BACKGROUND Evidence relating tobacco smoking to type 2 diabetes has accumulated rapidly in the last few years,rendering earlier reviews considerably incomplete.AIM To review and meta-analyse evidence from prospective ...BACKGROUND Evidence relating tobacco smoking to type 2 diabetes has accumulated rapidly in the last few years,rendering earlier reviews considerably incomplete.AIM To review and meta-analyse evidence from prospective studies of the relationship between smoking and the onset of type 2 diabetes.METHODS Prospective studies were selected if the population was free of type 2 diabetes at baseline and evidence was available relating smoking to onset of the disease.Papers were identified from previous reviews,searches on Medline and Embase and reference lists.Data were extracted on a range of study characteristics and relative risks(RRs)were extracted comparing current,ever or former smokers with never smokers,and current smokers with non-current smokers,as well as by amount currently smoked and duration of quitting.Fixed-and random-effects estimates summarized RRs for each index of smoking overall and by various subdivisions of the data:Sex;continent;publication year;method of diagnosis;nature of the baseline population(inclusion/exclusion of pre-diabetes);number of adjustment factors;cohort size;number of type 2 diabetes cases;age;length of follow-up;definition of smoking;and whether or not various factors were adjusted for.Tests of heterogeneity and publication bias were also conducted.RESULTS The literature searches identified 157 relevant publications providing results from 145 studies.Fifty-three studies were conducted in Asia and 53 in Europe,with 32 in North America,and seven elsewhere.Twenty-four were in males,10 in females and the rest in both sexes.Fifteen diagnosed type 2 diabetes from selfreport by the individuals,79 on medical records,and 51 on both.Studies varied widely in size of the cohort,number of cases,length of follow-up,and age.Overall,random-effects estimates of the RR were 1.33[95%confidence interval(CI):1.28-1.38]for current vs never smoking,1.28(95%CI:1.24-1.32)for current vs non-smoking,1.13(95%CI:1.11-1.16)for former vs never smoking,and 1.25(95%CI:1.21-1.28)for ever vs never smoking based on,respectively,99,156,100 and 100 individual risk estimates.Risk estimates were generally elevated in each subdivision of the data by the various factors considered(exceptions being where numbers of estimates in the subsets were very low),though there was significant(P<0.05)evidence of variation by level for some factors.Dose-response analysis showed a clear trend of increasing risk with increasing amount smoked by current smokers and of decreasing risk with increasing time quit.There was limited evidence of publication bias.CONCLUSION The analyses confirmed earlier reports of a modest dose-related association of current smoking and a weaker dose-related association of former smoking with type 2 diabetes risk.展开更多
AIM： To review evidence relating passive smoking to lung cancer risk in never smokers, considering various major sources of bias.METHODS： Epidemiological prospective or case-control studies were identifed which prov...AIM： To review evidence relating passive smoking to lung cancer risk in never smokers, considering various major sources of bias.METHODS： Epidemiological prospective or case-control studies were identifed which provide estimates of relative risk （RR） and 95%CI for never smokers for one or more of seven different indices of exposure to environmental tobacco smoke （ETS）： The spouse; household; workplace; childhood; travel; social and other; and total. A wide range of study details were entered into a database, and the RRs for each study, including descriptions of the comparisons made, were entered into a linked database. RRs were derived where necessary. Results were entered, where available, for all lung cancer, and for squamous cell cancer and adenocarcinoma. “Most adjusted” results were entered based on results available, adjusted for the greatest number of potential confounding variables. “Least adjusted” results were also entered, with a preference for results adjusted at least for age for prospective studies. A pre-planned series of fxed-effects and random-effects meta-analyses were conducted. Overall analyses and analyses by continent were run for each exposure index,with results for spousal smoking given by sex, and results for childhood exposure given by source of ETS exposure. For spousal exposure, more extensive analyses provide results by various aspects of study design and defnition of the RR. For smoking by the husband （or nearest equivalent）, additional analyses were carried out both for overall risk, and for risk per 10 cigarettes per day smoked by the husband. These adjusted for uncontrolled confounding by four factors （fruit, vegetable and dietary fat consumption, and education）, and corrected for misclassification of smoking status of the wife. For the confounding adjustment, estimates for never smoking women were derived from publications on the relationship of the four factors to both lung cancer risk and at home ETS exposure, and on the correlations between the factors. The bias due to misclassifcation was calculated on the basis that the proportion of ever smokers denying smoking is 10% in Asian studies and 2.5% elsewhere, and that those who deny smoking have the same risk as those who admit it. This approach, justifed in previous work, balances higher true denial rates and lower risk in deniers compared to non-deniers.RESULTS： One hundred and two studies were identifed for inclusion, published in 1981 onwards, 45 in Asia, 31 in North America, 21 in Europe, and fve elsewhere. Eighty-fve were of case-control design and 17 were prospective. Significant （P 〈 