Social inequalities in heat-attributable mortality in the city of Turin, northwest of Italy: a time series analysis from 1982 to 2018.

BACKGROUND: Understanding context specific heat-health risks in urban areas is important, especially given anticipated severe increases in summer temperatures due to climate change effects. We investigate social inequalities in the association between daily temperatures and mortality in summer in the city of Turin for the period 1982-2018 among different social and demographic groups such as sex, age, educational level, marital status and household occupants. METHODS: Mortality data are represented by individual all-cause mortality counts for the summer months between 1982 and 2018. Socioeconomic level and daily mean temperature were assigned to each deceased. A time series Poisson regression with distributed lag non-linear models was fitted to capture the complex nonlinear dependency between daily mortality and temperature in summer. The mortality risk due to heat is represented by the Relative Risk (RR) at the 99th percentile of daily summer temperatures for each population subgroup. RESULTS: All-cause mortality risk is higher among women (1.88; 95% CI = 1.77, 2.00) and the elderly (2.13; 95% CI = 1.94, 2.33). With regard to education, the highest significant effects for men is observed among higher education levels (1.66; 95% CI = 1.38, 1.99), while risks for women is higher for the lower educational level (1.93; 95% CI = 1.79, 2.08). Results on marital status highlighted a stronger association for widower in men (1.66; 95% CI = 1.38, 2.00) and for separated and divorced in women (2.11; 95% CI = 1.51, 2.94). The risk ratio of household occupants reveals a stronger association for men who lived alone (1.61; 95% CI = 1.39, 1.86), while for women results are almost equivalent between alone and not alone groups. CONCLUSIONS: The associations between heat and mortality is unequal across different aspects of social vulnerability, and, inter alia, factors influencing the population vulnerability to temperatures can be related to demographic, social, and economic aspects. A number of issues are identified and recommendations for the prioritisation of further research are provided. A better knowledge of these effect modifiers is needed to identify the axes of social inequality across the most vulnerable population sub-groups.

Avoidable hospitalisation for diabetes mellitus among immigrants and natives: Results from the Italian Network for Longitudinal Metropolitan Studies.

BACKGROUND AND AIMS: Italy has experienced a relevant increase in migration inflow over the last 20 years. Although the Italian Health Service is widely accessible, immigrants can face many barriers that limit their use of health services. Diabetes mellitus (DM) has a different prevalence across ethnic groups, but studies focusing on DM care among immigrants in Europe are scarce. This study aimed to compare the rates of avoidable hospitalisation (AH) between native and immigrant adults in Italy. METHODS AND RESULTS: A multi-centre open cohort study including all 18- to 64-year-old residents in Turin, Venice, Reggio-Emilia, Modena, Bologna and Rome between 01/01/2001 and 31/12/2013-14 was conducted. Italian citizens were compared with immigrants from high migratory pressure countries who were further divided by their area of origin. We calculated age-, sex- and calendar year-adjusted rate ratios (RRs) and 95% confidence intervals (95% CIs) of AH for DM by citizenship using negative binomial regression models. The RRs were summarized using a random effects meta-analysis. The results showed higher AH rates among immigrant males (RR: 1.63, 95% CI: 1.16-2.23), whereas no significant difference was found for females (RR: 1.14, 95% CI: 0.65-1.99). Immigrants from Asia and Africa showed a higher risk than Italians, whereas those from Central-Eastern Europe and Central-Southern America did not show any increased risk. CONCLUSION: Adult male immigrants were at higher risk of experiencing AH for DM than Italians, with differences by area of origin, suggesting that they may experience lower access to and lower quality of primary care for DM. These services should be improved to reduce disparities.

Is the association between precarious employment and mental health mediated by economic difficulties in males? Results from two Italian studies.

