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Arsenic contamination awareness among the rural residents in Bangladesh
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Social Science & Medicine 59 (2004) 1741–1755
Arsenic contamination awareness among the rural residents in Bangladesh Bimal Kanti Paul* Department of Geography, Kansas State University, Manhattan, KS 66506, USA
Abstract Arsenic poisoning of tubewell water, which constitutes the primary source of drinking water, has become the greatest health threat to the people of rural Bangladesh. Somewhere between 35 to 57 million people in the country are now suspected of being affected by drinking water contaminated with arsenic. While the Bangladesh government, nongovernment organizations (NGOs), and bilateral and multilateral assistance agencies are involved in combating this dreadful problem, all of their efforts to date have proceeded without having grassroots information about arsenic poisoning. The objectives of this study are to investigate the level of knowledge rural residents have regarding arsenic poisoning and to identify the correlates of that knowledge. Questionnaire surveys administered among residents of four rural areas in Bangladesh provided the major data source for this study. Twenty villages were selected from moderate and low arsenic risk regions and a total of 356 respondents, 177 from medium risk regions and 179 from low risk regions, were interviewed. Analysis of the survey data reveals that arsenic awareness is currently not widespread in the study villages, particularly in the low arsenic risk region. There are also gaps in arsenic knowledge regarding the diseases caused by arsenic poisoning and mitigating measures available to prevent contamination. This study identified arsenic risk region, level of education, gender, and age as important determinants of arsenic knowledge. The findings of this study will aid in making existing health education programs more effective and in reducing the risk of developing arsenic-related illnesses. r 2004 Elsevier Ltd. All rights reserved. Keywords: Arsenic contamination; Water supply; Rural Bangladesh; Health education; Mitigation; Risk regions
Introduction Arsenic in the drinking water of Bangladesh at levels exceeding the acceptable limit set by the World Health Organization (WHO) has emerged as a serious health problem in the country (Paul & De, 2000; Hossain, 2002).1 An estimated 35 to 57 million people in this country with a population of 130 million are now believed to be affected by drinking water contaminated with arsenic (see Akmam & Higano, 2002). Hand pumped tubewells (HPTWs), drawing water from *Tel: +1-785-532-3409; fax: +1-785-532-7310. E-mail address: [email protected] (B.K. Paul). 1 WHO’s recommended safety standard for arsenic concentration is 10 parts/billion (ppb) or 0.01 mg/l, the Bangladesh drinking-water standard is 50 ppb (0.05 mg/l).
underground sources, constitutes the primary source of drinking water for more than 95% of the rural population of Bangladesh (Caldwell, Caldwell, Mitra, & Smith, 2003a).2 Best estimates indicate that the total 2
Three types of tubewells (TWs) are in use in Bangladesh to extract groundwater for drinking and irrigation purposes: hand pumped tubewells (HPTWs), shallow tubewells (STWs), and Deep tubewells (DTWs). The water from STWs and DTWs is used primarily for irrigation purposes. Arsenic contamination is primarily confined to shallow aquifers, 33–230 ft (10–70 m) below the surface. Most HPTWs and STWs operate within these depths and were installed in the 1970s and 1980s in an effort to shift the country’s drinking water supply from surface to groundwater sources. This shift was prompted because drinking untreated surface water was determined to be the principal cause of widespread waterborne diseases among the rural population of Bangladesh, particularly children.
0277-9536/$ - see front matter r 2004 Elsevier Ltd. All rights reserved. doi:10.1016/j.socscimed.2004.01.037
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number of HPTWs in operation falls somewhere between 3 and 5 million (Hossain, 2002). Many Bangladeshis are suffering from arsenic-related diseases ranging from melanosis to skin cancer and gangrene (Fazal, Kawachi, & Ichion, 2001a). A recent report maintains that arsenic-tainted tubewell water is contributing to nearly 125,000 cases of skin cancer and killing 3000 in Bangladesh each year (see Clarke, 2003). The mortality rate from arsenic poisoning is expected to rise substantially in the near future. Arsenic was first detected in tubewell water by the Department of Public Health Engineering (DPHE) of the Bangladesh government in 1993. This issue received wide-spread attention in early 1995 when arsenic contamination was shown to be present across central and southern Bangladesh (Paul & De, 2000). The old deltaic plain of southwestern Bangladesh, the north and eastern parts of the active deltaic plain of the southern coast, and the Meghna River basin have been severely impacted by arsenic. In contrast, northwestern and southeastern Bangladesh have been less affected by arsenic poisoning Most scientific attention to date has focused on identifying the sources and causes of arsenic contamination and in developing cost-effective measures to remove arsenic from groundwater. While ascertaining the source and developing methods to remove arsenic from groundwater are essential in combating the contamination, research efforts should expand beyond these activities because arsenic poisoning has no immediate cure. Prevention is the best way to combat this problem. Additionally, all efforts undertaken to mitigate arsenic contamination thus far have proceeded without assessing the grassroots knowledge residents have of the problem. What do rural residents in Bangladesh, the beneficiaries of the remedial activities, think about the arsenic contamination problem? Are they aware of the problem? How accurate is their knowledge about contamination? The objectives of this study are to investigate the extent to which rural residents in Bangladesh possess knowledge of arsenic poisoning and to determine the association between various socio-economic and demographic characteristics of these residents and level of knowledge. Results of this study should help identify specific areas and segments of society where arsenic mitigation efforts need to be intensified. Interest in this study is not only to determine whether respondents have heard about the arsenic contamination problem per se, but to ascertain whether they are knowledgeable about important aspects of arsenic poisoning including the sources and the means by which it can be prevented. Specifically, knowledge of arsenic contamination as used in this study refers to whether respondents are familiar with the source of the poisoning, its symptoms, diseases caused by the poisoning, and its prevention.
Arsenic-related knowledge is compared between respondents living in regions classified as low and medium risk for arsenic contamination. Surveys conducted in 2001 and 2002 by this author found that residents in high risk areas were aware of the source and symptoms of arsenic poisoning, as well as diseases caused by ingestion of arsenic contaminated water (see also BGS/DPHE, 2001; Akmam & Higano, 2002; Caldwell et al., 2003a).3 This earlier finding motivated the exclusion of high-risk areas from the present study. To provide necessary background information for this study, general discussion on the spatial extent, sources, and causes of arsenic contamination in Bangladesh, including arsenic-related ailments and preventive measures, is presented in the next section. Research methods employed in this study are subsequently discussed. Among other methodological issues, this section provides a detailed note on construction of arsenic knowledge score. This is followed by a section that presents the results of the empirical analysis. The final section is devoted to concluding remarks.
Arsenic contamination in Bangladesh: a background Spatial extent of contamination Since the mid-1990s many national and international organizations have been involved in identifying arsenic contaminated tubewells in Bangladesh. Because of the lack of sophisticated laboratory facilities and financial constraints, most of these organizations began analyzing tubewell water by using a simple, and inexpensive fieldkit-method. This ‘field-kit’ is an instrument designed to identify whether arsenic is present in the sample water; it cannot detect the absolute concentration of arsenic in groundwater (Fazal et al., 2001a). Importantly, laboratory validations have revealed that these field kits frequently provide inaccurate results (see Pearce & Hecht, 2002). Although several organizations have used laboratory methods to identify arsenic concentration in tubewell water, only two such studies are based on nation-wide surveys; one is by the Dhaka Community Hospital (DCH) and the School of Environmental Studies (SOES) of Jadavpur University, Calcutta, India and the other is by the British Geological Survey (BGS) and DPHE. The former study collected data during 1995– 2000, while the latter was conducted in 1998–1999 (Akmam & Higano, 2002). The survey conducted by the DCH and SOES was biased in that arsenic victims were first identified and then tubewell water used by those victims was tested for arsenic contamination. For this 3 These surveys were funded by the National Science Foundation (NSF). The report is under preparation.
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reason, this paper uses information from the BGS and DPHE survey to establish the spatial extent of arsenic contamination in Bangladesh. The BGS/DPHE survey applied a stratified random sampling throughout Bangladesh with the exception of three hilly districts (i.e., Rangamati, Khagrachhari, and Bandarban) in the southeast. A district is the second largest administrative unit in Bangladesh with an average population of slightly over two million. The three hilly districts were not included in the survey because no primary symptoms of arsenicosis contamination were found there. The BGS/DPHE survey consisted of water samples collected from 3534 tubewells located in 433 of the 496 thanas throughout Bangladesh.4 Sample density was about 8 samples per thana, representing approximately one sample per 14 square miles (37 square km) (BGS/DPHE, 2001). The BGS and DPHE survey revealed that arsenic concentrations ranged from less than 0.25 ppb to over 1600 ppb (16 mg/l); the mean concentration was about 55 ppb (0.06 mg/l) (Hossain, 2002). Fig. 1 presents average arsenic concentration by district and shows that 10 of the 61 sampled districts have an arsenic concentration below the WHO standard (10 ppb) and the arsenic level ranges between the WHO and Bangladesh standard (50 ppt) in 27 districts. The former 10 districts are least affected, while the latter 27 districts may be considered moderately affected. The remaining 20 districts have arsenic levels exceeding the Bangladesh standard and can be considered severely affected by arsenic contamination (Fig. 1). Results illustrated in Fig. 1 suggest that nearly half of Bangladesh, lying primarily south of the Ganga River, suffers more from elevated arsenic levels than the rest of the country. Unlike other parts of Bangladesh, most rivers in the western part of this region (also known as the Moribund Delta) are less active with reduced flow or dry riverbeds. This plain is higher in elevation than the surrounding countryside and thus experiences less frequent inundation. Moreover, this part receives less rainfall (about 60 in or 1500 mm) than other parts of the country. Lack of annual replenishment in the upper aquifers may be associated with increased arsenic levels in this physiographic region. Active delta regions of Bangladesh, located east of the Moribund Delta, are subject to the action of tides and tidal effects play a significant role in fluvial processes of the distributary channels up to a distance of about 100 miles (150 km) upstream from estuaries (Johnson, 1975). These active delta regions and the Meghna River basin, which experience flooding every year, receive about 80 inches (2000 mm) of rainfall annually. Because of the annual inundation, it is difficult to explain why the
4
A thana is the basic administrative unit in Bangladesh.
