vulnerability of women's health to climate change

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The Journal of Geo-Environment The Journal of Geo Environment. Vol.13, PP 41–55 (Printed in August, 2016)

2016

ISSN 1682-1998

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VULNERABILITY OF WOMEN’S HEALTH TO CLIMATE CHANGE IMPACTS: A STUDY ON SUB-HILLY REGION OF BANGLADESH Jannatul Naim1, Dr. Shitangsu Kumar Paul2 Abstract: Climate change has already been predicted to have serious impacts on physical and socio-economic environment including human health which is disproportionately affecting the women. The objective of this study is to examine the climate change patterns and investigate the vulnerability of women’s health to climate change in Kamalganj Upazilla, a sub hilly region of Bangladesh. Both primary and secondary data have been used for this study. The findings of this study reveal the indirect health impacts of climate change and represent the interrelationship of climate change with physiographic diversity and socio-economic conditions. The extension of summer season, irregular rainfall and increasing of temperature and decreasing the duration of winter season are found in this study. As the temperature is increasing, rainfall becomes irregular; hence, the women’s health vulnerability to climate change impacts increases. People are becoming more vulnerable to temperature variability related diseases such as heat extortion, heat stroke, viral fever etc. followed by water borne disease due to lack of adaptation to temperature change. It also reveals that poor women groups are the most vulnerable to climate change impacts. Keywords: Women’s Health, Vulnerability, Climate Change Impacts, Bangladesh.

Introduction Global climate change has become one of the most serious environmental concerns of 21st century. Climate change poses challenges to human health through a range of direct and indirect mechanisms (Patz, Grabow, Limaye, 2014; Frumkin et al., 2008; McMichael et al., 2006; WHO, 2003). These include relatively direct effects of hazards such as heat waves, cold waves, floods and storms, drought, sea level rise, salinity intrusion and cyclone etc. (Patz, Grabow, Limaye, 2014). Climate change also indirectly effects through changes in the range of disease vectors, water-borne pathogens (Wu, et. al., 2016). Besides, demographic factors (such as age and sex), health status, culture, living condition, limited access to resources and services, and socio-political circumstances, environmental conditions, topographical settings act as compounding factors to increase the vulnerability of health due to climate change impacts (Machalaba, et.al. 2015). In the present study, vulnerability is perceived

1 2

Lecturer, Department of Geography and Environmental Studies, University of Rajshahi Professor, Department of Geography and Environmental Studies, University of Rajshahi

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as susceptibility of women to climate change impacts and their inability to cope with such adversity (Paul, 2012, 2013). The Inter-governmental Panel on Climate Change states that climate change is contributing to the global burden office diseases and premature deaths (IPCC, 2007). Thus, it becomes a global apprehension, and developing countries like Bangladesh are more vulnerable to the adverse impacts of climate change on human health (Climate Change Cell, 2009; Paul, 2014). Furthermore, women’s health is at higher risk to extreme events and to vector borne, water borne and infectious diseases than men due to climate change impacts (Agrawala et al, 2003). Women’s vulnerability to health impacts is not only determined by biology but also by the differences of their social role and responsibilities (Easterling, 2000; Wisner et al., 2004). As a result, Bangladesh is facing a tremendous challenge to human health especially to women’s health because of its geographical location, deltaic topography with 12% hill and 8% terrace region, extreme climatic variability and also gender oriented society, together with high population, and low income etc. World Health Organization estimated that the rising temperature and unequal heavy rainfall trends due to anthropogenic climate change of the past 30 years claimed over 150,000 lives annually (WHO, 2008, 2014). It is also reported that climate change causes 2.4 percentage of all cases of diarrhoea worldwide and 2 percent of all cases of malaria (WHO, 2006). Other also found that by 2080 approximately 6 billion people may be at risk of contracting dengue fever as a consequence of climate change (Hales et al. 2002). World health organization also projected for the year 2030 comparing with a future without climate change an additional 38,000 deaths annually due to heat exposure in elderly people, 48,000 due to diarrhoea, 60,000 due to malaria, and 95,000 due to childhood under nutrition (WHO, 2014). It is already identified that the severe impact will be felt in low-lying, tropical, heavily populated developing regions such as Bangladesh, particularly when coupled with sea level rise and extreme natural hazards (Machalaba, et. al. 2015). Other studies also points out that at least 3000 million people of all tropical countries are exposed to the risk of dengue, while 2400 million in tropics and subtropics are at risk of malaria (IPCC, 2001; Githeko and Woodward, 2003). In this regard, there is a growing need to explore the health vulnerability to climate change impact in micro-regional context. Moreover, there is no comprehensive study that highlighted women’s health related vulnerability to climate change impact in micro-regional context. Most of the earlier studies have dealt with the direct health impacts of climate change especially due to extreme weather events and narrowly focus on the indirect impacts of climate change to human health. Little attention has been paid to understand women’s vulnerability of health to climate change in mountainous regions of Bangladesh. Therefore, the present study intends to investigate vulnerability of women’s health to climate change in a sub-hilly regions of Bangladesh. Mainly this study focuses on the multifaceted socio-economic and topographical relationship with women’s health due to rising temperature, unequal rainfall, extending summer and short winter season in the north-eastern areas of Bangladesh.

