Background Socioeconomic status (SES) is a well-recognized determinant of health. A high prevalence of risk factors for non-communicable diseases along with reduced access to early diagnosis and effective treatment have historically been thought to be the main mechanisms underlying the relationship between low SES and poor health. However, the phenomenon is more complex and involves also psychosocial factors, such as stress, depression, financial difficulties, lack of social support, and low job control, all risk factors for poor health. Nowadays, inequalities in health represents a major challenge for health policies, having a high social, ethical and economic impact even in high-income countries. This is particularly true during economic recessions, when unemployment and financial problems is expected to affect more people with medium or low SES. However, results on the impact of macroeconomic changes on socioeconomic inequalities in health are controversial and substantial differences exist among European countries with higher inequality in North and East Europe compared to southern European countries. In Europe, the evidence on inequalities in mortality comes mainly from national, longitudinal, census-linked or unlinked studies, whereas in Italy most of the data are based only on urban areas. The lack of national study precludes a comprehensive analysis of socioeconomic inequalities in mortality in Italy which can measure the impact of SES on cause-specific mortality and evaluate within-country geographic differences and the interaction with other variables. Aim The study aimed to quantify socioeconomic inequality in premature mortality in absolute and relative terms in Italy considering also geographic differences and the role of other variables, such as marital status, size of the municipality, and social and material vulnerability of the municipality of residence. Methods The study was based on the record linkage of national administrative databases, including the 2011 census and the mortality registries. Each death occurred in Italy from census date (9 October 2011) onwards was linked to the census using the tax identification number as linkage key. This allowed to conduct a cohort study based on all Italian residents. In this report, the mortality registries for the period 2011-2015 were linked to the 2011 census and the individuals alive on 1 January 2012 were included in the cohort. Education and occupation were used to determine the SES of the individual. Four levels of education were considered: no education or primary school, middle school, high school and university. Occupation-based social class was obtained by using the Erikson-Goldthorpe scheme with the following classes: non-skilled manual, skilled manual workers, farmers, self-employees, routine non-manual and upper non-manual workers. Relative inequality was measured by computing the age-adjusted mortality rate ratio (MRR) and the relative index of inequality (RII), whereas absolute inequality was measured by calculating the slope index of inequality (SII). The MRR and the RII was estimated by fitting multiplicative Poisson regression models, whereas the SII was estimated by fitting additive Poisson models. RII and SII were obtained by regressing the mortality rate of SES groups on a specific measure of their relative position in the social hierarchy: the socioeconomic rank, i.e. the proportion of the population that has a higher position, scaled to take values between 0 (highest rank) and 1 (lowest rank). The level of education was used to obtain the socioeconomic rank. RII and SII express the magnitude of socioeconomic inequality in relative and absolute terms, respectively, by providing a unique estimate of the inequality that can be used for comparisons within the same population or between different populations. The resulting figures can be interpreted as the ratio (for RII) or difference (for SII) of mortality rates between those at the bottom and those at the top of the social hierarchy. RII and SII were used to rank the causes of death by relative and absolute inequality. Results A total of 35,708,445 subjects aged between 30 and 74 years were included in the study. In four years of follow-up, 573,335 deaths were registered over 137,847,954 person-years at risk. Being low educated and having a less prestigious job had a negative effect on overall premature mortality and mortality from most of the causes of death considered in this study. Compared to men with the highest level of education (university graduates), the MRR from all causes was 1.30 (95% CI: 1.10-1.53) for men with high school diploma, 1.64 (95% CI: 1.40-1.92) for those with middle school diploma and 1.93 (95% CI: 1.65-2.27) among those with no education or primary school certificate. Compared to women with the highest level of education (university graduates), the MRR from all causes was 1.14 (95% CI: 1.01-1.29) for