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PLOS One logoLink to PLOS One
. 2017 Aug 25;12(8):e0183550. doi: 10.1371/journal.pone.0183550

Preoperative characteristics of working-age patients undergoing total knee arthroplasty

Tjerk H Hylkema 1,2,*, Martin Stevens 1, Jan Van Beveren 3, Paul C Rijk 4, Hans Peter van Jonbergen 5, Reinoud W Brouwer 6, Sjoerd K Bulstra 1, Sandra Brouwer 2
Editor: Ara Nazarian7
PMCID: PMC5571908  PMID: 28841709

Abstract

Objective

Total Knee Arthroplasty (TKA) is performed more in working-age (<65 years) patients. Until now, research in this patient population has been conducted mainly among retired (≥65 years) patients. Aim of this study was therefore to describe demographic, physical, psychological and social characteristics of working TKA patients and to subsequently compare these characteristics with retired TKA patients and the general population.

Methods

A cross-sectional analysis. Preoperative data of 152 working TKA patients was used. These data were compared with existing data of retired TKA patients in hospital registers and with normative values from literature on the general population. Demographic, physical, psychological and social (including work) characteristics were analyzed.

Results

The majority (83.8%) of working TKA patients was overweight (42.6%) or obese (41.2%), a majority (72.4%) was dealing with two or more comorbidities, and most (90%) had few depressive symptoms. Mean physical activity level was 2950 minutes per week. Compared to the retired TKA population, working TKA patients perceived significantly more stiffness and better physical functioning and vitality, were more physically active, and perceived better mental health. Compared to the general population working TKA patients perceived worse physical functioning, worse physical health and better mental health, and worked fewer hours.

Conclusion

This study shows that a majority of working TKA patients are overweight/obese, have multiple comorbidities, but are highly active in light-intensity activities and have few depressive symptoms. Working patients scored overall better on preoperative characteristics than retired patients, and except for physical activity scored overall worse than the general population.

Introduction

Osteoarthritis (OA) is characterized as a chronic, progressive and inflammatory disease[1]. It is one of the most frequent causes of disability in Western populations [1]. In the Netherlands, approximately 594,000 people were dealing with OA of the knee in 2011 [2]. The risk of developing OA of the knee increases with age and overweight/obesity [1, 3]. The increasing numbers of ageing patients and patients with overweight/obesity stress a need for medical treatment for end-stage knee OA in Western societies that will further rise in the coming decades [17].

End-stage knee OA can be surgically treated with a Total Knee Arthroplasty (TKA) [8, 9]. Senior patients used to be primarily allocated to TKA. Prosthetic survivorship is currently longer and long-term results are known [10, 11]. The resulting trend is an increased number of TKA procedures in the retirement-age patients (≥65) age group (henceforth ‘‘retired patients”), as well as growing numbers of working-age OA patients under 65 (henceforth ‘‘working patients”) undergoing TKA [1218].

As the number of working patients grows, studies about the characteristics of this patient population are gaining more attention. Previous studies have examined mainly health outcomes, e.g. utilization rates, postoperative outcomes, revision rates and alternative treatments [17, 1921], yet it is also important to consider preoperative characteristics of working patients. Two recent studies have examined preoperative characteristics of younger patients. Keeney et al. [22] compared younger (<55 years) with older (65–75 years) patients, including demographics, physical activity and functioning levels before and after TKA. Results showed that in the younger group predominantly females were undergoing TKA, and more patients were obese and less active compared to older patients. Singh et al. [23] explored preoperative demographic, physical and psychological characteristics among TKA patients in different age groups. They found that among younger patients a number of individuals with a body mass index >40 was significantly higher and the prevalence of depression and anxiety increased sevenfold over 13 years’ time.

So far, studies that examine preoperative characteristics of working patients remain scarce. Existing studies survey only a few preoperative characteristics, lacking for example social and work characteristics. Moreover, working versus retired TKA patients have not yet been investigated specifically. This, along with a higher prevalence of working patients in the future, stresses the need to gain more insight into preoperative characteristics of working TKA patients. For physicians and other health professionals a better understanding of working patients in comparison to retired patients and the general population is useful during preoperative counseling and especially for discussing postoperative expectations (e.g. with respect to work). The primary objective of this study is therefore to describe the demographic, physical, psychological and social (including work) characteristics of working TKA patients. The second objective is to compare these characteristics of working patients with retired patients. At last, the third objective is to compare these characteristics with the general population.