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Study Area and Methodology The study area has been selected purposively considering physiographic condition (topographic divisions) and diversity of population group (Sub-urban, village and tribal women groups). The study is conducted in Rahimpur, Rasulpur and Magur Sarapan Punji villages of Kamalganj Upazilla, Maulvibazar district. Kamalganj Upazilla is located between 24°08´ to 24°29´ north latitudes and 91°45´ to 91°57´ east longitudes. Physiographically the Upazilla consists of three natural divisions. The hilly region is covered with forests; and the other two parts are plain and low land. The low land is also known as haor basin area. However, among three selected villages Rahimpur is a semi-urban area located in plain land; Rasulpur is located in haor basin with rural characteristics; and on the other hand, Magur Sarapan village is a hilly area with tribal population groups (Marma). To meet the needs of the present study both primary and secondary data are collected. Primary data are collected through informal interviews and household questionnaire survey in 2013. Women’s are the key respondents of household survey. Out of the 95 households in Rahimpur a sample size of 76, and out of 128 households in Rasulpur a sample size of 96 were determined using an assumed 95 % confidence level (Yamane, 1967). On the other hand, due to its small size, all 40 households in Magur Sarapan village were selected for this study. Based on field survey data, it reveals that the sex ratio of the respondents is 104.64:100 and dependency rate is 50.48. Out of the total respondents approximately 80.6% belongs to nuclear family and 19.4% belongs to extended family, and 60.2% households consist of five to eight family members. About 22.21% of the households are illiterate, 29.01% attained primary school, and 28.83% attained secondary school, 8.80% college and only 1.99% higher education. About 9.16% are under the age of going to school. Within the active population the most dominant occupation is agriculture (12.96%) and business (6.89%) and 1.99% contribute foreign remittance. The average monthly income is 11887.20 tk. The main types of house include hut (made up of bamboo-straw/mud or CI sheet) (49.3%) and semi-pacca house (27%). Analyzed data also shows that 19% household still using kaccha sanitation and 4.7% using open field for sanitation. Approximately 46% households use pond water for cooking, washing dishes, cloths and for bath. Among the surveyed villages socio-economic condition of Rasulpur is relatively very poor. This demographic and socio-economic conditions of the study area play an influencing role on health impacts due to climate change. Eight key informants’ interviews are conducted to understand the relationship between women’s health and climate change impacts in three villages. The informal interviews include doctor, local community leader, NGO worker and village member etc. To examine the climatic variability of the study area, daily maximum temperature, minimum temperature, rainfall and maximum humidity data are collected from Bangladesh meteorological department from 1950 to 2012. Health related data are collected from Kamalganj Upazilla Health Complex to examine seasonal variability of disease patterns across gender.

