- Email: [email protected]
Changes in smoking habits in adults: results from a prospective study in Spain
Changes in Smoking Habits in Adults: Results from a Prospective Study in Spain ANTONIO AGUDO, MD, MSC, GUILLEM PERA, BSC, MAURICIO RODRIGUEZ, MD, J. RAMON QUIROS, MD, CARMEN NAVARRO, MD, PHD, CARMEN MARTINEZ, MD, ˜ AGA, MD, MSC, ANA FERNANDEZ, MD, MIREN DORRONSORO, MD, MSC, NEREA LARRAN M. DOLORES CHIRLAQUE, MD, ANTONIO BERENGUER, BSC, AURELIO BARRICARTE, MD, EVA ARDANAZ, PHD, PILAR AMIANO, MSC, M. JOSE TORMO, PHD, AND CARLOS A. GONZALEZ, MD, PHD
PURPOSE: We assessed changes in smoking behavior and its related factors among healthy adults from five regions in Spain. METHODS: The smoking status at recruitment and after 3 years was compared in 14,288 men and 23,983 women aged 35 to 64 years. The pattern of smoking and several lifestyle factors were investigated as potential predictors of subsequent changes in smoking habits. RESULTS: Among current smokers at baseline the age-adjusted rates of cessation per 1000 person-years were 57.4 for men and 43.2 for women. Among former smokers at baseline the relapse rates were 37.6 and 48.8 per 1000 person-years for men and women, respectively. The initiation rate per 1000 personyears among men who had never smoked was 12.5 and 2.7 for women. Higher amount currently smoked and longer time since quitting were strong predictors of lower rates of cessation and relapse, respectively, while age was associated with lower initiation rates in women. Increased alcohol consumption was related to low cessation and high relapse and initiation rates, mainly among men, while more educated women had higher cessation and initiation rates. CONCLUSIONS: The current pattern of changes in smoking behavior in Spanish populations aged 35 to 64 years results in rather small prevalence reduction. Additional efforts should be made to promote successful cessation and prevent initiation to reduce the tobacco burden in Spain. Ann Epidemiol 2004;14:235–243. 쑕 2003 Elsevier Inc. All rights reserved. KEY WORDS:
Tobacco, Smoke, Smoking Cessation, Cohort Studies, Epidemiologic Factors, Life Style,
Adult.
INTRODUCTION Cigarette smoking is the most important cause of premature death in developed countries, and is emerging as a major
From the Unit of Epidemiology, Catalan Institute of Oncology, L’Hospitalet de Llobregat (Barcelona), Spain (A.A., G.P., A.B., C.A.G.); Escuela Andaluza de Salud Pu´blica, Granada, Spain (M.R., C.M.); Consejerı´a de Sanidad y Servicios Sociales de Asturias, Oviedo, Spain (J.R.Q., A.F.); Servicio de Epidemiologı´a, Consejerı´a de Sanidad y Consumo, Murcia, Spain (C.N., M.D.C., M.J.T.); Direccio´n de Salud de Guipu´zcoa, San Sebastia´n, Spain (N.L., M.D., P.A.); and Instituto de Salud Pu´blica, Departamento de Salud de Navarra, Pamplona, Spain (A.B, E.A.). Address correspondence and reprint requests to: Antonio Agudo, M.D., M.Sc., Unit of Epidemiology, Catalan Institute of Oncology, Av. Gran Via s/n km 2.7, L’Hospitalet de Llobregat 08907, Spain. Tel.: ⫹34-93260-7401; Fax: ⫹34-93-260-7787. E-mail: [email protected] The EPIC Study is coordinated by the Unit of Nutrition and Cancer of the International Agency for Research on Cancer (IARC), Agreement AEP/93/02. In Spain it receives financial support from the ““Europe Against Cancer Program”” of the European Union (Agreement SO 97 200302 05F02), the Health Research Fund (FIS) of the Spanish Ministry of Health (Exp. 96-0032), and participating Regional Governments. Received November 4, 2002; accepted May 9, 2003. 쑕 2003 Elsevier Inc. All rights reserved. 360 Park Avenue South, New York, NY 10010
public health concern in developing countries (1, 2). The estimated annual average of premature deaths due to smoking in the United States (1995–1999) was 440,000 (3). The years of potential life lost were on average 13.2 and 14.5 for adult male and female smokers, respectively, and the economic costs of smoking totaled $3391 per smoker per year. In Finland the estimated yearly costs induced by smoking in men aged 25 to 50 years were V3647 per smoker, almost 60% of which were due to premature deaths (4). In most adult populations in western Europe the smoking prevalence in men declined from the early 1980s to the mid1990s; smoking among women tended to increase in populations with low initial prevalence, such as southern and some eastern countries (5). In Spain the prevalence of current smokers in men aged 45 to 64 years decreased from 54% to 44% in 10 years (1987–1997), while there was a striking increase (5% to 13%) among women in the same age group (6). The number of deaths due to smoking can only be reduced if a substantial proportion of adults who currently smoke quit. Even those smokers who quit at age 65 have an increase in life expectancy relative to those who continued to smoke (7). Furthermore, cessation reduces the risk 1047-2797/04/$–see front matter doi:10.1016/S1047-2797(03)00245-X
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Selected Abbreviations and Acronyms BMI ⫽ body mass index CI ⫽ confidence interval CHD ⫽ coronary heart disease EPIC ⫽ European Prospective Investigation into Cancer and Nutrition OC ⫽ oral contraceptives RR ⫽ rate ratio
and slows progression of tobacco-related diseases, and leads to a compression of morbidity and improvement in quality of life (8). However, many people continue to smoke despite knowing about the health consequences of tobacco, and many who try to quit fail. Approximately one third of smokers try to stop smoking each year, and fewer than one out of ten smokers who attempt to quit on their own are successful in the long run (9). Although the main obstacle to quitting is the addictive nature of nicotine, tobacco use involves complex determinants, and successful cessation or relapse is also related to social and lifestyle factors. Changes in prevalence have not been uniform across sociodemographic groups (6). Furthermore, there is evidence that apart from smoking behavior characteristics and level of motivation, certain socioeconomic and lifestyle factors are consistently related with adopting and maintaining the habit of smoking (10). Assessment of overall changes in smoking has rarely been approached, probably because cessation is the most relevant factor for adults, while initiation does mainly concern young people. On the other hand, analyses of changes in smoking behavior over time are often based upon cross-sectional samples of a population rather than true longitudinal followup. The present article deals with changes in smoking habits over a 3-year period in healthy adults from five regions in Spain. We present cessation, relapse, and initiation rates, as well as their association with demographic and lifestyle factors.
METHODS Subjects The European Prospective Investigation into Cancer and Nutrition (EPIC) is a large cohort study that is being carried out in ten European countries. In Spain it includes 41,446 subjects (15,634 men and 25,812 women) aged 29 to 69 years, recruited between 1992 and 1996. They were healthy volunteers, mainly blood donors, from five regions of Spain: three from the north (Asturias, Guipu´zcoa, and Navarra), and two from the south (Murcia and Granada). The participation rate varied from 50% to 60% across centers. Each subject provided information on dietary habits and other lifestyle factors; anthropometric measurements
and blood sample collection were also taken at the time of inclusion. Smoking Habits at Recruitment The information on smoking habits was collected by means of personal interview together with other lifestyle factors. Individuals were asked to classify themselves according to smoking status: a current smoker was defined as any person who smoked regularly (at least one cigarette per day and/ or one cigar or one pipe per week) at the time of the interview. Subjects who had smoked at least one cigarette per day and/or one cigar or one pipe per week in the past were classified as former smokers. Never smokers were those who had never smoked any tobacco product regularly. Current smokers of cigarettes provided information about the number of cigarettes smoked per day and how deeply they inhale the smoke, as well as characteristics of the cigarettes: blond or dark, with or without filter, light or normal. For both current and former cigarette smokers, the age at starting and some characteristics of the behavior in the past were collected: average number of cigarettes daily smoked, use of filter, type of tobacco (blond or dark). Former smokers were also asked about the age at which they quit. Details about the habit of smoking cigars or pipes were only collected among men. Lifestyle Factors and Anthropometric Measurements Education was categorized into four levels, from uncompleted primary school to any schooling at the university level or beyond. The current job was classified into sedentary, standing, manual, and heavy manual work. The time spent in leisure or sport activities was computed as the sum of the mean number of hours per week during the last year practicing hobbies and sports, walking, cycling, and gardening. Subjects were asked whether they had been diagnosed and treated for any major chronic conditions, including cancer and coronary heart diseases (CHD). Women were also asked if they had ever used oral contraceptives (OC). The information on habitual food intake over the previous year was gathered using a computerized version of the diet history method previously validated (11). For every food item, including alcoholic beverages, the frequency of consumption and the portion size were reported and then used to estimate the daily consumption in grams. Energy intake, cholesterol and alcohol consumption were estimated using a food composition table especially compiled for the EPIC study in Spain (12). Height was measured using a movable stadiometer and weight was measured after urination, using an electronic weighting machine. Subjects were classified according to the body mass index (BMI) as follows: ⬍20.0 kg/ m2, “lean”; 20.0–24.9, “normal”; 25.0–29.9, “overweight”; and BMI ⭓ 30.0, “obese”.
