Proximity to Environmental Hazards and Reported Illness in Periurban Households of the Dominican Republic. - PDF

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Proximity to Environmental Hazards and Reported Illness in Periurban Households of the Dominican Republic. By Glenn A. Vorhes A REPORT Submitted in partial fulfillment of the requirements For the degree
Proximity to Environmental Hazards and Reported Illness in Periurban Households of the Dominican Republic. By Glenn A. Vorhes A REPORT Submitted in partial fulfillment of the requirements For the degree of MASTER OF SCIENCE IN ENVIRONMENTAL ENGINEERING MICHIGAN TECHNOLOGICAL UNIVERSITY 2009 Copyright Glenn A. Vorhes 2009 This report Proximity to Environmental Hazards and Reported Illness in Periurban Households of the Dominican Republic is hereby approved in partial fulfillment of the requirements for the Degree of MASTER OF SCIENCE IN ENVIRONMENTAL ENGINEERING. Civil and Environmental Engineering Master s International Program Signatures: Report Advisor James R. Mihelcic Department Chair William Bulleit Date i Abstract This research utilized data obtained from a household socioeconomic and health survey of three periurban neighborhoods in the Dominican Republic. A proxy for the frequency and severity of illness experienced by each household was generated based on survey responses. A demographic correction model was used to remove the correlation between this proxy and the number of household inhabitants. The residuals from this model represent the measure of illness in the house which is above or below that which would be expected based on the number and ages of household inhabitants. Environmental hazards analyzed included inadequate disposal of solid waste and sanitary facilities in poor condition measured through a scoring of survey responses, and uncontained wastewater in the street measured by qualitative evaluations. The dispersion of risks was modeled through the use of raster images in ArcGIS. Values extracted from these images were compared to the geographically referenced health data for correlation and Analysis of Variance or relative risks between populations grouped by dichotomous variables or ranges of values. Significant correlations were found between the metric of illness and the prevalence of uncontained wastewater in the street and sanitary facilities in poor condition. There was also a significant correlation between inadequate disposal of solid waste and the measure of illness though the modeled dispersion suggests that solid waste disposal is of more concern to welfare of the inhabitants of the house than it is for the general health of the neighborhood. Socioeconomic factors were also analyzed with no significant correlations found between illness and income or education. Those who reported drinking tap water rather than purchased filtered water were significantly more likely to report illness. Earlier studies used dichotomous variables to model risk of exposure to environmental hazards whereas this research is unique in using spatial techniques with continuous variables to model severity of and proximity to hazards and the relation to reported waterborne illness. ii Preface This report is based on the 33 months I spent living and working in The Dominican Republic while serving as a Peace Corps Volunteer from November, 2006 to September, I worked as an Environmental Sanitation Engineer/Promoter first in the small community of La Sierra in the municipality of Altamira and later in the Santiago, the second largest city in the country with population of about 500,000. This report is submitted to complete my master s degree in Environmental Engineering from the Master s International Program in Civil and Environmental Engineering at Michigan Technological University. Data was obtained from a health and socioeconomic diagnostic of three neighborhoods on the periphery of Santiago. Funding for the project was provided by the Rotary Club of Joliet, Illinois. The sponsors had no role in the design or implementation of the project or in interpretation of results. iii Acknowledgments Funding was provided by Rotary Club of Joliet, IL with special recognition to Howard Hamilton and David Crow of the Santiago, Dominican Republic chapter. Special thanks to the following people: Dr. James Mihelcic University of South Florida Dr. Noel Urban Michigan Technological University Dr. Christopher R. Webster Michigan Technological University Franklin Estrella Secretaría de Estado de Salud Pública y Asistencia Social Eddy Hernandez Muñoz Lissette Anyelina Frias Toribio iv Table of Contents Introduction... 1 Periurban Sectors in the Developing World... 2 Solid Waste Disposal... 3 Community Level Sanitation... 4 Residual Water... 4 Compounding Factors... 5 Epidemiological Methods... 6 Methods... 7 Study Site... 7 Survey Formulation... 