus non-infected individuals? Selective reporting Is there evidence of selective reporting within an article (e.g., outlining certain variables of interest in the methods but not providing any data on them in the results)? We assessed the overall quality of evidence for each meta-analysis after considering seven key characteristics. Each meta-analysis could receive a quality grade of very low, low, moderate, or high [45]. Meta-analyses of observational studies were classified as “low” by default, but could be downgraded (because of imprecision, indirectness, inconsistency, publication bias, and potential confounding) or upgraded (because of magnitude of effect, dose-response relationship, and potential confounding) on the basis of the overall strength of the evidence. Inconsistency (i.e., heterogeneity) was assessed with Moran's I 2 and Cochran's Q-test [46]. I 2 provides an estimate of the proportion of variability in a meta-analysis that is explained by differences between the included studies instead of sampling error [47]. If a study exhibited an I 2 value over 50%, there was potential cause for concern, and the Q-test was also checked for a p-value less than 0.10. Values for I 2 over 70% or Q-test p-values lower than 0.05 resulted in the automatic downgrading of a body of evidence. Publication bias was assessed through a visual inspection of funnel plots, though Egger's test also informed our interpretation [48]. Evidence quality was downgraded due to “imprecision” if the pooled effect estimate's 95% CI overlapped with the null (i.e., statistical significance at the 0.05 level). Although we provide CIs for pooled point estimates, imprecision remains a valuable criterion since not all consumers of reviews understand the importance of CIs and statistical uncertainty. Evidence quality was upgraded owing to large magnitude of effect if the meta-analysis yielded a pooled OR less than 0.33 or greater than 3.0 [41]. Traditionally, risk ratios (RRs) are considered to show a large magnitude if they are less than 0.5 or greater than 2.0. However, ORs overstate the effect size compared to RRs, especially when initial risk (i.e., the prevalence of the outcome of interest) is high [49]. Because STH infection is relatively common, a more conservative threshold was needed for ORs in order to qualify as a large magnitude of effect. Evidence quality could also be upgraded or downgraded on the basis of any unaccounted sources of potential confounding that would likely have a predictable direction on the effect estimate. For example, hygiene behaviors are typically over-reported in surveys, which could reduce the measured strength of effect for hygiene practices since the exposure group includes those who did not practice hygiene [50]–[52]. Due to the breadth of the review, indirectness was not a common concern, but would be more important for future reviews that focus on specific populations, settings, or interventions. Dose-response relationships were assessed by examining studies where exposures were discretized into ranked categories, e.g., analyzing “always washes hands” versus both “sometimes” and “never.” A dose-response relationship was considered possible if the point estimates improved between the ordinal categories, especially if relevant CIs did not overlap. Additional details about the meta-analysis GRADE criteria are available in Table 2. 10.1371/journal.pmed.1001620.t002 Table 2 Criteria for meta-analysis GRADE assessment. Criteria Description Imprecision Caused the evidence quality to be downgraded if the pooled effect estimate's 95% CI overlapped with the null (i.e., one for odds ratios). In this context, imprecision is synonymous with a pooled estimate being statistically non-significant at the 0.05 level. Imprecision is used to downgrade evidence quality because some consumers of reviews (e.g., policymakers and practitioners) often do not fully understand statistical uncertainty. Indirectness Did not cause any evidence quality to be downgraded. Our review had a broad scope that aimed to collect a wide array of evidence exploring different populations and contexts. Traditionally, indirectness refers to issues that may limit the generalizability of evidence's reported results to the review's specified research question. This could be caused by differences in study population, study design, co-interventions, etc. Inconsistency (i.e., heterogeneity) Assessed with Moran's I 2 and Cochran's Q-test [46]. If a study exhibited an I 2 value over 50%, there was potential cause for concern, and the Q-test was also checked for a p-value less than 0.10. Values for I 2 over 70% or Q-test p-values lower than 0.05 resulted in the downgrading of a body of evidence. Publication bias Assessed through a visual inspection of funnel plots, though Egger's test also informed our interpretation [48]. Detecting publication bias is difficult when dealing with dichotomous outcomes, especially when there is significant between-study heterogeneity. In such circumstances, the popular Egger's test is usually inappropriate, with the potential to result in many false positives. For this reason, qualitative funnel plot analysis served as our primary assessment tool, though we also computed Egger's statistics to inform our judgment. Tests described by Rücker et al. [135] and Peters et al. [136] were also considered, but not performed. A large magnitude of effect (also called “effect size”) Could upgrade overall evidence quality if pooled odds ratios were less than 0.33 or greater than 3.0 [41]. The standard criteria for risk ratios and hazard ratios is that effect estimates be less than 0.5 or greater than 2.0. However, since odds ratios will show a greater