A compartmental model for smoking dynamics in Italy: a pipeline for inference, validation, and forecasting under hypothetical scenarios.

We propose a compartmental model for investigating smoking dynamics in an Italian region (Tuscany). Calibrating the model on local data from 1993 to 2019, we estimate the probabilities of starting and quitting smoking and the probability of smoking relapse. Then, we forecast the evolution of smoking prevalence until 2043 and assess the impact on mortality in terms of attributable deaths. We introduce elements of novelty with respect to previous studies in this field, including a formal definition of the equations governing the model dynamics and a flexible modelling of smoking probabilities based on cubic regression splines. We estimate model parameters by defining a two-step procedure and quantify the sampling variability via a parametric bootstrap. We propose the implementation of cross-validation on a rolling basis and variance-based Global Sensitivity Analysis to check the robustness of the results and support our findings. Our results suggest a decrease in smoking prevalence among males and stability among females, over the next two decades. We estimate that, in 2023, 18% of deaths among males and 8% among females are due to smoking. We test the use of the model in assessing the impact on smoking prevalence and mortality of different tobacco control policies, including the tobacco-free generation ban recently introduced in New Zealand.

Lung cancer and smoking: years lived with disability in Tuscany (Italy). An analysis from the ACAB study.

BACKGROUND: Lung cancer (LC) is among the most common neoplasms, mostly caused by smoking. This study, carried out within the ACAB project, aims to provide local, updated and systematic estimates of years lived with disability (YLD) from LC due to smoking in the Tuscany region, Italy. METHODS: We estimated YLD for the year 2022 for the whole region and at subregional level by local health unit (LHU) using data from the Tuscany Cancer Registry and local surveys. YLD were calculated by applying the severity-specific LC prevalence, estimated with an incidence-based disease model, to the corresponding disability weight. The burden from smoking was computed by: modelling the prevalence of smokers with a Bayesian Dirichlet-Multinomial regression model; estimating the distribution of smokers by pack-years simulating individual smoking histories; collecting relative risks from the literature. RESULTS: In 2022 in Tuscany, LC caused 7.79 (95% uncertainty interval [UI] = 2.26, 17.27) and 25.50 (95% UI = 7.30, 52.68) YLDs per 100,000 females and males, respectively, with slight variations by LHU, and 53% and 66% of the YLDs were caused by smoking. CONCLUSION: The updated estimates of the burden of LC attributable to smoking for the Tuscany region as a whole and for each LHU provide indications to inform strategic prevention plans and set public health priorities. The impact of smoking on YLDs from LC is not negligible and heterogeneous by LHU, thus requiring local interventions.

The efficacy of bone reconstructive therapies in the management of peri-implantitis. A systematic review and meta-analysis.

AIM: To evaluate the efficacy of bone reconstructive procedures for the reduction of probing pocket depth (PPD), bleeding on probing (BOP), and suppuration in peri-implantitis-related bone defects at ≥12-month follow-up. MATERIALS AND METHODS: Three databases were searched for randomized controlled trials (RCTs) and controlled clinical trials (CCTs) that compared bone reconstructive therapies to access flap surgery (AFS) (Focused Question-FQ 1), and RCTs, CCTs, and prospective case series that assessed the efficacy of reconstructive therapies (FQ 2). Meta-analysis was performed for FQ1 when more than three studies were identified, while for FQ2 a network was drawn based on RCTs with common treatment arms. RESULTS: Seven RCTs were identified for FQ1 while five RCTs and six prospective case series for FQ2. There was no significant difference in PPD change between AFS and reconstructive surgery (-0.387; p = .325) at 12 months. Furthermore, no clear differences in terms of PPD and BOP changes resulted from the different reconstructive therapies included in the network. Only a small percentage of treated cases with any modality achieved peri-implantitis resolution, as defined by different composite outcomes. CONCLUSIONS: Reconstructive surgery does not offer significant improvements in peri-implant clinical parameters as compared to AFS at 12 months. It was not possible to establish a hierarchy of efficacy among the different biomaterials employed for reconstructive surgery.

[School-based screening strategies to prevent the spread of COVID-19 in school: a systematic review of the literature]. / Strategie di screening per contenere la diffusione del COVID-19 nella scuola: una revisione sistematica della letteratura.

