One study in particular reported that the greatest gender difference in children's PA was found in institutional settings, such as schools, where children relied on self-organized activities during recess and after-school day care [ 13].
Sample size calculations based on the assumption that about 30% of men and women would have a pre-AMI diagnosis of CHD suggested that an equivalent sample of 165 men and 165 women would be sufficient to identify a 10% or greater gender difference in the rate of pre-AMI diagnoses of CHD.
The greatest gender differences were found in Italy and the Netherlands (M∆ = .77; SEItaly = .13, SENetherlands = .17), and the lowest, but still significant, in France (M∆ = .49; SE = .14), revealing that boys showed less positive attitudes toward reading than girls.
Much greater gender differences were found in East and Southeast Asian in countries such as South Korea, Indonesia, and China, compared to Europe and the U.S. [ 2].
The greatest gender differences in morbidity with a preponderance for females were for the diagnoses Depression and Anxiety disorders, Osteoarthritis, Migraine, Insomnia, Asthma and COPD, Thyroid gland disorders and Cystitis.
Greater gender differences in the time allocated to market and nonmarket work are found in Italy relative to either France or the U.S. Cohabitation as a precursor or alternative to (first) marriage has increased dramatically in Europe and English-speaking countries outside Europe such as the United States, Canada, Australia, and New Zealand (Waite et al. 2000; Kiernan 2001; Nazio 2008).
The higher prevalence of CKD in women could thus explain, to a great extent, the gender difference in mortality.
The performance levels documented within the existing studies justify the expectation of great gender-specific differences despite self-selection and external selection processes (Baumert et al. 2001).
Gender medicine which investigates and incorporates the sometimes great gender-specific differences regarding an illness's symptoms, treatment and course is the first step to classify patient groups in the process towards personalised medicine.