magnitude than risk ratios, especially when an outcome is common, a more conservative cut-off value is needed. No firm rules have been established in the literature, so we increased the relevant effect size magnitude for odds ratios by 50%. Evidence of a dose-response relationship Can upgrade evidence quality. Dose-response relationships were assessed by examining studies where exposures were discretized into ranked categories, e.g., analyzing “always washes hands” versus both “sometimes” and “never.” A dose-response relationship was considered possible if the point estimates improved between the ordinal categories, especially if relevant confidence intervals did not overlap. Potential confounding Can upgrade a body of evidence if there are plausible factors that may be artificially weakening the observed pooled measurement. In the case of hygiene, individuals are known to overreport handwashing behaviors, which would systematically lower any apparent benefits. Potential downgrades are also possible, however, especially if established confounding variables are not taken into account by an analysis. Results Retrieved Studies The search yielded a total of 47,589 articles from PubMed (n = 21,718), Embase (n = 18,188), Web of Knowledge (n = 7,502), and LILACS (n = 181), with 42,882 unique records. Our PRISMA flow diagram is available in Figure 1. After reviewing titles and abstracts, we examined 397 articles more intensively: 264 were excluded for lacking a relevant effect measure, 30 were excluded for aggregating non-STH infections in the outcome, and 11 were excluded for being review or editorial articles (see Tables 3–5 for included studies and S1 for excluded ones). We contacted 11 authors to obtain additional data [53]–[60], but only three authors responded [61]–[63]. A total of 94 studies ultimately met our inclusion criteria, yielding over 450 estimates of effect. Retrieved data included findings from one unpublished investigation [64] and one publication with information about two related studies [65]. 10.1371/journal.pmed.1001620.g001 Figure 1 PRISMA flow diagram. 10.1371/journal.pmed.1001620.t003 Table 3 List of included studies with authors A–F. Author [cite ID], Year - Country Title of Article Setting and Population Sample Size Diagnosis Method Exposure Assessment and Study Method Main WASH Components Adjustment or Controlled Variables Ahmed [111], 2011 - Malaysiaa The burden of moderate-to-heavy soil-transmitted helminth infections among rural malaysian aborigines: an urgent need for an integrated control programme Satak, Raub district, Pahang-Sekolah Kebangsaan Satak school; Aboriginal schoolchildren, 6–13 years old 254 Kato-Katz and Harada Mori Questionnaire, cross-sectional Toilet, water source, playing in soil Source of drinking water, toilet in house, domestic animals in the house, age, playing barefoot in soil Aimpun [113], 2004 - Belizea Survey for intestinal parasites in Belize, Central America 5 villages in the Toledo district; all ages, Ketchi and Mopan ethnic groups 533 Formalin-ethyl-acetate concentration technique Questionnaire, cross-sectional Handwashing, shoes, water, latrine Race, occupation, years of education, population density, presence of trash pit near home, drinking water source, water treatment, and ownership of electrical appliances Alemu [137], 2011 - Ethiopia Soil transmitted helminths and schistosoma mansoni infections among school children in Zarima town, northwest Ethiopia Elementary school children from Zarima town in NW Ethiopia 319 Kato-Katz Questionnaire, observation, cross-sectional Handwashing, shoe wearing, presence of latrine, latrine usage, water source No adjusted WASH effect estimates identified Al-Mekhlafi [138], 2007 - Malaysia An unceasing problem: soil-transmitted helminthiases in rural malaysian communities 18 villages around Pos Betau School, Kuala Lipis; Primary schoolchildren (7–12) of Pos Betau School, Kuala Lipis, Pahang, Malaysia. 277 Kato-Katz and Harada Mori Questionnaire, cross-sectional Latrine availability, water access No adjusted WASH effect estimates identified Al-Mekhlafi [139], 2008 - Malaysia Pattern and predictors of soil-transmitted helminth reinfection among aboriginal schoolchildren in rural Peninsular Malaysia Pos Betau, Kuala Lipis, Pahang; Orang Asli (aborigine) primary schoolchildren, age 7–12 120 Modified cellophane thick smear and Harada Mori Questionnaire, longitudinal Toilet, water source No adjusted WASH effect estimates identified Alvarado [85], 2006 - Colombia Social determinants, feeding practices and nutritional consequences of intestinal parasitism in children 7–18 months old in Guapi, Cauca Guapi, Cauca; children 7–18 months old 136 Direct examination and concentrate Ritchie-Frick modified Questionnaire, cross-sectional Latrine type, floor type No adjusted WASH effect estimates identified Amahmid [140], 2005 - Morocco Assessment of the health hazards associated with wastewater reuse: transmission of geohelminthic infections (Marrakech, Morocco) Children (2–14 years) near Marrakech, Morocco 610 Formol-ether concentration Questionnaire, observation, cross-sectional Source of water No adjusted WASH effect estimates identified Asaolu [123], 2002 - Nigeriaa Effect of water supply and sanitation on the prevalence and intensity of Ascaris lumbricoides among pre-school-age children in Ajebandele and Ifewara, Osun State, Nigeria. Ajebandele and Ifewara, two peri-urban communities near Ile-Ife, Osun State, Nigeria; children aged 0 to 108 months from mix of different ethnic groups 516 Kato-Katz (modified) Questionnaire, cross-sectional Latrine type, water source Final, full model not given. Used stepwise selection in multiple regression. Initial