0.05） associations were noted, with random-effects of （RR = 1.22, 95%CI： 1.14-1.31, n = 93） for smoking by the husband （RR = 1.14, 95%CI： 1.01-1.29, n = 45） for smoking by the wife （RR = 1.22, 95%CI： 1.15-1.30, n = 47） for workplace exposure （RR = 1.15, 95%CI： 1.02-1.29, n = 41） for childhood exposure, and （RR = 1.31, 95%CI： 1.19-1.45, n = 48） for total exposure. No signifcant association was seen for ETS exposure in travel （RR = 1.34, 95%CI： 0.94-1.93, n = 8） or in social situations （RR = 1.01, 95%CI： 0.82-1.24, n = 15）. A signifcant negative association （RR = 0.78, 95%CI： 0.64-0.94, n = 8） was seen for ETS exposure in childhood, specifically from the parents. Significant associations were also seen for spousal smoking for both squamous cell carcinoma （RR = 1.44, 95%CI： 1.15-1.80, n = 24） and adenocarcinoma （RR = 1.33,95%CI： 1.17-1.51, n = 30）. Results generally showed marked heterogeneity between studies. For smoking by either the husband or wife, where 119 RR estimates gave an overall estimate of （RR = 1.21, 95%CI： 1.14-1.29）, the heterogeneity was highly significant （P 〈 0.001）, with evidence that the largest RRs were seen in studies published in 1981-89, in small studies （1-49 cases）, and for estimates unadjusted by age. For smoking by the husband, the additional analyses showed that adjustment for the four factors reduced the overall （RR = 1.22, 95%CI： 1.14-1.31） based on 93 estimates to （RR = 1.14, 95%CI： 1.06-1.22）, implying bias due to uncontrolled confounding of 7%. Further correction for misclassification reduced the estimate to a marginally non-signifcant （RR = 1.08, 95%CI： 0.999-1.16）. In the fully adjusted and corrected analyses, there was evidence of an increase in Asia （RR = 1.18, 95%CI： 1.07-1.30, n = 44）, but not in other regions （RR = 0.96, 95%CI： 0.86-1.07, n = 49）. Studies published in the 1980’s, studies providing dose-response data, and studies only providing results unadjusted for age showed elevated RRs, but later published studies, studies not providing dose-response data, and studies adjusting for age did not. The pattern of results for RRs per 10 cigs/d was similar, with no signifcant association in the adjusted and corrected results （RR = 1.03, 95%CI： 0.994-1.07）.CONCLUSION： Most, if not all, of the ETS/lung cancer association can be explained by confounding adjustment and misclassifcation correction. Any causal relationship is not convincingly demonstrated.展开更多
AIM： To quantify smoking/lung cancer relationships accurately using parametric modelling.METHODS： Using the International Epidemiological Studies on Smoking and Lung Cancer database of all epidemiological studies of...AIM： To quantify smoking/lung cancer relationships accurately using parametric modelling.METHODS： Using the International Epidemiological Studies on Smoking and Lung Cancer database of all epidemiological studies of 100＋ lung cancer cases published before 2000, we analyzed 97 blocks of data for amount smoked, 35 for duration of smoking, and 27 for age started. Pseudo-numbers of cases and controls （or at risk） estimated from RRs by dose level formed the data modelled. We fitted various models relating loge RR to dose （d）, including βd, βdY and βloge （1 ＋ Wd）, and investigated goodness-of-fit and heterogeneity between studies.0.833 loge [1 ＋ （8.1c/10）] for cigarettes/d （c）, 0.792 （y/10）0.74 for years smoked （y） and 0.176 [（70 - a）/10]1.44 for age of start （a）. Each model fitted well overall, though some blocks misfitted. RRs rose from 3.86 to 22.31 between c = 10 and 50, from 2.21 to 13.54 be-tween y = 10 and 50, and from 3.66 to 8.94 between a = 30 and 12.5. Heterogeneity （P 〈 0.001） existed by continent for amount, RRs for 50 cigarettes/d being 7.23 （Asia）, 26.36 （North America） and 22.16 （Europe）. Little heterogeneity was seen for duration of smoking or age started.CONCLUSION： The models describe the dose-relation-ships well, though may be biased by factors including misclassification of smoking status and dose.展开更多
BACKGROUND Misclassification of smoking habits leads to underestimation of true relationships between diseases and active smoking, and overestimation of true relationships with passive smoking. Information on misclass...BACKGROUND Misclassification of smoking habits leads to underestimation of true relationships between diseases and active smoking, and overestimation of true relationships with passive smoking. Information on misclassification rates can be obtained from studies using cotinine as a marker.AIM To estimate overall misclassification rates based on a review and meta-analysis of the available evidence, and to investigate how misclassification rates depend on other factors.METHODS We searched for studies using cotinine as a marker which involved at least 200 participants and which provided information on high cotinine levels in selfreported non-, never, or ex-smokers or on low levels in self-reported smokers. We estimated overall misclassification rates weighted on sample size and investigated heterogeneity by various study characteristics. Misclassification rates were calculated for two cotinine cut points to distinguish smokers and nonsmokers, the higher cut point intended to distinguish regular smoking.RESULTS After avoiding double counting, 226 reports provided 294 results from 205 studies. A total of 115 results were from North America, 128 from Europe, 25 from Asia and 26 from other countries. A study on 6.2 million life insurance applicants was considered separately. Based on the lower cut point, true current smokers represented 4.96%(95% CI 4.32-5.60%) of reported non-smokers, 3.00%(2.45-3.54%) of reported never smokers, and 10.92%(9.23-12.61%) of reported exsmokers. As percentages of true current smokers, non-, never and ex-smokers formed, respectively, 14.50%(12.36-16.65%), 5.70%(3.20-8.20%), and 