The impact of estimation methods for alcoholattributable mortality on long-term trends for the general population and by educational level in Finland and Italy (Turin)

Background and aims This paper assesses the impact of estimation methods for general and education-specific trends in alcohol-attributable mortality (AAM), and develops an alternative method that can be used when the data available for study is limited. Methods We calculated yearly adult (30+) age-standardised and age-specific AAM rates by sex for the general population and by educational level (low, middle, high) in Finland and Turin (Italy) from 1972 to 2017. Furthermore the slope index of inequality and relative inequality index were computed by country and sex. We compared trends, levels, age distributions, and educational inequalities in AAM according to three existing estimation methods: (1) Underlying COD (UCOD), (2) Multiple COD (MCOD) method, and (3) the population attributable fractions (PAF)-method. An alternative method is developed based on the pros and cons of these methods and the outcomes of the comparison. Results The UCOD and MCOD approaches revealed mainly increasing trends in AAM compared to the declining trends according to the PAF approach. These differences are more pronounced when examining AAM trends by educational groups, particularly for Finnish men. Until age 65, age patterns are similar for all methods, and levels nearly identical for MCOD and PAF in Finland. Our novel method assumes a similar trend and age pattern as observed in UCOD, but adjusts its level upwards so that it matches the level of the PAF approach for ages 30-64. Our new method yields levels in-between UCOD and PAF for Turin (Italy), and resembles the MCOD rates in Finland for females. Relative inequalities deviate for the PAFmethod (lower levels) compared to other methods, whereas absolute inequalities are generally lower for UCOD than all three methods that combine wholly and partly AAM. Conclusions The choice of method to estimate AAM affects not only levels, but also general and education- specific trends and inequalities. Our newly developed method constitutes a better alternative for multiple-country studies by educational level than the currently used UCODmethod when the data available for study is limited to underlying causes of death.</p

The impact of estimation methods for alcoholattributable mortality on long-term trends for the general population and by educational level in Finland and Italy (Turin)

Background and aims This paper assesses the impact of estimation methods for general and education-specific trends in alcohol-attributable mortality (AAM), and develops an alternative method that can be used when the data available for study is limited. Methods We calculated yearly adult (30+) age-standardised and age-specific AAM rates by sex for the general population and by educational level (low, middle, high) in Finland and Turin (Italy) from 1972 to 2017. Furthermore the slope index of inequality and relative inequality index were computed by country and sex. We compared trends, levels, age distributions, and educational inequalities in AAM according to three existing estimation methods: (1) Underlying COD (UCOD), (2) Multiple COD (MCOD) method, and (3) the population attributable fractions (PAF)-method. An alternative method is developed based on the pros and cons of these methods and the outcomes of the comparison. Results The UCOD and MCOD approaches revealed mainly increasing trends in AAM compared to the declining trends according to the PAF approach. These differences are more pronounced when examining AAM trends by educational groups, particularly for Finnish men. Until age 65, age patterns are similar for all methods, and levels nearly identical for MCOD and PAF in Finland. Our novel method assumes a similar trend and age pattern as observed in UCOD, but adjusts its level upwards so that it matches the level of the PAF approach for ages 30-64. Our new method yields levels in-between UCOD and PAF for Turin (Italy), and resembles the MCOD rates in Finland for females. Relative inequalities deviate for the PAFmethod (lower levels) compared to other methods, whereas absolute inequalities are generally lower for UCOD than all three methods that combine wholly and partly AAM. Conclusions The choice of method to estimate AAM affects not only levels, but also general and education- specific trends and inequalities. Our newly developed method constitutes a better alternative for multiple-country studies by educational level than the currently used UCODmethod when the data available for study is limited to underlying causes of death.</p

The impact of estimation methods for alcoholattributable mortality on long-term trends for the general population and by educational level in Finland and Italy (Turin)

