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List of Tables
List of Figures
List of Appendices
CHAPTER I INTRODUCTION
1.1 Background of the Study
1.2 Statement of the Problem
1.3 Objectives of the Study
1.4 Significance of the Study
CHAPTER II THEORETICAL BACKGROUND
2.1 Review of Related Literature
2.1.1 Etiology and Pathophysiology of Hookworm Infection
2.1.2 Health Impact of Hookworm Infection
2.1.3 Determinants of Hookworm Infection
2.1.4 Multilevel Analysis
2.2 Conceptual Framework
CHPATER III METHODOLOGY
3.1 Research Design
3.2 Sources of Data
3.2.1 Prevalence Survey for Schistosomiasis
3.2.2 The Group-Level Datasets
3.3 Study Areas and Number of Respondents
3.4 Definition of Variables
3.5 Data Processing
3.6 Data Analysis
3.6.1 Descriptive Analysis
3.6.2 Inferential Analysis
CHAPTER IV RESULTS OF THE STUDY
4.1 Descriptive Analysis
4.1.1 First-level Variables
4.1.2 Second-level Variables
4.1.3 Third-level Variables
4.1.4 Hookworm Prevalence
4.2 Inferential Analysis
4.2.1 Crude Association of Hookworm Infection With Individual-Level Variables
4.2.2 Crude Association of Hookworm Infection With Barangay-Level Variables
4.2.3 Crude Association of Hookworm Infection with Provincial-Level Variables
4.2.4 Multilevel Modeling
CHAPTER V DISCUSSION OF RESULTS
5.1 Analytic Techniques
5.1.1 Barangay-level variability of risk for hookworm infection
5.2 Correlates of hookworm infection
5.2.1 Individual-level correlates
5.2.2 Barangay-level correlates
5.2.3 Provincial-level correlates
5.3.1 Selection Bias
5.3.2 Information Bias
CHAPTER VI CONCLUSIONS AND RECOMMENDATIONS
Table 126.96.36.199 Summary statistics of study respondents’ age according to gender and presented by province
Table 188.8.131.52 Distribution of barangays by literacy rate and province, 2000†
Table 184.108.40.206 Distribution of respondents by literacy rate and province, 2000†
Table 220.127.116.11 Distribution of barangays by percentage of households without toilet facility and province, 2000†
Table 18.104.22.168 Distribution of respondents by percentage of households without toilet facility and province, 2000†
Table 22.214.171.124 Distribution of barangays and respondents by land cover type and province, 2005†
Table 126.96.36.199 Distribution of barangays by income classification and province, 2000†
Table 188.8.131.52 Distribution of respondents by income classification and province, 2000†
Table 184.108.40.206 Average maximum temperature and average rainfall amount of the 7 provinces in mindanao*,
Table 220.127.116.11 Provinces in mindanao by climate type*,
Table 18.104.22.168 Hookworm infection prevalence and odds ratio (95% confidence interval) according to individual-level variables
Table 22.214.171.124 Hookworm infection prevalence and odds ratio (95% confidence interval) according to barangay-level variables
Table 126.96.36.199 Hookworm infection prevalence and odds ratio (95% confidence interval) according to provincial-level variables
Table 188.8.131.52 Random intercept model
Table 184.108.40.206 Random coefficient models
Table 220.127.116.11 Coefficients and p-values of random intercept multilevel logistic regression model
Table 18.104.22.168 Odds ratio and 90% confidence intervals of random intercept multilevel logistic regression model
Figure 2.2.1 Conceptual framework for hookworm infection
Figure 22.214.171.124 Percentage of male and female respondents according to province
Figure 126.96.36.199 Age distribution of 7,018 study respondents
Figure 188.8.131.52 Prevalence of hookworm infection according to province
Figure 184.108.40.206 Association of barangay-level hookworm infection and literacy rate
Figure 220.127.116.11 Association of barangay-level hookworm infection and percentage of households without toilet facility
APPENDIX 1.4: REVIEW OF LITERATURE ON MULTILEVEL ANALYSIS OF HOOKWORM INFECTION
APPENDIX 2.1.4: MULTILEVEL LOGISTIC MODEL
APPENDIX 3.1: STUDY’S THREE-LEVEL DATA STRUCTURE
APPENDIX 3.2: CPH ETHICS REVIEW COMMITTEE APPROVAL
APPENDIX 3.3: STUDY’S PROVINCES, BARANGAYS AND NUMBER OF RESPONDENTS
APPENDIX 18.104.22.168: RANDOM INTERCEPT MODELING IN STATA
APPENDIX 22.214.171.124: RANDOM COEFFICIENT MODELING IN STATA
CURRICULUM VITAE 156
I would like to express my earnest thanks to the individuals who helped me in conceptualizing, developing and finishing this thesis. Dr. Maridel Borja, my thesis adviser, guided me throughout the duration of conceptualizing and writing the thesis. Dr. Lydia Leonardo allowed me to use part of her data on the Prevalence of Schistosomiasis. Dr. Jingky Lozano gave me some of the major articles used in developing the proposal. I would also like to express my gratitude to the panel members: Prof. Jennifer Frances dela Rosa made clear to me the concept of policy and program recommendations and Prof. Abubakar Asaad guided me in the application and appropriateness of the statistical theories. I am also grateful to Dr. Carmen Tolabing for being the reader/critic of this thesis.