8.93%(6.57-11.29%). Reported current smokers represented 3.65%(2.84-4.45%) of true non-smokers. There was considerable heterogeneity between misclassification rates.Rates of claiming never smoking were very high in Asian women smokers, the individual studies reporting rates of 12.5%, 22.4%, 33.3%, 54.2% and 66.3%. False claims of quitting were relatively high in pregnant women, in diseased individuals who may recently have been advised to quit, and in studies considering cigarette smoking rather than any smoking. False claims of smoking were higher in younger populations. Misclassification rates were higher in more recently published studies. There was no clear evidence that rates varied by the body fluid used for the cotinine analysis, the assay method used, or whether the respondent was aware their statements would be validated by cotinine-though here many studies did not provide relevant information. There was only limited evidence that rates were lower in studies classified as being of good quality,based on the extent to which other sources of nicotine were accounted for.CONCLUSION It is important for epidemiologists to consider the possibility of bias due to misclassification of smoking habits, especially in circumstances where rates are likely to be high. The evidence of higher rates in more recent studies suggests that the extent of misclassification bias in studies relating passive smoking to smoking-related disease may have been underestimated.展开更多
BACKGROUND Little information has been published on the risks of cigar smoking.Since 1990 cigar smoking has become more prevalent in the United States.AIM To summarise the evidence from the United States relating excl...BACKGROUND Little information has been published on the risks of cigar smoking.Since 1990 cigar smoking has become more prevalent in the United States.AIM To summarise the evidence from the United States relating exclusive cigar smoking to risk of the major smoking-related diseases.METHODS Literature searches detected studies carried out in the United States which estimated the risk of lung cancer,chronic obstructive pulmonary disease(COPD),heart disease,stroke or overall circulatory disease in exclusive cigar smokers as compared to those who had never smoked any tobacco product.Papers were identified from reviews and detailed searches on MEDLINE.For each study,data were extracted onto a study database and a linked relative risk database.Relative risks and 95%CIs were extracted,or estimated,relating to current,former or ever exclusive cigar smokers,and meta-analysed using standard methods.Sensitivity analyses were conducted including or excluding results from studies that did not quite fit the full selection criteria(for example,a paper presenting combined results from five studies,where 86%of the population were in the United States).RESULTS The literature searches identified 17 relevant publications for lung cancer,four for COPD and 12 for heart disease,stroke and circulatory disease.These related to 11 studies for lung cancer,to four studies for COPD and to eight studies for heart disease,stroke or overall circulatory disease.As some studies provided results for more than one disease,the total number of studies considered was 13,with results from four of these used in sensitivity analyses.There was evidence of significant heterogeneity in some of the meta-analyses so the random-effects estimates are summarized below.As the results from the sensitivity analyses were generally very similar to those from the main analyses,and involved more data,only the sensitivity results are summarized below.For lung cancer,relative risks(95%CI)for current,former and ever smokers were respectively,2.98(2.08 to 4.26),1.61(1.23 to 2.09),and 2.22(1.79 to 2.74)based on 6,4 and 10 individual study estimates.For COPD,the corresponding estimates were 1.44(1.16 to 1.77),0.47(0.02 to 9.88),and 0.86(0.48 to 1.54)based on 4,2 and 2 estimates.For ischaemic heart disease(IHD)the estimates were 1.11(1.04 to 1.19),1.26(1.03 to 1.53)and 1.15(1.08 to 1.23)based on 6,3 and 4 estimates,while for stroke they were 1.02(0.92 to 1.13),1.08(0.85 to 1.38),and 1.11(0.95 to 1.31)based on 5,3 and 4 estimates.For overall circulatory disease they were 1.10(1.05 to 1.16),1.11(0.84 to 1.46),and 1.15(1.06 to 1.26)based on 3,3 and 4 estimates.CONCLUSION Exclusive cigar smoking is associated with an increased risk of lung cancer,and less so with COPD and IHD.The increases are lower than for cigarettes.展开更多
The author, who has published numerous meta-analyses of epidemiological studies, particularly on tobacco, comments on various aspects of their content. While such meta-analyses, even when well conducted, are more diff...The author, who has published numerous meta-analyses of epidemiological studies, particularly on tobacco, comments on various aspects of their content. While such meta-analyses, even when well conducted, are more difficult to draw inferences from than are meta-analyses of clinical trials, they allow greater insight into an association than do simple qualitative reviews. This editorial starts with a discussion of some problems relating to hypothesis definition. These include the definition of the outcome, the exposure and the population to be considered, as well as the study inclusion and exclusion criteria. Under literature searching, the author argues against restriction to studies published in peer-reviewed journals, emphasising the fact that relevant data may be available from other sources. Problems of identifying studies and double counting are discussed, as are various issues in regard to data entry. The need to check published effect estimates is emphasised, and techniques to calculate estimates from material provided in the source publication are described. Once the data have been