MRC National Survey of Health and Development, University College London, Department of Epidemiology and Public Health, London WC1E 6BT, UK
* Author to whom correspondence should be addressed at: MRC National Survey of Health and Development, University College London, Department of Epidemiology and Public Health, London WC1E 6BT, UK. Tel: +44(0)207 679 1737; E-mail: m.richards{at}ucl.ac.uk
(Received 9 July 2004; first review notified 31 August 2004; in revised form 29 October 2004; accepted 30 October 2004)
![]() |
ABSTRACT |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
![]() |
INTRODUCTION |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
One limitation is that most of these studies are cross-sectional, making it difficult to rule out the possibility that those of higher ability have an advantageous lifestyle that protects against cognitive decline, which happens to include moderate social drinking. Available longitudinal evidence suggests weak or null associations between alcohol consumption and cognitive change, although these studies used either a brief follow-up interval (Dufouil et al., 1997), or a cognitive outcome (Mini-Mental State Examination, MMSE) that is relatively insensitive to change in younger people (Leroi et al., 2002
). In this study, we investigated the association between self-reported alcohol consumption and change in memory, speed and concentration between 43 and 53 years in the British 1946 birth cohort study, controlling for general ability, socio-economic status (social advantage), physical function and mental health. An additional advantage of this cohort is that all participants are of identical age, which may reduce the risk of confounding from poorer health and function associated with the age-related increase in alcohol abstention (Adams et al., 1990
).
![]() |
METHODS |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Of the 3035 participants interviewed at 53 years of age, 1764 had complete data for alcohol consumption, the cognitive outcome measures, general cognitive ability, educational attainment and adult occupational social class. These 1764 participants comprised the study sample. Those with any missing cognitive scores had a lower educational attainment than those with complete outcome data (P < 0.001). There was no difference at 5% significance in the level of alcohol consumption at 43 years between those with and without data for cognitive test scores at 53 years.
Measurement of alcohol consumption at 43 years
Information on alcohol consumption over the previous 7 days was obtained by a self-completed questionnaire when the participants were at 43 years of age. Questions were asked about (i) spirits or liqueurs (number of measures), (ii) wine, sherry, martini or port (number of glasses), and (iii) beer, lager, cider or stout (number of half-pints). Responses to these three items were totalled and divided by seven to provide an approximate measure of drinks per day, where a drink (or unit in UK terminology) contains 9.0 g of alcohol. Based on criteria used in the Framingham Heart Study (Elias et al., 1999
), this was coded into 0 drinks/day (abstainers), 0.11.0 drinks/day (very light drinkers), 1.12.0 drinks/day (light drinkers), 2.14.0 drinks/day (moderate drinkers) and >4.1 drinks/day (heavy drinkers). Moderate and heavy categories were merged for females because few women fell into the heavy drinking category.
Cognitive outcome variables at 43 and 53 years
Verbal memory was assessed by a 15 item word learning task devised by the NSHD. Each word was shown for 2 s. When all 15 words had been shown, the cohort member was asked to write down as many of the words as possible. The total number of words correctly recalled over three identical trials was summed to provide an overall score for short-term verbal memory (maximum score = 45). After a delay of approximately 2 min, while participants were engaged in another task, they were asked to recall the words again, without warning. The total number of words recalled correctly during this trial provided a score for delayed verbal memory (maximum score = 15). A different word list was given to each half of the cohort at 43 years and these lists were reversed when they were at 53 years of age, to minimize any practice effects.
Speed and concentration was assessed by a visual search task, wherein participants were required to cross out the letters P and W, randomly embedded within a page of other letters, as quickly and accurately as possible within 1 min. The score comprised the total number of letters searched (maximum score = 600). Target letters were in different positions on the page at 43 and 53 years.
Potential confounding variables
Potential confounding variables consisted of educational attainment, occupational social class, general cognitive ability and a range of health indicators.
The highest educational or training qualification achieved by 26 years was classified by the Burnham scale (Department of Education and Science, 1972) and grouped into no qualifications, below ordinary secondary qualifications, ordinary secondary qualifications (O levels and their training equivalents), advanced secondary education (A levels and their equivalents) or higher education (degree level or equivalent). The occupational social class of the participants at 43 years of age (or earlier if this was unavailable) was coded according to the Registrar General classification (OPCS, 1970), and classified as professional, managerial, intermediate, skilled manual, semi-skilled manual or unskilled.
General ability was measured by a test of word pronunciation, using the National adult reading test (NART; Nelson and Willison, 1991) at 53 years.
