Abstract
Background & objectives:
Exposure to air pollution due to combustion of biomass fuels remains one of the significant risk factors for chronic respiratory diseases such as chronic bronchitis. There is a need to identify the minimum threshold level of biomass index that is significantly associated with chronic bronchitis. This study was undertaken to identify a threshold for biomass exposure index in a rural women population in Mysore district, south India.
Methods:
A cross-sectional survey was conducted in a representative population of Mysore and Nanjangud taluks. Eight villages each from Mysore and Nanjangud were randomly selected based on the list of villages from census 2001. A house-to-house survey was carried out by trained field workers using the Burden of Obstructive Diseases questionnaire, which evaluated the biomass smoke exposure and chronic bronchitis. All the women aged above 30 yr were included in the study.
Results:
A total of 2011 women from Mysore and 1942 women from Nanjangud participated in the study. All women were non-smoking and used biomass fuels as the primary fuel for cooking. A threshold of biomass fuel exposure of 60 was identified on multivariate analysis in Mysore district after adjusting for age, passive smoking and working in a occupational exposure to dust, as the minimum required for a significant association with chronic bronchitis. One in every 20 women in Mysore district exposed to biomass fuel exposure index of 110 or more developed chronic bronchitis.
Interpretation & conclusions:
The minimum threshold of biomass exposure index of 60 is necessary to have a significant risk of developing chronic bronchitis in women. The number needed to harm to develop chronic bronchitis reduces with increasing biomass exposure index and women residing in rural Nanjangud have a higher risk for developing chronic bronchitis as compared to women in Mysore.
Keywords: Biomass, biomass exposure index, biomass fuel, chronic bronchitis, number needed to harm, threshold for biomass
Exposure to air pollution due to combustion of biomass fuels remains one of the significant risk factor for chronic respiratory diseases in the developing countries1. It is estimated that an average woman in India may be subjected to 60,000 h of exposure to smoke due to combustion of biomass fuels in her life time2. Combustion of biomass fuels is the most important source of indoor air pollution in the world3. About 50 per cent of deaths from chronic obstructive pulmonary disease (COPD) in developing countries are attributed to exposure to biomass fuel smoke and 75 per cent of these deaths are in women4. Studies both in India and other countries have confirmed that exposure to biomass fuels has a significant association to chronic respiratory symptoms such as chronic cough, chronic phlegm and chronic respiratory diseases such as chronic bronchitis, asthma, cor pulmonale and respiratory failure2,5–14, a decline in objective lung function parameters has been demonstrated, though not consistently1,2,11,15,16, and a higher mortality and morbidity3,17. A recent meta-analysis has shown that biomass fuel exposure is associated with a significant risk for chronic bronchitis and COPD18 and the strength of association was similar to that of cigarette smoking19. The major components of biomass affecting respiratory health are particulate matter, polycyclic aromatic hydrocarbons and carbon monoxide3,20. Chronic bronchitis is an important phenotype of COPD and is associated with a steeper decline in FEV121 and higher mortality rates22.
It is essential to have clinically meaningful exposure thresholds established for biomass fuel exposure. Exposure includes along with the concentration of the pollutants, the time spent by the person in that environment (person-time)3. Though assessment of biomass fuel exposures are estimated by measuring indoor concentrations of various pollutants including particulate matter (SPM10 and SPM2,5), personal exposures and breath levels of different pollutants3, these are difficult to apply in everyday clinical practice. A simple, easily applicable ‘biomass exposure index’ that was calculated utilizing the average hours spent on cooking per day multiplied by the number of years of cooking was developed by Behera et al2. The objective of this study was to identify the minimum threshold level of biomass index that is significantly associated with chronic bronchitis in the general population.
