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Table 1 Characteristics of studies

From: Biomass fuel as a risk factor for esophageal squamous cell carcinoma: a systematic review and meta-analysis

Author, Year of publication (country) Primary objective Case ascertainment Control ascertainment Matching Biomass fuel type Total cases Cases using biomass Total controls Controls using biomass OR (95% CI) Adjusted in regression Newcastle-Ottawa Scale rating
Castellsagué, 2000 [40] (Argentina, Brazil, Paraguay, and Uruguay) To estimate the effects of consuming hot beverages and other food items on esophageal cancer risk in South America Histology Hospital-based patients with diseases unrelated to alcohol or tobacco. Gender, age, admission to the same hospital and same period as the case, residence in the area for > 5 years. Charcoal 830 96 1779 110 1.22 (0.85, 1.76) Hospital, residency, years of education, cigarettes and ethanol. 8
Pacella-Norman, 2002 [35] (South Africa) Risk factors for esophageal, lung, oral and laryngeal cancers in black South Africans Histology Patients with cancers not associated with tobacco or alcohol consumption were used as controls Wood, coal, anthracite 405 354 2174 1787 1.29 (0.82, 2.03) Age, tobacco, alcohol 7
Dandara, 2006 [42] (South Africa) Role of SULT1A1 and CYP3A5 polymorphisms as risk modifiers for ESCC. Histology Healthy community controls Age-and geographical location Wood and Charcoal 245 91 288 45 4.78 (3.02, 7.56)a Alcohol consumption and tobacco smoking. 8
Li, 2010 [32] (South Africa) Evaluate the effects of polymorphisms in Glutathione S-transferase genotypes on the risk of developing ESCC Histology Hospitalized patients Wood or charcoal 245 46 288 3 12.1 (3.26, 49.00) Alcohol, race, sex, age, and tobacco 6
Sapkota, 2012 [43] (Russia, Romania, Poland, Hungary, Slovakia, and the Czech Republic) Indoor air pollution from coal and wood as risk factors for upper aerodigestive tract in the high-risk areas of Central and Eastern Europe. Histology Patients admitted to the same hospital as cases for conditions unrelated to smoking or alcohol. _ Wood 186 25 1110 61 2.71 (1.21, 6.10) Country, age, sex, BMI, tobacco, alcohol, and consumption of dairy, redmeat, fruits and vegetables. 6
Dar, 2013 [31] (India) The association of multiple indicators of SES and ESCC risk in the Kashmir valley. Histology Patients with disease not strongly associated with tobacco or alcohol consumption, based on published reports. Age, sex, and district of residence Animal dung, wood, biomass 703 685 1664 1358 1.24 (1.05, 2.20) Age, ethnicity, place of residence, religion, daily fresh fruit and vegetable intake, cigarettes, hookah, and nass, and bidi, gutka, and alcohol. 7
Mota, 2013 [34] (Brazil) Evaluate the risk factors for esophageal cancer in a low-incidence area. Histology Patients living in study area for atleast 1 year prior to the study and had no history of esophageal cancer. Gender, age (< 5 years) and place of residence (urban or rural). Wood 99 33 223 19 4.42 (2.35, 8.32) 5
Patel, 2013 [36] (Kenya) Identify the risk factors. Histology Patients or relatives or visitors at the hospital with no relation to cancer. Area of residence, tribe, age (< 2 yrs), sex, and time of admittance. Wood and charcoal 147 70 159 41 2.31 (1.41, 3.84) 6
Wang, 2013 [38] (South Africa) Polymorphisms and Environmental Smoke as risk of ESCC Histology Healthy individuals without any previous history of cancer and randomly recruited from the same population groups and geographical area as the cases. _ Wood and charcoal 565 192 1000 131 3.92 (2.35, 6.53)a Age, gender, tobacco smoking. 7
Kayamba, 2015 [39] (Zambia) Explore risk factors of ESCC. Histology Normal upper endoscopic evaluations Age and sex Wood and Charcoal 50 34 50 18 3.00 (1.20, 7.40) Smoking, alcohol intake, HIV and HPV infection, exposure to household smoke, educational level, residence, marital status and occupation. 8
Mlombe, 2015 [33] (Malawi) Explore environmental factors associated with esophageal cancer. Histology Healthy community members from hospital catchment areas, hospital staff and visitors aged 18 years or older with no history of cancer. _ Wood 96 66 180 13 12.60 (4.20, 37.70) Age, gender, socioeconomic status, cooking methods, and smoking. 8
Rafiq, 2016 [20] (India) Association between secondhand house smoke and risk of ESCC. Histology Patients without disease with strong association with tobacco or alcohol consumption. Age, sex, and district of residence. Biomass 703 685 1664 1358 4.42 (2.35, 8.32) _ 7
Shah, 2017 [44] (India) Association of cytochrome P-450 and sulfotransferase genotypes with ESCC risk and their modifying effects on different risk factors of ESCC. Histology Patients with disease not strongly associated with tobacco or alcohol consumption, based on published reports. Sex, age and district of residence. Biomass 404 213 404 84 5.11 (1.34, 19.50) Age, ethnicity, religion, gender, daily fruit and vegetable consumption, place of residence, education level, income, wealth score, nass chewing, and tobacco smoking. 8
Bhat, 2017 [30] (India) Association of genetic polymorphisms of cytochrome 2C19 and 2D6 genotypes with ESCC. Histology _ Age (< 5 years), sex, and place of residence. Biomass 492 120 492 349 4.60 (1.50, 14.10) Age, ethnicity, gender, place of residence, religion, education level, wealth score, animal contact, oral hygiene, log of fruits and vegetables, tobacco smoking, nass consumption, alcohol drinking, and family history of any cancer and salted tea. 8
Mmbaga, 2017 [41] (Tanzania) Characterize EC cases Histology Hospitalized with non-smoke/alcohol-related disease Age and sex Wood 375   375   2.66 (1.88, 3.76) _ 5
Dwomoh, 2019 [45] (Uganda) Cooking fuel type as a risk factor of ESCC Histology Normal upper endoscopic evaluations _ Wood 75   386   1.07 (0.07, 16.58) Age, sex, smoking, and alcohol 5
  1. aThis is a result of a mini meta analysis of results of the article of association of solid fuel use with ESCC which were segregated by race i.e., blacks (AOR 7.855, 95%CI 4.061, 15.194) and mixed ancestry (AOR 1.39, 95%CI 0.621, 3.114)