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Climate change has led to significant rise of 0.8°C–0.9°C in global mean temperature over the last century increasing the frequency and intensity of heat waves. According to a study conducted by department of hy drology and meteorology, the temperature of Nepal is rising by 0.056 degree per y ear. Climate related extreme heat exposure increases the number of people at risk of heat related medical conditions such as hy perthermia, heat stroke, heat exhaustion, heat syncope, heat cramps, and heat rash.
Under a high emissions scenario, the death due to heat in elderly (65+) are projected to increase to about 53 deaths per 100,000 by 2080 compared to the estimated baseline of approximately 4 deaths per 1 ,000,000 annually between 1961 and 1990 in Nepal.
A study among farmers also showed the cardiovascular risk of high heat exposure and ultimately reduced work productivity. Heat exposed jobs may have already caused the loss of 15% to 20% of annual work hours in South East Asia and the progress in global climate change may double this scenario by 2050. However, there are number of factors that is associated with vulnerability to heat stress.
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Poor people with minimum liv ing quality in laboring occupations are more prone to the effects of heat stress. Other factors like geography, health-system preparedness, health status, age, social class and support systems and pre-existing medical conditions such as obesity, cardiovascular and neurological diseases are significantly associated with the occurrence of HRS.
Nevertheless, there is lack of coping strategies adapted to reduce the health impacts of heat stress. A study in Terai region of Nepal identifies that there is inadequacy of facilities in factories for worker to combat the hot.
Long term adaptation strategies based on evidences is crucial in Nepal to combat the health threats of increasing heat exposure.
Climate change is happening in Nepal and this is expected to increase the mean annual temperature and intensity and frequency of heat waves. This simultaneously increases the number of people at risk of heat related medical conditions resulting to both mortality and morbidity from heat stress. Despite few studies in Nepal have examined vulnerability to heat stress due to work exposure there have been lack of studies attempting to understand the factors contributing to vulnerability of communities. Thus, to facilitate the public health preparedness and gain insights on reducing the health impacts of heat stress on communities, it is necessary to know the factors affecting vulnerability to heat stress, the health impacts and existing coping strategies.
Banke district lies in province 5 of Nepal. The district is located in terai region of country. It covers an area of 2,337 km² and a population of 491,313 in 2011. It is situated in the height of 129 meters to 1290 meters from sea level. This study will be conducted in Nepalgunj Sub-Metropolitan. It is the district headquarter of Banke district and a major commercial hub of Mid-Western Development Region. It has 27 wards with area of 85.94 sq. km and total population of 7 3,779. It is located at 28°03′N 81°37′E and an elevation of 150m.
To study the factors associated with vulnerability to heat stress, health impacts of heat stress and existing coping strategies in Banke District.
Specific Objectives:
First, the heat index would be assessed using secondary analy sis of meteorological data of last 3 months (from point of data collection) from the Nepalgunj (Regional Office) Station. Second, the factors associated with vulnerability to heat stress, health impacts and coping strategies would be assessed using descriptive cross-sectional design. The study period will be six months from June to November, 2019.
5 wards of Nepalgunj Sub-Metropolitan will be selected randomly. Proportionate sampling will be done to determine the number of households required from each of 5 wards. At the starting location, households will be selected randomly, followed by systematic selection of other households.
The findings of this study are based upon the following framework from a study in India to assess the household vulnerability to heat stress(12). Here the factors associated with heat vulnerability is segmented into the heat hazard probability and factors associated with exposure, susceptibility and adaptive capacity.
For calculating heat index, Measurement of single daily value of maximum and minimum air temperature and relative humidity per day from the Nepalgunj (Reg. Office) station will be taken of the last 3 months. For assessing the factors and health impacts, survey for quantitative study will be done. A structured questionnaire will be used as a data collection tool. Individual interviews will be conducted in the month of August 2019. An adult household member will be selected as the respondent who can provide information regarding all other members of the family (in the context of exposure to heat and heat related sy mptoms).
The type of Heat Related Sy mptoms (HRS) to be considered includes: small blisters or pimples, dry mouth, fatigue, leg cramps, heavy sweating, intense thirst, rapid heartbeat, headache, leg swelling, paranoid feeling, swelling of face, fever, diarrhea, hallucinations, vomiting and fainting. Hallucinations and fainting are considered as severe HRS whereas the rest will be considered as mild HRS.
Pretesting of tools will be done in 1 0% of total sample population. After pre-testing if necessary, the structured questionnaire will be rephrased.
For quantitative survey, Data will be entered into EpiData version 3.1 with pre-set jump and skip commands and exported to SPSS for further analysis. Descriptive statistics and cross tabulations will be used to analy ze the data. Vulnerability is seen in the context of occurrence of heat related symptoms. The occurrence of at least one HRS in the indiv idual is the health outcome of interest. At least one HRS will be cross tabulated against each variable, through which odds ratios (OR) will be calculated.
For heat index calculation, Daily mean temperature ((Tmax + Tmin) /2) and relativ e humidity (average of two ties value) will be computed, and then subsequently used for calculation of the Heat Index as per the NOAA ’s National Weather Serv ice (NWS) method.
The original regression equation of Rothfusz is
HI = -42.379 + 2.04901523×T + 10.14333127×RH - .22475541×T×RH - .00683783×T×T
- .05481717×RH×RH + .00122874×T×T×RH + .00085282×T×RH×RH - .00000199×T×T×RH×RH
Where, T is mean daily temperature (°F) and RH is mean daily relative humidity (%). For few exceptions of certain threshold of temperature and relative humidity values, adjustments using Steadman’s method will be applied. Microsoft Excel will be used for heat index calculation.
Ethical approval will be obtained from Institutional Review Committee, Pokhara University. Informed consent will be obtained from participants before containing the study.
The research activities are scheduled across six months, covering proposal development, literature review, tool development, pretesting, data collection, analysis, and dissemination.
This study will provide valuable insights into the vulnerability to heat stress in Banke District, Nepal, highlighting the urgent need for evidence-based adaptation strategies to mitigate health impacts and enhance community resilience against rising temperatures.
Vulnerability to heat stress and health impacts in Banke District, Nepal. (2024, Feb 23). Retrieved from https://studymoose.com/document/vulnerability-to-heat-stress-and-health-impacts-in-banke-district-nepal
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