Literature DB >> 33663469

Tobacco use and associated factors among adults reside in Arba Minch health and demographic surveillance site, southern Ethiopia: a cross-sectional study.

Befikadu Tariku Gutema1,2, Adefris Chuka3, Gistane Ayele4,5, Wubshet Estifaons6, Zeleke Aschalew Melketsedik6, Eshetu Zerihun Tariku4, Zerihun Zerdo5,7, Alazar Baharu5,8, Nega Degefa Megersa6.   

Abstract

BACKGROUND: Tobacco use is one of the world-leading preventable killers. There was a varied prevalence of tobacco use and cigarette smoking across different areas. The aim of the study was to assess the prevalence and factors associated with current tobacco use among adults residing in Arba Minch health and demographic surveillance site (HDSS).
METHODS: A community-based cross-sectional study was conducted among adults residing in Arba Minch HDSS in 2017. The estimated sample size was 3368 individuals which were selected by simple random sampling techniques using Arba Minch HDSS dataset. Data collection tools were obtained from the WHO STEPwise. Current use of tobacco, which defined as the current use of smoked and/or smokeless tobacco, was considered as the dependent variable. A binary logistic regression model was used to identify candidate variables for the multivariable logistic regression model. An adjusted odds ratio (AOR) at a p-value of less than 0.05 was used to determine a statistically significant association between independent and dependent variables. RESULT: The prevalence of tobacco use among adults was 20.2% (95% CI: 18.9-21.6%). The current use of smoked and smokeless tobacco were 17.1% (95%CI: 15.8-18.4%) and 9.7% (95%CI: 8.8-10.8%), respectively. The current use of tobacco was significantly associated with sex (female [AOR 0.54; 95%CI: 0.42-0.68] compared to men), age group (35-44 [AOR 1.57; 95%CI: 1.14-2.17], 45-54 [AOR 1.99; 95%CI: 1.45-2.74], and 55-64 [AOR 3.26; 95%CI: 2.37-4.48] years old compared to 25-35 years old), physical activity (moderate physical activity level [AOR 0.65; 95%CI: 0.44-0.96] compared with low) and residency (highland [AOR 4.39; 95% CI: 3.21-6.01] compared with at lowlander). Also, heavy alcohol consumption (AOR 3.97; 95% CI: 3.07-5.12), and Khat chewing (AOR 3.07(95%CI: 1.64-5.77) were also associated with the use of tobacco among the study participants.
CONCLUSION: Nearly one in five adults used tobacco currently in the study area, which is more than the national reports. Interventions for the reduction of tobacco use need to give due attention to men, older adults, uneducated, poor, and highlanders.

Entities:  

Keywords:  Ethiopia; Health and demographic surveillance site (HDSS); Smoked; Smokeless; Tobacco

Year:  2021        PMID: 33663469      PMCID: PMC7934440          DOI: 10.1186/s12889-021-10479-4

Source DB:  PubMed          Journal:  BMC Public Health        ISSN: 1471-2458            Impact factor:   3.295


  42 in total

1.  Smoking in Colombian medical schools: the hidden curriculum.

Authors:  D Rosselli; O Rey; C Calderon; M N Rodriguez
Journal:  Prev Med       Date:  2001-09       Impact factor: 4.018

2.  Tobacco associated mortality in Mumbai (Bombay) India. Results of the Bombay Cohort Study.

Authors:  Prakash C Gupta; Mangesh S Pednekar; D M Parkin; R Sankaranarayanan
Journal:  Int J Epidemiol       Date:  2005-10-25       Impact factor: 7.196

3.  Burden of total and cause-specific mortality related to tobacco smoking among adults aged ≥ 45 years in Asia: a pooled analysis of 21 cohorts.

Authors:  Wei Zheng; Dale F McLerran; Betsy A Rolland; Zhenming Fu; Paolo Boffetta; Jiang He; Prakash Chandra Gupta; Kunnambath Ramadas; Shoichiro Tsugane; Fujiko Irie; Akiko Tamakoshi; Yu-Tang Gao; Woon-Puay Koh; Xiao-Ou Shu; Kotaro Ozasa; Yoshikazu Nishino; Ichiro Tsuji; Hideo Tanaka; Chien-Jen Chen; Jian-Min Yuan; Yoon-Ok Ahn; Keun-Young Yoo; Habibul Ahsan; Wen-Harn Pan; You-Lin Qiao; Dongfeng Gu; Mangesh Suryakant Pednekar; Catherine Sauvaget; Norie Sawada; Toshimi Sairenchi; Gong Yang; Renwei Wang; Yong-Bing Xiang; Waka Ohishi; Masako Kakizaki; Takashi Watanabe; Isao Oze; San-Lin You; Yumi Sugawara; Lesley M Butler; Dong-Hyun Kim; Sue K Park; Faruque Parvez; Shao-Yuan Chuang; Jin-Hu Fan; Chen-Yang Shen; Yu Chen; Eric J Grant; Jung Eun Lee; Rashmi Sinha; Keitaro Matsuo; Mark Thornquist; Manami Inoue; Ziding Feng; Daehee Kang; John D Potter
Journal:  PLoS Med       Date:  2014-04-22       Impact factor: 11.069

4.  Gender differences in tobacco use in Africa, Asia, the Pacific, and Latin America.

Authors:  I Waldron; G Bratelli; L Carriker; W C Sung; C Vogeli; E Waldman
Journal:  Soc Sci Med       Date:  1988       Impact factor: 4.634

5.  Effects of acute psychosocial stress on cigarette craving and smoking.

Authors:  Emma Childs; Harriet de Wit
Journal:  Nicotine Tob Res       Date:  2010-01-25       Impact factor: 4.244

6.  Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015.

Authors: 
Journal:  Lancet       Date:  2016-10-08       Impact factor: 79.321

7.  Tobacco use and associated factors among adults in Ethiopia: further analysis of the 2011 Ethiopian Demographic and Health Survey.

Authors:  Yihunie Lakew; Demewoz Haile
Journal:  BMC Public Health       Date:  2015-05-13       Impact factor: 3.295

8.  Factors affecting tobacco smoking in Ethiopia: evidence from the demographic and health surveys.

Authors:  Harminder Guliani; Samuel Gamtessa; Monika Çule
Journal:  BMC Public Health       Date:  2019-07-12       Impact factor: 3.295

9.  Risk factors for chronic non-communicable diseases at gilgel gibe field research center, southwest ethiopia: population based study.

Authors:  Fessahaye Alemseged; Abraham Haileamlak; Ayalew Tegegn; Fasil Tessema; Kifle Woldemichael; Makonnen Asefa; Yoseph Mamo; Solomon Tamiru; Gemeda Abebe
Journal:  Ethiop J Health Sci       Date:  2012-08
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