The majority of prospective studies on alcohol use and mortality risk indicates that abstainers are at increased risk of mortality from both all causes and coronary heart disease (CHD). This meta-analysis of 54 published studies tested the extent to which a systematic misclassification error was committed by including as 'abstainers' many people who had reduced or stopped drinking, a phenomenon associated with ageing and ill health. The studies judged to be error free found no significant all-cause or cardiac protection, suggesting that the cardiac protection afforded by alcohol may have been over-estimated. Estimates of mortality from heavier drinking may also be higher than previously estimated.

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Meta-analysis is used to combine results of primary data from 12 longitudinal studies to examine the consistency of results with respect to the role of changes on the individual level in marital status and employment status on changes in consumption of alcohol per typical occasion. The analyses control for the effects of Time 1 consumption per occasion and education. Not getting married and becoming unmarried are associated with increased consumption at follow-up and both variables are positively related to increased consumption among older men, but only becoming unmarried was related to increased consumption among older women. Becoming married is homogeneously and negatively associated with consumption at follow-up for younger and older persons of both sexes. Chronic unemployment is negatively related to consumption at follow-up among older males and younger females. Becoming unemployed between measurements is homogeneously and negatively related to consumption among older males and females, but positively related among younger males. Becoming employed is homogeneously and positively related to later consumption among all groups except young females.

Meta-analysis (eight general population longitudinal studies) describes the relationships (regressions) between quantity per occasion and depressive symptomatology over time. Quantity and depression are the strongest and most consistent predictors of final levels of themselves in all data sets. Age significantly and consistently predicts quantity for both sexes combined (the general pattern is replicated among males only). Depression significantly predicts quantity and quantity significantly predicts depression for females. Controlling for interval between measurements produces stronger prediction (more consistent over shorter intervals) for males. Depression only predicts quantity over longer intervals and quantity only predicts depression over shorter intervals for females. Explicit control for age found stronger relationships between initial and final measurement quantity, and depression for males. Quantity and depression significantly predict quantity and depression among young females. The relationship between quantity and depression among females illustrates the importance of controlling for age and sex. Methodological considerations are discussed.

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