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Follow-up Cohort members were contacted by telephone approximately 3 years after recruitment, to obtain information about vital status, occurrence of major diseases, and some aspects of lifestyle. Regarding smoking habits, the participants must report whether they currently smoked cigarettes or had smoked cigarettes in the past, and the number of cigarettes smoked per day. The same questions were asked separately for cigars and pipes. The criteria to be classified as current or former smokers were the same used at recruitment: smoking (now or in the past) at least one cigarette per day and/ or one cigar or one pipe per week. A total of 691 subjects out of 41,446 (1.7%) could not be contacted: 228 had died, 200 refused, and 263 could not be located. Another 38 subjects had no information about smoking and 1754 individuals had inconsistencies between reported smoking status at recruitment and at follow-up (for instance, subjects initially self-reported as current or former smokers that declared afterwards that they had never smoked): all of them, as well as 692 subjects with age at recruitment below 35 or above 64 years were excluded. Thus, the final dataset for analysis of smoking behavior consisted of 38,271 subjects, 14,288 males and 23,983 females. Data Analysis All the analyses were carried out separately among men and women. Rates of cessation, relapse, and initiation were estimated among current, former, and never smokers, respectively, at recruitment, from the number of events (subjects who quit, resumed, or started to smoke, respectively) and the population-time at risk. The time at risk was computed as the number of days elapsed from the date of recruitment until the date of the follow-up. Since the exact time of changes was not recorded, the time at risk was halved for subjects reporting any change in their smoking habits during follow-up. The rates and corresponding 95% confidence interval (CI) are given per 1000 person-years standardized by the direct method (13) using as weights the age structure of the Spanish population. To facilitate external comparisons the rates were also standardized by age according to the world standard population. To assess the effect of factors potentially associated with the occurrence of a change in the smoking behavior over time, we fitted a generalized linear model using the complementary log-log function (14, 15). The time of follow-up was accounted for by specifying its logarithm as an offset in the model. It is assumed that events occur only once and the rate is constant during the follow-up period. The model provides for each covariate a parameter (and 95% CI) that estimates the effect of a unit change of the covariate in the rate measured in the log-scale; thus exponentiation of the parameter estimates the rate ratio (RR) associated with
Agudo et al. CHANGING SMOKING HABITS IN SPAIN
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this covariate. All factors were categorized and introduced into the model as dummy variables, so RRs were estimated for each category compared to a reference. The linear trend was tested by significance of the regression parameter of a variable coding the levels of increasing exposure in ordinal integers. To build a multivariate model for each type of change in smoking status we included all significant factors in at least one of the two genders in the univariate analysis (results not shown), as well as those factors supposed to have some effect based on previous studies: age, education, alcohol consumption, and characteristics of the smoking behavior. In addition to all the variables included in each model, the estimates were always adjusted by center. Furthermore, in order to address the effect of dietary composition as well as to control for measurement error, the estimates of dietary factors were always adjusted for total energy intake (16).
RESULTS The population studied consisted of three sets of subjects defined by their smoking status at recruitment (Table 1): 10,379 current smokers (5917 men and 4462 women), 6204 former smokers (4197 men and 2007 women), and 21,688 never smokers (4174 men and 17514 women). The age distribution is similar for men and women who never smoked, while women who were either current or former smokers tended to concentrate in the 35 to 44 years age group. Men had a higher proportion than women working in manual or heavy manual occupations, and they spent more time doing sports or other leisure activities, independent of their smoking status. The prevalence of obesity among current and former smokers is higher in men, while a higher proportion of obese women was observed among never smokers. However, the opposite pattern is seen for overweight. More than six out of ten women who were current smokers or had smoked in the past had used oral contraceptives during their lifetime, while only one third of never smokers had done so. Women consumed more coffee, while men tended to consume more alcohol. Among smokers (current and former), males had higher cigarette consumption. The cessation rates per 1000 person-years age-adjusted according to the Spanish population were 57.4(54-61) for men and 43.2(38-49) for women; the corresponding rates for relapse were 37.6(34-41) and 48.8(42-56), and 12.5(1115) and 2.7(2.2-3.2) for initiation. Standardization by Spanish population produced eventually the same values. As can be seen in the Figure 1 cessation sharply increases among the oldest group (55–64 years) in both sexes, while relapse has a consistent linear decrease with age; initiation is constant across age groups among men but decreases with age among women.
TABLE 1. Selected characteristics of subjects from the EPIC-Spain cohort 1992–96, according to their smoking status at recruitment (current, former, and never smokers) Current smokers
Center (province) Asturias Guipu´zcoa Navarra Murcia Granada Age group 35–44 years 45–54 years 55–64 years Education levela Primary not completed Primary school Secondary school University or technical Work activitya Sedentary Standing Manual, heavy manual Sports/leisure activity ⭐1 hour/week 1.1–7.0 hours/week 7.1–14.0 hours/week ⬎14 hours/week Body mass indexa,b Lean Normal Overweight Obese Antecedents of CHDa,c Antecedents of cancera Ever used OCa,d Alcohol consumptione Non consumer ⭐10.0 g/day 10.1–20.0 g/day 20.1–40.0 g/day 40.1–60.0 g/day ⬎60 g/day Coffee consumption ⭐50.0 ml/day 50.1–100.0 ml/day 100.1–200.0 ml/day ⬎200 ml/day Cigarette smokinga,f 1–10 cigarettes/day 11–20 cigarettes/day 21–30 cigarettes/day ⬎30 cigarettes/day Overall consumption of cigars and/or pipes Exclusive smokers of cigars and/or pipes Time since quitting smoking cigarettesa ⬍2 years 2–5 years 6–10 years ⬎10 years
Former smokers
Never smokers
Men (n ⫽ 5917) %
Women (n ⫽ 4462) %
Men (n ⫽ 4197) %
Women (n ⫽ 2007) %
Men (n ⫽ 4174) %
Women (n ⫽ 17,514) %
18.6 28.0 28.3 16.5 8.7
24.4 15.8 19.3 21.9 18.6
22.7 22.1 19.0 21.6 14.6
23.3 22.6 17.2 19.2 17.7
19.2 28.5 27.3 14.4 10.6
20.0 16.3 15.7 23.3 24.8
28.9 46.1 25.0
70.5 24.5 5.1
26.5 42.2 31.3
67.7 26.4 5.9
25.0 42.3 32.7
26.6 41.8 31.6
25.7 40.1 21.4 12.7
19.5 43.0 20.2 17.3
25.4 33.8 23.0 17.7
14.1 38.3 22.9 24.7
27.2 38.2 18.9 15.7
48.0 39.6 6.9 5.5
36.0 34.5 29.5
21.5 76.6 1.9
39.3 36.1 24.6
24.6 73.6 1.8
33.8 35.4 30.8
9.5 88.3 2.2
9.1 31.2 28.3 31.5
9.9 43.1 29.9 17.1
5.5 28.3 29.3 37.0
7.7 37.9 34.6 19.8
6.2 28.5 29.7 35.6
8.0 43.9 30.7 17.4
0.3 15.1 55.5 29.1 1.3 0.4 –
2.1 44.5 38.7 14.8 0.5 1.3 62.9
0.1 10.9 57.6 31.4 3.8 0.6 –
1.5 44.5 38.0 16.1 0.6 1.1 61.8
0.1 13.6 60.1 26.2 1.2 0.3 –
0.5 19.4 43.3 36.8 1.6 1.1 34.3
9.4 17.6 12.3 21.8 16.7 22.2
34.8 41.5 12.5 11.2
12.5 22.0 14.0 22.1 14.7 14.7
34.9 45.7 10.0 9.4
13.2 26.1 14.0 21.1 13.3 12.2
44.3 41.4 8.5 5.7
23.9 20.8 30.5 24.8
13.1 13.4 28.6 44.9
32.6 19.5 27.4 20.6
16.3 13.5 29.4 40.8
39.9 20.2 24.3 15.6
31.4 15.8 24.2 28.6
35.7 41.9 13.5 8.9 41.8 22.6
47.6 42.8 6.3 3.4 0.2 0.2
24.1 42.4 19.4 14.1 32.4 2.8
52.6 36.8 7.5 3.1 – –
13.7 22.1 25.5 38.7
19.6 27.3 22.9 30.1
a The percents reported are calculated over the number of subjects with valid information; the number of subjects (men ⫹ women) with missing information were as follows: education: 56 (29 ⫹ 27) current smokers, 38 (24 ⫹ 14) former smokers, and 158 (20 ⫹ 138) never smokers; type of work: 367 (267 ⫹ 98) current smokers, 237 (202 ⫹ 35) former smokers, and 686 (162 ⫹ 524) never smokers; body mass index: 30 (19 ⫹ 11) current smokers, 23 (18 ⫹ 5) former smokers, and 46 (11 ⫹ 35) never smokers; antecedents of CHD: 6 (2 ⫹ 4) current smokers, 6 (5 ⫹ 1) former smokers, and 18 (4 ⫹ 14) never smokers; antecedents of cancer: 47 (23 ⫹ 24) current smokers, 36 (27 ⫹ 9) former smokers, and 116 (17 ⫹ 99) never smokers; use of OC: 5 current smokers, 3 former smokers, and 21 never smokers; cigarette smoking: 1356 (1348 ⫹ 8) current smokers, and 212 (179 ⫹ 3) former smokers; years since quitting: 255 (242 ⫹ 13) former smokers. The high number of missing cigarette smoking and time since quitting is mainly due to men who smoked cigars and/or pipes exclusively. b Body mass index (kg/m2): lean, BMI ⬍ 20.0; normal, BMI 20.0–24.9; overweight, BMI 25.0–29.9; obese: BMI ⭓ 30.0. c Coronary heart diseases (includes angor and myocardial infarction). d Oral contraceptives. e Alcohol consumption: among women, the percent reported for the category 20.1–40.0 g/day actually corresponds to consumption of ⬎20.0 g/day. f Cigarette smoking: for current smokers the amount reported corresponds to current consumption at recruitment; for former smokers it corresponds to the average daily number of cigarettes smoked during the period when subjects smoked.
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The multivariate model for predictors of cessation among current smokers is shown in Table 2. Smoking cessation was positively associated with education in women; among men a higher rate of quitting was associated with high physical activity, antecedents of CHD, and low BMI, while high alcohol consumption and high cholesterol intake were predictors of low cessation rate. There was a consistent inverse association of cessation with the amount of cigarettes currently smoked in both sexes. The time elapsed since quitting was the strongest predictor of relapse among men and women former smokers (Table 3). The risk of relapse smoking after 2 years of abstinence was substantially reduced as compared with recent quitters (less than 2 years), and became very low among those who quit more than 10 years ago. On the other hand, the lifetime cigarette consumption was inversely related to relapse, heavier smokers being less likely to restart smoking once they had quit. There was a trend toward increased relapse associated with high alcohol consumption and low fruit intake, although no significant terms were observed for any category of consumption. The amount of cigarettes smoked per day and the number of packyears were predictors of cessation and relapse, respectively, due to which these variables were included in the final multivariate model and, therefore, subjects classified as current or former smokers at recruitment based solely on their cigars and/or pipe use were excluded. This means that the results reported in Tables 2 and 3 actually show the cessation and relapse patterns of daily cigarette smokers. Finally, initiation showed a strong inverse association with age among women and with education level among men (Table 4). High alcohol consumption (both sexes) and use of oral contraceptives (women) appeared to be important predictors of initiation.
