Abstract
Background
Increasing longevity raised the prospect of a workplace for ageing workers. Previous studies reveal that work ability decreases with age, even among the healthy, and decreased significantly with age among women. The aim of the study is to examine the perception of work ability of public sector employees aged 55 years and older and gender differences in three European countries.
Methods
A prospective longitudinal study design and standardized “Work Ability Index” (WAI) were used. This study analysed the relationship between ageing, gender, and perceived work ability among 1653 employees aged 45.06±10.90 years (562 men and 1091 women) from Spain, Bosnia and Herzegovina and Monte Negro. The research was conducted in 2018.
Results
Older employees had a better WAI than their younger colleagues (P<0.001). The lowest prevalence rate 20% of excellent WAI was between 35 and 44 years of age. The reduction of WAI in Bosnia and Herzegovina was huge 68%, compared with 30% in Monte Negro (more than 2 times) and 14% in Spain (almost 5 times more).
Conclusion
Gender and age was not protector and predictor of excellent or reduced work ability. Work ability did not decrease with age among women and men, public sector employees. Work ability depends of health and safety, promotion and preventive activities at the workplace.
Keywords: ageing, gender, work ability, public sector employees
Izvleček
Ozadje
Daljša življenjska doba je izboljšala možnosti za delovno mesto zaposlenih osebi, ki se starajo. Prejšnje študije so razkrile, da se delovna sposobnost zmanjšuje s starostjo tudi med zdravimi osebami in da se izrazito zmanjšuje s starostjo med ženskami. Cilj študije je pregled dojemanja delovne sposobnosti zaposlenih oseb v javnem sektorju s starostjo 55 let ali več in razlik med spoloma v treh evropskih državah.
Metode
Uporabljena sta bila prospektivna longitudinalna oblika študije in standardiziran »indeks delovne zmožnosti« (WAI). Ta študija je analizirala odnos med staranjem, spolom in zaznano delovno zmožnost med 1653 zaposlenimi osebami, starimi 45,06 ± 10,90 let (562 moških in 1091 žensk) iz Španije, Bosne in Hercegovine in Črne gore. Raziskava je bila opravljena leta 2018.
Rezultati
Starejše zaposlene osebe so imele boljši indeks WAI kot njihovi mlajši kolegi (P < 0,001). Najnižjo stopnjo razširjenosti, 20 % odličnega indeksa WAI, je imela starostna skupina od 35 do 44 let. Zmanjšanje indeksa WAI v Bosni in Hercegovini je bilo ogromnih 68 %, v primerjavi s 30 % v Črni gori (več kot dvakratna vrednost) in 14 % v Španiji (več kot skoraj petkratna vrednost).
Zaključek
Spol in staranje ne ščitita niti predvidevata odličnosti ali zmanjšanja delovne zmožnosti. Delovna zmožnost se ni zmanjšala s starostjo med ženskami in moškimi, zaposlenimi v javnem sektorju. Delovna zmožnost je odvisna od zdravja in varnosti na delovnem mestu, promocije in preventivnih dejavnosti na delovnem mestu.
Ključne besede: staranje; spol, delovna zmožnost; zaposleni v javnem sektorju
1. Introduction
The workforce is ageing and the contribution of older workers is considerable. Their occupational health profiles differ from those of their younger (1) colleagues. Demographic changes imply an increasing number of workers with health problems and a decreasing of ability to work (2). Functional capacities, mainly physical, show a declining trend after the age of 30 years, and the trend can become critical after the next 15–20 years if the physical demands of work do not decline (3, 4, 5). Consequently, efforts to maintain the ability to work of currently and future employees are of key importance. In this context, the Finish Institute of Occupational Health (FIOH) developed a generic tool during the 1980s to monitor and assess work ability, the so-called “Work Ability Index” (WAI) in the working population on a regular basis (6). WAI considers the workers’ self assessed work ability in relation to work demands, health status and particular type of work. The WAI has since then been widely disseminated and is nowadays the most commonly used tool for measuring work ability (7). Excellent ability to work is closely related to the possibility to increase quality of work, improve quality of life and well-being among employees, thereby decreasing the likelihood of their early retirement, decreasing absenteeism, as well increasing motivation and productiveness in employees of all ages (8).