model included: village, water source, latrine type, mothers' age and education, fathers' age and education, and gender/age of the child Awasthi [141], 2008 - India Prevalence and risk factors associated with worm infestation in pre-school children (6–23 months) in selected blocks of Uttar Pradesh and Jharkhand, India Preschool children (6–23 months) from Uttar Pradesh and Jharkhand, India 909 Formol-ether concentration Questionnaire, cross-sectional Drinking water source, toilets in home, washing hands after defecation No adjusted WASH effect estimates identified Balen [131], 2011 - Chinaa Risk factors for helminth infections in a rural and a peri-urban setting of the Dongting Lake area, People's Republic of China Wuyi and Laogang, two administrative villages in the Dongting Lake region of Hunan province; all ages from Wuyi, a rural village 1,298 Kato-Katz Questionnaire, cross-sectional Handwashing, water source Village, occupation, socio-economic status, soil contact, animal ownership, washing hands w/soap before eating/after defecating Barreto [142], 2010 - Brazil Impact of a citywide sanitation program in Northeast Brazil on intestinal parasites infection in young children Children (0–36 months) from Salvador, Brazil 1,920 Kato-Katz Questionnaire, observation, cross-sectional Regularity of water supply, hygiene behavior, indoor toilet, household excreta disposal Different variables depending on model, but could include: drainage type, regularity of water supply, absence of rubbish dumps, paved road/sidewalk, hygiene behavior, indoor toilet, open sewage nearby, household excreta disposal, coverage with program sewerage connections Basualdo [143], 2007 - Argentina Intestinal parasitoses and environmental factors in a rural population of Argentina, 2002–2003 Children ( 15 years old (adults) 126 Kato-Katz Questionnaire, cross-sectional Latrine use, shoes Age, gender, and community. Ivan [116], 2013 - Rwandaa Helminthic infections rates and malaria in HIV-infected pregnant women on anti-retroviral therapy in Rwanda HIV-positive pregnant women 980 Kato-Katz Questionnaire, cross-sectional Water source, shoe wearing, washing hands after defecation ART, employment, handwashing, CD4 count Jiraanankul [133], 2011 - Thailanda Incidence and Risk Factors of Hookworm Infection in a Rural Community of Central Thailand Tungsor Hongsa community, Chachoengsao Province, 228 km east of Bangkok, Thailand; all ages 585 Kato-Katz, water-ethyl acetate sedimentation technique Questionnaire, longitudinal Latrine use, shoes, washing hands Age, raising cats or buffalo Khieu [87], 2013 - Cambodia Diagnosis, Treatment and Risk Factors of Strongyloides stercoralis in Schoolchildren in Cambodia Semi-rural villages in Kandal province; Primary school children 458 Kato-Katz, KAP culture, and Baermann technique Questionnaire, cross-sectional Sanitation, handwashing, shoes No adjusted WASH effect estimates identified Knopp [125], 2011 - Zanzibara From morbidity control to transmission control: time to change tactics against helminths on Unguja Island, Zanzibar Individuals on the island of Unguja 2,858 Kato-Katz, koga agar plate method (KAP), and Baermann technique (BM) Questionnaire, interview, cross-sectional Latrine at home, washing hands before eating, washing hands after defecation Sex, age, and village Kounnavong [68], 2011 - Lao PDR Soil-transmitted helminth infections and risk factors in preschool children in southern rural Lao People's Democratic Republic Three rural remote districts of Savannakhet Province in southern Lao PDR; Pre-school children aged 12–59 months 570 Kato-Katz Questionnaire, cross-sectional Latrine access, improved water access No adjusted WASH effect estimates identified Koura [160], 2011 - Benin Prevalence and risk factors for soil-transmitted helminth infection in Beninese women during pregnancy Pregnant women at two maternity wards 300 Kato-Katz Questionnaire, cross-sectional Wearing shoes No adjusted WASH effect estimates identified Lee [161], 2007 - Brunei Hookworm infections in Singaporean soldiers after jungle training in Brunei Darussalam Singaporean soldiers returning from jungle training in Brunei Darussalam 113 Fecal screens via microscopy Questionnaire, interview, cross-sectional Water supply source, crawling on ground/soil, shoe use No adjusted WASH effect estimates identified Luoba [162], 2005 - Kenya Earth-eating and reinfection with intestinal helminths among pregnant and lactating women in western Kenya Pregnant women in Nyanza Province 824 Kato-Katz Interview, prospective cohort (longitudinal intervention) Geophagy No adjusted WASH effect estimates identified Mahmud [127], 2013 - Ethiopiaa Risk factors for intestinal parasitosis, anaemia, and malnutrition among school children in Ethiopia 12 primary schools; School children aged 6–15 600 Kato-Katz and direct saline wetmount, formalin ethyl concentration technique Questionnaire, observations, cross-sectional Latrine, hygiene, water source Age and sex Matthys [71], 2007 - Côte d'Ivoire Risk factors for Schistosoma mansoni and hookworm in urban farming communities in western Côte d'Ivoire Six agricultural zones in the town of Man, western Côte d'Ivoire; Households 716 Kato-Katz Questionnaire, cross-sectional Water source, latrine use Clustering, sex, age, education level, socioeconomic status, household crowding Mihrshahi [128], 2009 - Vietnama The effectiveness of 4 monthly albendazole treatment in the reduction of soil-transmitted helminth infections in women of reproductive age in Viet Nam Women of reproductive age in Yen Bai province 366 Kato-Katz Questionnaire, cross-sectional Sanitary latrine system, shoe use Age, education status, work (inside/outside), number