Tobacco use in shisha: Studies on waterpipe smoking

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13 National survey on cigarettes and waterpipe smok<strong>in</strong>g <strong>in</strong> Egypt, 2005 3.1 Introduction A multistage, random sampl<strong>in</strong>g method was <strong>use</strong>d to recruit ho<strong>use</strong>hold persons from the general population of Egypt for a survey designed to generate estimates of tobacco <strong>use</strong> prevalence. Stage one was to obta<strong>in</strong> a random stratified cluster sample of the adm<strong>in</strong>istrative districts of Egypt. The sampl<strong>in</strong>g frame was the list of adm<strong>in</strong>istrative districts of Egypt (n = 323). These districts were stratified <strong>in</strong>to six geographic and urban/rural strata as shown <strong>in</strong> the follow<strong>in</strong>g table. Districts for each stratum were listed <strong>in</strong> an Excel spreadsheet <strong>in</strong> the same order as <strong>in</strong> the CAPMAS (Central Agency for Public Mobilization and Statistics). A one-fifth (20%) proportional stratified random sample of all districts was obta<strong>in</strong>ed us<strong>in</strong>g random number generation <strong>in</strong> Excel software. The 65 sampled districts were <strong>in</strong> 25 governorates of Egypt (out of 27 total governorates). Geographic stratum Districts Sampled districts Frontier areas 36 qism and markaz 7 Metropolitan areas 70 qism 14 Rural Lower Egypt 85 markaz 17 Urban Lower Egypt 38 qism 8 Rural Upper Egypt 68 markaz 14 Urban Upper Egypt 26 qism 5 Total 323 65 Qism is the Arabic for an urban district. Markaz is the Arabic for a ma<strong>in</strong>ly rural district. Stage two obta<strong>in</strong>ed a clustered random sample of local villages (for the sampled rural districts) and local areas with<strong>in</strong> cities (for the sampled urban districts). The sampl<strong>in</strong>g frame for rural districts (markaz) was the list of villages from the same CAPMAS reference, and we randomly selected two villages to represent each district. The sampl<strong>in</strong>g frame for urban districts (qism) was the list of police jurisdictions (shiakha), and we randomly selected two such jurisdictions for each urban district. This process resulted <strong>in</strong> 31
3 the random selection of 122 total sites. The previous two stages were done <strong>in</strong> the office. The follow<strong>in</strong>g stages were designed <strong>in</strong> the office and implemented <strong>in</strong> the field. Stage three obta<strong>in</strong>ed a cluster random sample of neighbourhoods with<strong>in</strong> the 122 field sites. For this stage, the cluster is def<strong>in</strong>ed as a street. Two streets were to be selected from two different areas, one central area and another <strong>in</strong> a peripheral area. The central area was identified by a certa<strong>in</strong> landmark <strong>in</strong> the village or city site (such as a bus or tra<strong>in</strong> term<strong>in</strong>us, M<strong>in</strong>istry of Health and Population health unit, school, mosque or church). Streets <strong>in</strong> this central area were numbered, and <strong>in</strong>structions were given to field staff to start number<strong>in</strong>g at the right hand side and go anticlockwise. For the purpose of random selection of the street, random number tables were prepared us<strong>in</strong>g Excel software. The peripheral area was selected as far as possible from the central area, and the same procedure of street sampl<strong>in</strong>g was followed. This random selection was done by the field supervisor; the random number that was <strong>use</strong>d was then crossed out <strong>in</strong> the random number tables, not to be <strong>use</strong>d aga<strong>in</strong>. Stage four obta<strong>in</strong>ed a clustered random sample of build<strong>in</strong>gs with<strong>in</strong> the selected streets. The number of build<strong>in</strong>gs <strong>in</strong> the sampled street were either counted or estimated (<strong>in</strong> the case of long streets). For the systematic sampl<strong>in</strong>g procedure, the sampl<strong>in</strong>g fraction was calculated to allow for seven to eight build<strong>in</strong>gs to be sampled <strong>in</strong> each street. The first build<strong>in</strong>g was selected from the same random table. This random selection was done by the field supervisor, and the random number <strong>use</strong>d was crossed <strong>in</strong> the random table, not to be <strong>use</strong>d aga<strong>in</strong>. In stage five, a clustered