8 Interviewers and Preparation Conducting the Survey Privacy Data Entry Modeling Environmental Hazards Solid Waste Disposal Condition of Sanitary Facilities Street Sanitation Condition Extracting Pixel Values to Survey Data Illness Index Reported Illness from Survey Responses Illness Residual Data Transformation Data Analysis ANOVA and Relative Risk Linear Regression Results and Discussion Number of Household Inhabitants Reported Weekly Income, Per capita income Education Level of Heads of Household Drinking Water Source Property Owners or Renters Solid Waste Separators Solid Waste Disposal Condition of Sanitary Facilities Latrine or Indoor Toilet Sanitary Facility Condition Measure as Score from Responses Sanitary Facility Condition Raster Street Sanitation Presence of Residual Water Sanitation Condition Raster Sanitation Condition Survey Responses Relationship between Street Sanitation and Sanitary Facilities Raster Man or Woman Interviewed Multivariate Analysis Relative Importance of Factors Conclusion References Appendix A. Household Survey Form - English Appendix B. Household Survey Form - Spanish Appendix C. Rubric for Qualitative Evaluation of Residual Water Presence in Streets of Study Area Appendix D. Summary of Variables and Numbers of Responses Appendix E. Human Subjects in Research Approval v List of Figures Figure 1. Location of the Study Area... 7 Figure 2. Study Area Street Name/Number Map Included on Each Survey Form... 9 Figure 3. XYZ Points Used to Model Severity of Environmental Hazards Figure 4. Filter Tool Generates Output Raster from Pixel Values in Input Raster Figure 5. Raster Cell Size and Filter Application Effects on Association Between Z Coordinate Values and Pixel Values of Corresponding Cells Figure 6. Solid Waste Disposal Rasters with Various Cell Sizes, With and Without Smoothing Filters Figure 7. Representative Sanitary Facility Condition Rasters with Various Cell Sizes, With and Without Smoothing Filters Figure 8. Street Sanitation Condition Rasters from Qualitative Evaluations Figure 9. Visual of Extraction Process: Pixel Values Extracted from Rasters and Appended to Survey Data Figure 10. Coefficients of Linear Regression: Number of People in Various Age Categories as Explanatory Variables of the Illness Index Figure 11. Comparison of Predicted Illness Index from Age Specific (Demographic) and Per Capita Contribution Models Figure 12. Generation of Illness Residuals based on Multiple Linear Regression Coefficients Figure 13. Screenshot from Odds Ratio Generator Showing Format of Entry for Control and Treatment Groups with Improved and Unimproved Cases in Each Figure 14. Linear Regression of Solid Waste Disposal Raster Values and Illness Residuals: R 2 Values by Raster Image Cell Size and Filter Setting Figure 15. Linear Regression of Sanitary Facility Condition Raster Values and Illness Residuals: R 2 Values by Raster Image Cell Size and Filter Setting Figure 16. Relative Risk Results. Population Divided Into Control and Treatment Groups. Treatment Group Designated as Those Houses with a Street Sanitation Condition Raster Value Greater Than or Equal to the Value Given in Chart Figure 17. Association between Values from Hazard Models: Street Sanitation Condition and Sanitary Facility Condition. R 2 Values and Visual Comparison Shown Figure 18. Coefficients of Multiple Linear Regression with Illness Residual List of Tables Table 1. Survey Question Regarding Disposal of Solid Waste Table 2. Questions and Scoring of Responses Regarding Sanitary Facility Condition Table 3. Rubric for Qualitative Evaluation of Wastewater Presence in Streets of Study Area Table 4. Survey Health Questions and Scoring of Responses Table 5. Relationship Between Demographic Data, Illness Index, Demographic Prediction Model, and Illness Residual Table 6. Analysis of Variance and Relative Risk Analyses and Results Table 7. Simple Linear Regression Analyses and Results Table 8. Average Illness Residuals for Population Divided by Sanitation Facility Condition Score Table 9. Illness Residuals for Populations Grouped by Reported Frequency of Uncontained Wastewater in the Street Table 10. Street Sanitation Condition Raster Values for Populations Grouped by Reported Frequency of Uncontained Wastewater in the Street vi Introduction This research attempts to answer the scientific question, Is there a statistically significant relationship between the proximity to environmental hazards and the prevalence of waterborne illness which can be observed at the household scale within a neighborhood? While it may be shown that those living closer to an environmental hazard are more likely to become ill, it may also be that they are among the less well off economically or less well educated. An identified relationship between the proximity to an environmental hazard and illness should not be assumed to be a causal relationship without considering other factors. This research does an in depth analysis of health, environmental conditions, and socioeconomic factors. By showing both the presence and absence of significant relationships between various factors and illness, the reader can make inferences of causal factors. Environmental hazards from inadequate disposal of solid waste, sanitary facilities in poor condition, and uncontained residual water in the street were addressed. Methods included spatial analysis techniques to measure for relationships between the prevalence of waterborne illness, deduced from household survey responses, and environmental hazards. The use of continuous variables to model the distance to and severity of environmental hazards is unique to this investigation. Hazard severity is quantified by means of household survey responses as well as with qualitative observations distinct from the survey. 