Socioeconomic inequality in non-communicable diseases in Europe between 2004 and 2015: evidence from the SHARE survey

Bono, Filippa; Matranga, Domenica

doi:10.1093/eurpub/cky165

Cited by 19 publications

(15 citation statements)

References 34 publications

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“…For both SPH and NCDs, income did not play any role. This result is in line with other literature using the SHARE dataset, as it was found that both the number of NCDs and socioeconomic inequality in NCDs were more likely to be related to differences in education than income [50].…”

Section: Discussionsupporting

confidence: 93%

Self-Perceived Health, Objective Health, and Quality of Life among People Aged 50 and Over: Interrelationship among Health Indicators in Italy, Spain, and Greece

Maniscalco

Miceli

Bono

et al. 2020

IJERPH

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It is well known that self-perceived health (SPH), even if it is a subjective health indicator, is significantly associated with objective health and quality of life (QoL) in the general population. Whether it can be considered an indicator of cognitive functioning and quality of life in the elderly is still an open issue. This study used a data-driven approach to investigate the interrelationship among SPH, non-communicable diseases (NCDs), QoL, and cognitive functioning to answer this question. The study sample included information about 12,831 people living in Italy, Spain, and Greece, extracted from the Survey on Health, Aging, and Retirement in Europe, in the year 2015. The additive Bayesian networks methodology was used to identify the best directed acyclic graphs (DAG) for SPH, QoL, and NCDs. Results were given as posterior estimates of generalized linear models (GLM) coefficients, with 95% credibility intervals. Good SPH was associated with a decreasing number of chronic diseases in Italy (coeff = −0.52, 95%CI: [−0.59, −0.44]), Spain (coeff = −0.53, 95%CI: [−0.60, −0.46]) and Greece (coeff = −0.57, 95%CI: [−0.64, −0.50]). Age and Body Mass Index were determinants of NCDs in all countries. QoL of elderly was associated with SPH in Italy (coeff = 0.12, 95%CI: [0.10, 0.14]), Spain (coeff = 0.16, 95%CI: [0.15, 0.18]), and Greece (coeff = 0.18, 95%CI: [0.16, 0.20]). The number of NCDs was higher for people who were not employed in Spain (coeff = 0.45, 95%CI: [0.37, 0.53]) and was decreasing for a unitary increase in years of education in Greece (coeff = −0.12, 95%CI: [−0.14, −0.09]). As a general rule, the framework of the interrelationship among NCDs, SPH, and QoL was similar for Italy, Spain, and Greece. The connections found among indicators could be proposed to identify strategies for health promotion and healthy aging among people aged 50 and above, which are viable in general and at a country level. Reinforcing strategies targeted at some health indicators could have relevant effects on other related indicators.

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Section: Discussionsupporting

confidence: 93%

Self-Perceived Health, Objective Health, and Quality of Life among People Aged 50 and Over: Interrelationship among Health Indicators in Italy, Spain, and Greece

Maniscalco

Miceli

Bono

et al. 2020

IJERPH

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“…Obesity is significantly associated with all-cause mortality [ 9 ] for example by increased rates of diabetes, cardiovascular disease and cancer. Where there is strong social patterning of obesity it is likely to make an increasing contribution to health inequalities [ 10 ]. A European study used population attributable fractions and rate ratios from the literature to estimate how a scenario elimination of differences in obesity by education would decrease relative inequality in all-cause mortality.…”

Section: Introductionmentioning

confidence: 99%

Changing social inequalities in smoking, obesity and cause-specific mortality: Cross-national comparisons using compass typology

et al. 2020

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Background In many countries smoking rates have declined and obesity rates have increased, and social inequalities in each have varied over time. At the same time, mortality has declined in most high-income countries, but gaps by educational qualification persist-at least partially due to differential smoking and obesity distributions. This study uses a compass typology to simultaneously examine the magnitude and trends in educational inequalities across multiple countries in: a) smoking and obesity; b) smoking-related mortality and c) cause-specific mortality. Methods Smoking prevalence, obesity prevalence and cause-specific mortality rates (35-79 year olds by sex) in nine European countries and New Zealand were sourced from between 1980 and 2010. We calculated relative and absolute inequalities in prevalence and mortality (relative and slope indices of inequality, respectively RII, SII) by highest educational qualification. Countries were then plotted on a compass typology which simultaneously examines trends in the population average rates or odds on the x-axis, RII on the Y-axis, and contour lines depicting SII. Findings Smoking and obesity. Smoking prevalence in men decreased over time but relative inequalities increased. For women there were fewer declines in smoking prevalence and relative inequalities tended to increase. Obesity prevalence in men and women increased over time with a mixed picture of increasing absolute and sometimes relative inequalities.

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“…In Hong Kong, the association between ST and the weight outcomes was stronger in lower-educated than in higher-educated participants, while no moderating effect of educational level was found in Ghent. In general, lower-educated individuals often have a less healthy lifestyle than their higher-educated counterparts [52,53]. Thus, it is possible that higher-educated Hong Kong older adults might have compensated for the negative effects of ST by following a healthier diet.…”

Section: Discussionmentioning

confidence: 99%

Main and interacting effects of physical activity and sedentary time on older adults’ BMI: The moderating roles of socio-demographic and environmental attributes

et al. 2020

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Objectives Our first aim was to examine the main and interacting effects of accelerometer-based sedentary time (ST) and moderate-to-vigorous physical activity (MVPA) with BMI and the likelihood of being overweight/obese in Hong Kong and Ghent (Belgium) older adults. Second, we examined whether these main associations and interactions between MVPA and ST were moderated by socio-demographics (gender, education) and objective neighbourhood attributes supposed to be associated with healthy food intake (food outlet density, neighbourhood-level SES). Finally, we determined whether the associations and interactions were generalisable across study sites. Methods Data from the ALECS (Hong Kong) and BEPAS Seniors studies (Ghent), two comparable observational studies, were used. Older adults (n = 829, 65+) provided self-reported sociodemographic information and objective MVPA and ST data using Actigraph accelerometers. Annual household income data and GIS software were used to assess neighbourhood-level SES and food outlet density. Generalised additive mixed models were conducted in R. Results ST was linearly and positively related to both weight outcomes in the overall sample, while MVPA was not. The overall-sample analyses including the two-way interaction between MVPA and ST showed no interactions between these behaviours on weight outcomes. Three site-specific findings were identified, showing distinct associations in Hong Kong

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Socioeconomic inequality in non-communicable diseases in Europe between 2004 and 2015: evidence from the SHARE survey

Cited by 19 publications

References 34 publications

Self-Perceived Health, Objective Health, and Quality of Life among People Aged 50 and Over: Interrelationship among Health Indicators in Italy, Spain, and Greece

Self-Perceived Health, Objective Health, and Quality of Life among People Aged 50 and Over: Interrelationship among Health Indicators in Italy, Spain, and Greece

Changing social inequalities in smoking, obesity and cause-specific mortality: Cross-national comparisons using compass typology

Main and interacting effects of physical activity and sedentary time on older adults’ BMI: The moderating roles of socio-demographic and environmental attributes

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