Genevieve M. Nangit (2012). Correlates of Hookworm Infection in Selected Provinces of Mindanao, Philippines: A Multilevel Analysis. Master’s Thesis for the Degree of Master of Science in Epidemiology, College of Public Health, University of the Philippines Manila, 1st Semester, SY 2012-2013
The risk factors for hookworm infection are multi-factorial and they operate on different levels. Typical analyses of hookworm infection disparities have focused largely on either individual- or ecologic-level determinants, and none has analyzed them on both levels simultaneously. Hence, this study aimed to fill the need of simultaneously analyzing the correlates of hookworm infection on different levels, using the multilevel model. The general objective of the study was to identify the individual-level, barangay-level and provincial-level factors associated with hookworm infection in selected provinces in Mindanao. This thesis was a cross-sectional study that uses several secondary datasets. Individual-level variables were age, gender and hookworm infection status. The level 2 variables were land cover type (or also known as vegetation), barangay income classification, literacy rate and percentage of households without any form of toilet facility. The level 3 variables were climate type, average monthly rainfall and average monthly maximum temperature. The Mindanao provinces that were included in the study were Agusan del Sur, Davao del Sur, South Cotabato, Surigao del Sur, Misamis Oriental, Bukidnon, Surigao del Norte. Descriptive and crude analyses of hookworm infection were done using Microsoft Excel 2007 and Stata 10. Multilevel modeling was done using the Generalized Linear Latent and Mixed Models (GLLAMM) in Stata. The significant correlates of hookworm infection at the individual level are older age and male gender. While at the barangay level, it is a predominantly cultivated land cover. At the provincial level, these are average rainfall ≥100mm during LAR, average rainfall ≤100mm during HAR and Type 3 climate (seasons are not very pronounced). The significant factors at the barangay and provincial level can be used as criteria for selecting target areas for specific STH interventions. The STH interventions, which is primarily deworming, could expand its coverage and include as beneficiaries the older individuals.
Hookworm infection in humans is caused by helminth nematode parasites Necator americanus and Ancylostoma duodenale and is acquired through contact with contaminated soil (Hotez et al., 2004). Hookworm infection is widespread in tropical and subtropical parts of the world and is rampant particularly in impoverished countries. In the Philippines, the prevalence of hookworm infection nationwide ranged from 40% to 61%, varying only by province (Cabrera, 1998; Shaw et al., 2010).
Hookworm infection has many public health consequences but the major public health consequence is iron deficiency anemia (Awasthi et al., 2003; Bundy et al., 2004; Crompton and Nesheim, 2002; Farid et al., 1968; Hotez et al., 2004; Larocque et al., 2005; Stoltzfuz et al., 1996). Anemia caused by hookworm infection among pregnant women can cause adverse effects on the outcome of pregnancy (Allen, 2000; Bundy et al., 2004). Among infants and pre-school children, hookworm disease can result in growth stunting (Crompton and Nesheim, 2002) and behavioral deficits (Bundy et al., 2004; Farid et al., 1968; Hotez et al., 2004). Anemia caused by hookworm infection in school children may also adversely affect their intellectual and cognitive development (Ezeamama et al., 2005; Hotez et. al, 2004; Kvaslig et al., 1991; Pollitt et al., 1989; Soewondo et al., 1998; Stoltzfus et al., 2001). Indeed, a child with hookworm infection is often sick and absent from school, and frequent absences inevitably impede his learning ability. The cumulative effect of hookworm disease in the development of a child has far-reaching consequences. Growth and behavior deficits, low development quotients, cognitive impairments and underachievement in the prime of the child’s life will substantially affect his ability to be productive in his adult years.
There are several factors which affect the development of hookworm infection. These factors have been shown to operate at different levels. Hookworm infection is influenced, not only by individual-level factors, but also by environmental factors. Despite the customary assumption that hookworm transmission is a simple matter of poor hygiene, hookworm transmission depends on many components of the environment that affect hookworm larval activity. The transmission is not solely dependent on poor personal cleanliness because the eggs or ova are not infective to man. In fact, if ova are not deposited in soil, transmission will not occur.
The typical persistent nature of hookworm infection can be attributed to personal hygiene practices of the human hosts as well as exposure of the etiologic agents to environment that favor the survival of the infective larvae. Hence, this study investigates, precisely, the relationship between environmental and individual characteristics with the risk of hookworm infection. It also examines the variability in the individual’s risk caused by the clustering of individuals in barangays and provinces. By simultaneously analyzing the correlates of hookworm infection on different levels, the study offers itself as a contribution to the body of research done on hookworm infection.
The general objective of the study is to identify the provincial-level, barangay-level and individual-level factors associated with hookworm infection.
The specific objectives are the following
1. To identify the level 3 or provincial-level variables that are associated with hookworm infection, namely, climate type, average rainfall in 6 consecutive months with HAR, average rainfall in 6 consecutive months with LAR, average maximum temperature in 6 consecutive months with HAR, and average maximum temperature in 6 consecutive months with LAR that are associated with hookworm infection;
2. To identify the level 2 or barangay-level variables that are associated with hookworm infection, namely, land cover type, income classification, percentage of households without any form of toilet facility, and literacy rate;
3. To identify the level 1 or individual-level variables namely, age and gender that are associated with hookworm infection; and
4. To identify if there is an interaction between the level 3 or provincial-level variables namely, climate type, amount of average rainfall during wet season, average rainfall amount during dry season, average maximum temperature during wet season and average maximum temperature during dry season with level 2 or barangay-level variables land cover type in association with hookworm infection.
Hookworm infection is one of the most chronic infections with an estimated 1.3 billion cases globally. In the tropics and subtropics, there is an estimated 740 million cases of hookworm infection. It is common throughout much of South China and Southeast Asia, predominantly occurring amongst the world’s poorest people.
The public health consequence of hookworm infection is Iron Deficiency Anemia. In children, chronic hookworm disease can hinder physical growth and even lower levels of infection will negatively impact and aggravate a child’s well-being. Hookworm infection is also considered a health threat amongst adolescent girls and women of reproductive age, not only because it can reduce fertility and retard fetal intrauterine growth, but because it increases the risk of death both for the mother and fetus. Unlike other helminth infections, hookworm infection is predominant in adults who usually have larger worm burdens than children. As a result, infected adults tend to develop Iron Deficiency Anemia that can slow down their work productivity because of frequent fatigue. Given these consequences of helminth infection, there is a clear need to address the problem because it is not only a health concern but a socioeconomic issue.
Popular misconceptions about hookworm infection treat it as an individual concern or a question of personal hygiene, but several factors affect the development of hookworm infection and these factors operate at different levels. In fact, hookworm infection is influenced by both individual factors and environmental factors. Hence, understanding the environmental factors affecting hookworm survival provides a more comprehensive epidemiologic analysis of disease causation. Knowledge of the environmental factors influencing hookworm survival, which consequently affects hookworm infection, can facilitate geographically targeted soil-transmitted helminthiasis interventions.