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groundwater in portions of these zones contains high levels of arsenic. Most districts of northwestern Bangladesh contain a portion of the Barind which is a generally undulating region consisting of soils similar to those found in the Chittagong Hill Tracts. Facing the Barind across the Jamuna flood plain is the Madhupur Tract. This tract covers a large part of Gazipur district in central Bangladesh. As shown in Fig. 1, arsenic contamination in groundwater is relatively low in this district. Both the Barind and Madhupur Tracts share similar physiographic characteristics. Spatial patterns of arsenic contamination illustrated in Fig. 1 should be viewed carefully because there is considerable short-range variation in arsenic concentration from well to well. Even in areas of generally low arsenic concentrations, there are occasionally ‘hot spots’ where a cluster of wells with unusually high concentrations of arsenic can be found. Another reason for exercising caution stems from the need for retesting tubewells that have previously been reported as being marginally safe. Additionally, arsenic concentrations are believed to change by season and from year to year and several researchers have suggested that all arsenic interventions must be guided by repeated testing of tubewell water for arsenic levels (see Caldwell, Caldwell, Mitra, & Smith, 2003b). However, such sampling would require a institutionalized testing program in the country. Sources and causes of arsenic contamination in Bangladesh The precise cause of high arsenic concentration in the groundwater of Bangladesh has not been identified. Initially, several anthropogenic sources of potential arsenic contamination were considered, such as the excessive utilization of groundwater to both irrigate land and provide safe drinking water. Some researchers linked elevated arsenic levels with indiscriminate use of sub-standard agrochemicals since the early 1970s (Paul & De, 2000). Others have claimed it is a human-induced disaster caused by the diversion of surface water from the river Ganga by India (Bridge & Hossain, 1999). Still other explanations offered include the use of arsenic compounds as preservatives in wooden electric utility poles of the Rural Electrification Board, HPTW filters coated with arsenic compounds, industrial waste disposal, and enhanced leaching beneath irrigated lands (BGS/DPHE, 1999). On going research has called into question the veracity of these explanations. Two prevailing notions, pyrite oxidation and oxyhydroxide reduction, describe the likely method of arsenic contamination in the groundwater of Bangladesh (Fazal et al., 2001a, 376; Harvey et al., 2002). According to the first, arsenic is assumed to be present in
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Fig. 1. Extent of arsenic concentration in groundwater in Bangladesh by districts. Source: BGS/DPHE (2001).
certain sulphide minerals (pyrites) that are deposited within aquifer sediments at a depth of 66–330 ft (20– 100 m) by the major rivers of Bangladesh and India. Because of intensive irrigation development in the country, the underground water table drops creating a void which is then filled by atmospheric oxygen (Lepkowski, 1998). This inflow of oxygen and light pressure from tubewell water help break down sulphide in the arsenic-laden pyrite rock into fine particles. These particles later dissolve in groundwater (Bagla & Kaiser, 1996). Seasonal fluctuation of the water table also results in the rapid and regular intake of oxygen. The pyrite
oxidation theory is also known as the ‘lowering water table hypothesis’ (Fazal, Kawachi, & Ichion, 2001b). The oxy-hydroxide reduction hypothesis posits that the source of arsenic is geological and forms in an anoxic environment, a condition expected at the depths to which the tubewells are drilled (see Nickson et al., 1998). Arsenic is assumed to be present in alluvial sediments, concentrated in sand grains as a coating of iron hydroxide. These sediments were eroded from the Himalayas and deposited in the Bengal Basin. Organic matter deposited with the sediments reduces the arsenicbearing iron hydroxide and this reduced material—when
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exposed to aquifer water—leaches arsenic into the water (Lepkowski, 1998). Reduction of iron hydroxide is enhanced in this scenario by bacterial activity (Khan & Alam, 2000). According to the oxy-hydroxide hypothesis, the origin of arsenic rich groundwater in Bangladesh is due to natural processes and has no relationship to the excessive groundwater withdrawal. Based on empirical data, the BGS/DPHE rejected the pyrite oxidation hypothesis and accepted the oxyhydroxide reduction hypothesis as the most plausible cause of arsenic contamination in the groundwater of Bangladesh. However, several experts have questioned the validity of the BGS/DPHE findings (see Fazal et al., 2001a, b). Based on an investigation of 15 drilled wells in one site in southern Bangladesh, Harvey et al. (2002) claim that irrigation pumping may affect arsenic concentration, but not by the oxidation of sulfides as has been proposed. A detailed analysis of the causes of groundwater contamination with arsenic by Fazal et al. (2001b) concluded that their own findings as well as the BGS/DPHE results are not dependable enough to offer any conclusion regarding the cause of arsenic contamination. There are, however, traditional explanations for sources and causes of arsenic contamination in Bangladesh. Many villagers in arsenic-prone areas do not suspect that anything is wrong with tubewell water because the water has no bad smell and/or taste. Moreover, they observe that some members of the same family show signs of arsenic poisoning while others do not and, therefore, many be inclined to attribute this to the will of God or superstition. Some even believe a poisoned well is a sign that a snake has been struck during the digging of the tubewells (Paul & De, 2000; Bhuiyan & Uddin 2001). Arsenic-related ailments and preventive measures Arsenic is a known carcinogen. A person with excessive arsenic in his/her body is said to be suffering from arsenicosis. Chronic arsenic poisoning results from long-term exposure to this heavy metal. Early symptoms include skin pigmentation, gangrene, and keratosis which generally develop over an incubation period of 5–10 years after initial exposure. Incubation differs from person to person depending on the amount of arsenic intake, nutritional status, and immunity of the individual. After 10–20 years of prolonged exposure to arsenic, persons often develop skin, lung, bladder, liver, and/or kidney cancer (Rahman, 1999). There are four recognized stages of chronic arsenic poisoning, and the first two stages occur before the condition becomes irreversible. In the first or pre-clinical stage, patients show no symptoms but arsenic can be detected in urine or body tissue samples. In the clinical stage, effects of arsenic poisoning are visible on the skin.
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In the third stage, manifestations become more pronounced and the internal organs are affected. By the final stage, as mentioned, affected persons usually develop skin, lung, or bladder cancer. It is imperative for people to recognize the initial symptoms so as to begin treatment early. For this reason, there is an immediate need to understand not only the extent of arsenic knowledge among rural residents of Bangladesh, but also to raise awareness of the symptoms of arsenic exposure among people in both affected and unaffected areas. Because chronic arsenic poisoning has no immediate cure, prevention is the best response. Preventive measures depend largely on the consumption of arsenic free-water and early diagnosis of arsenic contamination. Provision of safe water can be accomplished by the extraction of arsenic-free water from deeper aquifers through the installation of deep tubewells (DTWs). Another approach is the removal of arsenic from contaminated water by using filters. Several filter methods are currently available in Bangladesh (Ahmed, 2000; Akmam & Higano, 2002). Since surface and rainwater are generally free of arsenic contamination, water from these sources can be used for drinking, but surface water must be purified either by boiling or by using chemicals before consumption. Boiling water for purification however, requires an amount of fuel that few villagers can afford (Paul & De, 2000).
Research Methods Questionnaire surveys administered among 356 residents of four rural areas in Bangladesh provided the primary source of data for this study. Pertinent information was also collected from secondary sources such as government offices, NGOs involved in arsenic mitigation programs, and other agencies providing financial and technical support in dealing with the arsenic contamination problem in Bangladesh. Study area and subject selection As mentioned, the areas studied were selected from moderate and low arsenic risk zones. Narayanganj and Comilla districts were chosen from the former zone, while Rangpur and Tangail districts were selected from the latter zone. Since the level of arsenic contamination varies greatly within a district, one thana from each of the four selected districts was chosen. In order to select thanas, all the thanas of the selected districts were arranged alphabetically and one thana from each district was selected using the table of random digits referenced in L’esperance (1971). The selected thanas were: Muradnagar (Comilla), Araihazar (Narayanganj), Pirganj (Rangpur), and Ghatail (Tangail) (Fig. 2). For
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Fig. 2. Study area.
logistical reason, five contiguous villages from each selected thana were then chosen as study sites. Villages were selected in such a way that they represent the arsenic level of their respective districts and thanas. Almost all families in the selected villages use tubewell water for drinking and cooking; all families have access to HPTWs. According to data provided by the Muradnagar and Arihazar DPHE offices, nearly 90% of all tested HPTWs in these two thanas are contaminated with arsenic above the WHO guideline value of 10 ppb. Like other parts of the country, most HTPWs in these two thanas are privately owned. Water from almost all public and nearly 50% of all private HTPWs in these two thanas was tested at the time of this survey.
In both thanas, more than 1500 people were suffering from arsenic-related ailments. Only tubewells owned by the government were tested for arsenic contamination in the Pirganj and Ghatail thanas and water from all HPTWs in these two thanas appears to be safe. The target population of this study was individual households within selected villages. Prior to the selection of the respondents, a complete list of all households in the selected villages was obtained from the local government office. A quick field survey was conducted to verify the list. The list contained few errors and these errors were corrected before drawing samples based on the list. Using the same random sampling procedure outlined above, an appropriate number of respondents
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was then selected from each villages. The number of household selected from each villages was proportional to their size. From each selected household, one individual was interviewed. In more than 50% of cases, this person was also the head of the family. Since women are more vulnerable to arsenic poisoning than men, in 20 instances a deliberate attempt was made to interview female respondents from the selected households. Physicians suggest that dietary intake is the most vital factor in determining who will be afflicted with arsenic poisoning. It has been found that selenium (found in fruits, eggs, and milk) is able to diminish the effects of arsenic (Paul & De, 2000). Unfortunately poorer families are unable to purchase these products. Since women in Bangladesh bear the burden of poverty, there is a gender divide in arsenic poisoning. A total of 356 respondents, 177 from medium arsenicrisk zones and 179 from low risk zones, were interviewed. Women accounted for almost 31% of the all respondents. A structured questionnaire was used to collect information from the respondents. The questionnaire included two broad sections: a section to characterize respondent knowledge of the arsenic contamination problem; and a socio-demographic section that included questions on age, gender, education, occupation, income, and landholding size of the respondent and/or respondent family. This questionnaire was pre-tested through a pilot study and the actual survey was conducted during July–August 2002. The questionnaire was administered by the author aided by three Bangladeshi field investigators. All of them were graduate students in geography at the University of Dhaka, Bangladesh and they have previously worked with the author on his past research projects. Although this veteran field survey team was quite familiar with the field work, they were uniformly trained for this project to assure consistency and quality in survey delivery. A face-to-face interview was conducted among the selected respondents and it took slightly over half an hour to complete each interview. More than half of the all female respondents were interviewed by the lone female field investigator. Because of religious reasons, they were not willing to answer questions asked by the male field investigators. Arsenic knowledge score To ensure the objectivity of the knowledge assessment, a composite score for each respondent was calculated based on answers to 10 questions regarding the source, symptoms, and diseases caused by arsenic poisoning, as well as preventive measures available and solutions to the arsenic problem. As shown in Table 1, these 10 questions are grouped into six sections with the number of questions per section ranging from one to
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three. In preparing this table, the existing literature on arsenic poisoning and a WHO model survey instrument (used to collect information reflecting knowledge, attitudes, behaviors, and practices concerning HIV/ AIDS in developing countries) were consulted (see Schopper et al., 1993; Al-Owaish, Moussa, Anwar, AlShoumer, & Sharma, 1999).5 In order to determine points for expected answers, two focus group meetings were organized in Comilla and Tangail. Each group composed of 10 persons and the participants included village leaders, local government and NGO officials, and villagers. Based on the suggestions of the participants four points were assigned for each answer rated correct and a zero for an answer rated incorrect; correct answers are listed in Table 1. Provision for partial credit was made for questions 2, 7, and 8 due to their nature. Specifically, in the context of question number 2, four points were assigned for answers indicating the respondent first heard of the arsenic contamination problem four or more years ago and zero points assigned for respondents who became aware of the problem less than one year ago. One, two, and three points were assigned for respondents who first heard of the problem one, two, and three years ago, respectively. In reference to question number 7, most (informed) sources claim an incubation period of 5–10 years for development of visible symptoms of arsenicosis. However, several sources (e.g., Khatun, 2000) mention a shorter time period (2–4 years) for the appearance of arsenic symptoms. Four points are awarded for this question to respondents who specified an incubation period of 5 years or more on question 7 and two points are assigned for respondents who specified an incubation period of 2–4 years. Similarly, two points are assigned for question 8 if respondents reported that arsenic-related cancer develops after 5–9 years of exposure, while four points are assigned for those who specified a time-frame greater than 9 years. If a respondent answered all 10 questions correctly, he/she could score a maximum of 40 points and a score of zero would be obtained if all questions were answered incorrectly. For both an incorrect answer or a ‘‘don’t know’’ response, zero points were assigned. A respondent score of 40 indicates he/she has thorough knowledge regarding the referenced aspects of arsenic poisoning; the opposite is true for a respondent who received a score of zero. Instead of simply asking whether a respondent had heard of the arsenic contamination problem, these 10 relevant questions were used because a single question is unlikely to 5 There are some similarities between arsenic poisoning and HIV/AIDS. In both, symptoms do not appear for several years. In addition, victims of both suffer from a host of opportunistic diseases and frequently experience social discrimination.
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Table 1 Questions, accurate/expected answers, and assigned points regarding comprehensive arsenic knowledge of the respondents Assigned points
A. Respondent Knowledge about Arsenic Poisoning 1. Have you heard about arsenic contamination problem? 2. If yes, how long ago did you first heard about it?
