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Editorial
. 2020 Dec;15(4):490-502.
doi: 10.26574/maedica.2020.15.4.490.

Association of Family Income with Health Indices and Healthcare Utilization in a Large Sample of Residents in Northern Greece

Orestia Zissimopoulou  1 , Eleni Leontidou  1 , Dimitrios Tsiptsios  2 , Apostolos Manolis  1 , Dimitrios Ioannides  3 , Ioanna Trypsiani  1 , Paschalis Steiropoulos  4 , Theodoros C Constantinidis  5 , Gregory Tripsianis  1 , Evangelia Nena  6
Affiliations
Editorial

Association of Family Income with Health Indices and Healthcare Utilization in a Large Sample of Residents in Northern Greece

Orestia Zissimopoulou et al. Maedica (Bucur). 2020 Dec.

Abstract

Objective:To describe the impact of subjects' family income, which was used as a proxy for socioeconomic status, with health characteristics and healthcare utilization of a large representative sample of population in Northern Greece, taking into account several socio-demographic characteristics and health behaviors of the participants. Material and method:Eight hundred and twelve participants (43.7% males) with a mean age of 49.±14.8 years (range 19-83 years), from the area of Thrace, Greece, were enrolled in this cross-sectional populational study. A two-stage stratified sampling scheme was used and subjects were classified, according to the net mean monthly household income, into three financial levels: low .1000 Euro; medium 1001-2000 Euro; and high >2000 Euro. Self-reported questionnaires for socio-demographic, lifestyle and health related characteristics were collected. Sleep characteristics, utilizing Epworth Sleepiness Scale, Athens Insomnia Scale, Pittsburgh Sleep Quality Index and Berlin Questionnaire, and mental health, using Zung Self-rating Anxiety Scale and Beck Depression Inventory have been also assessed. Results:The majority of participants belonged to the lower income level (476 subjects, 58.6%). Lower income level was associated with a higher prevalence of high alcohol consumption (p=0.030), low adherence to Mediterranean diet (p=0.016), low physical activity (p<0.001) and either short or long nocturnal sleep duration (p<0.001). After adjusting for all socio-demographic and lifestyle characteristics, subjects with low income had a higher risk for anxiety (aOR=1.97, p=0.017), depression (aOR=4.88, p<0.001), dyslipidemia (aOR=2.50, p=0.007), diabetes (aOR=3.58, p<0.001), obesity (aOR=1.97, p=0.038), cardiovascular disease (aOR=3.04, p=0.015) and sleep disorders, as well as for primary (aOR=3.56, p=0.017) and secondary (aOR=2.49, p=0.010) healthcare utilization compared to subjects with high income. Conclusion:Low income is an important factor, which adversely affects the health of individuals via different pathways such as adaptation of harmful everyday habits. Large-scale prospective cohort studies are necessary to verify these associations in a methodologically more robust way.

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Figures

TABLE 1.
TABLE 1.
Association of participants’ income with their sociodemographic characteristics
TABLE 2.
TABLE 2.
Association of subjects’ income with lifestyle factors, health characteristics and healthcare utilization
TABLE 3.
TABLE 3.
Association of subjects’ income with their health characteristics and healthcare utilization expressed as crude odds ratios (OR) with 95% confidence intervals (95% CIs) obtained by means logistic regression analysis.
TABLE 4.
TABLE 4.
Association of subjects’ income with their health characteristics and healthcare utilization expressed as adjusted odds ratios (aOR) with 95% confidence intervals (95% CI) obtained by means multivariate logistic regression analysis.
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References

    1. Organization for Economic Co-operation and Development (OECD) Society at a Glance 2014. Available from https://read.oecd-ilibrary.org/social-issues-migration-health/society-at.... Accessed on November 3rd, 2020. 2020.
    1. Andriopoulou E, Karakitsios A, Tsakloglou P. Inequality and Poverty in Greece: Changes in Times of Crisis. In: Katsikas D, Sotiropoulos D, Zafiropoulou M, eds. Socioeconomic Fragmentation and Exclusion in Greece under the Crisis. New Perspectives on South-East Europe. Palgrave Macmillan/Cham. 2018. pp. 23–54.
    1. Organization for Economic Co-operation and Development (OECD) Youth unemployment rate. 2018 figures. Available from: https://data.oecd.org/unemp/youthunemployment- rate.htm#indicator-chart. 2020.
    1. Mitrakos T. Inequality, poverty and living conditions in Greece: Recent developments and prospects. Social Cohesion and Development. 2013;1:37–58.
    1. Eurostat. In-work poverty in the EU. 2017 figures. Available from: https://ec.europa.eu/eurostat/web/ products-eurostat-news/-/DDN-20180316-1. Accessed on November 3rd, 2020. 2020.

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