Background and aims This paper assesses the impact of estimation methods for general and education-specific trends in alcohol-attributable mortality (AAM), and develops an alternative method that can be used when the data available for study is limited. Methods We calculated yearly adult (30+) age-standardised and age-specific AAM rates by sex for the general population and by educational level (low, middle, high) in Finland and Turin (Italy) from 1972 to 2017. Furthermore the slope index of inequality and relative inequality index were computed by country and sex. We compared trends, levels, age distributions, and educational inequalities in AAM according to three existing estimation methods: (1) Underlying COD (UCOD), (2) Multiple COD (MCOD) method, and (3) the population attributable fractions (PAF)-method. An alternative method is developed based on the pros and cons of these methods and the outcomes of the comparison. Results The UCOD and MCOD approaches revealed mainly increasing trends in AAM compared to the declining trends according to the PAF approach. These differences are more pronounced when examining AAM trends by educational groups, particularly for Finnish men. Until age 65, age patterns are similar for all methods, and levels nearly identical for MCOD and PAF in Finland. Our novel method assumes a similar trend and age pattern as observed in UCOD, but adjusts its level upwards so that it matches the level of the PAF approach for ages 30-64. Our new method yields levels in-between UCOD and PAF for Turin (Italy), and resembles the MCOD rates in Finland for females. Relative inequalities deviate for the PAFmethod (lower levels) compared to other methods, whereas absolute inequalities are generally lower for UCOD than all three methods that combine wholly and partly AAM. Conclusions The choice of method to estimate AAM affects not only levels, but also general and education- specific trends and inequalities. Our newly developed method constitutes a better alternative for multiple-country studies by educational level than the currently used UCODmethod when the data available for study is limited to underlying causes of death.</p

The contribution of alcohol-related deaths to the life-expectancy gap between people with and without depression – a cross-country comparison

Publisher Copyright: © 2022 The AuthorsBackground: Alcohol-related deaths may be among the most important reasons for the shorter life expectancy of people with depression, yet no study has quantified their contribution. We quantify the contribution of alcohol-related deaths to the life-expectancy gap in depression in four European countries with differing levels of alcohol-related mortality. Methods: We used cohort data linking population registers with health-care and death records from Denmark, Finland, Sweden and Turin, Italy, in 1993–2007 (210,412,097 person years, 3046,754 deaths). We identified psychiatric inpatients with depression from hospital discharge registers in Denmark, Finland, and Sweden and outpatients with antidepressant prescriptions from prescription registers in Finland and Turin. We assessed alcohol-related and non-alcohol-related deaths using both underlying and contributory causes of death, stratified by sex, age and depression status. We quantified the contribution of alcohol-related deaths by cause-of-death decomposition of the life-expectancy gap at age 25 between people with and without depression. Results: The gap in life expectancy was 13.1–18.6 years between people with and without inpatient treatment for depression and 6.7–9.1 years between those with and without antidepressant treatment. The contribution of alcohol-related deaths to the life-expectancy gap was larger in Denmark (33.6%) and Finland (18.1–30.5%) – i.e., countries with high overall alcohol-related mortality – than in Sweden (11.9%) and Turin (3.2%), and larger among men in all countries. The life-expectancy gap due to other than alcohol-related deaths varied little across countries. Conclusions: Alcohol contributes heavily to the lower life expectancy in depression particularly among men and in countries with high overall alcohol-related mortality.Peer reviewe

Micro-scale {UHI} risk assessment on the heat-health nexus within cities by looking at socio-economic factors and built environment characteristics: The Turin case study (Italy)

Today the most substantial threats facing cities relate to the impacts of climate change. Extreme temperature such as heat waves and the occurrence of Urban Heat Island (UHI) phenomena, present the main challenges for urban planning and design. Climate deterioration exacerbates the already existing weaknesses in social systems, which have been created by changes such as population increases and urban sprawl. Despite numerous attempts by researchers to assess the risks associated with the heat-health nexus in urban areas, no common metrics have yet been defined yet. The objective of this study, therefore, is to provide an empirical example of a flexible and replicable methodology to estimate the micro-scale UHI risks within an urban context which takes into account all the relevant elements regarding the heat-health nexus. For this purpose, the city of Turin has been used as a case study. The methodological approach adopted is based on risk assessment guidelines suggested and approved by the most recent scientific literature. The risk framework presented here used a quantitative estimate per each census tract within the city based on the interaction of three main factors: hazard, exposure, and vulnerability. Corresponding georeferenced maps for each indicator have been provided to increase the local knowledge on the spatial distribution of vulnerability drivers. The proposed methodology and the related findings represent an initial stage of the urban risk investigation within the case study. This will include participatory processes with local policymakers and health-stakeholders with a view to guiding the local planning agenda of climate change adaptation and resilience strategies in the City of Turin

