• Entry to medical school a the gender question. What has happened?

      O‘Flynn, S; Mills, A; Fitzgerald, AP (Irish Medical Journal, 2013-09)
    • Gender awareness, symptom expressions and Irish mental health-care provision

      Bergin, Michael; Wells, John S.G.; Owen, Sara; Department of Nursing, Waterford Institute of Technology. (Journal of Gender Studies, 2014-05)
    • Gender specific trends in alcohol use: cross-cultural comparisons from 1998 to 2006 in 24 countries and regions

      Simons-Morton, Bruce G.; Farhat, Tilda; ter Bogt, Tom F.M.; Hublet, Anne; Kuntsche, Emmanuel; Nic Gabhainn, Saoirse; Godeau, Emmanuelle; Kokkevi, Anna; HBSC Risk Behaviour Focus Group; Prevention Research Branch, Eunice Kennedy Shriver National Institute of Child Health and Human Development, (Birkhäuser Verlag, Basel, 2009)
    • Sex dependent risk factors for mortality after myocardial infarction: individual patient data meta-analysis

      van Loo, Hanna M; van den Heuvel, Edwin R; Schoevers, Robert A; Anselmino, Matteo; Carney, Robert M; Denollet, Johan; Doyle, Frank; Freedland, Kenneth E; Grace, Sherry L; Hosseini, Seyed H; et al. (2014-12-17)
      Abstract Background Although a number of risk factors are known to predict mortality within the first years after myocardial infarction, little is known about interactions between risk factors, whereas these could contribute to accurate differentiation of patients with higher and lower risk for mortality. This study explored the effect of interactions of risk factors on all-cause mortality in patients with myocardial infarction based on individual patient data meta-analysis. Methods Prospective data for 10,512 patients hospitalized for myocardial infarction were derived from 16 observational studies (MINDMAPS). Baseline measures included a broad set of risk factors for mortality such as age, sex, heart failure, diabetes, depression, and smoking. All two-way and three-way interactions of these risk factors were included in Lasso regression analyses to predict time-to-event related all-cause mortality. The effect of selected interactions was investigated with multilevel Cox regression models. Results Lasso regression selected five two-way interactions, of which four included sex. The addition of these interactions to multilevel Cox models suggested differential risk patterns for males and females. Younger women (age <50) had a higher risk for all-cause mortality than men in the same age group (HR 0.7 vs. 0.4), while men had a higher risk than women if they had depression (HR 1.4 vs. 1.1) or a low left ventricular ejection fraction (HR 1.7 vs. 1.3). Predictive accuracy of the Cox model was better for men than for women (area under the curves: 0.770 vs. 0.754). Conclusions Interactions of well-known risk factors for all-cause mortality after myocardial infarction suggested important sex differences. This study gives rise to a further exploration of prediction models to improve risk assessment for men and women after myocardial infarction.
    • Unequal status, unequal treatment: the gender restructing of welfare: Ireland

      Yeates,Nicola; Stoltz, Pauline; Women's Education Research and Resource Centre (Women's Education Research and Resource Centre, University College Dublin, 1995-07)