Water, Worms and Weird Diseases: Water Quality Variability and Pediatric Health Outcomes in Northern Coastal Ecuador Open Access
Fanny, Sanemba Aya (2016)
Abstract
Background: poor water quality (WQ) is known to contribute to poor health outcomes such as diarrhea and soil transmitted helminth (STH) infections. However, studies attempting to link WQ and waterborne illnesses often find conflicting results while studies of interventions that aim at reducing water contamination successfully show that improved water quality decreases waterborne illness risk. Experts argue that this contrast can be explained by study design and the variability of microbial indicators.
Purpose: this study intended to: 1) characterize the factors that influence WQ within households (i.e. rural vs urban setting, water source, intermittent water supply, storage, and treatment), 2) determine the association between WQ, diarrhea and STH infections, 3) compare intra- and inter- household WQ variability in order to help guide potential new WQ standards, and inform better study designs.
Methods: a field study was conducted in the district of Quinindé, Ecuador. Survey data and water samples were collected during household visits. WQ was measured using E.coli (EC) and total coliforms (TC) as bacterial indicators. Non-parametric tests, linear and logistic regression were used for data analysis.
Results: River water had the highest contamination but all other sources of water were also contaminated. Rural households that do not have access to improved municipal water sources had significantly higher contamination (EC:1.17 log10 MPN/100 mL , TC: 2.87 log10 MPN/100 mL) than urban households (EC:0.90 log10 MPN/100 mL, TC: 2.49 log10 MPN/100 mL). Boiled water was strongly associated with lower contamination when compared to untreated water (EC: β=-0.73, p<0.0001; TC: β=-0.87, p=0.0002). Storage was a strong predictor for higher contamination (EC: β=0.33, p=0.0014; TC: β=0.62, p<0.0001). For households that used potable water, intermittent water supply was linked with higher rates of storage (OR=2.2, p=0.01). Both diarrhea (OR=1.1, p=0.0475) and STH infections (OR=1.16, p<0.0001) were associated with higher contamination levels. EC was a more accurate microbial indicator than TC. WQ variability was greater within rural households.
Conclusions: WQ measurements and factors that pose a contamination risk such as storage, water source and treatment should be incorporated into new water safety and risk assessment measures for more accurate monitoring of progress made towards universal access to safe water.
Table of Contents
Chapter 1: Introduction 1
Introduction and rationale 1
Problem statement 2
Purpose statement 3
Significance statement 4
Definition of terms 5
Chapter 2: Literature review 7
Burden of disease 7
International efforts around water, hygiene and sanitation 9
MDG target 7c and JMP monitoring 10
Is the mission really accomplished? MDG criticism and skepticism 11
Less than optimal access 13
Household water storage and its effects on water quality 15
Water quality variability and reliability of indicator organisms 18
Does clean water really matter? Evidence supporting efforts for clean water 20
Summary 22
Chapter 3: Materials and methods 24
Introduction 24
Population and sample 24
Research design 26
Procedures 26
Instruments 27
Data Analysis 28
Ethical Considerations 28
Limitations and delimitations 29
Chapter 4: Results 30
Descriptive statistics 30
Factors affecting water quality 33
Geographical location 33
Intermittent water supply 34
Storage 36
Source 37
Treatment 38
Simple linear regression 39
Multiple linear regression 40
Factors leading to water storage 43
Factors predicting diarrhea 44
Water quality and STH infection 44
Intra- versus inter- household water quality variability 45
Water quality measurements variability based on microbial indicator 48
Chapter 5: Discussion 49
Factors affecting water quality 49
Factors predicting water storage 52
Factors predicting diarrhea 53
Factors predicting STH infection 53
Intra- versus inter-household water quality variability 54
Water quality measurements variability based on microbial indicators 54
Limitations and future directions 55
Conclusion 57
Recommendations 57
Literature Cited 60
Appendix A: Questionnaire form for surveys 64
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