collected and an overall effect estimate obtained, tests for heterogeneity should be conducted in relation to different study characteristics. Though some meta-analysts recommend classifying studies by an overall index of study quality, the author prefers to separately investigate heterogeneity by those factors which contribute to the assessment of quality. Reasons why an association may not actually reflect a true causal relationship are also discussed, with the editorial describing techniques for investigating the relevance of confounding, and referring to problems resulting from misclassification of key variables. Misclassification of disease, exposure and confounding variables can all produce a spurious association, as can misclassification of the variable used to determine whether an individual can enter the study, and the author points to techniques to adjust for this. Issues relating to publication bias and the interpretation of "statistically significant" results are also discussed. The editorial should give the reader insight into the difficulties of producing a good meta-analysis.展开更多
AIM To review evidence relating passive smoking to heart disease risk in never smokers. METHODS Epidemiological studies were identified providing estimates of relative risk(RR) of ischaemic heart disease and 95%CI for...AIM To review evidence relating passive smoking to heart disease risk in never smokers. METHODS Epidemiological studies were identified providing estimates of relative risk(RR) of ischaemic heart disease and 95%CI for never smokers for various indices of exposure to environmental tobacco smoke(ETS). "Never smokers" could include those with a minimal smoking experience. The database set up included the RRs and other study details. Unadjusted and confounderadjusted RRs were entered, derived where necessary using standard methods. The fixed-effect and randomeffects meta-analyses conducted for each exposure index included tests for heterogeneity and publication bias. For the main index(ever smoking by the spouse or nearest equivalent, and preferring adjusted to unadjusted data), analyses investigated variation in the RR by sex, continent, period of publication, number of cases, study design, extent of confounder adjustment, availability of dose-response results and biomarkerdata, use of proxy respondents, definitions of exposure and of never smoker, and aspects of disease definition. Sensitivity analyses were also run, preferring current to ever smoking, or unadjusted to adjusted estimates, or excluding certain studies.RESULTS Fifty-eight studies were identified, 20 in North America, 19 in Europe, 11 in Asia, seven in other countries, and one in 52 countries. Twenty-six were prospective, 22 case-control and 10 cross-sectional. Thirteen included 100 cases or fewer, and 11 more than 1000. For the main index, 75 heterogeneous(P < 0.001) RR estimates gave a combined random-effects RR of 1.18(95%CI: 1.12-1.24), which was little affected by preferring unadjusted to adjusted RRs, or RRs for current ETS exposure to those for ever exposure. Estimates for each level of each factor considered consistently exceeded 1.00. However, univariate analyses revealed significant(P < 0.001) variation for some factors. Thus RRs were lower for males, and in North American, larger and prospective studies, and also where the RR was for spousal smoking, fatal cases, or specifically for IHD. For case-control studies RRs were lower if hospital/diseased controls were used. RRs were higher when diagnosis was based on medical data rather than death certificates or self-report, and where the never smoker definition allowed subjects to smoke products other than cigarettes or have a limited smoking history. The association with spousal smoking specifically(1.06, 1.01-1.12, n = 34) was less clear in analyses restricted to married subjects(1.03, 0.99-1.07, n = 23). In stepwise regression analyses only those associations with source of diagnosis, study size, and whether the spouse was the index, were independently predictive(at P < 0.05) of heart disease risk. A significant association was also evident with household exposure(1.19, 1.13-1.25, n = 37). For those 23 studies providing dose-response results for spouse or household exposure, 11 showed a significant(P < 0.05) positive trend including the unexposed group, and two excluding it. Based on fewer studies, a positive, but non-significant(P > 0.05) association was found for workplace exposure(RR = 1.08, 95%CI: 0.99-1.19), childhood exposure(1.12, 0.95-1.31), and biomarker based exposure indices(1.15, 0.94-1.40). However, there was a significant association with total exposure(1.23, 1.12-1.35). Some significant positive dose-response trends were also seen for these exposure indices, particularly total exposure, with no significant negative trends seen. The evidence suffers from various weaknesses and biases. Publication bias may explain the large RR(1.66, 1.30-2.11) for the main exposure index for smaller studies(1-99 cases), while recall bias may explain the higher RRs seen in casecontrol and cross-sectional than in prospective studies. Some bias may also derive from including occasional smokers among the "never smokers", and from misreporting smoking status. Errors in determining ETS exposure, and failing to update exposure data in long term prospective studies, also contribute to the uncertainty. The tendency for RRs to increase as more factors are adjusted for,argues against the association being due to uncontrolled confounding.CONCLUSION The increased risk and dose-response for various exposure indices suggests ETS slightly increases heart disease risk. However heterogeneity, study limitations and possible biases preclude definitive conclusions.展开更多
基金Supported by Japan Tobacco International,No.PO 4700389462.