Multimorbidity and SARS-CoV-2–Related Outcomes: Analysis of a Cohort of Italian Patients

Background: Since the outbreak of the COVID-19 pandemic, identifying the main risk factors has been imperative to properly manage the public health challenges that the pandemic exposes, such as organizing effective vaccination campaigns. In addition to gender and age, multimorbidity seems to be one of the predisposing factors coming out of many studies investigating the possible causes of increased susceptibility to SARS-CoV-2 infection and adverse outcomes. However, only a few studies conducted have used large samples. Objective: The objective is to evaluate the association between multimorbidity, probability to be tested, susceptibility, and severity of SARS-CoV-2 infection in the Piedmont population (Northern Italy, about 4 million inhabitants). For this purpose, we considered five main outcomes: access to swab, positivity to SARS-CoV-2, hospitalization, ICU admission, and death within 30 days from the first positive swab. Methods: Data were obtained from different Piedmont health-administrative databases. Subjects aged between 45 and 74 years and infections diagnosed between February and May 2020 were considered. Multimorbidity was defined both with the Charlson Comorbidity Index (CCI) and by identifying patients with previous comorbidities such as diabetes, and oncological, cardiovascular, and respiratory diseases. Multivariable logistic regression models (adjusted for age and month of infection and stratified by gender) were performed for each outcome. Analyses were also conducted by separating two age groups (45-59 and 60-74 years). Results: Out of 1,918,549 subjects, 85,348 performed at least one swab, 12,793 tested positive for SARS-CoV-2, 4,644 were hospitalized, 1,508 were admitted to the ICU, and 749 died within 30 days from the first positive swab. Individuals with a higher CCI had a higher probability of being swabbed but a lower probability of testing positive. We observed the same results when analyzing subjects with previous oncological and cardiovascular diseases. Moreover, especially in the youngest group, we identified a greater risk of being hospitalized and dying. Among comorbidities considered in the study, respiratory diseases seem to be the most likely to increase the risk of having a positive swab and worse disease outcomes. Conclusions: Our study shows that patients with multimorbidity, although swabbed more frequently, are less likely to result infected with SARS-CoV-2, probably due to greater attention on protective methods. Moreover, a history of respiratory diseases is a risk factor for a worse prognosis of COVID-19. Nonetheless, whatever comorbidities affect the patients, a strong dose-response effect was observed between an increased score of CCI and COVID-19 hospitalization, ICU admission, and death. These results are important in terms of public health because they help in identifying a group of subjects that are more prone to worse SARS-CoV-2 outcomes. This information is important for promoting targeted prevention and developing policies for the prioritization of public health interventions

Cohort profile: the Italian Network of Longitudinal Metropolitan Studies (IN-LiMeS), a multicentre cohort for socioeconomic inequalities in health monitoring.

PURPOSE: The Italian Network of Longitudinal Metropolitan Studies (IN-LiMeS) is a system of integrated data on health outcomes, demographic and socioeconomic information, and represents a powerful tool to study health inequalities. PARTICIPANTS: IN-LiMeS is a multicentre and multipurpose pool of metropolitan population cohorts enrolled in nine Italian cities: Turin, Venice, Reggio Emilia, Modena, Bologna, Florence, Leghorn, Prato and Rome. Data come from record linkage of municipal population registries, the 2001 population census, mortality registers and hospital discharge archives. Depending on the source of enrolment, cohorts can be closed or open. The census-based closed cohort design includes subjects resident in any of the nine cities at the 2001 census day; 4 466 655 individuals were enrolled in 2001 in the nine closed cohorts. The open cohort design includes subjects resident in 2001 or subsequently registered by birth or immigration until the latest available follow-up (currently 31 December 2013). The open cohort design is available for Turin, Venice, Reggio Emilia, Modena, Bologna, Prato and Rome. Detailed socioeconomic data are available for subjects enrolled in the census-based cohorts; information on demographic characteristics, education and citizenship is available from population registries. FINDINGS TO DATE: The first IN-LiMeS application was the study of differentials in mortality between immigrants and Italians. Either using a closed cohort design (nine cities) or an open one (Turin and Reggio Emilia), individuals from high migration pressure countries generally showed a lower mortality risk. However, a certain heterogeneity between the nine cities was noted, especially among men, and an excess mortality risk was reported for some macroareas of origin and specific causes of death. FUTURE PLANS: We are currently working on the linkage of the 2011 population census data, the expansion of geographical coverage and the implementation of the open design in all the participating cohorts