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Source: Authors Map1: Locational Map of the Study Area In the first section of the study, the climatic variability of the study area are examined using anomaly and trends analysis which help to link disease with climatic variability. In the next section, monthly and seasonal diseases pattern are presented by graphs to compare the disease variation between the male and female concerning different climatic conditions. People’s perception regarding vulnerability to disease has also represented in map. In the last section, informal interviews and literatures have been presented which help to develop a conceptual framework to show the relationship between climate change and women’s health. Result and Discussion Climatic Variability in the Study Area The Intergovernmental Panel on Climate Change (IPCC) reported on the Third Assessment Report that the peak intensity of rainfall might be increased by 5% to 10% and precipitation rates might be increased by 20% to 30% in Bangladesh (IPCC 2001). Ahmed and Hassan (2009) has also reported that during the period from 1961 to 1990 the annual mean temperature increased at the rate of 0.0037°C, however, during 1961 to 2000 the rate was 0.0072°C in Bangladesh. On the other hand, General Circulation Model (GCM) projected that mean temperature will increase to 1°C by 2030, 1.4°C by 2050 and 2.4°C by 2100 respectively in Bangladesh ( Rahman, 2010). Therefore, if such projection turned

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to be true, the people of Bangladesh will suffer much to a variety of vector borne and water borne diseases due to the odd climatic condition. Besides, to understand the climate changing pattern of the study area, the climatic data of Srimangal weather station have been used as it presents the similar characteristics like as the study area. In this study area dry winter season starts from December to February, pre-monsoon hot summer is from March to May, rainy season from June to September and the post-monsoon lasts from October to November (Rasid, 1991). The minimum and maximum temperature are the most important indicator to examine climate change pattern. The study represents the anomaly of minimum and maximum temperature in different seasons. Anomaly means deviation from the normal or common order or form or rule (Rahman, 2015). It has been estimated that the average minimum temperature in winter is 10.7°C, in premonsoon is 20.29°C, and in rainy season is 24.80° C and 18.93°C in postmonsoon (Figure 1). The analysed data shows that the minimum temperature in rainy season is higher than other seasons of the study area. It has been observed that the minimum temperature of winter from 1950-1981 scores under the mean minimum temperature in winter and from the years of 1981-2012 the minimum temperature of winter scores above then the average. The pattern clearly states that the minimum temperature is increasing in winter. The anomaly of minimum temperature in pre-monsoon reveals that 27 years minimum temperature is higher than the average and rest of them are low from the average. The patterns of premonsoon minimum temperature is not regular. The minimum temperature of rainy season is almost higher than the average of 1984. The patterns reveal that the minimum temperature in monsoon is gradually increasing. The minimum temperature in post-monsoon is lower than the mean minimum temperature 1953-1974. Moreover, the deviation is higher than the average. It has also been evident from the trend line that the average minimum temperature in all seasons is significantly increasing which indicates the rising temperature of the study area. Minimum Temperature in Pre-monsoon (Anomaly)

Minimum Temperature in Winter (Anomaly)

0

Source: Analysed from BMD data Fig 1: Minimum Temperature in Different Seasons

2012

2008

2004

2000

1996

1992

Year

1988

1984

1978

1974

1970

1966

1962

1958

1954

Year

y = 0.011x - 0.3455

-1 1950

1950 1953 1956 1959 1962 1965 1968 1971 1974 1977 1982 1985 1988 1991 1994 1997 2000 2003 2006 2009 2012

y = 0.0296x - 0.9192

2012

2009

2006

2003

2000

1997

1994

1991

1988

1985

1982

1977

1974

1971

1968

1965

Minimum Temperature in Rainy Season (Anomaly)

1

2 -8

1962

Year

Minimum Temperature in Post-monsoon (Anomaly )