The search and review of articles showed that the simultaneous effect of group-level determinants (e.g., a neighborhood’s physical and socioeconomic factors) and individual-level determinants to an individual’s risk of hookworm infection has been relatively unexplored (Appendix 1.4). Typical analyses of hookworm infection have focused largely on either individual-level or ecologic-level determinants but never both levels together and how they relate and co-influence each other. Thus, this study situates itself within that gap in scientific studies on hookworm infection and strives to gain a better insight on an individual’s risk of hookworm infection, by simultaneously analyzing individual-level and ecologic-level determinants of hookworm infection using a multilevel model of analysis.
The results of the multilevel analysis can aid in planning appropriate prevention and control measures, by not isolating cases of hookworm infection as individual problems but by including the environmental factors that affects hookworm survival.
The most prevalent and damaging helminths in many areas worldwide are soil-transmitted (Crompton and Nesheim, 2002; WHO, 1964). Hookworm, a soil-transmitted helminth, is estimated to infect 1.3 billion people globally, and some 65,000 deaths each year can be directly attributed to it (WHO, 2001).
Hookworm infection is one of the most chronic infections in the tropics and subtropics, particularly in developing countries (Chan et al., 1997; Crompton and Nesheim, 2002; De Silva et al., 2003). Unlike other helminth infections which are prevalent in the younger age groups, hookworm infection is common among adults who also tend to have larger worm burdens (Bundy et al., 2004; Chan et al., 1997; Hotez et al., 2004).
In the Philippines, prevalence of hookworm infection ranged from 40-61% nationwide in 1998 (Cabrera, 1998; Shaw et al., 2010). Two local studies done in Mindanao showed that 41% of rural residents in Agusan del Norte (Carney et al., 1987) and 44% in Bukidnon (Carney et al., 1981) were infected with hookworm at the time of the research. Two recently published local studies in Leyte showed that 46% of school children in the area (Ezeamama et al., 2005), and 61% of children and young adults (Shaw et al., 2010) were with hookworm infection.
The most common hookworms that infect man are N. americanus and A. duodenale . They are blood-sucking nematodes that attach to the mucosa of the small intestine and occur as single or mixed infections with other soil-transmitted helminths.
Hookworm eggs exit the human body in feces and, when deposited in moist and shaded soil with adequate warmth of around 25–35oC, hatch into first stage larvae within 24 to 48 hours. Development to first-stage larvae is slower at more extreme temperatures (Pawlowski et al., 1991); in fact, at 15oC hatching does not occur until the fifth day and development of larvae slows down as temperature increases up to 40oC. Some 90% of A. duodenale and N. americanus eggs hatch at temperatures that range from 15-35oC and 20-35oC, respectively. A. duodenale fails to hatch above 40oC; N. americanus above 45oC (Pawlowski et al., 1991).
Hookworm larvae molt twice as they develop to third-stage non-feeding organisms. At this stage, the larva can live for several weeks in the soil until their lipid metabolic resources are exhausted (Hotez et al., 2004). The third-stage larvae are very active. They can move upwards to the uppermost layer of the soil as long as it is moist enough (Pawlowski et al., 1991).
The natural history of hookworm infection may involve (1) the skin at the site of entry of the filariform larvae and as for the species A. duodenale, it may be also acquired through oral route (WHO, 1964); (2) the lung during larval migration; and, (3) the small intestines which is the habitat of the adult worms.
Pawlowski (1991) best describe the pathophysiology of hookworm infection in humans:
“When the invasive filariform larvae penetrate the skin, they may cause a stinging sensation, followed by irritation, erythema, edema and a papulovesicular eruption – the so-called “ground itch”. Migration of larvae through the respiratory tract may cause coughing, due to irritation of the bronchial and tracheal mucous membranes. In the duodenum and jejunum, hookworms attach themselves to the intestine by engulfing a part of the intestinal mucosa in their buccal cavities. At the points of attachment, there is usually some bleeding and inflammatory reaction, but these minute lesions heal quickly when hookworms move to other sites, which they do every 4-6 hours. During the intestinal phase, those infected may have epigastric duodenal-type pain, indigestion, loss of appetite or diarrhea.”
The foremost public health consequence of hookworm infection is blood loss, which can lead to iron deficiency anemia. The relationship between hookworm infection and anemia has been noted as early as 1880 (Farid et al., 1968) and recent studies have confirmed that increasing amounts of hookworm infection result in concomitant decreases in hemoglobin concentration (Awasthi et al., 2003; Bundy et al., 2004; Crompton and Nesheim, 2002; Hotez et al., 2004; Larocque et al., 2005; Stoltzfuz et al., 1996). While this has been discussed briefly in the previous chapter, it is necessary to examine in greater detail the significance of these diseases.
The term “hookworm disease” refers primarily to parasite-induced iron deficiency anemia with reduced host haemoglobin, serum ferritin, and protoporphyrin. The severity of the disease is directly correlated with the number of parasites found in the body, as measured by quantitative egg counts. Blood loss caused by hookworm infection has been estimated at 0.20 ml per worm per day (range 0.14–0.26 ml) for A. duodenale and 0.04ml per worm per day (range 0.02-0.07 ml) for N. americanus (Pawlowski et al., 1991). Consequently, heavy hookworm loads in people with minimum iron stores and low intake of dietary iron can result to iron deficiency anemia within just a few weeks (Pawlowski et al., 1991).
Adults are more susceptible to hookworm infection because of work exposure, particularly those who work in farms or mines where the soil could be contaminated with hookworm larvae. Infected adults usually carry larger worm burdens than children. Consequently, the susceptibility to hookworm infection as well as the larger worm burden generally puts adults at risk of iron deficiency anemia. When hemoglobin levels are below normal, the blood cannot carry oxygen to the tissues, and this adversely affects their fitness to work (Crompton and Nesheim, 2002; Gilgen et al., 2001; Guyatt, 2000; Hotez and Pritchard, 1995; Viteri and Torun, 1974). Thus, anemia, as a secondary complication to hookworm infection especially if it remains untreated, could significantly lessen work productivity.
While adults may be more prone to hookworm infection, hookworm disease in children cannot be taken too lightly. Chronic hookworm disease in children slows down their physical growth (Crompton and Nesheim, 2002). Even lower levels of infection can make unnecessary demands on a child’s resources and well-being.