OBJECTIVES: to describe studies that evaluated the screening programmes implemented in the school during the COVID-19 pandemic. DESIGN: a systematic literature review was conducted according to the PRISMA 2020 Guidelines. Studies published until December 2021 were included. The methodological quality of the studies was assessed with validated scales. Study selection, data extraction, and quality assessment were carried out by two authors independently. SETTING AND PARTICIPANTS: teachers and students belonging to schools of all levels, including universities. MAIN OUTCOMES MEASURES: a. transmission-related outcomes (such as the number or proportion of cases, cumulative frequency, incidence); b. feasibility/acceptability of the screening strategies; c. socioeconomic outcomes (such as testing cost, number of days spent in school, quarantine). RESULTS: after having removed duplicate articles, 2,822 records were retrieved. Thirty-six studies were included (15 used an observational design and 21 modelling study). Regarding the former, the methodological quality has been rated as high in 2 studies, intermediate in 6 and low in 2; in the remaining ones, it was not evaluated because only descriptive. Screenings were quite different in terms of school study population, types of tests used, methods of submission and analysis, and level of incidence in the community at the time of implementation. Outcome indicators were also varied, a heterogeneity that, on the one hand, did not allow for meta-analysis of results and, on the other, allowed for testing the performance of the screenings in very different settings. All of the field studies claim that the screenings reduced SARS-CoV-2 exposure and infection among children, adolescents, and college students, curbing at-school transmission and helping to reduce the number of closing school days. Studies that evaluated the cost of the intervention emphasized its cost-effectiveness, while those that focused on the acceptability of the instrument showed a preference among children, adolescents, and parents for minimally invasive, self-administered tests with high sensitivity and lower frequency of repetition. Simulation-based studies are mostly based on compartmental and agent-based models. Their quality is quite high methodologically, although uncertainty quantification and external validation, aimed at verifying the model ability to reproduce observed data, are lacking in many cases. The contexts to which the simulations refer are all school-based, although 7 studies consider residential situations, which are poorly suited to the Italian context. All simulation-based models indicate the importance of planning repeated testing on asymptomatic individuals to limit contagion. However, the costs of these procedures can be high unless assessments are spaced out or pool testing procedures are used. Obtaining high student adherence to the screening programme is extremely important to maximize results. CONCLUSIONS: school-based screenings, especially when combined with other preventive measures, have been important public health tools to contain infections during COVID-19 waves and to ensure children's and adolescents' right to education and to prevent the fallout in physical and mental health (with strong equity consequences) associated with school closures.

Different actors for the same play: the impact of the embryologist performing the embryo transfer.

RESEARCH QUESTION: Does the embryologist performing the embryo transfer impact the cycle outcome, in terms of ongoing pregnancy rate (OPR)? DESIGN: This single-centre retrospective study analysed the results, corrected for main confounders, from 28 embryologists and 32 physicians who performed respectively 24,992 and 24,669 fresh embryo transfers (either at cleavage or blastocyst stage) during a 20-year period from January 2000 to December 2019, in a university-affiliated tertiary care assisted reproductive technology (ART) centre. Primary outcome was OPR, defined as the number of viable pregnancies that had completed at least 12 weeks of gestation on the total number of embryo transfers performed. The study also assessed whether the embryologist's experience, measured in terms of number of embryo transfers performed prior to the day of the procedure, had an impact on their performance. The secondary aim was to assess which variable, between the embryologist and physician, more significantly impacted OPR. RESULTS: The overall unadjusted OPR was 22.54%. The embryologist performing the embryo transfer was found to significantly affect the OPR (P < 0.0001), corrected for potential confounders. However, the physician factor made a slightly greater contribution to the model (likelihood ratio 21.86, P < 0.001 versus likelihood ratio 17.20, P < 0.0001). No significant association was found between the experience of the embryologist and OPR (P = 0.067). CONCLUSIONS: These results show how the 'human factor' influences the chances of a positive outcome in the final step of a high-tech procedure and underline the importance of implementing an operator quality performance programme (both for physicians and embryologists) to ensure the maintenance of benchmark results and eventually retrain underperforming operators.

Missing not at random in end of life care studies: multiple imputation and sensitivity analysis on data from the ACTION study.