Methods

Study design and subjects

Preoperative data of patients in the working-age group were used from the prospective cohort study ‘Work participation In Patients with Osteoarthritis’ (WIPO). In this cohort patients with knee osteoarthritis planned for TKA between March 2012 and July 2014 were included. Preoperative and postoperative data were gathered during a two-year follow-up. Inclusion criteria were primary or secondary knee OA and undergoing TKA, preoperative employment and age 18–63. The age of 63 was chosen in order to complete the two-year follow-up before the Dutch retirement age of 65 years. Exclusion criteria were insufficient knowledge of the Dutch language and having undergone joint arthroplasty in the previous six months. Four hospitals participated: University Medical Center Groningen (UMCG) (tertiary university hospital), Medical Center Leeuwarden (MCL) (large teaching hospital), Martini Hospital Groningen (MHG) (large teaching hospital) and Röpcke-Zweers Hospital Hardenberg (general hospital). The study was approved by the Medical Ethical Committee of University Medical Center Groningen (METc 2012.153) and in accordance with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Informed consent was considered obtained if the patient granted our request to participate in the study by returning a set of completed questionnaires. If patients did not want to participate in the study, they were requested to return a blank questionnaire. Patients were informed of this way of obtaining consent by an information letter. In this information letter they were also informed of the voluntary nature of the study, and that all data was processed anonymously. The Medical Ethical Committee specifically approved this consent procedure.

Preoperative data of retired TKA patients were gathered by using existing datasets of patients older than 65, where TKA was performed between 2008 and 2013 at one of the following hospitals: UMCG, Haga Hospital The Hague (large teaching hospital), MCL and Deventer Hospital (large teaching hospital). Data about the characteristics of the general population were collected by using normative or reference data found in the literature.

Procedures

Available data of working TKA patients, retired TKA patients and the general population were gathered from different sources (see Table 1). For the working TKA patients preoperative data of 152 patients of the WIPO cohort were used (see Study design and subjects). Twenty-two (14%) were included from a tertiary hospital (UMCG) and 130 (86%) from general/large teaching hospitals (MHG, MCL, Röpcke-Zweers).

Table 1. Overview of the available data of different questionnaires of working TKA patients, retired TKA patients and the general population.

Patient characteristic Instrument Working TKA patients Retired TKA patients General population
Demographic Age X X
Gender X X
Educational level X X
Physical BMIa X X
Comorbidity X
SQUASH X X X
WOMACb X X X
RAND-36 X X X
Psychological PHQ-9c X X
RAND-36 X X X
Social (including work) RAND-36 X X X
Actual working hours X n.a. X
Contractual working hours X n.a. X
Self-employed or employee X n.a. X

a = body mass index;

b = Western Ontario and McMaster Osteoarthritis Index;

c = Patient Health Questionnaire 9;

n.a. = not applicable;

X = available data

Data about the characteristics of the retired patients (n = 523) was gathered from existing databases of four hospitals. Haga Hospital provided physical activity data of n = 96 patients, Deventer hospital self-perceived physical functioning data of n = 202 patients, MCL health-related quality of life data of n = 51 patients, and UMCG provided data of n = 175 patients for all characteristics.

Normative or reference values of the general population were available for demographic, physical, psychological and social characteristics. Normative data from the literature on self-perceived physical functioning, health-related quality of life and depressive symptoms were categorized into age classes (S1S3 Tables).

Measures

All data for working TKA patients and retired TKA patients were gathered with paper-based surveys.

Demographic characteristics

Data were collected about age, gender and educational level (categorized into low, medium and high).

Physical characteristics

Body Mass Index (BMI): In order to assess BMI, height and weight were asked. BMI scores were categorized into underweight (<18.50), normal (18.50–24.99), overweight (25.00–30.00) and obese (>30.00). Reference data for the general population were obtained from Statistics Netherlands [24].