DISCUSSION
FIGURE 1. Changes in smoking habits in the EPIC-Spain cohort (1992-96 to 1996-99) by sex and age group. Rates and 95% confidence intervals per 1,000 person-years of cessation, relapse, and initiation.
We have assessed the rates of changes in smoking behavior among healthy adults 35 to 64 years of age in Spain over a 3-year period. Cessation and initiation rates were higher among men while relapse rates were higher in women. Overall, healthy habits such as physical activity at leisure time, low alcohol consumption and cholesterol intake, and high intake of fruits tended to correlate positively with cessation and negatively with relapse and initiation. Comparison with other studies is difficult because age and time of follow-up vary markedly. Several studies in the United States (17–21) and one in Denmark (10, 22) found annual cessation rates ranging from 17 to 43 per thousand; compared to ours, all of them included younger populations with longer follow-up. A multicenter European study among subjects from the placebo group of a trial followed for 1 year (23) found a cessation rate of 99 per 1000
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TABLE 2. Factors associated with smoking cessation among current smokers in the EPIC-Spain cohort (1992–96 to 1996–99) Men RR Age group (reference: 35–44 years)
Education level (reference: primary not completed)
Work activity (reference: sedentary) Leisure or sports activity (hours/week) (reference: ⭐1 h/w)
Antecedents of CHDb Antecedents of cancer Body mass indexc (reference: normal weight)
Alcohol consumptiond (reference: non-consumer)
Coffee consumption (reference: ⭐50.0 ml/day)
Cigarettes per day (reference: 1–10)
Smoked cigars and/or pipes Cholesterol intake (reference: quartile 1)
45–54 years 55–64 years linear trend Primary school Secondary school University Standing Manual/heavy 1.1–7.0 hours/week 7.1–14.0 hours/week ⬎14 hours/week linear trend
Lean Overweight Obese linear trend ⭐10.0 g/day 10.1–20.0 g/day 20.1–40.0 g/day 40.1–60.0 g/day ⬎60 g/day linear trend 50.1–100.0 ml/day 100.1–200.0 ml/day ⬎200 ml/day linear trend 11–20 cigarettes/day 21–30 cigarettes/day ⬎30 cigarettes/day linear trend Quartile 2 Quartile 3 Quartile 4 linear trend
a
1.14 1.31 p ⫽ 0.007 0.91 0.91 1.09 0.98 1.04 1.35 1.27 1.33 p ⫽ 0.31 1.80 1.02 2.69 1.11 1.21 p ⫽ 0.12 0.99 0.79 0.88 0.76 0.75 p ⫽ 0.005 1.02 1.16 1.00 p ⫽ 0.64 0.81 0.69 0.58 p ⬍ 0.001 0.60 0.90 0.92 0.76 p ⫽ 0.038
Women 95% CI
a
0.97, 1.34 1.07, 1.60 0.77, 0.74, 0.86, 0.84, 0.87, 1.03, 0.96, 1.02,
1.08 1.12 1.36 1.14 1.24 1.77 1.67 1.75
1.17, 0.42, 1.17, 0.92, 0.98,
2.76 2.48 6.17 1.34 1.50
0.78, 0.61, 0.69, 0.58, 0.57,
1.25 1.04 1.12 0.99 0.97
0.84, 1.24 0.97, 1.38 0.82, 1.21 0.69, 0.95 0.54, 0.88 0.43, 0.79 0.49, 0.75, 0.75, 0.59,
0.74 1.09 1.12 0.97
a
RR
95% CIa
1.08 1.37 p ⫽ 0.20 1.37 1.57 1.74 0.81 1.21 1.08 1.20 0.93 p ⫽ 0.89 2.00 2.26 1.07 1.05 0.98 p ⫽ 0.99 1.16 0.87 0.85
0.88, 1.34 0.93, 2.02
p ⫽ 0.26 1.00 0.79 0.85 p ⫽ 0.16 0.67 0.62 0.43 p ⬍ 0.001 1.31 1.20 1.30 p ⫽ 0.20
1.05, 1.15, 1.26, 0.66, 0.68, 0.78, 0.86, 0.65,
1.80 2.15 2.40 1.01 2.16 1.48 1.68 1.35
0.87, 1.22, 0.60, 0.87, 0.74,
4.59 4.18 1.91 1.28 1.31
0.95, 1.42 0.64, 1.19 0.61, 1.19
0.73, 1.37 0.59, 1.04 0.65, 1.11 0.56, 0.81 0.41, 0.92 0.23, 0.82
1.01, 1.69 0.91, 1.58 0.93, 1.81
a
Rate ratios and 95% confidence intervals mutually adjusted for all the covariates in the table plus center, duration (years) of smoking and energy intake. Coronary heart diseases (includes angor and myocardial infarction). Body mass index (kg/m2): lean, BMI ⬍ 20.0; normal, BMI 20.0–24.9; overweight, BMI 25.0–29.9; obese: BMI ⭓ 30.0. The p-value for linear trend was calculated coding the categories according to the natural order (lean, normal, overweight, obese). d Alcohol consumption: among women, the RR and 95% CI reported for the category 20.1–40.0 g/day actually correspond to consumption of ⬎20.0 g/day. b c
person-years. The data concerning relapse are scarce: a study in male former smokers aged 54 years or older followed for 6 years (24) reported an annual relapse rate of 29 per thousand; another cohort (25) with 2-year follow-up observed a rate of about 40 per 1000 person-years for both sexes combined. Only one study (19) over a 10-year follow-up of subjects aged 18 to 35 years reported initiation rates for white men and women of 5.2 and 3.6 per thousand, respectively. Regarding factors associated with changes in smoking behavior, most studies found that heavier smokers (10, 17, 18, 21–23) and less educated people (10, 17, 20, 22, 23) are less likely to quit. A decrease in cessation rate associated with alcohol consumption has been often reported as well
(10, 17, 22). We observed a similar pattern, although a strong association with education was restricted to women. Among men, higher cessation was associated with physical activity, as was found in a Danish study (10), and with antecedents of CHD, as was observed in the Framingham study (21). We did not find any association between cessation and BMI in women, while lean men (BMI⬍20) were more prone to quit. Although men with obesity or overweight tended to have increased cessation rates there were no significant differences as compared with those with normal BMI. Only one study (22) showed a linear increase of cessation with BMI. Although weight concern, mainly among young women, might prevent them from attempting
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TABLE 3. Factors associated with smoking relapse among former smokers in the EPIC-Spain cohort (1992–96 to 1996–99) Men RR Age group (reference: 35–44 years)
Body mass indexb (reference: normal weight)
Alcohol consumptionc (reference: non-consumer)
Coffee consumption (reference: ⭐50.0 ml/day)
Years since quitting (reference: ⬍ 2 years)
Packyears smokedd (reference: ⭐5.0)
Fruit intake (reference: quartile 1)
45–54 years 55–64 years linear trend Lean Overweight Obese linear trend ⭐10.0 g/day 10.1–20.0 g/day 20.1–40.0 g/day 40.1–60.0 g/day ⬎60 g/day linear trend 50.1–100.0 ml/day 100.1–200.0 ml/day ⬎200 ml/day linear trend 2–5 years 6–10 years ⬎10 years linear trend 5.1–10.0 packyears 10.1–20.0 packyears 20.1–30.0 packyears ⬎30 packyears linear trend Quartile 2 Quartile 3 Quartile 4 linear trend
a
Women 95% CI
a
1.06 0.90 p ⫽ 0.76
0.85, 1.33 0.69, 1.17
0.96 1.12 p ⫽ 0.37 1.03 1.24 1.03 1.40 1.35 p ⫽ 0.042 1.46 1.25 1.13 p ⫽ 0.30 0.30 0.16 0.10 p ⬍ 0.001 0.73 0.60 0.50 0.49 p ⬍ 0.001 0.98 0.95 0.76 p ⫽ 0.06
0.70, 1.31 0.80, 1.56 0.71, 0.84, 0.71, 0.95, 0.90,
1.48 1.83 1.49 2.05 2.01
1.11, 1.90 0.97, 1.62 0.85, 1.50 0.23, 0.38 0.12, 0.21 0.07, 0.13 0.50, 0.43, 0.35, 0.35,
1.07 0.85 0.71 0.70
0.76, 1.27 0.73, 1.23 0.57, 1.01
RR
a
0.93 0.82 p ⫽ 0.43 0.88 1.14 1.18 p ⫽ 0.19 1.19 1.32 1.40
p ⫽ 0.10 1.43 1.17 1.38 p ⫽ 0.14 0.35 0.17 0.08 p ⬍ 0.001 0.99 0.79 0.93 0.69 p ⫽ 0.11 0.94 0.79 0.86 p ⫽ 0.22
95% CIa 0.71, 1.23 0.47, 1.43 0.28, 2.79 0.89, 1.47 0.85, 1.64 0.91, 1.56 0.88, 1.98 0.91, 2.14
0.94, 2.18 0.80, 1.71 0.96, 1.98 0.27, 0.45 0.12, 0.24 0.05, 0.12 0.73, 0.59, 0.63, 0.37,
1.35 1.08 1.38 1.29
0.69, 1.28 0.57, 1.09 0.62, 1.19
a
Rate ratios and 95% confidence intervals mutually adjusted for all the covariates in the table plus center and energy intake. Body mass index (kg/m2): lean, BMI ⬍ 20.0; normal, BMI 20.0–24.9; overweight, BMI 25.0–29.9; obese: BMI ⭓ 30.0. The RR could not be estimated for the lean category among men because of small number of subjects. The p-value for linear trend was calculated coding the categories according to the natural order (lean, normal, overweight, obese). c Alcohol consumption: among women, the RR and 95% CI reported for the category 20.1–40.0 g/day actually correspond to consumption of ⬎20.0 g/day. d Cumulative exposure (cigarettes smoked) during the time that these subjects smoked. b
to quit, that concern does not appear to affect cessation success (26). High levels of alcohol consumption and of cholesterol intake were associated with lower cessation rates among men. Time since quitting is an excellent predictor of long-term abstinence (25). We also found that the amount smoked is inversely related with relapse; this suggests that heavy smokers are less likely to quit, but once they stop they tend to remain abstainers. High alcohol and coffee consumption have been reported as predictors of late smoking relapse in men (24); we observed a trend of increased relapse with alcohol consumption in men, but no association with coffee. Finally, the only study (22) that dealt with initiation reported an inverse association with education and income; in our study the inverse association was limited to men, while more educated women were more likely to initiate smoking. We are not aware of other reports showing an association of starting to smoke during adulthood with OC use and alcohol consumption.