Infants and pre-school children with iron deficiency anemia caused by hookworm infection are vulnerable to develop behavioral deficits (Bundy et al., 2004; Farid et al., 1968; Hotez et al., 2004). Recent studies suggest that hookworm infection has subtle yet profound adverse effects on memory, reasoning ability, and reading comprehension in children (Ezeamama et al., 2005; Hotez et al., 2004; Kvalsig et al., 1991; Pollitt et al., 1989; Soewondo et al., 1998; Stoltzfus et al., 2001). Hookworm infection may also cause irreversible effects during childhood such as cognitive deficits (Bundy et al., 2004; Hotez and Pritchard, 1995), adverse effects on some elements of mental development (Bundy et al., 2004), and some growth retardation effects (Bundy et al., 2004). The low mental development, cognitive impairment, and underachievement have substantial effects on the child’s ability to be productive in their adult years.
Hookworm infection is considered a major health threat to adolescent girls and women of reproductive age. It can reduce fertility and intrauterine growth rate, and, worse, increase mortality among pregnant mothers and their fetus (Allen, 2000; Bundy et al., 2004). The adverse effect of hookworm infection and anemia is greatest in multigravidas.
According to Dreyfuss et al. (2000), “During pregnancy, iron requirements exceed storage iron for most women. The increased need of the body for iron is due to increase in the red cell mass, iron needs of the fetus and iron losses during delivery. Inadequate iron supply can limit red cell mass expansion and lead to further deterioration in iron status during pregnancy.” Severe anemia during pregnancy is associated with a woman’s increased risk of death, and moderate to severe anemia can increase the risk of low birth weight and preterm delivery (Allen, 2000; Dreyfuss et al., 2000; Von Korff et al., 1992). Consequently, premature birth puts preterm infants at risk of perinatal complications, growth stunting, and low stores of iron and other nutrients (Allen, 2000).
As it is with the risk factors of other diseases, risk factors of hookworm infection do not cause disease by themselves. Rather, disease causation is multi-factorial. In the case of hookworm infection, the risk factors operate at different levels, either on the individual-level or the group-level.
The existence of hookworm infection in a community also depends on the components of the environment that affect parasite life cycle and activity. Its transmission is not solely dependent on personal cleanliness because the eggs are not immediately infective to man. If the eggs are not deposited in soil or other suitable sites, transmission will not occur. Hookworm eggs require particular soil types for survival. Transmission is favored by moist and shaded soils that allow optimum development and survival of the larvae (Appleton et al., 1999; Brooker et al., 2000; Hall et al., 1982; Mabaso et al., 2004; Mabaso et al., 2003; Pawlowski et al., 1991).
The environmental factors that influence hookworm infection in the community are temperature (Appleton et al, 1999; Chanders and Read, 1961; Mabaso et al., 2003; Pawlowski et al., 1991; Saathoff et al., 2005; Udonsi and Atata, 1987), rainfall (Appleton et al., 1999; Beaver, 1953; Brooker et al., 2004; Brooker et al., 2002; Pawlowski et al., 1991), soil type (Beaver, 1953; Mabaso et al., 2004; Mabaso et al., 2003; Pawlowski et al., 1991; Saathoff et al., 2005), shade (Pawlowski et al., 1991; Saathoff et al., 2005; Udonsi and Atata, 1987; Xu et al., 1995), and vegetation (Saathoff et al., 2005).
Temperature is a major determinant on the geographic distribution of hookworm infection in some countries (Appleton et al., 1999; Chanders and Read, 1961; Saathoff et al., 2005). A nationwide survey conducted in China by L. Xu and others (1995) showed a positive curvilinear correlation between the prevalence of hookworm infection and temperature. When temperature, particularly land mean temperature, is higher than 470C, hookworm prevalence decreases (Brooker et al., 2002). At 400C to 450C, most eggs of Ancylostoma duodenale and Necator americanus will fail to hatch; above 450C, larvae of both species will die (Pawlowski et al., 1992). The eggs and larvae of Necator americanus are more tolerant to high temperatures and the larvae can survive up to 450C. On the other hand, larvae of Ancylostoma duodenale is more capable of surviving in low temperatures (Pawlowski et al., 1992; Udonsi and Atata, 1987). The favorable temperature for eggs of Ancylostoma duodenale and Necator americanus to hatch is 150C to 350C while larval survival is most favorable at 200C to 350C (Pawlowski et al., 1992).
The pattern of rainfall is also a major factor to hookworm prevalence. Studies have shown that a positive correlation exists between hookworm infection prevalence and rainfall (Brooker et al., 2004; Brooker et al., 2002). Rainfall provides moisture to the soil which is essential for the survival of the infective larvae. The infective larvae migrate to the soil surface during periods of dampness produced by rain or by moisture condensation (dew). They further migrate upward on the grass or other surfaces where there is moisture. At this layer of the surface soil, the larvae can readily penetrate the skin upon contact with any part of the body.
In contrast, during dry periods, the larvae withdraw from the outermost layer of the soil and escape below the surface. During this period, a high percentage of larvae perish because they fail to escape desiccation. Alternate wetting and drying could hasten the destruction of larvae due to desiccation (Beaver, 1953). Seasonal rainfall that only lasts a few months could result in light infections and low prevalence. For favorable transmission of hookworm, about 100mm of evenly distributed rainfall is required every month (Appleton et al., 1999; Pawlowski et al., 1992).
Rainfall and temperature are climatic factors that interactively facilitate hookworm survival and transmission. Although the parasite is vulnerable to desiccation and high temperatures, heavy rain showers in areas with high temperature can still facilitate hookworm survival (Appleton et al., 1999; Mabaso et al., 2003). Differences in temperature and rainfall across areas result in marked differences in regional and local intensity of hookworm infection (Pawlowski et al., 1992).
Hookworm transmission is most viable in areas where there is high moisture and sandy soils with less than 15% clay content (Beaver, 1953; Mabaso et al., 2004; Mabaso et al., 2003). A loamy soil type facilitates hookworm larval development and survival. It is a mixture of sand, clay and silt that holds moisture but does not become soaked with water. It is for this reason that farmers who practice cropping on loamy soil are at greater risk for transmission of hookworm infection.
Shade and moisture also favor hookworm larval development and survival (Pawlowski et al., 1992; Saathoff et al., 2005; Udonsi and Atata, 1987; Xu et al., 1995). Land cover or vegetation provides shade that shelters surface-dwelling hookworm larvae from ultraviolet radiation and helps retain moisture in the soil which prevents desiccation of the top soil (Saathoff et al., 2005). Heavy infection may also occur in arid zones, or arable land or fruit and vegetable farms, if irrigation provides enough soil moisture.
