A multicenter, cross-sectional observational study (Italian GENder Differences in Awareness of Cardiovascular risk, IGENDA study) was carried out to evaluate the perception and knowledge of cardiovascular risk among Italian women. An anonymous questionnaire was completed by 4454 women (44.3 ± 14.1 years). The 70% of respondents correctly identified cardiovascular disease (CVD) as the leading cause of death. More than half of respondents quoted cancer as the greatest current and future health problem of women of same age. Sixty percent of interviewed women considered CVD as an almost exclusively male condition. Although respondents showed a good knowledge of the major cardiovascular risk factors, the presence of cardiovascular risk factors was not associated with higher odds of identifying CVD as the biggest cause of death. Less than 10% of respondents perceived themselves as being at high CVD risk, and the increased CVD risk perception was associated with ageing, higher frequency of cardiovascular risk factors and disease, and a poorer self-rated health status. The findings of this study highlight the low perception of cardiovascular risk in Italian women and suggest an urgent need to enhance knowledge and perception of CVD risk in women as a real health problem and not just as a as a life-threatening threat.

Aims and background: In the last decades, many epidemiological studies have implicated outdoor environmental carcinogens in the onset of lung cancer. The present investigation evaluated lung cancer mortality in two areas of the Province of La Spezia (Northern Italy) exposed to environmental pollution emitted by a coal-fired power station and other industrial sources, including a waste incinerator. Methods: In the two exposed areas, lung cancer mortality risk for the 1988-1996 calendar period was evaluated using the whole Province population as referent. The corresponding relative risks (RR) were estimated after controlling for age structure, urban/rural gradient and deprivation factors (occupation, education, home ownership, housing conditions and family structure) by a Poisson regression modeling. The geographic pattern of risk for the whole province was evaluated via the Besag, York and Mollié (BYM) bayesian model. Results: Persons living in urban areas showed the highest rates in both sexes. No statistically significant risk excess was found in the two exposed areas among males, after excluding rural and semi-rural zones from the analyses (RR = 1.03 and RR = 0.77). In contrast, a risk excess was observed for females in both exposed areas, which remained elevated and statistically significant (P <0.05) after restriction to urban/semi-urban municipalities and after controlling for deprivation factors (RR = 1.54 and RR = 2.14, respectively). Bayesian mapping confirmed the rural/urban gradient and the risk excess observed in females near the industrial sites. Conclusions: The risk observed among females is consistent with pollution measurements and with other epidemiologic findings, whereas a strong confounding from occupational exposures and smoking habit could account for the lack of an excess risk in males. However, the ecologic nature of this investigation prevented drawing a causal inference. The pollution-related risk observed in the female gender is an important clue that deserves further epidemiologic attention.

Clinical medicine faces many challenges, e.g. applying personalized medicine and genomics in daily practice; utilizing highly specialized diagnostic technologies; prescribing costly therapeutics. Today's population is aging and patients are diagnosed with more co-morbid conditions than in the past. Co-morbidity makes management of the elderly difficult also in terms of pharmacotherapy. The high prevalence of hypertension and diabetes as co-morbidities is indicative of the complexities that can impact accuracy in diagnosis and treatment, with poly-pharmacy being a significant component. It is essential to apply analytic methods to evaluate retrospective data to understand real world patients and medical practice. This study applies social network analysis, a novel method, to administrative data to evaluate the scope and impact of poly-pharmacy and reveal potential problems in management of elderly patients with diabetes and hypertension. Social Network Analysis (SNA) enables the examination of large patient data sets to identify complex relationships that may exist and go undetected either because of infrequent observation or complexity of the interactions. The application of SNA identifies critical aspects derived from over-connected portions of the network. These criticalities mainly involve the high rate of poly-pharmacy that results from the observation of additional co-morbid conditions in the study population. The analysis identifies crucial factors for consideration in developing clinical guidelines to deal with real-world patient observations. The analysis of routine health data, as analyzed using SNA, can be further compared with the inclusion/exclusion criteria presented in the current guidelines and can additionally provide the basis for further enhancement of such criteria.