Insights from Research on Age and Gender

Literature review

There are numerous factors that have an impact on sickness related absence, according to the articles, books, and research studies that have been done so far. Age and gender are among the two factors that are highlighted, which can affect sickness absence. A majority of the researches that have been conducted do recognize age and gender as factors that do have an effect. Generally, age plays a significant role in the rise to sickness absence levels as pointed out by the vast researches done (ed Smedley et al. 2013). Gender also goes hand in hand with age. As much as older age affects the increase in sickness absence, a literature review using Google Scholar, Medline, Embase, and PubMed revealed that this was not always the case in the research conducted.

Research by Beemsterboer et al. (2009) looked into various studies conducted between the years 1984 and 2004 in search of the main factors that contribute to sickness absence and to establish the consistency of those factors. It looks at how these factors affect the duration and number of sickness absence episodes. The article seeks only to point out crucial determinants that are associated with sick leave and not to look into the scale of the effects of those determinants to sick leave, including age and gender. It is vital to look into the relative influence of the determinants, and this is what this review focuses on; taking into consideration. It will provide a sense of direction to take in the proposal.

Steentra et al. (2005) looks into studies from 1966 to 2003 reviews and evaluates the theory that there are aspects about the individuals themselves, the role and other psychological, social and environmental factors that play a role in the duration of the sickness absence due to lower back pain. The study concludes that patients that have lower back pains risk being absent for more extended time periods and are mostly older females. Radiating pain, social dysfunction, and higher disability levels had a more than two effect size. Age did hit a more than two effect size in areas with groups that had a 31-year age difference. Positives about the article are that it deployed explicit exclusion and inclusion method for an inception cohort and for one being on sick leave. This makes it protected from bias due to the mixed population that is acute and chronic and one at work and on sick leave. Making use of the right technique of statistics to put together study results made a positive impact on influencing the study size on the results. On the other hand, the results of the psychological factors were not correctly put in to place to have an effect on the topic of the research proposal. The results that were deemed to be non-significant were not put together, and it only focused on what was relevant. Overall it is a definite article that will be relied on hugely for this study.

Brenner’s and Ahern’s (2000) research is based on construction workers in order to come up with an in-depth pattern of the nature and level of injuries and illnesses that result in absence from work. It concludes that both the rate and the duration of absence due to ill health increased with age. The most significant cause of absence was injuries, and it is not known whether the type of industry, one involving heavy manual work, played a role in these findings, perhaps it can be presumed to be so (Brenner). This study did not include all workers in the industry as it used records of those who were members of a pension fund and sick pay scheme; an estimated one-third of the workforce was not included as a result of not being members. The workers were also almost entirely male (99%). A high percentage of sick absence was covered by musculoskeletal disorders, infectious diseases, and injuries leaving little room for age and gender.

Valentin et al. (2016) reviewed studies looking at the association between various factors with incapacity and sickness absence due to pain arising from other issues apart from cancer and lasted for a period not exceeding three months. The conclusion of the report was that some studies showed a strong association between older age and poorer outcomes while others did not. The reviewers in this review concluded that overall, there was an association between older age and disability. The qualitative methodology of this study does not provide useful insight and conclusion to the nature of the survey being conducted. This makes it challenging to come up with a final agreement on what was discovered and how best to move forward. The flaws in the report make it least suitable to be fully used as a piece that is concrete of evidence of the relation of age and gender to absence as the estimates provided are not factual enough basing on the data collected. This review included a large proportion of studied on low back pain, which could have an impact on the application of the conclusions to a patient in pain from other sites. Concern regarding publication bias was mentioned. Gender was not considered in this review (Valentin et al., 2016).

Nieuwenhuijsen’s et al. (2006) report states that older age was one of the factors that lead to a longer time off when the absence was related to common mental illnesses. They compared data from occupational health physicians on 188 individuals, mainly teachers, who had a similar stage of their disease and followed them up for a year. They found that together with other factors, such as the individuals own perceptions of their recovery, level of education and diagnosis itself, age was a predictor, with older employees taking more extended periods of sickness absence. On the positive side, the predictors used in this study were assessed at baseline, and the outcome measured at the time of the follow-up. The assessment of predictors was also done without the researchers and employees involved knowledge. The precise definition of the outcome was vital and of importance clinically in calculating and coming up with results. Ideally, the rule of prediction should have been obtained from one group of employees and tested on another so as to get enough validation externally. There was also an overrepresentation of employees with high education levels as teachers were many in the study.

The study by Gotz et al. (2018) used data collected from men and women who are employed in Germany to look into how work-related stress is associated with a subsequent number of sick days. It found that work that was more demanding resulted in higher levels of sickness absence in both men and women and in all age groups. They also found that men had lower levels of stress and lower levels of related sickness absence than women did in all age groups. Sickness absence was generally found to increase with age in this study, but the interplay in this study did not reach statistical significance. Interestingly the distribution of mean and median numbers suggest that older workers had a higher number of short absences. (Gotz et al., 2018). This study did not include part-time or self-employed workers and relied on self-reporting so recall bias may impact on results. The study also only looked at stress at a single point in time, and so is limited in its assessment of the workplace stress itself (i.e., repeated or long term stress versus more minor limited exposures to stress). The results may also have underestimated the level of si,ckness absence itself, and it’s a link to workplace stress by the exclusion of individuals who were off sick at the starting point.