of children, meat consumption, shoe use, latrine type, socio-economic status, and handwashing Moraes [163], 2004 - Brazil Impact of drainage and sewerage on intestinal nematode infections in poor urban areas in Salvador, Brazil Nine poor urban areas of the city of Salvador (pop. 2.44 million), capital of Bahia State, in Northeast Brazil; children aged between 5 and 14 years old 1,893 Kato-Katz Questionnaire, cross-sectional Sanitation Child's sex, child's age, number of children aged 5–14 years in the household, crowding (number of people per room), years of schooling of the household head, monthly per capita income, religion, animals in the house, and the house floor material Moraes [164], 2007 - Brazil [Household solid waste bagging and collection and their health implications for children living in outlying urban settlements in Salvador, Bahia State, Brazil]. Nine peri-urban settlements of the city of Salva-pain, Bahia, Brazil; Children 5–14 years old 1,893 Kato-Katz Questionnaire, longitudinal Solid waste collection Age and sex of the child, number of household members, number of persons/room, monthly family income per capita, religion, presence of lavatory, floor of the home, and excreta disposal of sewage Morales-Espinoza [117], 2003 - Mexicoa Intestinal parasites in children, in highly deprived areas of the border region of Chiapas, Mexico Chiapas, 32 communities; children under 15 years of age 1,148 Faust Method Questionnaire, cross-sectional Water source, latrine Age, overcrowding, living conditions, and educational level a Studies contributed to a meta-analysis. 10.1371/journal.pmed.1001620.t005 Table 5 List of included studies with authors N–Z. Author [cite ID], Year - Country Title of Article Setting and Population Sample Size Diagnosis Method Exposure Assessment and Study Method Main WASH Components Adjustment or Controlled Variables Narain [84], 2000 - Indiaa Prevalence of Trichuris trichiura in relation to socio-economic and behavioral determinants of exposure to infection in rural Assam Dibrugarh district in upper Assam; adults and children aged 5 years old, period of residency, and previous treatment status. Walker [179], 2011 - Bangladesh Individual Predisposition, Household Clustering and Risk Factors for Human Infection with Ascaris lumbricoides: New Epidemiological Insights Dhaka; households 2,929 Ether sedimentation technique Questionnaire, longitudinal Shared latrines, shared water sources, floor material Clustering, age, sex, household socioeconomic status, ethnicity, and household characteristics Wang [112], 2012 - Chinaa Soil-Transmitted Helminth Infections and Correlated Risk Factors in Preschool and School-Aged Children in Rural Southwest China 141 impoverished rural areas of Guizhou and Sichuan Provinces in Southwest China; SAC and Pre-sac (3–5-year-old group and an 8–10-year-old group) 1,707 Kato-Katz Questionnaire, cross-sectional Washing hands, boiling water, latrine type, use of manure fertilizer STH treatment history, individual characteristics, health and sanitation behaviors, and household characteristics Wordemann [97], 2006 - Cubaa Prevalence and risk factors of intestinal parasites in Cuban children San Juan y Martinez and Fomento; Cuban schoolchildren aged 4–14 1,320 Kato-Katz Questionnaire, cross-sectional Water source, latrine use Age, sex, municipality, urban/rural background, and interaction between municipality and urban/rural background Worrell [74], 2013 - Kenya Water, Sanitation, and Hygiene-Related Risk Factors for Soil-Transmitted Helminth Infection in Urban School- and Pre-School-Aged Children in Kibera, Nairobi Kibera; pre-school and school-aged children 676 Kato-Katz (three stools) Questionnaire, observations, cross-sectional Numerous Age, presence of an infected sibling(s) in the household, household crowding, deworming in the last year, ability to meet water needs, treating water, and soap use Xu [75], 2001 - China On cleanliness of hands in diminution of Ascaris lumbricoides infection in children Shaowu, Fujian Province; Children (pupils in preliminary school) 654 Kato-Katz Experimental, longitudinal Handwashing No adjusted WASH effect estimates identified Yajima [180], 2009 - Vietnam High latrine coverage is not reducing the prevalence of soil-transmitted helminthiasis in Hoa Binh province, Vietnam Residents of Tien Xuan commune, Hoa Binh province, Vietnam 155 Kato-Katz Questionnaire, cross-sectional Latrine at home No adjusted WASH effect estimates identified Yori [88], 2006 - Peru Seroepidemiology of strongyloidiasis in the Peruvian Amazon Residents of Santo Tomas, Peru 908 Direct smear, Baermann, simple sedimentation agar plate, serologic assays (ELISA) Questionnaire, cross-sectional Source and storage of drinking water, human waste disposal, wearing of shoes Age Young [82], 2007 - Tanzaniaa Association of geophagia with Ascaris, Trichuris and hookworm transmission in Zanzibar, Tanzania Pemba Island, Zanzibar; pregnant women 970 Kato-Katz Questionnaire, cross-sectional Geophagy, improved sanitation Geophagia during current pregnancy, age, urban/rural, number of durable goods, pit toilet in HH, formal education a Studies contributed to a meta-analysis. HAZ, height for age Z score; SES, socioeconomic status. Most included studies were published in English (n = 86), though articles in Portuguese (n = 4), Chinese (n = 2), and Spanish (n = 2) were also included. Studies researched populations in Asia (n = 42), Africa (n = 29), and the Americas (n = 23). Studies investigated access and practices relating to water (n = 56), sanitation (n = 79), and hygiene (n = 53) (Figure 2); the most commonly explored were access to sanitation (n = 63), access to water (n = 45), handwashing (n = 30), and wearing shoes (n = 27). Studies reported investigating infection with A. lumbricoides (n = 69), T. trichiura (n = 60), hookworm (n = 63), S. stercoralis (n = 12), and any STH collectively (n = 52). Tables 6 and 7 illustrate the number of articles in which both specific WASH components and helminth infections were investigated. 