Material & Methods
Study design and subjects: The study was a cross-sectional survey to estimate the prevalence of COPD in a representative population in rural Mysore district23. The present study was a sub-study of this study and included all women above the age of 30 yr. Briefly, a two stage sampling was performed, with two taluks randomly selected out of five taluks in Mysore and eight villages in each taluk were randomly selected out of a list of all the villages. The sample size was estimated utilizing the available information on the prevalence of COPD in India14,24. With a 5 per cent prevalence and a 10 per cent error on the estimate, the sample size for the study was calculated to be 8000 adults. The sampling unit of the study was “household” and all the eligible persons in the households were included in the study. Nearly 25-30 per cent of the population is above 30 yr of age25 and thus a total of 32,000 population was needed to be covered to identify 8000 eligible subjects for the study. With an average village size of 2000, 16 villages were covered. The villages (n=16) were randomly selected, eight villages in each taluk from the list of all villages according to the census 2001.
Field work and definition of outcome variables: The total duration of the study for the field work in both Mysore and Nanjangud was three years from June 2006 to May 2009. A validated ‘Burden of Obstructive Lung Disease’ questionnaire26 was utilized for the study and was administered by trained field workers after a house-to-house visit. The questionnaire included demographic variables, various respiratory symptoms and risk factors including biomass fuel exposure. The questionnaire was translated into the local language according to standard procedures for translation and back-translation and pilot tested in the population studied. The questionnaire was read out to the patient in exactly the same order as listed in the questionnaire and sufficient time was given to the patient to respond to the questions. If the patient did not understand the questions, it was repeated. If the patient still was doubtful about the answer, it was recorded as “No”. The survey was conducted both at morning and in the evening to ensure compliance. The field workers visited all the houses in the selected villages. Cases of ‘chronic bronchitis’ were identified in both the identification and validation stages on the basis of a positive response to the question ‘Do you cough for at least 3 months in a year for at least two consecutive years?’ according to the definition of the Medical Research Council, UK (MRC)27. Biomass exposure index was calculated as the average number of hours spent on cooking daily for cooking multiplied by the total number of years spent in cooking personally2. Information was collected on potential confounders relevant for chronic bronchitis such as passive smoking and working in a occupational exposure to dust. Passive smoking and working in a occupational exposure to dust were defined as present if an answer was “Yes” to the questions ‘Does anyone living in your home, smoke cigarettes or beedies regularly inside your home?’ and ‘Have you ever worked for an year or more in a occupational exposure to dust?’.
Statistical analysis: The data analysis was carried out utilizing EPIINFO 8 and SPSS Inc. SPPS13 for Windows, Chicago: SPSS Inc., 2005 to calculate the odds ratios and 95% CI (confidence interval) for different biomass index exposures varying from 20 to 110 to identify the initial threshold of biomass index exposure significantly associated with chronic bronchitis in women. Fischer's exact test was used to determine the level of significance. A linear regression line was fitted between the log odds of the disease and increasing dose of biomass exposure to assess if there was a significant linear relationship between dose of biomass exposure and the odds of having the disease. A multiple logistic regression analysis was performed to assess independent association of biomass exposure index and chronic bronchitis after adjusting for potential confounders such as age, passive smoking and working in a occupational exposure to dust in Mysore district.The number needed to harm (NNH) values were calculated for chronic bronchitis for Mysore and Nanjangud among women exposed to various thresholds of biomass fuel exposure. The online calculator from Graphpad was used (http://www.graphpad.com/quickcalcs/NNT2.cfm). A receiver operator characteristic (ROC) curve was constructed for different thresholds of biomass index and the significance of the area under the curve was analysed.
The study protocol was approved by the institutional ethics committee of the JSS Medical College, Mysore.