A number of other studies done on different populations have also found a link between older age and higher levels of sickness absence. Eshoj et al. (2001) in their study looking at risk factors for long term sickness absence in workers in one county in Denmark found that older age was strongly associated with such absences, particularly in men. This was less so in women; where the difference between older and younger workers was less pronounced (Eshojetal). This study was designed to include only those who were off sick for over 10 weeks as ‘cases’ and was questionnaire based, thus lending itself to bias. An interview-based study was undertaken by Labrio et al. (2006) that aimed to look at physical and psychosocial factors that could increase sickness absence levels also found that increased age was associated with increased sickness as was female gender (Labrio et al., 2006). This study was based on both self-reported sickness absence level and self-rated health, again lending itself to bias. The responders were questioned twice. Once at baseline and a second time 5 years later, asking only about absence in the year prior. Individuals had to have responded to both rounds to have been included in the study, and thus, those who were off sick or retired (possibly due to ill-health) were excluded. This may have impacted on the study findings.

The study by Lotter et al (2006) was set to look systematically into evidence on factors that predict the period of sick leave amongst workers after enduring 6 weeks of sick lea e due to lower back pain. The paper does a great job in pointing out factors related to lower back pain and other factors that have an impact on duration of sick leave. However the study underestimates the psychosocial work environment in its later phases. The lack of common ground amongst researchers on a clear way on how to measure psychosocial constructs and analyse data in regard to the currently available theoretical models even makes it much more riskier to use this research in the study. The end phase of the review did not put into consideration the impact of workplace factors. Generally a prognostic study is not the best way to look into the effectiveness of interventions as the results have loopholes and can be influenced or biased in one way or the other if the necessary control group is missing. This makes the study a stepping stone into the research as the issues addressed are not very strong.

Thomson et al. (2000) considered the relationship between age, length of service and sickness absence in a study of 2417 government workers. They felt that tenure tended to restrain sickness absence levels. While it would seem likely that longer tenure would be associated with older age; the changes in workplace practices that are becoming more commonplace (such as moves to self-employed and ‘consulting’, flexible employment arrangements such as zero hour contracts, etc.) may mean that this is can no longer be presumed to be the case (Thomson et al., 2000). This study did not assess gender differences and also did not look at the different types of tenure (i.e. tenure in different roles which may differ). The scanty information provided does not give much support and explanation on how age affects the length of service thereby indicating how this leads to sick leaves. This is a good paper to put one on a path of discovery and provide support information to the main articles of the research work.

In the study by Barnby et al (2002), when looking at data from labour force surveys in Canada, Czech Republic, France, Luxembourg, Slovenia, Spain, Sweden, Switzerland and the UK found that in general and in most countries men had lower sickness absence than women and younger employees had lower sickness absence than older ones. However they did find some variation in some countries where younger males were found to have higher sickness absence than their similar aged female counterparts (France, Slovenia, Spain and Luxembourg). Interestingly, in contrast to the opinion of Thompson et al, they found that a longer tenure was itself associated with higher sickness absence even when age is accounted for. Greater usual hours of work were also found to bear a link to higher sickness absence (Barnbey et al., 2002). They also found that sickness absence is influenced by the availability of sick pay.

Allebeck and Mastekaasa (2004) discuss various studies that looked at the causes of sickness absence. Unsurprisingly they found that there are various factors that play a role in sickness absence. Specifically with regards age and gender, they found that while studies seem to show that older age has been showed to be linked to an increase in sickness absence level (as has other factors such as gender and length of term etc.), they refer to a study that shows that sickness absence is increasing as is the working population in general; however only a small increase in sickness absence could be attributed to the generally increasing age of the workforce. This suggests that other factors have to be playing a role. They identify while there are many studies that mention age, or indeed gender, and their relation to sickness absence levels, that these studies do not adequately tackle the reasons behind these associations (Allebeck & Mastekaasa, 2004). There are clear several limitations to this study firstly casual interpretations are made due to assumptions of the mediation analysis not being violated, this is due to lack of indicators of adolescent and childhood health indicators. This could lead to an estimation of the association between adult social positions on sick leave. The measure of physical workload was based on three self-report questions that have not been approved putting the report validity into question. The assumption by the study on personality measured in adulthood being a mirror of childhood and adolescent personality is baseless and has been challenged by recent researches that have been conducted which depict lifespan personality alterations. Lastly the huge number of people who did not participate in the third study and 30% of those who took party in the first study and return incomplete questioners makes the final report and conclusion not highly factual.

Vahtera et al. (2001) look into single day absences that could be used to prolong weekends looked at total absences but also single day absences on different days of the week for both men and women and in different age groups. The study was done on full-time, permanent municipal workers in different towns in Finland. They found that the general trend of the absence levels were largely the same across age groups and genders but found that single day absences were decreasing as the age groups increased with older men having the lowest levels of single day absences. Younger employees and men were found to have more single day absences that fell on a Monday (Vahtera et al., 2001). However, single day absences made up a very small proportion of absences making it difficult to extrapolate to absences general. The study is useful to the research due to its results being obtained from a detailed and extensive database that covered a lot of people who are in various positions which is a plus for the research. The days that were under study for this research are not however sufficient to come up with a thoroughly inclusive research that is well detailed for finer conclusions.