The following health indicators were used as potential confounders when the participants were at 43 years of age:
Statistical methods
Analysis of covariance was used to test the association between alcohol consumption and change in verbal memory and visual search speed between 43 and 53 years of age, separately for men and women. Conditional models of change were employed, adjusting for the memory and search speed scores at 53 years for their corresponding scores at 43 years, because different versions of the cognitive tests were used at the different ages. Multiple regression was then used to obtain regression coefficients and to adjust the associations for educational attainment, occupational social class and general ability and then for each health indicator in turn.
![]() |
RESULTS |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
|
|
Alcohol consumption and memory
Table 3 shows the results of the multiple regression analyses for memory, separately for men and women. Regression coefficients represent mean difference in memory at 53 years for a given memory score at 43 years, for each alcohol category compared with abstainers (reference group). Hence, these coefficients can also be interpreted as a change in memory score between 43 and 53 years for a given score at 43 years. Since there is a decline in scores between the two ages, positive coefficients represent a slower decline. All coefficients are shown before and after adjustment for educational attainment, occupational social class and general cognitive ability.
|
Alcohol consumption and visual search speed
Table 4 summarizes the regression analyses for visual search speed. There was little evidence of an association between alcohol consumption and change in search speed in men, before or after adjustment for education, social class and general ability. However, alcohol was associated with a more rapid decline in search speed from 43 to 53 years in women (F = 2.94, P = 0.03), and a faster decline with increasing alcohol consumption (P for trend = 0.008). Adjustment for education, social class and general ability had little effect on this association and the sex x alcohol consumption interaction was not significant at the 10% level.
|
Alcohol abstention and past potential alcohol abuse
Ten (2.1%) of the abstainers (six males and four females) reported that they had scored positive, at some time in their life, on at least two items in the CAGE screen, the recommended threshold with this measure for potential alcohol abuse (Ewing, 1984). Results of the regression analyses were almost identical when these participants were excluded from the analyses.
![]() |
DISCUSSION |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
We should note several potential limitations of this study. First, measures of alcohol consumption were self-reported, which raises the question of inaccurate or biased recall. Although self-report measures do not give a precise estimate of actual consumption, they are useful for classifying people into broad consumption bands (Eren, 1995). Second, the questions about alcohol consumption applied only to the previous 7 days, and can only be assumed to represent typical weekly alcohol consumption. There is some justification for this, since most studies report temporal stability in patterns of alcohol use (Glynn et al., 1985
; Temple and Leino, 1989
; Adams et al., 1990
). Third, these measures of alcohol use did not provide information on the pattern of alcohol consumption within the 7 days. Thus, we were unable to identify binge drinking, which is known to have adverse effects on health (Murray et al., 2002
). Fourth, since cognition was only part of a wide range of functions measured in this study, our test battery was necessarily of limited range, and to date, repeat measures have only been obtained for one measure each of memory and search speed. It would therefore be important to extend this investigation using a wider range of repeated cognitive measures. Finally, there was a disproportionate loss to follow-up of those with a lower cognitive ability. This is a common problem with studies of cognitive ageing, and may have led to an underestimation of the negative effects of alcohol on cognitive function, although we have no reason to believe that this loss influenced the pattern of associations.
Against these limitations, two advantages of the 1946 birth cohort can be highlighted. First, we were able to adjust for general cognitive ability, which, along with educational and occupational attainment, increased the rigour of control against confounding from social position. Second, all participants were of identical age, which reduces the risk of uncontrolled confounding from an age-associated decline in health and function.
With these methodological issues in mind, what accounts for the protective effect of alcohol consumption on memory decline? Since moderate drinking is associated with a healthy lifestyle and general well-being, it is possible that the underlying aspects of health were responsible. The inability of cardiovascular risk to explain this association raises doubts over whether it was mediated by the cardioprotective effects of alcohol. There is population-based evidence that moderate drinkers have fewer white matter abnormalities in later life than abstainers or heavy drinkers (Mukamal et al., 2001), raising the possibility of a neuroprotective effect of moderate alcohol consumption, via direct benefit to cerebral blood flow (Golumb et al., 1995
). However, only a small proportion of people are likely to have white matter disease in middle age.
Moreover, it is unclear whether a healthy lifestyle explains the positive association between alcohol and memory in men. We did not find that physical exercise or smoking had a confounding effect. To date, however, nutrition is an unexplored possibility in this cohort. Alcohol consumption in the UNC Alumni Heart Study was associated with a healthy diet in relation to non-consumption (Barefoot et al., 2002), although an earlier study of health behaviour clustering found that a healthy diet was associated with relatively low alcohol consumption (Patterson et al., 1994
). Associations between nutrient profile, alcohol consumption and cognitive function will be a matter for detailed investigation in the 1946 birth cohort.