BACKGROUND: Flexible employment is increasing across Europe and recent studies show an association with poor mental health. The goal of the current study is to examine this association in the Italian population to assess the possible mediating role of financial strain. METHODS: Data were obtained by two Italian cross-sectional studies (PASSI and HIS) aimed at monitoring the general population health status, health behaviours and determinants. Mental health status was assessed using alternatively two validated questionnaires (the PHQ-2 and the MCS-12 score) and Poisson regression models were performed to assess if precarious work was associated with poor mental health. A formal mediation analysis was conducted to evaluate if the association between precarious work and mental health was mediated by financial strain. RESULTS: The analyses were performed on 31,948 subjects in PASSI and on 21,894 subjects in HIS. A nearly two-fold risk of depression and poor mental health was found among precarious workers, compared to workers with a permanent contract, which was strongly mediated by financial strain. CONCLUSIONS: Even with the limitations of a cross-sectional design, this research supports that precarious employment contributes through financial strain to reduce the mental health related quality of life and to increase mental disorders such as symptoms of depression or dysthymia. This suggests that when stability in work cannot be guaranteed, it would be appropriate to intervene on the wages of precarious jobs and to provide social safety nets for ensuring adequate income.

[Immigrants' health and socioeconomic inequalities of overall population residing in Italy evaluated through the Italian network of Longitudinal Metropolitan Studies]. / Salute degli immigrati e disuguaglianze socioeconomiche nella popolazione residente in Italia valutate attraverso la rete degli Studi Longitudinali Metropolitani.

INTRODUCTION: Describing and monitoring socioeconomic inequalities in health are the prerequisite for planning equity policies. In Italy, some cities have integrated personal information from the municipal registries with Census data and with data from healthcare information systems to set up Longitudinal Metropolitan Studies (LMS). Under the coordination of the Italian National Institute for Health, Migration, and Poverty (NIHMP), six cities in the LMS network have contributed to the present monograph: Turin, Venice, Reggio Emilia, Modena, Bologna, and Rome. MORTALITY RESULTS. Significant socioeconomic differences by level of education were seen in all the participating centres. People who live alone or in single-parent households are more likely to die, as are those living in a substandard dwelling. Immigrants resident in the six cities included in the study showed lower all-cause mortality than Italians (males: MRR 0.83; 95%CI 0.78-0.90 - females: MRR 0.70; 95%CI 0.64-0.77). Sub-Saharan Africans experienced a significant higher mortality than Italians (males: MRR 1.33; 95%CI 1.12-1.59 - females: MMR 1.69; 95%CI 1.31-2.17). Immigrants had a neonatal and post-neonatal mortality risk about 1.5 times higher than Italians (neonatal: OR 1.71; 95%CI 1.22-2.39 - post-neonatal: OR 1.63; 95%CI 1.03-2.57). A difference between Italians and immigrants was also observed for mortality in children aged 1-4 years, though less marked (OR 1.24; 95%CI 0.73-2.11). Excesses concerned particularly immigrants from North Africa and from sub-Saharan Africa as well as those residing in Italy for >5 years. HOSPITALISATION RESULTS. Hospitalisation rates are lower for immigrants than for Italians, except when due to infectious diseases, blood disorders, and, among women, for reasons linked to pregnancy and childbirth. Avoidable hospitalisation rates of adults from low migratory pressure Countries are lower than or equal to those of Italians. On the contrary, adults from low migratory pressure Countries show higher avoidable hospitalisation rates compared to Italians in every cohort, with the exception of Rome (RR 0.81; 95%CI 0.78-0.85), with RR ranging from 1.08 (95%CI 0.96-1.22) in Venice to 1.64 (95%CI 1.47-1.83) in Modena. CONCLUSIONS: Maternal and child health is the most critical area of health for immigrant population. Considering the importance that the issue of health equity has taken on in the political agenda, the data presented in this volume are a great asset, particularly in light of the long recession and the social crisis that have impacted the Country.

Contextual and individual inequalities in breast cancer screening participation and outcomes in Turin (North-West Italy).