12

1959

y = 0.0163x - 0.5063 1956

2012

2008

2004

2000

1996

1992

1984

1978

1974

1970

1966

1962

1958

1954

1950

Year

1988

y = 0.0396x - 1.2257

-5

1953

2 1 0 -1 -2

0

1950

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y = 0.0121x - 0.3768

-2

2012

2007

2002

1970

Year

1997

y = 0.0195x - 0.6074

-4

1965

1950 1955 1960 1965 1970 1975 1982 1987 1992 1997 2002 2007 2012

-4

-2

1960

-2

0

1955

0

2

Anomaly of Maximum Temperature in Post monsoon

1950

Anomaly of Maximum Temperature in Pre-monsoon 4 y = -0.0098x + 0.3072 2

Year

Temperature in 0 C

Temperature in 0 C

Year

1992

1950 1955 1960 1965 1970 1975 1982 1987 1992 1997 2002 2007 2012

-2

-1

1987

0

0

1982

y = -0.0051x + 0.155

1975

2

1

Anomaly of Maximum Temperature in Rainy Season

1950 1955 1960 1965 1970 1975 1982 1987 1992 1997 2002 2007 2012

4

Anomaly of Maximum Temperature in Winter Temperature in 0 C

Temperature in 0 C

The mean maximum temperature in winter is 26.6°C, 32.43°C in pre-monsoon, 32.08°C in rainy season and 26.62°C in post-monsoon. In the past 25 years (19502012) the maximum temperature in winter shows above the mean maximum temperature and the rest shows below the mean (Figure 2). The figure shows that after 1975 the maximum temperature in winter becomes irregular. The premonsoon maximum temperature of 28 years is higher than the average and rest of the year’s maximum temperature in pre-monsoon is lower than the average. The study also indicates that the maximum temperature in rainy season is almost irregular before 1994, the patterns of maximum temperature was almost irregular and shows increasing trends from 1994. The maximum temperature in postmonsoon is higher in 1958, 1965-1966, 1973, 1982-1983, 1985, 1989 than the mean maximum temperature and the temperature of post-monsoon is gradually increasing from 1992. The trends shows that the maximum temperature in winter and pre-monsoon are slightly decreasing and on the other hand, the maximum temperature is relatively increasing in rainy season and post-monsoon period.

Year

Source: Analysed from BMD data Fig 2: Maximum Temperature in Different Seasons The present study finds that the summer season is extending and winter is reducing significantly. It is observed that rising above 32°C lead to high turnover of vector populations resulting in weak individuals and high mortality (Craig, 2009). An estimation shows that at least 3000 million people of all tropical countries are exposed to the risk of dengue while 2400 million in tropics and subtropics are at risk of malaria (IPCC, 2001; Githeko and Woodward, 2003). It is also found that the mean rainfall in winter is 0.56 millimetres, 7.43 millimetres in pre-monsoon season, 11.4 millimetres in rainy season and 3.32

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millimetres in post-monsoon (Figure 3). The 24 years rainfall in winter seasons presents above the mean and 29 years presents under the mean. The figure clearly indicated that from 2007, the amount of rainfall is gradually decreasing from the mean. The rainfall in pre-monsoon are under the mean in the year of 1954-1962, 1968-1972, 1975-1976, and 1992-1999 and the rainfall of pre-monsoon shows quite high from the average in 1983-1991, 2000-2005 and 2008-2012. The rainfall in rainy seasons shows are above the mean in 1951-1959, 1965, 1966, 1968-1970, 1976, 1983, 1988, 1993, 1995, 1997, 2001-2002, 2004 and rest of the years are decreasing from the average. In post-monsoon the 22 years rainfall are higher than the average and 37 years have shown under the average. It reveals that the patterns of rainfall in different seasons are almost irregular. But the trends of rainfall in different seasons show that the rainfall in pre-monsoon season is increasing and rest of the season it is decreasing Therefore, it can be stated that rainfall will increase in hot summer season because of rising temperature and the amount of rainfall will be uneven. As a result, the transmission of vector borne and water borne disease will change their nature and distribution and the severity of diseases may increase in the study area.

1 0

-1

y = -0.0021x + 0.0618

2 y = 0.0359x - 1.1497

-8

1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010

-2

Anomaly of Rainfall in Pre-monsoon

1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010

2

Rainfall in mm

Rainfall in mm

Anomaly of Rainfall in Winter

Year

Year

Anomaly of Rainfall in Post-monsoon

Anomaly of Rainfall in Monsoon

Rainfall in mm

2

-3 y = -0.0103x + 0.3316

-8 1950 1954 1958 1962 1966 1970 1974 1978 1982 1986 1990 1994 1998 2002 2006 2010

y = -0.0047x + 0.1479 1950 1954 1958 1962 1966 1970 1974 1978 1982 1986 1990 1994 1998 2002 2006 2010

Rainfall in mm

12 9 6 3 0 -3 -6 -9 -12

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Year

Year

Source: Analysed from BMD data Fig 3: Rainfall in Different Seasons In this regard, the findings significantly unveils that the people of the study area are at high risk to diseases due to extension of summer season, rising temperature and uneven rainfall. Monthly and Seasonal Disease Pattern in the Study Area The analysis of data reveals that the number of viral fever patients are highest in July and moderately high in February and November (Figure 4). These months are the transitional period of converting one season to another. Change of seasons

