Library Bulletin - Journal Articles - December 2010
Back to Bulletin Articles Index
STATISTICS
EKHOLM, Ola and GUNDGAARD, Jens and others. The effect of health, socio-economic position, and mode of data collection on non-response in health interview surveys. Scandinavian Journal of Public Health Vol 38, No 7 - 2010: 699-706
Abstract:
Aims: To investigate the relationship between potential explanatory factors (socio-economic factors and health) and non-response in two general population health interview surveys (face-to-face and telephone), and to compare the effects of the two interview modes on non-response patterns. Methods: Data derives from The Danish Health Interview Survey 2000 (face-to-face interview) and The Funen County Health Survey 2000/2001 (telephone interview). Data on all invited individuals were obtained from administrative registers and linked to survey data at individual level. Multiple logistic regression analyses were used to examine associations between potential explanatory factors and non-response. Results: The overall response rate was higher in the face-to-face interview survey (74.5%) than in the telephone survey (69.2%). Refusal was the most common reason for non-response and the same factors were generally associated with non-response in both modes of interview. The non-response rate was high among persons with low socio-economic position. No significant associations between health and non-response were found. Conclusions: Health status does not play a systematic role for non-response rates in health interview surveys, but the non-response rate is higher in lower socio-economic groups. Analyses of non-response should be performed to understand the implications of survey findings.
NAESS, Oyvind and LEYLAND, Alastair H. Analysing the effect of area of residence over the life course in multilevel epidemiology. Scandinavian Journal of Public Health Vol 38, supplement 5 - 2010: 119-126
Abstract:
Background: In this paper we present multilevel models of individuals’ residential history at multiple time points through the life course and their application and discuss some advantages and disadvantages for their use in epidemiological studies. Methods: Literature review of research using longitudinal multilevel models in studies of neighbourhood effects, statistical multilevel models that take individuals’ residential history into account, and the application of these models in the Oslo mortality study. Results: Measures of variance have been used to investigate the contextual impact of membership to collectives, such as area of residence, at several time points. The few longitudinal multilevel models that have been used suggest that early life area of residence may have an effect on mortality independently of residence later in life although the proportion of variation attributable to area level is small compared to individual level. The following multilevel models have been developed: simple multilevel models for each year separately, a multiple membership model, a cross-classified model, and finally a correlated cross-classified model. These models have different assumptions regarding the timing of influence through the life course. Conclusions: To fully recognise the origin of adult chronic diseases, factors at all stages of the life course at both individual and area level needs to be considered in order to avoid biased estimates. Important challenges in making life course residential data available for research and assessing how changing administrative coding over time reflect contextual impact need to be overcome before these models can be implemented as normal practice in multilevel epidemiology.