10.1371/journal.pmed.1001620.g002 Figure 2 Retrieved articles by WASH group. 10.1371/journal.pmed.1001620.t006 Table 6 Number of studies (n = 94) that investigated STH species and WASH domains. Studies Water Sanitation Hygiene Water and Sanitation Water and Hygiene Sanitation and Hygiene Water, Sanitation, and Hygiene Any STH (grouped) 34 44 28 32 16 21 15 A. lumbricoides 43 59 37 38 20 30 18 Hookworm 34 53 37 28 17 30 14 T. trichiura 38 52 34 34 20 28 18 S. stercoralis 10 11 6 9 4 5 3 Total (all studies) 56 79 53 49 26 42 23 Each cell indicates the number of reviewed studies that investigated both an STH species (or any STH) and WASH domains. Higher numbers suggest that certain WASH-STH relationships are more commonly explored in the literature. 10.1371/journal.pmed.1001620.t007 Table 7 Number of studies that investigated STH species and WASH access and practices. STH Species Water Sanitation Hygiene Water Access Water Typesa Treat Water Sanit. Access Latrine Typesa Sharing Latrines Latrine Maint. Washing Hands Soap Washing Vegetables Shoe Use Geophagy Hygiene Education Any STH 30b 5 9b 34b 8 3 2 17b 7b 2 13b 4 4 A. lumbricoides 33b 3 15 45b 13 5 2 20b 9 2 14 8 4 Hookworm 28 2 11 44b 11 3 2 16 5 1 20b 8 2 T. trichiura 31b 3 12 41b 12 3 2 18 7 2 12 7 3 S. stercoralis 8 1 5 11 2 1 0 5 2 0 3 1 0 Cells with high numbers but no meta-analysis (no footnote) indicate that effect measures were not reported (selective reporting), reported measures were not statistically adjusted, or that the WASH access and practice was too diverse to be effectively grouped in a meta-analysis (e.g., handwashing can be measured before eating or after defecating). a Water Types and Latrine Types refer to studies that measured multiple sanitation comparisons, not just “latrine versus no latrine.” For example, a study could examine water collected from rivers, wells, or piped connections. b Gray cells indicate that a meta-analysis was conducted for that WASH variable and STH outcome. Of 94 studies, 89 were observational: 75 used a cross-sectional epidemiologic design, 13 were prospective, and the remaining was a case-control study. Most studies investigated multiple potential risk factors for STH infection. Exposure status for WASH access and practices was typically determined through self-report, although 15 studies also used some form of observation to validate self-reported information. All included studies reported the diagnostic method used to assess helminth infection, with the Kato-Katz technique most frequently mentioned (n = 63). To assess the independent effect of WASH components on STH infection, authors typically used multiple regression analysis (n = 68), though adjusted effect estimates were often not reported for WASH covariates if they were not statistically significant. Not all multivariable models were reported with a full list of included covariates either. Slightly more than one-third of the studies (n = 33) reported at least one non-significant adjusted effect estimate. Study bias assessment is presented in Table S2. Meta-analysis results are available in Table 8 and grades summarized in Table 9. 10.1371/journal.pmed.1001620.t008 Table 8 Meta-analysis results. Meta-Analysis Odds Ratio (95% CI) Tau Squared Q p-Value I 2 (95% Uncertainty) Egger's Test P n Studies GRADE Piped water use (any STH) 0.93 (0.28–3.11) 1.86 80%). Strongyloides stercoralis We found 12 studies that investigated the relationship between WASH and S. stercoralis infection, but only located relevant effect estimates in five. Among school children in Cambodia, Khieu and colleagues found crude associations between infection and handwashing, shoe-wearing, and sanitation access [87]. Hall and colleagues found mixed results for a range of sanitation-related exposures, with some evidence that open defecation and use of community latrines were associated with higher odds of S. stercoralis infection in children [72]. In a multivariable model using data from a rural Peruvian community, Yori and colleagues found that wearing shoes never or occasionally (versus more frequently) was associated with higher odds of infection (OR 1.89, 95% CI 1.10–3.27) [88]. Knopp and colleagues did not find a significant association between S. stercoralis infection and home latrine ownership or handwashing after defecation [89]. Discussion We conducted a systematic review and meta-analysis of the relationship between WASH access and practices and STH infection. Our analysis revealed that WASH access and practices are generally, but not universally, associated with lower odds of STH infection. Particularly strong associations emerged between wearing shoes and hookworm infection (OR 0.29, 95% CI 0.18–0.47), piped water use and A. lumbricoides infection (OR 0.40, 95% CI 0.39–0.41), and treated water use and infection by any STH (OR 0.46, 95% CI 0.36–0.60). Pooled estimates for all meta-analyses, except for two (i.e., piped water use for any STH and sanitation access for hookworm), indicated at least a 33% lower odds of STH infection associated with specific WASH behaviors or access (Table 8). All but two of the meta-analyses were statistically significant at the 5% level. On the basis of the evidence available, this review primarily draws upon observational studies. Observational research typically has greater risks to internal validity than randomized controlled