Comorbidity: Comorbidity was measured by using a 27-item chronic conditions questionnaire of Statistics Netherlands [25]. Number of comorbidities was categorized into having no, one or two, and more than two comorbidities. Comorbidity could not be compared with retired patients, and not all hospitals registered comorbidity. Reference data for the general population were not available.

Self-perceived physical functioning: To measure self-perceived physical functioning the Dutch version of the Western Ontario and McMaster Universities Arthritis Index (WOMAC) was used [26]. Using a Likert-scale, subjects rate themselves on multiple items grouped into three domains: pain (5 items), stiffness (2 items) and physical functioning (17 items). Each subscale is scored as a summation of items. The scores of the subscales make up the total score. The total score was recoded into a 100-point scale, with a higher score representing better physical functioning. The WOMAC has proven to be valid and reliable [27, 28]. Normative values of a general population were obtained from an Australian population [29].

Physical health: Physical health was measured with four subscales of the Dutch version of the RAND 36-item Health Survey, which measures health-related quality of life [30], i.e. physical functioning, vitality, bodily pain, and physical role functioning limitations. Subscores range is 0–100 and higher scores reflect better perception of physical health. The RAND-36 is a reliable and valid instrument [30]. Normative values of a general population were obtained from a Dutch population [31].

Physical activity level: Physical activity was measured with the SQUASH questionnaire, which measures habitual physical activity [32]. Respondents were asked how many days per week they performed physical activities, how many minutes per day, and how intense the activities were. The SQUASH includes questions on commuting activities, activities at work or school, and household and leisure-time activities [32]. The total score is reproduced as minutes per week [33]. The SQUASH has been tested on reliability and validity in the general population and in persons after THA [34]. To compare with the general population, two analyses were conducted. First, total activity time of working patients was compared with data of 273 healthy Dutch individuals under age 65 in a previous cohort from UMCG [35]. This was considered as the first normative value. The extent to which the working TKA patients complied with the Dutch guideline of 30 minutes moderate-intensity activity at least five days per week was considered as the second normative value [36].

Psychological characteristics

Depressive symptoms: The PHQ-9 is the depression module from the PRIME-MD instrument for common mental disorders, which scores each of the 9 DSM IV criteria from 0 (‘not at all’) to 3 (‘nearly every day’) [37]. Subjects were asked how often they have been bothered by each of the depressive symptoms over the last two weeks. PHQ-9 scores range from 0 to 27, scores of 9 or less indicate no depression, 10 to 14 moderate depression, 15 to 19 moderately severe depression and 20 to 27 severe depression[37]. The PHQ-9 has shown to be reliable and valid. Normative values of a general population were obtained from a German population [38].

Psychological functioning: The subscales mental health and emotional role functioning of the RAND-36 were used [31]. Scores range from 0 to 100 and higher scores reflect higher perceived mental health/better emotional role functioning. Normative values of a general population were obtained from a Dutch population [31].

Social characteristics

Social functioning: The subscale social functioning of the RAND-36 was used [31]. Scores range from 0 to 100 and higher scores reflect higher perceived social functioning. Normative values of a general population were obtained from a Dutch population [31].

Work: To assess work status, contractual working hours, actual number of working hours and a question about being self-employed or an employee were asked. As reference value in the Dutch population, mean contractual working hours from 2010 were derived from Statistics Netherlands [39]. The number of patients who were self-employed or employees was also compared with 2011 data from Statistics Netherlands [40, 41].

Statistical analysis

Statistical analyses were performed using IBM SPSS, version 20. Missing data were addressed by adding the average of a scale or questionnaire, in conformity with questionnaire recommendations. Missing values regarding self-perceived physical functioning, physical health, physical activity, psychological functioning and social functioning were multiple imputed. Multiple imputation using predictive mean matching method was used. Data was imputed m = 20 times, so that the pooled results can be considered reliable[42, 43].

To answer the first objective of this study, the working TKA patients were first described on demographic, physical, psychological and social characteristics. To answer the second objective, they were compared with the retired TKA patients by means of Independent Samples T-tests or Mann-Whitney U-tests and Chi-square tests.