Breast cancer incidence and screening participation exhibit an unequal distribution in the population. This study aims to investigate the impact of socioeconomic position (SEP) on three breast screening indicators (participation, recall, and cancer detection rates) among women aged 50-69 in the city of Turin between 2010 and 2019. The study also aims to determine whether contextual factors (deprivation index) or individual factors (educational level) have a greater influence. The data used in this study are sourced from the Turin Breast Screening Program (TBSP) and the Turin Longitudinal Study (TLS). To test the hypothesis and account for the hierarchical structure of the data, multilevel models were used. Both contextual and individual SEP were found to be associated with screening participation. Participation increased with higher levels of deprivation (odds ratio for most deprived: 1.13; 95% CI 1.11-1.16) and decreased with higher educational levels (OR for low educated: 1.37; 95% CI 1.34-1.40). Contextual SEP did not show any association with recall or cancer detection rates, but individual SEP had an impact. Women with lower educational levels had a statistically significant 19% lower odds of being recalled and a statistically significant 20% lower odds of being diagnosed with cancer. Additionally, immigrant women were less likely to participate in screening, be recalled, or receive a cancer diagnosis. Educational level consistently influenced the analyzed screening indicators, while contextual deprivation appeared to have less importance. It is likely that women living in less deprived areas and with higher education have greater access to opportunistic screening.

Avoidable Hospitalization for Heart Failure Among a Cohort of 18- to 64-Year-Old Italian Citizens and Immigrants: Results From the Italian Network for Longitudinal Metropolitan Studies.

BACKGROUND: Heart failure (HF) represents a severe public health burden. In Europe, differences in hospitalizations for HF have been found between immigrants and native individuals, with inconsistent results. Immigrants face many barriers in their access to health services, and their needs may be poorly met. We aimed to compare the rates of avoidable hospitalization for HF among immigrants and native individuals in Italy. METHODS: All 18- to 64-year-old residents of Turin, Venice, Reggio Emilia, Modena, Bologna, and Rome between January 1, 2001 and December 31, 2013 were included in this multicenter open-cohort study. Immigrants from high migratory pressure countries (divided by area of origin) were compared with Italian citizens. Age-, sex-, and calendar year-adjusted hospitalization rate ratios and the 95% CIs of avoidable hospitalization for HF by citizenship were estimated using negative binomial regression models. The hospitalization rate ratios were summarized using a random effects meta-analysis. Additionally, we tested the contribution of socioeconomic status to these disparities. RESULTS: Of the 4 470 702 subjects included, 15.8% were immigrants from high migratory pressure countries. Overall, immigrants showed a nonsignificant increased risk of avoidable hospitalization for HF (hospitalization rate ratio, 1.26 [95% CI, 0.97-1.68]). Risks were higher for immigrants from Sub-Saharan Africa and for males from Northern Africa and Central-Eastern Europe than for their Italian citizen counterparts. Risks were attenuated adjusting for socioeconomic status, although they remained consistent with nonadjusted results. CONCLUSIONS: Adult immigrants from different geographic macroareas had higher risks of avoidable hospitalization for HF than Italian citizens. Possible explanations might be higher risk factors among immigrants and reduced access to primary health care services.

Predictive Modeling for Frailty Conditions in Elderly People: Machine Learning Approaches.