In Spain, cross-sectional data from the National Health Survey (27) used the ratio between former and ever smokers as a surrogate for cessation and the ratio between ever and never smokers as a surrogate for initiation. Cessation was inversely associated with alcohol and positively associated with age, practicing sports, and antecedents of heart diseases, while initiation showed the opposite pattern. Association with educational level was investigated in the Catalan Health Survey (28) using the same approach. More educated women were more likely to quit but no association was seen among men, while initiation rates decreased with education in men but increased with education level among women. We have shown rates and analysis of factors associated with changes in smoking behaviors separately for men and women, however, there appear to be important gender differences. In our study men had higher cessation and initiation rates, and lower relapse rates. On the other hand, while characteristics of the smoking habits and alcohol consumption were the main factors associated with changes in
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TABLE 4. Factors associated with smoking initiation among never smokers in the EPIC-Spain cohort (1992–96 to 1996–99) Men RR Age group (reference: 35–44 years)
Education level (reference: primary not completed)
Work activity (reference: sedentary) Leisure or sports activity (hours/week) (reference: ⭐1 h/w)
Ever used oral contraceptives Alcohol consumptionb (reference: non-consumer)
a
Women 95% CI
a
45–54 years 55–64 years linear trend Primary school Secondary school University Standing Manual/heavy 1.1–7.0 hours/week 7.1–14.0 hours/week ⬎14 hours/week linear trend
0.88 0.76 p ⫽ 0.20 0.83 0.90 0.31 0.99 1.16 0.52 0.57 0.68 p ⫽ 1.00
0.60, 1.30 0.48, 1.19 0.57, 0.56, 0.14, 0.66, 0.76, 0.29, 0.32, 0.39,
1.22 1.44 0.69 1.49 1.75 0.92 1.00 1.18
⭐10.0 g/day 10.1–20.0 g/day 20.1–40.0 g/day 40.1–60.0 g/day ⬎60 g/day linear trend
1.58 1.46 2.37 2.65 3.48 p ⬍ 0.001
0.77, 0.65, 1.17, 1.26, 1.67,
3.25 3.27 4.81 5.54 7.25
a
RR
95% CIa
0.32 0.12 p ⬍ 0.001 1.50 2.85 1.83 1.67 2.25 0.60 0.41 0.73 p ⫽ 0.55 1.74 1.06 1.20 2.34
0.21, 0.50 0.05, 0.27 0.93, 1.56, 0.86, 0.87, 0.70, 0.33, 0.21, 0.38,
2.41 5.19 3.88 3.20 7.27 1.09 0.80 1.41
1.18, 0.69, 0.59, 1.24,
2.57 1.63 2.44 4.43
p ⫽ 0.024
a
Rate ratios and 95% confidence intervals mutually adjusted for all the covariates in the table plus center and energy intake. b Alcohol consumption: among women, the RR and 95% CI reported for the category 20.1–40.0 g/day actually correspond to consumption of ⬎20.0 g/day.
smoking behaviors among men, sociodemographic factors such as age and educational level dominate in women. Although age could hardly be considered a confounder of gender differences since these were consistent across all age groups (Figure 1), we formally tested differences of rates between men and women adjusted by age and educational level (results not shown). The differences were significant for every type of change (cessation, relapse, initiation), with the same pattern observed for crude rates. Gender differences in our population can be more easily interpreted by considering men and women in different stages of smoking behavior, consistent with stages of tobacco epidemic (29). Among men, increasing cessation and decreasing relapse tend to produce a higher prevalence of former smokers, typical of stage III, in which smoking is changing from being socially acceptable to a socially abnormal behavior. In this phase smoking prevalence in women shows a plateau or initiates a slight decline; consistent with our results, there is likely to be a marked age gradient, and more educated people lead changes in smoking behavior, as is the case in other health-related factors. In the interpretation of our results some issues must be considered. We studied healthy adults, and there were no specific programs to reduce tobacco use in the populations where they were recruited. The cohort was not designed to be representative of the adult Spanish population. However, it was recruited in five different regions and included a wide range of individuals from different educational levels, residents in rural and urban areas with different degree of industrialization; only the two extremes of very rich and
very poor people are underrepresented. Smoking prevalence in our study was similar with the prevalence of smoking in the Spanish adult population: in our sample, 27.1% of subjects were current smokers at recruitment, 16.2% were former smokers, and 56.7% had never smoked; the corresponding prevalences in the National Health Survey in Spain 1997 (30) in the age group 45 to 64 years were 27.5%, 18.1%, and 54.3%, respectively. On the other hand, classification of smoking status in or study was based upon regular smoking of any tobacco product (cigarettes, cigars, and pipe). Although smoking is often defined based on cigarette consumption, it must be recalled that, as it has been recently pointed out, all tobacco products, not just cigarettes, have devastating effects on health (9). The follow-up was complete for 98.2% of the cohort; although subjects lost to follow-up might be different regarding the likelihood of changing smoking behavior this would hardly affect the results given the low proportion of losses. A few subjects below age 35 or above age 64 were included in the cohort; given the small number, these were not included in the analysis in order to provide rates for an age group (35–64 years) well characterized in most routinely reported population data. Nevertheless, given the small proportion of such individuals (1.7%), this was not likely to have a major impact on the results. Concerning the exclusion of 4.3% subjects with inconsistent information, such discrepancies are in fact within the range of expected errors. Comparison of smoking status in self- and interviewer-administered questionnaires, or based on a screening or detailed interview produced discrepancies of
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4.5% and 3.9%, respectively (31). We followed subjects for 3 years; in intervention studies most attempts to quit occur during the first year but up to 5 or 10 years are needed to estimate sustained changes. We assumed constant rates of changes during follow-up, so that the estimates reported are average rates over 3 years; given the relatively short period, estimation of the average rate seems acceptable. In our population about 5% of men and 4% of women who currently smoke stop smoking every year; this is partially counterbalanced by the relatively similar rates of relapse of former smokers, mainly among women. Furthermore, there is still a low but non-negligible rate of smoking initiation in adults, especially among men. The net balance is positive but rather poor: the smoking prevalence among men in a 3-year period decreased from 41.4% to 38.7%, which results in 0.9% decrease per year. Among women the reduction in the absolute difference of the smoking prevalence was only 0.45%, or 0.15% per year. Our data suggest that additional efforts should be made in Spain to reduce tobacco burden. Comprehensive strategies to promote cessation and decrease initiation must follow evidence-based effective recommendations (32), within the framework of general smoking control policies.
REFERENCES 1. World Health Organization. The World Health Report, 2002. Reducing Risks, Promoting Healthy Life. Geneva (Switzerland): World Health Organization; 2002. 2. Vainio H, Weiderpass E, Kleihues P. Smoking cessation in cancer prevention. Toxicology. 2001;166:47–52. 3. Centers for Disease Control and Prevention. Annual smoking-attributable mortality and years of potential life lost, and economic costs–United States, 1995–1999. MMWR Morb Mortal Wkly Rep. 2002;51:300–303. 4. Kiiskinen U, Vartiainen E, Puska P, Pekurinen M. Smoking-related costs among 25- to 59-year-old males in a 19-year individual follow-up. Eur J Public Health. 2002;12:145–151. 5. Molarius A, Parsons RW, Dobson AJ, Evans A, Fortmann SP, Jamrozik K, et al. Trends in cigarette smoking in 36 populations from the early 1980s to the mid-1990s: findings from the WHO MONICA Project. Am J Public Health. 2001;91:206–212. 6. Regidor E, Gutierrez-Fisac JL, Calle ME, Navarro P, Domı´nguez V. Trends in cigarette smoking in Spain by social class. Prev Med. 2001;33:241–248. 7. Taylor DH, Hasselblad V, Henley SJ, Thun MJ, Sloan FA. Benefits of smoking cessation for longevity. Am J Public Health. 2002;92:990–996. 8. Nusselder WJ, Looman CWN, Marang-van de Mheen PJ, van de Mheen H, Mackenbach JP. Smoking and the compression of morbidity. J Epidemiol Community Health. 2000;54:566–574. 9. The Tobacco Use and Dependence Clinical Practice Guideline Panel, Staff, and Consortium Representatives. A clinical practice guideline for treating tobacco use and dependence: A US Public Health Service report (Consensus Statement). JAMA. 2000;283:3244–3254. 10. Osler M, Prescott E. Psychosocial, behavioural, and health determinants of successful smoking cessation: a longitudinal study of Danish adults. Tob Control. 1998;7:262–267. 11. EPIC Group of Spain. Relative validity and reproducibility of a diet history questionnaire in Spain. I. Foods. Int J Epidemiol. 1997;26(suppl. 1):91–99.