Economic factors, in particular economic poverty (WHO, 2002) and low literacy (Crompton and Nesheim, 2002; Soewondo et al., 1989) may affect the hygiene practices of the people.
In the poorest countries, unsafe water is one of the top three risk factors leading to disease, disability, or death (WHO, 2002), and poor economic conditions of a community contribute to the limited access to safe water. Also, the community's economic poverty generates unhealthy living conditions and creates barriers to the use of health services and information. A barangay with low or no income might offer less opportunity for proper water and sanitation infrastructure and health programs for treatment and prevention of soil-transmitted helminthiasis (STH). In a community where a high proportion of households are without toilet facilities, there is often indiscriminate defecation in areas where adults and children usually mingle (e.g., the agricultural fields). Consequently, deprivation of the basic water and sanitation services places the entire community at risk of STH diseases.
Furthermore, a community with low literacy usually has poor hygiene practices because of lack of knowledge on good hygiene behavior and practices. For instance, one of the poor hygiene practices that increase an individual’s risk to hookworm infection is not wearing footwear. This habit increases the risk of an individual for hookworm infection, particularly if he or she frequently visits or works in areas where hookworm survival is high, such as agricultural fields. However, in many rural areas, it is common practice for people to play, work, or travel barefoot.
Improving the community’s level of literacy is also important for developing appropriate hygiene education programs (Crompton and Nesheim, 2002; Soewondo et al., 1989). Hygiene educational materials that are not designed according to a community's literacy rate can hinder the delivery of knowledge and affect the people’s hygiene practices. For example, in a community with low literacy rate, the education materials should largely consist of posters with drawings and less written messages.
All of these environmental and economic determinants are factors in the community’s risk susceptibility to hookworm infection. They operate simultaneously with individual-level determinants to constitute the multilayered conditions of this major public health concern.
Hookworm infection is generally more common in adults. An increasing body of evidence suggests that the distribution of hookworm intensity does not exhibit age distributions similar to those of other major soil-transmitted helminths. Unlike ascariasis and trichuriasis where the highest intensity infections occur primarily in school-aged children, high intensity of hookworm infections frequently occurs in adult populations (Bundy et al., 2004; Chan et al., 1997; Gandhi et al., 2001). The intensity of hookworm infection steadily rises during childhood and then peaks and levels off in adulthood (Hotez et al., 2004).
Furthermore, the prevalence of hookworm infection in adults is more varied as compared to children, and this is reflected by the age-specific trend in the proportions infected (Bundy et al., 2004). The highly variable distribution of hookworm infection among adults can be explained by variable work conditions and exposures. In particular, those who work in the fields where Necator americanus and Ancylostoma duodenale are prevalent are more at risk of hookworm infections. It is generally thought that the differences in levels of hookworm infection in children and adults are due to exposure differences, as hookworm is generally transmitted in the fields (Chan et al., 1997; Chanders and Read, 1961). This may also explain why the overall prevalence and intensity of hookworm infection are higher in males than in females, because fields and mines, where hookworm thrive, are often male-dominated fields of work (Cabrera, 1998; Chanders and Read, 1961; Hotez et al., 2004).
In the Philippines, the difference in the prevalence of hookworm infection between children and adults may also be attributed to the control and prevention program for Soil-Transmitted Helminthiasis (STH) infection. The Soil-Transmitted Helminthiass Control Programme of the Department of Health began in 1999 (Crompton et al., 2003) for an efficient control of STH infection through mass deworming. The main strategy of the program was mass targeted treatment of 2 to 14 year old children. Children aged 2-5 years old are treated as the mother gives the antihelminthic drug to the child under the supervision of barangay health workers. While children aged 6-14 years, teachers provide the antihelminthic drugs under the supervision of a school nurse. The prescribed duration of treatment is 3 years because eggs remain viable in the soil and are infective for up to 2 years. At the end of 3 years, treatment should become selective provided that prevalence and intensity of infection have declined.
Other major individual-level determinants of hookworm infection are occupation (Brooker et al., 2003; Bundy et al., 1995; Cabrera, 1998; Chan et al., 1997; Chongsuvivatwong et al., 1994), defecation habits (Cabrera, 1998; Chanders and Read, 1961; Pawlowski et al., 1991), poor footwear practices (Mangali et al., 1994), and use of night-soil as fertilizer (Pawlowski et al., 1992; Xu et al., 1995).
As previously discussed, the individual’s type of work is considered as a determining factor for hookworm infection. The use of night-soil as fertilizer also puts field workers at risk of infection. Poor sanitation practices such as indiscriminate defecation increases an individual’s susceptibility to hookworm infection because of probable contact with soil where hookworms thrive. If workers with hookworm infection defecate on soil which they regularly have contact with (i.e., agricultural fields and mines) and their coworkers work barefooted, the infective hookworm larvae can penetrate their skin. This can also happen in communities where there is no proper waste disposal and people defecate indiscriminately in common areas where adults and children mingle.
Moreover, apart from the aforementioned economic factors such as low literacy and lack of education, an individual’s personal knowledge and attitude about hygiene and sanitation also certainly, albeit indirectly, affects hookworm infection (Soewondo et al., 1989). One’s knowledge and attitude about hygiene and sanitation affect one’s hygiene and sanitation practices, which have a direct link to one’s susceptibility to hookworm infection. For example, an individual who does not know or has poor attitude towards safe fecal disposal and footwear practices as preventive measure against hookworm infection would be more likely to have poor hygiene and sanitation practices. Consequently, the poor practice of hygiene and sanitation increases an individual’s risk of hookworm infection.
Multilevel modeling has been used in the fields of sociology, education and demography. More recently, it has become valuable in epidemiologic studies, due in part to the increasing interest in the potential ecological-, macro- or group-level determinants of health, but more significantly in its contributions to the analysis of practical implications for the prevention of disease (Diez-Roux and Aiello, 2005; Diez-Roux, 2004; Diez-Roux, 2000; Von Korff et al., 1992).