trials, but such research is also key to providing a broad evidence base. When conducted well, randomized controlled trials provide the strongest evidence of a causal relationship between an exposure (e.g., an intervention) and an outcome. In the WASH context, however, conducting RCTs can be ethically and financially challenging. Traditional randomized designs can be costly and require that a subset of the target population be allocated to the control group, receiving only a limited intervention. Observational studies can be conducted more quickly and affordably in a wide array of contexts, allowing for WASH access and practices to be investigated in different social-ecological systems. This diversity is critical, since the effectiveness of specific WASH interventions can vary widely across settings, and interventions will most likely provide the greatest impact after being tailored to local conditions. Looking forward, a stepped wedge design represents a powerful compromise between ethics, operational feasibility, and internal validity. With a stepped wedge approach, the rollout of an intervention is randomized so that all participants eventually receive the study benefits, but at different times. Because many WASH interventions require staggered implementation owing to limited financial and human resources, randomizing the order in which communities are visited is often feasible. Combined with longitudinal data analysis, this design allows for robust assessments that can integrate with many interventions without radically altering implementing organizations' plans. This review highlights important gaps in the WASH and STH body of literature. For example, only a few of the studies that met our inclusion criteria investigated the impact of sharing latrines (n = 6) or latrine maintenance (n = 3) on STH infection. The effect of treating water (n = 7) and geophagy (n = 10) were also infrequently explored. S. stercoralis was by far the least commonly investigated STH infection, reflecting another important knowledge gap. A total of 35 studies contributed data to the 14 meta-analyses. A lack of standardized WASH definitions across studies limited our ability to pool results via additional meta-analyses. More consistent use of the Joint Monitoring Program's water and sanitation ladder definitions would aid future review efforts. Additional meta-analyses could have been conducted if all reviewed studies had provided relevant adjusted estimates of association. For example, many studies investigated the relationship between “toilet sharing” on any STH infection and “water access” on hookworm infection, but a dearth of reported adjusted estimates stymied meta-analyses of these relationships (Table 7). Few studies analyzed the relationship between fecal egg count, a proxy for intensity of infection, and WASH [27],[81],[90], even though intensity of infection represents a more relevant predictor for morbidity than prevalence alone [91]. A lack of measures on this relationship represents a considerable gap in the literature, though many studies did report broadly on intensity of infection. Zero-inflated modeling strategies have recently shown promise in analyzing fecal egg count datasets, which often contain excess zero counts due to some individuals not harboring infections [92]–[94]. Contemporary analysis of existing data represents a potentially cost-effective mechanism for yielding additional insights into this topic. Our findings build upon past reviews by Asaolu and Ofoezie [32] and Ziegelbauer and colleagues [26], which both concluded that WASH represents a valuable strategy for STH control. Although Asaolu and Ofoezie did not conduct a meta-analysis, their comprehensive review found broad evidence of reductions in STH prevalence and intensity resulting from multiple types of WASH interventions. Asaolu and Ofoezie concluded that improvements in sanitation systems and hygiene practices were important tools to not only sustain preventive chemotherapy benefits, but also help protect the uninfected. Results from our meta-analyses support their conclusion using systematically aggregated quantitative data. Ziegelbauer and colleagues focused more specifically on latrine access and use, conducting a rigorous meta-analysis using primarily crude odds ratios. The results from our meta-analyses, which drew upon adjusted odds ratios, are consistent with their findings and lend additional support to the value of sanitation improvements for STH control. Our meta-analyses also broadened focus to include water and hygiene components, allowing for a quantitative summary of currently available evidence across the three core WASH domains. Our analysis of the relationship between access to a piped water source and STH infection yielded significantly protective associations for A. lumbricoides and T. trichiura, but not for any STH infection generally. The meta-analysis of any STH yielded strong heterogeneity statistics, reflecting a spread in observed effects. While the inclusion of hookworm infections in the “any STH” analysis may seem like a possible source of the variability, we found no clear evidence to support this explanation. The only study that analyzed hookworm infection and piped water use with an adjusted model found a significantly protective association, so other sources of heterogeneity should be considered. The presence of heterogeneity can be systematically investigated by statistics like Moran's I 2 and Cochran's Q, but these global tests do not themselves uncover specific causes of heterogeneity. Diversity among studies can originate from a plethora of sources: population, setting, diagnostic approach, study design, analytic