To answer the third objective of this study, two analyses were conducted to compare the working patients with the general population. Normative values derived from the literature were presented in different age classes (see S1S3 Tables). In the first analysis the normative value of the age class correlating to the average age (55 years) was compared with the mean value of our cohort. As the age range of our cohort was between 28 and 63, we also did a second age-match analysis calculating the total number of working patients per age class who scored above or below the normative value. The comparison of working TKA patients with the normative values of the general population was tested with a one-sample T-test. A P-value < .05 was considered statistically significant.

Results

Characteristics of the working TKA patients

The physical, psychological and social characteristics of the working TKA patients are presented in Table 2. Mean age of the working patients was 55 (sd = 5.5), ranging from 28 to 63 years, and 59% was women. Working patients mainly had a low (34.7%) or secondary (46.3%) educational level. A majority (83.8%) was dealing with overweight (42.6%) or obesity (41.2%). Most patients (72.4%) reported two or more comorbidities. Mean physical activity performed was 2950 minutes (49 hours and 10 minutes) per week; most of the time was spent on work or household activities primarily of light and moderate intensity. Most working patients had no or few depressive symptoms. Lastly, most patients were employees and worked 31.3 hours per week.

Table 2. Demographic, physical, psychological and social characteristics of working TKA patients compared with retired TKA patients and the general population.

Characteristics Working TKA patients (n = 152) Retired TKA patients (n = 523) p-valued General population p-valuee
DEMOGRAPHIC
Age (mean(sd) (range)) 55(5.5) (28–63) 74(6.0) (65–91) X
Gender (no. (%)) 0.004
Male 65(44.2) 158(29.5) X
Female 87(59.2) 377(70.5) X
Educational level (%) (n = 147)a
Low 34.7 X 30
Secondary 46.3 X 42
High 19.0 X 28
PHYSICAL
BMIb (%) (n = 148)a
normal 16.2 X 54.5
overweight 42.6 X 33.7
obese 41.2 X 11.8
Self-perceived PFf (mean(se)) (n = 152) (n = 523)
Physical functioning 47.7 (1.4) 46.0 (0.6) 0.219 84.4c <0.001
Pain 41.8 (1.8) 44.3 (1.0) 0.206 84.8c <0.001
Stiffness 41.2 (1.6) 45.8 (0.8) 0.005 78.1c <0.001
Total 45.8 (1.3) 45.8 (0.5) 0.999 X
Physical health (mean(se)) (n = 152) (n = 523)
Physical functioning 31.5 (1.3) 25.4 (1.3) 0.001 84.0c <0.001
Vitality 60.1 (1.6) 56.2 (1.2) 0.038 68.6c <0.001
Bodily pain 38.3 (1.6) 37.9 (1.3) 0.876 71.8c <0.001
Physical role functioning 35.0 (3.1) 31.5 (3.3) 0.432 74.5c <0.001
Physical activity (mean minutes/week(se)) (n = 152) (n = 523)
Activities to/from work 164.7(46.3) n.a. 21.2(130.3) 0.002
Activities at work 1507.9 (68.9) n.a. 349.0(805.3) <0.001
Household activities 777.6 (71.2) 770.9 (29.9) 0.917 645.9(886.5) 0.071
Leisure-time activities 500.4 (54.7) 503.9 (42.3) 0.953 485.6(808.4) 0.753
 sports activities 73.5 (11.9) 132.9 (215.9) 0.788 62.8(206.8) 0.229
Activity intensity
 light 2009.8 (93.9) 1110.4 (29.2) <0.001 X
 moderate 744.3 (72.3) 355.2 (12.6) <0.001 X
 vigorous 196.5 (42.7) 196.5 (10.8) 0.999 X
Total minutes 2950.6 (108.6) 1662.2 (36.4) <0.001 1501.6(1528.3) <0.001
Satisfies Dutch norm (30 min. moderate activity 5–7 days/week) 69.7% 47.9% <0.001 64.8%
PSYCHOLOGICAL
Depressive symptoms (n = 151)
Mean (mean(sd)) 4.09 (3.8) X X 3.12(3.57) 0.002
No depression (n (%)) 137 (90.7) X X X
Moderate depression (n (%)) 13 (8.6) X X X
Moderately severe depression (n (%)) 1 (0.7) X X X
Severe depression (n(%)) 0 X X X
Psychological functioning (mean(se)) (n = 152) (n = 535)
Mental health 78.3 (1.2) 69.7 (1.4) <0.001 75.6c 0.030
Emotional role functioning 74.7 (3.2) 70.2 (3.5) 0.345 81.6c 0.027
SOCIAL
Social functioning (mean(se)) (n = 151) (n = 181)
Social functioning 69.3(2.2) 71.7(2.1) 0.417 83.5c <0.001
Work
Actual working hours/week (mean(sd)) 33.9(17.8) n.a. n.a. X
Contractual working hours/week (mean(sd)) 31.3(16.1) n.a. n.a. 34.4c 0.022
Self-employed or employee (%)
 self-employed 13.2 n.a. n.a. 14.2
 employee 80.9 n.a. n.a. 72.1
 missing 5.9 n.a. n.a. X

