A meta-analysis of coffee drinking, cigarette smoking, and the risk of Parkinson's disease

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Abstract

We conducted a systematic review to summarize the epidemiological evidence on the association between cigarette smoking, coffee drinking, and the risk of Parkinson's disease. Case-control and cohort studies that reported the relative risk of physician-confirmed Parkinson's disease by cigarette smoking or coffee drinking status were included. Study-specific log relative risks were weighted by the inverse of their variances to obtain a pooled relative risk and its 95% confidence interval (CI). Results for smoking were based on 44 case-control and 4 cohort studies, and for coffee 8 case-control and 5 cohort studies. Compared with never smokers, the relative risk of Parkinson's disease was 0.59 (95% CI, 0.54-0.63) for ever smokers, 0.80 (95% CI, 0.69-0.93) for past smokers, and 0.39 (95% CI, 0.32-0.47) for current smokers. The relative risk per 10 additional pack-years was 0.84 (95% CI, 0.81-0.88) in case-control studies and 0.78 (95% CI, 0.73-0.84) in cohort studies. Compared with non-coffee drinkers, relative risk of Parkinson's disease was 0.69 (95% CI, 0.59-0.80) for coffee drinkers. The relative risk per three additional cups of coffee per day was 0.75 (95% CI, 0.64-0.86) in case-control studies and 0.68 (95% CI, 0.46-1.00) in cohort studies. This meta-analysis shows that there is strong epidemiological evidence that smokers and coffee drinkers have a lower risk of Parkinson's disease. Further research is required on the biological mechanisms underlying this potentially protective effect.

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Prospective study of caffeine consumption and risk of Parkinson's disease in men and women.

A Ascherio, S Zhang, M Hernán … (2001)

Results of case-control studies and of a prospective investigation in men suggest that consumption of coffee could protect against the risk of Parkinson's disease, but the active constituent is not clear. To address the hypothesis that caffeine is protective against Parkinson's disease, we examined the relationship of coffee and caffeine consumption to the risk of this disease among participants in two ongoing cohorts, the Health Professionals' Follow-Up Study (HPFS) and the Nurses' Health Study (NHS). The study population comprised 47,351 men and 88,565 women who were free of Parkinson's disease, stroke, or cancer at baseline. A comprehensive life style and dietary questionnaire was completed by the participants at baseline and updated every two to four years. During the follow-up (10 years in men, 16 years in women), we documented a total of 288 incident cases of Parkinson's disease. Among men, after adjustment for age and smoking, the relative risk of Parkinson's disease was 0.42 (95% CI: 0.23-0.78; p for trend < 0.001) for men in the top one-fifth of caffeine intake compared to those in the bottom one-fifth. An inverse association was also observed with consumption of coffee (p for trend = 0.004), caffeine from noncoffee sources (p for trend < 0.001), and tea (p for trend = 0.02) but not decaffeinated coffee. Among women, the relationship between caffeine or coffee intake and risk of Parkinson's disease was U-shaped, with the lowest risk observed at moderate intakes (1-3 cups of coffee/day, or the third quintile of caffeine consumption). These results support a possible protective effect of moderate doses of caffeine on risk of Parkinson's disease.

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Andy Chang, Yonghong Chen, Jiann-Chu Chen … (1997)

To explore environmental risk factors for Parkinson's disease (PD) in Taiwan, we investigated 120 patients with PD and 240 hospital control subjects matched with patients on age (+/-2 years) and sex. Based on a structured open-ended questionnaire, we carried out standardized interviews to obtain history of exposure to environmental factors, including place of residence, source of drinking water, and environmental and occupational exposures to various agricultural chemicals. In the univariate analysis, the history of living in a rural environment, farming, use of herbicides/pesticides, and use of paraquat were associated with an increased PD risk in a dose-response relationship. After adjustment for multiple risk factors through conditional logistic regression, the biological gradient between PD and previous uses of herbicides/pesticides and paraquat remained significant. The PD risk was greater among subjects who had used paraquat and other herbicides/pesticides than those who had used herbicides/pesticides other than paraquat. There were no significant differences in occupational exposures to chemicals, heavy metals, and minerals between PD patients and matched control subjects. The duration of drinking well water and alcohol consumption was not significantly associated with PD. There was an inverse relationship between cigarette smoking and PD. Environmental factors, especially exposures to paraquat and herbicides/pesticides, may play important roles in the development of PD in Taiwan.

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Evaluation of old and new tests of heterogeneity in epidemiologic meta-analysis.

B Takkouche, C Cadarso-Suarez, D Spiegelman (1999)

The identification of heterogeneity in effects between studies is a key issue in meta-analyses of observational studies, since it is critical for determining whether it is appropriate to pool the individual results into one summary measure. The result of a hypothesis test is often used as the decision criterion. In this paper, the authors use a large simulation study patterned from the key features of five published epidemiologic meta-analyses to investigate the type I error and statistical power of five previously proposed asymptotic homogeneity tests, a parametric bootstrap version of each of the tests, and tau2-bootstrap, a test proposed by the authors. The results show that the asymptotic DerSimonian and Laird Q statistic and the bootstrap versions of the other tests give the correct type I error under the null hypothesis but that all of the tests considered have low statistical power, especially when the number of studies included in the meta-analysis is small (<20). From the point of view of validity, power, and computational ease, the Q statistic is clearly the best choice. The authors found that the performance of all of the tests considered did not depend appreciably upon the value of the pooled odds ratio, both for size and for power. Because tests for heterogeneity will often be underpowered, random effects models can be used routinely, and heterogeneity can be quantified by means of R(I), the proportion of the total variance of the pooled effect measure due to between-study variance, and CV(B), the between-study coefficient of variation.