Yes One year or more
Yes=4; No=0 o1 year=0 1 year=1 2 years=2 3 years=3 >3 years=4
B. Respondents Knowledge about the Cause/Source of Arsenic Poisoning 3. What is the source of arsenic poisoning?
Drinking of arsenic contaminated tubewell water
4
Darkening of skin on palms, dark spots on the body, and keratosis
I correct answer=2 pts.
C. Respondents Knowledge about Symptoms of Arsenic Poisoning 4. What are the early symptoms of arsenic poisoning (list at least two)? What are the more visible symptoms of arsenic
5.
2 correct answer=4 pts. Darkening of skin on palms, dark spots on the body, and keratosis, and cardiovascular and respiratory disorder
poisoning (list at least two)? D. Respondents Knowledge about Arsenic-Related Diseases 6. What are the diseases caused because of arsenic poisoning (list at least two)? 7. How long does it take to develop visible symptoms? 8. How long does it take to develop cancer?
’’
Keratosis, ganggrenous ulcer, skin, lung, and bladder cancer
’’
2–10 years
2–4 yrs.=2 >4 yrs.=4 5–9 yrs.=2 >9 yrs.=4
5–20 years
E. Respondents Knowledge about Preventive Measures 9. How can arsenic be removed from the water (list at least one)?
Filter, tablets, and arsenic treatment plant
4
F. Respondents Knowledge about Solution to the Arsenic Problem 10. What is the solution to the arsenic problem (list at least one)?
Consumption of water from non-contaminated sourcesa
4
a
Includes deep tubewell, surface water, rainwater, and filter water.
pts. pts. pts. pts.
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Question
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prove reliable in capturing true respondent dispositions regarding arsenic knowledge (Dekker & Mootz, 1992). Correlate selection Based on existing literature, eight variables were selected to examine their influence on arsenic awareness among survey respondents (e.g., Al-Owaish et al., 1999; Khatun, 2000; Paul & De, 2000). These selected variables were: landholding size, occupation, annual income, level of education, marital status, age, gender, and place of residence (arsenic risk region). The first four variables represent socio-economic characteristics of the respondents. Two of these four variables (landholding size and annual income) characterize household condition, while the remaining two (occupation and level of education) characterize the respondents themselves as do the three demographic variables: marital status, age, and gender. Available literature suggests that the younger and more educated exhibit a higher level of arsenic awareness than older and/or less educated people (see Al-Owaish et al., 1999). A similar interpretation may also be applicable to other socio-economic variables considered in this study. For example, it was expected that women would have less knowledge regarding arsenic poisoning than men because women in Bangladesh are generally less educated. Moreover, Bangladeshi women are typically confined to their home compound and have less access to information sources relative to that of men. Further, it was expected that respondents living in a medium arsenic risk zone should be more knowledgeable of arsenic contamination than respondents living in a low arsenic risk zone. Data analysis Both bivariate and multivariate approaches were used to analyze the survey data. Pearson chi-square testing was used to determine the significance of association between two categorical variables. The two sample difference of mean test (Z-test), Pearson correlation analysis, and F -test were employed to assess the significance of the selected dependent and independent variables. The F -test was used when the independent variable was categorical in nature and the Z-test and correlation analysis were performed when the independent variable was continuous. Multiple linear regression analysis was employed to relate overall arsenic knowledge scores to multiple determinants, adjusting for confounding. One regression model was empirically tested. The dependent variable used was the knowledge score and the independent variables were arsenic risk
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region, landholding size, occupation, annual income, level of education, marital status, gender, and age. One independent variable (marital status) was found insignificantly associated with the dependent variable in bivariate analysis. This variable was excluded form the multivariate regression model. Respondent profile Table 2 shows that nearly 26% of all respondents in the study area were landless. Although this proportion is generally consistent with the national average, the percentage of households with a small landholding was lower than the national figure. This suggests that the sample included relatively more affluent respondents. However, chi-square testing indicates the percentage of respondents in different landholding classes considered in this study does not differ significantly between the medium and low arsenic risk regions (Table 2). Table 2 shows respondent occupation categorized in six groups: farmers, service holders, businessmen, housewives, students and others. The last group includes respondents of different occupations such as laborers (both agricultural and non-agricultural) as well as unemployed and retired people. Only 14% of the respondents engaged in farming, a much lower percentage than for the country as a whole. This is because respondents grouped under the housewife and student occupation categories originate from farming households. Unlike the landownership pattern, the two study sites do significantly differ with respect to occupational categories. More respondents of the medium arsenic risk region were engaged in service and business categories than respondents in the low risk region. This finding was expected however, because the literacy rate is higher in the former region relative to the latter (see Table 2). All respondents were asked to report their annual income. About 19% of the respondents earned less than Tk. 36,000 (US $620)/year, while 12% earned more than Tk. 72,000 (US $1,241) (Table 2). The two risk regions differ significantly with respect to income reported by the respondents. Average annual income was higher in the medium arsenic risk region (Tk. 56,768 or US $980) compared to the low risk region (Tk. 46,642 or US $805). Again, this finding is consistent with the occupational characteristics of the two study sites. A similar situation is also observed for respondent level of education. Table 2 shows that the largest proportion of respondents (nearly 46.63%) belonged to the 30-45 years age group. Further, as many as 69% respondents were male and 82% were married at the time of field survey. Calculated chi-square values suggest that the two study sites do not differ significantly with respect to age, gender, and marital status (Table 2).
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Table 2 Selected characteristics of the respondents Characteristic
Landholding size Landless Small Medium Large w2 ¼ 2:680 (d.f.=3; p ¼ 0:444) Occupation Farming Service Business Housewife Student Others
Medium risk region ðn ¼ 177Þ No. (%) 44 27 59 47
(24.86) (15.25) (33.33) (26.55)
Low risk region ðn ¼ 179Þ No. (%) 48 20 53 58
(26.82) (11.17) (29.61) (32.40)
Total ðN ¼ 356Þ No. (%) 92 47 112 105
(25.84) (13.20) (31.46) (29.49)
12 (6.78) 55 (31.07) 53 (29.94) 29 (16.38) 18 (10.17) 10 (5.65)
38 (21.23) 26 (14.53) 36 (20.11) 41 (22.90) 21 (11.73) 17 (9.50)
50 (14.05) 81 (22.75) 89 (25.00) 70 (19.66) 39 (10.96) 27 (7.58)
25 (14.12) 126 (71.19) 26 (14.69)
42 (23.46) 120 (67.04) 17 (9.50)
67 (18.82) 246 (69.10) 43 (12.08)
w2 ¼ 31:242 (d.f.=5; p ¼ o0:0001) Annual income (in Taka) o36,000 36,000–72,000 >72,000 w2 ¼ 6:333 (d.f.=2; p ¼ 0:042) Level of education (years in schools) 0 1–5 6–10 >10
34 (19.21) 17 (9.61) 35 (19.77) 91 (51.41)
49 24 56 50
(27.37) (13.41) (31.29) (27.93)
83 41 91 141
(23.31) (11.52) (25.56) (39.61)
56 (31.64) 84 (47.46) 35 (19.77) 2 (1.13)
51 (28.49) 82 (45.81) 41 (22.91) 5 (2.79)
107 (30.06) 166 (46.63) 76 (21.35) 7 (1.96)
147 (83.05) 30 (16.95)
143 (79.89) 36 (20.11)
290 (81.46) 66 (18.54)
123 (69.49) 54 (30.51)
123 (68.72) 56 (31.28)
246 (69.10) 110 (30.90)
w2 ¼ 20:664 (d.f.=3; p ¼ 0:0001) Age (in years) o30 30–45 46–64 >64 w2 ¼ 1:222 (d.f.=2; p ¼ 0:543) Marital status Married Others w2 ¼ 0:589 (d.f.=1; p ¼ 0:443) Gender Male Female w2 ¼ 0:025 (d.f.=1; p ¼ 0:874)
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Results Respondent Arsenic knowledge The face-to-face questionnaire survey executed in this study permits an exploration of respondent knowledge regarding different manifestations of arsenic poisoning. Survey data reveal that of the 356 respondents, 35 (9.83%) had never heard of the groundwater arsenic contamination problem. All of these respondents were living in the low arsenic risk region. While all respondents in the medium arsenic risk region (Comilla and Narayanganj) had knowledge of the problem, nearly 20% of the respondents in the low risk region (Tangail and Rangpur) were unaware of it. This difference in arsenic-related knowledge between respondents of the two regions was not unexpected. Although no systematic attempt was made to identify the sources of knowledge, conversations with the respondents and community leaders suggest that most respondents learned of the arsenic contamination problem from radio, television, newspapers, and NGO workers. A number of respondents in the medium arsenic risk region mentioned that the seminar organized by NGOs in their village was the primary source of knowledge. Additionally, nearly 54% of all respondents who had knowledge about elevated arsenic levels acquired that knowledge less than one year ago. As expected, more respondents from the low arsenic risk region had heard about the arsenic problem only recently compared to respondents from the medium arsenic risk region. Survey data also indicate that 92% of all respondents in the medium risk region and 76% from the low risk region knew that the manifestation of arsenic-related symptoms in the villages studied was due to arsenic contaminated tubewell water that people had been using for decades. Interestingly, although a considerable number of respondents were unaware of the cause of the contamination, they did not postulate traditional causes, such as the existence of a poisonous snake at the bottom of contaminated tubewells, a curse and/or the intervention of a deity. Contrary to claims reported in earlier studies (e.g., Shafie, 2000), no respondent in the current study mentioned a geo-political rationale, such as India poisoning the ground water of Bangladesh, for the arsenic contamination in the study area. Several respondents indicated that variation in underground soil was responsible for arsenic poisoning in rural Bangladesh. Some of them identified this altered soil as the outcome of excessive withdrawal of underground water for irrigation purposes. Other respondents mentioned internal body resistance as a major factor regulating the appearance of symptoms of arsenicosis arguing that while many people drink water from the same tubewell, only a few show signs of arsenic
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poisoning. This finding is consistent with earlier findings reported by Shafie (2000). Nearly 50% of the respondents in both study sites who were aware of the arsenic contamination were not entirely familiar with the signs, symptoms, and diseases caused by the ingestion of arsenic contaminated water. Many of these respondents were aware of the initial signs and symptoms of arsenic poisoning, however, knowledge about diseases associated with advanced stages of arsenic poisoning was limited and incomplete. Additionally, nearly two-thirds of all respondents were not able to correctly specify the incubation period for visible symptoms associated with the consumption of arsenic through contaminated drinking water. A similar percentage of respondents were unaware of the various arsenic mitigation techniques available and potential solutions to the arsenic problem. Previous studies (e.g., Bhuiyan & Uddin, 2001; Paul & De, 2000) report that villagers in Bangladesh often confuse arsenic-related skin manifestations with leprosy, causing affected persons to be avoided socially. Those afflicted are frequently refused water from neighboring tubewells and/or are discouraged from appearing in public. This field survey revealed no such misconception and/or discrimination against victims of arsenocosis in the study area. Importantly, conversations with respondents suggest that some victims hesitate to acknowledge their disease. Table 3 presents respondent average knowledge scores by arsenic risk region. This table shows that the average composite knowledge score for the study area is only 19.39 out of a maximum score of 40.0. As previously mentioned, nearly 10% of all respondents had no knowledge about arsenic contamination and all of these respondents were living in low arsenic risk region. In contrast, only five respondents had complete knowledge regarding the arsenic problem as demonstrated by correctly answering all 10 questions included in the questionnaire. These well-informed respondents were all living in the medium arsenic risk region. Low overall awareness regarding arsenic poisoning in the study area suggests that the existing awareness campaign is Table 3 Respondents arsenic knowledge by arsenic risk regions Knowledge Component a
Arsenic poisoning (8) Sources of arsenic poisoning (4) Symptoms of arsenic poisoning (8) Arsenic-related diseases (12) Preventive measures (4) Solution to arsenic poisoning (4) Overall (40) a
Risk region Medium Low
Total
5.33 3.66 5.74 5.09 2.85 3.28 26.04
4.63 3.35 3.86 2.90 1.98 2.61 19.39
3.94 3.04 2.00 0.73 1.12 1.95 12.81
Figures within parentheses indicate total possible scores.
