Literature DB >> 24988268

Nonresponse bias in survey estimates of alcohol consumption and its association with harm.

Deborah A Dawson1, Risë B Goldstein2, Roger P Pickering2, Bridget F Grant2.   

Abstract

OBJECTIVE: Selective nonresponse represents a major source of potential bias in survey-based estimates of alcohol consumption and its association with harm. This study examined whether consumption differs for respondents and nonrespondents after correcting for their sociodemographic differences.
METHOD: This study compared baseline consumption among initial respondents who did (n = 34,653) and did not (n = 5,306) respond to a 3-year follow-up interview in a prospective study of the U.S. general population. Differences in consumption measures were presented before and after adjustment or sociodemographic differences, and interactions of nonresponse with consumption were assessed in models predicting various types of harm.
RESULTS: After we adjusted for sociodemographic differences and factored in the overall level of nonresponse (13.3%), the degree to which the prevalence of drinking was underestimated in the total population was only 1.6%, and the extent to which consumption was overestimated among drinkers lay in the range of 1.7% to 2.4%. There was no consistent evidence that nonresponse moderated the association between consumption and alcohol-related harm. Sociodemographic differentials in nonresponse generally matched those reported for cross-sectional studies in the literature.
CONCLUSIONS: The extent of nonresponse bias in survey estimates of alcohol consumption should not affect drinking guidelines and planning for prevention and treatment programs. The findings of this study are supportive of study designs that have been used to assess nonresponse bias, including the use of registry data on alcohol-related harms and secondary nonresponse data from prospective studies.

Entities:  

Mesh:

Year:  2014        PMID: 24988268      PMCID: PMC4108608          DOI: 10.15288/jsad.2014.75.695

Source DB:  PubMed          Journal:  J Stud Alcohol Drugs        ISSN: 1937-1888            Impact factor:   2.582


  27 in total

1.  Non-response bias in a sample survey on alcohol consumption.

Authors:  Viviënne M H C J Lahaut; Harrie A M Jansen; Dike van de Mheen; Henk F L Garretsen
Journal:  Alcohol Alcohol       Date:  2002 May-Jun       Impact factor: 2.826

2.  Estimating non-response bias in a survey on alcohol consumption: comparison of response waves.

Authors:  Viviënne M H C J Lahaut; Harrie A M Jansen; Dike van de Mheen; Henk F L Garretsen; Jacqueline E E Verdurmen; Ad van Dijk
Journal:  Alcohol Alcohol       Date:  2003 Mar-Apr       Impact factor: 2.826

3.  Psychopathology and attrition in the epidemiologic catchment area surveys.

Authors:  W W Eaton; J C Anthony; S Tepper; A Dryman
Journal:  Am J Epidemiol       Date:  1992-05-01       Impact factor: 4.897

4.  Non-response bias in alcohol and drug population surveys.

Authors:  Jinhui Zhao; Tim Stockwell; Scott Macdonald
Journal:  Drug Alcohol Rev       Date:  2009-11

5.  Understanding nonresponse to the 2007 Medicare CAHPS survey.

Authors:  David J Klein; Marc N Elliott; Amelia M Haviland; Debra Saliba; Q Burkhart; Carol Edwards; Alan M Zaslavsky
Journal:  Gerontologist       Date:  2011-06-23

6.  Non-response bias in a lifestyle survey.

Authors:  A Hill; J Roberts; P Ewings; D Gunnell
Journal:  J Public Health Med       Date:  1997-06

7.  Sociodemographic and psychiatric determinants of attrition in the Netherlands Study of Depression and Anxiety (NESDA).

