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(1) Influenza causes a significant health and socio-economic burden every year, and health personnel (HP) are at higher risk of exposure to respiratory pathogens than the general population. (2) The study’s purpose was to describe and compare influenza vaccine uptake and its prognostic factors among Medical Doctors (MDs) and Non-Medical Health Personnel (NMHP) vs. Non-HP (NHP). We analyzed 2014–2018 data (n = 105,608) from the Italian Behavioral Risk Factor Surveillance System PASSI that, since 2008, has been collecting health-related information continuously in sampled adults. (3) MDs and NMHP represented, respectively, 1.1% and 4.6% of the sample. Among HP, 22.8% (CI 19.8–26.1%) of MDs and 8.5% (CI 7.5–9.5%) of NMHP reported to have been vaccinated vs. 6.3% (CI 6.1–6.5%) in NHP. This difference is confirmed in the three categories (MDs, NMHP, NHP), even more across age groups: in 18–34 yy, respectively, 9.9%, 4.4%, 3.4% vs. 28.4%, 13.9%, 10.6% in 50–64 yy. PASSI surveillance shows an increasing influenza vaccination uptake over time, especially among MDs (22.2% in 2014 vs. 30.5% in 2018). (4) Despite such an increase, especially among younger HP, influenza vaccination uptake is low. Even more under pandemic scenarios, these figures represent key information to address effective strategies for disease prevention and health promotion.

(1) Influenza causes a significant health and socio-economic burden every year, and health personnel (HP) are at higher risk of exposure to respiratory pathogens than general population. (2) The study purpose was to describe and compare influenza vaccine uptake and its prognostic factors among Medical Doctors (MDs) and Non-Medical Health Personnel (NMHP) vs Non-HP (NHP). We analysed 2014-2018 data (N=105,608) from the Italian Behavioural Risk Factor Surveillance System PASSI that, since 2008, has been collecting health-related information continuously in sampled adults. (3) MDs and NMHP represented, respectively, 1.1% and 4.6% of the sample. Among HP, 22.8% (CI 19.8% - 26.1%) of MDs and 8.5% (CI 7.5% - 9.5%) of NMHP reported to have been vaccinated vs 6.3% (CI 6.1% - 6.5%) in NHP. This difference is confirmed in the three categories (MDs, NMHP, NHP), even more across age groups: in 18-34yy, respectively, 9.9%, 4.4%, 3.4% vs 28.4%, 13.9%, 10.6% in 50-64yy. PASSI surveillance shows an increasing influenza vaccination uptake over time, especially among MDs (22.2% in 2014 vs 30.5% in 2018). (4) Despite such increase, especially among younger HP, influenza vaccination uptake is low. Even more under pandemic scenarios, these figures represent key information to address effective strategies for disease prevention and health promotion.

Background Insufficient physical activity (PA) or physical inactivity (PI) is one of the ten leading risk factors for global mortality. PI leads to 20-30% increased risk of all-cause mortality and monitoring its current levels and trends in general population is essential to track progress towards health targets, identify at-risk groups, assess policies' effectiveness, guide future planning. Methods PASSI (Progressi delle Aziende Sanitarie per la Salute in Italia - Progresses in ASSessing adult population health in Italy) is an ongoing cross-sectional Behavioral Risk Factor Surveillance System (BRFSS) that monitors prevalence and temporal trends for the major modifiable health-related risk factors in the adults (18-69 years) residing in Italy. Data are collected in the Local Health Units (LHU) by trained personnel who administer a standardized questionnaire telephonically to sampled people. In the period 2015-2018, 132,717 people were interviewed in more of 90% LHUs (89 out of 101 in 2018), achieving a response rate above 80%. Concerning PA/PI, respondents are classified as per the WHO indicators in: (i) Active - basing on levels achieved in leisure time and/or heavy work; (ii) Partially active - in leisure time and/or moderate work or in spare time and without regular work; (iii) Inactive - in leisure time with sedentary work or in spare time and without regular work. PASSI calculates prevalence of PA/PI overall and by socio-demographic characteristics, including 95% confidence intervals (CI), and a logistic regression model estimates adjusted prevalence ratios (APR). Results In Italy, 28.8% (CI95%:28.5-29.1%) of adult population is featured by a sedentary lifestyle: PI is greater among women (32.4% vs. 25.1%; APR: 1.26), grows with age (34% in over50 vs. 24.7% among 18-34 year-old; APR: 1.34), is higher among deprived people both per economic difficulties (41.7% if many vs. 22.4% if none; APR: 1.39) and for education level (23.7% university vs. 47.2% primary/any; APR: 1.33). We observed a highly evident geographic gradient: PI amounts to 18.3% in the North, 25.2% in the Centre and 40.6% in the South. A multivariate analysis confirms these values are statistically significant. Conclusions PASSI data provide strong evidence to support community prevention interventions on territorial planning or advice by health professionals.