The most studied demographic factor regarding WAI was age, and some authors reported a decreased WAI with ageing (9, 10, 11). In the Finish Health 2000 survey, nearly half of young adults perceived their work ability as excellent compared to 8% of 55-64 year-olds (12). Work ability decreases with age even among the healthy (13). Work ability significantly decreased with age among the women. Also, the ageing trend of WAI is different, depending on the sector of the economy. Work ability seems to be lower in farming and agriculture, the wood industry, the metal industry and transport, as well as in social services and in some countries among teachers (public sector) (14). The present study therefore aims at examining perception of work ability and its dimensions of public service employees aged 55 and older and gender differences in three cohorts in three European countries.
2. Methods
2.1. Study Population and Design
A longitudinal study was performed between January and September 2018 among public service professionals in Spain, Monte Negro and Bosnia and Herzegovina (B&H). We assessed the influence of ageing and gender to work ability among public sector employees (in three various European countries: Spain (country in Europe Union), Monte Negro and B&H (countries in South East Europe region). We compared national and gender differences of work ability in older employees aged ≥55 years in relation to young employees in between the ages of 19 to 54.
The study sample covered 1653 out of 2500 respondents who were invited and randomly selected aged between 18 and 72 years (797, 48% from Spain; 266, 16% from Monte Negro; and 590, 36% from Bosnia and Herzegovina), and the response rate was 66.12%. The women comprised 1091 (66%) of the study population, much more than men, 592. The mean age of the employees was 45.06±10.90 (SD) and the mean length of service 20.74±11.12 (SD) years. The study participants were staff members of primary health care wards, children and youth schools and other administrative services in these health care institutions and schools from Seville capitol of Andalusia in Spain, Podgorica, capitol of Monte Negro and Tuzla Canton, the most populous canton in B&H (52% teachers, 34% health care providers and 14% administrative officers) (Table 1).
Table 1.
Numerical screening data of a sample (n=1653).
| Characteristics of subjects | Mean ± SD | Minimum | Maximum |
|---|---|---|---|
| Age (years) | 45.06±10.90 | 1.00 | 72.00 |
| Length of service (years) | 20.74±11.12 | 0.00 | 51.00 |
| Sick- leave (days) | 5.72±23.71 | 0.00 | 334.00 |
| WAI score | 40.08± 6.17 | 1.00 | 49.00 |
Legend: SD- standard deviation
2.2. Measuring Study Instruments
The survey study was conducted by WAI, which was used in the previous research and, on such occasions, adapted and translated into Spanish and South Slavic languages (Bosnian and Montenegrin) [14-17]. WAI measures seven aspects: current Work Ability (WA) compared with lifetime best; WA in relation to the physical and mental demands; current number of common chronic diseases; sick leave taken in the past 12 months; the worker’s own prognosis of his or her work ability in two years’ time; the worker’s mental resources to accomplish his or her job. WAI is derived as the sum of the ratings on these seven items. The range of the summative index is 7-49 and the WAI categories are: poor, 7-27; moderate, 28-36; good, 37-43; and excellent 44-49. The internal consistency of each 7 items of the WAI questionnaire in our study sample was excellent (Cronbach, alpha=0.82).
2.3. Statistical Analysis
We performed a data analysis using IBM SPSS Statistics for Windows, Version 19.0. We used descriptive, co-relational and explanatory linear regression methods (to provide predictive or protective potential between excellent WAI among 446 and poor WAI among 195 examiners as dependent variables; gender, country, age and each WAI scale as independent variables). To estimate differences and associations between WAI score categories in younger and older employees (≥55), we use a variable that contains the age dichotomized to 18-54 (mark 1) and equal to or more than 55 years (mark 2). All p-values <0.05 were regarded as statistically significant.
3. Results
Between individual characteristics of respondents the mean by standard deviation (SD) were for: age 45.06±10.90 years; length of service 20.74±11.12 years; sick leave 5.72±23.71 days; and WAI score 40.08±6.17 (Table 1).
The study sample consisted of more women 1091 (66%) than men 562. The total number of respondents aged between 18 and 54 was 1287 (78%) and between them older employees aged ≥55 were 366 (22%). The poor WAI in women being 17% compared to 9.4% in men or excellent WAI found in women 24.5% vs. 31.9% in men (P=0.001). Women were much more affected by health disorders thatinfluence their work than men (P=0.004). Women expressed much more (almost two times more) poor WA prognosis for the next two years than men, 22.6% vs. 11.6% (P=0.001). Women rarely enjoy their regular daily activities, other than men, who admit that they enjoy their daily activities (P=0.044) (Table 2).
Table 2.