BACKGROUND: Missing data are common in end-of-life care studies, but there is still relatively little exploration of which is the best method to deal with them, and, in particular, if the missing at random (MAR) assumption is valid or missing not at random (MNAR) mechanisms should be assumed. In this paper we investigated this issue through a sensitivity analysis within the ACTION study, a multicenter cluster randomized controlled trial testing advance care planning in patients with advanced lung or colorectal cancer. METHODS: Multiple imputation procedures under MAR and MNAR assumptions were implemented. Possible violation of the MAR assumption was addressed with reference to variables measuring quality of life and symptoms. The MNAR model assumed that patients with worse health were more likely to have missing questionnaires, making a distinction between single missing items, which were assumed to satisfy the MAR assumption, and missing values due to completely missing questionnaire for which a MNAR mechanism was hypothesized. We explored the sensitivity to possible departures from MAR on gender differences between key indicators and on simple correlations. RESULTS: Up to 39% of follow-up data were missing. Results under MAR reflected that missingness was related to poorer health status. Correlations between variables, although very small, changed according to the imputation method, as well as the differences in scores by gender, indicating a certain sensitivity of the results to the violation of the MAR assumption. CONCLUSIONS: The findings confirmed the importance of undertaking this kind of analysis in end-of-life care studies.

Employment Instability and Fertility in Europe: A Meta-Analysis.

The relationship between employment instability and fertility is a major topic in demographic research, with a proliferation of published papers on this matter, especially since the Great Recession. Employment instability, which most often manifests in unemployment or time-limited employment, is usually deemed to have a negative effect on fertility, although different fertility reactions are hypothesized by sociological theories, and micro-level evidence is fragmented and contradictory. We used meta-analytic techniques to synthesize European research findings, offer general conclusions about the effects of employment instability on fertility (in terms of direction and size), and rank different sources of employment instability. Our results suggest that employment instability has a nonnegligible negative effect on fertility. Men's unemployment is more detrimental for fertility than men's time-limited employment; conversely, a woman having a fixed-term contract is least likely to have a child. Next, the negative effect of employment instability on fertility has become stronger over time, and is more severe in Southern European countries, where social protection for families and the unemployed is least generous. Finally, meta-regression estimates demonstrate that failing to account for income and partner characteristics leads to an overestimation of the negative effect of employment instability on fertility. We advance the role of these two factors as potential mechanisms by which employment instability affects fertility. Overall, this meta-analysis provides the empirical foundation for new studies on the topic.

Assessing short-term impact of PM10 on mortality using a semiparametric generalized propensity score approach.

BACKGROUND: The shape of the exposure-response curve describing the effects of air pollution on population health has crucial regulatory implications, and it is important in assessing causal impacts of hypothetical policies of air pollution reduction. METHODS: After having reformulated the problem of assessing the short-term impact of air pollution on health within the potential outcome approach to causal inference, we developed a method based on the generalized propensity score (GPS) to estimate the average dose-response function (aDRF) and quantify attributable deaths under different counterfactual scenarios of air pollution reduction. We applied the proposed approach to assess the impact of airborne particles with a diameter less than or equal to 10 µm (PM10) on deaths from natural, cardiovascular and respiratory causes in the city of Milan, Italy (2003-2006). RESULTS: As opposed to what is commonly assumed, the estimated aDRFs were not linear, being steeper for low-moderate values of exposure. In the case of natural mortality, the curve became flatter for higher levels; this behavior was less pronounced for cause-specific mortality. The effect was larger in days characterized by higher temperature. According to the curves, we estimated that a hypothetical intervention able to set the daily exposure levels exceeding 40 µg/m3 to exactly 40 would have avoided 1157 deaths (90%CI: 689, 1645) in the whole study period, 312 of which for respiratory causes and 771 for cardiovascular causes. These impacts were higher than those obtained previously from regression-based methods. CONCLUSION: This novel method based on the GPS allowed estimating the average dose-response function and calculating attributable deaths, without requiring strong assumptions about the shape of the relationship. Its potential as a tool for investigating effect modification by temperature and its use in other environmental epidemiology contexts deserve further investigation.