a = n reduced due to missing data;

b = body mass index;

c = SD not available;

d = p-value of comparison between working and retired TKA patients;

e = p -value of comparison between working TKA patients and general population;

f = self-perceived physical functioning;

X = no data available;

n.a. = not applicable; bold values represent significant values (p < .05).

Working TKA patients compared to retired TKA patients

Table 2 presents the characteristics of the retired patients. Mean age was 74 (sd = 6.0), ranging from 65–91 years; 70% were women, in contrast to the working patient cohort (59%). Major differences between the working and retired groups were observed on physical characteristics. Working patients perceived more stiffness (p = 0.005), better physical functioning (p = 0.001) and better vitality (p = 0.038). The total amount of physical activity was significantly (p<0.001) different (2950 versus 1662 minutes per week). Working patients performed more light- and moderate-intensity activities than retired patients (p<0.001). More working patients met the Dutch guideline of 30 minutes moderate-intensity activity at least five days per week, compared to retired patients (69% versus 47%). Significant differences were also observed on psychological characteristics: working patients perceived better mental health (p<0.001). Scores on social functioning were generally similar in both groups.

Working TKA patients compared to the general population

The normative and reference data of the general population are presented in Table 2. Working patients showed significantly (p<0.001) worse self-perceived physical functioning and significantly (p<0.001) worse physical health than the general population. Working TKA patients performed more activity (p<0.001) than the general population (2950 vs. 1501 minutes per week). Almost seventy percent of the working patients met the Dutch guideline of 30 minutes moderate activity 5–7 days per week, compared with 64% in the general population. The two groups also differed significantly on some psychological and social characteristics. Working patients reported more depressive symptoms (p = 0.002) and perceived better mental health (p = 0.026). However, working patients perceived worse emotional role functioning (p = 0.027), perceived worse social functioning (p<0.001) and worked fewer hours per week (p = 0.022).

The second analysis of the comparison between working patients and the general population showed the following results. For physical health, almost all patients (n = 149, 99.3%) scored worse on physical functioning; 109 (72.8%) patients perceived worse physical role functioning, 95 patients (63.3%) scored worse on vitality and 148 patients (98.0%) perceived more pain. For self-perceived physical functioning, 148 patients (96.1%) scored worse on physical functioning, 144 patients (95.4%) scored worse on the pain subscale and 141 (95.3%) patients scored worse on the stiffness subscale. For psychological factors, 48 (31.8%) patients scored worse on mental health, 49 (32.7%) patients scored worse on emotional role functioning and 93 (61.2%) patients had more depressive symptoms. Lastly, 95 (63.3%) patients perceived worse social functioning than the general population.

Discussion

Main study findings are that working TKA patients have distinct preoperative characteristics: a majority of patients had overweight/obesity, most patients had multiple comorbidities, patients performed a high amount of light-intensity physical activity and a few patients were depressed. In comparison to retired patients and the general population, the results showed that working patients scored overall better on preoperative characteristics than retired patients and scored overall worse—except for physical activity level—than the general population.

