Edited by: Tomasz Holecki, Medical University of Silesia, Poland
Reviewed by: Habib Nawaz Khan, University of Science and Technology Bannu, Pakistan; Martin Dlouhy, University of Economics Prague, Czechia
Specialty section: This article was submitted to Health Economics, a section of the journal Frontiers in Public Health
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
Disability either due to illness, aging, or both causes remains an essential contributor shaping European labor markets. Ability of modern day welfare states to compensate an impaired work ability and absenteeism arising from incapacity is very diverse. The aims of this study were to establish and explain intercountry differences among selected European OECD countries and to provide forecasts of future work absenteeism and expenditures on wage replacement benefits.
Two major public registries, European health for all database and Organization for Economic Co-operation and Development database (OECD Health Data), were coupled to form a joint database on 12 core indicators. These were related to disability, work absenteeism, and sickness benefits in European OECD countries. Time horizon 1989–2013 was observed. Forecasting analysis was done on mean values of all data for each single variable for all observed countries in a single year. Trends were predicted on a selected time horizon based on the mean value, in our case, 7 years up to 2020. For this purpose, ARIMA prediction model was applied, and its significance was assessed using Ljung–Box Q test.
Our forecasts based on ARIMA modeling of available data indicate that up to 2020, most European countries will experience downfall of absenteeism from work due to illness. The number of citizens receiving social/disability benefits and the number being compensated due to health-related absence from work will decline. As opposed to these trends, cancer morbidity may become the top ranked disability driver as hospital discharge diagnoses. Concerning development is the anticipated bold growth of hospital discharge frequencies due to cancer across the region. This effectively means that part of these savings on social support expenditure shall effectively be spent to combat strong cancer morbidity as the major driver of disability.
We have clearly growing work load for the national health systems attributable to the clinical oncology acting as the major disability contributor. This effectively means that large share of these savings on public expenditure shall effectively be spent to combat strong cancer morbidity. On another side, we have all signs of falling societal responsibility toward the citizens suffering from diverse kinds of incapacity or impaired working ability and independence. Citizens suffering from any of these causes are likely to experience progressively less social support and publicly funded care and work support compared to the golden welfare era of previous decades.
Permanent or temporary medically confirmed disability has increasingly become a matter of public attention throughout Europe (
Two major public registries, World Health Organization (WHO) that issued European health for all database (HFA-DB) (
Forecasting analysis is the process of making predictions of the future based on past and present data and analysis of trends (
The 12 indicators for this analysis were selected from the complete list of available indicators, because only these ones could be subject to forecasting analysis due to large number of missing values for other indicators. Therefore, countries observed for “absenteeism from work due to illness” indicator (days per employee per year; source: HFA-DB) were Austria, Czech Republic, Hungary, Netherlands, and Slovenia. For indicator number of “people receiving social/disability benefits per 100,000” (source: HFA-DB), observed countries were Austria, Czech Republic, Estonia, Finland, Hungary, Israel, Netherlands, Norway, Slovakia, Sweden, and Switzerland. For indicator “hospital discharges due to cancer” (source: HFA-DB), observed countries were Austria, Czech Republic, Denmark, Estonia, Finland, Greece, Hungary, Italy, Netherlands, Norway, Portugal, Slovenia, Slovakia, Spain, Sweden, and Turkey. For indicator “public expenditure on incapacity%GDP” (disability + sickness benefits; source: OECD Health Data), observed countries were Austria, Czech Republic, France, Hungary, Luxembourg, Netherlands, Slovenia, Sweden, and United Kingdom. For indicator “compensated absence from work due to illness” (source: OECD Health Data), observed countries were Austria, Belgium, Czech Republic, Denmark, Finland, France, Germany, Greece, Ireland, Italy, Luxembourg, Netherlands, Norway, Poland, Portugal, Spain, Sweden, Switzerland, Turkey, and United Kingdom.
Forecasting analysis was done on mean values of all data for each single variable for all observed countries in a single year. On the basis of that mean value trend 1989–2013, we predicted on a selected time horizon, in our case 7 years (2014–2020), how this variable is likely to behave in the future. For this purpose, ARIMA prediction modeling was applied, and its significance was assessed using Ljung–Box Q test.