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Table 4 Results of bivariate analysis Name of Variable Categorical variable Occupation Farming, housewife, and others Service, business, and students Marital Status Married Others Gender Male Female Non-categorical variable Landholding size Income Level of education Age
Test results (including p-value)
Name of test
Z-test
8.69 (o0.0001)
Z-test
1.36 (0.174)
Z-test
3.71 (0.002)
Correlation Correlation Correlation Correlation
inadequate in informing all potential victims of the harmful effects of arsenic and possible remedial methods. Intensification and/or modification of the campaign is necessary to increase the likelihood of saving lives. Information contained in Table 3 may be useful for intensifying the arsenic education campaign in the study area and throughout Bangladesh. Based on average composite knowledge scores, it appears that respondents were least aware of arsenic-related diseases. The average score in this survey component is only 2.90 out of a maximum score of 12 (Table 3). In contrast, study respondents were most aware of the causes of arsenic poisoning. The average score in this knowledge component is 3.35 out of a maximum score of 4 (Table 3). Table 4 further illustrates that respondents of the low arsenic risk region had less awareness of arsenic contamination compared to respondents in the medium risk zone. This finding is reflected in three ways. First, composite arsenic knowledge scores in the low risk region range from 0 to 32 and in the medium risk region from 6 to 40. Second, all six knowledge component scores are higher in the medium arsenic risk region than the low risk region (Table 3). Additionally, the medium risk region has much higher average composite score (26.04) than the low risk region (12.81). These scores suggest that the two risk regions differ significantly with respect to respondent arsenic awareness and statistical test (z-test) supports this. Correlates of arsenic awareness A two-stage analysis is used in this study. The crude effect of exposure variables on arsenic knowledge is examined first in a bivariate manner and the net effect of these variables is then estimated using multivariate
Coefficient Coefficient Coefficient Coefficient
ðrÞ ðrÞ ðrÞ ðrÞ
0.801 0.470 0.558 0.170
(o0.0001) (o0.0001) (o0.0001) (0.001)
regression analysis. Table 4 presents results of the bivariate analysis. For categorical variables (gender, marital status, and occupation), a two sample difference of mean test (z-test) was performed to examine their crude effect on composite arsenic knowledge scores. Arsenic risk region is also considered, but this variable is not included in Table 4 because the effect of the variable on arsenic knowledge has been discussed earlier (see Table 3). In addition to the four categorical variables, four noncategorical variables (income, age, landholding size, and level of education) were also considered in both the bivariate and multi-variate analyses. Pearson product moment correlation coefficient analyses were performed to examine any effect of these non-categorical variables on respondent arsenic knowledge. Although initially six respondent occupation categories were considered, after further analyses, these categories were aggregated into two. ANOVA analysis suggests that composite scores statistically differ by occupation categories (F ¼ 20:19; po0:0001). However, application of the Scheffe’s Test indicates that the scores for occupation group one (farming), four (house wife), and six (laborers and others) do not differ statistically.6 These three categories are aggregated into one occupation group and the remaining categories are aggregated into another group. The survey data shows that farmers, home-makers, and laborers possessed considerably less arsenic knowledge compared to respondents attending schools and colleges as well as employed in the service and business 6
Scheffe’s Test is used as a post hoc test of multiple comparisons in the context of the ANOVA analysis (see Sirkin, 1999).
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categories at the time of field survey. The average composite knowledge score for the former occupational group was 13.69 and 22.67 for the student group. This difference in knowledge score between these two occupational groups is statistically significant (z-value=8.69; p ¼ o0:001). As expected, males had higher scores compared with females and married respondents had lower knowledge scores than unmarried respondents. While the difference in arsenic knowledge is statistically significant in the case of gender, it is not for marital status (Table 4). Annual reported household income, landholding size, and level of education of the respondents are directly associated with arsenic knowledge scores as shown in Table 4. In contrast, an inverse relationship is observed in the case of age, implying arsenic awareness is greater among younger respondents. The direction of relationship between composite arsenic knowledge scores, and income, landholding size, level of education, and age corresponds to expectations. Calculated r-values are statistically significant, indicating that these variables are important correlates of respondent arsenic awareness. Bivariate analysis demonstrated the relative importance of key individual variables as determinants of arsenic awareness among respondents in the study area. The extent to which these variables are significant predictors of such knowledge was assessed through the use of a multivariate regression model. This model was screened using a stepwise procedure and results of the regression analysis are presented in Table 5. The selected model is highly significant (F ¼ 118:50; p ¼ o0:0001), suggesting arsenic risk region, level of education, gender, age of the respondent, and income of the respondent households are essential to explain differences in arsenic knowledge in the study area. Table 5 further shows that the coefficients of all variables included in the model have the predicted signs, and four of the five coefficients are statistically significant at the 0.001 level. The selected regression model explained 63% of the total variance in the arsenic awareness of respondents in the study area. Among all the variables included in the Table 5 Results of multiple regression analysis Step
Variable entered
1 Arsenic risk region 2 Level of education 3 Annual income 4 Gender 5 Age F -Value 118.50 ðp ¼ o0:0001Þ Significant at the 0.001 level.
R2 -value
Cumulative R2 -value
0.410 0.198 0.010 0.008 0.003
— 0.608 0.618 0.626 0.629
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model, arsenic risk region appeared as the most influential predictor of arsenic knowledge as tested by the survey instrument. This variable has the largest coefficient value (11.206), it entered first in the model, and it alone explained 41% of the total variation in the selected model. The second most influential predictor of arsenic awareness is the level of education of the respondent, which explained 20% of the total variation in respondent arsenic knowledge scores. The remaining three predictors (annual household income, age and gender of the respondents) together explained only 2% of the variation in the regression model. As noted earlier, respondents in the two arsenic risk regions studied do not differ with respect to age and gender. Yet, these two variables appeared in the regression model as determinants of arsenic awareness in the study villages. The two regions significantly differed in terms of level of education and household income of the respondents. These two variables also appeared as second and third most powerful determinants of arsenic awareness in the selected regression model (Table 5). A careful examination of the data reveals that level of education differed among villages selected from the low risk region. Regression residuals show respondents in medium risk regions had low awareness and no systematic pattern was identified with the residuals. Although useful, the regression model selected in this study fails to explain some 37% of the variation in the arsenic knowledge scores among study area respondents. This might occur for two reasons. First, previous field surveys suggest that overall arsenic knowledge is greater among households where members experience arsenic-related symptoms compared to households having no such members (Nizamuddin & Chakraborty, 2001). Inclusion of this variable would probably improve the explanatory power of the selected regression model. However, only few respondents reported arsenic-patients in their households and all of them were living in the medium risk region. For this reason, this variable was not included in the regression analysis. A comparison of Figs. 1 and 2 suggest that inclusion of distance from the study villages to the nearest high risk regions would also increase the explanatory power of the regression model. Villages selected from the medium risk region are much closer to areas severely affected by arsenic contamination compared to those selected from the low risk region. As noted earlier, residents of high risk regions have a much greater awareness of the arsenic problem compared to the residents of medium and low risk regions. Because of the assumed negative relationship between distance and access to information, it appears that distance from the high risk regions have some impact on arsenic awareness in the study villages.
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Conclusion A high concentration of arsenic in groundwater has been identified as the most alarming health hazard in rural Bangladesh. This study has examined the extent of knowledge villagers possess regarding the source of arsenic contamination, its symptoms, diseases caused by arsenic, and potential solutions. It has also related survey respondent knowledge to socio-economic and other variables. These are critical issues in guiding policy for arsenic mitigation and education programs throughout Bangladesh. The findings of this empirical study clearly suggest that arsenic awareness is currently not ubiquitous in rural Bangladesh; less is known about arsenic in low-risk regions. While most respondents surveyed had some knowledge about level of the arsenic problem, there are gaps in their knowledge especially regarding diseases caused by this toxic heavy metal and mitigation measures available to prevent contamination. Increasing awareness through the dissemination of relevant information may help individuals lower their risk of developing arsenocosis and arsenic-related illnesses. Equally important, an intensification of the existing education program is essential to effectively implement remedial measures to help prevent further health consequences. In developing and delivering awareness and educational campaigns, more attention should be directed toward informing the public of the signs and symptoms of arsenic poisoning as well as the diseases caused or exacerbated by chronic arsenic exposure. This study found that survey respondents reported limited knowledge in these specific areas compared with other aspects of the arsenic contamination problem. Additionally, it has been found that awareness is related to arsenic risk region, educational level, gender, and age. Public awareness programs should expand and target low and medium arsenic risk regions, paying particular attention to villagers with little or no education, the poor, women, and people of older age groups in all areas.
Acknowledgements The data for this study was collected in Bangladesh by the author as a Senior Fellow of the American Institute of Bangladesh Studies (AIBS). He is grateful to Dr. Mizanur Rahman Shelley, Chairman of the Center for Development Research, Bangladesh (CDRB) and Overseas Director of the AIBS, Dhaka, Bangladesh for providing logistical support for this research. This study was also partially supported by a University Small Research Grant (USRG) from Kansas State University. Special thanks are also due to Mati Lal Chanda, Ruhul
Amin, and Abu Al Sayed for conducting field surveys in Bangladesh, and Andrew W. Elmore, Department of Geography, Kansas State University for creating the figures for this paper.
References Ahmed, H. S. (2000). Combating a deadly menace: Early experiences with a community-based Arsenic Mitigation Project in Bangladesh. Dhaka: BRAC. Akmam, W., & Higano, Y. (2002). Arsenic contamination in ground water in Bangladesh: Supplying safe water with special reference to three villages in Meherpur district. Journal of Bangladesh Studies, 4, 25–36. Al-Owaish, R., Moussa, M. A. A., Anwar, S., Al-Shoumer, H., & Sharma, P. (1999). Knowledge, attitudes, beliefs, and practices about HIV/AIDS in Kuwait. AIDS Education and Prevention, 11, 163–173. Bagla, P., & Kaiser, J. (1996). India’s spreading health crisis draws global arsenic experts. Science, 274, 174–175. BGS/DPHE. (1999). Groundwater studies for arsenic contamination in Bangladesh. Dhaka: DPHE. BGS/DPHE. (2001). Arsenic contamination of groundwater in Bangladesh, Vol. 1, Summary. Dhaka: DPHE. Bhuiyan, R. H., & Uddin, B. (2001). Social and psychological scenario of arsenic patients: A gender perspective. Oriental Geographer, 45, 17–28. Bridge, T. E., & Hossain, M. (1999). Arsenic disaster in Bangladesh: An urgent call to save a nation. NFB (News From Bangladesh), March 14. Caldwell, B. K., Caldwell, J. C., Mitra, S. N., & Smith, W. (2003a). Tubewells and arsenic in Bangladesh: Challenging a public health success story. International Journal of Population Geography, 9, 23–38. Caldwell, B. K., Caldwell, J. C., Mitra, S. N., & Smith, W. (2003b). Searching for an optimum solution to the Bangladesh arsenic crisis. Social Science & Medicine, 56, 2089–2096. Clarke, T. (2003). Well water could be killing 3000 Bangladeshis each year. Nature Review. July 2 (http://www.nature.com/ nsu/030623/030623-7.html). Dekker, P., & Mootz, M. (1992). AIDS as threat, AIDS as stigma: Correlates of AIDS beliefs among the Dutch General Public. Psychology and Health, 6, 347–365. Fazal, M. A., Kawachi, T., & Ichion, E. (2001a). Extent and severity of groundwater arsenic contamination in Bangladesh. Water International, 26, 370–379. Fazal, M. A., Kawachi, T., & Ichion, E. (2001b). Validity of the latest research findings on causes of groundwater arsenic contamination in Bangladesh. Water International, 26, 380–389. Harvey, Charles F., et al. (2002). Arsenic mobility and groundwater extraction in Bangladesh. Science, 298, 1602–1606. Hossain, M. A. (2002). Arsenic contamination in drinking water and environmental threats: Mitigation perspectives in Bangladesh. Regional Development Dialogue, 23, 83–105. Johnson, B. L. C. (1975). Bangladesh. New York: Barnes & Noble Books.