Results
A total of 3953 women 30 yr of age were studied from Mysore district, (2011 and 1942 women from Mysore and Nanjangud taluks, respectively).The demographic variables and the biomass fuel exposure indices for the study subjects from Mysore district and from Mysore and Nanjangud taluks are presented in Table I. The distribution of the number of cases of chronic bronchitis across various biomass exposure indices are presented in Table II. All the women were non-smokers. The prevalence of chronic bronchitis in Mysore district was 133 (3.36%), Mysore taluk, 36 (1.79%) and in Nanjangud taluk 97 (4.99%). Women in Nanjangud had a higher prevalence of chronic bronchitis along with a higher mean biomass index exposure as compared to women in Mysore. A linear regression analysis was performed and the log odds was regressed using biomass exposure index. The regression was found to be highly significant (P=0.002) for Mysore district (Fig. 1a), Mysore taluk (P=0.008) (Fig. 1b) and Nanjangud taluk (P=0.001) (Fig. 1c). The prevalence of chronic bronchitis in women with a biomass exposure index of <60 was 1.6 (95% CI 1.08-2.50), between 60-120 was 3.15 (95% CI 2.46-4.02) and >120 was 8.26 (95% CI 6.27-10.80). A significant dose-response relationship was observed with a higher risk of developing chronic bronchitis with increasing biomass exposure as compared to subjects with a biomass exposure index of >60 in women from Mysore district [biomass exposure of 60-120 (OR 1.9; 95% CI 1.14-3.19) 2 and >120 (OR 5.36; 95% CI 3.12-9.27)]. A multiple logistic regression analysis was performed for independent association of biomass exposure index in Mysore district and chronic bronchitis after adjusting for potential confounders such as age, passive smoking and working in a occupational exposure to dust, and a significant association was observed from a biomass exposure index of 60 (Table III). Age >50 yr was found to be significantly associated with chronic bronchitis and no association could be found for occupational exposure to dust and passive smoking across various biomass exposure indices (data not shown). A receiver operator characteristic (ROC) curve (Fig. 2) constructed for different thresholds of biomass index and the area under the curve (AUC) was found to be significant (0.7; P<0.000). The cut-off of biomass index with the combination of highest sensitivity and specificity was found to be 97.5.
Table I.
Table II.
Table III.
The number needed to harm for the various exposure thresholds of biomass indices in women of Mysore district, Mysore and Nanjangud taluks to cause chronic bronchitis are presented in Table IV. Of the 39 women exposed to a biomass exposure of 60 or more, one will develop chronic bronchitis, and of the 20 women exposed to a biomass exposure of 110 or more, one will develop chronic bronchitis in rural women in Mysore district. A differential risk was observed on sub-group analysis of women from Mysore and Nanjangud taluks. Of the 85 women exposed to a biomass exposure of 60 or more, one will develop chronic bronchitis and of the 47 women exposed to a biomass exposure of 110 or more, one will develop chronic bronchitis in rural women in Mysore taluk. In contrast, of the 28 women exposed to a biomass exposure of 60 or more, one will develop chronic bronchitis and of the 13 women exposed to a biomass exposure of 110 or more, one will develop chronic bronchitis in rural women in Nanjangud taluk. For the same levels of biomass index exposure there is a substantial difference in risk in genetically homogeneous population from the same district.
Table IV.
Discussion
Biomass fuel exposure has been found to be significantly associated with chronic bronchitis2. ‘Biomass exposure index’ is a simple clinically applicable tool that has the potential to be widely applicable in subjects exposed to biomass fuels, similar to pack years of smoking or smoking index that are used to assess exposure to tobacco smoking and quantify the risk of developing disease. For biomass exposure index to be clinically applicable there is a need to identify the minimum threshold of exposure beyond which there is a significant risk of developing disease. This study identified the minimum threshold of biomass exposure index that was significantly associated with the development of chronic bronchitis in the general population. In Mysore district, the minimum amount of biomass exposure required to be significantly associated with chronic bronchitis was a biomass exposure index of 60 after adjusting for potential confounders. Age and biomass exposure index were found to be independently associated with chronic bronchitis. A linear regression analysis confirmed the dose response relationship of increasing biomass exposure and chronic bronchitis in women from Mysore district. On sub-group analysis, a stronger association was observed in women in Nanjangud who also had a mean higher exposure levels to biomass fuels as compared to women in Mysore. This study also demonstrated the number needed to harm for varying levels of biomass exposure indices and found a clear association of increasing chronic bronchitis with increasing biomass exposure. Interestingly, the number needed to harm for biomass exposure in women in Nanjangud was much lower than for women in Mysore for the same degree of exposure. Further studies are required to elucidate reasons for this; whether it is related to poorer ventilation in houses in Nanjangud which leads to a higher exposure to indoor air pollutants; whether presence of heavy industries in Nanjangud is contributing to a higher outdoor air pollution; whether the biomass fuels used or cooking practices adopted in Nanjangud produces higher levels of indoor air pollutants; whether it is related to an increased susceptibility in women in Nanjangud or whether it is related to poor nutrition, prior respiratory infections, overcrowding and other poverty associated factors. A ROC curve analysis showed that the cut-off for the combination of highest sensitivity and specificity was observed at a biomass index of 97.5.