1 Periurban Sectors in the Developing World There is no consensus definition for the periurban sector but the term generally refers to urban areas on the margins of the physical and regulatory city boundaries that have uncertain legal tenure, low household incomes, and lack urban services (Hogrewe et al., 1993). Services in poorer and often newer neighborhoods of many Latin American cities lag behind those in central districts (Komives, 1999). Periurban poor receive substandard or no urban services while wealthier areas are covered at subsidized rates (Paterson et al., 2007). Solid waste collection is less profitable in periurban areas due to the lower reclaimable value of discarded items and difficult collection in steep terrain or narrow streets (Coura Cuentro and Gadji, 1990). Poor neighborhoods are left unserved by sewer networks because residents cannot afford high connection charges (Wright, 1997). Levels of fecal contamination and incidence of childhood diarrhea are at least as high in periurban settings as they are in rural areas (Lopez de Romana et al. 1989, Schorling et al. 1990). Children from disadvantaged slums are malnourished from repeated episodes of diarrhea during their most important formative years (Guerrant, 1994). Accidents and environmental hazards are the major causes of illness, injury, and premature death in most urban areas of the developing world (Hancock, 1996). It is commonly asserted that periurban communities are ignored by municipal authorities as their size and population outpaces the capacity of local planning and government (Hogrewe et al., 1993). However, Mehta (2006) found problems regardless of population size or growth. Boston sanitary surveyors reported in 1850 that, Cities are not necessarily unhealthy, but circumstances are permitted to exist, which make them so (Schultz and McShane, 1978). Especially in periurban settings where salient needs are 2 basic subsistence and housing, elected officials and residents do not tend to perceive environmental health as a vital concern (Hubbard et al., 2005). Despite their large numbers and unique situation, data are rarely collected that illuminate the plight of periurban residents. Health indicators such as infant mortality and diarrhea are much worse in crowded squatter settlements though statistics are generally not disaggregated from those of the city as a whole (Wright, 1997). While data are gathered for areas designated as rural or urban, statistics for periurban residents are not collected in Latin America or Africa (Hogrewe et al., 1993). The level of health is rarely deduced from measured variables distinctly for periurban areas such that improvements are difficult to quantify in those areas where health is generally worse than in other parts of the city (Moore et al., 2003). Solid Waste Disposal Improper disposal of household solid waste is a source of air, land, and water pollution and creates hazards to human health and the environment (Medina, 1999). Accumulated solid waste in urban areas can affect not only those from which it came, but can also be an environmental health hazard for nearby residents. As with concerns relating to sanitation and residual waters, inadequate solid waste disposal can put a population more at risk of exposure to disease causing agents. Uncollected garbage provides a breeding ground for disease vectors such as flies and rats (Coura Cuentro and Gadji, 1990) that contaminate food (McGranahan, et al., 1997). This is important to an analysis of waterborne illness that uses diarrhea as a metric because food contamination potentially accounts for 15 to 70% of diarrhea cases (Esrey and Feachem, 1989). 3 Community Level Sanitation Sanitation at the community level is a more important measure for health benefit than is individual access to improved sanitation (Bateman et al., 1993). The percentage of residents with sewer connections is not a reliable indicator of community health (Nance, 2005) as was found by Heller (1999) in Brazil. It is suggested that at least 75% of the community should have access to improved sanitation as lower coverage puts all residents at risk from poor environmental conditions (Bateman et al., 1993). A study in Guatemala found that children living in a community with a generally high level of sanitation had low rates of growth stunting regardless of in home access to a flush toilet (Bateman and Smith, 1991). When compared in multivariate analyses, the method of wastewater disposal showed no significant relationship with health though those living near streets with uncontained wastewater had