Characteristics of a sample per gender (n=1653).
| Characteristics of subjects | No (%) |
P-value | ||
|---|---|---|---|---|
| Man 562 (34) | Women 1091 (66) | |||
| Country | B&H, 590 (36) | 174 (31.0) | 416 (38.1) | 21.275 |
| Monte Negro, 266 (16) | 73 (13.0) | 193 (17.7) | 0.001 | |
| Spain, 797 (48) | 315 (56.0) | 482 (44.2) | ||
| Age-groups (years) | 18-34, 330 (20) | 105 (18.7) | 225 (20.6) | 96.706 |
| 35-44, 416 (25) | 126 (22.4) | 290 (26.6) | 0.001 | |
| 45-54, 537 (33) | 172 (30.6) | 365 (33.5) | ||
| 55-64, 336 (20) | 136 (24.2) | 200 (18.3) | ||
| 65 or more than 65, 34 ( 2) | 23 (4.1) | 11 (1.0) | ||
| Occupations in public sector | Health care providers, 563 (34) | 106 (18.9) | 457 (41.9) | 27.911 |
| Children and youth teachers, 865 (52) | 381 (67.8) | 484 (44.4) | 0.001 | |
| Others administrative officers, 225 (14) | 75 (13.3) | 150 (13.7) | ||
| Marital status | married, 1109 (67) | 387 (68.9) | 722 (66.2) | 11.432 |
| single | 131 (23.3) | 232 (21.3) | 0.043 | |
| divorced | 30 (5.3) | 95 (8.7) | ||
| widowed | 25 (4.4) | 42 (3.8) | ||
| Educational level | low, 60 (3) | 24 (4.3) | 36 (3.3) | 20.649 |
| medium, 724 (44) | 230 (40.9) | 494 (45.3) | 0.001 | |
| high, 869 (53) | 308 (54.8) | 561 (51.4) | ||
| Work ability determinates | ||||
| Work ability score groups | poor, 195 (12) | 53 (9.4) | 142 (13.0) | 18.442 |
| moderate, 399 (24) | 112 (19.9) | 287 (26.3) | 0.000 | |
| good, 613 (37) | 218 (38.8) | 395 (36.2) | ||
| excellent, 446 (27) | 179 (31.9) | 267 (24.5) | ||
| Current work ability | from minimal 1 | 3 (0.5) | 9 (0.9) | 22.173 |
| compared with | 2 | 0 (0.0) | 1 (0.1) | 0.014 |
| lifetime best | 3 | 2 (0.4) | 12 (1.1) | |
| 4 | 6 (1.1) | 15 (1.4) | ||
| 5 | 27 (4.8) | 36 (3.3) | ||
| 6 | 18 (3.2) | 58 (5.3) | ||
| 7 | 83 (14.7) | 122 (11.2) | ||
| 8 | 163 (29.0) | 265 (24.3) | ||
| 9 | 117 (20.8) | 272 (24.9) | ||
| to maximal 10 | 143 (25.5) | 301 (27.5) | ||
| Work ability in relation | very poor | 39 (6.9) | 109 (9.9) | 8.367 |
| to mental demands | rather poor | 75 (13.4) | 144 (13.0) | 0.079 |
| moderate | 92 (16.4) | 220 (20.1) | ||
| rather good | 212 (37.7) | 389 (35.5) | ||
| very good | 144 (25.6) | 236 (21.5) | ||
| Number of diagnosed | 0 | 298 (52.9) | 606 (55.6) | 6.124 |
| diseases | 1 | 99 (17.6) | 151 (13.8) | 0.294 |
| 2 | 60 (10.7) | 103 (9.5) | ||
| 3 | 38 (6.8) | 77 (7.0) | ||
| 4 | 24 (4.2) | 43 (3.9) | ||
| 5 | 43 (7.7) | 111 (10.2) | ||
| Estimated impairment | In my opinion, I am entirely unable to work | 76 (13.5) | 162 (14.9) | 18.937 |
| of health influence to work | I feel I am able to do only part- time work | 40 (7.1) | 85 (7.8) | 0.004 |
| I must often slow down my work pace or change | 33 (5.9) | 86 (7.9) | ||
| I must sometimes slow down my work | 39 (6.9) | 98 (8.9) | ||
| pace or change my work methods | ||||
| I am able to do my job, but it causes some symptoms | 93 (16.6) | 228 (20.9) | 4.432 | |
| There is no hindrance/ I have no disease | 281 (50.0) | 432 (39.6) | 0.489 | |
| Sick leave during | 100-365 days | 15 (2.7) | 26 (2.4) | |
| the past year | 25-99 days | 13 (2.3) | 43 (3.9) | |
| 10-24 days | 30 (5.4) | 69 (6.3) | ||
| ≤ 9 days | 133 (23.6) | 256 (23.5) | ||
| 0 days | 371 (66.0) | 697 (63.9) | ||
| Own forecast of work ability | unlikely | 12 (2.1) | 31 (2.8) | 31.560 |
| for the next two years | not certain | 65 (11.6) | 247 (22.6) | 0.001 |
| relative certain | 485 (86.3) | 813 (74.5) | ||
| Enjoy your regular daily | often | 198 (35.0) | 362 (34.0) | 11.401 |
| activities (mental resource) | rather often | 204 (36.0) | 362 (34.0) | 0.044 |
| sometimes | 123 (22.0) | 253 (22.0) | ||
| rather seldom | 35 (6.0) | 113 (10.0) | ||
| never | 2 (1.0) | 1 (0.0) | ||
Legend: P-value, Pearson Chi-Square
Respondents aged ≥55 years significantly frequent attained excellent WAI and in particular good WAI compared to younger (P=0.001). Older employees more frequent perceived higher current work ability compared with lifetime best than younger respondents (P=0.002).