method, definitions, and so on. Without additional subgroup analysis or meta-regression, which both require a large body of studies, it is difficult to investigate the myriad potential causes of heterogeneity. Without clarification, the presence of heterogeneity indicates that pooled results are averaging multiple related, but distinct effects. For example, access to piped water could have different levels of benefit depending on distance to the source [95],[96], water quality [70],[97], or other unknown factors—especially when studies use different diagnostic assays and are conducted in a variety of community settings. Concerning sanitation, our meta-analyses of access to sanitation yielded considerably lower odds of infection with A. lumbricoides, T. trichiura, or any STH for those with latrine access. We did not find evidence of a statistically significant association between sanitation and hookworm, though the pooled estimate suggested reduced odds of infection. Our sanitation findings were comparable to those found by Ziegelbauer and colleagues, who asserted that improved sanitation access should be prioritized alongside preventive chemotherapy to achieve a sustainable reduction in helminthiasis burden. They found an overall pooled odds ratio of 0.51 (95% CI 0.44–0.61) for the effect of sanitation availability and use, while we found an odds ratio of 0.66 (95% CI 0.57–0.76). Species-specific results were similar as well, with the exception of hookworm. Differences in the magnitude of our findings may be attributed to the use of adjusted measures in our analysis, since Ziegelbauer and colleagues used unadjusted estimates. In addition, we did not include separate estimates for sanitation use and access. Taken together, these two reviews support the hypothesis that improved access to, and use of, sanitation prevents STH infection. Additional research could help explore the complementarity of sanitation promotion with MDA. For hygiene, three randomized controlled trials provided strong evidence linking hygiene practices—especially handwashing with soap—to reductions in STH infection [75]–[77]. However, not all hygiene interventions may be effective in reducing STH infection [86]. Our meta-analyses of the effect of handwashing before eating and after defecation for A. lumbricoides infection, along with handwashing after defecation and soap use for any STH infection, also yielded significant results that suggest protective effects. Accurately assessing handwashing is challenging; self-reported and observed measures are often highly biased [33]. Many studies rely on self-report, but individuals have consistently been shown to over-report handwashing behaviors [98]. Heterogeneity was exhibited in the analysis of handwashing after defecation, suggesting that the benefits of handwashing may vary considerably depending on circumstances and definitions. Beyond handwashing, our analysis also showed that wearing shoes was associated with significantly lower odds of infection with hookworm and any STH. These results may be of interest to several audiences. Researchers can take note of the gaps in the literature identified by this review and focus investigation on key outstanding questions (e.g., the impact of WASH on S. stercoralis infections). Policymakers should understand that, despite gaps in data, these findings provide a broad evidence base in support of WASH for STH control—especially from randomized trials for hygiene interventions. WASH practitioners will recognize that these findings provide further support for their efforts and, we hope, will consider partnering with STH researchers to evaluate future interventions. Strengths and Limitations Our review included only adjusted effect estimates in meta-analyses, which lends greater strength to our pooled results [37]. Many different variables were controlled across studies, which may contribute to heterogeneity. However, this variation in adjusted models may also serve as a small buffer against the inherent heterogeneity across observational studies. Different covariates will vary in importance for different populations and circumstances, so a broad review like ours may benefit from pooling estimates from models that were adapted by researchers to best fit their data and contexts. There are many factors that could confound the relationship between WASH access or practices and STH prevalence, including socioeconomic status, age, and gender. Consideration of only crude associations would likely overstate the magnitude of effect for WASH exposures or even misinterpret the true direction of effect [99]. Limiting our focus to adjusted measures of effect reduces the number of eligible studies, which may impact the generalizability of our results. This strategy also amplifies the impact of selective reporting, since many authors reported only statistically significant adjusted estimates. Evidence quality was typically “low”—the default GRADE for observational research—meaning that our confidence in pooled effect estimates is limited, and that the true effect may be markedly different from the results reported here [40]. A much stronger case can be made for the benefit of hygiene because of the evidence provided by recent randomized controlled trials, but results from our meta-analyses suggest that the protective effect of hygiene practices on STH infection may be variable depending on context. Publication bias also represents a concern. Five meta-analyses (piped water for any STH and A. lumbricoides, wearing shoes for hookworm and any STH, sanitation access for hookworm) showed evidence of publication bias in funnel plot assessments. However, two of those plots (piped water for A. lumbricoides