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12. Slimani N, Farran A, Torrent M, Farriol N, Moreno I, He´mon B, et al. European Prospective Investigation into Cancer and Nutrition (EPIC): Food Composition Tables – Spain. 2nd ed. Lyon: International Agency for Research on Cancer (IARC); 1996. 13. Breslow NE, Day NE. Statistical Methods in Cancer Research. Volume II: The design and analysis of cohort studies. IARC Scientific publications No. 82. Lyon (France): International Agency for Research on Cancer; 1987. 14. Martuzzi M, Elliott P. Estimating the incidence rate ratio in cross-sectional studies using a simple alternative to logistic regression. Ann Epidemiol. 1998;8:52–55. 15. Carlin JB, Wolfe R, Coffey C, Patton GC. Analysis of binary outcomes in longitudinal studies using weighted estimating equations and discrete-time survival methods: prevalence and incidence of smoking in an adolescent cohort. Stat Med. 1999;18:2655–2679. 16. Willet WC. Nutritional Epidemiology. 2nd ed. New York: Oxford University Press; 1998. 17. Hymowitz N, Cummings KM, Hyland A, Lynn WR, Pechacek TF, Hartwell TD. Predictors of smoking cessation in a cohort of adult smokers followed for five years. Tob Control. 1997;6(suppl. 2):57–62. 18. The COMMIT Research Group. Community Intervention Trial for Smoking Cessation (COMMIT): I. Cohort results from a four-year community intervention. Am J Public Health. 1995;85:183–192. 19. Kiefe CI, Williams OD, Lewis CE, Allison JJ, Sekar P, Wagenknecht LE. Ten-year changes in smoking among young adults: are racial differences explained by socioeconomic factors in the CARDIA study? Am J Public Health. 2001;91:213–218. 20. Nordstrom BL, Kinnunen T, Utman CH, Krall EA, Vokonas PS, Garvey AJ. Predictors of continued smoking over 25 years of follow-up in the normative aging study. Am J Public Health. 2000;90:404–406. 21. Freund KM, D’Agostino RB, Belanger AJ, Kannel WB, Stokes J III. Predictors of smoking cessation: the Framingham Study. Am J Epidemiol. 1992;135:957–964. 22. Osler M, Prescott E, Godtfredsen N, Hein HO, Schnohr P. Gender and determinants of smoking cessation: a longitudinal study. Prev Med. 1999;29:57–62. 23. Monso E, Campbell J, Tonnesen P, Gustavsson G, Morera J. Sociodemographic predictors of success in smoking intervention. Tob Control. 2001;10:165–169. 24. Krall EA, Garvey AJ, Garcia RI. Smoking relapse after 2 years of abstinence: findings from the VA Normative Aging Study. Nicotine Tob Res. 2002;4:95–100. 25. Gilpin EA, Pierce JP, Farkas AJ. Duration of smoking abstinence and success in quitting. J Natl Cancer Inst. 1997;89:572–576. 26. U.S. Department of Health and Human Services. Reducing Tobacco Use: A Report of the Surgeon General. Atlanta, Georgia: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention, and Health Promotion, Office on Smoking and Health; 2000. 27. Pinilla J, Gonzalez B. Profile of the population of Spain with respect to the smoking habit, period 1993–1997. Eur J Public Health. 2001;11:346–351. 28. Fernandez E, Garcia M, Schiaffino A, Borras JM, Nebot M, Segura A. Smoking initiation and cessation by gender and educational level in Catalonia, Spain. Prev Med. 2001;32:218–223. 29. Lopez AD, Collishaw, Piha T. A descriptive model of the cigarette epidemic in developed countries. Tob Control. 1994;3:242–247. 30. Ministerio de Sanidad y Consumo. Encuesta Nacional de Salud, 1997. Madrid (Spain): Ministerio de Sanidad y Consumo; 1999. 31. Brittingham A, Tourangeau R, Kay W. Reports of smoking in a national Survey: data from screening and detailed interviews, and from self- and interviewer-administered questions. Ann Epidemiol. 1998;8:393–401. 32. Task Force on Community Preventive Services. Recommendations regarding interventions to reduce tobacco use and exposure to environmental tobacco smoke. Am J Prev Med. 2001;20(2S):10–15.
PURPOSE: We assessed changes in smoking behavior and its related factors among healthy adults from five regions in Spain. METHODS: The smoking status at recruitment and after 3 years was compared in 14,288 men and 23,983 women aged 35 to 64 years. The pattern of smoking and several lifestyle factors were investigated as potential predictors of subsequent changes in smoking habits. RESULTS: Among current smokers at baseline the age-adjusted rates of cessation per 1000 person-years were 57.4 for men and 43.2 for women. Among former smokers at baseline the relapse rates were 37.6 and 48.8 per 1000 person-years for men and women, respectively. The initiation rate per 1000 personyears among men who had never smoked was 12.5 and 2.7 for women. Higher amount currently smoked and longer time since quitting were strong predictors of lower rates of cessation and relapse, respectively, while age was associated with lower initiation rates in women. Increased alcohol consumption was related to low cessation and high relapse and initiation rates, mainly among men, while more educated women had higher cessation and initiation rates. CONCLUSIONS: The current pattern of changes in smoking behavior in Spanish populations aged 35 to 64 years results in rather small prevalence reduction. Additional efforts should be made to promote successful cessation and prevent initiation to reduce the tobacco burden in Spain. Ann Epidemiol 2004;14:235–243. 쑕 2003 Elsevier Inc. All rights reserved. KEY WORDS:
Tobacco, Smoke, Smoking Cessation, Cohort Studies, Epidemiologic Factors, Life Style,
Adult.
INTRODUCTION Cigarette smoking is the most important cause of premature death in developed countries, and is emerging as a major
From the Unit of Epidemiology, Catalan Institute of Oncology, L’Hospitalet de Llobregat (Barcelona), Spain (A.A., G.P., A.B., C.A.G.); Escuela Andaluza de Salud Pu´blica, Granada, Spain (M.R., C.M.); Consejerı´a de Sanidad y Servicios Sociales de Asturias, Oviedo, Spain (J.R.Q., A.F.); Servicio de Epidemiologı´a, Consejerı´a de Sanidad y Consumo, Murcia, Spain (C.N., M.D.C., M.J.T.); Direccio´n de Salud de Guipu´zcoa, San Sebastia´n, Spain (N.L., M.D., P.A.); and Instituto de Salud Pu´blica, Departamento de Salud de Navarra, Pamplona, Spain (A.B, E.A.). Address correspondence and reprint requests to: Antonio Agudo, M.D., M.Sc., Unit of Epidemiology, Catalan Institute of Oncology, Av. Gran Via s/n km 2.7, L’Hospitalet de Llobregat 08907, Spain. Tel.: ⫹34-93260-7401; Fax: ⫹34-93-260-7787. E-mail: [email protected] The EPIC Study is coordinated by the Unit of Nutrition and Cancer of the International Agency for Research on Cancer (IARC), Agreement AEP/93/02. In Spain it receives financial support from the ““Europe Against Cancer Program”” of the European Union (Agreement SO 97 200302 05F02), the Health Research Fund (FIS) of the Spanish Ministry of Health (Exp. 96-0032), and participating Regional Governments. Received November 4, 2002; accepted May 9, 2003. 쑕 2003 Elsevier Inc. All rights reserved. 360 Park Avenue South, New York, NY 10010
public health concern in developing countries (1, 2). The estimated annual average of premature deaths due to smoking in the United States (1995–1999) was 440,000 (3). The years of potential life lost were on average 13.2 and 14.5 for adult male and female smokers, respectively, and the economic costs of smoking totaled $3391 per smoker per year. In Finland the estimated yearly costs induced by smoking in men aged 25 to 50 years were V3647 per smoker, almost 60% of which were due to premature deaths (4). In most adult populations in western Europe the smoking prevalence in men declined from the early 1980s to the mid1990s; smoking among women tended to increase in populations with low initial prevalence, such as southern and some eastern countries (5). In Spain the prevalence of current smokers in men aged 45 to 64 years decreased from 54% to 44% in 10 years (1987–1997), while there was a striking increase (5% to 13%) among women in the same age group (6). The number of deaths due to smoking can only be reduced if a substantial proportion of adults who currently smoke quit. Even those smokers who quit at age 65 have an increase in life expectancy relative to those who continued to smoke (7). Furthermore, cessation reduces the risk 1047-2797/04/$–see front matter doi:10.1016/S1047-2797(03)00245-X
236 Agudo et al.
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Selected Abbreviations and Acronyms BMI ⫽ body mass index CI ⫽ confidence interval CHD ⫽ coronary heart disease EPIC ⫽ European Prospective Investigation into Cancer and Nutrition OC ⫽ oral contraceptives RR ⫽ rate ratio
and slows progression of tobacco-related diseases, and leads to a compression of morbidity and improvement in quality of life (8). However, many people continue to smoke despite knowing about the health consequences of tobacco, and many who try to quit fail. Approximately one third of smokers try to stop smoking each year, and fewer than one out of ten smokers who attempt to quit on their own are successful in the long run (9). Although the main obstacle to quitting is the addictive nature of nicotine, tobacco use involves complex determinants, and successful cessation or relapse is also related to social and lifestyle factors. Changes in prevalence have not been uniform across sociodemographic groups (6). Furthermore, there is evidence that apart from smoking behavior characteristics and level of motivation, certain socioeconomic and lifestyle factors are consistently related with adopting and maintaining the habit of smoking (10). Assessment of overall changes in smoking has rarely been approached, probably because cessation is the most relevant factor for adults, while initiation does mainly concern young people. On the other hand, analyses of changes in smoking behavior over time are often based upon cross-sectional samples of a population rather than true longitudinal followup. The present article deals with changes in smoking habits over a 3-year period in healthy adults from five regions in Spain. We present cessation, relapse, and initiation rates, as well as their association with demographic and lifestyle factors.