Inequalities in the Health Impact of the First Wave of the COVID-19 Pandemic in Piedmont Region, Italy

(1) Introduction: Several studies observe a social gradient in the incidence and health consequences of SARS-CoV-2 infection, but they rely mainly on spatial associations because individual-level data are lacking. (2) Objectives: To assess the impact of social inequalities in the health outcomes of COVID-19 during the first epidemic wave in Piedmont Region, Italy, evaluating the role of the unequal social distribution of comorbidities and the capacity of the healthcare system to promote equity. (3) Methods: Subjects aged over 35, resident in Piedmont on 22 February 2020, were followed up until 30 May 2020 for access to swabs, infection, hospitalization, admission to intensive care unit, in-hospital death, COVID-19, and all-cause death. Inequalities were assessed through an Index of Socioeconomic Disadvantage composed of information on education, overcrowding, housing conditions, and neighborhood deprivation. Relative incidence measures and Relative Index of Inequality were estimated through Poisson regression models, stratifying by gender and age groups (35&ndash;64 years; &ge;65 years), adjusting for comorbidity. (4) Results: Social inequalities were found in the various outcomes, in the female population, and among elderly males. Inequalities in ICU were lower, but analyses only on in-patients discount the hypothesis of preferential access by the most advantaged. Comorbidities contribute to no more than 30% of inequalities. (5) Conclusions: Despite the presence of significant inequities, the pandemic does not appear to have further exacerbated health inequalities, partly due to the fairness of the healthcare system. It is necessary to reduce inequalities in the occurrence of comorbidities that confer susceptibility to COVID-19 and promote prevention policies that limit inequalities in the mechanisms of contagion and improve out-of-hospital timely treatment

The impact of estimation methods for alcoholattributable mortality on long-term trends for the general population and by educational level in Finland and Italy (Turin)

Background and aims This paper assesses the impact of estimation methods for general and education-specific trends in alcohol-attributable mortality (AAM), and develops an alternative method that can be used when the data available for study is limited. Methods We calculated yearly adult (30+) age-standardised and age-specific AAM rates by sex for the general population and by educational level (low, middle, high) in Finland and Turin (Italy) from 1972 to 2017. Furthermore the slope index of inequality and relative inequality index were computed by country and sex. We compared trends, levels, age distributions, and educational inequalities in AAM according to three existing estimation methods: (1) Underlying COD (UCOD), (2) Multiple COD (MCOD) method, and (3) the population attributable fractions (PAF)-method. An alternative method is developed based on the pros and cons of these methods and the outcomes of the comparison. Results The UCOD and MCOD approaches revealed mainly increasing trends in AAM compared to the declining trends according to the PAF approach. These differences are more pronounced when examining AAM trends by educational groups, particularly for Finnish men. Until age 65, age patterns are similar for all methods, and levels nearly identical for MCOD and PAF in Finland. Our novel method assumes a similar trend and age pattern as observed in UCOD, but adjusts its level upwards so that it matches the level of the PAF approach for ages 30-64. Our new method yields levels in-between UCOD and PAF for Turin (Italy), and resembles the MCOD rates in Finland for females. Relative inequalities deviate for the PAFmethod (lower levels) compared to other methods, whereas absolute inequalities are generally lower for UCOD than all three methods that combine wholly and partly AAM. Conclusions The choice of method to estimate AAM affects not only levels, but also general and education- specific trends and inequalities. Our newly developed method constitutes a better alternative for multiple-country studies by educational level than the currently used UCODmethod when the data available for study is limited to underlying causes of death.</p