文摘BACKGROUND Evidence relating tobacco smoking to type 2 diabetes has accumulated rapidly in the last few years,rendering earlier reviews considerably incomplete.AIM To review and meta-analyse evidence from prospective studies of the relationship between smoking and the onset of type 2 diabetes.METHODS Prospective studies were selected if the population was free of type 2 diabetes at baseline and evidence was available relating smoking to onset of the disease.Papers were identified from previous reviews,searches on Medline and Embase and reference lists.Data were extracted on a range of study characteristics and relative risks(RRs)were extracted comparing current,ever or former smokers with never smokers,and current smokers with non-current smokers,as well as by amount currently smoked and duration of quitting.Fixed-and random-effects estimates summarized RRs for each index of smoking overall and by various subdivisions of the data:Sex;continent;publication year;method of diagnosis;nature of the baseline population(inclusion/exclusion of pre-diabetes);number of adjustment factors;cohort size;number of type 2 diabetes cases;age;length of follow-up;definition of smoking;and whether or not various factors were adjusted for.Tests of heterogeneity and publication bias were also conducted.RESULTS The literature searches identified 157 relevant publications providing results from 145 studies.Fifty-three studies were conducted in Asia and 53 in Europe,with 32 in North America,and seven elsewhere.Twenty-four were in males,10 in females and the rest in both sexes.Fifteen diagnosed type 2 diabetes from selfreport by the individuals,79 on medical records,and 51 on both.Studies varied widely in size of the cohort,number of cases,length of follow-up,and age.Overall,random-effects estimates of the RR were 1.33[95%confidence interval(CI):1.28-1.38]for current vs never smoking,1.28(95%CI:1.24-1.32)for current vs non-smoking,1.13(95%CI:1.11-1.16)for former vs never smoking,and 1.25(95%CI:1.21-1.28)for ever vs never smoking based on,respectively,99,156,100 and 100 individual risk estimates.Risk estimates were generally elevated in each subdivision of the data by the various factors considered(exceptions being where numbers of estimates in the subsets were very low),though there was significant(P<0.05)evidence of variation by level for some factors.Dose-response analysis showed a clear trend of increasing risk with increasing amount smoked by current smokers and of decreasing risk with increasing time quit.There was limited evidence of publication bias.CONCLUSION The analyses confirmed earlier reports of a modest dose-related association of current smoking and a weaker dose-related association of former smoking with type 2 diabetes risk.
文摘AIM： To review evidence relating passive smoking to lung cancer risk in never smokers, considering various major sources of bias.METHODS： Epidemiological prospective or case-control studies were identifed which provide estimates of relative risk （RR） and 95%CI for never smokers for one or more of seven different indices of exposure to environmental tobacco smoke （ETS）： The spouse; household; workplace; childhood; travel; social and other; and total. A wide range of study details were entered into a database, and the RRs for each study, including descriptions of the comparisons made, were entered into a linked database. RRs were derived where necessary. Results were entered, where available, for all lung cancer, and for squamous cell cancer and adenocarcinoma. “Most adjusted” results were entered based on results available, adjusted for the greatest number of potential confounding variables. “Least adjusted” results were also entered, with a preference for results adjusted at least for age for prospective studies. A pre-planned series of fxed-effects and random-effects meta-analyses were conducted. Overall analyses and analyses by continent were run for each exposure index,with results for spousal smoking given by sex, and results for childhood exposure given by source of ETS exposure. For spousal exposure, more extensive analyses provide results by various aspects of study design and defnition of the RR. For smoking by the husband （or nearest equivalent）, additional analyses were carried out both for overall risk, and for risk per 10 cigarettes per day smoked by the husband. These adjusted for uncontrolled confounding by four factors （fruit, vegetable and dietary fat consumption, and education）, and corrected for misclassification of smoking status of the wife. For the confounding