| Abstract |
This study aimed to assess health assessment and compare the use of preventive and other health services and their cost or availability in different regions of Europe before and during the economic crisis.
The data used in the study were taken from Wave 8 (2019/2020), (Release data 8.0.0/10.02.2022), of the 'Survey of Health, Ageing and Retirement in Europe - SHARE' ('Survey of Health, Ageing and Retirement in Europe - SHARE', http://www.share-project.org/home0.html) (Börsch-Supan, 2022? Bergmann & Börsch-Supan, 2021; Bergmann & Börsch-Supan, 2021; Börsch-Supan et al., 2013), with a sample size of 46,106 individuals aged ≥50 years in 27 countries, 2013), and Wave 1 data (2004/5), with 16,120 adults aged 50+ years in 11 countries; Austria, Belgium, Denmark, France, Germany, Greece, Italy, The Netherlands, Spain, Sweden, and Switzerland, adjusted to represent a population of N=180,886. The overall study sample was composed of representative, stratified, composite samples of adults, selected proportionally in each country by probability sampling. From the beginning of the study (Wave 1, 2004/5), the target population consisted of households, and by extension their members, where at least one member was 50+ years old (Bergmann & Börsch-Supan, 2021; Börsch-Supan, 2022).
The research was organized & coordinated by the Research Institute of Mannheim-Germany and is a collaborative effort of interdisciplinary, national & transnational working groups (the Greek team consists of members of the Universities of Panteion, Piraeus and Crete).
The CAPI questionnaire, consisting of 31 modules such as demographic data of the participants (or their household members or proxies), social networks, physical & mental health, employment and retirement, cognitive function, etc. was administered by personal computer interview. or measures such as handgrip strength or walking speed. In some sections, pre-selected cards were used to aid understanding, direct and reliable responses to the questions (Crimmins et al., 2011).
Preventive health services utilization scores (PHSUs) and health care services utilization scores (HCSUs) were assessed as a composite of responses to 12 and 16 questions respectively, on a scale ranging from 0 to 100. The estimates were based on a composite study design.
Lack of accessibility/availability of healthcare services (LAAHCS) was assessed with a composite score using 16 questions. Frailty symptomatology refers to the absence or aggregation/presence of multiple symptoms 1-4 for populations aged 50+ years. It was measured using four indicators: 'falling down', 'fear of falling down', 'dizziness, faints or blackouts' & 'fatigue'.
Data were analyzed using the SPSS software package (IBM SPSS Statistics for Windows, version 25.0, IBM Corp., Armonk, NY, USA). Relative and absolute distributions of descriptive characteristics of participants were estimated, as weights were applied according to the study's composite multi-stage stratification sampling design, taking into account non-responses. Using the weights, the results were extrapolated to the actual estimated reference population of the countries. The prevalence and comparative respective 95% confidence intervals (95% CI) of the PHSU, HCSU and LAAHCS components were estimated. In the 27 countries, PHSUs, HCSUs and LAAHCSs were plotted as a spider diagram. The frequency of LAAHCS scores in relation to participant characteristics was estimated using the chi-square χ2 method. In addition, the mean PHSUs and HCSUs were assessed and compared across European regions or according to the frequency of LAAHCS scores using analysis of covariance (ANCOVA) that also estimated the respective 95% CIs for comparative purposes. Estimates were based on composite sample analysis using as covariates (potential confounders) the baseline characteristics of participants, such as sex, age distribution (years), education status (years), marital status, occupation, and chronic conditions or diseases.
In the 11 countries, PHSUs and HCSUs were also depicted on a spider graph. Finally, comparisons of PHSUs and HCSUs according to different participant characteristics were examined using multivariate analysis of covariance. Excluding the current characteristic each time, the covariates used were gender, age (year categories), education (year categories), living status, chronic diseases, retirement status, income, and European regions (polynomial trends in the classified characteristics were assessed).
According to the results of the present study, participants from Central European countries were found to have significantly higher mean PHSU and HCSU values than their counterparts in the northern and southern regions, (p < 0.05) and also showed a greater difference between the two values (29.3, 95%CI: 28.6-30.1). The overall mean PHSU score was 39.9 (95%CI: 39.4-40.4) and the mean HCSU score was 12.4 (95%CI: 12.2-12.7). Women had higher mean PHSUs and HCSUs (p < 0.001); as age increased, PHSUs decreased and HCSUs increased (p < 0.001). Better educated participants appear to have higher mean PHSUs and HCSUs (p < 0.001). In addition, both of the above scores increase with the presence of chronic diseases (p < 0.001). Southern countries had lower use of preventive services and higher use of other health services compared to northern countries, with a significant lack of convergence. In addition, the use of preventive health services decreased, while the use of secondary care services increased during the period of economic crisis and austerity. Southern European countries had a significantly higher prevalence of lack of accessibility. There was an increase in the prevalence of lack of accessibility/availability of health services from 2004/5 to 2019/20.
Finally participants with 3-4 symptoms of frailty versus those with none appeared to have significantly higher health service prevention and utilisation scores (p-trend≤0.001). At the same time, they have a significantly smaller discrepancy between the two types of services. The range (gap) is less than double in prevention-use between the two groups and thus the multiple presence of fragility symptoms determines higher use of both types of services.
In conclusion, there is a strong association between comorbidity, increasing age, educational level and retirement on the one hand, and increased use of health services on the other hand. In addition, our findings suggest that health inequalities increase in times of crisis and fragility is associated with increased use of health services. The use of health services is a major issue in terms of public health policy making. Therefore, health policy interventions need to prioritise accessibility and expand health coverage and preventive services, reducing the vulnerability of the ageing population.
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