[Analysis and future scenarios of the SARS-CoV-2 epidemic in Tuscany Region (Central Italy)]. / Analisi e previsioni dell'epidemia da SARS-CoV-2 in Toscana.

OBJECTIVES: about two months after the end of the lockdown imposed for the containment of the SARS-CoV-2 epidemic, the contagion dynamics in the Tuscany Region (Central Italy) have been assessed from the beginning of the emergency to the end of June through a compartmental model, and future medium-long term projections have been produced. DATA AND METHODS: this study used a SIRD model in which the infection reproduction number R0 varied over time, according to a piecewise constant function. The fatality parameter and the time from contagion to infection resolution (death or recovery) were fixed to ensure parameter identifiability, and the model was calibrated on the Covid-19 deaths notified from March 9th to June 30th 2020. The uncertainty around the estimates was quantified through parametric bootstrap. Finally, the resulting model was used to produce medium-long term projections of the epidemic dynamics. RESULTS: the date of the first infection in Tuscany was estimated as February 21st 2020. The value of R0(t) ranged from 7.78 (95%CI 7.55-7.89), at the beginning of the outbreak, to a value very close to 0 between April 27th and May 17th. Finally, R0(t) rose, reaching an average of 0.66 (0.32, 0.88) between May 18th and June 30th. At the epidemic peak, estimated at the beginning of April, the notified infected people circulating in the region were just 22% of those predicted by the model. According to the estimated SIRD, under the hypothetical scenario that R0(t) slightly exceeds 1 from the beginning of October 2020, a new wave of contagion could arise by next spring. CONCLUSIONS: the estimated trend of R0(t) is suggestive of a strong effect of the lockdown in Tuscany and of a mild increase of the contagion potentially attributable to the easing of the containment measures. Medium-long term projections unequivocally indicate that the danger of a new epidemic wave has not been averted.

Evaluating a SARS-CoV-2 screening strategy based on serological tests.

BACKGROUND: facing the SARS-CoV-2 epidemic requires intensive testing on the population to early identify and isolate infected subjects. Although RT-PCR is the most reliable technique to detect ongoing infections, serological tests are frequently proposed as tools in heterogeneous screening strategies. OBJECTIVES: to analyse the performance of a screening strategy proposed by the local government of Tuscany (Central Italy), which first uses qualitative rapid tests for antibody detection, and then RT-PCR tests on the positive subjects. METHODS: a simulation study is conducted to investigate the number of RT-PCR tests required by the screening strategy and the undetected ongoing infections in a pseudo-population of 500,000 subjects, under different prevalence scenarios and assuming a sensitivity of the serological test ranging from 0.50 to 0.80 (specificity 0.98). A compartmental model is used to predict the number of new infections generated by the false negatives two months after the screening, under different values of the infection reproduction number. RESULTS: assuming a sensitivity equal to 0.80 and a prevalence of 0.3%, the screening procedure would require on average 11,167 RT-PCR tests and would produce 300 false negatives, responsible after two months of a number of contagions ranging from 526 to 1,132, under the optimistic scenario of a reproduction number between 0.5 to 1. Resources and false negatives increase with the prevalence. CONCLUSIONS: the analysed screening procedure should be avoided unless the prevalence and the rate of contagion are very low. The cost and effectiveness of the screening strategies should be evaluated in the actual context of the epidemic, accounting for the fact that it may change over time.

Comparison of two statistical indicators in communicating epidemiological results to the population: a randomized study in a high environmental risk area of Italy.

BACKGROUND: When communicating risks to the general population, the format of the epidemiological results may affect individual reactions. In environmental epidemiology, no study has compared the use of different statistical formats in communicating results to the population. The aim of this paper is to investigate whether the degree of concern expressed by residents of a high environmental risk site, regarding epidemiological results on cancer mortality in the area where they live, is influenced by the statistical indicator used in communication. METHODS: A sample of residents in the high environmental risk area of Livorno (Italy) was randomized to respond to different questionnaires, in which the same epidemiological results were expressed by two alternative risk indexes: percent excess risk and time needed to harm, defined as the number of days that one has to wait for, on average, to observe 1 death in excess in respect to the baseline. Participants were asked to express their concern on a quantitative scale or to rank different diseases according to their impressions. The statistical analysis was performed using an Inverse Probability of Treatment Weighting approach based on propensity score, in order to account for sample stratification and adjust for unbalance between groups occurring despite randomization. RESULTS: The probability of high concern levels was larger under time needed to harm than under percent excess, with a difference between proportions of 6.7% (95% Confidence Interval, 0.6,12.8%). Mortality from sexual glands cancer was ranked as more worrisome and mortality from thyroid gland cancer as less worrisome under time needed to harm than under percent excess. No rank change was found for lung cancer. Larger differences between the two indicators arose in subjects with higher education or better numerical skills. CONCLUSIONS: Communicating epidemiological results to the population is not a neutral task. The degree of concern and judgments when comparing results on different diseases may depend on the risk indicators used. Translating scientific results into lay language should not exempt from careful evaluation of the impact of this translation on lay people.