adjustment, estimates for never smoking women were derived from publications on the relationship of the four factors to both lung cancer risk and at home ETS exposure, and on the correlations between the factors. The bias due to misclassifcation was calculated on the basis that the proportion of ever smokers denying smoking is 10% in Asian studies and 2.5% elsewhere, and that those who deny smoking have the same risk as those who admit it. This approach, justifed in previous work, balances higher true denial rates and lower risk in deniers compared to non-deniers.RESULTS： One hundred and two studies were identifed for inclusion, published in 1981 onwards, 45 in Asia, 31 in North America, 21 in Europe, and fve elsewhere. Eighty-fve were of case-control design and 17 were prospective. Significant （P 〈 0.05） associations were noted, with random-effects of （RR = 1.22, 95%CI： 1.14-1.31, n = 93） for smoking by the husband （RR = 1.14, 95%CI： 1.01-1.29, n = 45） for smoking by the wife （RR = 1.22, 95%CI： 1.15-1.30, n = 47） for workplace exposure （RR = 1.15, 95%CI： 1.02-1.29, n = 41） for childhood exposure, and （RR = 1.31, 95%CI： 1.19-1.45, n = 48） for total exposure. No signifcant association was seen for ETS exposure in travel （RR = 1.34, 95%CI： 0.94-1.93, n = 8） or in social situations （RR = 1.01, 95%CI： 0.82-1.24, n = 15）. A signifcant negative association （RR = 0.78, 95%CI： 0.64-0.94, n = 8） was seen for ETS exposure in childhood, specifically from the parents. Significant associations were also seen for spousal smoking for both squamous cell carcinoma （RR = 1.44, 95%CI： 1.15-1.80, n = 24） and adenocarcinoma （RR = 1.33,95%CI： 1.17-1.51, n = 30）. Results generally showed marked heterogeneity between studies. For smoking by either the husband or wife, where 119 RR estimates gave an overall estimate of （RR = 1.21, 95%CI： 1.14-1.29）, the heterogeneity was highly significant （P 〈 0.001）, with evidence that the largest RRs were seen in studies published in 1981-89, in small studies （1-49 cases）, and for estimates unadjusted by age. For smoking by the husband, the additional analyses showed that adjustment for the four factors reduced the overall （RR = 1.22, 95%CI： 1.14-1.31） based on 93 estimates to （RR = 1.14, 95%CI： 1.06-1.22）, implying bias due to uncontrolled confounding of 7%. Further correction for misclassification reduced the estimate to a marginally non-signifcant （RR = 1.08, 95%CI： 0.999-1.16）. In the fully adjusted and corrected analyses, there was evidence of an increase in Asia （RR = 1.18, 95%CI： 1.07-1.30, n = 44）, but not in other regions （RR = 0.96, 95%CI： 0.86-1.07, n = 49）. Studies published in the 1980’s, studies providing dose-response data, and studies only providing results unadjusted for age showed elevated RRs, but later published studies, studies not providing dose-response data, and studies adjusting for age did not. The pattern of results for RRs per 10 cigs/d was similar, with no signifcant association in the adjusted and corrected results （RR = 1.03, 95%CI： 0.994-1.07）.CONCLUSION： Most, if not all, of the ETS/lung cancer association can be explained by confounding adjustment and misclassifcation correction. Any causal relationship is not convincingly demonstrated.
文摘AIM： To quantify smoking/lung cancer relationships accurately using parametric modelling.METHODS： Using the International Epidemiological Studies on Smoking and Lung Cancer database of all epidemiological studies of 100＋ lung cancer cases published before 2000, we analyzed 97 blocks of data for amount smoked, 35 for duration of smoking, and 27 for age started. Pseudo-numbers of cases and controls （or at risk） estimated from RRs by dose level formed the data modelled. We fitted various models relating loge RR to dose （d）, including βd, βdY and βloge （1 ＋ Wd）, and investigated goodness-of-fit and heterogeneity between studies.0.833 loge [1 ＋ （8.1c/10）] for cigarettes/d （c）, 0.792 （y/10）0.74 for years smoked （y） and 0.176 [（70 - a）/10]1.44 for age of start （a）. Each model fitted well overall, though some blocks misfitted. RRs rose from 3.86 to 22.31 between c = 10 and 50, from 2.21 to 13.54 be-tween y = 10 and 50, and from 3.66 to 8.94 between a = 30 and 12.5. Heterogeneity （P 〈 0.001） existed by continent for amount, RRs for 50 cigarettes/d being 7.23 （Asia）, 26.36 （North America） and 22.16 （Europe）. Little heterogeneity was seen for duration of smoking or age started.CONCLUSION： The models describe the dose-relation-ships well, though may be biased by factors including misclassification of smoking status and dose.