They had a much higher number of diagnosed illnesses (from 1 to 5) than younger employees (P=0.001), but older employees were significantly more influenced by diseases to work and work inability due to disease (Table 3).
Table 3.
Work ability determinates compared by ageing (n=1653).
| Work ability determinates | Age groups (years) |
P-value* | ||
|---|---|---|---|---|
| ≤54 1287 | ≥55 366 | |||
| Work ability score groups | poor, 195 (12) | 178 (13.8) | 17 (4.6) | 32.552 |
| moderate, 399 (24) | 321 (24.9) | 78 (21.3) | 0.001 | |
| good, 613 (37) | 444 (34.6) | 169 (46.2) | ||
| excellent, 446 (27) | 344 (26.7) | 102 (27.9) | ||
| Current work ability | from minimal 1 | 8 (0.6) | 4 (1.1) | 27.575 |
| compared with lifetime best | 2 | 1 (0.1) | 0 (0.0) | 0.002 |
| 3 | 13 (1.0) | 1 (0.3) | ||
| 4 | 20 (1.6) | 1 (0.3) | ||
| 5 | 51 (3.9) | 12 (3.3) | ||
| 6 | 59 (4.7) | 17 (4.6) | ||
| 7 | 152 (11.8) | 53 (14.5) | ||
| 8 | 312 (24.3) | 116 (31.7) | ||
| 9 | 296 (22.9) | 93 (25.4) | ||
| to maximal 10 | 375 (29.1) | 69 (18.8) | ||
| Work ability in relation | very poor | 121 (9.5) | 20 (5.5) | 8.571 |
| to mental demands | rather poor | 177 (13.7) | 42 (11.5) | 0.073 |
| moderate | 243 (18.9) | 69 (18.8) | ||
| rather good | 453 (35.2) | 148 (40.4) | ||
| very good | 293 (22.7) | 87 (23.8) | ||
| Number of diagnosed | 5 | 102 (7.9) | 52 (14.2) | 29.895 |
| diseases | 4 | 48 (3.7) | 19 (5.2) | 0.001 |
| 3 | 80 (6.2) | 35 (9.5) | ||
| 2 | 125 (9.7) | 38 (10.4) | ||
| 1 | 186 (14.5) | 64 (17.5) | ||
| 0 | 746 (58.0) | 158 (43.2) | ||
| Estimated impairment | In my opinion, I am entirely unable to work | 215 (16.7) | 23 (6.3) | 39.108 |
| of health influence to work | I feel I am able to do only part- time work | 102 (7.9) | 23 (6.3) | 0.001 |
| I must often slow down my work pace or change | 102 (7.9) | 17 (4.6) | ||
| I must sometimes slow down my work pace or | 107 (8.3) | 30 (8.2) | ||
| change my work methods | ||||
| I am able to do my job, but it causes some symptoms | 241 (18.7) | 80 (21.9) | ||
| There is no hindrance/I have no disease | 520 (40.5) | 193 (52.7) | ||
Legend: P-value, Pearson Chi-Square
Table 4.