Donders et al. (2012) looked at age and how the link between sickness absence and a few other aspects that play a role in sickness absence are affected by age. The population of this study was divided into four age groups and the differences in the impact of the various other aspects were compared between these groups. Sickness absence focussed on either frequent spells (which they defined as more than 3 spells in a 12 month period) or prolonged sickness absence (which they defined as a total of more than 2 week off sick in a 12 months period). This study found that older workers had more sickness absence which lasted over two weeks in total but less frequent sickness absence spells. They also found that older workers had more chronic diseases but that there was little difference reported in subjective health complaints, physical and emotional fatigue and various other psychosocial work features (dondersetal). This was a questionnaire-based study with resultant liability to biases. The response rate was 49%. Limitations of the study include, it being cross-sectional it was difficult to point out casual relationships. The self-reported measures that were collected through one questionnaire are vulnerable to common ratter effect. Lastly the study does not give room for other psychosocial work environment to be taken into consideration. The basis

Lund et al (2007) made a study in Denmark where they followed up a sample of employees across different sectors to assess risk factors for long term sickness absence. They found that women were at higher of risk of such absences. However with regards age they found that the trend was for sickness absence to increase only until 59 year of age. The levels in the oldest age group 60 to 69 were no different to the youngest age group (18-29) (Lund et al., 2007). Due to the scarcity of theory models the paper made use of two modelling approaches which had scant evidence supporting its conclusions. The other issue comes in on specification of empirical models basing on observable variable that is aimed at reducing bias. This paper not only gives a theoretical reasoning but also makes use of epidemiological outcomes. Relevant data use is very vital for research, this paper makes use of two data sets for survey but fails to provide supplementary question which makes one to mistakenly conclude some inferences to sickness absence. Not being able to pass a definitive judgement in the end makes it open for other interpretations and lack of closure to the reader as to what was the final conclusions of the paper. This closes the ability of using the paper to make a definitive conclusion in this proposal.

Gjesdal et al. (2018) study data of all General practitioners’ consultations in Norway over a period of one year looked at the incidence of musculoskeletal conditions in the working population under 67 years of age. Amongst their findings were only slight differences between men and women: while men were more likely to be certified off sick for a musculoskeletal ailment than women, women were more likely to have stayed off sick beyond 16 days. Women were also more likely to have remained off for a year. Their findings for age were interesting. In men, while older age decreased the risk of being certified off sick, the duration of illness was longer in older age. Older age increased the risk of staying off sick longer than 16 days in both genders. However, women were likely to return to work sooner than men (Gjesdal). The strengths of the study include the large population study that allowed cross-national comparisons and the design for national representative outlook. Being able to overcome limitations in sickness comparisons is a positive review. Limitations are that recall bias is bound to occur due to study variables being self-reported. There is room for residual confounding due to little scope of factors that affect sickness absence. Lack of data on sickness periods of sickness made it difficult in looking into the recurrent sickness absences. This makes it a little difficult to tie the findings to age and sick absence in this proposal.

Thorsen et al. (2018) made comparisons on self-reported sickness absence with recorded data and how it differed by a few characteristics, amongst which were sex and age. Although not the primary aim, of the study, the levels of absence in this study also found that women had higher sickness absence than men. The results in this study showed that those under 29 years old having the lowest average number of sickness absence days after which the average number of sickness absence days remained relatively stable until the age of 60 when the average number of sickness absence days was slightly lower again(but still higher than those under 29). The access to an in depth Sa register and a large size to sample from which included public and private sectors give this report an upper hand and make it comfortable to use and insightful to the topic of discussion. However no presence of information on the work schedules makes the paper use assumptions which cannot be considered as factual findings. Some variables in the research lack relevant data, registered and self-reported based that excludes some employees from the final analysis.

The article by Taimela et al. (2007) looked into the link between sickness absence and the health problems reported by the workers themselves. This study found that younger individuals did not report more ill-health than their older counterparts, but despite their own reports of less ill-health, younger individuals had higher sickness absence levels. In contrast to other study findings, this study also found that women had a similar number of absence days to men. The researchers mentioned that as this was based on questionnaires and although response rates were general similar to other studies, it was possible that those who did not respond may have been too unwell to do so. This would then have the effect of undervaluing the link between sickness absence and self –reports as those that responded would have been in better health than those who did not. Similar to Thorsen et al who suggested that differences in reporting may skew results. Interestingly, Taimela et al found that those who did not respond were younger than those who did respond. They did feel that since the sickness absence levels in those that responded when compared to those who did not respond were similar, their study population was a fair representation of their intended study population. They also mentioned the potential of ‘reverse causality playing a role (Taimela et al, 2007). Younger age was found by Sado et al (2014) to be a risk factor for higher likelihood of recurrent sickness absence levels due to mental health conditions. This was felt to possibly be related to early onset of mental illness being a poor prognostic indicator (Sado 2014). In terms of accuracy , consistency and coverage recorded data like in this case has superior advantage in making conclusions as to the impact age has on sick leaves as the decisions made or conclusions are from accurate data. The difficulty comes in when one is using traditional methods of statistics to analyse the data collected due to a large fraction being clustered as a zero value which is bigger than any basic model of probability for counting data.