In Tables
Country (1989–2013) | HFA-DB absenteeism from work due to illness, days per employee per year | HFA-DB people receiving social/disability benefits per 100,000 | HFA-DB% of disabled people of working age engaged in regular occupational activity | HFA-DB disability-adjusted life expectancy (World Health Report) | HFA-DB new invalidity/disability cases per 100,000 | HFA-DB hospital discharges, all neoplasms per 100,000 |
---|---|---|---|---|---|---|
Austria | 12.4 (11.7–12.6) | 4,646.4 (4,441.1–4,925.3) | – | 70.0 (67.1–72.6) | 322.5 (267.9–333.0) | 2,572.8 (2,397.5–2,673.2) |
Belgium | 7.2 (7.0–7.4) | 2,096.0 (2,088.0–2,405.6) | – | 71.0 (67.0–72.7) | – | 1,243.6 (1,223.7–1,263.3) |
Czech Republic | 21.1 (18.2–21.3) | 5,065.1 (4,812.5–5,200.1) | 22.4 (15.7–24.6) | 69.0 (64.2–71.4) | 436.4 (385.8–450.2) | 1,905.9 (1,751.3–1,920.8) |
Denmark | 8.3 (8.1–8.6) | 3,295.3 (3,307.4–3,683.8) | – | 70.0 (66.6–72.1) | – | 1,886.6 (1,874.1–2,027.0) |
Estonia | 9.3 (8.8–9.9) | 6,794.3 (5,306.4–7,595.7) | 22.4 (19.2–26.1) | 67.0 (58.3–72.2) | 1,257.5 (912.3–1,664.5) | 1,136.8 (930.9–1,168.5) |
Finland | 7.8 (7.6–8.2) | 5,401.0 (5,425.1–5,845.9) | 3.9 (3.8–4.1) | 71.0 (67.1–73.1) | 538.2 (508.3–585.1) | 2,209.9 (2,067.5–2,317.8) |
France | – | 441.4 (421.8–451.8) | – | 72.0 (67.8–74.1) | – | 2,035.7 (1,993.1–2,103.4) |
Germany | 16.4 (15.3–17.0) | 8,116.2 (7,794.8–8,612.6) | 4.2 (4.0–4.2) | 71.0 (67.2–73.4) | 218.3 (224.3–279.1) | 2,296.4 (2,176.9–2,348.4) |
Greece | – | 748.7 (691.1–1,010.1) | – | 71.0 (67.4–73.4) | – | 1,444.8 (1,368.0–1,638.3) |
Hungary | 14.9 (13.2–17.3) | 6,547.3 (5,641.6–6,551.9) | 9.5 (8.2–9.5) | 65.0 (60.0–67.9) | 420.0 (364.8–481.0) | 2,421.8 (1,925.4–2,495.7) |
Ireland | – | 3,545.1 (3,245.7–3,592.1) | 31.2 | 71.0 (65.3–74.5) | 147.5 (128.4–408.3) | 822.1 (814.1–838.8) |
Israel | 4.1 (3.9–4.4) | 3,066.6 (2,822.2–3,248.3) | 13.5 (11.2–15.5) | 72.0 (66.8–75.3) | 328.3 (312.0–343.1) | 785.2 (732.5–810.3) |
Italy | – | 2,181.1 (2,056.0–2,633.4) | 16.3 (15.0–16.6) | 73.0 (68.3–75.6) | 860.1 (728.5–902.1) | 1,397.2 (1,360.7–1,480.8) |
Luxembourg | 9.9 (9.2–10.3) | 3,090.6 (2,435.1–3,746.1) | – | 71.0 (66.5–74.6) | – | 1,732.6 (1,659.5–1,969.9) |
Netherlands | 12.0 (11.9–13.9) | 5,655.3 (5,291.3–5,735.3) | 33.5 (31.2–36.5) | 71.0 (67.2–73.7) | – | 947.0 (927.6–977.6) |
Norway | 17.3 (17.0–18.1) | 6,103.5 (5,802.6–6,151.2) | 43.1 (35.7–46.3) | 71.0 (66.4–73.1) | 631.5 (593.6–668.6) | 1,756.4 (1,706.3–1,773.5) |
Poland | 12.3 (8.2–12.0) | 8,776.8 (7,908.6–9,176.2) | 20.8 (19.5–21.5) | 67.0 (62.7–69.6) | 157.2 (139.0–229.0) | 1,147.5 (1,127.4–1,668.3) |
Portugal | 13.0 (10.8–14.7) | 3,421.1 | – | 71.0 (65.1–74.3) | – | 780.2 (733.9–882.7) |
Slovak Republic | 30.9 (26.2–37.0) | 5,167.6 (4,433.0–5,042.5) | 24.1 (9.6–25.6) | 67.0 (62.0–69.5) | 329.9 (311.6–383.5) | 1,571.7 (1,490.5–1,632.2) |
Slovenia | 13.8 (13.0–14.4) | – | 1.0 (0.8–1.2) | 69.0 (63.4–73.0) | 380.5 (339.4–387.3) | 1,652.2 (1,503.5–1,678.3) |
Spain | 12.9 (7.4–17.7) | 497.6 (472.7–525.8) | 27.2 (24.7–28.4) | 73.0 (68.5–75.9) | 364.0 (321.6–416.9) | 882.3 (792.1–884.3) |
Sweden | 20.0 (18.5–22.5) | 4,763.5 (4,652.8–5,232.8) | 44.0 | 72.0 (68.6–73.5) | 530.5 (415.7–575.3) | 1,654.1 (1,562.4–1,770.3) |