Mortality from liver angiosarcoma, hepatocellular carcinoma, and cirrhosis among vinyl chloride workers.

BACKGROUND: Occupational exposure to vinyl chloride monomer (VCM) has been established as a cause of hepatocellular carcinoma (HCC) and liver angiosarcoma (ASL). However, some controversy remains due to conflicting results on liver cirrhosis, and to evidence on HCC based on few confirmed cases. The aim of the study is to clarify the association between VCM exposure and mortality from liver diseases. METHODS: In a cohort of 1658 workers involved in VCM production and polymerization, Poisson regression was adopted to estimate rate ratios (RR) across categories of VCM exposure for mortality due to ASL (n = 9), HCC (n = 31) confirmed by histological/clinical records, and the combination of deaths from liver cirrhosis and from liver cancer with clinical/histological evidence of cirrhosis (n = 63). RESULTS: Cumulative VCM exposure was associated with study outcomes; RRs in the highest compared to the lowest exposure category were: ASL 91.1 (95%Confidence Interval 16.8-497), HCC 5.52 (2.03-15.0), liver cirrhosis 2.60 (1.19-5.67). CONCLUSIONS: The risk of death from liver cirrhosis, as well as from HCC in the largest available series of confirmed cases, increased with VCM exposure.

Bayesian inference for causal mechanisms with application to a randomized study for postoperative pain control.

We conduct principal stratification and mediation analysis to investigate to what extent the positive overall effect of treatment on postoperative pain control is mediated by postoperative self administration of intra-venous analgesia by patients in a prospective, randomized, double-blind study. Using the Bayesian approach for inference, we estimate both associative and dissociative principal strata effects arising in principal stratification, as well as natural effects from mediation analysis. We highlight that principal stratification and mediation analysis focus on different causal estimands, answer different causal questions, and involve different sets of structural assumptions.

Assessing the short term impact of air pollution on mortality: a matching approach.

BACKGROUND: The opportunity to assess short term impact of air pollution relies on the causal interpretation of the exposure-response association. However, up to now few studies explicitly faced this issue within a causal inference framework. In this paper, we reformulated the problem of assessing the short term impact of air pollution on health using the potential outcome approach to causal inference. We considered the impact of high daily levels of particulate matter ≤10 µm in diameter (PM10) on mortality within two days from the exposure in the metropolitan area of Milan (Italy), during the period 2003-2006. Our research focus was the causal impact of a hypothetical intervention setting daily air pollution levels under a pre-fixed threshold. METHODS: We applied a matching procedure based on propensity score to estimate the total number of attributable deaths (AD) during the study period. After defining the number of attributable deaths in terms of difference between potential outcomes, we used the estimated propensity score to match each high exposure day, namely each day with a level of exposure higher than 40 µg/m3, with a day with similar background characteristics but a level of exposure lower than 40 µg/m3. Then, we estimated the impact by comparing mortality between matched days. RESULTS: During the study period daily exposures larger than 40 µg/m3 were responsible for 1079 deaths (90% CI: 116; 2042). The impact was more evident among the elderly than in the younger age classes. Exposures ≥ 40 µg/m3 were responsible, among the elderly, for 1102 deaths (90% CI: 388, 1816), of which 797 from cardiovascular causes and 243 from respiratory causes. Clear evidence of an impact on respiratory mortality was found also in the age class 65-74, with 87 AD (90% CI: 11, 163). CONCLUSIONS: The propensity score matching turned out to be an appealing method to assess historical impacts in this field, which guarantees that the estimated total number of AD can be derived directly as sum of either age-specific or cause-specific AD, unlike the standard model-based procedure. For this reason, it is a promising approach to perform surveillance focusing on very specific causes of death or diseases, or on susceptible subpopulations. Finally, the propensity score matching is free from issues concerning the exposure-confounders-mortality modeling and does not involve extrapolation. On the one hand this enhances the internal validity of our results; on the other, it makes the approach scarcely appropriate for estimating future impacts.

