Information bias of social gradients in sickness absence: a comparison of self-report data in the Norwegian Mother and Child Cohort Study (MoBa) and data in national registries

• Published in: BMC public health Vol. 18; no. 1; p. 1275
• Main Authors: Kristensen, Petter, Corbett, Karina, Mohn, Ferdinand A, Hanvold, Therese N, Mehlum, Ingrid S
• Format: Journal Article
• Language: English
• Published: England BioMed Central 20.11.2018; BMC
• Subjects: Bias; Cohort analysis; Confidence intervals; Data processing; Data quality; Differential error (misclassification); Education; Education level; Educational Status; Epidemiology; Error analysis; Female; Humans; Information bias; Norway; Pregnancy; Prospective Studies; Public health; Questionnaires; Register data; Registries; Regression analysis; Risk; Self Report; Sick leave; Sick Leave - statistics & numerical data; Socioeconomic factors; Statistical analysis; Studies; Womens health; Norway; Differential error (misclassification); Pregnancy; Register data; Education level; Information bias; Social inequalities in health; Data quality; Sickness absence; The Norwegian Mother and Child Cohort Study (MoBa); Self-report data
• ISSN: 1471-2458; 1471-2458
• DOI: 10.1186/s12889-018-6208-9

Measurement error in self-report questionnaires is a common source of bias in epidemiologic studies. The study aim was to assess information bias of the educational gradient in sickness absence among participants in the Norwegian Mother and Child Cohort Study (MoBa), comparing self-report data with national register data. MoBa is a national prospective cohort study. The present study included 49,637 participants, born 1967-1976, who gave birth 2000-2009. The highest completed education level was recorded in categories and as educational years. Sickness absence was defined as one or more spell lasting more than 16 days between pregnancy weeks 13 and 30. We computed sickness absence risk in mid-pregnancy in strata of education level. Associations between completed educational years and sickness absence were estimated as risk differences in binomial regression and compared between self-report and register data. In additional analyses, we aimed to explain discrepancies between estimates from the two data sources. The overall registry-based sickness absence risk was 0.478 and decreased for increasingly higher education in a consistent fashion, yielding an additive risk difference in association with one additional education year of - 0.032 (95% confidence interval - 0.035 to - 0.030). The self-report risk was lower (0.307) with a corresponding risk difference of only - 0.013 (95% confidence interval - 0.015 to - 0.011). The main explanation of the lower risk difference in the self-report data was a tendency for mothers in low education categories to omit reporting sickness absence in the questionnaire. A plausible explanation for the biased self-report association is complexity of the sickness absence question and a resulting educational gradient in non-response. As shown for sickness absence in mid-pregnancy in the present study, national registries could be a preferred alternative to self-report questionnaires.