ARTICLE IN PRESS B.K. Paul / Social Science & Medicine 59 (2004) 1741–1755 Khan, A. A., & Alam, S. M. M. (2000). Oxidation-reduction debate on arsenic groundwater vis-a-vis options for safe water. In M. F. Ahmed (Ed.), Bangladesh Environment 2000 (pp. 210–221). Dhaka: BAPA. Khatun, K. (2000). Arsenic contamination in ground water of Bangladesh: A study of measure the knowledge and awareness of people in selected villages of Bangladesh. Social Science Review, 17, 83–98. Lepkowski, W. (1998). Arsenic crisis in Bangladesh. Chemical and Engineering News, 76, 27–29. L’esperance, W. L. (1971). Modern Statistics for Business and Economics. New York: Macmillan. Nickson, R., McArthur, J., Burgess, W., Ahmed, K. Z., Ravenscrft, P., & Rahman, R. (1998). Arsenic poisoning of Bangladesh groundwater. Nature, 395, 338. Nizamuddin, K., & Chakraborty, R. K. (2001). Arsenic pollution in Hatkopa village: A case study. In K. Nizamuddin (Ed.), Disaster In Bangladesh: Selected
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readings (pp. 95–108). Dhaka: DRTMC, University of Dhaka. Paul Bimal K., & Sujata, De. (2000). Arsenic poisoning in Bangladesh: A geographical analysis. Journal of the American Water Resources Association, 36, 799–809. Pearce, Fred, & Jeff Hecht. (2002). Flawed water tests put millions at risk. New Scientist (November 19): 1–3 (http:// www.newscientist.com/news/news). Rahman, M. (1999). Nonmaligrant health effects of arsenic exposure. Linkoping: Linkopings University. Schopper, D., et al. (1993). Sexual behavior relevant to HIV transmission in a rural African population. Social Science & Medicine, 37, 401–412. Shafie, H. A. (2000). Health seeking behavior of the arsenic contaminated people in rural Bangladesh. Social Science Review, 17, 140–147. Sirkin, R. M. (1999). Statistics for the Social Sciences. Thousand Oaks: Sage Publications.
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Arsenic contamination awareness among the rural residents in Bangladesh Bimal Kanti Paul* Department of Geography, Kansas State University, Manhattan, KS 66506, USA
Abstract Arsenic poisoning of tubewell water, which constitutes the primary source of drinking water, has become the greatest health threat to the people of rural Bangladesh. Somewhere between 35 to 57 million people in the country are now suspected of being affected by drinking water contaminated with arsenic. While the Bangladesh government, nongovernment organizations (NGOs), and bilateral and multilateral assistance agencies are involved in combating this dreadful problem, all of their efforts to date have proceeded without having grassroots information about arsenic poisoning. The objectives of this study are to investigate the level of knowledge rural residents have regarding arsenic poisoning and to identify the correlates of that knowledge. Questionnaire surveys administered among residents of four rural areas in Bangladesh provided the major data source for this study. Twenty villages were selected from moderate and low arsenic risk regions and a total of 356 respondents, 177 from medium risk regions and 179 from low risk regions, were interviewed. Analysis of the survey data reveals that arsenic awareness is currently not widespread in the study villages, particularly in the low arsenic risk region. There are also gaps in arsenic knowledge regarding the diseases caused by arsenic poisoning and mitigating measures available to prevent contamination. This study identified arsenic risk region, level of education, gender, and age as important determinants of arsenic knowledge. The findings of this study will aid in making existing health education programs more effective and in reducing the risk of developing arsenic-related illnesses. r 2004 Elsevier Ltd. All rights reserved. Keywords: Arsenic contamination; Water supply; Rural Bangladesh; Health education; Mitigation; Risk regions
Introduction Arsenic in the drinking water of Bangladesh at levels exceeding the acceptable limit set by the World Health Organization (WHO) has emerged as a serious health problem in the country (Paul & De, 2000; Hossain, 2002).1 An estimated 35 to 57 million people in this country with a population of 130 million are now believed to be affected by drinking water contaminated with arsenic (see Akmam & Higano, 2002). Hand pumped tubewells (HPTWs), drawing water from *Tel: +1-785-532-3409; fax: +1-785-532-7310. E-mail address: [email protected] (B.K. Paul). 1 WHO’s recommended safety standard for arsenic concentration is 10 parts/billion (ppb) or 0.01 mg/l, the Bangladesh drinking-water standard is 50 ppb (0.05 mg/l).
underground sources, constitutes the primary source of drinking water for more than 95% of the rural population of Bangladesh (Caldwell, Caldwell, Mitra, & Smith, 2003a).2 Best estimates indicate that the total 2
Three types of tubewells (TWs) are in use in Bangladesh to extract groundwater for drinking and irrigation purposes: hand pumped tubewells (HPTWs), shallow tubewells (STWs), and Deep tubewells (DTWs). The water from STWs and DTWs is used primarily for irrigation purposes. Arsenic contamination is primarily confined to shallow aquifers, 33–230 ft (10–70 m) below the surface. Most HPTWs and STWs operate within these depths and were installed in the 1970s and 1980s in an effort to shift the country’s drinking water supply from surface to groundwater sources. This shift was prompted because drinking untreated surface water was determined to be the principal cause of widespread waterborne diseases among the rural population of Bangladesh, particularly children.
0277-9536/$ - see front matter r 2004 Elsevier Ltd. All rights reserved. doi:10.1016/j.socscimed.2004.01.037
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number of HPTWs in operation falls somewhere between 3 and 5 million (Hossain, 2002). Many Bangladeshis are suffering from arsenic-related diseases ranging from melanosis to skin cancer and gangrene (Fazal, Kawachi, & Ichion, 2001a). A recent report maintains that arsenic-tainted tubewell water is contributing to nearly 125,000 cases of skin cancer and killing 3000 in Bangladesh each year (see Clarke, 2003). The mortality rate from arsenic poisoning is expected to rise substantially in the near future. Arsenic was first detected in tubewell water by the Department of Public Health Engineering (DPHE) of the Bangladesh government in 1993. This issue received wide-spread attention in early 1995 when arsenic contamination was shown to be present across central and southern Bangladesh (Paul & De, 2000). The old deltaic plain of southwestern Bangladesh, the north and eastern parts of the active deltaic plain of the southern coast, and the Meghna River basin have been severely impacted by arsenic. In contrast, northwestern and southeastern Bangladesh have been less affected by arsenic poisoning Most scientific attention to date has focused on identifying the sources and causes of arsenic contamination and in developing cost-effective measures to remove arsenic from groundwater. While ascertaining the source and developing methods to remove arsenic from groundwater are essential in combating the contamination, research efforts should expand beyond these activities because arsenic poisoning has no immediate cure. Prevention is the best way to combat this problem. Additionally, all efforts undertaken to mitigate arsenic contamination thus far have proceeded without assessing the grassroots knowledge residents have of the problem. What do rural residents in Bangladesh, the beneficiaries of the remedial activities, think about the arsenic contamination problem? Are they aware of the problem? How accurate is their knowledge about contamination? The objectives of this study are to investigate the extent to which rural residents in Bangladesh possess knowledge of arsenic poisoning and to determine the association between various socio-economic and demographic characteristics of these residents and level of knowledge. Results of this study should help identify specific areas and segments of society where arsenic mitigation efforts need to be intensified. Interest in this study is not only to determine whether respondents have heard about the arsenic contamination problem per se, but to ascertain whether they are knowledgeable about important aspects of arsenic poisoning including the sources and the means by which it can be prevented. Specifically, knowledge of arsenic contamination as used in this study refers to whether respondents are familiar with the source of the poisoning, its symptoms, diseases caused by the poisoning, and its prevention.
Arsenic-related knowledge is compared between respondents living in regions classified as low and medium risk for arsenic contamination. Surveys conducted in 2001 and 2002 by this author found that residents in high risk areas were aware of the source and symptoms of arsenic poisoning, as well as diseases caused by ingestion of arsenic contaminated water (see also BGS/DPHE, 2001; Akmam & Higano, 2002; Caldwell et al., 2003a).3 This earlier finding motivated the exclusion of high-risk areas from the present study. To provide necessary background information for this study, general discussion on the spatial extent, sources, and causes of arsenic contamination in Bangladesh, including arsenic-related ailments and preventive measures, is presented in the next section. Research methods employed in this study are subsequently discussed. Among other methodological issues, this section provides a detailed note on construction of arsenic knowledge score. This is followed by a section that presents the results of the empirical analysis. The final section is devoted to concluding remarks.
Arsenic contamination in Bangladesh: a background Spatial extent of contamination Since the mid-1990s many national and international organizations have been involved in identifying arsenic contaminated tubewells in Bangladesh. Because of the lack of sophisticated laboratory facilities and financial constraints, most of these organizations began analyzing tubewell water by using a simple, and inexpensive fieldkit-method. This ‘field-kit’ is an instrument designed to identify whether arsenic is present in the sample water; it cannot detect the absolute concentration of arsenic in groundwater (Fazal et al., 2001a). Importantly, laboratory validations have revealed that these field kits frequently provide inaccurate results (see Pearce & Hecht, 2002). Although several organizations have used laboratory methods to identify arsenic concentration in tubewell water, only two such studies are based on nation-wide surveys; one is by the Dhaka Community Hospital (DCH) and the School of Environmental Studies (SOES) of Jadavpur University, Calcutta, India and the other is by the British Geological Survey (BGS) and DPHE. The former study collected data during 1995– 2000, while the latter was conducted in 1998–1999 (Akmam & Higano, 2002). The survey conducted by the DCH and SOES was biased in that arsenic victims were first identified and then tubewell water used by those victims was tested for arsenic contamination. For this 3 These surveys were funded by the National Science Foundation (NSF). The report is under preparation.
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reason, this paper uses information from the BGS and DPHE survey to establish the spatial extent of arsenic contamination in Bangladesh. The BGS/DPHE survey applied a stratified random sampling throughout Bangladesh with the exception of three hilly districts (i.e., Rangamati, Khagrachhari, and Bandarban) in the southeast. A district is the second largest administrative unit in Bangladesh with an average population of slightly over two million. The three hilly districts were not included in the survey because no primary symptoms of arsenicosis contamination were found there. The BGS/DPHE survey consisted of water samples collected from 3534 tubewells located in 433 of the 496 thanas throughout Bangladesh.4 Sample density was about 8 samples per thana, representing approximately one sample per 14 square miles (37 square km) (BGS/DPHE, 2001). The BGS and DPHE survey revealed that arsenic concentrations ranged from less than 0.25 ppb to over 1600 ppb (16 mg/l); the mean concentration was about 55 ppb (0.06 mg/l) (Hossain, 2002). Fig. 1 presents average arsenic concentration by district and shows that 10 of the 61 sampled districts have an arsenic concentration below the WHO standard (10 ppb) and the arsenic level ranges between the WHO and Bangladesh standard (50 ppt) in 27 districts. The former 10 districts are least affected, while the latter 27 districts may be considered moderately affected. The remaining 20 districts have arsenic levels exceeding the Bangladesh standard and can be considered severely affected by arsenic contamination (Fig. 1). Results illustrated in Fig. 1 suggest that nearly half of Bangladesh, lying primarily south of the Ganga River, suffers more from elevated arsenic levels than the rest of the country. Unlike other parts of Bangladesh, most rivers in the western part of this region (also known as the Moribund Delta) are less active with reduced flow or dry riverbeds. This plain is higher in elevation than the surrounding countryside and thus experiences less frequent inundation. Moreover, this part receives less rainfall (about 60 in or 1500 mm) than other parts of the country. Lack of annual replenishment in the upper aquifers may be associated with increased arsenic levels in this physiographic region. Active delta regions of Bangladesh, located east of the Moribund Delta, are subject to the action of tides and tidal effects play a significant role in fluvial processes of the distributary channels up to a distance of about 100 miles (150 km) upstream from estuaries (Johnson, 1975). These active delta regions and the Meghna River basin, which experience flooding every year, receive about 80 inches (2000 mm) of rainfall annually. Because of the annual inundation, it is difficult to explain why the
4
A thana is the basic administrative unit in Bangladesh.