Estimating deaths attributable to airborne particles: sensitivity of the results to different exposure assessment approaches.

BACKGROUND: Epidemiological evidences support the existence of an effect of airborne particulate on population health. However, few studies evaluated the robustness of the results to different exposure assessment approaches. In this paper, we estimated short term effects and impacts of high levels of particulate matter with aerodynamic diameter ≤10 µm (PM10) and ≤2.5 µm (PM2.5) in the Emilia-Romagna region (Northern Italy), one of the most polluted areas in Europe, in the period 2006-2010, and checked if the results changed when different exposure definitions were used. METHODS: Short-term impact of particles on population mortality was assessed, both considering the 9 provincial capitals of the Emilia-Romagna and the region as a whole. We estimated the effects of PM10 and PM2.5 on natural mortality by combining city-specific results in a Bayesian random-effects meta-analysis, and we used these estimates to calculate impacts in terms of attributable deaths. For PM10, we considered different definitions of exposure, based on the use of the air pollutant levels measured by different monitoring stations (background or traffic monitors) or predicted by a dispersion model. RESULTS: Annual average concentrations of PM10 and PM2.5 exceeding the WHO limits of 20 and 10 µg/m3 were respectively responsible for 5.9 and 3.0 deaths per 100 000 inhabitants per year in the provincial capitals, during the period 2006-2010. The total impact in the region in 2010 amounted to 4.4 and 2.8 deaths per 100 000 for PM10 and PM2.5, respectively. The impact estimates for PM10 did not substantially change when the exposure levels were derived from background or traffic monitoring stations, or arose from the dispersion model, in particular when the counterfactual value of 20 µg/m3 was considered. The effect estimates appeared more sensitive to the exposure definition. CONCLUSIONS: A reduction in particle concentrations could have produced significant health benefits in the region. This general conclusion did not change when different exposure definitions were used, provided that the same exposure assessment approach was used for both effect and impact estimations. Caution is therefore recommended when using effect estimates from the literature to assess health impacts of air pollution in actual contexts.

Air pollution exposure, cause-specific deaths and hospitalizations in a highly polluted Italian region.

BACKGROUND: The Lombardy region in northern Italy ranks among the most air polluted areas of Europe. Previous studies showed air pollution short-term effects on all-cause mortality. We examine here the effects of particulate matter with aerodynamic diameter ≤10µm (PM10) and nitrogen dioxide (NO2) exposure on deaths and hospitalizations from specific causes, including cardiac, cerebrovascular and respiratory diseases. METHODS: We considered air pollution, mortality and hospitalization data for a non-opportunistic sample of 18 highly polluted and most densely populated areas of the region in the years 2003-2006. We obtained area-specific effect estimates for PM10 and NO2 from a Poisson regression model on the daily number of total deaths or cause-specific hospitalizations and then combined them in a Bayesian random-effects meta-analysis. For cause-specific mortality, we applied a case-crossover analysis. Age- and season-specific analyses were also performed. Effect estimates were expressed as percent variation in mortality or hospitalizations associated with a 10µg/m(3) increase in PM10 or NO2 concentration. RESULTS: Natural mortality was positively associated with both pollutants (0.30%, 90% Credibility Interval [CrI]: -0.31; 0.78 for PM10; 0.70%, 90%CrI: 0.10; 1.27 for NO2). Cardiovascular deaths showed a higher percent variation in association with NO2 (1.12%, 90% Confidence Interval [CI]: 0.14; 2.11), while the percent variation for respiratory mortality was highest in association with PM10 (1.64%, 90%CI: 0.35; 2.93). The effect of both pollutants was more evident in the summer season. Air pollution was also associated to hospitalizations, the highest variations being 0.77% (90%CrI: 0.22; 1.43) for PM10 and respiratory diseases, and 1.70% (90%CrI: 0.39; 2.84) for NO2 and cerebrovascular diseases. The effect of PM10 on respiratory hospital admissions appeared to increase with age. For both pollutants, effects on cerebrovascular hospitalizations were more evident in subjects aged less than 75 years. CONCLUSIONS: Our study provided a sound characterization of air pollution exposure and its potential effects on human health in the most polluted, and also most populated and productive, Italian region, further documenting the need for effective public health policies.

