Binge drinking and cardiovascular disease: a meta-analysis Vincenzo Bagnardi, Lorenza Scotti, Giovanni Corrao ( Department of Statistics, University of.

Slides:



Advertisements
Similar presentations
Exploring the behaviours and lifestyles of young non-drinkers A mixed method approach Linda Ng Fat
Advertisements

Alcohol and disease Murielle Bochud, MD, PhD Assistant professor SSPH+ University Institute of Social and Preventive Medicine, Lausanne.
METHODS A systematic review of evidence-based literature was performed using Medline and Cochrane databases. Studies reviewed include randomized controlled.
Chance, bias and confounding
Center for Disease Control and Prevention National Center for Health Statistics National Health Interview Survey Source: Centers for Disease Control and.
Journal Club Alcohol, Other Drugs, and Health: Current Evidence July-August 2007.
Journal Club Alcohol and Health: Current Evidence March-April 2007.
Journal Club Alcohol, Other Drugs, and Health: Current Evidence July–August 2009.
Journal Club Alcohol, Other Drugs, and Health: Current Evidence July–August 2008.
1 Journal Club Alcohol, Other Drugs, and Health: Current Evidence May–June 2011.
Journal Club Alcohol and Health: Current Evidence July–August 2004.
Journal Club Alcohol and Health: Current Evidence January-February 2005.
Lesson #11 Relative Risk and the Odds Ratio. The risk of disease, given exposure, is: The risk of disease, given no exposure, is: The relative risk is.
1 Journal Club Alcohol, Other Drugs, and Health: Current Evidence November–December 2010.
THREE CONCEPTS ABOUT THE RELATIONSHIPS OF VARIABLES IN RESEARCH
Biology in Focus, HSC Course Glenda Childrawi, Margaret Robson and Stephanie Hollis A Search For Better Health Topic 11: Epidemiology.
Journal Club Meena Meka MD. Topic Association of Coffee Drinking with Total and Cause-Specific Mortality.
Are the results valid? Was the validity of the included studies appraised?
1 Journal Club Alcohol, Other Drugs, and Health: Current Evidence January–February 2014.
Meta Analysis MAE Course Meta-analysis The statistical combination and analysis of data from separate and independent studies to determine if there.
Epidemiology The Basics Only… Adapted with permission from a class presentation developed by Dr. Charles Lynch – University of Iowa, Iowa City.
CHP400: Community Health Program- lI Research Methodology STUDY DESIGNS Observational / Analytical Studies Case Control Studies Present: Disease Past:
HEALTH RISKS OF DRINKING Devaunshi Doshi Beloit College, Beloit, Wisconsin Abstract I investigated how heavy drinking affects the human body. I hypothesized.
European Society of Cardiology Cardiovascular diseases in women.
The Meta-analysis: A noon conference presentation Kendall Moseley, MD Kevin Woods, MD With commentary by Hunter Young, MD MHS.
ALCOHOL AND HEALTH Morten Grønbæk National Institute of Public Health Copenhagen, Denmark.
Dr Tatiana Macfarlane University of Aberdeen Dental School Scotland 3rd International Conference on Epidemiology & Public Health 2015 Aspirin use and risk.
Alcohol and Drinking leads to many bad things and causes problems in a family.
Statistics for clinicians Biostatistics course by Kevin E. Kip, Ph.D., FAHA Professor and Executive Director, Research Center University of South Florida,
Are we overestimating the beneficial effects of moderate alcohol consumption in later life? The sick quitter and sick non-starter hypotheses Linda Ng Fat.
Sleep and Maternal Report of Sleep Habits and Temperament Following Prenatal Alcohol Exposure Christopher Sherman & Matthew J. Parisot University of Maine,
1 Journal Club Alcohol, Other Drugs, and Health: Current Evidence September–October 2015.
INDIANA UNIVERSITY BLOOMINGTON D.T. Dibaba MPH, S. Horbal MPH, M. A. Sayegh PhD, MPH Indiana University School of Public Health- Bloomington Department.
Coffee and Cardiovascular Disease
Case-Control Studies Abdualziz BinSaeed. Case-Control Studies Type of analytic study Unit of observation and analysis: Individual (not group)
Instructor Resource Chapter 15 Copyright © Scott B. Patten, Permission granted for classroom use with Epidemiology for Canadian Students: Principles,
POPLHLTH 304 Regression (modelling) in Epidemiology Simon Thornley (Slides adapted from Assoc. Prof. Roger Marshall)
Types of Studies. Aim of epidemiological studies To determine distribution of disease To examine determinants of a disease To judge whether a given exposure.
Taking a life-course perspective – does previous drinking matter? Annie Britton Research Department of Epidemiology and Public Health University College.
Case control & cohort studies
Flow Diagram of the Trial Selection Process Jeffrey S. Berger et al, JAMA. 2006;295:
Meta-analysis of observational studies Nicole Vogelzangs Department of Psychiatry & EMGO + institute.
Alcohol-related mortality in European countries II Working Meeting on Adult Premature Mortality in European Union Warsaw, October 2006.
META ANALYSIS “ statistical alchemy of the 21 st century” Presented by Sanghati Mukherjee.
Methodological quality assessment of observational studies Nicole Vogelzangs Department of Psychiatry & EMGO + institute.
Chapter 9: Case Control Studies Objectives: -List advantages and disadvantages of case-control studies -Identify how selection and information bias can.
Alcohol, Other Drugs, and Health: Current Evidence July–August 2017
Brady Et Al., "sequential compression device compliance in postoperative obstetrics and gynecology patients", obstetrics and gynecology, vol. 125, no.
Is the freedom from Cognitive Impairment really at hand?
The Rise and Fall of Hormone Replacement Therapy
Supplementary Table 1. PRISMA checklist
Overview of the GRADE approach – selected slides
PHP 1540: Alcohol Use and Misuse October 11, 2012
Measures of Association
Epidemiologic Measures Of Association
THE ROLE OF DIFFERENT TYPES OF ALCOHOL ON THE RISK OF SELECTED CANCERS
Lecture 4: Meta-analysis
دانشگاه علوم پزشکی بوشهر دانشکده بهداشت
Coffee drinking and leukocyte telomere length: A meta-analysis
Lecture 3: Introduction to confounding (part 1)
اپيدميولوژي مصرف الكل در ايران و جهان
Jürgen Rehm 1,2,3 & Benjamin Taylor 2
Alcohol drinking patterns and liver cirrhosis risk: analysis of the prospective UK Million Women Study  Rachel F Simpson, MB BCh, Carol Hermon, MSc, Bette.
Epidemiology MPH 531 Analytic Epidemiology Case control studies
Evaluating Effect Measure Modification
Alcohol, Other Drugs, and Health: Current Evidence
The risk of cardiovascular events with increased apolipoprotein CIII: A systematic review and meta-analysis  Moritz C. Wyler von Ballmoos, MD, MPH, Bernhard.
Cohort Study.
Confounders.
Alcohol, Other Drugs, and Health: Current Evidence May–June 2019
Presentation transcript:

Binge drinking and cardiovascular disease: a meta-analysis Vincenzo Bagnardi, Lorenza Scotti, Giovanni Corrao ( Department of Statistics, University of Milan- Bicocca, Milan, Italy) Carlo La Vecchia (Laboratory of Epidemiology, Istituto di Ricerche Farmacologiche Mario Negri, Milan, Italy) Witold Zatonski (Department of Epidemiology and Cancer Prevention, Marie Sklodowska-Curie Memorial Cancer Centre, Warsaw)

Introduction There is convincing evidence that moderate alcohol consumption protects against the risk of coronary heart disease (CHD). On the other hand, it has been consistently shown that heavy alcohol consumption and problem drinking are associated with increased risk of CHD and other cardiovascular diseases. The combination of protective and harmful effects results in a U- or J-shaped dose-response relationship between alcohol and CHD.

Introduction Alcohol and coronary heart disease: a meta-analysis [Corrao et al., 2000]. RR

Introduction Evidence from Eastern Europe of a positive association between alcohol and cardiovascular diseases has challenged the prevailing view that drinking is cardioprotective. Decreasing cardiovascular mortality rates have been observed in Russia after the 1985 anti-alcohol campaign and in Poland in time of alcohol rationing, during the martial law in This differential effect could be related to the particular conseguences of binge drinking, which is common in Eastern Europe.

Introduction Different patterns of alcohol intake could interact with the dose-related effect. Alcohol and coronary heart disease: a meta-analysis [Corrao et al., 2000]. RR

With the main aim to evaluate whether drinking pattern modifies the effect of alcohol intake on the risk of CVD, we have summarized the available data on this topic using a meta-analytic approach. Binge drinking and cardiovascular disease: a meta-analysis Investigate the role of drinking pattern in modifying the effect of the amount of alcohol consumed is not straightforward. Only sparse data are still available on this topic.