Farrants’ et al (2018) research studied whether there were any changes in the sick leave patterns of those who stayed employed beyond the age of 65. They obtained data from the National Social Insurance agency in Sweden on all individuals who remained at work in 4 different years between 1995 and 2010. Those who turned 65 by the end of the preceding year and who had access to public sick leave benefits were included in the study. The rates of sick leave for people aged between 66 and 70 and those 71 years or older were analysed by a few factors, one of which was gender. They found that the number of people who remained in paid work after 65 year of age increased significantly but the sickness absence rates of these age groups had decreased. The sickness absence rates of these two groups were also compared to the rates of people aged between 60 and 64 and it was found that those in the 60 to 64 year age group had higher sickness absence rates in all of the years included in this study. Women were found to have higher sickness absence rates than men in two of the four years but lower sickness absence rates than men in the other two years (Farrants et al., 2018).This was the first research of its kind that was founded on four different population groups inclusive of almost all individuals older than 65 years during four various years. The huge study groups give room for analysis of smaller groups, register with high quality data and minimal losses on follow up. The fact that only periods with sick leave that had benefits from social insurance agencies were included in the study. Shorter periods of sick leaves are omitted but longer ones are well covered. Self-employed people sick leaves are also missed on the report which has the probability to introduce bias among sick leave for the self-employed. The research produces a perfect balance of information that is factual and relevant and will be used as a main study article.

The article by Hensing et al (2004) looks at the predictive elements for sickness absence and disability due to a mental health diagnosis. They found conflicting outcomes in the studies for gender and age and mental health related incapacity. This review ultimately concluded that there is limited evidence for women having a higher risk of such absences. Similarly conflicting study outcomes lead them to conclude that there is not sufficient evidence for an association between age and sickness absence due to mental health ailments either (Hensing et al., 2004). There are very few studies that have emphasised on differences in gender during periods of illness like this study has. However, in the relation to sick leave a risk of overestimating the morbidity of women and underestimating the male when there is the use of these measures. A perfect balance of the age and gender influence on sick leave is just perfect for this research and a lot will be obtained and used to come to a validated conclusion.

Koopmans et al (2010) highlighted recurrent sickness absence due to common mental health problems in Dutch post and telecommunication workers and found no difference in the recurrent rates of absence based on age in men and that younger women (under 44) had a higher recurrence rate than their older female colleagues (Koopmans et al., 2010). The use of sick leave certificates rather than self-reported complaints makes this report a bonus. However the authenticity of psychiatric diagnosis on absence certificates is a currently debatable topic scientifically. Lack of data on co-morbidity is another fat that limits this study. Sick leave only had a single diagnosis. With a higher likelihood of depression with comorbid disorders taking place again we are not made aware of whether there was a shift of diagnosis over time. Despite the limitations of the research it was a well written paper that has great content that this proposal will be leaning towards and borrowing from for more insights and depth in analysis.

Barnby et al (2002) recognised sickness absence in women was higher than men in all age groups in their report based on data from United Kingdom labour force surveys between 1984 and 1997. They found that sickness absence levels increased as age increased in both men and women. However, they also found a significant decline in sickness absence after the usual retirement age in both men and women, sickness absence levels in women remained higher than that for men even in the post ‘usual’ retirement age group. They felt that this was a result of those staying on after what was then the usual retirement age, were a self-selected group who were less likely to take sickness absence. The ‘healthy-worker’ effect also would presumably play a role here (Barnby et al., 2002).

A study done in Norway looked at sickness absence due to mental health ailments in the years 1994, 1996, 1998 and 2000. In this study all those workers between the ages of 16 and 66 years of age, who had access to the paid sick leave but not receiving a pension due to disability, were included. From this group, those who had been off sick for at least two weeks due to a mental health ailment were considered ‘cases’. The cumulative incidences were measured. They found that sickness absence due to mental health diagnoses increased in both men and women and in all ages in the periods studied. However the differences in the increases between groups is of relevance when looking at age and gender. The increases in men were lower than that seen in women in all ages. The highest increases in both men and women were seen in the middle age group (defined as between 30 to 59 years in this study) with the lowest increases, in both men and women, being in the younger and the older age groups. The study population did not, however, include individuals over 66 years of age (Hensing et al., 1996).

A Swedish Counties registration of all sickness absence lasting over 7 days between 1985 and 1987 were studied. The study undertaken by Hensing et al. (1995), looked at age, gender and occupation and their relation to sickness absence due to less significant mental health ailments. Their study found that overall women had higher incidence of such sickness absence; however there were differences between industries where one gender dominated the workforce. They found that the gender that was in the minority in an industry had a highest incidence of sickness absence for that gender in that particular industry and where there was equal distribution of genders the incidence of sickness absence was the lowest (Hensing et al., 1995). With men still dominating many workplaces, this may explain many study outcomes that find higher levels of sickness absence in women.

A study explored whether age had an impact in Danish workers who were working permanent nights. Although it was felt that the self-selection that would occur in working permanent night might have meant that older workers actually did better, this study found that although the sickness absence levels in workers who worked nights permanently was higher than those who worked permanent days or a combination of both days and nights, they found no association between age and sickness absence in these workers (Garde et al, 2018).