Approximately, half the world's population and around 90 per cent of rural households are exposed to biomass fuels for their daily energy needs1,3. World Health Organization attributes more than 1.6 million deaths per year and 38.5 million disability-adjusted-life years to indoor smoke from biomass fuels that predominantly affect women and children28. Indoor air pollution due to biomass fuels is ranked 10th among most preventable risk factors for global disease burden and ranked 4th when only developing countries are considered3. Biomass smoke is a complex mixture of hundreds of volatile and particulate matter including organic and inorganic compounds and most of these (>90%) are in the respirable range (<10 microns)3,20.The most important toxic constituents are solid particulate matter (PM10 and PM2.5), carbon monoxide, nitrogen and sulphur oxides, aldehydes such as formaldehyde, polycyclic aromatic hydrocarbons such as benzopyrene, volatile organic compounds and free radicals3,20. Cooking is the most common activity involving combustion of biomass fuels and in developing countries is conducted in open fireplaces which result in significant emissions and the mean 24 h PM10 values may range from 300 to 3000 μg/m3 and may reach 30,000 μg/m3 during cooking3. The mean 24 h carbon monoxide values ranged from 2-50 ppm and peak of 500 ppm during cooking3.
There is strong evidence linking inhalation of biomass fuel smoke and chronic bronchitis in women aged above 30 yr with a relative risk of 3.2 (95% CI 2.3-4.8)3. Population based studies have demonstrated a clear link between exposure to smoke from biomass fuels and COPD in India2,5, Colombia8, China13, Spain29 and Mexico11. The Colombian18 study with more than 5500 subjects showed that the exposure to biomass fuels for more than 10 years is a risk factor for COPD (OR 1.50; 95% CI 1.36-2.36).Reducing the indoor air pollution proved to be of benefit. Two studies, in Guatemala30 and Mexico31 showed that using modified cooking stoves to reduce indoor air pollution was associated with reduction of chronic respiratory symptoms over a follow up of more than a year.
In conclusion, our findings demonstrated that a minimum threshold of biomass exposure index of 60 was necessary to have a significant risk of developing chronic bronchitis. The number needed to harm to develop chronic bronchitis reduces with increasing biomass exposure index and women residing in rural Nanjangud have a higher risk for developing chronic bronchitis as compared to women in Mysore, the reasons for which need to be ascertained. Future research on the effect of use of modified cooking stoves that reduces indoor air pollution including the cost-effectiveness is required to develop preventive strategies.
