| Literature DB >> 20386628 |
Gauravi A Mishra1, Surendra S Shastri, Pallavi A Uplap, Parishi V Majmudar, Pallavi S Rane, Subhadra D Gupta.
Abstract
BACKGROUND: Tobacco use is highly prevalent and culturally accepted in rural Maharashtra, India. AIMS: To study the knowledge, attitude, and practices (KAP) regarding tobacco consumption, identify reasons for initiation and continuation of tobacco use, identify prevalence of tobacco consumption and its relation with different precancerous lesions, provide professional help for quitting tobacco, and develop local manpower for tobacco cessation activities. SETTINGS, DESIGN, METHODS AND MATERIAL: The present study was conducted for one year in a chemical industrial unit in Ratnagiri district. All employees (104) were interviewed and screened for oral neoplasia. Their socio-demographic features, habits, awareness levels etc. were recorded. Active intervention in the form of awareness lectures, focus group discussions, one-to-one counseling and, if needed, pharmacotherapy was offered to the tobacco users.Entities:
Keywords: Tobacco cessation; focus group discussions; health awareness; oral screening; workplace
Year: 2009 PMID: 20386628 PMCID: PMC2847335 DOI: 10.4103/0019-5278.55129
Source DB: PubMed Journal: Indian J Occup Environ Med ISSN: 0973-2284
Figure 1Health awareness lecture
Figure 2Focus Group Discussions
Figure 3Prevalence of different forms of tobacco use
Socio-demographic Characteristics of Participants In the Tobacco Cessation Program
| Variables Total | Total Participants (%) 104 | Tobacco non users (%) 54 | Tobacco Users (%) 50 | ||
|---|---|---|---|---|---|
| Age Groups (in years) | ≤ 30 | 2 (1.92) | 2 (3.7) | - | |
| 31–35 | - | - | - | ||
| 36–40 | 19 (18.27) | 9 (16.67) | 10 (20.00) | χ2 = 2.2567 | |
| 41–45 | 47 (45.19) | 24 (44.44) | 23 (46.00) | ||
| 46–50 | 24 (23.08) | 12 (22.22) | 12 (24.00) | ||
| > 50 | 12 (11.54) | 7 (12.96) | 5 (10.00) | ||
| Mean Age in years (SD) | 43.28 (4.58) | 43.5 (5.09) | 44.3 (3.97) | ||
| Education | Primary [1–4] | 2 (1.92) | 0 -- | 2 (4.00) | |
| Secondary [5–10] | 14 (13.46) | 9 (16.67) | 5 (10.00) | ||
| Jr. College [11–12] | 19 (18.27) | 8 (14.81) | 11 (22.00) | χ2 = 3.843 | |
| Sr. College [13–15] | 35 (33.66) | 19 (35.19) | 16 (32.00) | ||
| Graduates and above | 34 (32.69) | 18 (33.33) | 16 (32.00) | ||
| Income per month | Rs. 10,000–20,000 | 30 (29.13) | 16 (30.19) | 14 (28.00) | |
| Rs. 21,000–30,000 | 46 (44.66) | 23 ((43.40) | 23 (46.00) | χ2=1.0205 | |
| Rs.31,000–40,000 | 19 (18.44) | 11 (20.75) | 8 (16.00) | ||
| > Rs.40,000 | 8 (7.77) | 3 (5.66) | 5 (10.00) | ||
| Religion | Hindu | 102 (98.08) | 54 (100) | 48 (96.00) | χ2=2.202 |
| Muslim | 1 (0.96) | -- -- | 1 (2.00) | ||
| Others | 1 (0.96) | -- -- | 1 (2.00) | ||
| Duration of Service (in years) | < 5 | 2 (1.92) | 2 (3.70) | 0 -- | |
| 5–10 | 1 (0.96) | 1 (2.00) | |||
| 11–15 | 8 (7.70) | 6 (11.11) | 2 (4.00) | χ2=6.1608 | |
| 16–20 | 45 (43.27) | 25 (46.30) | 20 (40.00) | ||
| 21–25 | 48 (46.15) | 21 (38.89) | 27 (54.00) | ||
| > 25 | -- | -- | -- | ||
| Presence of Shift Duty | Yes | 65 (62.50) | 33 (61.11) | 32 (64.00) | χ2=0.0924 |
| No | 39 (37.50) | 21 (38.89) | 18 (36.00) |
Comparison of Pre-Intervention responses regarding harmful effects of tobacco in tobacco users and nonusers
| Knowledge-based questions on tobacco Total Participants (104) | Employees who identified | Nontobacco users (%) the risk correctly (%) | Tobacco users (%) | |
|---|---|---|---|---|
| Employees who identified tobacco as injurious to health | 104 (100) | 54 (51.92) | 50 (48.08) | -- |
| Employees who identified tobacco as risk factor for Cancer | 99 (95.19) | 53 (53.54) | 46 (46.46) | χ2 =2.144 ( |
| Employees who identified tobacco as risk factor for Bronchitis | 41 (39.42) | 21 (51.22) | 20 (48.78) | χ2=0.0134 ( |
| Employees who identified tobacco as risk factor for Heart Attack | 49 (47.16) | 24 (48.98) | 25 (51.02) | χ2=0.3216 ( |
| Employees who identified tobacco as risk factor for Paralysis/Stroke | 41 (39.42) | 21 (51.22) | 20 (48.78) | χ2= 0.0134 ( |
| Employees who identified tobacco as risk factor for wrinkling of skin, early aging, infertility in females and impotence among males | 58 (55.77) | 29 (50.00) | 29 (50.00) | χ2=2.517 ( |
| Employees who identified cigarettes, beedi, tobacco chewing, betel nuts, betel leaves with tobacco, paan masala, gutkha, hookah all as harmful | 45 (43.27) | 24 (53.33) | 21 (46.67) | χ2=0.0632 ( |
| Employees who identified filtered, low tar, low nicotine cigarettes as unsafe | 57 (54.81) | 28 (49.12) | 29 (50.88) | χ2=0.396 ( |
| Employees who identified passive smoking dangerous | 101 (97.12) | 54 (53.47) | 47 (46.53) | χ2=3.336 (v=0.068) |
| Employees who knew that tobacco is dangerous even when consumed infrequently | 86 (82.69) | 45 (52.33) | 41 (47.67) | χ2=0.0322 ( |
| Employees who knew that professional help is available to quit tobacco | 78 (75) | 36 (46.15) | 42 (53.85) | χ2=4.160 ( |
Figure 4Factors responsible for initiation of tobacco habit
Figure 5Factors responsible for continuation of tobacco habit