Are the educational differences in incidence of cardiovascular disease explained by underlying familial factors? A twin study.

To isolate the effect of education from the influence of potential underlying factors, we investigated the association of education with the risk of cardiovascular disease (CVD) and ischemic heart disease (IHD) using twin data to adjust for familial factors shared within twins, including genetic make-up and childhood environment. The study was based on data from the Danish Twin Registry linked to administrative and heath registers in Statistics Denmark. A total of 11,968 monozygotic and 20,464 dizygotic same sexed twins were followed from 1980 to 2009, including more than 8000 events of CVD.

Are familial factors underlying the association between socioeconomic position and prescription medicine? A register-based study on Danish twins.

Objectives: Although well established, the association between socioeconomic position and health and health behaviour is not clearly understood, and it has been speculated that familial factors, for example, dispositional factors or exposures in the rearing environment, may be underlying the association. The objective was to compare prescription fillings within twin pairs who are partly or fully genetically identical and share childhood exposures.

Design: Twin cohort study.

Matched survival data in a co-twin control design.

When using the co-twin control design for analysis of event times, one needs a model to address the possible within-pair association. One such model is the shared frailty model in which the random frailty variable creates the desired within-pair association. Standard inference for this model requires independence between the random effect and the covariates.

Preterm birth and birthweight-for-gestational age among immigrant women in Denmark 1978-2007: a nationwide registry study.

Background: We sought to examine whether age at immigration and length of residence were associated with preterm and small-for-gestational age (SGA) delivery among immigrant women in Denmark.

Methods: We included all live singleton deliveries from Danish-born women (1626880) and women from the five largest immigrant groups (68936) from 1978 to 2007. Data from the Danish Medical Birth Registry were linked to: parental country of origin, length of residence and age at immigration.

Does computer use affect the incidence of distal arm pain? A one-year prospective study using objective measures of computer use.

Purpose: To study how objectively recorded mouse and keyboard activity affects distal arm pain among computer workers.

Methods: Computer activities were recorded among 2,146 computer workers. For 52 weeks mouse and keyboard time, sustained activity, speed and micropauses were recorded with a software program installed on the participants' computers.

Are low Danish fertility rates explained by changes in timing of births?

Aims: The most commonly used indicator of fertility, the period total fertility rate (TFR(p)), tends to underestimate actual fertility when women delay childbearing. The objective of this study was to examine to which extent fluctuations in Danish fertility rates result from changes in timing of births and, thus, whether the conventional TFR(p) is a distorted indicator of fertility quantum. In addition, we investigated whether such changes in timing explained the observed regional differences in the TFR(p) in Denmark.

SAS and R functions to compute pseudo-values for censored data regression.

Recently, in a series of papers, a method based on pseudo-values has been proposed for direct regression modeling of the survival function, the restricted mean and cumulative incidence function with right censored data. The models, once the pseudo-values have been computed, can be fit using standard generalized estimating equation software. Here we present SAS macros and R functions to compute these pseudo-values.

Non-parametric estimation and model checking procedures for marginal gap time distributions for recurrent events.

For recurrent events there is evidence that misspecification of the frailty distribution can cause severe bias in estimated regression coefficients (Am. J. Epidemiol 1998; 149:404-411; Statist.