References
- 1.Saha A, Rao NM, Kulkarni PK, Majumdar PK, Saiyed HN. Pulmonary function and fuel use: a population survey. Respir Res. 2005;6:127. doi: 10.1186/1465-9921-6-127. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Behera D, Jindal SK. Respiratory symptoms in Indian women using domestic cooking fuels. Chest. 1991;100:385–8. doi: 10.1378/chest.100.2.385. [DOI] [PubMed] [Google Scholar]
- 3.Torres-Duque C, Maldonado D, Perez-Padilla R, Ezzati M, Viegi G. Biomass fuels and respiratory diseases: a review of the evidence. Proc Am Thorac Soc. 2008;5:577–90. doi: 10.1513/pats.200707-100RP. [DOI] [PubMed] [Google Scholar]
- 4.Salvi SS, Barnes PJ. Chronic obstructive pulmonary disease in non-smokers. Lancet. 2009;374:733–43. doi: 10.1016/S0140-6736(09)61303-9. [DOI] [PubMed] [Google Scholar]
- 5.Behera D, Chakrabarti T, Khanduja KL. Effect of exposure to domestic cooking fuels on bronchial asthma. Indian J Chest Dis Allied Sci. 2001;43:27–31. [PubMed] [Google Scholar]
- 6.Bruce N, Perez-Padilla R, Albalak R. Indoor air pollution in developing countries: a major environmental and public health challenge. Bull World Health Organ. 2000;78:1078–92. [PMC free article] [PubMed] [Google Scholar]
- 7.Kiraz K, Kart L, Demir R, Oymak S, Gulmez I, Unalacak M, et al. Chronic pulmonary disease in rural women exposed to biomass fumes. Clin Invest Med. 2003;26:243–8. [PubMed] [Google Scholar]
- 8.Caballero A, Torres-Duque CA, Jaramillo C, Bolivar F, Sanabria F, Osorio P, et al. Prevalence of COPD in five Colombian cities situated at low, medium, and high altitude (PREPOCOL study) Chest. 2008;133:343–9. doi: 10.1378/chest.07-1361. [DOI] [PubMed] [Google Scholar]
- 9.Menezes AM, Perez-Padilla R, Jardim JR, Muino A, Lopez MV, Valdivia G, et al. Chronic obstructive pulmonary disease in five Latin American cities (the PLATINO study): a prevalence study. Lancet. 2005;366:1875–81. doi: 10.1016/S0140-6736(05)67632-5. [DOI] [PubMed] [Google Scholar]
- 10.Shrestha IL, Shrestha SL. Indoor air pollution from biomass fuels and respiratory health of the exposed population in Nepalese households. Int J Occup Environ Health. 2005;11:150–60. doi: 10.1179/oeh.2005.11.2.150. [DOI] [PubMed] [Google Scholar]
- 11.Regalado J, Perez-Padilla R, Sansores R, Ramirez Paramo JI, Brauer M, Pare P, et al. The effect of biomass burning on respiratory symptoms and lung function in rural Mexican women. Am J Respir Crit Care Med. 2006;174:901–5. doi: 10.1164/rccm.200503-479OC. [DOI] [PubMed] [Google Scholar]
- 12.Ellegard A. Cooking fuel smoke and respiratory symptoms among women in low-income areas in Maputo. Environ Health Perspect. 1996;104:980–5. doi: 10.1289/ehp.104-1469451. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Liu S, Zhou Y, Wang X, Wang D, Lu J, Zheng J, et al. Biomass fuels are the probable risk factor for chronic obstructive pulmonary disease in rural South China. Thorax. 2007;62:889–97. doi: 10.1136/thx.2006.061457. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Jindal SK. Emergence of chronic obstructive pulmonary disease as an epidemic in India. Indian J Med Res. 2006;124:619–30. [PubMed] [Google Scholar]
- 15.Ekici A, Ekici M, Kurtipek E, Akin A, Arslan M, Kara T, et al. Obstructive airway diseases in women exposed to biomass smoke. Environ Res. 2005;99:93–8. doi: 10.1016/j.envres.2005.01.004. [DOI] [PubMed] [Google Scholar]
- 16.Reddy TS, Guleria R, Sinha S, Sharma SK, Pande JN. Domestic cooking fuel and lung functions in healthy non-smoking women. Indian J Chest Dis Allied Sci. 2004;46:85–90. [PubMed] [Google Scholar]