In this study, the outcome of interest (i.e., presence of hookworm infection) is associated with processes operating at more than one level. In order to gain a more complete understanding of the etiology of hookworm infection, all the relevant levels will be considered in the analysis simultaneously.
Multilevel analysis or MLA is the appropriate statistical approach for data with a hierarchical structure (Diez-Roux and Aiello, 2005; Diez-Roux, 2000; Goldstein, 1995; Hox, 1995; Snijders and Bosker, 1999). A multilevel regression model takes the variability at different levels of the data into account and allows simultaneous examination of effects of factors at different levels to the individual-level outcome (Diez-Roux and Aiello, 2005; Duncan et al., 1998; Weich et al., 2003). MLA examines the factors at different levels of the data and does not force aggregation of data to one level of analysis.
Fundamental to multilevel modeling is “that the outcome has an individual as well as group aspect.” (Snijders and Bosker, 1999) This analytical framework is reflected in the study model by including explanatory variables at the individual-level and at the group-level. Unexplained variations in the 2 higher levels of the data are modeled as well. Unexplained variations between-groups are conceived as random variation, or what are commonly expressed in multilevel models as “random effects.” Thus the multilevel models of hookworm infection include an error term for the 2nd and 3rd level (Hox ,1995; Snijders and Bosker, 1999).
Multilevel models are constructed either by including random intercepts only or by including both random interceptsA and random slopesB (Appendix 2.1.4) Variables may also be added to the model to explain variability at the individual and group levels, and to explain the differences in slopes. For example, in a model with 2 levels where the 2nd level is the barangay, a random intercept can account for unobserved group effects between barangays. These unobserved group effects may be attributed to the different vegetation present in various areas in the barangay. Including a barangay-level (2nd level) variable “vegetation” could explain part of the group effects.
Multilevel models are the suitable technique of analysis for data with hierarchical structures of various origins because the conventional regression models do not recognize the existence of clustering of individuals and may render invalid inferences. Conventional regression models can utilize only one of either individual- or group-level factors when examining effects and random variations (called random error). Meanwhile, the analytical model of individual-level studies can only incorporate the individual-level explanatory variables in explaining the individual health outcome and its variance. In ecologic studies, where the unit of analysis is the group, the analytical model includes only group-level explanatory variables with the outcome variable measured at the group-level. In a multilevel analysis, the model can accommodate group-level variables and adjust to individual-level variables in explaining the individual health outcome.
Furthermore, multilevel analysis allows the effects of individual-level explanatory variables to vary from group to group, and examines not only inter-individual variability but also inter-group variability (Diez-Roux and Aiello, 2005). If a dataset has a hierarchical structure, the data at the lower level may be dependent on the higher levels and application of a conventional statistical approach might lead to underestimation of the standard errors. Meanwhile, applications of multilevel analysis to examine such data will model this nested-effect explicitly and prevent erroneous inferences.
If the hierarchical structure of the data is ignored, the data will inevitably be analyzed at either an aggregate level or disaggregate level. Incorporating group-level characteristics by disaggregating higher-level variables to the individual-level dramatically increases the sample size of the group-level variables. By disaggregation, the individual outcome will be treated independent from each other even if the individual outcomes within groups are actually correlated. The basic assumption of independence of observations in traditional regression will thence be violated. The wrong assumption that these observations are independent would lead to complacency in the estimated level of significance arising out of the underestimation of standard errors. The consequence is an inflated probability of type 1 error when examining between-group differences and conservative tests when examining within-group differences (Diez-Roux, 2000; Duncan et al., 1998; Goldstein, 1995; Snijders and Bosker, 1999).
Epidemiologists have had a long-standing interest in how environmental and social-related variables modify individual susceptibility to disease (Macmahon and Trichopoulos, 1996; Pawlowski et al., 1991). There has also been an acknowledged need to simultaneously examine individual- and group-level factors in studying the causes of diseases (Appleton et al., 1999; Beaglehole et al., 1993; Diez-Roux, 2004; Diez-Roux, 1998; Duncan et al., 1998). In the epidemiologic triangle, the group-level factors represent the “environment,” which, depending on the scale of the study, may be defined at different levels and characterized by specific factors (Gordis, 1996; Mauny et al., 2004).
In a study of susceptibility to hookworm infection, it must be taken into account that there is a relationship between individual susceptibility to infection and environmental factors because hookworm infection is a persistent cycle where hosts are continually re-infected upon their exposure to an environment that favors the survival of the infective larvae. The data gathered for this study thence has three levels and ordered hierarchically: individuals (level 1 units) are subsumed under barangays/municipal (level 2 units), which are, subsumed under provinces (level 3 units). The structure of the dataset takes into account the conditions that the risk to hookworm infection is influenced by both individual (level 1) and environmental factors (level 2 and level 3).
Figure 2.2.1 represents the conceptual framework of this study: a multilevel structure of hookworm infection model which includes the individual-, barangay/municipal- and provincial-levels in the analysis. The individual-level is in the innermost oval and the ecologic- or environment-level is the area outside the innermost oval. The ecologic-level is divided into two: the barangay/municipal-level and the provincial-level.
The individual-level factors included in the study are age (Bethony et al., 2002; Bundy et al., 2004; Chan et al., 1997; Hotez et al., 2004; Saathoff et al., 2005;) and gender (Cabrera, 1998; Hotez et al., 2004; Saathoff et al., 2005) because these are hypothesized to affect the individual’s risk of acquiring hookworm infection (Bundy et al., 2004). There are differences in susceptibility to hookworm infection between children and adults that may be explained by the fact that adults are the ones who usually work in the fields, such in farms or mines, where the physical condition of the soil and other environmental factors favor the survival of the infective larvae. Between genders, the difference of hookworm infection may be explained by the differences in work exposure of men and women. Farming and mining, for instance, which are major sources of livelihood in the areas studied here, are male-dominated occupations. However, presently, there are females, particularly those in the reproductive age groups, who are getting more involved in farming, putting them at risk of hookworm infection and, consequently, anemia, which is the insidious effect of hookworm infection.
Type of occupation (Brooker et al., 2004; Cabrera, 1998; Chan et al.,1997; Mangali et al., 1994; Pawlowski et al., 1991), defecation habits (Cabrera, 1998; Pawlowski et al., 1991; Saathoff et al., 2005), knowledge and attitude about hygiene and sanitation, poor footwear practices (Mangali et al., 1994) and use of night-soil (Brooker et al., 2004; Pawlowski et al., 1991) as fertilizer are also risk factors of hookworm infection. However this study will not examine these individual factors because they were not collected in the prevalence survey of schistosomiasis.