Authors:  Femke Lamers; Adriaan W Hoogendoorn; Johannes H Smit; Richard van Dyck; Frans G Zitman; Willem A Nolen; Brenda W Penninx
Journal:  Compr Psychiatry       Date:  2011-03-11       Impact factor: 3.735

8.  Participants and non-participants of different categories in a health survey. A cross-sectional register study.

Authors:  C G Ohlson; B Ydreborg
Journal:  Scand J Soc Med       Date:  1985

9.  Characteristics of non-respondents in a US national longitudinal survey on drinking and intimate partner violence.

Authors:  Raul Caetano; Suhasini Ramisetty-Mikler; Christine McGrath
Journal:  Addiction       Date:  2003-06       Impact factor: 6.526

10.  Methodological issues in measuring alcohol use.

Authors:  Deborah A Dawson
Journal:  Alcohol Res Health       Date:  2003
View more
  11 in total

1.  The 3-Year Course of Multiple Substance Use Disorders in the United States: A National Longitudinal Study.

Authors:  Sean Esteban McCabe; Brady T West
Journal:  J Clin Psychiatry       Date:  2017-05       Impact factor: 4.384

2.  Nosologic Comparisons of DSM-IV and DSM-5 Alcohol and Drug Use Disorders: Results From the National Epidemiologic Survey on Alcohol and Related Conditions-III.

Authors:  Risë B Goldstein; S Patricia Chou; Sharon M Smith; Jeesun Jung; Haitao Zhang; Tulshi D Saha; Roger P Pickering; W June Ruan; Boji Huang; Bridget F Grant
Journal:  J Stud Alcohol Drugs       Date:  2015-05       Impact factor: 2.582

3.  Intersections of poverty, race/ethnicity, and sex: alcohol consumption and adverse outcomes in the United States.

Authors:  Joseph E Glass; Paul J Rathouz; Maurice Gattis; Young Sun Joo; Jennifer C Nelson; Emily C Williams
Journal:  Soc Psychiatry Psychiatr Epidemiol       Date:  2017-03-27       Impact factor: 4.328

4.  Multiple DSM-5 substance use disorders: A national study of US adults.

Authors:  Sean Esteban McCabe; Brady T West; Emily M Jutkiewicz; Carol J Boyd
Journal:  Hum Psychopharmacol       Date:  2017-07-27       Impact factor: 1.672

5.  Selective nonresponse bias in population-based survey estimates of drug use behaviors in the United States.

Authors:  Sean Esteban McCabe; Brady T West
Journal:  Soc Psychiatry Psychiatr Epidemiol       Date:  2015-09-16       Impact factor: 4.328

6.  Unravelling the alcohol harm paradox: a population-based study of social gradients across very heavy drinking thresholds.

Authors:  Dan Lewer; Petra Meier; Emma Beard; Sadie Boniface; Eileen Kaner
Journal:  BMC Public Health       Date:  2016-07-19       Impact factor: 3.295

7.  Assessment of Non-Response Bias in Estimates of Alcohol Consumption: Applying the Continuum of Resistance Model in a General Population Survey in England.

Authors:  Sadie Boniface; Shaun Scholes; Nicola Shelton; Jennie Connor
Journal:  PLoS One       Date:  2017-01-31       Impact factor: 3.240

8.  Adjustment for survey non-representativeness using record-linkage: refined estimates of alcohol consumption by deprivation in Scotland.

Authors:  Emma Gorman; Alastair H Leyland; Gerry McCartney; Srinivasa Vittal Katikireddi; Lisa Rutherford; Lesley Graham; Mark Robinson; Linsay Gray
Journal:  Addiction       Date:  2017-04-25       Impact factor: 6.526

9.  Correcting for non-participation bias in health surveys using record-linkage, synthetic observations and pattern mixture modelling.

Authors:  Linsay Gray; Emma Gorman; Ian R White; S Vittal Katikireddi; Gerry McCartney; Lisa Rutherford; Alastair H Leyland
Journal:  Stat Methods Med Res       Date:  2019-06-11       Impact factor: 2.494

10.  Social Inequalities in Harmful Drinking and Alcohol-Related Problems Among Swedish Adolescents.

Authors:  Siri Thor; Patrik Karlsson; Jonas Landberg
Journal:  Alcohol Alcohol       Date:  2019-01-09       Impact factor: 2.826

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.