METHODS Subjects The European Prospective Investigation into Cancer and Nutrition (EPIC) is a large cohort study that is being carried out in ten European countries. In Spain it includes 41,446 subjects (15,634 men and 25,812 women) aged 29 to 69 years, recruited between 1992 and 1996. They were healthy volunteers, mainly blood donors, from five regions of Spain: three from the north (Asturias, Guipu´zcoa, and Navarra), and two from the south (Murcia and Granada). The participation rate varied from 50% to 60% across centers. Each subject provided information on dietary habits and other lifestyle factors; anthropometric measurements
and blood sample collection were also taken at the time of inclusion. Smoking Habits at Recruitment The information on smoking habits was collected by means of personal interview together with other lifestyle factors. Individuals were asked to classify themselves according to smoking status: a current smoker was defined as any person who smoked regularly (at least one cigarette per day and/ or one cigar or one pipe per week) at the time of the interview. Subjects who had smoked at least one cigarette per day and/or one cigar or one pipe per week in the past were classified as former smokers. Never smokers were those who had never smoked any tobacco product regularly. Current smokers of cigarettes provided information about the number of cigarettes smoked per day and how deeply they inhale the smoke, as well as characteristics of the cigarettes: blond or dark, with or without filter, light or normal. For both current and former cigarette smokers, the age at starting and some characteristics of the behavior in the past were collected: average number of cigarettes daily smoked, use of filter, type of tobacco (blond or dark). Former smokers were also asked about the age at which they quit. Details about the habit of smoking cigars or pipes were only collected among men. Lifestyle Factors and Anthropometric Measurements Education was categorized into four levels, from uncompleted primary school to any schooling at the university level or beyond. The current job was classified into sedentary, standing, manual, and heavy manual work. The time spent in leisure or sport activities was computed as the sum of the mean number of hours per week during the last year practicing hobbies and sports, walking, cycling, and gardening. Subjects were asked whether they had been diagnosed and treated for any major chronic conditions, including cancer and coronary heart diseases (CHD). Women were also asked if they had ever used oral contraceptives (OC). The information on habitual food intake over the previous year was gathered using a computerized version of the diet history method previously validated (11). For every food item, including alcoholic beverages, the frequency of consumption and the portion size were reported and then used to estimate the daily consumption in grams. Energy intake, cholesterol and alcohol consumption were estimated using a food composition table especially compiled for the EPIC study in Spain (12). Height was measured using a movable stadiometer and weight was measured after urination, using an electronic weighting machine. Subjects were classified according to the body mass index (BMI) as follows: ⬍20.0 kg/ m2, “lean”; 20.0–24.9, “normal”; 25.0–29.9, “overweight”; and BMI ⭓ 30.0, “obese”.
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Follow-up Cohort members were contacted by telephone approximately 3 years after recruitment, to obtain information about vital status, occurrence of major diseases, and some aspects of lifestyle. Regarding smoking habits, the participants must report whether they currently smoked cigarettes or had smoked cigarettes in the past, and the number of cigarettes smoked per day. The same questions were asked separately for cigars and pipes. The criteria to be classified as current or former smokers were the same used at recruitment: smoking (now or in the past) at least one cigarette per day and/ or one cigar or one pipe per week. A total of 691 subjects out of 41,446 (1.7%) could not be contacted: 228 had died, 200 refused, and 263 could not be located. Another 38 subjects had no information about smoking and 1754 individuals had inconsistencies between reported smoking status at recruitment and at follow-up (for instance, subjects initially self-reported as current or former smokers that declared afterwards that they had never smoked): all of them, as well as 692 subjects with age at recruitment below 35 or above 64 years were excluded. Thus, the final dataset for analysis of smoking behavior consisted of 38,271 subjects, 14,288 males and 23,983 females. Data Analysis All the analyses were carried out separately among men and women. Rates of cessation, relapse, and initiation were estimated among current, former, and never smokers, respectively, at recruitment, from the number of events (subjects who quit, resumed, or started to smoke, respectively) and the population-time at risk. The time at risk was computed as the number of days elapsed from the date of recruitment until the date of the follow-up. Since the exact time of changes was not recorded, the time at risk was halved for subjects reporting any change in their smoking habits during follow-up. The rates and corresponding 95% confidence interval (CI) are given per 1000 person-years standardized by the direct method (13) using as weights the age structure of the Spanish population. To facilitate external comparisons the rates were also standardized by age according to the world standard population. To assess the effect of factors potentially associated with the occurrence of a change in the smoking behavior over time, we fitted a generalized linear model using the complementary log-log function (14, 15). The time of follow-up was accounted for by specifying its logarithm as an offset in the model. It is assumed that events occur only once and the rate is constant during the follow-up period. The model provides for each covariate a parameter (and 95% CI) that estimates the effect of a unit change of the covariate in the rate measured in the log-scale; thus exponentiation of the parameter estimates the rate ratio (RR) associated with
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237
this covariate. All factors were categorized and introduced into the model as dummy variables, so RRs were estimated for each category compared to a reference. The linear trend was tested by significance of the regression parameter of a variable coding the levels of increasing exposure in ordinal integers. To build a multivariate model for each type of change in smoking status we included all significant factors in at least one of the two genders in the univariate analysis (results not shown), as well as those factors supposed to have some effect based on previous studies: age, education, alcohol consumption, and characteristics of the smoking behavior. In addition to all the variables included in each model, the estimates were always adjusted by center. Furthermore, in order to address the effect of dietary composition as well as to control for measurement error, the estimates of dietary factors were always adjusted for total energy intake (16).
RESULTS The population studied consisted of three sets of subjects defined by their smoking status at recruitment (Table 1): 10,379 current smokers (5917 men and 4462 women), 6204 former smokers (4197 men and 2007 women), and 21,688 never smokers (4174 men and 17514 women). The age distribution is similar for men and women who never smoked, while women who were either current or former smokers tended to concentrate in the 35 to 44 years age group. Men had a higher proportion than women working in manual or heavy manual occupations, and they spent more time doing sports or other leisure activities, independent of their smoking status. The prevalence of obesity among current and former smokers is higher in men, while a higher proportion of obese women was observed among never smokers. However, the opposite pattern is seen for overweight. More than six out of ten women who were current smokers or had smoked in the past had used oral contraceptives during their lifetime, while only one third of never smokers had done so. Women consumed more coffee, while men tended to consume more alcohol. Among smokers (current and former), males had higher cigarette consumption. The cessation rates per 1000 person-years age-adjusted according to the Spanish population were 57.4(54-61) for men and 43.2(38-49) for women; the corresponding rates for relapse were 37.6(34-41) and 48.8(42-56), and 12.5(1115) and 2.7(2.2-3.2) for initiation. Standardization by Spanish population produced eventually the same values. As can be seen in the Figure 1 cessation sharply increases among the oldest group (55–64 years) in both sexes, while relapse has a consistent linear decrease with age; initiation is constant across age groups among men but decreases with age among women.
TABLE 1. Selected characteristics of subjects from the EPIC-Spain cohort 1992–96, according to their smoking status at recruitment (current, former, and never smokers) Current smokers
Center (province) Asturias Guipu´zcoa Navarra Murcia Granada Age group 35–44 years 45–54 years 55–64 years Education levela Primary not completed Primary school Secondary school University or technical Work activitya Sedentary Standing Manual, heavy manual Sports/leisure activity ⭐1 hour/week 1.1–7.0 hours/week 7.1–14.0 hours/week ⬎14 hours/week Body mass indexa,b Lean Normal Overweight Obese Antecedents of CHDa,c Antecedents of cancera Ever used OCa,d Alcohol consumptione Non consumer ⭐10.0 g/day 10.1–20.0 g/day 20.1–40.0 g/day 40.1–60.0 g/day ⬎60 g/day Coffee consumption ⭐50.0 ml/day 50.1–100.0 ml/day 100.1–200.0 ml/day ⬎200 ml/day Cigarette smokinga,f 1–10 cigarettes/day 11–20 cigarettes/day 21–30 cigarettes/day ⬎30 cigarettes/day Overall consumption of cigars and/or pipes Exclusive smokers of cigars and/or pipes Time since quitting smoking cigarettesa ⬍2 years 2–5 years 6–10 years ⬎10 years
Former smokers
Never smokers
Men (n ⫽ 5917) %
Women (n ⫽ 4462) %
Men (n ⫽ 4197) %
Women (n ⫽ 2007) %
Men (n ⫽ 4174) %
Women (n ⫽ 17,514) %
18.6 28.0 28.3 16.5 8.7
24.4 15.8 19.3 21.9 18.6
22.7 22.1 19.0 21.6 14.6
23.3 22.6 17.2 19.2 17.7
19.2 28.5 27.3 14.4 10.6
20.0 16.3 15.7 23.3 24.8
28.9 46.1 25.0
70.5 24.5 5.1
26.5 42.2 31.3
67.7 26.4 5.9
25.0 42.3 32.7
26.6 41.8 31.6
25.7 40.1 21.4 12.7
19.5 43.0 20.2 17.3
25.4 33.8 23.0 17.7
14.1 38.3 22.9 24.7
27.2 38.2 18.9 15.7
48.0 39.6 6.9 5.5
36.0 34.5 29.5
21.5 76.6 1.9
39.3 36.1 24.6
24.6 73.6 1.8
33.8 35.4 30.8
9.5 88.3 2.2
9.1 31.2 28.3 31.5
9.9 43.1 29.9 17.1
5.5 28.3 29.3 37.0
7.7 37.9 34.6 19.8
6.2 28.5 29.7 35.6
8.0 43.9 30.7 17.4
0.3 15.1 55.5 29.1 1.3 0.4 –
2.1 44.5 38.7 14.8 0.5 1.3 62.9
0.1 10.9 57.6 31.4 3.8 0.6 –
1.5 44.5 38.0 16.1 0.6 1.1 61.8
0.1 13.6 60.1 26.2 1.2 0.3 –
0.5 19.4 43.3 36.8 1.6 1.1 34.3
9.4 17.6 12.3 21.8 16.7 22.2
34.8 41.5 12.5 11.2
12.5 22.0 14.0 22.1 14.7 14.7
34.9 45.7 10.0 9.4
13.2 26.1 14.0 21.1 13.3 12.2
44.3 41.4 8.5 5.7
23.9 20.8 30.5 24.8
13.1 13.4 28.6 44.9
32.6 19.5 27.4 20.6
16.3 13.5 29.4 40.8
39.9 20.2 24.3 15.6
31.4 15.8 24.2 28.6
35.7 41.9 13.5 8.9 41.8 22.6
47.6 42.8 6.3 3.4 0.2 0.2
24.1 42.4 19.4 14.1 32.4 2.8
52.6 36.8 7.5 3.1 – –
13.7 22.1 25.5 38.7
19.6 27.3 22.9 30.1
a The percents reported are calculated over the number of subjects with valid information; the number of subjects (men ⫹ women) with missing information were as follows: education: 56 (29 ⫹ 27) current smokers, 38 (24 ⫹ 14) former smokers, and 158 (20 ⫹ 138) never smokers; type of work: 367 (267 ⫹ 98) current smokers, 237 (202 ⫹ 35) former smokers, and 686 (162 ⫹ 524) never smokers; body mass index: 30 (19 ⫹ 11) current smokers, 23 (18 ⫹ 5) former smokers, and 46 (11 ⫹ 35) never smokers; antecedents of CHD: 6 (2 ⫹ 4) current smokers, 6 (5 ⫹ 1) former smokers, and 18 (4 ⫹ 14) never smokers; antecedents of cancer: 47 (23 ⫹ 24) current smokers, 36 (27 ⫹ 9) former smokers, and 116 (17 ⫹ 99) never smokers; use of OC: 5 current smokers, 3 former smokers, and 21 never smokers; cigarette smoking: 1356 (1348 ⫹ 8) current smokers, and 212 (179 ⫹ 3) former smokers; years since quitting: 255 (242 ⫹ 13) former smokers. The high number of missing cigarette smoking and time since quitting is mainly due to men who smoked cigars and/or pipes exclusively. b Body mass index (kg/m2): lean, BMI ⬍ 20.0; normal, BMI 20.0–24.9; overweight, BMI 25.0–29.9; obese: BMI ⭓ 30.0. c Coronary heart diseases (includes angor and myocardial infarction). d Oral contraceptives. e Alcohol consumption: among women, the percent reported for the category 20.1–40.0 g/day actually corresponds to consumption of ⬎20.0 g/day. f Cigarette smoking: for current smokers the amount reported corresponds to current consumption at recruitment; for former smokers it corresponds to the average daily number of cigarettes smoked during the period when subjects smoked.