a relative risk of diarrheal morbidity of 2.38 (95% confidence: ) over those in the wastewater absent settings (Heller, 1999). The most important intervention goal with regard to sanitation is proper disposal of all wastewater in the drainage basin in order to avoid overflows to the street (Heller, 1999). Residual Water Pit latrines and pour flush latrines are considered as improved sanitation (WHO and UNICEF, 2004), however any sanitation technology requires safe disposal of water from washing and bathing (Kalbermatten et al., 1982), hereafter referred to as gray water. Off site sanitation such as conventional sewerage protects the user from exposure to excreta but may contaminate groundwater or increase hazards to downstream populations (Hogrewe et al., 1993). The quality of upstream solutions determines the hazards for those downstream (Heller, 1999, McGranaham, 1997). 4 Many residents route wastewater to storm drains or to pit latrines that can contaminate groundwater (Watson, 1995). Gray water in storm drains may come from houses that are connected to sewer systems but have routed wash water to the street instead of to the sewer (Nance, 2005). Water from bathroom facilities contains higher concentrations of contaminants but gray water is not benign. Gray water contains excreted pathogens, organic compounds, and twenty to thirty grams of biological oxygen demand per capita per day (Kalbermatten et al., 1982). Untreated wastewater should always be assumed to contain high levels of pathogens (Esrey et al., 1998). Health improvements have not been realized solely by improved water services with no attention to drainage or sanitation. Water supply improvements without adequate means for disposal can exacerbate problems (Katakura and Bakalian, 1998, UN Habitat, 1987). Nawab et al. (2006) found that incidence of waterborne illnesses increased after the installation of a piped water system and that villagers were able to differentiate between the diseases prevalent before and after the infrastructure improvement. Environmental problems in the United States in the 19 th century worsened due to larger quantities of water brought in by new supply systems (Schultz and McShane, 1978) and continued to take a toll on urban populations until the early 20 th century (Weber, 1899, Hancock, 1996). That health has improved in developed world cities shows that infrastructure improvements can protect the population (Satterthwaite, 1993). Compounding Factors This research did not assume that solid waste collection and/or sanitation infrastructure are the only or even the most important factors with respect to general health or prevalence of illness. Though the transmission of fecal-oral disease is well 5 understood, it may be difficult to identify the most important routes even within a given neighborhood (McGranahan, 1997). Factors pertaining to fecal-oral disease tend to be related to other environmental health problems (McGranaham, 1997). Illness associated with environmental hazards may also be linked to individual or group behavior (Moore and Carpenter, 1999). Hygiene behavior may be as important as sanitation infrastructure with respect to health. Even without latrines, diarrheal morbidity is reduced with improved hygiene practices (WHO, 1993). Simple burial of excreta breaks the transmission route (Waterkeyn & Cairncross, 2005). If maintained and used by all, any sanitation scheme should lead to health benefits (Feachem et al., 1980). An investigation of sanitation and health should also take into account socioeconomic factors before suggesting causal relationships. Previous studies have found that metrics of education or wealth have significant relationships with measures of health. Checkley et al. (2004) found that children living in households where water was stored in small containers were more likely to have growth stunting than were those where water was stored in large containers. Mothers education levels and articles owned were shown to be related with caloric intake of children in some settings (Bairagi, 1980). Epidemiological Methods A major concern of epidemiology has been to find the risk factors associated with various diseases (Haug et al., 1997). The idea of using geography in health research comes from an appreciation of non-uniformity in the distribution of illness (Mayer, 1983). The first geographically referenced epidemiological data are attributed to Dr. John Snow who mapped illness reports to suggest that a certain water pump was the source of the London cholera outbreak in 1854 (Haug et al., 1997, Moore and Carpenter, 1999). 6 Numerical-spatial investigations such as identifying health factors within a community can be facilitated by the use of Geographic Information Systems (GIS) (Scotch et al., 2006). Moore and Carpenter (1999) provided a review of several epidemiological studies that made use of GIS technology. Spatial analysis is normally performed by plotting geographically referenced illness events and looking for hazards which have the same
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