(1) Age-friendly health systems ensure access to quality healthcare services to all people, especially older adults. (2) We used data on elderly population collected from 2016 to 2019 by the Italian ongoing surveillance system PASSI d’Argento to analyze the prevalence and associations between accessing health services and modifiable risk factors included in the 25 × 25 strategy for the burden of noncommunicable diseases with health outcomes. (3) Chronic diseases and hospitalization as descriptors of health status showed that the elderly perceived as having poor access to care and prevention incurred a higher risk of hospitalization. The association between difficulties in accessing health services and hospitalization was always the highest in terms of the adjusted prevalence ratio (aPR), regardless of the other behavioral risk factors considered, controlling each model with sociodemographic conditions. Elderly hospitalized at least once for two days or more in the last 12 months had greater risk to have problems in accessing health services, whereas the model included health conditions such as obesity (aPR = 1.95 95% CI 1.75–2.17), smoking (aPR = 1.95 95% CI 1.76–2.16), alcohol use (aPR = 1.93 95% CI 1.73–2.14), hypertension (aPR = 1.92 95% CI 1.73–2.13) and diabetes (aPR = 1.91 95% CI 1.73–2.12). (4) Health policies should encompass socio-economic and living environment barriers which prevent access to care among older adults.

Cardiovascular disease (CVD) is the first cause of death in Europe and over the world. This study analyses health-related behaviours in adults referring doctor-diagnosed CVDs.We used data from the Italian cross-sectional Behavioural Risk Factor Surveillance System PASSI gathered in 2015-2018. Complex survey design analyses included the Taylor series method for variance estimation and Poisson regression for associations between socio-demographic characteristics and CVD.Among 132,598 respondents, the prevalence of doctor-diagnosed CVD was 5%. Higher percentages are observed among: men, older individuals, socioeconomically disadvantaged people. Compared to the general population, people with CVD have greater risk and aggravating factors, and a worse health status overall. All protective behaviors and lifestyles shall be improved.In Italy, adults with CVD are more likely to be exposed to aggravating modifiable risk factors: it represents a valuable information for increased preventive interventions, even more in the light of the COVID-19 pandemic scenario.