Outcome investigated Outcome investigated: Cardiovascular Disease Cerebrovascular Disease Hemorrhagic stroke Ischemic stroke Coronary Heart Disease (CHD)

Exposure definition Due to the lack of a standard definition of pattern of alcohol drinking, the search focused on several terms: drinking pattern, irregular drinking, binge drinking, problem drinking, alcoholic intoxication, heavy episodic drinking, and hangover

case–control or cohort studies published as an original article. findings expressed as relative risk, considering different combinations of quantity and frequency of alcohol intake OR directly considering the drinking pattern (e.g. binging or irregular heavy drinking). precision of RR for each exposure category reported. considered abstainers as reference category. Inclusion criteria

Number of occasions in the past week =N Usual number of drinks they consumed per occasion =D g/day = 12.5 x [(N x D) / 7] g/day RR 1.0 Dose-response analysis (usual analysis)

No attempt to separate the effect of different patterns of drinking (i.e. Regular vs Irregular) Number of occasions in the past week =N Usual number of drinks they consumed per occasion =D g/day = 12.5 x [(N x D) / 7] g/day RR 1.0

Number of occasions in the past week =N Usual number of drinks they consumed per occasion =D g/week = 12.5 x (N x D) if N>=3:Regular drinkers if N<3:Irregular drinkers Different patterns Irregular Regular g/week RR 1.0 Hypothesis: Pattern as an effect modifier.

Number of occasions in the past week =N Usual number of drinks they consumed per occasion =D g/week = 12.5 x (N x D) if N>=3:Regular drinkers if N<3:Irregular drinkers Different patterns Irregular Regular g/week RR 1.0 Hypothesis: Pattern as an effect modifier. Few studies report this stratification

To estimate the dose-response relationship between cumulative weekly alcohol intake in regular and irregular drinkers, and to test the possible interaction between pattern and the relationship, several meta-regression non linear models (fractional polynomial models) were fitted. Analysis A g/week RR 1.0 Irregular Regular

Irregular Heavy Drinkers Regular Heavy Drinkers g/week RR 1.0 Irregular Regular Assumption: Irregular Heavy Drinkers could be considered as binge drinkers. Analysis B No transformation of data was performed: we simply used, in the calculation of pooled estimate, the RRs of the categories defined by the authors as Regular Heavy Drinkers, Irregular Heavy Drinkers or Binge Drinkers. + Binge drinkers (reported directly)

Assumption: Irregular Heavy Drinkers could be considered as binge drinkers. Analysis B Irregular Heavy Drinkers Regular Heavy Drinkers g/week RR Binge drinkers (reported directly) RR 1.0 vs. abstainers vs. abstainers No transformation of data was performed: we simply used, in the calculation of pooled estimate, the RRs of the categories defined by the authors as Regular Heavy Drinkers, Irregular Heavy Drinkers or Binge Drinkers.

Main characteristics of the 11 included studies.

Meta-regression dose-response relation between weekly alcohol intake and relative risk of stroke in regular and irregular drinkers. Results (Analysis A) p-value interaction parameters pattern*dose: n.s.

Results (Analysis B) Forest plots of drinking pattern and stroke. Regular Heavy Drinkers vs Abstainers Pooled RR: 1.2 ( ) Irregular Heavy Drinkers and Binge vs Abstainers Pooled RR: 0.9 ( ) RR

Results (Analysis B) Forest plots of drinking pattern and stroke. Regular Heavy Drinkers vs Abstainers Pooled RR: 1.2 ( ) Irregular Heavy Drinkers and Binge vs Abstainers Pooled RR: 0.9 ( ) RR = p-value homogeneity test: n.s.

Meta-regression dose-response relation between weekly alcohol intake and relative risk of CHD in regular and irregular drinkers. Results (Analysis A) p-value interaction parameters pattern*dose: <0.05

Results (Analysis B) Forest plots of drinking pattern and CHD. Regular Heavy Drinkers vs Abstainers Pooled RR: 0.7 ( ) Irregular Heavy Drinkers and Binge vs Abstainers Pooled RR: 1.1 ( )

Results (Analysis B) Forest plots of drinking pattern and CHD. Regular Heavy Drinkers vs Abstainers Pooled RR: 0.7 ( ) Irregular Heavy Drinkers and Binge vs Abstainers Pooled RR: 1.1 ( )  p-value homogeneity test: <0.05

Results (Analysis B) Forest plots of drinking pattern and CHD. Regular Heavy Drinkers vs Abstainers Pooled RR: 0.7 ( ) Irregular Heavy Drinkers and Binge vs Abstainers Pooled RR: 1.1 ( ) = Pooled RR Irregular Heavy drinkers and Binge vs Regular Heavy drinkers : 1.5 (1.3 – 1.8) [1.5 in Men / 1.4 in Women]

Not included studies Other studies reporting estimates for proxy of binge drinking ( due to the heterogeneity of the exposure definition and reference category, no pooled estimates were computed ).

Conclusion  Drinking pattern modifies the action of alcohol intake on the CHD risk.  The well established protective effect of alcohol on the CHD risk was confirmed for regular drinkers.  Compared with abstainers, binge and heavy irregular drinkers are at increased risk of CHD.

Limits  Few epidemiological studies included information to test the hypothesis that drinking pattern could modify the protective effect of alcohol on the risk of CVD.  Publication bias.  Residual confounding due to socio-economic status.  Heterogeneity in the exposure definition.