A systematic review undertaken by Artus et al. (2017) looked at general factors which could predict sickness absence and subsequent return to work in individuals with musculoskeletal discomfort. Age and gender were included in the 78 factors identified by the studies that were included in this review. The review of the studies found some contradictory associations for age with some studies showing some association but many more showing none. Similarly some studies showed females as having higher likelihood of poorer outcomes with others showing no association between gender and such outcomes. This review overall found no significant evidence for an association between either age or gender and poorer outcomes for musculoskeletal pain (Artus et al., 2017).

A Norwegian study looked at register based data to establish risk factors for sickness absence lasting longer than eight weeks due mental health diagnoses. They found that women were at a higher risk of such absences than men. They did not find that these absences were higher in older ages as the highest was found in the 40- to 45-year age group (Foss et al., 2010).

Another Norwegian study based on register data found that sickness absence levels actually decreased as age increased up the age of 45 years, after which it began to increase again. They attribute the higher levels of sickness absence in younger individuals to a different ‘work ethic’ as well as the presumption that those individuals who would have had high levels of absence in younger years may no longer be employed by the time they are older. They also considered that younger workers may not yet have found themselves in a job that they matched well with. They found that women had a higher risk of sickness absence than men and slightly slower recovery rates than men did (Markussen et al., 2011).

A Japanese study of sickness absence lasting 30 days or more in employees of twelve different private companies had some interesting findings. They found that sickness absence due to all causes in women decreased as age increased. The finding in men was different; with youngest and oldest groups having similar sickness absence levels with the lowest and highest sickens absence levels in the middle ages groups of 30 to 39 and 50 to 59 years respectively. In men there was therefore no correlation with age when looking at all-cause sickness absence levels in this study (Nishiura et al., 2017).

An American study that at sickness absence of civil servants at a national agency between 2004 and 2012. This study also found that women had higher sickness absence levels than men. Their findings for age did not show a specific pattern. The highest levels of sickness absence was found in the 35 to 44 year old group. With only a small difference between the youngest age group who took a day less per year than the oldest age group (Gajewski et al., 2015).

A study looked at the trends in sickness absence of female municipal and healthcare workers in two Scandinavian countries over a five year period. Their results show no increase in sickness absence with age; In fact those in the youngest group (20 to 29) and those aged 50 to 59 had the highest levels of sickness absence. This study included workers up to 67 years old and the oldest group had lower levels of sickness absence. The study also found that sickness absence in younger age groups increased to a greater extent than it did in other age groups (Krane et al., 2014). Perhaps this indicates a change in the individual and other factors that influence sickness absence between different generations that has resulted in the various different study outcomes.

A Lebanese study of various levels of staff working at a teaching hospital found that younger workers had more sickness absence overall than older workers and they also had sickness absence more frequently than older workers (Rahme et al., 2006)

A study on university workers in the Netherlands aimed to investigate the difference in sickness absence levels in those with a chronic ailments with those who did not have chronic ailment. Unsurprisingly they found that those with a chronic ailments took more frequent sickness absence and also sickness absences of a longer duration. However, they found that individuals under 36 years of age took more sickness absence than those over 46 years old (Roskes et al., 2005).

An Australian study looked at sickness absence levels and tried to explore some reasons behind them. This study found that the oldest workers took the least sick leave overall. However, in keeping with other studies they did find that older workers tended to have longer sickness absences (Cant et al., 2001).

A study by Rozemberg (2018) undertaken on the sickness absence data of various institutions that the researcher had been providing Occupational health services in Sao Paulo was presented at a recent conference. A review of absences up to 15 days between 1989 and 2004 were studied. This study found sickness absence to be higher in women and both in the youngest and oldest age groups (Rozemberg, 2018).

A meta-analysis undertaken by Martoccio (1989) found that frequency and duration of sickness absence was actually lower as age increased (Martoccio, 1989).

It seems that as Briner (1996) found, studies did not find consistent results when looking at the links between age and sickness absence. Brines review showed that older age can translate into either increased or decreased absences but that women generally were found to have higher levels of absence than men(Briner, 1996). As is clear sickness absence is a complex issue, and the interplay between the many factors that influence it may well be the reason the while disease tends to be more prevalent in older age, this doesn’t necessarily translate into higher levels of sickness absence. Study methods also vary, ages included and grouping varies as did the classification of the type of sickness absence. What is ‘young’ or ‘old’, and what is ‘short’ or ‘long’ absences varies between studies making comparisons difficult. These complexities aside, as Farrant et al found there is a paucity of studies that include workers over 65, most studies stop at 65 and many slightly younger. It is interesting that those which included workers over 65 mostly did not find higher levels of sickness absence in the oldest workers.

References

Alexanderson, K. (1998). Sickness absence: a review of performed studies with focused on levels of exposures and theories utilized. Scandinavian journal of social medicine, 26(4), 241-249.

Allebeck, P., & Mastekaasa, A. (2004). Chapter 5. Risk factors for sick leave - general studies. Scandinavian Journal of Public Health, 32(63_suppl), 49-108. doi:10.1080/14034950410021853

Anderson, G. F., & Hussey, P. S. (2000). Population Aging: A Comparison Among Industrialized Countries: Populations around the world are growing older, but the trends are not cause for despair. Health affairs, 19(3), 191-203.