基金Japan Tobacco International for financial support and assistance in obtaining some of the references
文摘BACKGROUND Misclassification of smoking habits leads to underestimation of true relationships between diseases and active smoking, and overestimation of true relationships with passive smoking. Information on misclassification rates can be obtained from studies using cotinine as a marker.AIM To estimate overall misclassification rates based on a review and meta-analysis of the available evidence, and to investigate how misclassification rates depend on other factors.METHODS We searched for studies using cotinine as a marker which involved at least 200 participants and which provided information on high cotinine levels in selfreported non-, never, or ex-smokers or on low levels in self-reported smokers. We estimated overall misclassification rates weighted on sample size and investigated heterogeneity by various study characteristics. Misclassification rates were calculated for two cotinine cut points to distinguish smokers and nonsmokers, the higher cut point intended to distinguish regular smoking.RESULTS After avoiding double counting, 226 reports provided 294 results from 205 studies. A total of 115 results were from North America, 128 from Europe, 25 from Asia and 26 from other countries. A study on 6.2 million life insurance applicants was considered separately. Based on the lower cut point, true current smokers represented 4.96%(95% CI 4.32-5.60%) of reported non-smokers, 3.00%(2.45-3.54%) of reported never smokers, and 10.92%(9.23-12.61%) of reported exsmokers. As percentages of true current smokers, non-, never and ex-smokers formed, respectively, 14.50%(12.36-16.65%), 5.70%(3.20-8.20%), and 8.93%(6.57-11.29%). Reported current smokers represented 3.65%(2.84-4.45%) of true non-smokers. There was considerable heterogeneity between misclassification rates.Rates of claiming never smoking were very high in Asian women smokers, the individual studies reporting rates of 12.5%, 22.4%, 33.3%, 54.2% and 66.3%. False claims of quitting were relatively high in pregnant women, in diseased individuals who may recently have been advised to quit, and in studies considering cigarette smoking rather than any smoking. False claims of smoking were higher in younger populations. Misclassification rates were higher in more recently published studies. There was no clear evidence that rates varied by the body fluid used for the cotinine analysis, the assay method used, or whether the respondent was aware their statements would be validated by cotinine-though here many studies did not provide relevant information. There was only limited evidence that rates were lower in studies classified as being of good quality,based on the extent to which other sources of nicotine were accounted for.CONCLUSION It is important for epidemiologists to consider the possibility of bias due to misclassification of smoking habits, especially in circumstances where rates are likely to be high. The evidence of higher rates in more recent studies suggests that the extent of misclassification bias in studies relating passive smoking to smoking-related disease may have been underestimated.
基金Supported by the JT International SA,Assignment Schedule,No.14.
文摘BACKGROUND Little information has been published on the risks of cigar smoking.Since 1990 cigar smoking has become more prevalent in the United States.AIM To summarise the evidence from the United States relating exclusive cigar smoking to risk of the major smoking-related diseases.METHODS Literature searches detected studies carried out in the United States which estimated the risk of lung cancer,chronic obstructive pulmonary disease(COPD),heart disease,stroke or overall circulatory disease in exclusive cigar smokers as compared to those who had never smoked any tobacco product.Papers were identified from reviews and detailed searches on MEDLINE.For each study,data were extracted onto a study database and a linked relative risk database.Relative risks and 95%CIs were extracted,or estimated,relating to current,former or ever exclusive cigar smokers,and meta-analysed using standard methods.Sensitivity analyses were conducted including or excluding results from studies that did not quite fit the full selection criteria(for example,a paper presenting combined results from five studies,where 86%of the population were in the United States).RESULTS The literature searches identified 17 relevant publications for lung cancer,four for COPD and 12 for heart disease,stroke and circulatory disease.These related to 11 studies for lung cancer,to four studies for COPD and to eight studies for heart disease,stroke or overall circulatory disease.As some studies provided results for more than one disease,the total number of studies considered was 13,with results from four of these used in sensitivity analyses.There was evidence of significant heterogeneity in some of the meta-analyses so the random-effects estimates are summarized below.As the results from the sensitivity analyses were generally very similar to those from the main analyses,and involved more data,only the sensitivity results are summarized below.For lung cancer,relative risks(95%CI)for current,former and ever smokers were respectively,2.98(2.08 to 4.26),1.61(1.23 to 2.09),and 2.22(1.79 to 2.74)based on 6,4 and 10 individual study estimates.For COPD,the corresponding estimates were 1.44(1.16 to 1.77),0.47(0.02 to 9.88),and 0.86(0.48 to 1.54)based on 4,2 and 2 estimates.For ischaemic heart disease(IHD)the estimates were 1.11(1.04 to 1.19),1.26(1.03 to 1.53)and 1.15(1.08 to 1.23)based on 6,3 and 4 estimates,while for stroke they were 1.02(0.92 to 1.13),1.08(0.85 to 1.38),and 1.11(0.95 to 1.31)based on 5,3 and 4 estimates.For overall circulatory disease they were 1.10(1.05 to 1.16),1.11(0.84 to 1.46),and 1.15(1.06 to 1.26)based on 3,3 and 4 estimates.CONCLUSION Exclusive cigar smoking is associated with an increased risk of lung cancer,and less so with COPD and IHD.The increases are lower than for cigarettes.