Introduction Current lengthening of average life and constant increase of population ageing associated to forces that include rapid unplanned urbanisation and globalisation of unhealthy behaviours have determined the huge relevance of noncommunicable diseases (NCDs). Monitoring key modifiable behavioural risk factors has resulted to be crucial both in spatial terms and as per temporal trends in order to allow comparisons between different geographic areas or levels and over time. Materials and Methods In Italy, PASSI (Progressi delle Aziende Sanitarie per la Salute in Italia) and Passi d’Argento are the ongoing Behavioural Risk Factor Surveillance Systems (BRFSSs), respectively, on adults (people aged 18−69) and elderly (65 and older). Results The two Italian surveillances are information systems providing data not only on the third Sustainable Development Goal (SDG) that explicitly addresses ensuring healthy lives and promoting well-being for all, but on a total of nine health-related SDGs (HRSDGs) and 19 HRSDG targets/indicators. We describe these pairs more in detail specifying where in case of BRFSS core indicators (N = 14 HRSDG targets/indicators) concerning six HRSDGs or, on the other hand, as per BRFSS further in-depth analysis (N = five HRSDG targets/indicators) in regard of four different HRSDGs. About the HRSDG 3, HRSDG target 3.4, HRSDG indicator 3.4.1, from the PASSI and Passi d’Argento data it is possible not only to detect the prevalence of NCDs in adults and elderly living in Italy, but also to evaluate the social determinants of health, such as gender, age group, educational level, economic difficulties, as well as the associations with modifiable lifestyle risk factors. Conclusions The two Italian BRFSSs generate accurate data, which are highly relevant to design, implement, monitor, and evaluate programs and policies at different levels (local, regional, national) for NCD prevention and health promotion. They provide numbers which can also serve as propaedeutic or, in some cases, complementary ground to address a robust measurement of several HRSDG patterns.

The differences in volatile profile of

In the Hospitals of the Ordine della Provincia Romana San Giovanni di Dio Fatebenefratelli (FBF) (consisting of four hospitals located in three Italian regions) Patient Centeredness has always been considered a central point. In 2015, the Central Hospitals' Health Direction decided to use a check-list for the evaluation of the degree of Patient Centered Care Facilities, drawn up by the National Agency for Regional Health Services (Age.Na.S) during the 2010 Research Project "Experimentation and transfer of organizational empowerment models for evaluating and improving the quality of health services." The aim of the work was to measure the "Patient Centered Care degree" of the FBF structures by means of the Age.Na.S. check-list in order to identify effective and sustainable improvement measures, and to evaluate the applicability and the critical points of the questionnaire. The check-list was divided into four areas: care systems oriented at citizen's respect and centrality; physical accessibility, liveability and comfort of the places of care; access to information, simplification and transparency; care of the relationship with the patient and the citizen. The four areas were divided into 12 sub-areas, 29 criteria and 144 items with sub-items (248 questions), defined as quantitative or qualitative variables allowing for an evaluation of observed reality. Some items from different areas have been grouped into Focus and Operational Units (UU.OO./Facilities). The results of the Age.Na.S. study were used to compare the results obtained in the Roman Province FBF structures with the national ones. The Medical Directors and the responsible of FBF Quality Systems completed the cheek-list. A working group within the Central Hospitals' Health Direction analysed the data and processed the results, using the same scores provided by Age.Na.S.. The analysis of the results was divided into three levels. Focus and UU.OO./Facilities scores were calculated based on Age.Na.S.The distinction into three levels of analysis allowed for a thorough study of results, from the evaluation of the areas to the items. By comparing the results, the overall final value (range 6-6.5) and single area scores are close to the national average for beds number category in all the FBF hospitals. The most critical criteria, recurring in different levels are: 1.1.2 (Activities/projects to promote sociability and continuity with the outside world); 3.2.3 (Content and accessibility of the website); 4.1.2 (Training and support to the staff for the care of the relationship with the patient) and 4.2.3 (Training of the front-office staff), which had alt; 4 score in at least three hospitals and generally achieve a value below the national average (level II and III of analysis). The analysis was extremely useful for detecting positive and negative aspects in the structures under examination. It also permitted to plan improvement measures based on set priorities and objective criteria, aimed at enforcing organizational empowerment models for improving the quality of patient-focused health services. However, during the compilation we found difficulties related to the applicability of the questionnaire. Indeed some questions, while having the same impact on the overall score, are less relevant, considering the patient centrality as main aim. It would be desirable that Age.Na.S. considers in a future survey the observations from hospitals joining previous investigations, in order to facilitate the use of the questionnaire and to improve this tool, which proved to be highly effective.