women with high school diploma, 1.31 (95% CI: 1.16-1.48) for those with middle school diploma and 1.44 (95% CI: 1.28-1.63) among those with no education or primary school certificate. Compared to men in the upper non-manual class, the MRR from all causes was 1.24 (95% CI: 1.18-1.30) among routine non-manual workers, 1.31 (95% CI: 1.24- 1.38) among self-employees, 1.48 (95% CI: 1.35-1.63) among farmers, 1.37 (95% CI: 1.30- 1.45) among skilled manual workers and 1.63 (95% CI: 1.55-1.71) among non-skilled manual workers. In women, all the other classes showed only a slight increase in mortality as compared to upper non-manual workers, with the only exception of farmers who had comparable mortality rates. The MRR was 1.07 (95% CI: 1.02-1.13) among routine non-manual workers, 1.14 (95% CI: 1.06-1.23) among self-employees, 1.03 (95% CI: 0.89-1.19) among farmers, 1.08 (95% CI: 0.98-1.20) among skilled manual workers and 1.09 (95% CI: 1.03-1.16) among non-skilled manual workers. Socioeconomic inequality for all-cause mortality was higher in men than in women, both in relative (RII for men: 2.07, 95% CI: 1.81-2.37, RII for women: 1.51, 95% CI: 1.35-1.68) and absolute terms (SII for men: 373 deaths per 100.000 person-years, 95% CI: 327-419, SII for women: 113 deaths per 100.000 person-years, 95% CI: 88-138). In relative terms, the causes of death with the highest inequality were: laryngeal cancer (RII: 5.69, 95% CI: 4.54-7.15), chronic liver diseases (RII: 5.03, 95% CI: 3.72-6.80), chronic lower respiratory diseases (RII: 4.83, 95% CI: 3.59-6.50) and HIV/AIDS (RII: 4.77, 95% CI: 3.11-7.31) among men, and diabetes (RII: 5.75, 95% CI: 4.48-7.37), HIV/AIDS (RII: 4.33, 95% CI: 2.55-7.38) and chronic liver diseases (RII: 3.47, 95% CI: 2.71-4.44) among women. The causes of death with the highest absolute socioeconomic inequality were: circulatory system diseases (SII: 85 deaths per 100,000 person-years, 95% CI: 76-94) and lung cancer (SII: 58 deaths, 95% CI: 52-64) among men, and circulatory system diseases (SII: 43 deaths, 95% CI: 37-49) and diabetes (SII: 12 deaths, 95% CI: 10; 14) among women. Socioeconomic inequality in all-cause mortality was higher among singles (RII in men: 3.24, 95% CI: 2.68-3.92, RII in women: 2.71, 95% CI: 2.11-3.49), separated or divorced (RII in men: 2.58, 95% CI: 2.30-2.58, RII in women: 1.67, 95% CI: 1.26-1.50) than married individuals (RII in men: 1.80, 95% CI: 1.63-1.98, RII in women 1.42, 95% CI: 1.32-1.53). People living in large municipalities (≥50,000 residents) showed a higher level of socioeconomic inequality (RII in men: 2.42, 95% CI: 2.09-2.79, RII in women: 1.68, 95% CI: 1.68, 95% CI 1.52-1.86) than those living in small municipalities (<2000 residents) (RII in men: 1.88, 95% CI: 1.66-2.14, RII in women: 1.40, 95% CI: 1.12-1.62). Women living in municipalities with high social and material vulnerability showed higher socioeconomic inequality in overall mortality (RIIs: 1.70, 95% CI: 1.51-1.91 and 1.34, 95% CI: 1.19-1.49 for those living in the last and first fifths of the distribution of the vulnerability index of the municipality of residence, respectively), whereas the estimates among men overlapped. Socioeconomic inequality in mortality from circulatory system diseases and diabetes was greater in women from southern Italy, while there are no substantial geographic differences in men. The RIIs for all circulatory system diseases were: 2.73 (95% CI: 2.39-3.12) in women living in the South, 1.86 (95% CI: 1.55-2.22) in those living in the Center and 2.01 (95% CI: 2.01, 1.72-2.36) in those living in the North. The RIIs for diabetes were: 6.21 (95% CI: 4.80-8.08) in women living in the South, 4.32 (95% CI: 3.33-5.61) in those living in the Center and 3.71 (95% CI: 2.78, 1.72-4.95) in those living in the North of the country. Conclusions The successful linkage of national databases allowed, for the first time, to provide a comprehensive picture of socioeconomic inequality in mortality in Italy. Socioeconomic inequality in premature mortality is still a major public health problem in Italy. It is more pronounced among some groups of the population, such as singles, separated and divorced individuals, those living in large municipalities, and women living in southern Italy or in municipalities with high social and material vulnerability. Lung cancer (in men), circulatory system diseases (in both sexes) and diabetes (in women) are the major contributors to the absolute socioeconomic inequality in Italy. The findings of this study will have important implications for planning policies to reduce the existing disparities in mortality in Italy.

SOCIOECONOMIC INEQUALITY IN PREMATURE MORTALITY IN ITALY: A NATIONAL CENSUS-BASED RECORD LINKAGE STUDY / G. Alicandro ; tutor: C. La Vecchia. - : . DIPARTIMENTO DI SCIENZE CLINICHE E DI COMUNITA', 2019 Jan 18. ((31. ciclo, Anno Accademico 2018. [10.13130/alicandro-gianfranco_phd2019-01-18].