文摘The author, who has published numerous meta-analyses of epidemiological studies, particularly on tobacco, comments on various aspects of their content. While such meta-analyses, even when well conducted, are more difficult to draw inferences from than are meta-analyses of clinical trials, they allow greater insight into an association than do simple qualitative reviews. This editorial starts with a discussion of some problems relating to hypothesis definition. These include the definition of the outcome, the exposure and the population to be considered, as well as the study inclusion and exclusion criteria. Under literature searching, the author argues against restriction to studies published in peer-reviewed journals, emphasising the fact that relevant data may be available from other sources. Problems of identifying studies and double counting are discussed, as are various issues in regard to data entry. The need to check published effect estimates is emphasised, and techniques to calculate estimates from material provided in the source publication are described. Once the data have been collected and an overall effect estimate obtained, tests for heterogeneity should be conducted in relation to different study characteristics. Though some meta-analysts recommend classifying studies by an overall index of study quality, the author prefers to separately investigate heterogeneity by those factors which contribute to the assessment of quality. Reasons why an association may not actually reflect a true causal relationship are also discussed, with the editorial describing techniques for investigating the relevance of confounding, and referring to problems resulting from misclassification of key variables. Misclassification of disease, exposure and confounding variables can all produce a spurious association, as can misclassification of the variable used to determine whether an individual can enter the study, and the author points to techniques to adjust for this. Issues relating to publication bias and the interpretation of "statistically significant" results are also discussed. The editorial should give the reader insight into the difficulties of producing a good meta-analysis.
文摘AIM To review evidence relating passive smoking to heart disease risk in never smokers. METHODS Epidemiological studies were identified providing estimates of relative risk(RR) of ischaemic heart disease and 95%CI for never smokers for various indices of exposure to environmental tobacco smoke(ETS). "Never smokers" could include those with a minimal smoking experience. The database set up included the RRs and other study details. Unadjusted and confounderadjusted RRs were entered, derived where necessary using standard methods. The fixed-effect and randomeffects meta-analyses conducted for each exposure index included tests for heterogeneity and publication bias. For the main index(ever smoking by the spouse or nearest equivalent, and preferring adjusted to unadjusted data), analyses investigated variation in the RR by sex, continent, period of publication, number of cases, study design, extent of confounder adjustment, availability of dose-response results and biomarkerdata, use of proxy respondents, definitions of exposure and of never smoker, and aspects of disease definition. Sensitivity analyses were also run, preferring current to ever smoking, or unadjusted to adjusted estimates, or excluding certain studies.RESULTS Fifty-eight studies were identified, 20 in North America, 19 in Europe, 11 in Asia, seven in other countries, and one in 52 countries. Twenty-six were prospective, 22 case-control and 10 cross-sectional. Thirteen included 100 cases or fewer, and 11 more than 1000. For the main index, 75 heterogeneous(P < 0.001) RR estimates gave a combined random-effects RR of 1.18(95%CI: 1.12-1.24), which was little affected by preferring unadjusted to adjusted RRs, or RRs for current ETS exposure to those for ever exposure. Estimates for each level of each factor considered consistently exceeded 1.00. However, univariate analyses revealed significant(P < 0.001) variation for some factors. Thus RRs were lower for males, and in North American, larger and prospective studies, and also where the RR was for spousal smoking, fatal cases, or specifically for IHD. For case-control studies RRs were lower if hospital/diseased controls were used. RRs were higher when diagnosis was based on medical data rather than death certificates or self-report, and where the never smoker definition allowed subjects to smoke products other than cigarettes or have a limited smoking history. The association with spousal smoking specifically(1.06, 1.01-1.12, n = 34) was less clear in analyses restricted to married subjects(1.03, 0.99-1.07, n = 23). In stepwise regression analyses only those associations with source of diagnosis, study size, and whether the spouse was the index, were independently predictive(at P < 0.05) of heart disease risk. A significant association was also evident with household exposure(1.19, 1.13-1.25, n = 37). For those 23 studies providing dose-response results for spouse or household exposure, 11 showed a significant(P < 0.05) positive trend including the unexposed group, and two excluding it. Based on fewer studies, a positive, but non-significant(P > 0.05) association was found for workplace exposure(RR = 1.08, 95%CI: 0.99-1.19), childhood exposure(1.12, 0.95-1.31), and biomarker based exposure indices(1.15, 0.94-1.40). However, there was a significant association with total exposure(1.23, 1.12-1.35). Some significant positive dose-response trends were also seen for these exposure indices, particularly total exposure, with no significant negative trends seen. The evidence suffers from various weaknesses and biases. Publication bias may explain the large RR(1.66, 1.30-2.11) for the main exposure index for smaller studies(1-99 cases), while recall bias may explain the higher RRs seen in casecontrol and cross-sectional than in prospective studies. Some bias may also derive from including occasional smokers among the "never smokers", and from misreporting smoking status. Errors in determining ETS exposure, and failing to update exposure data in long term prospective studies, also contribute to the uncertainty. The tendency for RRs to increase as more factors are adjusted for,argues against the association being due to uncontrolled confounding.CONCLUSION The increased risk and dose-response for various exposure indices suggests ETS slightly increases heart disease risk. However heterogeneity, study limitations and possible biases preclude definitive conclusions.