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groundwater in portions of these zones contains high levels of arsenic. Most districts of northwestern Bangladesh contain a portion of the Barind which is a generally undulating region consisting of soils similar to those found in the Chittagong Hill Tracts. Facing the Barind across the Jamuna flood plain is the Madhupur Tract. This tract covers a large part of Gazipur district in central Bangladesh. As shown in Fig. 1, arsenic contamination in groundwater is relatively low in this district. Both the Barind and Madhupur Tracts share similar physiographic characteristics. Spatial patterns of arsenic contamination illustrated in Fig. 1 should be viewed carefully because there is considerable short-range variation in arsenic concentration from well to well. Even in areas of generally low arsenic concentrations, there are occasionally ‘hot spots’ where a cluster of wells with unusually high concentrations of arsenic can be found. Another reason for exercising caution stems from the need for retesting tubewells that have previously been reported as being marginally safe. Additionally, arsenic concentrations are believed to change by season and from year to year and several researchers have suggested that all arsenic interventions must be guided by repeated testing of tubewell water for arsenic levels (see Caldwell, Caldwell, Mitra, & Smith, 2003b). However, such sampling would require a institutionalized testing program in the country. Sources and causes of arsenic contamination in Bangladesh The precise cause of high arsenic concentration in the groundwater of Bangladesh has not been identified. Initially, several anthropogenic sources of potential arsenic contamination were considered, such as the excessive utilization of groundwater to both irrigate land and provide safe drinking water. Some researchers linked elevated arsenic levels with indiscriminate use of sub-standard agrochemicals since the early 1970s (Paul & De, 2000). Others have claimed it is a human-induced disaster caused by the diversion of surface water from the river Ganga by India (Bridge & Hossain, 1999). Still other explanations offered include the use of arsenic compounds as preservatives in wooden electric utility poles of the Rural Electrification Board, HPTW filters coated with arsenic compounds, industrial waste disposal, and enhanced leaching beneath irrigated lands (BGS/DPHE, 1999). On going research has called into question the veracity of these explanations. Two prevailing notions, pyrite oxidation and oxyhydroxide reduction, describe the likely method of arsenic contamination in the groundwater of Bangladesh (Fazal et al., 2001a, 376; Harvey et al., 2002). According to the first, arsenic is assumed to be present in
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Fig. 1. Extent of arsenic concentration in groundwater in Bangladesh by districts. Source: BGS/DPHE (2001).
certain sulphide minerals (pyrites) that are deposited within aquifer sediments at a depth of 66–330 ft (20– 100 m) by the major rivers of Bangladesh and India. Because of intensive irrigation development in the country, the underground water table drops creating a void which is then filled by atmospheric oxygen (Lepkowski, 1998). This inflow of oxygen and light pressure from tubewell water help break down sulphide in the arsenic-laden pyrite rock into fine particles. These particles later dissolve in groundwater (Bagla & Kaiser, 1996). Seasonal fluctuation of the water table also results in the rapid and regular intake of oxygen. The pyrite
oxidation theory is also known as the ‘lowering water table hypothesis’ (Fazal, Kawachi, & Ichion, 2001b). The oxy-hydroxide reduction hypothesis posits that the source of arsenic is geological and forms in an anoxic environment, a condition expected at the depths to which the tubewells are drilled (see Nickson et al., 1998). Arsenic is assumed to be present in alluvial sediments, concentrated in sand grains as a coating of iron hydroxide. These sediments were eroded from the Himalayas and deposited in the Bengal Basin. Organic matter deposited with the sediments reduces the arsenicbearing iron hydroxide and this reduced material—when
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exposed to aquifer water—leaches arsenic into the water (Lepkowski, 1998). Reduction of iron hydroxide is enhanced in this scenario by bacterial activity (Khan & Alam, 2000). According to the oxy-hydroxide hypothesis, the origin of arsenic rich groundwater in Bangladesh is due to natural processes and has no relationship to the excessive groundwater withdrawal. Based on empirical data, the BGS/DPHE rejected the pyrite oxidation hypothesis and accepted the oxyhydroxide reduction hypothesis as the most plausible cause of arsenic contamination in the groundwater of Bangladesh. However, several experts have questioned the validity of the BGS/DPHE findings (see Fazal et al., 2001a, b). Based on an investigation of 15 drilled wells in one site in southern Bangladesh, Harvey et al. (2002) claim that irrigation pumping may affect arsenic concentration, but not by the oxidation of sulfides as has been proposed. A detailed analysis of the causes of groundwater contamination with arsenic by Fazal et al. (2001b) concluded that their own findings as well as the BGS/DPHE results are not dependable enough to offer any conclusion regarding the cause of arsenic contamination. There are, however, traditional explanations for sources and causes of arsenic contamination in Bangladesh. Many villagers in arsenic-prone areas do not suspect that anything is wrong with tubewell water because the water has no bad smell and/or taste. Moreover, they observe that some members of the same family show signs of arsenic poisoning while others do not and, therefore, many be inclined to attribute this to the will of God or superstition. Some even believe a poisoned well is a sign that a snake has been struck during the digging of the tubewells (Paul & De, 2000; Bhuiyan & Uddin 2001). Arsenic-related ailments and preventive measures Arsenic is a known carcinogen. A person with excessive arsenic in his/her body is said to be suffering from arsenicosis. Chronic arsenic poisoning results from long-term exposure to this heavy metal. Early symptoms include skin pigmentation, gangrene, and keratosis which generally develop over an incubation period of 5–10 years after initial exposure. Incubation differs from person to person depending on the amount of arsenic intake, nutritional status, and immunity of the individual. After 10–20 years of prolonged exposure to arsenic, persons often develop skin, lung, bladder, liver, and/or kidney cancer (Rahman, 1999). There are four recognized stages of chronic arsenic poisoning, and the first two stages occur before the condition becomes irreversible. In the first or pre-clinical stage, patients show no symptoms but arsenic can be detected in urine or body tissue samples. In the clinical stage, effects of arsenic poisoning are visible on the skin.
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In the third stage, manifestations become more pronounced and the internal organs are affected. By the final stage, as mentioned, affected persons usually develop skin, lung, or bladder cancer. It is imperative for people to recognize the initial symptoms so as to begin treatment early. For this reason, there is an immediate need to understand not only the extent of arsenic knowledge among rural residents of Bangladesh, but also to raise awareness of the symptoms of arsenic exposure among people in both affected and unaffected areas. Because chronic arsenic poisoning has no immediate cure, prevention is the best response. Preventive measures depend largely on the consumption of arsenic free-water and early diagnosis of arsenic contamination. Provision of safe water can be accomplished by the extraction of arsenic-free water from deeper aquifers through the installation of deep tubewells (DTWs). Another approach is the removal of arsenic from contaminated water by using filters. Several filter methods are currently available in Bangladesh (Ahmed, 2000; Akmam & Higano, 2002). Since surface and rainwater are generally free of arsenic contamination, water from these sources can be used for drinking, but surface water must be purified either by boiling or by using chemicals before consumption. Boiling water for purification however, requires an amount of fuel that few villagers can afford (Paul & De, 2000).
Research Methods Questionnaire surveys administered among 356 residents of four rural areas in Bangladesh provided the primary source of data for this study. Pertinent information was also collected from secondary sources such as government offices, NGOs involved in arsenic mitigation programs, and other agencies providing financial and technical support in dealing with the arsenic contamination problem in Bangladesh. Study area and subject selection As mentioned, the areas studied were selected from moderate and low arsenic risk zones. Narayanganj and Comilla districts were chosen from the former zone, while Rangpur and Tangail districts were selected from the latter zone. Since the level of arsenic contamination varies greatly within a district, one thana from each of the four selected districts was chosen. In order to select thanas, all the thanas of the selected districts were arranged alphabetically and one thana from each district was selected using the table of random digits referenced in L’esperance (1971). The selected thanas were: Muradnagar (Comilla), Araihazar (Narayanganj), Pirganj (Rangpur), and Ghatail (Tangail) (Fig. 2). For
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Fig. 2. Study area.
logistical reason, five contiguous villages from each selected thana were then chosen as study sites. Villages were selected in such a way that they represent the arsenic level of their respective districts and thanas. Almost all families in the selected villages use tubewell water for drinking and cooking; all families have access to HPTWs. According to data provided by the Muradnagar and Arihazar DPHE offices, nearly 90% of all tested HPTWs in these two thanas are contaminated with arsenic above the WHO guideline value of 10 ppb. Like other parts of the country, most HTPWs in these two thanas are privately owned. Water from almost all public and nearly 50% of all private HTPWs in these two thanas was tested at the time of this survey.
In both thanas, more than 1500 people were suffering from arsenic-related ailments. Only tubewells owned by the government were tested for arsenic contamination in the Pirganj and Ghatail thanas and water from all HPTWs in these two thanas appears to be safe. The target population of this study was individual households within selected villages. Prior to the selection of the respondents, a complete list of all households in the selected villages was obtained from the local government office. A quick field survey was conducted to verify the list. The list contained few errors and these errors were corrected before drawing samples based on the list. Using the same random sampling procedure outlined above, an appropriate number of respondents
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was then selected from each villages. The number of household selected from each villages was proportional to their size. From each selected household, one individual was interviewed. In more than 50% of cases, this person was also the head of the family. Since women are more vulnerable to arsenic poisoning than men, in 20 instances a deliberate attempt was made to interview female respondents from the selected households. Physicians suggest that dietary intake is the most vital factor in determining who will be afflicted with arsenic poisoning. It has been found that selenium (found in fruits, eggs, and milk) is able to diminish the effects of arsenic (Paul & De, 2000). Unfortunately poorer families are unable to purchase these products. Since women in Bangladesh bear the burden of poverty, there is a gender divide in arsenic poisoning. A total of 356 respondents, 177 from medium arsenicrisk zones and 179 from low risk zones, were interviewed. Women accounted for almost 31% of the all respondents. A structured questionnaire was used to collect information from the respondents. The questionnaire included two broad sections: a section to characterize respondent knowledge of the arsenic contamination problem; and a socio-demographic section that included questions on age, gender, education, occupation, income, and landholding size of the respondent and/or respondent family. This questionnaire was pre-tested through a pilot study and the actual survey was conducted during July–August 2002. The questionnaire was administered by the author aided by three Bangladeshi field investigators. All of them were graduate students in geography at the University of Dhaka, Bangladesh and they have previously worked with the author on his past research projects. Although this veteran field survey team was quite familiar with the field work, they were uniformly trained for this project to assure consistency and quality in survey delivery. A face-to-face interview was conducted among the selected respondents and it took slightly over half an hour to complete each interview. More than half of the all female respondents were interviewed by the lone female field investigator. Because of religious reasons, they were not willing to answer questions asked by the male field investigators. Arsenic knowledge score To ensure the objectivity of the knowledge assessment, a composite score for each respondent was calculated based on answers to 10 questions regarding the source, symptoms, and diseases caused by arsenic poisoning, as well as preventive measures available and solutions to the arsenic problem. As shown in Table 1, these 10 questions are grouped into six sections with the number of questions per section ranging from one to
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three. In preparing this table, the existing literature on arsenic poisoning and a WHO model survey instrument (used to collect information reflecting knowledge, attitudes, behaviors, and practices concerning HIV/ AIDS in developing countries) were consulted (see Schopper et al., 1993; Al-Owaish, Moussa, Anwar, AlShoumer, & Sharma, 1999).5 In order to determine points for expected answers, two focus group meetings were organized in Comilla and Tangail. Each group composed of 10 persons and the participants included village leaders, local government and NGO officials, and villagers. Based on the suggestions of the participants four points were assigned for each answer rated correct and a zero for an answer rated incorrect; correct answers are listed in Table 1. Provision for partial credit was made for questions 2, 7, and 8 due to their nature. Specifically, in the context of question number 2, four points were assigned for answers indicating the respondent first heard of the arsenic contamination problem four or more years ago and zero points assigned for respondents who became aware of the problem less than one year ago. One, two, and three points were assigned for respondents who first heard of the problem one, two, and three years ago, respectively. In reference to question number 7, most (informed) sources claim an incubation period of 5–10 years for development of visible symptoms of arsenicosis. However, several sources (e.g., Khatun, 2000) mention a shorter time period (2–4 years) for the appearance of arsenic symptoms. Four points are awarded for this question to respondents who specified an incubation period of 5 years or more on question 7 and two points are assigned for respondents who specified an incubation period of 2–4 years. Similarly, two points are assigned for question 8 if respondents reported that arsenic-related cancer develops after 5–9 years of exposure, while four points are assigned for those who specified a time-frame greater than 9 years. If a respondent answered all 10 questions correctly, he/she could score a maximum of 40 points and a score of zero would be obtained if all questions were answered incorrectly. For both an incorrect answer or a ‘‘don’t know’’ response, zero points were assigned. A respondent score of 40 indicates he/she has thorough knowledge regarding the referenced aspects of arsenic poisoning; the opposite is true for a respondent who received a score of zero. Instead of simply asking whether a respondent had heard of the arsenic contamination problem, these 10 relevant questions were used because a single question is unlikely to 5 There are some similarities between arsenic poisoning and HIV/AIDS. In both, symptoms do not appear for several years. In addition, victims of both suffer from a host of opportunistic diseases and frequently experience social discrimination.