SOCIOECONOMIC INEQUALITY IN PREMATURE MORTALITY IN ITALY: A NATIONAL CENSUS-BASED RECORD LINKAGE STUDY

ALICANDRO, GIANFRANCO
2019-01-18

Abstract

Background Socioeconomic status (SES) is a well-recognized determinant of health. A high prevalence of risk factors for non-communicable diseases along with reduced access to early diagnosis and effective treatment have historically been thought to be the main mechanisms underlying the relationship between low SES and poor health. However, the phenomenon is more complex and involves also psychosocial factors, such as stress, depression, financial difficulties, lack of social support, and low job control, all risk factors for poor health. Nowadays, inequalities in health represents a major challenge for health policies, having a high social, ethical and economic impact even in high-income countries. This is particularly true during economic recessions, when unemployment and financial problems is expected to affect more people with medium or low SES. However, results on the impact of macroeconomic changes on socioeconomic inequalities in health are controversial and substantial differences exist among European countries with higher inequality in North and East Europe compared to southern European countries. In Europe, the evidence on inequalities in mortality comes mainly from national, longitudinal, census-linked or unlinked studies, whereas in Italy most of the data are based only on urban areas. The lack of national study precludes a comprehensive analysis of socioeconomic inequalities in mortality in Italy which can measure the impact of SES on cause-specific mortality and evaluate within-country geographic differences and the interaction with other variables. Aim The study aimed to quantify socioeconomic inequality in premature mortality in absolute and relative terms in Italy considering also geographic differences and the role of other variables, such as marital status, size of the municipality, and social and material vulnerability of the municipality of residence. Methods The study was based on the record linkage of national administrative databases, including the 2011 census and the mortality registries. Each death occurred in Italy from census date (9 October 2011) onwards was linked to the census using the tax identification number as linkage key. This allowed to conduct a cohort study based on all Italian residents. In this report, the mortality registries for the period 2011-2015 were linked to the 2011 census and the individuals alive on 1 January 2012 were included in the cohort. Education and occupation were used to determine the SES of the individual. Four levels of education were considered: no education or primary school, middle school, high school and university. Occupation-based social class was obtained by using the Erikson-Goldthorpe scheme with the following classes: non-skilled manual, skilled manual workers, farmers, self-employees, routine non-manual and upper non-manual workers. Relative inequality was measured by computing the age-adjusted mortality rate ratio (MRR) and the relative index of inequality (RII), whereas absolute inequality was measured by calculating the slope index of inequality (SII). The MRR and the RII was estimated by fitting multiplicative Poisson regression models, whereas the SII was estimated by fitting additive Poisson models. RII and SII were obtained by regressing the mortality rate of SES groups on a specific measure of their relative position in the social hierarchy: the socioeconomic rank, i.e. the proportion of the population that has a higher position, scaled to take values between 0 (highest rank) and 1 (lowest rank). The level of education was used to obtain the socioeconomic rank. RII and SII express the magnitude of socioeconomic inequality in relative and absolute terms, respectively, by providing a unique estimate of the inequality that can be used for comparisons within the same population or between different populations. The resulting figures can be interpreted as the ratio (for RII) or difference (for SII) of mortality rates between those at the bottom and those at the top of the social hierarchy. RII and SII were used to rank the causes of death by relative and absolute inequality. Results A total of 35,708,445 subjects aged between 30 and 74 years were included in the study. In four years of follow-up, 573,335 deaths were registered over 137,847,954 person-years at risk. Being low educated and having a less prestigious job had a negative effect on overall premature mortality and mortality from most of the causes of death considered in this study. Compared to men with the highest level of education (university graduates), the MRR from all causes was 1.30 (95% CI: 1.10-1.53) for men with high school diploma, 1.64 (95% CI: 1.40-1.92) for those with middle school diploma and 1.93 (95% CI: 1.65-2.27) among those with no education or primary school certificate. Compared to women with the highest level of education (university graduates), the MRR from all causes was 1.14 (95% CI: 