The validity of self-reported smoking: a review and meta-analysis.

Abstract

OBJECTIVES. The purpose of this study was to identify circumstances in which biochemical assessments of smoking produce systematically higher or lower estimates of smoking than self-reports. A secondary aim was to evaluate different statistical approaches to analyzing variation in validity estimates. METHODS. Literature searches and personal inquiries identified 26 published reports containing 51 comparisons between self-reported behavior and biochemical measures. The sensitivity and specificity of self-reports of smoking were calculated for each study as measures of accuracy. RESULTS. Sensitivity ranged from 6% to 100% (mean = 87.5%), and specificity ranged from 33% to 100% (mean = 89.2%). Interviewer-administered questionnaires, observational studies, reports by adults, and biochemical validation with cotinine plasma were associated with higher estimates of sensitivity and specificity. CONCLUSIONS. Self-reports of smoking are accurate in most studies. To improve accuracy, biochemical assessment, preferably with cotinine plasma, should be considered in intervention studies and student populations.

The Association of Duration of Residence in the United States with Cardiovascular Disease Risk Factors Among South Asian Immigrants

“…Self-reports of hypertension, hypercholesterolemia, and diabetes are likely related to one's access to health care, though we controlled statistically for variations in access to care by controlling for health insurance status and having a usual source of care. Furthermore, several studies have reported agreement between self-reported diabetes, hypertension, smoking, and alcohol consumption and medical record data or biochemical measures [72][73][74][75]. There is less agreement between selfreported high cholesterol and medical record data [76].…”

Nicotine and cotinine in adults’ urine: The German Environmental Survey 1998

“…Measurements of nicotine-related biomarkers have often been used to validate questionnaire-derived data on smoking and exposure to ETS (Patrick et al, 1994). However, systematic multivariate modelling of potential factors influencing these biomarkers including estimation of the effect size in population-based samples is still missing.…”

Tobacco use in sub-Sahara Africa: Estimates from the demographic health surveys

“…Among cigarette smokers, the number of cigarettes used in the last day measures intensity (ranging from 0 to 20). Although U.S. studies find that self-reported smoking is generally accurate (Patrick et al, 1994), the validity of such items in low-income nations is less clear, and the items may reflect differential reporting by SES. Lacking physiological measures, survey responses remain the commonly accepted source of nearly all data on global patterns of tobacco prevalence.…”