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and extreme heat are the influencing factor for increasing the frequency of viral fever affected patients. Diarrhoea and dysentery are the most common waterborne diseases in the study area. The number diarrhoea affected people are pretty high in hot summer (April to July) and relatively low in August. The number of dysentery affected patients are quiet high in July than other months. Asthma affected patients are also noticeable in the study area where the number of asthma affected patients are high in February. The present study also finds that pollen and other aeroallergen levels are also high in extreme heat (WHO, 2003) and it helps to increase asthma in the study area. It is estimated that extreme heat can prompt asthma, which affects around 300 million people of the world (WHO, 2003). The number of high blood pressure affected patients are also high in June, pneumonia affected patients are high in May, skin disease is high in November and malaria is high in August. Figure 4 indicates that among all mentioned diseases the number of female patients’ is higher than the number of male.

0

Female

Female

Dysentery

100 80 60 40 20 0

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Diarrhea

Male

Male

Population per 10000

Asthma

Female

High Blood Pressure 10

Male

Dec

Oct

Female

Nov

Jul

Aug

Jun

Apr

May

Mar

0

Jan

Female

5

Feb

Male

Population per 10000

40 30 20 10 0

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Population per 10000

Male

Sep

70 60 50 40 30 20 10 0

0

Female

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Population per 10000

Male

20

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

100

Skin Disease

40

Population per 10000

200

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Population per 10000

Fever 300

Vulnerability of Women’s Health to Climate Change Impacts:

Male

Female

Male

Dec

Oct

Nov

Sep

Jul

Aug

Jun

Apr

May

0

Mar

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

0

1

Jan

2

2

Feb

4

Population per 10000

Population per 10000

Malaria

Pneumonia

6

9

Female

Source: Data analyzed from monthly health reports of community clinics Fig 4: Monthly Diseases Pattern of the Study Area Based on the informal key informants interviews and expert opinions the present study finds that the viral fever is tremendously increasing in the study area because of rising temperature and extension of disaster risk seasons for example during flash flooding period. The respondents have mentioned that Kamalganj Upazila was severely vulnerable to diarrhoea and dysentery during the last few years. But at present the prevalence of diarrhoea, dysentery and malaria are relatively lower than before and under control because of growing public awareness and coping strategies. Pneumonia is high in winter where the number of female patients is higher than male. Most of the womens’ of the study area have stated that they are suffering from high blood pressure, fever, skin diseases, dehydration, physical weakness, headache etc. because of the irregular climatic conditions. It has been found that most of the diseases of the study area are very high during hot rainy season because of its hot, humid and rainy climatic conditions (Figure 5). This is an important factor for mosquitos breeding and as well as other vectors. Besides, heavy rainfall causes water logging, make soil wet and muddy and germ can easily mix with various water sources. However, the overall situation can raise the intensity of waterborne, vector borne and skin diseases in the study area. On the other hand, the extended summer season is playing as a vital role to increase the intensity and frequency of viral fever, physical weakness, dehydration, heat stress, heat extortion etc.

