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Physiological and pathological processes differ in men and women, depending on factors such as sex and sociological and anthropological characteristics. However, many diseases are still approached from a masculine point of view. In this respect, ischemic heart disease is one of the diseases that most clearly reflects biological differences and social inequalities. In women, the disease presents at a more advanced age, and presentation is frequently atypical with a higher prevalence of comorbidities and greater severity. Consequently, treatment and outcome differ from those in men. Additionally, women differ in their knowledge, and beliefs regarding ischemic heart disease, as well as in their attitudes at symptom onset. Therefore, clinical practice should place significant emphasis on all these aspects in order to avoid inequalities between men and women in the correct diagnosis, treatment, prevention, and rehabilitation of ischemic heart disease.

Background and Objective: Despite the number of plans leading to lose weight among individuals in the developed countries, the prevalence of obesity has increased since 1980. The knowledge of ponderal evolution in a given population is very important because the adverse effects of obesity vary greatly among individuals and populations. The objective of the present paper was to determine the modifications in the different degrees of body adiposity in a population in Catalunya., Patients and Methods: A measurement was made of weight and height of 24554 users aged over 14 years (10595 males and 13959 females) attended at four basic health areas (BHA): Girona 1, Girona 4, Salt and Camprodon, and a Primary Health Center (PHC) in the Girona province, for a five-year period, 1995-1999. The prevalence of the different degrees of obesity was compared with that obtained in a previous study with 6373 individuals during the 1986-1989 period (4,579 males and 1794 females)., Results: The prevalence of women with overweight (defined as a body mass index [BMI] > 25 kg/m2) increased from 7.3% (1986-1989, study 0) to 17.6% (1995-1999, study 1) for women aged 15 to 24 years ( p < 0.001), from 17.9 % to 28.1% for women aged 25 to 34 years (p < 0.001), and from 37.5% to 44.7 % for women aged 35 to 44 years (p < 0.001). In the latter age group, the proportion of women with obesity (BMI > 30 kg/m2) increased from 6.9% to 12.9%. Similar trends were observed among men, and the change in the 35-44 year age group (from 10.5 % of obese men to 16% [p < 0.001]), and 55 to 65 years (from 16.6% of obese men to 22.7% [p < 0.001] was particularly significant. And lastly, it is also noteworthy the proportion of individuals with low weight (BMI < 18.5 kg/m2) which increased from 7.3% to 11.6% for women aged 15 to 24 years, and from 0.3% to 2.2% for women aged 35 to 44 years. This trend was also observed for men aged 15 to 24 years (11% to 17.2%)., Conclusions: The relative increase in the prevalence of overweight and obesity runs in parallel to that found in other surrounding countries. Also, it is worth mentioning that among women aged 15 to 24 years the increase in the prevalence of low weight and obesity is almost identical, which invalidates the mean and median values as a means to assess the ponderal evolution in this population. The current compartmentalization between the extreme BMIs, particularly among the youngest portion of population should be addressed from a multidisciplinary perspective.

The time series methods in the epidemiological studies on air pollution are reviewed, illustrated by means of an autoregressive Poisson regression which was employed in the APHEA and EMECAM Projects. A listing is provided of the variations in the daily number of deaths of people over age 70 (all causes, CIE-9:001-799) in Barcelona, 1991-1995, with the average variations in the daily smog pollution levels. A Poisson regression is used insofar as the dependent random variable presumably follows such a probability distribution. As variable possibly leading to confusion, the impact of weather variables (daily temperature and relative humidity averages), seasonal, tendency-related behaviours and day of the year on the death rate are taken into account (all estimated on a determinist basis), in addition to any other variable which behaves in a way that it can be related to the dependent variable (i.e. flu epidemics). The relationship between the death rate and the confusing-causing variables is modelled on a non-linear basis, and the foreseeable lag times are also taken into account (i.e. by using explicative variable time lags). However, due to control not being perfect, it has been decided to opt for estimating an autoregressive Poisson model (adding in some different explicative variables time giving rise to a lag in the death rate) offsetting the residual autocorrelation. The main advantage of the method of analysis described above is that of making it possible to control confusing variables from a determinist standpoint with a software to which all of the groups taking part in this Project had access. This also affords the possibility of using this method in a set, standardized manner, facilitating the comparison of results and making an objective point analysis possible.