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Table 1 Questions, accurate/expected answers, and assigned points regarding comprehensive arsenic knowledge of the respondents Assigned points
A. Respondent Knowledge about Arsenic Poisoning 1. Have you heard about arsenic contamination problem? 2. If yes, how long ago did you first heard about it?
Yes One year or more
Yes=4; No=0 o1 year=0 1 year=1 2 years=2 3 years=3 >3 years=4
B. Respondents Knowledge about the Cause/Source of Arsenic Poisoning 3. What is the source of arsenic poisoning?
Drinking of arsenic contaminated tubewell water
4
Darkening of skin on palms, dark spots on the body, and keratosis
I correct answer=2 pts.
C. Respondents Knowledge about Symptoms of Arsenic Poisoning 4. What are the early symptoms of arsenic poisoning (list at least two)? What are the more visible symptoms of arsenic
5.
2 correct answer=4 pts. Darkening of skin on palms, dark spots on the body, and keratosis, and cardiovascular and respiratory disorder
poisoning (list at least two)? D. Respondents Knowledge about Arsenic-Related Diseases 6. What are the diseases caused because of arsenic poisoning (list at least two)? 7. How long does it take to develop visible symptoms? 8. How long does it take to develop cancer?
’’
Keratosis, ganggrenous ulcer, skin, lung, and bladder cancer
’’
2–10 years
2–4 yrs.=2 >4 yrs.=4 5–9 yrs.=2 >9 yrs.=4
5–20 years
E. Respondents Knowledge about Preventive Measures 9. How can arsenic be removed from the water (list at least one)?
Filter, tablets, and arsenic treatment plant
4
F. Respondents Knowledge about Solution to the Arsenic Problem 10. What is the solution to the arsenic problem (list at least one)?
Consumption of water from non-contaminated sourcesa
4
a
Includes deep tubewell, surface water, rainwater, and filter water.
pts. pts. pts. pts.
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Question
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prove reliable in capturing true respondent dispositions regarding arsenic knowledge (Dekker & Mootz, 1992). Correlate selection Based on existing literature, eight variables were selected to examine their influence on arsenic awareness among survey respondents (e.g., Al-Owaish et al., 1999; Khatun, 2000; Paul & De, 2000). These selected variables were: landholding size, occupation, annual income, level of education, marital status, age, gender, and place of residence (arsenic risk region). The first four variables represent socio-economic characteristics of the respondents. Two of these four variables (landholding size and annual income) characterize household condition, while the remaining two (occupation and level of education) characterize the respondents themselves as do the three demographic variables: marital status, age, and gender. Available literature suggests that the younger and more educated exhibit a higher level of arsenic awareness than older and/or less educated people (see Al-Owaish et al., 1999). A similar interpretation may also be applicable to other socio-economic variables considered in this study. For example, it was expected that women would have less knowledge regarding arsenic poisoning than men because women in Bangladesh are generally less educated. Moreover, Bangladeshi women are typically confined to their home compound and have less access to information sources relative to that of men. Further, it was expected that respondents living in a medium arsenic risk zone should be more knowledgeable of arsenic contamination than respondents living in a low arsenic risk zone. Data analysis Both bivariate and multivariate approaches were used to analyze the survey data. Pearson chi-square testing was used to determine the significance of association between two categorical variables. The two sample difference of mean test (Z-test), Pearson correlation analysis, and F -test were employed to assess the significance of the selected dependent and independent variables. The F -test was used when the independent variable was categorical in nature and the Z-test and correlation analysis were performed when the independent variable was continuous. Multiple linear regression analysis was employed to relate overall arsenic knowledge scores to multiple determinants, adjusting for confounding. One regression model was empirically tested. The dependent variable used was the knowledge score and the independent variables were arsenic risk
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region, landholding size, occupation, annual income, level of education, marital status, gender, and age. One independent variable (marital status) was found insignificantly associated with the dependent variable in bivariate analysis. This variable was excluded form the multivariate regression model. Respondent profile Table 2 shows that nearly 26% of all respondents in the study area were landless. Although this proportion is generally consistent with the national average, the percentage of households with a small landholding was lower than the national figure. This suggests that the sample included relatively more affluent respondents. However, chi-square testing indicates the percentage of respondents in different landholding classes considered in this study does not differ significantly between the medium and low arsenic risk regions (Table 2). Table 2 shows respondent occupation categorized in six groups: farmers, service holders, businessmen, housewives, students and others. The last group includes respondents of different occupations such as laborers (both agricultural and non-agricultural) as well as unemployed and retired people. Only 14% of the respondents engaged in farming, a much lower percentage than for the country as a whole. This is because respondents grouped under the housewife and student occupation categories originate from farming households. Unlike the landownership pattern, the two study sites do significantly differ with respect to occupational categories. More respondents of the medium arsenic risk region were engaged in service and business categories than respondents in the low risk region. This finding was expected however, because the literacy rate is higher in the former region relative to the latter (see Table 2). All respondents were asked to report their annual income. About 19% of the respondents earned less than Tk. 36,000 (US $620)/year, while 12% earned more than Tk. 72,000 (US $1,241) (Table 2). The two risk regions differ significantly with respect to income reported by the respondents. Average annual income was higher in the medium arsenic risk region (Tk. 56,768 or US $980) compared to the low risk region (Tk. 46,642 or US $805). Again, this finding is consistent with the occupational characteristics of the two study sites. A similar situation is also observed for respondent level of education. Table 2 shows that the largest proportion of respondents (nearly 46.63%) belonged to the 30-45 years age group. Further, as many as 69% respondents were male and 82% were married at the time of field survey. Calculated chi-square values suggest that the two study sites do not differ significantly with respect to age, gender, and marital status (Table 2).
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Table 2 Selected characteristics of the respondents Characteristic
Landholding size Landless Small Medium Large w2 ¼ 2:680 (d.f.=3; p ¼ 0:444) Occupation Farming Service Business Housewife Student Others
Medium risk region ðn ¼ 177Þ No. (%) 44 27 59 47
(24.86) (15.25) (33.33) (26.55)
Low risk region ðn ¼ 179Þ No. (%) 48 20 53 58
(26.82) (11.17) (29.61) (32.40)
Total ðN ¼ 356Þ No. (%) 92 47 112 105
(25.84) (13.20) (31.46) (29.49)
12 (6.78) 55 (31.07) 53 (29.94) 29 (16.38) 18 (10.17) 10 (5.65)
38 (21.23) 26 (14.53) 36 (20.11) 41 (22.90) 21 (11.73) 17 (9.50)
50 (14.05) 81 (22.75) 89 (25.00) 70 (19.66) 39 (10.96) 27 (7.58)
25 (14.12) 126 (71.19) 26 (14.69)
42 (23.46) 120 (67.04) 17 (9.50)
67 (18.82) 246 (69.10) 43 (12.08)
w2 ¼ 31:242 (d.f.=5; p ¼ o0:0001) Annual income (in Taka) o36,000 36,000–72,000 >72,000 w2 ¼ 6:333 (d.f.=2; p ¼ 0:042) Level of education (years in schools) 0 1–5 6–10 >10
34 (19.21) 17 (9.61) 35 (19.77) 91 (51.41)
49 24 56 50
(27.37) (13.41) (31.29) (27.93)
83 41 91 141
(23.31) (11.52) (25.56) (39.61)
56 (31.64) 84 (47.46) 35 (19.77) 2 (1.13)
51 (28.49) 82 (45.81) 41 (22.91) 5 (2.79)
107 (30.06) 166 (46.63) 76 (21.35) 7 (1.96)
147 (83.05) 30 (16.95)
143 (79.89) 36 (20.11)
290 (81.46) 66 (18.54)
123 (69.49) 54 (30.51)
123 (68.72) 56 (31.28)
246 (69.10) 110 (30.90)
w2 ¼ 20:664 (d.f.=3; p ¼ 0:0001) Age (in years) o30 30–45 46–64 >64 w2 ¼ 1:222 (d.f.=2; p ¼ 0:543) Marital status Married Others w2 ¼ 0:589 (d.f.=1; p ¼ 0:443) Gender Male Female w2 ¼ 0:025 (d.f.=1; p ¼ 0:874)
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Results Respondent Arsenic knowledge The face-to-face questionnaire survey executed in this study permits an exploration of respondent knowledge regarding different manifestations of arsenic poisoning. Survey data reveal that of the 356 respondents, 35 (9.83%) had never heard of the groundwater arsenic contamination problem. All of these respondents were living in the low arsenic risk region. While all respondents in the medium arsenic risk region (Comilla and Narayanganj) had knowledge of the problem, nearly 20% of the respondents in the low risk region (Tangail and Rangpur) were unaware of it. This difference in arsenic-related knowledge between respondents of the two regions was not unexpected. Although no systematic attempt was made to identify the sources of knowledge, conversations with the respondents and community leaders suggest that most respondents learned of the arsenic contamination problem from radio, television, newspapers, and NGO workers. A number of respondents in the medium arsenic risk region mentioned that the seminar organized by NGOs in their village was the primary source of knowledge. Additionally, nearly 54% of all respondents who had knowledge about elevated arsenic levels acquired that knowledge less than one year ago. As expected, more respondents from the low arsenic risk region had heard about the arsenic problem only recently compared to respondents from the medium arsenic risk region. Survey data also indicate that 92% of all respondents in the medium risk region and 76% from the low risk region knew that the manifestation of arsenic-related symptoms in the villages studied was due to arsenic contaminated tubewell water that people had been using for decades. Interestingly, although a considerable number of respondents were unaware of the cause of the contamination, they did not postulate traditional causes, such as the existence of a poisonous snake at the bottom of contaminated tubewells, a curse and/or the intervention of a deity. Contrary to claims reported in earlier studies (e.g., Shafie, 2000), no respondent in the current study mentioned a geo-political rationale, such as India poisoning the ground water of Bangladesh, for the arsenic contamination in the study area. Several respondents indicated that variation in underground soil was responsible for arsenic poisoning in rural Bangladesh. Some of them identified this altered soil as the outcome of excessive withdrawal of underground water for irrigation purposes. Other respondents mentioned internal body resistance as a major factor regulating the appearance of symptoms of arsenicosis arguing that while many people drink water from the same tubewell, only a few show signs of arsenic
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poisoning. This finding is consistent with earlier findings reported by Shafie (2000). Nearly 50% of the respondents in both study sites who were aware of the arsenic contamination were not entirely familiar with the signs, symptoms, and diseases caused by the ingestion of arsenic contaminated water. Many of these respondents were aware of the initial signs and symptoms of arsenic poisoning, however, knowledge about diseases associated with advanced stages of arsenic poisoning was limited and incomplete. Additionally, nearly two-thirds of all respondents were not able to correctly specify the incubation period for visible symptoms associated with the consumption of arsenic through contaminated drinking water. A similar percentage of respondents were unaware of the various arsenic mitigation techniques available and potential solutions to the arsenic problem. Previous studies (e.g., Bhuiyan & Uddin, 2001; Paul & De, 2000) report that villagers in Bangladesh often confuse arsenic-related skin manifestations with leprosy, causing affected persons to be avoided socially. Those afflicted are frequently refused water from neighboring tubewells and/or are discouraged from appearing in public. This field survey revealed no such misconception and/or discrimination against victims of arsenocosis in the study area. Importantly, conversations with respondents suggest that some victims hesitate to acknowledge their disease. Table 3 presents respondent average knowledge scores by arsenic risk region. This table shows that the average composite knowledge score for the study area is only 19.39 out of a maximum score of 40.0. As previously mentioned, nearly 10% of all respondents had no knowledge about arsenic contamination and all of these respondents were living in low arsenic risk region. In contrast, only five respondents had complete knowledge regarding the arsenic problem as demonstrated by correctly answering all 10 questions included in the questionnaire. These well-informed respondents were all living in the medium arsenic risk region. Low overall awareness regarding arsenic poisoning in the study area suggests that the existing awareness campaign is Table 3 Respondents arsenic knowledge by arsenic risk regions Knowledge Component a
Arsenic poisoning (8) Sources of arsenic poisoning (4) Symptoms of arsenic poisoning (8) Arsenic-related diseases (12) Preventive measures (4) Solution to arsenic poisoning (4) Overall (40) a
Risk region Medium Low
Total
5.33 3.66 5.74 5.09 2.85 3.28 26.04
4.63 3.35 3.86 2.90 1.98 2.61 19.39
3.94 3.04 2.00 0.73 1.12 1.95 12.81
Figures within parentheses indicate total possible scores.