Meanwhile, the ecological factors in 2nd level and 3rd level that are taken into consideration in this study are hypothesized to influence, not just the individual’s risk of acquiring the infection, but on the overall prevalence of hookworm infection. This hypothesis is consistent with the ecological theory of hookworm infection that environmental characteristics favorable to the survival of hookworm are most likely to influence hookworm infection of the population.
The 2nd level factors studied here are land cover type, barangay income classification, barangay literacy rate and percentage of household in the barangay without any form of toilet facility.
The land cover type of the barangay is significant to the study because it defines the vegetation present in the community. Vegetation provides shade and moisture to the soil, which makes hookworm survival favorable (Brooker et al., 2004; Brooker et al., 2002; Chanders and Read, 1961; Ezeamama et al., 2005; Pawlowski et al., 1991). Conversely, open areas with an unfavorable temperature and rainfall pattern is detrimental to larval survival. While studies have shown that the community’s type of soil is a determinant of hookworm prevalence as well, this environmental factor will not be analyzed because the data on soil type from the Bureau of Soil and Water Management of the Department of Agriculture is inappropriate and insufficient for the study at hand.
The barangay/municipal-level income classification and barangay/municipal-level literacy rate of the studied areas will also be examined in the research. These are socioeconomic indicators which can impact the prevalence of hookworm infection. In this study, the municipality income classification will be used as the barangay income classification, because the Philippines has a decentralized health system and the lowest political jurisdiction for government planning and resource allocation is the municipal level. Indeed, the local government plays a central role in providing the community with access to public health services. Consequently, a barangay in a municipality with low income may offer fewer opportunities for water and sanitation projects, such as water and sanitation infrastructures, hygiene education campaign, and mass treatment. Lack or deprivation of hygiene education and soil-transmitted helminthiases prevention programs in a community can collectively put the residents at risk of infection.
Another ecological factor to consider is the percentage of households in the barangay without any form of toilet facility. The availability of such facilities may mediate the individual’s hygiene practices with resulting effects on his/her susceptibility to hookworm infection. A community with a high proportion of households without toilet facility may result in the residents’ indiscriminate defecation in areas where adults and children usually mingle (e.g., in the agricultural fields where both parents and children work together), thus increasing risk to helminth infection. The mediating effect of higher-level variables to the individual’s poor hygiene practices is called nested-effect or “cross-level interaction.”
The 3rd level factors considered in this study are climate type, temperature and rainfall. These are provincial-level factors (Appleton et al., 1999; Beaver, 1953; Mabaso et al., 2003; Pawlowski et al., 1991; Saathoff et al., 2005; Udonsi and Atata, 1987) that influence hookworm prevalence in an area because they play an important role in the hookworm life cycle and transmission (Cabrera, 1998; Hotez et al., 2004; Pawlowski et al., 1991). As may be deduced from the previous chapter’s discussion on the life cycle of hookworm, evenly distributed rainfall all year round and favorable temperature facilitate hookworm survival.
illustration not visible in this excerpt
[A] Random intercept – Suppose Abbildung in dieser Leseprobe nicht enthaltenis the constant intercept of a traditional logistic regression. Since the data is hierarchically structured with 3 levels, thenAbbildung in dieser Leseprobe nicht enthaltenis expanded to Abbildung in dieser Leseprobe nicht enthalten making the intercept random, that is varying between level 2 units (denoted by Abbildung in dieser Leseprobe nicht enthalten) and level 3 units (denoted by Abbildung in dieser Leseprobe nicht enthalten).
B Random slope - Suppose Abbildung in dieser Leseprobe nicht enthaltenis the constant coefficient (slope) of one individual-level explanatory variable Abbildung in dieser Leseprobe nicht enthaltenin logistic regression model. Since the data is hierarchically structured with 3 levels, then Abbildung in dieser Leseprobe nicht enthaltenis expanded to Abbildung in dieser Leseprobe nicht enthalten making the coefficient random by varying between level 2 units (denoted by Abbildung in dieser Leseprobe nicht enthalten) and level 3 units (denoted by Abbildung in dieser Leseprobe nicht enthalten).
This research was a cross-sectional study that examined both ecologic and individual correlates of hookworm infection. The individual correlates of hookworm infection were presented in the first level of the model while the ecologic determinants of hookworm infection were presented in the two higher levels: the barangay/municipal-level and the provincial-level (Appendix 3.1).
This study did a secondary analysis of data generated in the Prevalence Survey of Schistosomiasis in Mindanao and data generated by several government agencies. Information on the individual-level variables came from the 2005 Prevalence Survey of Schistosomiasis in Mindanao while data on the group-level variables came from the Department of Interior and Local Government, National Mapping and Resource Information Authority (NAMRIA, 2005), Philippine Atmospheric, Geophysical and Astronomical Services Administration (PAGASA, 2004), and the National Statistics Office (NSO, 2000). Despite the fact that the data utilized by this study were all secondary data, the author had the study proposal reviewed and subsequently approved by the College of Public Health Ethics Review Committee (Appendix 3.2).
The first phase of the Prevalence Survey for Schistosomiasis in the Philippines was conducted in MindanaoA and began in 2005 through the collaborative efforts of the Department of Health, College of Public Health of the University of the Philippines Manila, and the World Health Organization. The data for the individual-level factors were gathered from the first phase of the schistosomiasis prevalence survey.
The first phase of the Prevalence Survey for Schistosomiasis used stratified 3-stage systematic cluster sampling design. The stratification variables were region and the prevalence level of schistosomiasis. Mindanao has 6 regions and 25 provinces. The provinces in each region were classified into three levels of prevalence of schistosomiasis: those with high schistosomiasis prevalence rates (>8%), those with moderate schistosomiasis prevalence rates (>2% to 8%) and those with low schistosomiasis prevalence rates (≤2%). All provinces in the first two groups (high and moderate prevalence rates) were included while random selection was done for the provinces with low prevalence rates. The primary sampling units were the provinces and the secondary sampling units were the barangays. The barangays were selected proportional to the provincial population size. A master list of all the households in the barangay was used to systematically select the sample households. Within the selected households, household members aged two years and above were eligible to participate in the survey.