and sanitation access for hookworm) showed that larger studies yielded more protective associations, suggesting that the results from those analyses may be underestimating the true relationship strength. This was unexpected—and possibly caused by the natural heterogeneity across observational studies—since larger studies are traditionally expected to show smaller magnitudes of effect. Heterogeneity creates great difficulty in assessing publication bias accurately with statistical tests, so it is impossible to know how pronounced publication bias may be throughout our meta-analyses [100]. Conclusion A vibrant discussion continues in the literature about the role of MDA in measurably mitigating morbidity from STH infection at the population level [101]–[106]. MDA alone is unlikely to permanently interrupt STH transmission. Our review provides evidence that WASH is a valuable component for STH control strategies, but guidelines and targets for the integration of these approaches are needed. Increased attention towards WASH for STH also has great potential to catalyze synergies with integrated NTD control programs, while jointly elevating awareness of WASH and NTDs [5],[28],[107]. Additional high-quality research into the potential of integrated WASH interventions is merited, specifically on the complementarity of WASH and MDA. Recent and ongoing research continues to build an evidence-base that can guide policymaking and programmatic decisions [27],[28],[108]. Increased collaboration between the health and WASH sectors represents a key enterprise for the future of NTD control and elimination [109],[110]. Supporting Information Figure S1 Funnel plot for treated water use and any STH infection. (EPS) Click here for additional data file. Figure S2 Funnel plot for piped water use and any STH infection. (EPS) Click here for additional data file. Figure S3 Funnel plot for piped water use and A. lumbricoies infection. (EPS) Click here for additional data file. Figure S4 Funnel plot for piped water use and T. trichiura infection. (EPS) Click here for additional data file. Figure S5 Funnel plot for sanitation access and any STH infection. (EPS) Click here for additional data file. Figure S6 Funnel plot for sanitation access and A. lumbricoides infection. (EPS) Click here for additional data file. Figure S7 Funnel plot for sanitation access and T. trichiura infection. (EPS) Click here for additional data file. Figure S8 Funnel plot for sanitation access and hookworm infection. (EPS) Click here for additional data file. Figure S9 Funnel plot for soap use and any STH infection. (EPS) Click here for additional data file. Figure S10 Funnel plot for handwashing before eating and A. lumbricoides infection. (EPS) Click here for additional data file. Figure S11 Funnel plot for handwashing after defecating and A. lumbricoides infection. (EPS) Click here for additional data file. Figure S12 Funnel plot for handwashing after defecating and any STH infection. (EPS) Click here for additional data file. Figure S13 Funnel plot for wearing shoes and hookworm infection. (EPS) Click here for additional data file. Figure S14 Funnel plot for wearing shoes and any STH infection. (EPS) Click here for additional data file. Table S1 Excluded studies. (DOC) Click here for additional data file. Table S2 Study bias assesment. (DOC) Click here for additional data file. Text S1 PRISMA checklist. (DOC) Click here for additional data file. Text S2 MOOSE checklist. (DOC) Click here for additional data file. Text S3 Original methods protocol. (DOC) Click here for additional data file.

                Author and article information

                BMC Public Health
                BMC Public Health
                BMC Public Health
                BioMed Central (London )
                5 April 2017
                5 April 2017
                : 17
                [1 ]GRID grid.424087.d, Department of Social Dentistry, , Academic Centre for Dentistry Amsterdam, ; Gustav Mahlerlaan 3004, 1081LA Amsterdam, The Netherlands
                [2 ]GRID grid.83440.3b, Department of Epidemiology and Public Health, , University College London, ; Torrington Place 1-19, London, WC1E 6BT UK
                [3 ]Gesellschaft für Internationale Zusammenarbeit (GIZ), L.P. Leviste cor Rufino Street, Makati City, Metro Manila, Philippines
                [4 ]Social Basic Services Bureau of West Java, Governor’s Office, Jl. Diponegoro No. 22, Citarum, Bandung Wetan, Bandung, West Java 40115 Indonesia
                [5 ]Department of Preventive Dentistry and Pediatric Dentistry, University Hospital Jena, Friedrich Schiller University Jena, Bachstraße 18, 07743 Jena, Germany
                [6 ]Institute of Human Genetics, University Hospital Jena, Friedrich Schiller University Jena, Kollegiengasse 10, 07740 Jena, Germany
                [7 ]Department of School Health of the Ministry of Education, Youth and Sport of the Kingdom of Cambodia, Street 380, Chao Ponheahok Primary School, BKK1, Khann Chamkarmorn, Phnom Penh, Cambodia
                [8 ]Department of Preschool and Primary Education, Ministry of Education and Sports, Ministry of Education Building No 1, Lane Xang Ave, P.O. Box 067, Vientiane Capital, Laos
                [9 ]GRID grid.137628.9, Department of Epidemiology and Health Promotion, College of Dentistry, , New York University, ; 433 First Avenue, New York, NY 10010 USA
                © The Author(s). 2017

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                school health,water sanitation and hygiene,handwashing,toothbrushing,deworming,dental caries,underweight,soil-transmitted helminth infection


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