random sample of ho<strong>use</strong>holds was obta<strong>in</strong>ed. We selected one ho<strong>use</strong>hold from each build<strong>in</strong>g: these were almost always flats <strong>in</strong> the case of urban streets. Us<strong>in</strong>g random number tables, the flats were numbered start<strong>in</strong>g at the first floor go<strong>in</strong>g up, start<strong>in</strong>g on the right hand side. In village streets, the families <strong>in</strong> s<strong>in</strong>gle-family ho<strong>use</strong>s were numbered as the families were identified by the <strong>in</strong>terviewer. This random selection was done by the <strong>in</strong>terviewers, and the random number <strong>use</strong>d was crossed out <strong>in</strong> the list, not to be <strong>use</strong>d aga<strong>in</strong>. Stage six was a random sample of <strong>in</strong>dividuals, stratified by age and sex. The family members <strong>in</strong> each randomly selected ho<strong>use</strong>hold were listed by code or relation <strong>in</strong> the ho<strong>use</strong>hold (e.g., father, daughter) <strong>in</strong>to four categories (strata) as follows: a) males, 18 years of age and older; b) females, 18 years of age and older; c) males, between 12 and 17 years of age; d) females, between 12 and 17 years of age. We selected one person from each category whenever available, depend<strong>in</strong>g on random number tables. This random selection was done by the <strong>in</strong>terviewers, who crossed out the <strong>use</strong>d random number <strong>in</strong> the list, not to be <strong>use</strong>d aga<strong>in</strong>. They then <strong>in</strong>terviewed the randomly selected <strong>in</strong>dividuals about the smok<strong>in</strong>g habits us<strong>in</strong>g a standard questionnaire. A salivary cot<strong>in</strong><strong>in</strong>e test strip was <strong>use</strong>d to validate the self-reported smok<strong>in</strong>g habits. 3.2 Results The sample response rate was very good for the overall group; however for males, both adults (18 years and above) and adolescents, the response rate was less than females, beca<strong>use</strong> most of them were unavailable for two <strong>in</strong>terview visits. Also, a large proportion was work<strong>in</strong>g for more than two months outside the place of <strong>in</strong>terview (either abroad or <strong>in</strong> another governorate). Table 3.1 shows the age, sex and urban/rural status of the surveyed <strong>in</strong>dividuals. <strong>Tobacco</strong> <strong>use</strong> <strong>in</strong> <strong>shisha</strong>
Page 3 and 4: WHO Library Cataloguin</str
Page 5 and 6: 7. The micronucleus test in
Page 8 and 9: Summary The waterpipe (also known a
Page 10 and 11: 14. As an example of biomarker-base
Page 12 and 13: 1.2 Structure of waterpipes Parts a
Page 14 and 15: The average nicotin</strong
Page 16 and 17: (shisha) smok<stro
Page 18 and 19: 2.2 Subjects and methods In 2002, a
Page 20 and 21: Type of smoker Adult male (%) Exclu
Page 22 and 23: Overall cigarette consumption (mill
Page 24 and 25: Table 2.6 Hypertension, high random
Page 26 and 27: individuals are cu
Page 28 and 29: 2.6 Limitations of the study and re
Page 30 and 31: [23] Gomma RA. Report of health <st
Page 34 and 35: Table 3.1 Age, sex and residence di
Page 36 and 37: It is very well shown that there is
Page 38 and 39: Group 2: non-current waterpipe smok
Page 40 and 41: 4 Epidemiology of waterpipe smok<st
Page 42 and 43: 16% 4% 1% 79% Figure 4.1 Overall sm
Page 44 and 45: Waterpipe smoking
Page 46 and 47: Many waterpipe smokers (57%) have a
Page 48 and 49: Nearly one-third of all smokers wer
Page 50 and 51: In the present study the prevalence
Page 52 and 53: [24] Fadel AK, Hamam MH, Abdel Aziz
Page 54 and 55: could encourage smokin</str
Page 56 and 57: It is less harmful To decrease smok
Page 58 and 59: population was aware that smok<stro
Page 60 and 61: 6 Behavioural and biological aspect
Page 62 and 63: turn, health is affected by occupat
Page 64 and 65: Percentage Figure 6.2 Carboxyhaemog
Page 66 and 67: oth groups) levels in</stro
Page 68 and 69: to cigarette smokers needs further
Page 70 and 71: significant association between tob
Page 72 and 73: [15] El-Shaer AAA, El-Mosalamy MA,
Page 74 and 75: [43] Amin AAA. Eff
Page 76 and 77: [70] El Shimy WS, Shallouf MA, Ghor
Page 78 and 79: [98] Bayoumi W, Muhamed SF, Mursi.
Page 80 and 81: 7.2 Subjects and methods The Egypti
Page 82 and 83:
Table 7.1 Mean TMN and smok
Page 84 and 85:
[7] Desai SS, Ghaisas SD, Jakhi SD,
Page 86:
The rules and regulations stipulate
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