Population per 10000

600 400 200

Male

Female

Postmonsoon

Rainy

Pre-monsoon

Winter

0

Population per 10000

Fever

800

20

High Blood Pressure

15 10 5 0

Male

Female

150

Diarrhea

Asthma 250 200 150 100 50 0

Population per 10000

Population per 10000

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100 50 0

Male

Female

Male

Pneumonia Population per 10000

Population per 10000

Dysentery 300 200

100 0

10

5 0

Male

Male

Female

Female

Source: Data analyzed from monthly health reports of community clinics Fig 5: Diseases Pattern of the Study Area in Different Seasons Spatial Pattern of Vulnerability to Diseases Geographical location acts as a prominent factor for influencing human health. Map 2(a) shows the spatial pattern of diseases of women in the study area and map 2(b) presents the respondent’s perception about vulnerability to diseases in the study area. The respondents of the surveyed area have mentioned that they are highly vulnerable to viral fever, diarrhoea, malaria, asthma, skin disease, dengue, pneumonia, Tuberculosis (TB), cholera, acidity etc. (see: box 2 & 3). Respondents also mentioned that among the diseases the vulnerability to viral fever is very high. It is also found that Rahimpur and Rasulpur villages are very vulnerable to Diarrhoea and Kamalganj is highly vulnerable to malaria. Besides, asthma, pneumonia, skin diseases are also very common irrespective of study villages (Map 2). It is also found that Rasulpur is a low lying haor basin (marshy land) and rural area that helps to increase the vulnerability of waterborne diseases such as diarrhoea, dysentery etc.; on the contrary, Kamalganj is a hilly area with the cover of forest and moist soil in rainy season that helps to increase vector borne diseases such as malaria (see: box 1). Hence, the present study unveils that there are indirect relationship between physiographic characteristics, elements of weather with the vulnerabilities to diseases of a region.

Vulnerability of Women’s Health to Climate Change Impacts:

Spatial Pattern of Disease DDDiseases

Source: Field Survey, 2014

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Vulnerability to Diseases

Source: Analysis from Monthly Health Reports

Map 2: a) Spatial Pattern of Disease, b) Vulnerability to Diseases Relationship between Climate Change and Women’s Health Study also finds that in spite of uneven and extensive rainfall and extension of risky season to diseases have been increased, however because of adopting suitable adaptation measures such as increasing public awareness, drinking safe water and hygienic sanitation are at present making people less vulnerable to vector and water borne diseases than before (Box 2). On the other hand, because of the rising temperature over the last few years and having inadequate adaptation measures (such as limited use of fan, air condition or other modern technologies) to prevent extreme heat problem people are becoming more vulnerable to viral fever, physical weakness, dehydration, heat stroke and heat extortion etc. Box-1 Dr. Md. Rofiqul Islam of Rajshahi Medical College Hospital gave a brief interview about the relation of diseases with climate change. He states, ‘climate and spatial context can act as vital factors for many diseases. The intensity of typhoid, viral fever, scabies, eczema etc. can increase during hot summer and rainy season. Asthma, pneumonia, skin diseases become high during winter season. Asthma may also increase during very hot summer because of sweating and poor adaptation. When the temperature reach minimum 42°c, the possibility of heat stroke (symptoms: increase high pressure, vomiting etc.) could arise and when the temperature reach 40°c the probability of heat extortion (lot of sweating, low pressure etc.) could arise’. Hence, these health hazards would be increased due to climate change. Md. Islam also argues, ‘Women’s in the rural areas of Bangladesh is more vulnerable to health hazards because of social negligence, pressure of huge household chores, unhygienic condition, lack of balance food, physical amenity etc. He also suggested that well education, gender equity, balance food and proper nutrition etc. can reduce the women’s vulnerability to health hazards’.

12 The Journal of Geo Environment. 2016 Box-2

Prafulla Chandra Sutradhar (Sub Assistant Community Medical Officer) of Munshi Bazar Family and Welfare Center, Maulvibazar gave a brief interview on people’s health condition of the study area. According to him ‘Malaria, diarrhoea and dysentery etc. were extremely high in Kamalganj. Diarrhoea patients were almost more than 60% and it spread as an epidemic during the summer and rainfall seasons in previous years. But at present the percentage of these water borne diseases become low because of the growing public awareness and effective NGO programmes. People are now more aware of using sanitation and water supply facilities. Moreover, they are conscious about visiting doctors for treatment and able to state their disease symptoms or other health problems. However, because of sufficient adaptation measures for reducing diarrhoea and dysentery, it is currently controllable in the study area in spite of climate change is taken place. Fever, high blood pressure, skin disease, asthma etc. are also increasing due to the extension of disease risk seasons. He also added that, ‘The women’s are affected much than men because of malnutrition, family negligence about women’s health, early marriage, maternal problems, use of unhygienic water such as washing dish and cloths in the pond, spending long time for cooking and collecting water from long distance etc.’.