Arola, H., Pitknen, M., Nygrd, C. H., Huhtala, H., & Manka, M. L. (2003). The connection between age, job control and sickness absences among Finnish food workers. Occupational Medicine, 53(3), 229-230. doi:10.1093/occmed/kqg035

Artus, M., Campbell, P., Mallen, C. D., Dunn, K. M., & van Der Windt, D. A. W. (2017). Generic prognostic factors for musculoskeletal pain in primary care: a systematic review. BMJ Open, 7(1). doi:10.1136/bmjopen-2016-012901

Barmby, T. A., Ercolani, M. G., & Treble, J. G. (2002). SICKNESS ABSENCE: AN INTERNATIONAL COMPARISON. Economic Journal, 112(480), F315-F331. doi:10.1111/1468-0297.00046

Beemsterboer, W., Stewart, R., Groothoff, J., & Nijhuis, F. (2009). A literature review on sick leave determinants (1984-2004). International journal of occupational medicine and environmental health, 22(2), 169-179.

Brenner, H., & Ahern, W. (2000). Sickness absence and early retirement on health grounds in the construction industry in Ireland. Occupational and Environmental Medicine, 57(9), 615-620. doi:10.1136/oem.57.9.615

Briner, R. B. (1996). ABC of Work Related Disorders: ABSENCE FROM WORK. BMJ, 313(7061), 874. doi:10.1136/bmj.313.7061.874

Burmeister, E. A., Kalisch, B. J., Xie, B., Doumit, M. A. A., Lee, E., Ferraresion, A., . . . Bragadóttir, H. (2019). Determinants of nurse absenteeism and intent to leave: An international study. Journal of nursing management, 27(1), 143. doi:10.1111/jonm.12659

Cant, R., O'Loughlin, K., & Legge, V. (2001). Sick leave -- Cushion or entitlement? A study of age cohorts' attitudes and practices in two Australian workplaces. Work (Reading, Mass.), 17(1), 39-48.

Chevalier, A., Luce, D., Blanc, C., & Goldberg, M. (1987). Sickness absence at the French National Electric and Gas Company. British Journal of Industrial Medicine, 44(2), 101. doi:10.1136/oem.44.2.101

Dekkers-Sánchez, P. M., Hoving, J. L., Sluiter, J. K., & Frings-Dresen, M. H. W. (2008). Factors associated with long-term sick leave in sick-listed employees: a systematic review. Occupational and Environmental Medicine, 65(3), 153. doi:10.1136/oem.2007.034983

Disney, R. (2000). Crises in public pension programmes in OECD: What are the reform options? The Economic Journal, 110(461), 1-23.

Donders, N. C. G. M., Bos, J. T., van Der Velden, K., & van Der Gulden, J. W. J. (2012). Age differences in the associations between sick leave and aspects of health, psychosocial workload and family life: a cross-sectional study. BMJ Open, 2(4). doi:10.1136/bmjopen-2012-000960

Dünner, S., Decrey, H., Burnard, B., & Pécoud, A. (2001). Sickness certification in primary care. Sozial- und Präventivmedizin, 46(6), 389-395. doi:10.1007/bf01321665

Eshoj, P., Jepsen, Jr., & Nielsen, C. (2001). Long-term sickness absence - risk indicators among occupationally active residents of a Danish county. Occupational Medicine-Oxford, 51(5), 347-353.

Farrants, K., Kjeldgård, L., Marklund, S., Head, J., & Alexanderson, K. (2018). Sick leave before and after the age of 65 years among those in paid work in Sweden in 2000 or 2005: a register-based cohort study. Journal of International Medical Research, 46(2), 564-577. doi:10.1177/0300060517734744

Farrants, K., Marklund, S., Kjeldgård, L., Head, J., & Alexanderson, K. (2018). Sick leave among people in paid work after age 65: A Swedish population-based study covering 1995, 2000, 2005 and 2010. Scandinavian Journal of Public Health, 46(3), 297-305. doi:10.1177/1403494817731487

Firat, H., Yuceege, M., Kiran, S., Akgun, M., Demir, A., Aksu, M., . . . Yilmaz, H. (2015). Absenteeism and Delay to Work Due to Sleep Disorders in the Turkish Adult Population: A Questionnaire Based National Survey. Chest, 148(4), 1054A-1054A. doi:10.1378/chest.2220527

Flach, P. A., Krol, B., & Groothoff, J. W. (2008). Determinants of sick-leave duration: A tool for managers? Scandinavian Journal of Public Health, 36(7), 713-719. doi:10.1177/1403494808092251

Foss, L., Gravseth, H. M., Kristensen, P., Claussen, B., Mehlum, I. S., & Skyberg, K. (2010). Risk Factors for Long-Term Absence Due To Psychiatric Sickness: A Register-Based 5-Year Follow-Up From the Oslo Health Study. Journal of Occupational and Environmental Medicine, 52(7), 698-705. doi:10.1097/JOM.0b013e3181e98731

Gabbay, M., Shiels, C., & Hillage, J. (2015). Factors associated with the length of fit note-certified sickness episodes in the UK. Occupational and Environmental Medicine, 72(7). doi:10.1136/oemed-2014-102307

Gajewski, R. K., Burris, R. D., Spears, R. D., Sullivan, R. K., Oyinloye, R. O., McNeil, R. C., . . . Chapman, R. S. (2015). Demographic Trends of Sick Leave Absenteeism Among Civil Service Employees at a Federal Agency From 2004 to 2012. Journal of Occupational and Environmental Medicine, 57(3), 277-283. doi:10.1097/JOM.0000000000000347

Garde, A., Hansen, Å., Kolstad, H., Hansen, J., Nielsen, H., & Larsen, A. (2018). 1617a Permanent night work, age and sickness absence. In: BMJ Publishing Group Ltd.