1.01-1.29) for women with high school diploma, 1.31 (95% CI: 1.16-1.48) for those with middle school diploma and 1.44 (95% CI: 1.28-1.63) among those with no education or primary school certificate. Compared to men in the upper non-manual class, the MRR from all causes was 1.24 (95% CI: 1.18-1.30) among routine non-manual workers, 1.31 (95% CI: 1.24- 1.38) among self-employees, 1.48 (95% CI: 1.35-1.63) among farmers, 1.37 (95% CI: 1.30- 1.45) among skilled manual workers and 1.63 (95% CI: 1.55-1.71) among non-skilled manual workers. In women, all the other classes showed only a slight increase in mortality as compared to upper non-manual workers, with the only exception of farmers who had comparable mortality rates. The MRR was 1.07 (95% CI: 1.02-1.13) among routine non-manual workers, 1.14 (95% CI: 1.06-1.23) among self-employees, 1.03 (95% CI: 0.89-1.19) among farmers, 1.08 (95% CI: 0.98-1.20) among skilled manual workers and 1.09 (95% CI: 1.03-1.16) among non-skilled manual workers. Socioeconomic inequality for all-cause mortality was higher in men than in women, both in relative (RII for men: 2.07, 95% CI: 1.81-2.37, RII for women: 1.51, 95% CI: 1.35-1.68) and absolute terms (SII for men: 373 deaths per 100.000 person-years, 95% CI: 327-419, SII for women: 113 deaths per 100.000 person-years, 95% CI: 88-138). In relative terms, the causes of death with the highest inequality were: laryngeal cancer (RII: 5.69, 95% CI: 4.54-7.15), chronic liver diseases (RII: 5.03, 95% CI: 3.72-6.80), chronic lower respiratory diseases (RII: 4.83, 95% CI: 3.59-6.50) and HIV/AIDS (RII: 4.77, 95% CI: 3.11-7.31) among men, and diabetes (RII: 5.75, 95% CI: 4.48-7.37), HIV/AIDS (RII: 4.33, 95% CI: 2.55-7.38) and chronic liver diseases (RII: 3.47, 95% CI: 2.71-4.44) among women. The causes of death with the highest absolute socioeconomic inequality were: circulatory system diseases (SII: 85 deaths per 100,000 person-years, 95% CI: 76-94) and lung cancer (SII: 58 deaths, 95% CI: 52-64) among men, and circulatory system diseases (SII: 43 deaths, 95% CI: 37-49) and diabetes (SII: 12 deaths, 95% CI: 10; 14) among women. Socioeconomic inequality in all-cause mortality was higher among singles (RII in men: 3.24, 95% CI: 2.68-3.92, RII in women: 2.71, 95% CI: 2.11-3.49), separated or divorced (RII in men: 2.58, 95% CI: 2.30-2.58, RII in women: 1.67, 95% CI: 1.26-1.50) than married individuals (RII in men: 1.80, 95% CI: 1.63-1.98, RII in women 1.42, 95% CI: 1.32-1.53). People living in large municipalities (≥50,000 residents) showed a higher level of socioeconomic inequality (RII in men: 2.42, 95% CI: 2.09-2.79, RII in women: 1.68, 95% CI: 1.68, 95% CI 1.52-1.86) than those living in small municipalities (<2000 residents) (RII in men: 1.88, 95% CI: 1.66-2.14, RII in women: 1.40, 95% CI: 1.12-1.62). Women living in municipalities with high social and material vulnerability showed higher socioeconomic inequality in overall mortality (RIIs: 1.70, 95% CI: 1.51-1.91 and 1.34, 95% CI: 1.19-1.49 for those living in the last and first fifths of the distribution of the vulnerability index of the municipality of residence, respectively), whereas the estimates among men overlapped. Socioeconomic inequality in mortality from circulatory system diseases and diabetes was greater in women from southern Italy, while there are no substantial geographic differences in men. The RIIs for all circulatory system diseases were: 2.73 (95% CI: 2.39-3.12) in women living in the South, 1.86 (95% CI: 1.55-2.22) in those living in the Center and 2.01 (95% CI: 2.01, 1.72-2.36) in those living in the North. The RIIs for diabetes were: 6.21 (95% CI: 4.80-8.08) in women living in the South, 4.32 (95% CI: 3.33-5.61) in those living in the Center and 3.71 (95% CI: 2.78, 1.72-4.95) in those living in the North of the country. Conclusions The successful linkage of national databases allowed, for the first time, to provide a comprehensive picture of socioeconomic inequality in mortality in Italy. Socioeconomic inequality in premature mortality is still a major public health problem in Italy. It is more pronounced among some groups of the population, such as singles, separated and divorced individuals, those living in large municipalities, and women living in southern Italy or in municipalities with high social and material vulnerability. Lung cancer (in men), circulatory system diseases (in both sexes) and diabetes (in women) are the major contributors to the absolute socioeconomic inequality in Italy. The findings of this study will have important implications for planning policies to reduce the existing disparities in mortality in Italy.
LA VECCHIA, CARLO VITANTONIO BATTISTA
Settore MED/01 - Statistica Medica
SOCIOECONOMIC INEQUALITY IN PREMATURE MORTALITY IN ITALY: A NATIONAL CENSUS-BASED RECORD LINKAGE STUDY / G. Alicandro ; tutor: C. La Vecchia. - : . DIPARTIMENTO DI SCIENZE CLINICHE E DI COMUNITA', 2019 Jan 18. ((31. ciclo, Anno Accademico 2018. [10.13130/alicandro-gianfranco_phd2019-01-18].
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