Correlation between WAI dimensions’ and gender; and correlation between WAI dimensions’ and aging in all respondents (n=1653).
| Spearman correlation between gender and WAI | Correlation factor | Spearman correlation between aging and WAI | Correlation factor |
|---|---|---|---|
| Current work ability compared with lifetime best | 0.036 (>0.05) | Current work ability compared with lifetime best | -0.115 (<0.001) |
| Mental demands of work | -0.059 (<0.05) | Mental demands to work | 0.084 (<0.001) |
| Health impairment influence to work | -0.080 (<0.001) | Health disorders influence to work | 0.177 (<0.001) |
| Sick leave during one year | -0.025 (>0.05) | Sick leave during one year | 0.043 (>0.05) |
| WA prognosis for two years | -0.134 (<0.001) | WA prognosis for two years | -0.006 (>0.05) |
| Enjoyment of daily tasks | -0.047 (>0.05) | Enjoyment of daily tasks | 0.056 (<0.05) |
| Be physically and psychological active | 0.003 (>0.05) | Be physically and psychological active | 0.026 (>0.05) |
| Optimism about the future | 0.000 (>0.05) | Optimism about the future | -0.046 (>0.05) |
| Decreased WAI score | -0.104 (<0.001) | Decreased WAI score | 0.076 (<0.001) |
There are significantly negative correlations between WAI dimensions’ and gender (P<0.001): health disorders influence to work (correlation=-0.080); WA prognosis for two years (correlation=-0.134); and decreased WAI score (correlation=-0.104) more in women than men; and a significantly negative correlation between mental demands of and gender among women (P<0.05; correlation=-0.059). Increased ageing positive correlated with WA dimensions ‘at the level of P<0.001: mental demands of work (correlation=0.084); health disorders influence to work (correlation=0.177); and decreased WAI score (correlation=0.076). We found a negative correlation between ageing and current work ability compared with lifetime best (correlation factor=-0.115).
Using a multilevel logistic regression model we found that the excellent work ability index was associated with the following predictors: to live in Spain or Europe Union (β=-0.185, 95%CI, -5.612- -2.576, P<0.000), higher level of education (β=0.123, 95%CI, 0.778-2.414, P<0.001), higher level of current work ability (β=0.280, 95%CI, -0.9731.421, P<0.000), lower level of physical demands of work (β=-0.084, 95%CI, -0.023- -0.046, P<0.003), lower level of mental demands of work (β=-0.048, 95%CI, -1.085- -0.084, P<0.022), sick leave during the past year (β=0.144, 95%CI, 0.323-0.073, P<0.001), and prognosis of work ability in next two years (β=0.305, 95%CI, 0.566-0.866, P<0.001) among 446 (27%) respondents.
Predictors of poor WAI were: to live in southeast Europe countries (β=0.334, 95%CI, 0.659- 1.728, P<0.000), to be divorced or widowed (β=-0.078, 95%CI, -0.527- -0.043, P<0.021), low level of education (β=-0.191, 95%CI, -0.771-0.201, P<0.001), high level of physical demands at work (β=0.452, 95%CI, 0.054-0.080, P<0.001), high level of mental demands at work (β=0.194, 95%CI, 0.561-1.151, P<0.001), high level of impairment due to disease (β=0.452, 95%CI, 0.054-0.080, P<0.001), bad prognosis of WA in next two years (β=0.331, 95%CI, 1.062-1.624, P<0.001), and decline of mental resources (β=0.097, 95%CI, 0.092-0.510, P<0.005) among 195 (12%) respondents (shown in Table 5).
Table 5.
Results of the multiple linear regression analyses for respondents with excellent work ability (n=446) and for respondents with poor work ability index (n=195) as dependent variables; demographic factors and work environment factors obtained (independent variables).