Gjesdal, S., Holmaas, T. H., Monstad, K., & Hetlevik, Ø. (2016). GP consultations for common mental disorders and subsequent sickness certification: Registerbased study of the employed population in Norway. Family Practice, 33(6), 656-662. doi:10.1093/fampra/cmw072

Gjesdal, S., Holmaas, T. H., Monstad, K., & Hetlevik, Ø. (2018). New episodes of musculoskeletal conditions among employed people in Norway, sickness certification and return to work: a multiregister-based cohort study from primary care. BMJ open, 8(3), e017543.

Götz, S., Hoven, H., Müller, A., Dragano, N., & Wahrendorf, M. (2018). Age differences in the association between stressful work and sickness absence among full-time employed workers: evidence from the German socio-economic panel. International Archives of Occupational and Environmental Health, 91(4), 479-496. doi:10.1007/s00420-018-1298-3

Hensing, G., Alexanderson, K., Allebeck, P., & Bjurulf, P. (1996). Sick-leave due to psychiatric disorder: Higher incidence among women and longer duration for men. The British Journal of Psychiatry, 169(6), 740. doi:10.1192/bjp.169.6.740

Hensing, G., Alexanderson, K., Åkerlind, I., & Bjurulf, P. (1995). Sick-leave due to minor psychiatric morbidity: role of sex integration. Social Psychiatry and Psychiatric Epidemiology, 30(1), 39-43. doi:10.1007/BF00784433

Hensing, G., & Wahlstrom, R. (2004). Chapter 7. Sickness absence and psychiatric disorders. Scandinavian Journal of Public Health, 32, 152-180.

Koopmans, P. C., Roelen, C. A. M., Bültmann, U., Hoedeman, R., van der Klink, J. J. L., & Groothoff, J. W. (2010). Gender and age differences in the recurrence of sickness absence due to common mental disorders: a longitudinal study. BMC Public Health, 10, 426-426. doi:10.1186/1471-2458-10-426

Krane, L., Johnsen, R., Fleten, N., Nielsen, C. V., Stapelfeldt, C. M., Jensen, C., & Braaten, T. (2014). Sickness absence patterns and trends in the health care sector: 5-year monitoring of female municipal employees in the health and care sectors in Norway and Denmark. Human resources for health, 12(1), 37. doi:10.1186/1478-4491-12-37

Labriola, M., Lund, T., & Burr, H. (2006). Prospective study of physical and psychosocial risk factors for sickness absence. Occupational Medicine, 56(7), 469-474. doi:10.1093/occmed/kql058

Lidwall, U., Bill, S., Palmer, E., & Olsson Bohlin, C. (2018). Mental disorder sick leave in Sweden: A population study. Work (Reading, Mass.), 59(2), 259-272. doi:10.3233/WOR-172672

Lund, T., Labriola, M., & Villadsen, E. (2007). Who is at risk for long-term sickness absence? A prospective cohort study of Danish employees. Work, 28(3), 225-230.

Lötters, F., & Burdorf, A. (2006). Prognostic Factors for Duration of Sickness Absence due to Musculoskeletal Disorders. The Clinical Journal of Pain, 22(2), 212-221. doi:10.1097/01.ajp.0000154047.30155.72

Markussen, S., Røed, K., Røgeberg, O. J., & Gaure, S. (2011). The anatomy of absenteeism. Journal of Health Economics, 30(2), 277-292. doi:10.1016/j.jhealeco.2010.12.003

Martocchio, J. (1989). AGE-RELATED DIFFERENCES IN EMPLOYEE ABSENTEEISM - A META-ANALYSIS. Psychology And Aging, 4(4), 409-414.

Nieuwenhuijsen, K., Verbeek, J. H. A. M., de Boer, A. G. E. M., Blonk, R. W. B., & van Dijk, F. J. H. (2006). Predicting the duration of sickness absence for patients with common mental disorders in occupational health care. Scandinavian journal of work, environment & health, 32(1), 67-74. doi:10.5271/sjweh.978

Nishiura, C., Nanri, A., Kashino, I., Hori, A., Kinugawa, C., Endo, M., . . . Dohi, S. (2017). Age-, sex-, and diagnosis-specific incidence rate of medically certified long-term sick leave among private sector employees: The Japan Epidemiology Collaboration on Occupational Health (J-ECOH) study. Journal of Epidemiology, 27(12), 590-595. doi:10.1016/j.je.2017.01.003

Palmer, K. T., Cox, R. A. F., & Brown, I. (2007). Fitness for Work (Vol. 4th edition): Oxford.

Rabacow, F. M., Levy, R. B., Menezes, P. R., do Carmo Luiz, O., Malik, A. M., & Burdorf, A. (2014). The influence of lifestyle and gender on sickness absence in Brazilian workers. Acta Veterinaria Scandinavica, 14(1), 317. doi:10.1186/1471-2458-14-317

Rahme, D. V., Razzouk, G. N., Musharrafieh, U. M., Rahi, A. C., & Akel, M. M. (2006). Sickness-related absence among employees at a tertiary care center in Lebanon. Archives of environmental & occupational health, 61(6), 279-284.