BACKGROUND: Frailty is one of the most critical age-related conditions in older adults. It is often recognized as a syndrome of physiological decline in late life, characterized by a marked vulnerability to adverse health outcomes. A clear operational definition of frailty, however, has not been agreed so far. There is a wide range of studies on the detection of frailty and their association with mortality. Several of these studies have focused on the possible risk factors associated with frailty in the elderly population while predicting who will be at increased risk of frailty is still overlooked in clinical settings. OBJECTIVE: The objective of our study was to develop predictive models for frailty conditions in older people using different machine learning methods based on a database of clinical characteristics and socioeconomic factors. METHODS: An administrative health database containing 1,095,612 elderly people aged 65 or older with 58 input variables and 6 output variables was used. We first identify and define six problems/outputs as surrogates of frailty. We then resolve the imbalanced nature of the data through resampling process and a comparative study between the different machine learning (ML) algorithms - Artificial neural network (ANN), Genetic programming (GP), Support vector machines (SVM), Random Forest (RF), Logistic regression (LR) and Decision tree (DT) - was carried out. The performance of each model was evaluated using a separate unseen dataset. RESULTS: Predicting mortality outcome has shown higher performance with ANN (TPR 0.81, TNR 0.76, accuracy 0.78, F1-score 0.79) and SVM (TPR 0.77, TNR 0.80, accuracy 0.79, F1-score 0.78) than predicting the other outcomes. On average, over the six problems, the DT classifier has shown the lowest accuracy, while other models (GP, LR, RF, ANN, and SVM) performed better. All models have shown lower accuracy in predicting an event of an emergency admission with red code than predicting fracture and disability. In predicting urgent hospitalization, only SVM achieved better performance (TPR 0.75, TNR 0.77, accuracy 0.73, F1-score 0.76) with the 10-fold cross validation compared with other models in all evaluation metrics. CONCLUSIONS: We developed machine learning models for predicting frailty conditions (mortality, urgent hospitalization, disability, fracture, and emergency admission). The results show that the prediction performance of machine learning models significantly varies from problem to problem in terms of different evaluation metrics. Through further improvement, the model that performs better can be used as a base for developing decision-support tools to improve early identification and prediction of frail older adults.

[Testing of interventions for prevention of heat wave related deaths: results among frail elderly and methodological problems]. / Sperimentazione di interventi di prevenzione di danni alla salute da ondate di calore: risultati sulla popolazione anziana fragile e problemi metodologici.

OBJECTIVE: to evaluate the impact of a programme based on soft home care services and an offer of social caretaking, compared to one based only on soft home care, for the prevention of heat-related health events among clinically and/or functionally frail elderly. DESIGN: cluster randomised controlled trial. SETTING AND PARTICIPANTS: the study population included 2,612 persons over 75 years of age living alone in the city of Turin, North-West Italy, who were classified as clinically (hospitalization with specific diagnoses before summer 2004) and/or functionally (were receiving a disability pension) frail. MAIN OUTCOME MEASURES: a programme' s impact was evaluated on the basis of the hospitalizations and deaths that occurred during summer 2004, using gender-specific multilevel logistic regression models, controlling first for age and then also for education and income. RESULTS: among males, a weak protection against emergency hospitalization was observed within the group randomised to soft home care services and offer of social caretaking, compared to the only soft home care group (OR=0.33, 95% CI=0.11; 0.96). Among females, the programme including social caretaking seemed to lower the overall risk of hospitalization (OR=0.96, 95% CI=0.93; 0.98). CONCLUSION: this study has two important public health implications: first, it highlights the potential impact of programmes based on both soft home care and offer of social caretaking; second, it helps to raise awareness, both among health/social work and in the community, of the need for protection during summer periods for the elderly.

The Effects of the Urban Built Environment on Mental Health: A Cohort Study in a Large Northern Italian City.

Mental health (MH) has a relevant burden on the health of populations. Common MH disorders (anxiety and non-psychotic depression) are well associated to socioeconomic individual and neighborhood characteristics, but little is known about the influence of urban structure. We analyzed among a Turin (Northwest Italy) urban population the association at area level of different urban structure characteristics (density, accessibility by public transport, accessibility to services, green and public spaces) and consumption of antidepressants. Estimates were adjusted by individual socio-demographic variables (education, housing tenure, employment) and contextual social environment (SE) variables (social and physical disorder, crime rates). Data was extracted from the Turin Longitudinal Study (TLS)-a census-based cohort study following up prospectively the mortality and morbidity of the population. As expected, individual characteristics show the strongest association with antidepressant drug consumption, while among built environment (BE) indicators accessibility by public transport and urban density only are associated to MH, being slightly protective factors. Results from this study, in agreement with previous literature, suggest that BE has a stronger effect on MH for people who spend more time in the neighborhood. Therefore, this research suggests that good accessibility to public transport, as well as a dense urban structure (versus sprawl), could contribute to reduced risk of depression, especially for women and elderly, by increasing opportunities to move around and have an active social life.