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Table 4 Results of bivariate analysis Name of Variable Categorical variable Occupation Farming, housewife, and others Service, business, and students Marital Status Married Others Gender Male Female Non-categorical variable Landholding size Income Level of education Age
Test results (including p-value)
Name of test
Z-test
8.69 (o0.0001)
Z-test
1.36 (0.174)
Z-test
3.71 (0.002)
Correlation Correlation Correlation Correlation
inadequate in informing all potential victims of the harmful effects of arsenic and possible remedial methods. Intensification and/or modification of the campaign is necessary to increase the likelihood of saving lives. Information contained in Table 3 may be useful for intensifying the arsenic education campaign in the study area and throughout Bangladesh. Based on average composite knowledge scores, it appears that respondents were least aware of arsenic-related diseases. The average score in this survey component is only 2.90 out of a maximum score of 12 (Table 3). In contrast, study respondents were most aware of the causes of arsenic poisoning. The average score in this knowledge component is 3.35 out of a maximum score of 4 (Table 3). Table 4 further illustrates that respondents of the low arsenic risk region had less awareness of arsenic contamination compared to respondents in the medium risk zone. This finding is reflected in three ways. First, composite arsenic knowledge scores in the low risk region range from 0 to 32 and in the medium risk region from 6 to 40. Second, all six knowledge component scores are higher in the medium arsenic risk region than the low risk region (Table 3). Additionally, the medium risk region has much higher average composite score (26.04) than the low risk region (12.81). These scores suggest that the two risk regions differ significantly with respect to respondent arsenic awareness and statistical test (z-test) supports this. Correlates of arsenic awareness A two-stage analysis is used in this study. The crude effect of exposure variables on arsenic knowledge is examined first in a bivariate manner and the net effect of these variables is then estimated using multivariate
Coefficient Coefficient Coefficient Coefficient
ðrÞ ðrÞ ðrÞ ðrÞ
0.801 0.470 0.558 0.170
(o0.0001) (o0.0001) (o0.0001) (0.001)
regression analysis. Table 4 presents results of the bivariate analysis. For categorical variables (gender, marital status, and occupation), a two sample difference of mean test (z-test) was performed to examine their crude effect on composite arsenic knowledge scores. Arsenic risk region is also considered, but this variable is not included in Table 4 because the effect of the variable on arsenic knowledge has been discussed earlier (see Table 3). In addition to the four categorical variables, four noncategorical variables (income, age, landholding size, and level of education) were also considered in both the bivariate and multi-variate analyses. Pearson product moment correlation coefficient analyses were performed to examine any effect of these non-categorical variables on respondent arsenic knowledge. Although initially six respondent occupation categories were considered, after further analyses, these categories were aggregated into two. ANOVA analysis suggests that composite scores statistically differ by occupation categories (F ¼ 20:19; po0:0001). However, application of the Scheffe’s Test indicates that the scores for occupation group one (farming), four (house wife), and six (laborers and others) do not differ statistically.6 These three categories are aggregated into one occupation group and the remaining categories are aggregated into another group. The survey data shows that farmers, home-makers, and laborers possessed considerably less arsenic knowledge compared to respondents attending schools and colleges as well as employed in the service and business 6
Scheffe’s Test is used as a post hoc test of multiple comparisons in the context of the ANOVA analysis (see Sirkin, 1999).
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categories at the time of field survey. The average composite knowledge score for the former occupational group was 13.69 and 22.67 for the student group. This difference in knowledge score between these two occupational groups is statistically significant (z-value=8.69; p ¼ o0:001). As expected, males had higher scores compared with females and married respondents had lower knowledge scores than unmarried respondents. While the difference in arsenic knowledge is statistically significant in the case of gender, it is not for marital status (Table 4). Annual reported household income, landholding size, and level of education of the respondents are directly associated with arsenic knowledge scores as shown in Table 4. In contrast, an inverse relationship is observed in the case of age, implying arsenic awareness is greater among younger respondents. The direction of relationship between composite arsenic knowledge scores, and income, landholding size, level of education, and age corresponds to expectations. Calculated r-values are statistically significant, indicating that these variables are important correlates of respondent arsenic awareness. Bivariate analysis demonstrated the relative importance of key individual variables as determinants of arsenic awareness among respondents in the study area. The extent to which these variables are significant predictors of such knowledge was assessed through the use of a multivariate regression model. This model was screened using a stepwise procedure and results of the regression analysis are presented in Table 5. The selected model is highly significant (F ¼ 118:50; p ¼ o0:0001), suggesting arsenic risk region, level of education, gender, age of the respondent, and income of the respondent households are essential to explain differences in arsenic knowledge in the study area. Table 5 further shows that the coefficients of all variables included in the model have the predicted signs, and four of the five coefficients are statistically significant at the 0.001 level. The selected regression model explained 63% of the total variance in the arsenic awareness of respondents in the study area. Among all the variables included in the Table 5 Results of multiple regression analysis Step
Variable entered
1 Arsenic risk region 2 Level of education 3 Annual income 4 Gender 5 Age F -Value 118.50 ðp ¼ o0:0001Þ Significant at the 0.001 level.
R2 -value
Cumulative R2 -value
0.410 0.198 0.010 0.008 0.003
— 0.608 0.618 0.626 0.629
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model, arsenic risk region appeared as the most influential predictor of arsenic knowledge as tested by the survey instrument. This variable has the largest coefficient value (11.206), it entered first in the model, and it alone explained 41% of the total variation in the selected model. The second most influential predictor of arsenic awareness is the level of education of the respondent, which explained 20% of the total variation in respondent arsenic knowledge scores. The remaining three predictors (annual household income, age and gender of the respondents) together explained only 2% of the variation in the regression model. As noted earlier, respondents in the two arsenic risk regions studied do not differ with respect to age and gender. Yet, these two variables appeared in the regression model as determinants of arsenic awareness in the study villages. The two regions significantly differed in terms of level of education and household income of the respondents. These two variables also appeared as second and third most powerful determinants of arsenic awareness in the selected regression model (Table 5). A careful examination of the data reveals that level of education differed among villages selected from the low risk region. Regression residuals show respondents in medium risk regions had low awareness and no systematic pattern was identified with the residuals. Although useful, the regression model selected in this study fails to explain some 37% of the variation in the arsenic knowledge scores among study area respondents. This might occur for two reasons. First, previous field surveys suggest that overall arsenic knowledge is greater among households where members experience arsenic-related symptoms compared to households having no such members (Nizamuddin & Chakraborty, 2001). Inclusion of this variable would probably improve the explanatory power of the selected regression model. However, only few respondents reported arsenic-patients in their households and all of them were living in the medium risk region. For this reason, this variable was not included in the regression analysis. A comparison of Figs. 1 and 2 suggest that inclusion of distance from the study villages to the nearest high risk regions would also increase the explanatory power of the regression model. Villages selected from the medium risk region are much closer to areas severely affected by arsenic contamination compared to those selected from the low risk region. As noted earlier, residents of high risk regions have a much greater awareness of the arsenic problem compared to the residents of medium and low risk regions. Because of the assumed negative relationship between distance and access to information, it appears that distance from the high risk regions have some impact on arsenic awareness in the study villages.
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Conclusion A high concentration of arsenic in groundwater has been identified as the most alarming health hazard in rural Bangladesh. This study has examined the extent of knowledge villagers possess regarding the source of arsenic contamination, its symptoms, diseases caused by arsenic, and potential solutions. It has also related survey respondent knowledge to socio-economic and other variables. These are critical issues in guiding policy for arsenic mitigation and education programs throughout Bangladesh. The findings of this empirical study clearly suggest that arsenic awareness is currently not ubiquitous in rural Bangladesh; less is known about arsenic in low-risk regions. While most respondents surveyed had some knowledge about level of the arsenic problem, there are gaps in their knowledge especially regarding diseases caused by this toxic heavy metal and mitigation measures available to prevent contamination. Increasing awareness through the dissemination of relevant information may help individuals lower their risk of developing arsenocosis and arsenic-related illnesses. Equally important, an intensification of the existing education program is essential to effectively implement remedial measures to help prevent further health consequences. In developing and delivering awareness and educational campaigns, more attention should be directed toward informing the public of the signs and symptoms of arsenic poisoning as well as the diseases caused or exacerbated by chronic arsenic exposure. This study found that survey respondents reported limited knowledge in these specific areas compared with other aspects of the arsenic contamination problem. Additionally, it has been found that awareness is related to arsenic risk region, educational level, gender, and age. Public awareness programs should expand and target low and medium arsenic risk regions, paying particular attention to villagers with little or no education, the poor, women, and people of older age groups in all areas.
Acknowledgements The data for this study was collected in Bangladesh by the author as a Senior Fellow of the American Institute of Bangladesh Studies (AIBS). He is grateful to Dr. Mizanur Rahman Shelley, Chairman of the Center for Development Research, Bangladesh (CDRB) and Overseas Director of the AIBS, Dhaka, Bangladesh for providing logistical support for this research. This study was also partially supported by a University Small Research Grant (USRG) from Kansas State University. Special thanks are also due to Mati Lal Chanda, Ruhul
Amin, and Abu Al Sayed for conducting field surveys in Bangladesh, and Andrew W. Elmore, Department of Geography, Kansas State University for creating the figures for this paper.
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