Attrition in the Swiss Household Panel: Is change associated with drop-out?

This study examines the importance of change in characteristics and circumstances ofhouseholds and household members for contact and cooperation patterns. The literaturesuggests that there might be an underrepresentation of change in panel studies, becauserespondents facing more changes would be more likely to drop out. We approach this problemby analysing whether previous changes are predictive of later attrition or temporary drop-out,using eleven waves of the Swiss Household Panel (1999-2009). Our analyses supportprevious findings to some extent. Changes in household composition, employment status andsocial involvement as well as moving are associated mainly with attrition and less withtemporary drop-out. These changes affect obtaining cooperation rather than obtaining contact,and tend to increase attrition.

Application of discriminant function analysis and change-point problem in dating volcanic ashes

The application of Discriminant function analysis (DFA) is not a new idea in the studyof tephrochrology. In this paper, DFA is applied to compositional datasets of twodifferent types of tephras from Mountain Ruapehu in New Zealand and MountainRainier in USA. The canonical variables from the analysis are further investigated witha statistical methodology of change-point problems in order to gain a betterunderstanding of the change in compositional pattern over time. Finally, a special caseof segmented regression has been proposed to model both the time of change and thechange in pattern. This model can be used to estimate the age for the unknown tephrasusing Bayesian statistical calibration

Predictive value of Glasgow Coma Scale after brain trauma: change in trend over the past ten years.

BACKGROUND: Age and the Glasgow Coma Scale (GCS) score on admission are considered important predictors of outcome after traumatic brain injury. We investigated the predictive value of the GCS in a large group of patients whose computerised multimodal bedside monitoring data had been collected over the previous 10 years. METHODS: Data from 358 subjects with head injury, collected between 1992 and 2001, were analysed retrospectively. Patients were grouped according to year of admission. Glasgow Outcome Scores (GOS) were determined at six months. Spearman's correlation coefficients between GCS and GOS scores were calculated for each year. RESULTS: On average 34 (SD: 7) patients were monitored every year. We found a significant correlation between the GCS and GOS for the first five years (overall 1992-1996: r = 0.41; p<0.00001; n = 183) and consistent lack of correlations from 1997 onwards (overall 1997-2001: r = 0.091; p = 0.226; n = 175). In contrast, correlations between age and GOS were in both time periods significant and similar (r = -0.24 v r = -0.24; p<0.002). CONCLUSIONS: The admission GCS lost its predictive value for outcome in this group of patients from 1997 onwards. The predictive value of the GCS should be carefully reconsidered when building prognostic models incorporating multimodality monitoring after head injury.

Protocol for the modeling the epidemiologic transition study: a longitudinal observational study of energy balance and change in body weight, diabetes and cardiovascular disease risk.

ABSTRACT: BACKGROUND: The prevalence of obesity has increased in societies of all socio-cultural backgrounds. To date, guidelines set forward to prevent obesity have universally emphasized optimal levels of physical activity. However there are few empirical data to support the assertion that low levels of energy expenditure in activity is a causal factor in the current obesity epidemic are very limited. METHODS: The Modeling the Epidemiologic Transition Study (METS) is a cohort study designed to assess the association between physical activity levels and relative weight, weight gain and diabetes and cardiovascular disease risk in five population-based samples at different stages of economic development. Twenty-five hundred young adults, ages 25-45, were enrolled in the study; 500 from sites in Ghana, South Africa, Seychelles, Jamaica and the United States. At baseline, physical activity levels were assessed using accelerometry and a questionnaire in all participants and by doubly labeled water in a subsample of 75 per site. We assessed dietary intake using two separate 24-h recalls, body composition using bioelectrical impedance analysis, and health history, social and economic indicators by questionnaire. Blood pressure was measured and blood samples collected for measurement of lipids, glucose, insulin and adipokines. Full examination including physical activity using accelerometry, anthropometric data and fasting glucose will take place at 12 and 24 months. The distribution of the main variables and the associations between physical activity, independent of energy intake, glucose metabolism and anthropometric measures will be assessed using cross-section and longitudinal analysis within and between sites. DISCUSSION: METS will provide insight on the relative contribution of physical activity and diet to excess weight, age-related weight gain and incident glucose impairment in five populations' samples of young adults at different stages of economic development. These data should be useful for the development of empirically-based public health policy aimed at the prevention of obesity and associated chronic diseases.