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The multivariate model for predictors of cessation among current smokers is shown in Table 2. Smoking cessation was positively associated with education in women; among men a higher rate of quitting was associated with high physical activity, antecedents of CHD, and low BMI, while high alcohol consumption and high cholesterol intake were predictors of low cessation rate. There was a consistent inverse association of cessation with the amount of cigarettes currently smoked in both sexes. The time elapsed since quitting was the strongest predictor of relapse among men and women former smokers (Table 3). The risk of relapse smoking after 2 years of abstinence was substantially reduced as compared with recent quitters (less than 2 years), and became very low among those who quit more than 10 years ago. On the other hand, the lifetime cigarette consumption was inversely related to relapse, heavier smokers being less likely to restart smoking once they had quit. There was a trend toward increased relapse associated with high alcohol consumption and low fruit intake, although no significant terms were observed for any category of consumption. The amount of cigarettes smoked per day and the number of packyears were predictors of cessation and relapse, respectively, due to which these variables were included in the final multivariate model and, therefore, subjects classified as current or former smokers at recruitment based solely on their cigars and/or pipe use were excluded. This means that the results reported in Tables 2 and 3 actually show the cessation and relapse patterns of daily cigarette smokers. Finally, initiation showed a strong inverse association with age among women and with education level among men (Table 4). High alcohol consumption (both sexes) and use of oral contraceptives (women) appeared to be important predictors of initiation.
DISCUSSION
FIGURE 1. Changes in smoking habits in the EPIC-Spain cohort (1992-96 to 1996-99) by sex and age group. Rates and 95% confidence intervals per 1,000 person-years of cessation, relapse, and initiation.
We have assessed the rates of changes in smoking behavior among healthy adults 35 to 64 years of age in Spain over a 3-year period. Cessation and initiation rates were higher among men while relapse rates were higher in women. Overall, healthy habits such as physical activity at leisure time, low alcohol consumption and cholesterol intake, and high intake of fruits tended to correlate positively with cessation and negatively with relapse and initiation. Comparison with other studies is difficult because age and time of follow-up vary markedly. Several studies in the United States (17–21) and one in Denmark (10, 22) found annual cessation rates ranging from 17 to 43 per thousand; compared to ours, all of them included younger populations with longer follow-up. A multicenter European study among subjects from the placebo group of a trial followed for 1 year (23) found a cessation rate of 99 per 1000
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TABLE 2. Factors associated with smoking cessation among current smokers in the EPIC-Spain cohort (1992–96 to 1996–99) Men RR Age group (reference: 35–44 years)
Education level (reference: primary not completed)
Work activity (reference: sedentary) Leisure or sports activity (hours/week) (reference: ⭐1 h/w)
Antecedents of CHDb Antecedents of cancer Body mass indexc (reference: normal weight)
Alcohol consumptiond (reference: non-consumer)
Coffee consumption (reference: ⭐50.0 ml/day)
Cigarettes per day (reference: 1–10)
Smoked cigars and/or pipes Cholesterol intake (reference: quartile 1)
45–54 years 55–64 years linear trend Primary school Secondary school University Standing Manual/heavy 1.1–7.0 hours/week 7.1–14.0 hours/week ⬎14 hours/week linear trend
Lean Overweight Obese linear trend ⭐10.0 g/day 10.1–20.0 g/day 20.1–40.0 g/day 40.1–60.0 g/day ⬎60 g/day linear trend 50.1–100.0 ml/day 100.1–200.0 ml/day ⬎200 ml/day linear trend 11–20 cigarettes/day 21–30 cigarettes/day ⬎30 cigarettes/day linear trend Quartile 2 Quartile 3 Quartile 4 linear trend
a
1.14 1.31 p ⫽ 0.007 0.91 0.91 1.09 0.98 1.04 1.35 1.27 1.33 p ⫽ 0.31 1.80 1.02 2.69 1.11 1.21 p ⫽ 0.12 0.99 0.79 0.88 0.76 0.75 p ⫽ 0.005 1.02 1.16 1.00 p ⫽ 0.64 0.81 0.69 0.58 p ⬍ 0.001 0.60 0.90 0.92 0.76 p ⫽ 0.038
Women 95% CI
a
0.97, 1.34 1.07, 1.60 0.77, 0.74, 0.86, 0.84, 0.87, 1.03, 0.96, 1.02,
1.08 1.12 1.36 1.14 1.24 1.77 1.67 1.75
1.17, 0.42, 1.17, 0.92, 0.98,
2.76 2.48 6.17 1.34 1.50
0.78, 0.61, 0.69, 0.58, 0.57,
1.25 1.04 1.12 0.99 0.97
0.84, 1.24 0.97, 1.38 0.82, 1.21 0.69, 0.95 0.54, 0.88 0.43, 0.79 0.49, 0.75, 0.75, 0.59,
0.74 1.09 1.12 0.97
a
RR
95% CIa
1.08 1.37 p ⫽ 0.20 1.37 1.57 1.74 0.81 1.21 1.08 1.20 0.93 p ⫽ 0.89 2.00 2.26 1.07 1.05 0.98 p ⫽ 0.99 1.16 0.87 0.85
0.88, 1.34 0.93, 2.02
p ⫽ 0.26 1.00 0.79 0.85 p ⫽ 0.16 0.67 0.62 0.43 p ⬍ 0.001 1.31 1.20 1.30 p ⫽ 0.20
1.05, 1.15, 1.26, 0.66, 0.68, 0.78, 0.86, 0.65,
1.80 2.15 2.40 1.01 2.16 1.48 1.68 1.35
0.87, 1.22, 0.60, 0.87, 0.74,
4.59 4.18 1.91 1.28 1.31
0.95, 1.42 0.64, 1.19 0.61, 1.19
0.73, 1.37 0.59, 1.04 0.65, 1.11 0.56, 0.81 0.41, 0.92 0.23, 0.82
1.01, 1.69 0.91, 1.58 0.93, 1.81
a
Rate ratios and 95% confidence intervals mutually adjusted for all the covariates in the table plus center, duration (years) of smoking and energy intake. Coronary heart diseases (includes angor and myocardial infarction). Body mass index (kg/m2): lean, BMI ⬍ 20.0; normal, BMI 20.0–24.9; overweight, BMI 25.0–29.9; obese: BMI ⭓ 30.0. The p-value for linear trend was calculated coding the categories according to the natural order (lean, normal, overweight, obese). d Alcohol consumption: among women, the RR and 95% CI reported for the category 20.1–40.0 g/day actually correspond to consumption of ⬎20.0 g/day. b c
person-years. The data concerning relapse are scarce: a study in male former smokers aged 54 years or older followed for 6 years (24) reported an annual relapse rate of 29 per thousand; another cohort (25) with 2-year follow-up observed a rate of about 40 per 1000 person-years for both sexes combined. Only one study (19) over a 10-year follow-up of subjects aged 18 to 35 years reported initiation rates for white men and women of 5.2 and 3.6 per thousand, respectively. Regarding factors associated with changes in smoking behavior, most studies found that heavier smokers (10, 17, 18, 21–23) and less educated people (10, 17, 20, 22, 23) are less likely to quit. A decrease in cessation rate associated with alcohol consumption has been often reported as well
(10, 17, 22). We observed a similar pattern, although a strong association with education was restricted to women. Among men, higher cessation was associated with physical activity, as was found in a Danish study (10), and with antecedents of CHD, as was observed in the Framingham study (21). We did not find any association between cessation and BMI in women, while lean men (BMI⬍20) were more prone to quit. Although men with obesity or overweight tended to have increased cessation rates there were no significant differences as compared with those with normal BMI. Only one study (22) showed a linear increase of cessation with BMI. Although weight concern, mainly among young women, might prevent them from attempting
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TABLE 3. Factors associated with smoking relapse among former smokers in the EPIC-Spain cohort (1992–96 to 1996–99) Men RR Age group (reference: 35–44 years)
Body mass indexb (reference: normal weight)
Alcohol consumptionc (reference: non-consumer)
Coffee consumption (reference: ⭐50.0 ml/day)
Years since quitting (reference: ⬍ 2 years)
Packyears smokedd (reference: ⭐5.0)
Fruit intake (reference: quartile 1)
45–54 years 55–64 years linear trend Lean Overweight Obese linear trend ⭐10.0 g/day 10.1–20.0 g/day 20.1–40.0 g/day 40.1–60.0 g/day ⬎60 g/day linear trend 50.1–100.0 ml/day 100.1–200.0 ml/day ⬎200 ml/day linear trend 2–5 years 6–10 years ⬎10 years linear trend 5.1–10.0 packyears 10.1–20.0 packyears 20.1–30.0 packyears ⬎30 packyears linear trend Quartile 2 Quartile 3 Quartile 4 linear trend
a
Women 95% CI
a
1.06 0.90 p ⫽ 0.76
0.85, 1.33 0.69, 1.17
0.96 1.12 p ⫽ 0.37 1.03 1.24 1.03 1.40 1.35 p ⫽ 0.042 1.46 1.25 1.13 p ⫽ 0.30 0.30 0.16 0.10 p ⬍ 0.001 0.73 0.60 0.50 0.49 p ⬍ 0.001 0.98 0.95 0.76 p ⫽ 0.06
0.70, 1.31 0.80, 1.56 0.71, 0.84, 0.71, 0.95, 0.90,
1.48 1.83 1.49 2.05 2.01
1.11, 1.90 0.97, 1.62 0.85, 1.50 0.23, 0.38 0.12, 0.21 0.07, 0.13 0.50, 0.43, 0.35, 0.35,
1.07 0.85 0.71 0.70
0.76, 1.27 0.73, 1.23 0.57, 1.01
RR
a
0.93 0.82 p ⫽ 0.43 0.88 1.14 1.18 p ⫽ 0.19 1.19 1.32 1.40
p ⫽ 0.10 1.43 1.17 1.38 p ⫽ 0.14 0.35 0.17 0.08 p ⬍ 0.001 0.99 0.79 0.93 0.69 p ⫽ 0.11 0.94 0.79 0.86 p ⫽ 0.22
95% CIa 0.71, 1.23 0.47, 1.43 0.28, 2.79 0.89, 1.47 0.85, 1.64 0.91, 1.56 0.88, 1.98 0.91, 2.14
0.94, 2.18 0.80, 1.71 0.96, 1.98 0.27, 0.45 0.12, 0.24 0.05, 0.12 0.73, 0.59, 0.63, 0.37,
1.35 1.08 1.38 1.29
0.69, 1.28 0.57, 1.09 0.62, 1.19
a