Root coverage procedures improve patient aesthetics. A systematic review and Bayesian network meta-analysis.

BACKGROUND: The aim of this study was to perform a systematic review (SR) of randomized controlled trials (RCTs) to explore if periodontal plastic surgery procedures for the treatment of single and multiple gingival recessions (Rec) may improve aesthetics at patient and professional levels. MATERIAL AND METHODS: In order to combine evidence from direct and indirect comparisons by different trials a Bayesian network meta-analysis (BNM) was planned. A literature search on PubMed, Cochrane libraries, EMBASE, and hand-searched journals until January 2016 was conducted to identify RCTs presenting aesthetic outcomes after root coverage using standardized evaluations at patient and professional level. RESULTS: A total of 16 RCTs were selected in the SR; three RTCs presenting professional aesthetic evaluation with Root coverage Aesthetic Score (RES) and three showing final self-perception using the Visual Analogue Scale (VAS Est) could be included in a BNM model. Coronally Advanced Flap plus Connective Tissue Graft (CAF + CTG) and CAF + Acellular Dermal Matrix (ADM) and Autologous Fibroblasts (AF) were associated with the best RES outcomes (best probability = 24% and 64%, respectively), while CAF + CTG and CAF + CTG + Enamel matrix Derivatives (EMD) obtained highest values of VAS Est score (best probability = 44% and 26%, respectively). CONCLUSIONS: Periodontal Plastic Surgery (PPS) techniques applying grafts underneath CAF with or without the adding of EMD are associated with improved aesthetics assessed by final patient perception and RES as professional evaluation system.

Projected heat-related mortality under climate change in the metropolitan area of Skopje.

BACKGROUND: Excessive summer heat is a serious environmental health problem in Skopje, the capital and largest city of the former Yugoslav Republic of Macedonia. This paper attempts to forecast the impact of heat on mortality in Skopje in two future periods under climate change and compare it with a historical baseline period. METHODS: After ascertaining the relationship between daily mean ambient air temperature and daily mortality in Skopje, we modelled the evolution of ambient temperatures in the city under a Representative Concentration Pathway scenario (RCP8.5) and the evolution of the city population in two future time periods: 2026-2045 and 2081-2100, and in a past time period (1986-2005) to serve as baseline for comparison. We then calculated the projected average annual mortality attributable to heat in the absence of adaptation or acclimatization during those time windows, and evaluated the contribution of each source of uncertainty on the final impact. RESULTS: Our estimates suggest that, compared to the baseline period (1986-2005), heat-related mortality in Skopje would more than double in 2026-2045, and more than quadruple in 2081-2100. When considering the impact in 2081-2100, sampling variability around the heat-mortality relationship and climate model explained 40.3 and 46.6 % of total variability. CONCLUSION: These results highlight the importance of a long-term perspective in the public health prevention of heat exposure, particularly in the context of a changing climate.

Analyzing the effect of selected control policy measures and sociodemographic factors on alcoholic beverage consumption in Europe within the AMPHORA project: statistical methods.

This paper describes the methods used to investigate variations in total alcoholic beverage consumption as related to selected control intervention policies and other socioeconomic factors (unplanned factors) within 12 European countries involved in the AMPHORA project. The analysis presented several critical points: presence of missing values, strong correlation among the unplanned factors, long-term waves or trends in both the time series of alcohol consumption and the time series of the main explanatory variables. These difficulties were addressed by implementing a multiple imputation procedure for filling in missing values, then specifying for each country a multiple regression model which accounted for time trend, policy measures and a limited set of unplanned factors, selected in advance on the basis of sociological and statistical considerations are addressed. This approach allowed estimating the "net" effect of the selected control policies on alcohol consumption, but not the association between each unplanned factor and the outcome.