Life course trajectories of alcohol consumption in the United Kingdom using longitudinal data from nine cohort studies

BMC Medicine

Steven Bell³  Diana Kuh²  Michaela Benzeval⁴  Yoav Ben-Shlomo¹  Annie Britton³ 

[1] School of Social & Community Medicine, University of Bristol, Canynge Hall, 39 Whatley Road, Bristol BS8 2PS, UK;MRC Unit for Lifelong Health & Ageing at UCL, 33 Bedford Place, London WC1B 5JU, UK;Research Department of Epidemiology and Public Health, University College London, 1-19 Torrington Place, London WC1E 6BT, UK;Institute of Health and Wellbeing, University of Glasgow, 1 Lilybank Gardens, Glasgow G12 8RZ, UK

关键词: Longitudinal;    Life course;    Alcohol;   

Others  :  1135491
DOI  :  10.1186/s12916-015-0273-z

 received in 2014-10-03, accepted in 2015-01-09,  发布年份 2015

【 摘 要 】

Background

Alcohol consumption patterns change across life and this is not fully captured in cross-sectional series data. Analysis of longitudinal data, with repeat alcohol measures, is necessary to reveal changes within the same individuals as they age. Such data are scarce and few studies are able to capture multiple decades of the life course. Therefore, we examined alcohol consumption trajectories, reporting both average weekly volume and frequency, using data from cohorts with repeated measures that cover different and overlapping periods of life.

Methods

Data were from nine UK-based prospective cohorts with at least three repeated alcohol consumption measures on individuals (combined sample size of 59,397 with 174,666 alcohol observations), with data spanning from adolescence to very old age (90 years plus). Information on volume and frequency of drinking were harmonised across the cohorts. Predicted volume of alcohol by age was estimated using random effect multilevel models fitted to each cohort. Quadratic and cubic polynomial terms were used to describe non-linear age trajectories. Changes in drinking frequency by age were calculated from observed data within each cohort and then smoothed using locally weighted scatterplot smoothing. Models were fitted for men and women separately.

Results

We found that, for men, mean consumption rose sharply during adolescence, peaked at around 25 years at 20 units per week, and then declined and plateaued during mid-life, before declining from around 60 years. A similar trajectory was seen for women, but with lower overall consumption (peak of around 7 to 8 units per week). Frequent drinking (daily or most days of the week) became more common during mid to older age, most notably among men, reaching above 50% of men.

Conclusions

This is the first attempt to synthesise longitudinal data on alcohol consumption from several overlapping cohorts to represent the entire life course and illustrates the importance of recognising that this behaviour is dynamic. The aetiological findings from epidemiological studies using just one exposure measure of alcohol, as is typically done, should be treated with caution. Having a better understanding of how drinking changes with age may help design intervention strategies.