- 17.Ramirez-Venegas A, Sansores RH, Perez-Padilla R, Regalado J, Velazquez A, Sanchez C, et al. Survival of patients with chronic obstructive pulmonary disease due to biomass smoke and tobacco. Am J Respir Crit Care Med. 2006;173:393–7. doi: 10.1164/rccm.200504-568OC. [DOI] [PubMed] [Google Scholar]
- 18.Hu G, Zhou Y, Tian J, Yao W, Li J, Li B, et al. Risk of COPD from exposure to biomass smoke: a metaanalysis. Chest. 2010;138:20–31. doi: 10.1378/chest.08-2114. [DOI] [PubMed] [Google Scholar]
- 19.Salvi S, Barnes PJ. Is exposure to biomass smoke the biggest risk factor for COPD globally? Chest. 2010;138:3–6. doi: 10.1378/chest.10-0645. [DOI] [PubMed] [Google Scholar]
- 20.Zelikoff JT, Chen LC, Cohen MD, Schlesinger RB. The toxicology of inhaled woodsmoke. J Toxicol Environ Health B Crit Rev. 2002;5:269–82. doi: 10.1080/10937400290070062. [DOI] [PubMed] [Google Scholar]
- 21.Snoeck-Stroband JB, Lapperre TS, Gosman MM, Boezen HM, Timens W, ten Hacken NH, et al. Chronic bronchitis sub-phenotype within COPD: inflammation in sputum and biopsies. Eur Respir J. 2008;31:70–7. doi: 10.1183/09031936.00137006. [DOI] [PubMed] [Google Scholar]
- 22.Ekberg-Aronsson M, Pehrsson K, Nilsson JA, Nilsson PM, Lofdahl CG. Mortality in GOLD stages of COPD and its dependence on symptoms of chronic bronchitis. Respir Res. 2005;6:s98. doi: 10.1186/1465-9921-6-98. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Mahesh PA, Jayaraj BS, Prabhakar AK, Chaya SK, Vijayasimha R. Prevalence of chronic cough, chronic phlegm & associated factors in Mysore, Karnataka, India. Indian J Med Res. 2011;134:91–100. [PMC free article] [PubMed] [Google Scholar]
- 24.Jindal SK, Aggarwal AN, Chaudhry K, Chhabra SK, D’Souza GA, Gupta D, et al. A multicentric study on epidemiology of chronic obstructive pulmonary disease and its relationship with tobacco smoking and environmental tobacco smoke exposure. Indian J Chest Dis Allied Sci. 2006;48:23–9. [PubMed] [Google Scholar]
- 25.censusindia.gov.in [homepage on the internet] Census of India Website. Census 2001 Social Cultural Data. c2010-11. Available from: http://www.censusindia.gov.in/Census_Data_2001/Census-Data_Online’Social_and cultural/Age_Groups.aspx .
- 26.Buist AS, McBurnie MA, Vollmer WM, Gillespie S, Burney P, Mannino DM, et al. International variation in the prevalence of COPD (the BOLD Study): a population-based prevalence study. Lancet. 2007;370:741–50. doi: 10.1016/S0140-6736(07)61377-4. [DOI] [PubMed] [Google Scholar]
- 27.Definition and classification of chronic bronchitis for clinical and epidemiological purposes. A report to the Medical Research Council by their Committee on the Aetiology of Chronic Bronchitis. Lancet. 1965;1:775–9. [PubMed] [Google Scholar]
- 28.Smith KRMS, Maeusezahl-Feuz M, editors. Indoor air pollution from household use of solid fuels: comparative quantification of health risk. Geneva, Switzerland: World Helth Organization; 2004. [Google Scholar]
- 29.Orozco-Levi M, Garcia-Aymerich J, Villar J, Ramirez-Sarmiento A, Anto JM, Gea J. Wood smoke exposure and risk of chronic obstructive pulmonary disease. Eur Respir J. 2006;27:542–6. doi: 10.1183/09031936.06.00052705. [DOI] [PubMed] [Google Scholar]
- 30.Smith-Sivertsen T, Diaz E, Pope D, Lie RT, Diaz A, McCracken J, et al. Effect of reducing indoor air pollution on women's respiratory symptoms and lung function: the RESPIRE Randomized Trial, Guatemala. Am J Epidemiol. 2009;170:211–20. doi: 10.1093/aje/kwp100. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Romieu I, Riojas-Rodriguez H, Marron-Mares AT, Schilmann A, Perez-Padilla R, Masera O. Improved biomass stove intervention in rural Mexico: impact on the respiratory health of women. Am J Respir Crit Care Med. 2009;180:649–56. doi: 10.1164/rccm.200810-1556OC. [DOI] [PubMed] [Google Scholar]