Box-3 Tahmina Sultana (24) one of the respondent of Rahimpur village states, ‘Most of the women of the region have been suffering from diarrhoea, dysentery, skin disease, asthma etc. Although the frequency of diarrhoea affected patients have reduced than before. Growing public awareness, improving sanitation facilities and drinking safe water etc. are assisting to minimize the water borne diseases. But it is still higher than the other regions of Bangladesh. Because, many villagers are still drinking and using unsafe water from ponds which spread water borne and skin diseases’. She also mentioned, ‘The duration of summer is increasing and it causes viral fever, physical weakness, dehydration, headache etc. Nevertheless, patients of asthma and pneumonia are increasing in our village’. Therefore, in this circumstances she finds, ‘if the education could be ensured for all, the following incidence of diagram diseases would reduced in-spite of of climate change.’ She also The showsbe the relationship climate change with argues, ‘People should be motivated more and more about the using of safe drinking human health. water, healthy sanitations and building awareness about the climate change impacts on health of women’.

The following diagram shows the relationship of climate change with human health:

Climate Change

CLIMATIC ELEMENTS: o Heat waves o Extreme weather o Temperature o Rainfall o Humidity o Regional weather change Direct Exposer

Indirect Exposer

Factor help to increase the adverse impact on health:  Socio-economic circumstances  Environmental conditions  Topographic conditions  Demographic characteristics  Human perception  calamitous event  Hydrological situation  Culture and Custom

HEALTH EFFECTS: o Water-food borne disease: Example: -Diarrhea, Dysentery, -Cholera o Vector-borne & Rodent borne diseases: -Malaria, Dengue o Respiratory Diseases: -Pneumonia, Asthma o Skin Diseases o Increase of Temperature -Virus fever, Pou -Blood Pressure -Heart attack -Malnutrition -Dehydration etc o Mental Diseases o Infectious Diseases

Source: Authors

Women

-Children -Old people

MOST VULNERABLE:

Human Health

Why Women?  Physical Weakness  Negligence  Maternal Problems  Social Problems  Hard working  Dependency on family head

Fig 6: Relationship between Women’s Health and Climate Change

Vulnerability of Women’s Health to Climate Change Impacts: 13

14 The Journal of Geo Environment. 2016 Conclusion The present study explains the relationships between climate change and women’s health together with the spatial patterns of vulnerability to diseases in the context of changing climate. The study finds that the impacts of climate change on women’s health have multi-faceted complex linkages with various socio-economic factors and spatial differentiations. Unhygienic sanitation, using contaminated water, poor house type, traditional cooking facilities, collecting drinking water from far distance, long time working outside during hot summer, walking outside without wearing any kind of shoe during hot rainy season are primarily responsible for increasing the intensity of health hazards due to changing climate. Similarly, malnutrition and physical weakness due to the lack of proper nutritious food and healthcare are identified as the key factors of women’s vulnerability to climate change. Besides, family members and woman herself show negligence about their health. Moreover, cultural barriers of the study area are also work as a crucial factor for women’s vulnerability to the health hazards. Early marriage, high birth rate, gender discrimination, illiteracy, lack of awareness are adding additional burden of diseases to women’s health due to climate change. In the study area, the physiographic diversity is also controlling the intensity and types of diseases to health hazards. Therefore, it can be argued that in order to minimize intrinsic vulnerability of women’s health demands the key attention for healthcare measures and climate change adaptation programmes undertaken by government and non-governmental organizations are urgently needed. Improving socio-economic conditions and raising public awareness about health impact and climate change can significantly reduce the vulnerability to diseases caused by climate change impacts. Nonetheless, reducing cultural barriers, improving healthcare and educational facilities and awareness raising also deserve a careful consideration.

References Agrawala, S., Ota, T., Ahmed, A.U., Smith, J. & Aalst, M. V. (2003). Development and Climate Change in Bangladesh: Focus on Coastal Flooding and the Sunderbans. Organization for Economic Co-operation and Development (OECD), Paris. Craig, A. D. (2009). How do you feel—now? The anterior insula and human awareness. Nature reviews neuroscience, 10(1): 59-70. Cox, P. M., Betts, R. A., Bunton, C. B., Essery, R. L. H., Rowntree, P. R., & Smith, J. (1999). The impact of new land surface physics on the GCM simulation of climate and climate sensitivity. Climate Dynamics, 15(3):183-203. Climate Change Cell. (2009). Climate Change, Gender and Vulnerable Groups in Bangladesh. DoE, MoEF, CDMP, MoFDM, Dhaka.

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