【 授权许可】

   
2015 Britton et al.; licensee BioMed Central.

【 图 表 】

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【 参考文献 】

• [1]Room R, Babor T, Rehm J: Alcohol and public health. Lancet 2005, 365:519-530.
• [2]Office for National Statistics: Alcohol-related deaths in the United Kingdom, registered in 2012. ONS, London; 2014.
• [3]Office for National Statistics: Drinking habits amongst adults, 2012. ONS, London; 2013.
• [4]Beer B, Association P: Statistical handbook 2009. Brewing Publications Limited, London; 2012.
• [5]Robinson S, Bugler C: General lifestyle survey 2008. Smoking and drinking among adults, 2008. ONS, London; 2010.
• [6]Mindell J, Biddulph JP, Hirani V, Stamatakis E, Craig R, Nunn S, et al.: Cohort profile: the health survey for England. Int J Epidemiol 2012, 41:1585-1593.
• [7]Gray L, Batty GD, Craig P, Stewart C, Whyte B, Finlayson A, et al.: Cohort Profile: The Scottish Health Surveys Cohort: linkage of study participants to routinely collected records for mortality, hospital discharge, cancer and offspring birth characteristics in three nationwide studies. Int J Epidemiol 2010, 39:345-350.
• [8]Knott CS, Scholes S, Shelton NJ: Could more than three million older people in England be at risk of alcohol-related harm? A cross-sectional analysis of proposed age-specific drinking limits. Age Ageing 2013, 42:598-603.
• [9]Twigg L, Moon G: The spatial and temporal development of binge drinking in England 2001–2009: an observational study. Soc Sci Med 2013, 91:162-167.
• [10]Smith L, Foxcroft DR: Drinking in the UK: an exploration of trends. Joseph Rowntree Foundation, York; 2009.
• [11]Britton A, McPherson K: Mortality in England and Wales attributable to current alcohol consumption. J Epidemiol Community Health 2001, 55:383-388.
• [12]Health and Social Care Information Centre: Statistics on alcohol: England, 2013. Health and Social Care Information Centre, Leeds; 2013.
• [13]Fillmore KM: Prevalence, incidence and chronicity of drinking patterns and problems among men as a function of age: a longitudinal and cohort analysis. Br J Addict 1987, 82:77-83.
• [14]Kerr WC, Fillmore KM, Bostrom A: Stability of alcohol consumption over time: evidence from three longitudinal surveys from the United States. J Stud Alcohol Drugs 2002, 63:325.
• [15]Gilhooly ML: Reduced drinking with age: is it normal? Addict Res Theory 2005, 13:267-280.
• [16]Fan AZ, Russell M, Stranges S, Dorn J, Trevisan M: Association of lifetime alcohol drinking trajectories with cardiometabolic risk. J Clin Endocrinol Metab 2008, 93:154-161.
• [17]Berg N, Kiviruusu O, Karvonen S, Kestilä L, Lintonen T, Rahkonen O, et al.: A 26-year follow-up study of heavy drinking trajectories from adolescence to mid-adulthood and adult disadvantage. Alcohol Alcohol 2013, 48:452-457.
• [18]Kuh D, Ben-Shlomo Y, Lynch J, Hallqvist J, Power C: Life course epidemiology. J Epidemiol Community Health 2003, 57:778-783.
• [19]Casswell S, Pledger M, Pratap S: Trajectories of drinking from 18 to 26 years: identification and prediction. Addiction 2002, 97:1427-1437.
• [20]Maggs JL, Patrick ME, Feinstein L: Childhood and adolescent predictors of alcohol use and problems in adolescence and adulthood in the National Child Development Study. Addiction 2008, 103:7-22.
• [21]Merline A, Jager J, Schulenberg JE: Adolescent risk factors for adult alcohol use and abuse: stability and change of predictive value across early and middle adulthood. Addiction 2008, 103:84-99.
• [22]Degenhardt L, O’Loughlin C, Swift W, Romaniuk H, Carlin J, Coffey C, et al.: The persistence of adolescent binge drinking into adulthood: findings from a 15-year prospective cohort study. BMJ Open 2013, 3:e003015.
• [23]Staff J, Schulenberg JE, Maslowsky J, Bachman JG, O’Malley PM, Maggs JL, et al.: Substance use changes and social role transitions: proximal developmental effects on ongoing trajectories from late adolescence through early adulthood. Dev Psychopathol 2010, 22:917.
• [24]Moos RH, Schutte KK, Brennan PL, Moos BS: Older adults’ alcohol consumption and late‐life drinking problems: a 20‐year perspective. Addiction 2009, 104:1293-1302.
• [25]Bobo JK, Greek AA, Klepinger DH, Herting JR: Alcohol use trajectories in two cohorts of US women aged 50 to 65 at baseline. J Am Geriatr Soc 2010, 58:2375-2380.
• [26]Brennan PL, Schutte KK, Moos RH: Patterns and predictors of late-life drinking trajectories: a 10-year longitudinal study. Psychol Addict Behav 2010, 24:254-264.
• [27]Bobo JK, Greek AA, Klepinger DH, Herting JR: Predicting 10-year alcohol use trajectories among men age 50 years and older. Am J Geriatr Psychiatry 2013, 21:204-213.
• [28]Molander RC, Yonker JA, Krahn DD: Age-related changes in drinking patterns from mid- to older age: results from the Wisconsin longitudinal study. Alcohol Clin Exp Res 2010, 34:1182-1192.
• [29]Platt A, Sloan FA, Costanzo P: Alcohol-consumption trajectories and associated characteristics among adults older than age 50. J Stud Alcohol Drugs 2010, 71:169.
• [30]Fillmore KM, Hartka E, Johnstone BM, Leino EV, Motoyoshi M, Temple MT: A meta-analysis of life course variation in drinking. Br J Addict 1991, 86:1221-1268.