Two stool samples were collected on separate days from the eligible household members in the selected households. Using the Kato-Katz thick smear examination, the collected stool samples were diagnosed for schistosomiasis and for the possible presence of eggs of other parasites such as hookworm. Each individual’s samples were processed and all slides prepared from the survey were kept and stored properly.
The survey team was composed of barangay health workers (BHWs) and two microscopists. The BHWs had all undergone data collection training facilitated by the study investigators before the field work. During the survey, the role of the BHWs was to inform the community to be surveyed, distribute the stool cups to households concerned, and collect the stools. The microscopists prepared the stools for the Kato-Katz examination, read the slides, and recorded the results.
Readings from the slides were written on standard forms which were brought to the College of Public Health (CPH) of the University of the Philippine Manila for encoding. The same was done for the accomplished survey forms. All survey data and slide readings were encoded using Epi Info, wherein a customized data structure with a check and validation program had been developed prior to data collection.
During the time the survey was conducted there was no ethical requirement, however, a verbal informed consent was obtained from the participants.
The second-level variables considered were land cover type, barangay income classification, literacy rate and percentage of households without any form of toilet facility. The land cover type data came from National Mapping and Resource Information Authority (NAMRIA), which was collected in 2005 and published in 2006. The barangay income classification data came from Provincial Profiles of the National Statistics Office (NSO). The literacy rate and percentage of households without any form of toilet facility were derived from the 2000 Census of Population and Housing from the National Statistics Office. Income classification of the municipalities or cities was from the Department of Interior and Local Government. Meanwhile, the data for the third-level variables (climate type, average monthly rainfall, and average monthly maximum temperature) came from the Climate Data of the Philippine Atmospheric, Geophysical and Astronomical Services Administration (PAGASA) collected from 2000 to 2004.
This study used only the data from the Prevalence Survey for Schistosomiasis in 2005 that have climate information from PAGASA. Only respondents from provinces with climatic data from PAGASA were included for the analysis to attain one of the objectives of the study which was to determine the effects of climate on the risk of hookworm infection. There were seven provinces in Mindanao with recorded data on rainfall amount and maximum temperature: Surigao del Norte, Agusan del Sur, Bukidnon, Misamis Oriental, South Cotabato, Surigao del Sur, and Davao del Sur. Hence, using only the data from these provinces, the study examined the age and gender of 7,018 respondents (Appendix 3.3).
This study had 3 set of variables: 1st level variables are collected from the individuals, 2nd level variables are barangay/municipal data, and 3rd level variables are provincial data.
The dependent variable is
Hookworm Infection - an individual was considered positive with hookworm infection if hookworm eggs were found in his/her stool sample as examined by the microscopist. The following were the symbols used to indicate the result of the diagnosis:
1 = with hookworm infection if at least one hookworm egg was found in at least one of the two slides used in stool examination
0 = without hookworm infection if no hookworm egg was found in the two slides used in stool examination
The independent variables are:
Age - This variable refers to the age in years of the respondent as of his/her last birthday from the date of survey. The age variable was further dichotomized in the analysis stage:
1 = 15 years old and above
0 = 14 years old and below
Gender - This variable refers to the gender of the respondent.
1 = Male
0 = Female
Land Cover Type - refers to the different land or vegetative covers of the area.
1 = Closed or open forest
2 = Mangrove forest
3 = Natural and wooded land
4 = Cultivated land
5 = Fishpond, built-up area or inland water
The land cover classification variable was dichotomized in the analysis stage:
1 = predominantly cultivated land
0 = predominantly closed/open forest, mangrove forest, natural and wooded land, fishpond, built-up area or inland water
Income Classification - Municipalities or cities in the Philippines are divided into income classes according to their average annual income during the last four calendar years.
illustration not visible in this excerpt
Percentage of Households in the Barangay Without Any Form of Toilet Facility - This variable refers to the proportion of households in the barangay without any form of toilet facility.
Literacy Rate - The literacy rate refers to the proportion of individuals who are 10 years or older who can read and write simple messages using his or her own language.
illustration not visible in this excerpt
Average Rainfall in 6 Consecutive Months with High Amounts of Rainfall (HAR) - This variable refers to the average amount of precipitation in the province during the six consecutive months of the year with high amounts of rainfall. This data is collected in the weather station and is expressed in millimeters measuring the depth of the layer of water which had fallen. Abbildung in dieser Leseprobe nicht enthaltenin the equation is the amount of rainfall in the i th month. Then this variable was dichotomized in the analysis:
1 = Average rainfall of 100mm or less
0 = Average rainfall of more than 100mm
Average Rainfall in the 6 Consecutive Months with Low Amounts of Rainfall (LAR) - This variable refers to the average amount of precipitation collected in the weather station for 6 consecutive months with low amounts of rainfall. It is expressed in millimeter depth of the layer of the water which has fallen. Abbildung in dieser Leseprobe nicht enthaltenin the equation is the amount of rainfall in the i th month. Then this variable was dichotomized in the analysis:
1 = Average rainfall of 100mm and more
0 = Average rainfall of less than 100mm
Average Maximum Temperature in 6 Consecutive Months with High Amounts of Rainfall (HAR) - This variable refers to the average maximum temperature during the 6 consecutive months with high amounts of rainfall. The maximum day temperature usually occurs in the early afternoon. Abbildung in dieser Leseprobe nicht enthaltenin the equation is the maximum temperature in the i th month.
Average Maximum Temperature in 6 Consecutive Months with Low Amounts of Rainfall (LAR) – This variable refers to the average maximum temperature during the 6 consecutive months with low amounts of rainfall. This data is still based on the maximum day temperature which typically occurs in the early afternoon. Abbildung in dieser Leseprobe nicht enthaltenin the equation is the maximum temperature in the i th month.
Climate Type – This variable refers to the prevailing weather conditions in a particular region.
Type 1 = Two pronounced seasons: dry from November to April, wet the rest of the year
Type 2 = No dry season, with very pronounced rainfall from November to January
Type 3 = Seasons are not very pronounced: relatively dry from November to April, wet during the rest of the year
Type 4 = Rainfall is more or less evenly distributed throughout the year
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