Roelen, C. A. M., Koopmans, P. C., Hoedeman, R., Bültmann, U., Groothoff, J. W., & van der Klink, J. J. L. (2009). Trends in the incidence of sickness absence due to common mental disorders between 2001 and 2007 in the Netherlands. The European Journal of Public Health, 19(6), 625-630. doi:10.1093/eurpub/ckp090

Roskes, K., Donders, N., & Gulden, J. W. J. (2005). Health-related and work-related aspects associated with sick leave: a comparison of chronically ill and non-chronically ill workers. International Archives of Occupational and Environmental Health, 78(4), 270-278. doi:10.1007/s00420-004-0596-0

Rozemberg, D. (2018). 287 Sick absence in the sÃo paulo region. Occupational and Environmental Medicine, 75(Suppl 2), A171-A171. doi:10.1136/oemed-2018-ICOHabstracts.483

Sado, M., Shirahase, J., Yoshimura, K., Miura, Y., Yamamoto, K., Tabuchi, H., . . . Mimura, M. (2014). Predictors of repeated sick leave in the workplace because of mental disorders. Neuropsychiatric disease and treatment, 10, 193-200. doi:10.2147/NDT.S55490

Schellevis, F. G., van der Velden, J., van de Lisdonk, E., Van Eijk, J. T. M., & van Weel, C. v. (1993). Comorbidity of chronic diseases in general practice. Journal of clinical epidemiology, 46(5), 469-473.

Sharp, C., & Watt, S. (1995). A study of absence rates in male and female employees working in occupations of equal status. Occupational Medicine, 45(3), 131-136. doi:10.1093/occmed/45.3.131

Shiels, C., Gabbay, M. B., & Ford, F. M. (2004). Patient factors associated with duration of certified sickness absence and transition to long-term incapacity. British Journal of General Practice, 54(499), 86-91. doi:10.3399/bjgp08X342147

Smedley, J., Dick, F., & Sadhra, S. S. (2013). Oxford handbook of occupational health (2nd ed. ed.). Oxford: Oxford University Press.

Steenstra, I. A., Verbeek, J. H., Heymans, M. W., & Bongers, P. M. (2005). Prognostic factors for duration of sick leave in patients sick listed with acute low back pain: a systematic review of the literature. Occupational and Environmental Medicine, 62(12), 851-860. doi:10.1136/oem.2004.015842

Sumanen, H., Pietilaeinen, O., Lahti, J., Lahelma, E., & Rahkonen, O. (2015). Sickness absence among young employees. Journal of Occupational Health, 57(5), 474-474. doi:10.1539/joh.14-0236-OA

Taimela, S., Lr, E., Malmivaara, A., Tiekso, J., Sintonen, H., Justn, S., & Aro, T. (2007). Self-reported health problems and sickness absence in different age groups predominantly engaged in physical work. Occupational and Environmental Medicine, 64(11), 739. doi:10.1136/oem.2006.027789

Taimela, S., Lr, E., Malmivaara, A., Tiekso, J., Sintonen, H., Justn, S., & Aro, T. (2007). Self-reported health problems and sickness absence in different age groups predominantly engaged in physical work. Occupational and Environmental Medicine, 64(11), 739. doi:10.1136/oem.2006.027789

Thomson, L., Griffiths, A., & Davison, S. (2000). Employee absence, age and tenure: A study of nonlinear effects and trivariate models. Work & Stress, 14(1), 16-34. doi:10.1080/026783700417203

Thorsen, S. V., Flyvholm, M.-A., & Bültmann, U. (2018). Self-reported or register-based? A comparison of sickness absence data among 8110 public and private employees in Denmark. Scandinavian journal of work, environment & health, 44(6), 631-638.

Tsai, P. S., Wendt, K. J., Ahmed, S. F., Donnelly, P. R., & Strawmyer, R. T. (2005). Illness Absence Patterns Among Employees in a Petrochemical Facility: Impact of Selected Health Risk Factors. Journal of Occupational and Environmental Medicine, 47(8), 838-846. doi:10.1097/01.jom.0000169091.28589.8a

Vahtera, J., Kivimäki, M., & Pentti, J. (2001). The role of extended weekends in sickness absenteeism. Occupational and Environmental Medicine, 58(12), 818. doi:10.1136/oem.58.12.818

Valentin, G. H., Pilegaard, M. S., Vaegter, H. B., Rosendal, M., Ørtenblad, L., Væggemose, U., & Christensen, R. (2016). Prognostic factors for disability and sick leave in patients with subacute non-malignant pain: a systematic review of cohort studies. BMJ Open, 6(1), e007616. doi:10.1136/bmjopen-2015-007616

Vellas, B. J., Albarede, J.-L., & Garry, P. J. (1992). Diseases and aging: patterns of morbidity with age; relationship between aging and age-associated diseases. The American journal of clinical nutrition, 55(6), 1225S-1230S.

Vignoli, M., Guglielmi, D., Bonfiglioli, R., & Violante, F. S. (2016). How job demands affect absenteeism? The mediating role of work–family conflict and exhaustion. International archives of occupational and environmental health, 89(1), 23-31.

Whitaker, S. C. (2001). The management of sickness absence. Occupational and environmental medicine, 58(6), 420-424.

Continue your journey with our comprehensive guide to Insights from Existing Research Evidence.