• [31]Johnstone BM, Leino EV, Ager CR, Ferrer H, Fillmore KM: Determinants of life-course variation in the frequency of alcohol consumption: meta-analysis of studies from the collaborative alcohol-related longitudinal project. J Stud Alcohol Drugs 1996, 57:494.
• [32]Singer JD, Willett JB: Applied longitudinal data analysis: modeling change and event occurrence. Oxford University Press, Oxford; 2003.
• [33]Barnett AG, van der Pols JC, Dobson AJ: Regression to the mean: what it is and how to deal with it. Int J Epidemiol 2005, 34:215-220.
• [34]Kerr WC, Greenfield TK, Bond J, Ye Y, Rehm J: Age–period–cohort modelling of alcohol volume and heavy drinking days in the US National Alcohol Surveys: divergence in younger and older adult trends. Addiction 2009, 104:27-37.
• [35]Wills AK, Lawlor DA, Matthews FE, Sayer AA, Bakra E, Ben-Shlomo Y, et al.: Life course trajectories of systolic blood pressure using longitudinal data from eight UK cohorts. PLoS Med 2011, 8:e1000440.
• [36]Wadsworth M, Kuh D, Richards M, Hardy R: Cohort profile: the 1946 National Birth Cohort (MRC National Survey of Health and Development). Int J Epidemiol 2006, 35:49-54.
• [37]Kuh D, Pierce M, Adams J, Deanfield J, Ekelund U, Friberg P, et al.: Cohort profile: updating the cohort profile for the MRC National Survey of Health and Development: a new clinic-based data collection for ageing research. Int J Epidemiol 2011, 40:e1-e9.
• [38]Power C, Elliott J: Cohort profile: 1958 British birth cohort (National Child Development Study). Int J Epidemiol 2006, 35:34-41.
• [39]Elliott J, Shepherd P: Cohort profile: 1970 British Birth Cohort (BCS70). Int J Epidemiol 2006, 35:836-843.
• [40]Steptoe A, Breeze E, Banks J, Nazroo J: Cohort profile: the English longitudinal study of ageing. Int J Epidemiol 2013, 42:1640-1648.
• [41]Marmot M, Brunner E: Cohort profile: the Whitehall II study. Int J Epidemiol 2005, 34:251-256.
• [42]Benzeval M, Der G, Ellaway A, Hunt K, Sweeting H, West P, et al.: Cohort profile: West of Scotland twenty-07 study: health in the community. Int J Epidemiol 2009, 38:1215-1223.
• [43]The Caerphilly and Speedwell Collaborative Group: Caerphilly and Speedwell collaborative heart disease studies J Epidemiol Community Health 1979 1984, 38:259-262.
• [44]Department of Health, United Kingdom: Sensible drinking report of an inter-departmental working group. Department of Health, London; 1995.
• [45]Royston P, Ambler G, Sauerbrei W: The use of fractional polynomials to model continuous risk variables in epidemiology. Int J Epidemiol 1999, 28:964-974.
• [46]Royston P, Altman DG: Regression using fractional polynomials of continuous covariates: parsimonious parametric modelling. Appl Stat 1994, 43:429-467.
• [47]StataCorp: Stata Statistical Software: Release 13. StataCorp LP, College Station, TX; 2013.
• [48]Crome I, Brown A, Dar K, Harris L, Janikiewicz S: Our invisible addicts: first report of the Older Persons’ Substance Misuse Working Group of the Royal College of Psychiatrists. Royal College of Psychiatrists, London; 2011.
• [49]Stockwell T, Donath S, Cooper-Stanbury M, Chikritzhs T, Catalano P, Mateo C: Under-reporting of alcohol consumption in household surveys: a comparison of quantity–frequency, graduated–frequency and recent recall. Addiction 2004, 99:1024-1033.
• [50]Meier PS, Meng Y, Holmes J, Baumberg B, Purshouse R, Hill-McManus D, et al.: Adjusting for unrecorded consumption in survey and per capita sales data: quantification of impact on gender- and age-specific alcohol-attributable fractions for oral and pharyngeal cancers in Great Britain. Alcohol Alcohol 2013, 48:241-249.
• [51]Rehm J, Kehoe T, Gmel G, Stinson F, Grant B, Gmel G: Statistical modeling of volume of alcohol exposure for epidemiological studies of population health: the US example. Popul Health Metr 2010, 8:3. BioMed Central Full Text
• [52]Grittner U, Gmel G, Ripatti S, Bloomfield K, Wicki M: Missing value imputation in longitudinal measures of alcohol consumption. Int J Methods Psychiatr Res 2011, 20:50-61.
• [53]Meng Y, Holmes J, Hill-McManus D, Brennan A, Meier PS: Trend analysis and modelling of gender-specific age, period and birth cohort effects on alcohol abstention and consumption level for drinkers in Great Britain using the General Lifestyle Survey 1984–2009. Addiction 2014, 109:206-215.
• [54]Global Information System on Alcohol and Health (GISAH). http://www.who.int/gho/alcohol/consumption_levels/en/.
• [55]Office for National Statistics: General lifestyle survey, 2010. ONS, London; 2012.
• [56]Muthén B, Muthén LK: Integrating person‐centered and variable‐centered analyses: growth mixture modeling with latent trajectory classes. Alcohol Clin Exp Res 2000, 24:882-891.
• [57]Oxford ML, Gilchrist LD, Morrison DM, Gillmore MR, Lohr MJ, Lewis SM: Alcohol use among adolescent mothers: heterogeneity in growth curves, predictors, and outcomes of alcohol use over time. Prev Sci 2003, 4:15-26.
• [58]Mishra G, Nitsch D, Black S, De Stavola B, Kuh D, Hardy R: A structured approach to modelling the effects of binary exposure variables over the life course. Int J Epidemiol 2009, 38:528-537.
• [59]Greenfield TK, Kerr WC: Commentary on Liang & Chikritzhs (2011): Quantifying the impacts of health problems on drinking and subsequent morbidity and mortality – life-course measures are essential. Addiction 2011, 106:82-83.