Rate ratios and 95% confidence intervals mutually adjusted for all the covariates in the table plus center and energy intake. Body mass index (kg/m2): lean, BMI ⬍ 20.0; normal, BMI 20.0–24.9; overweight, BMI 25.0–29.9; obese: BMI ⭓ 30.0. The RR could not be estimated for the lean category among men because of small number of subjects. The p-value for linear trend was calculated coding the categories according to the natural order (lean, normal, overweight, obese). c Alcohol consumption: among women, the RR and 95% CI reported for the category 20.1–40.0 g/day actually correspond to consumption of ⬎20.0 g/day. d Cumulative exposure (cigarettes smoked) during the time that these subjects smoked. b
to quit, that concern does not appear to affect cessation success (26). High levels of alcohol consumption and of cholesterol intake were associated with lower cessation rates among men. Time since quitting is an excellent predictor of long-term abstinence (25). We also found that the amount smoked is inversely related with relapse; this suggests that heavy smokers are less likely to quit, but once they stop they tend to remain abstainers. High alcohol and coffee consumption have been reported as predictors of late smoking relapse in men (24); we observed a trend of increased relapse with alcohol consumption in men, but no association with coffee. Finally, the only study (22) that dealt with initiation reported an inverse association with education and income; in our study the inverse association was limited to men, while more educated women were more likely to initiate smoking. We are not aware of other reports showing an association of starting to smoke during adulthood with OC use and alcohol consumption.
In Spain, cross-sectional data from the National Health Survey (27) used the ratio between former and ever smokers as a surrogate for cessation and the ratio between ever and never smokers as a surrogate for initiation. Cessation was inversely associated with alcohol and positively associated with age, practicing sports, and antecedents of heart diseases, while initiation showed the opposite pattern. Association with educational level was investigated in the Catalan Health Survey (28) using the same approach. More educated women were more likely to quit but no association was seen among men, while initiation rates decreased with education in men but increased with education level among women. We have shown rates and analysis of factors associated with changes in smoking behaviors separately for men and women, however, there appear to be important gender differences. In our study men had higher cessation and initiation rates, and lower relapse rates. On the other hand, while characteristics of the smoking habits and alcohol consumption were the main factors associated with changes in
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TABLE 4. Factors associated with smoking initiation among never smokers in the EPIC-Spain cohort (1992–96 to 1996–99) Men RR Age group (reference: 35–44 years)
Education level (reference: primary not completed)
Work activity (reference: sedentary) Leisure or sports activity (hours/week) (reference: ⭐1 h/w)
Ever used oral contraceptives Alcohol consumptionb (reference: non-consumer)
a
Women 95% CI
a
45–54 years 55–64 years linear trend Primary school Secondary school University Standing Manual/heavy 1.1–7.0 hours/week 7.1–14.0 hours/week ⬎14 hours/week linear trend
0.88 0.76 p ⫽ 0.20 0.83 0.90 0.31 0.99 1.16 0.52 0.57 0.68 p ⫽ 1.00
0.60, 1.30 0.48, 1.19 0.57, 0.56, 0.14, 0.66, 0.76, 0.29, 0.32, 0.39,
1.22 1.44 0.69 1.49 1.75 0.92 1.00 1.18
⭐10.0 g/day 10.1–20.0 g/day 20.1–40.0 g/day 40.1–60.0 g/day ⬎60 g/day linear trend
1.58 1.46 2.37 2.65 3.48 p ⬍ 0.001
0.77, 0.65, 1.17, 1.26, 1.67,
3.25 3.27 4.81 5.54 7.25
a
RR
95% CIa
0.32 0.12 p ⬍ 0.001 1.50 2.85 1.83 1.67 2.25 0.60 0.41 0.73 p ⫽ 0.55 1.74 1.06 1.20 2.34
0.21, 0.50 0.05, 0.27 0.93, 1.56, 0.86, 0.87, 0.70, 0.33, 0.21, 0.38,
2.41 5.19 3.88 3.20 7.27 1.09 0.80 1.41
1.18, 0.69, 0.59, 1.24,
2.57 1.63 2.44 4.43
p ⫽ 0.024
a
Rate ratios and 95% confidence intervals mutually adjusted for all the covariates in the table plus center and energy intake. b Alcohol consumption: among women, the RR and 95% CI reported for the category 20.1–40.0 g/day actually correspond to consumption of ⬎20.0 g/day.
smoking behaviors among men, sociodemographic factors such as age and educational level dominate in women. Although age could hardly be considered a confounder of gender differences since these were consistent across all age groups (Figure 1), we formally tested differences of rates between men and women adjusted by age and educational level (results not shown). The differences were significant for every type of change (cessation, relapse, initiation), with the same pattern observed for crude rates. Gender differences in our population can be more easily interpreted by considering men and women in different stages of smoking behavior, consistent with stages of tobacco epidemic (29). Among men, increasing cessation and decreasing relapse tend to produce a higher prevalence of former smokers, typical of stage III, in which smoking is changing from being socially acceptable to a socially abnormal behavior. In this phase smoking prevalence in women shows a plateau or initiates a slight decline; consistent with our results, there is likely to be a marked age gradient, and more educated people lead changes in smoking behavior, as is the case in other health-related factors. In the interpretation of our results some issues must be considered. We studied healthy adults, and there were no specific programs to reduce tobacco use in the populations where they were recruited. The cohort was not designed to be representative of the adult Spanish population. However, it was recruited in five different regions and included a wide range of individuals from different educational levels, residents in rural and urban areas with different degree of industrialization; only the two extremes of very rich and
very poor people are underrepresented. Smoking prevalence in our study was similar with the prevalence of smoking in the Spanish adult population: in our sample, 27.1% of subjects were current smokers at recruitment, 16.2% were former smokers, and 56.7% had never smoked; the corresponding prevalences in the National Health Survey in Spain 1997 (30) in the age group 45 to 64 years were 27.5%, 18.1%, and 54.3%, respectively. On the other hand, classification of smoking status in or study was based upon regular smoking of any tobacco product (cigarettes, cigars, and pipe). Although smoking is often defined based on cigarette consumption, it must be recalled that, as it has been recently pointed out, all tobacco products, not just cigarettes, have devastating effects on health (9). The follow-up was complete for 98.2% of the cohort; although subjects lost to follow-up might be different regarding the likelihood of changing smoking behavior this would hardly affect the results given the low proportion of losses. A few subjects below age 35 or above age 64 were included in the cohort; given the small number, these were not included in the analysis in order to provide rates for an age group (35–64 years) well characterized in most routinely reported population data. Nevertheless, given the small proportion of such individuals (1.7%), this was not likely to have a major impact on the results. Concerning the exclusion of 4.3% subjects with inconsistent information, such discrepancies are in fact within the range of expected errors. Comparison of smoking status in self- and interviewer-administered questionnaires, or based on a screening or detailed interview produced discrepancies of
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4.5% and 3.9%, respectively (31). We followed subjects for 3 years; in intervention studies most attempts to quit occur during the first year but up to 5 or 10 years are needed to estimate sustained changes. We assumed constant rates of changes during follow-up, so that the estimates reported are average rates over 3 years; given the relatively short period, estimation of the average rate seems acceptable. In our population about 5% of men and 4% of women who currently smoke stop smoking every year; this is partially counterbalanced by the relatively similar rates of relapse of former smokers, mainly among women. Furthermore, there is still a low but non-negligible rate of smoking initiation in adults, especially among men. The net balance is positive but rather poor: the smoking prevalence among men in a 3-year period decreased from 41.4% to 38.7%, which results in 0.9% decrease per year. Among women the reduction in the absolute difference of the smoking prevalence was only 0.45%, or 0.15% per year. Our data suggest that additional efforts should be made in Spain to reduce tobacco burden. Comprehensive strategies to promote cessation and decrease initiation must follow evidence-based effective recommendations (32), within the framework of general smoking control policies.
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