Switzerland | – | 2,847.5 (2,512.5–2,925.1) | 41.7 | 72.0 (68.4–74.6) | 305.3 (249.5–307.8) | 1,113.2 (1,074.2–1,197.5) |
Turkey | 3.4 (2.6–4.0) | 9,956.7 (9,191.4–10,781.9) | 21.7 | 65.0 (56.9–70.4) | – | 351.1 (308.0–491.9) |
United Kingdom | 1.1 (1.0–1.2) | – | – | 70.0 (66.5–72.9) | – | 995.5 (966.9–1,015.8) |
Kruskal–Wallis test |
Country (period 1989–2013) | HFA-DB incidence of cancer per 100,000 | HFA-DB prevalence of cancer (%) | OECD—self-reported absence from work due to illness (number of days lost per person per year) | OECD—compensated absence from work due to illness | OECD—public expenditure on incapacity%GDP (disability + sickness benefits) | Disability benefits per 100,000 |
---|---|---|---|---|---|---|
Austria | 453.5 (435.4–455.8) | 3.4 (3.2–3.6) | – | 12.4 (11.7–12.6) | 2.7 (2.5–2.7) | 3,466.2 (3,381.9–3,511.9) |
Belgium | 467.5 (409.4–504.8) | – | – | 9.3 (8.4–10.2) | 2.7 (2.5–2.8) | 4,582.3 (3,805.4–5,342.9) |
Czech Republic | 601.0 (570.6–674.5) | 3.0 (2.7–3.6) | 8.3 | 21.1 (18.2–21.3) | 2.3 (2.2–2.4) | 4,081.0 (3,877.7–4,184.6) |
Denmark | 517.0 (518.7–585.2) | 3.5 (3.4–3.8) | 6.9 (6.4–8.00) | 8.4 (8.3–8.8) | 3.8 (3.7–4.2) | 1,907.7 (281.5–3,607.2) |
Estonia | 431.7 (406.6–480.9) | 2.4 (2.1–2.7) | 8.3 (7.4–9.1) | 9.3 (8.8–9.9) | 1.8 (1.7–2.1) | 6,353.6 (5,622.9–7,209.4) |
Finland | 453.8 (431.7–488.5) | 3.0 (2.7–3.5) | 8.4 (8.1–8.7) | – | 4.1 (4.0–4.5) | 4,941.0 (4,697.7–5,092.7) |
France | 523.6 (429.8–571.4) | 1.3 (0.8–1.8) | 9.0 | 8.0 (7.8–8.2) | 1.9 (1.8–2.02) | 3,945.7 (3,857.9–4,006.9) |
Germany | 501.8 (474.2–527.0) | 1.7 (1.6–1.8) | – | 16.4 (15.5–17.1) | 2.1 (2.0–2.2) | 1,035.5 (1,021.0–1,071.9) |
Greece | – | 0.9 (0.6–1.2) | 14.8 | 3.6 (3.4–3.7) | 0.9 (0.9–1.1) | 1,283.3 (1,153.6–1,331.8) |
Hungary | 805.9 (510.8–778.8) | – | 8.3 (2.7–12.9) | 14.9 (13.2–17.3) | 2.7 (2.5–2.8) | 3,793.3 (3,083.4–4,410.3) |
Ireland | 384.2 (364.9–399.1) | 2.5 | – | 16.9 | 1.7 (1.6–1.9) | 3,384.0 (3,323.7–3,442.7) |
Israel | 343.8 (317.0–343.8) | 1.1 (0.9–1.1) | 4.1 (3.8–4.3) | – | 2.8 (2.5–2.9) | – |
Italy | 510.0 (470.5–519.0) | 3.0 (2.8–3.4) | 5.8 (4.5–7.1) | – | 1.8 (1.7–1.9) | 1,602.5 (1,563.9–1,639.4) |
Luxembourg | 423.6 (398.8–429.5) | – | – | 11.2 (10.6–11.6) | 3.1 (3.0–3.2) | 3,576.4 (3,541.8–3,645.8) |
Netherlands | 493.9 (487.3–565.6) | 2.5 (2.3–2.7) | – | 12.0 (11.9–13.9) | 3.9 (3.8–4.8) | 937.7 (802.0–1,235.7) |
Norway | 498.9 (479.8–524.4) | 3.4 (3.1–3.6) | – | 17.3 (16.9–18.1) | 4.7 (4.9–4.8) | 6,169.5 (6,007.3–6,713.6) |
Poland | 300.8 (281.9–325.6) | – | 6.7 | – | 3.4 (3.3–4.6) | 4,095.7 (3,867.6–4,613.4) |
Portugal | 318.9 (265.6–363.8) | 1.9 | 6.3 | – | 2.2 (2.2–2.3) | 3,769.5 (3,563.2–3,962.0) |
Slovak Republic | 399.9 (386.8–443.5) | 0.4 (0.4–0.4) | – | 13.9 (12.4–14.9) | 2.0 (1.8–2.1) | 3,998.2 (3,713.2–4,367.6) |
Slovenia | 459.2 (429.1–519.6) | 2.4 (2.2–2.9) | 12.9 | 13.8 (13.0–14.4) | 2.4 (2.3–2.6) | 2,035.6 (1,849.5–2,173.5) |
Spain | – | – | 9.2 | 10.5 (8.9–11.0) | 2.5 (2.4–2.5) | 2,475.7 (2,452.6–2,493.9) |
Sweden | 530.1 (518.0–563.5) | 4.5 (4.3–4.8) | – | 13.3 (11.4–15.1) | 5.1 (4.9–5.3) | 5,176.5 (4,336.8–5,959.3) |
