Patients with Type 2 Diabetes Mellitus (T2DM) are rapidly increasing in Italy due to aging, preventable risk factors, and worsening socioeconomic context. T2DM and its sequelae take a heavy toll on healthcare systems and the economy, given costly management, difficulties in coping with everyday life, and decreasing patient/worker productivity. Considering long life expectancy in Italy and a decreasing mortality rate due to T2DM, this study aims to calculate the years lived with disability (YLDs) of T2DM and its sequelae grouped into three categories: Neuropathy, Chronic Kidney Disease and No Complications, taking into consideration sex, year, and geographical location. This is the first attempt to measure YLDs from data that do not rely on self-reported diabetes diagnoses. Data come from the Italian Diabetologists Association dataset, the most comprehensive longitudinal source of national outpatient data. YLDs are obtained by multiplying the number of individuals living with a specific health condition and a disability weight which represents the magnitude of health loss associated with that particular condition. Findings show increasing YLD age-standardized rates for T2DM and its sequelae, especially Neuropathy, with the trend being stronger in the central macro-region and among men, and that 2009 marks a structural change in YLD growth rate. Systematic data collection for measuring the burden of diseases is key, among other things, to policy-making and implementation.

A growing body of literature supports the association between ambient particulate pollution and the risk of type 2 diabetes (T2DM). Both issues are particularly relevant in Italy. This study investigates the relationship between T2DM and exposure to PM_2.5 and PM₁₀ in Italian municipalities from 2013 to 2021. Data on T2DM were provided by the Italian Association of Diabetologists (AMD), representing the only national outpatient dataset not based on self-reported information. Air pollution data, sourced from the Italian Institute for Environmental Protection and Research, ISPRA, were summarized using the population-weighted exposure (PWE) indicator. Both datasets were made available through a dedicated research agreement. Random effects models and non-parametric methods were applied to assess the association between air pollution and T2DM. Results indicate a statistically significant relationship, particularly between T2DM and PM2.5. T2DM incidence rates were significantly negatively associated with time (coefficient = − 0.07961, p < 0.01), indicating a decreasing trend over time. After adjusting for other covariates, PM₁₀ population-weighted exposure was not significantly associated with incidence rates (coefficient = − 0.00057, p = 0.58). On the other hand, increases in the ratio of PM_2.5 to PM₁₀ (pwratio) were significantly positively associated with increases in T2DM incidence rates (coefficient = 0.52304, p < 0.01) at the municipal level. T2DM prevalence proportions were significantly positively associated with time (coefficient = 0.01749, p < 0.01), suggesting an increasing trend over time. PM₁₀ was significantly negatively associated with prevalence proportions (coefficient = − 0.00298, p = 0.03), while increases in pwratio were significantly positively associated with increases in prevalence proportions (coefficient = 0.18724, p < 0.01). Thus, municipalities with a higher share of PM_2.5 within the same level of PM₁₀, tended to show higher T2DM prevalence proportions and incidence rates, consistent with the spatial distribution of air pollution and disease burden observed across Italy.

Introduction: An educational mismatch is defined as the situation where the education qualifications of an employee do not match the qualifications required for the job they do. A mismatch can be vertical where the level of the employee's qualification is not the one required by the job. This study contributes to the literature on work-related social determinants of health, by carrying out the first assessment of the relationship between educational mismatch and health in Italy.Methods: Data come from PLUS, a national survey of labor supply. The risk of suffering from bad or very bad health associated with educational mismatch is investigated through a logistic regression model accounting for the socioeconomic context and occupation.Results: Our findings show women are at greater risk of suffering from bad or very bad health than men, especially if under-educated.Discussion: Our results show the need to address more research on work-related social determinants of health, which can represent a barrier to achieving health equity.

Aim: The association between particulate air pollution and increased risk of type 2 diabetes (T2DM) is well established. Air pollution, a major public health concern worldwide, affects several noncommunicable diseases, including T2DM. Italy faces significant challenges in relation to both particulate air pollution and T2DM. There are no studies in Italy assessing the association between particulate matter and T2DM in a large dataset of patients with clinically diagnosed T2DM. Subject and methods: This study aims to assess the association between particulate matter (PM2.5 and PM10) and T2DM prevalence and incidence rates in Lombardy compared with the rest of Italy from 2006 to 2019. The association with years lived with disability (YLDs) was assessed using data from 2006 to 2016. Data were obtained from the AMD dataset, a comprehensive outpatient longitudinal dataset, while particulate matter data were obtained from the European Environment Agency and ARPA Lombardy, the regional environmental protection agency for Lombardy. The association was assessed using mixed-effects models. Results: The mixed-effects model showed a significant positive association between particulate matter and T2DM incidence in Italy, with notable variations over time and between regions (Lombardy vs. the rest of Italy). While no significant effect of particulate matter was observed with respect to prevalence and YLD rates, a significant positive association was found between particulate matter and incidence rates for Italy, with the effect increasing over time. The opposite tendency was observed for Lombardy, with a negative association between particulate matter and incidence, and a decreases in the effect over time. Conclusion: Particulate matter pollution, specifically PM2.5 and PM10, appears to be significantly associated with T2DM incidence rates in Italy. However, the effect varies between regions, with Lombardy showing a complex relationship influenced by socioeconomic factors. This study highlights the importance of addressing air pollution as a public health priority, particularly in regions with high levels of pollution such as Lombardy, in order to reduce the risk of T2DM and its associated burden. Graphical

Diabetes is associated with the development of sequelae that further reduce patients' quality of life. A valuable instrument for assessing the severity of sequelae is the disability weight. The evaluation of the risks associated with the potential deterioration of sequelae has direct implications for healthcare. The objective of this study is to estimate the risk of progression from no complications to any complications in both type 2 and type 1 diabetes and to examine the progression of risk over time. Survival analysis methods are applied. The Kaplan-Meier and the Cox proportional hazards models are employed to ascertain the probability of developing complications in the future, given that the subject is currently free of such complications. Patients were obtained from the longitudinal dataset of the Italian Association of Diabetologists, collected between 2005 and 2017. This is the first study in Italy to estimate the risk of transition to complications in people with diabetes. The results indicate that older males with type 2 diabetes living in the central and northern regions of the country are associated with a higher risk profile. Since the patients excluded from the baseline have the same risk characteristics as the patients studied, the results can be generalized. Our findings provide evidence within a large clinical cohort and suggest potential applicability of the proposed approach in other settings beyond the Italian context. Quantifying risk in a way that is easily understood by policymakers and the general public is a valuable tool, as diabetes complications are a significant burden for individuals and society as a whole.