| Predictors of work ability | β | P-value | 95% Confidence | interval |
|---|---|---|---|---|
| Excellent work ability index | ||||
| Sex | 0.008 | 0.612 | -0.587 | 0.995 |
| Country | -0.185 | 0.000 | -5.612 | -2.576 |
| Age | 0.002 | 0.892 | -0.370 | 0.425 |
| Marital status | -0.019 | 0.252 | -0.792 | 0.209 |
| Educational level | 0.123 | 0.000 | 0.778 | 2.414 |
| Current WA compared with lifetime best | 0.280 | 0.000 | 0.973 | 1.421 |
| Physical demands of work | -0.084 | 0.003 | -0.023 | -0.046 |
| Mental demands of work | -0.048 | 0.022 | -1.085 | -0.084 |
| Health impairment influence to work | -0.062 | 0.002 | -0.805 | -0.186 |
| Lower incidence of sick leave | 0.052 | 0.019 | 0.091 | 0.988 |
| Prognosis of WA in two next years´ time | 0.273 | 0.000 | 1.182 | 1.906 |
| Mental resources | 0.063 | 0.085 | -0.112 | 1.711 |
| Poor (bad) work ability index | ||||
| Sex | -0.022 | 0.472 | -0.429 | 0.199 |
| Country | 0.334 | 0.000 | 0.659 | 1.728 |
| Age | -0.030 | 0.413 | -0.233 | 0.096 |
| Marital status | -0.078 | 0.021 | -0.527 | - 0.043 |
| Educational level | -0.191 | 0.001 | -0.771 | -0.201 |
| Current WA compared with lifetime best | 0.338 | 0.000 | 0.701 | 1.048 |
| Physical demands of work | 0.452 | 0.001 | 0.054 | 0.080 |
| Mental demands of work | 0.194 | 0.000 | 0.561 | 1.151 |
| Health impairment influence to work | 0.452 | 0.000 | 0.054 | 0.080 |
| Higher incidence of sick leave | 0.058 | 0.085 | 0.029 | 0.448 |
| Prognosis of WA in two next years´ time | 0.331 | 0.000 | 1.062 | 1.624 |
| Decline of mental resources | 0.097 | 0.005 | 0.092 | 0.510 |
Legend: β, Beta coefficient in regression ANOVA analysis of potential predictors
4. Discussion
The present study adds important knowledge about 1653 (1091 female) employees in the public sector of which most were employed in health care or education field of service and coming from Spain, B&H and Monte Negro at the time of progressive population aging and when extended working life is a necessity and a possibility. This survey aims to answer the following question: are individual factors, physical or mental demands of work, and health determinants of excellent or poor WAI? Twenty seven percent of the entire population based cohort reported excellent WAI and 12% perceived poor WAI.
The relations observed between WAI and individual variables generally support those reported in the literature. The authors of numerous studies suggested a strong association between ageing and the decline in work ability and demonstrated that young workers estimate their WAI at a higher level than older ones (18, 19, 20, 21, 22, 23). Ageing is related to decreasing physical work capacity (7, 8, 24). Work ability in relation to demands in working life results in increasing strain in older employees (18). Furthermore, ageing results in a higher prevalence of clinical diseases (25, 26, 27, 28). Work ability among Croatian nurses confirmed that the WAI score decreases significantly with age (29, 30). The relations observed between WAI and the individual variables generally support those reported in the literature. The authors of numerous studies suggested a strong association between ageing and a decline in work ability. They demonstrated that young workers estimate their WAI at a higher level than older ones. We found a significant correlation between aging and decreased WAI score, decreased current work ability among our participants too, but our older employees aged 55 and over 55 years had better levels (categories) of WAI than their younger colleagues.
According study results, ageing and gender did not influence work ability among our respondents (Table 5). Some prior studies also demonstrated no association between ageing and WAI (12, 31, 32), and one study found a higher risk for a poor WAI among younger workers (26). High physical workload among women working in social and health care is likely to contribute to the gender differences (31).
According to study results, ageing and gender did not influence work ability among our respondents. Predictors for poor work ability were: a high level of mental demands at work, a low level of education, health impairments during work, and bad self-prognosis for work. Our finding is in accordance with data that was reported by other authors (11, 12, 13 22, 33, 34). On the basis of assessment of protectors for excellent WAI (excellent WAI) were: a high level of education, a low level of impairment influenced to work and reduced sick leave days.
5. Conclusion
Gender and ageing wasn’t associated with low or high level of work ability among public sector employees. High mental and physical workload among women working in public sector occupations are likely to contribute to the work ability gender differences, but we didn’t found it among our respondents. As workers age, their physical, physiological and psychosocial capabilities change. Keeping older workers healthy is a key goal of the labour policy. Providing educational and career prospects can contribute to maintaining work ability during all your working life.
Footnotes
Conflict of interest
The authors declare that there was no conflict of interest.
Funding
The research did not receive a specific grant from any funding agency in the public, commercial, or not-for-profit sector. The work of the authors is part of their work in a working group as members in EU COST Action IS1409.
Ethical approval
Research includes human data, which have been performed in accordance with Declaration of Helsinki and have been approved by the Ethics Committee of University of Tuzla, Ethics Committee of Universidad Pablo de Olavide and Ethics Committee of University of Monte Negro. Before interviews, the nature and the purpose of the study were explained and full confidentiality was assured to all participants. All participants were informed about their right not to participate in the study and gave their oral consent before the study.
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