An unexpected finding was the negative association between alcohol consumption and visual search speed in women, which was observed even in light drinkers. This apparently contradicts the results of Dufouil et al. (1997), who found a positive association between alcohol and performance in two speeded tests, Digit-Symbol Substitution, and Trailmaking, in older women. Yet their study was based on a relatively socially advantaged cohort. Our finding is unlikely to be explained by the well-known phenomenon of higher blood-alcohol level in women than in men for a given dose of alcohol, since this was effectively controlled after adjustment for body water weight (Ely et al., 1999
). Psychomotor function may be particularly vulnerable to the long-term central effects of alcohol, a matter of particular relevance in view of the public health concern over the increasing rates of alcohol consumption in young people (CASA, 2002
). Therefore, a follow-up testing of psychomotor function in the 1946 birth cohort is planned.
![]() |
ACKNOWLEDGEMENTS |
---|
![]() |
REFERENCES |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Barefoot, J. C., Gronbaek, M., Feaganes, J. R., McPherson, R. S., Williams, R. B. and Siegler, I. C. (2002) Alcoholic beverage preference, diet, and health habits in the UNC Alumni Heart Study. American Journal of Clinical Nutrition 76, 466472.
CASA report on underage drinking. National Center on Addiction and Substance Abuse at Columbia University (New York, NY), February 2002. Available at: www.casacolumbia.org
Delin, C. R. and Lee, T. H. (1992) Drinking and the brain: current evidence. Alcohol and Alcoholism 27, 117126.[Abstract]
Department of Education and Science (1972) Burnham further education committee grading courses. HMSO, London.
Dufouil, C., Ducimetiere, P. and Alperovitch, A. (1997) Sex differences in the association between alcohol consumption and cognitive performance. American Journal of Epidemiology 146, 405412.[Abstract]
Elias, P. K., Elias, M. F., D'Agostino, R. B., Silbershatz, H. and Wolf, P. A. (1999) Alcohol consumption and cognitive performance in the Framingham Heart Study. American Journal of Epidemiology 150, 580589.[Abstract]
Elias, M. F., Wolf, P. A., D'Agostino, R. B., Cobb, J. and White, J. R. (1993) Untreated blood pressure level is inversely related to cognitive functioning: the Framingham Study. American Journal of Epidemiology 138, 353364.[Abstract]
Ely, M., Hardy, R., Longford, N. T. and Wadsworth, M. E. (1999) Gender differences in the relationship between alcohol consumption and drink problems are largely accounted for by body water. Alcohol and Alcoholism 34, 894902.
Eren B. (1995) Alcohol consumption. In The Scottish Health Survey. Available at: www.archive.official-documents.co.uk/document/scottish/health
Ewing, J. A. (1984) Detecting alcoholism: the CAGE questionnaire. Journal of the American Medical Association 252, 19051907.[Abstract]
Glynn, R. J., Bouchard, G. R., LoCastro, J. S. and Laird, N. M. (1985) Aging and generational effects on drinking behaviors in men: results from the normative aging study. American Journal of Public Health 75, 14131419.[Abstract]
Goodwin, J. S., Sanchez, C. J., Thomas, P., Hunt, C., Garry, P. J. and Goodwin, J. M. (1987) Alcohol intake in a healthy elderly population. American Journal of Public Health 77, 173177.[Abstract]
Graham, K., Wilsnack, R., Dawson, D. and Vogeltanz, N. (1998) Should alcohol consumption measures be adjusted for gender differences? Addiction 93, 11371147.[CrossRef][ISI][Medline]
Golumb, J., Kluger, A., Gianutsos, J., Ferris, S. H., de Leon, M. J. and George, A. E. (1995) Nonspecific leukoencephalopathy associated with aging. Neuroimaging Clinics of North America 5, 3344.[Medline]
Hebert, L. E., Scherr, P. A., Beckett, L. A., Albert, M. S., Rosner, B., Taylor, J. O. and Evans, D. A. (1993) Relation of smoking and low-to-moderate alcohol consumption to change in cognitive function: a longitudinal study in a defined community of older persons. American Journal of Epidemiology 137, 881891.[Abstract]
Hendrie, H. C., Gao, S., Hall, K. S., Hui, S. L. and Unverzagt, F. W. (1996) The relationship between alcohol consumption, cognitive performance, and daily functioning in an urban sample of older Black Americans. Journal of the American Geriatric Society 44, 11581165.[ISI]
Istvan, J. and Matarazzo, J. D. (1984) Tobacco, alcohol, and caffeine use: a review of their interrelationships. Psychological Bulletin 95, 301326.[CrossRef][ISI][Medline]
Kalmijn, S., van Boxtel, M. P. J., Verschuren, M. W. M., Jolles, J. and Launer, L. J. (2002) Cigarette smoking and alcohol consumption in relation to cognitive performance in middle age. American Journal of Epidemiology 156, 936944.