Switzerland | 463.4 (443.3–468.3) | – | 7.7 (6.9–8.6) | – | 2.6 (2.4–2.8) | 5,000.4 (4,751.3–5,229.2) |
Turkey | 60.4 (57.4–93.4) | – | 3.4 (2.6–4.0) | – | 0.2 (0.2–0.2) | 860.8 (750.0–947.8) |
United Kingdom | 489.2 (482.5–505.4) | – | – | 7.8 (7.2–8.0) | 2.4 (2.4–2.6) | 3,308.5 (3,266.5–3,339.1) |
Kruskal–Wallis test |
Our forecasts based on ARIMA modeling of available data indicate that up to 2020, most European countries will experience a downward trend of absenteeism from work due to illness (Figure
More details on each of five prominent indicators (each one reflecting slightly different group of nations) can be found in Figure
Of extracted data, we can observe great transnational variability of most indicators depicting disability burden in the European region (
Work absenteeism due to illness and consecutively number of citizens receiving disability benefits were falling steadily over most of the past three decades and are about to decline further (
The flat line trend forecast for the public expenditure on incapacity should be taken cautiously. It is more realistic to expect downward trend here as well (
As previously explained, projected flat trend in public expenditure on incapacity up to 2020 expressed as %GDP share should be taken carefully. This value actually refers to joint disability and sickness benefits among the OECD member nations (
An increase in hospital discharges due to cancer over the past 25 years presents quite an increase and thereby a significant finding in this study. The prevalence and incidence of most types of malignancies tends to increase in most of Europe (
Based on all projections, it appears that many European countries may experience shrinking disability-related social costs driven by absenteeism, incapacity benefits, and absence compensations from public funds. This trend is not in line with ongoing morbidity developments since the global burden of disease continues to grow further even in industrialized European countries (
What we might be able to see here at a number of European OECD nation states presents a contradiction to a certain extent and a great challenge. We have clearly growing work load for the national health systems attributable to the clinical oncology acting as the major disability contributor. This effectively means that large share of these savings on public expenditure shall effectively be spent to combat strong cancer morbidity (
On another side, we have all signs of falling societal responsibility toward the citizens suffering from diverse kinds of incapacity or impaired working ability and independence (
All authors listed, MJ, CM-S, OM, NR, and DB, have made substantial, direct, and intellectual contribution to the work and approved it for publication.
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
This Original Research was prepared based on the HFA-DB and OECD Health Data.
ISCH COST Action CA1211 Cancer and Work CANWON has financially supported the data mining, extraction and writing of this Data Report through its Short Term Scientific Mission. Ministry of Education Science and Technological Development of the Republic of Serbia has supported these efforts by its Grant OI 175 014.
1