Launer, L. J., Feskens, E. J., Kalmijn, S. and Kromhout, D. (1996) Smoking, drinking, and thinking. American Journal of Epidemiology 143, 219227.[Abstract]
Leroi, I., Sheppard, J. M. and Lyketsos, C. G. (2002) Cognitive function after 11.5 years of alcohol use: relation to alcohol use. American Journal of Epidemiology 156, 747752.
Lindelow, M., Hardy, R. and Wadsworth, M. E. J. (1997) Development of a scale to measure symptoms of anxiety and depression in the general population: the Psychiatric Symptom Frequency (PSF) Scale. Journal of Epidemiology and Community Health 51, 549557.[Abstract]
Mortensen, E. L., Jensen, H. H., Sanders, S. A. and Reinisch, J. M. (2001) Better psychological functioning and higher social status may largely explain the apparent health benefits of wine: a study of wine and beer drinking in young Danish adults. Archives of Internal Medicine 161, 18441848.
Mukamal, K. J., Longstreth, W. T., Mittleman, M. A., Crum, R. M. and Siscovick, D. S. (2001) Alcohol consumption and subclinical findings on magnetic resonance imaging of the brain in older adults: the cardiovascular health study. Stroke 32, 19391946.
Murray, R. P., Connett, J. E., Tyas, S. L., Bond, R., Ekuma, O., Silversides, C. K. and Barnes, G. E. (2002) Alcohol volume, drinking pattern, and cardiovascular disease morbidity and mortality: is there a U-shaped function? American Journal of Epidemiology 155, 242248.
Nelson, H. E. and Willison, J. R. (1991) National Adult Reading Test (NART). 2nd edn. NFER-Nelson, Windsor, UK.
Office of Population Censuses and Surveys (1970) Classification of occupations; HMSO, London.
Orgogozo, J. M., Dartigues, J. F., Lafont, S., Letenneur, L., Commenges, D., Salamon, R., Renaud, S. and Breteler, M. B. (1997) Wine consumption and dementia in the elderly: a prospective community study in the Bordeaux area. Revue Neurologique (Paris) 153, 185192.
Patterson, R. E., Haines, P. S. and Popkin, B. M. (1994) Health lifestyle patterns of U.S. adults. Preventive Medicine 23, 453460.[CrossRef][ISI][Medline]
Rehm, J. T., Bondy, S. J., Sempos, C. T. and Vuong, C. V. (1997) Alcohol consumption and coronary heart disease morbidity and mortality. American Journal of Epidemiology 146, 495501.[Abstract]
Richards, M., Hardy, R. and Wadsworth, M. (2003a) Does active leisure protect cognition? Evidence from a national birth cohort. Social Science and Medicine 56, 785792.[CrossRef][ISI][Medline]
Richards, M., Jarvis, M. J., Thompson, N. and Wadsworth, M. E. J. (2003b) Cigarette smoking and cognitive decline in midlife: evidence from a prospective birth cohort study. American Journal of Public Health 93, 994998.
Rimm, E. B., Klatsky, A., Grobbee, D. and Stampfer, M. J. (1996) Review of moderate alcohol consumption and reduced risk of coronary heart disease: is the effect due to beer, wine, or spirits? British Journal of Medicine 321, 731736.
Temple, M. T. and Leino, E. V. (1989) Long-term outcomes of drinking: a 20-year longitudinal study of men. British Journal of Addiction 84, 889899.[ISI][Medline]
Wadsworth, M. E. J., Butterworth, S. L., Hardy, R., Kuh, D., Richards, M., Langenberg, C. and Connor, M. (2003) The life course design: an example of benefits and problems associated with study longevity. Social Science and Medicine 57, 21932205.[CrossRef][ISI][Medline]
Williams, D., Skinner, R., Silverstone, J. et al. (1983) Obesity: a report of the Royal College of Physicians. Journal of the Royal College of Physicians 17, 565.[ISI]
|