The physical characteristics of the working patients are of interest to discuss. Working patients scored significantly worse on all physical characteristics (pain, physical functioning, vitality, stiffness and physical role functioning) compared to the general population, but scored better than retired patients on physical functioning and vitality. The finding that all characteristics were different between working TKA patients and the general population is not unexpected, as knee OA is a painful and highly disabling illness [1, 44]. The majority of the working patients were dealing with two or more comorbidities as well as with overweight or obesity. It is known that obesity, anxiety, depression and cardiovascular diseases are closely related to limitations in self-perceived physical functioning in patients with knee or hip osteoarthritis [45, 46]. Singh et al. found that, in particular, the number of cardiovascular diseases of TKA patients increased between 1993 and 2005 [23]. It is therefore important to assess these comorbidities, which are correlated to poor outcomes and to promote health.

The working patients were highly active during the week, considering the 2950 minutes of activity per week. It is questionable to what extent the high physical activity level is helpful to their health status though, as a majority was overweight/obese and perceived poor physical functioning. Seventy percent met the Dutch norm of 30 minutes moderate-intensity activity per day, but that is apparently insufficient to reach normal weight, therefore the focus for these patients should be on caloric intake. Healthcare professionals need to stimulate working patients to lower their caloric intake per day in order to lose weight [47]. Losing weight will improve physical functioning and result in better postoperative outcomes [4750]. The finding that working patients performed twice more activity than retired patients and the general population can be mainly attributed to working patients’ activities at work of 1507 minutes per week. The rather large difference in mean minutes per week of work activities between working patients and the general population can be explained by age and employment status of the two study samples. The working patients had a mean age of 55 and were all employed, in contrast to the general population, which had an average age of 62.7 and was probably not all employed. Employment status was not an inclusion criteria though.

With respect to psychological characteristics, working patients generally had a relatively good mental health with no depressive symptoms. Although working patients dealt on average with significantly more depressive symptoms than the general population, however this was considered not clinically relevant as both are under the threshold of being depressed (>10 symptoms). Singh et al., observed a sevenfold increase in the prevalence of depression among younger (<50 years) TKA patients [23]. Social functioning did not differ between working and retired patients, but working patients perceived significantly worse social functioning compared to the general population. Such poor social functioning was observed in other studies of retired TKA patients [51, 52]. A lack of social support negatively influences social functioning [53].

Working patients worked significantly fewer hours than the general population. This is a common phenomenon in other patient groups dealing with musculoskeletal disorders such as low back pain or rheumatoid arthritis [54, 55]. An additional analysis showed that working patients had mainly physically demanding or a combination of physically and mentally demanding jobs. In a study of Hermans et al. it was found that physically demanding jobs performed by working knee OA patients were leading to significant productivity loss and sickness absence [56]. In that study patients with overweight/obesity and knee pain were absent from work more frequently. Patients in the present study were also dealing with these characteristics, and this may explain the finding that working patients worked fewer hours than the general population.

This study has several strengths and limitations. One of the strengths is that is gives a broader insight into the preoperative characteristics from a representative sample of Dutch TKA patients, compared to previous studies. We used data with preoperative characteristics of working TKA patients covering demographic, physical, psychological and social (including work) characteristics. A second strength is that we were able to compare the characteristics with data of retired TKA patients and the general population, which strengthened the interpretation and grading of the characteristics of working patients. However, there are also some limitations which should be taken into account.

One of the limitations is that the data of working and retired patients was provided by different hospitals. The majority of working patients were planned for TKA in general hospitals, in contrast with the data of retired patients, which were mainly derived from an academic hospital. While more severe knee OA patients are operated in academic hospitals, the cohort of retired patients may include higher comorbidity cases. Moreover, while data was lacking for some characteristics of retired patients (e.g comorbidity), not all characteristics could be compared with retired patients, which limited the interpretation of the data. A limitation of the normative values of the general population is that these values were derived from different countries. Comparisons of normative data between countries (despite them all being Western countries) are sensitive to bias by external factors such as legislation, disability compensation rates and health care [57, 58]. Another limitation is the use of self-administered recall questionnaires to assess preoperative characteristics. With self-reported questionnaires, it is known that overestimation can be an intrinsic property for aspects like physical activity. For that reason it is advised not to use self-reported questionnaires at the individual level, but at the group level, as was done in the present study [59, 60].

Results from the present study show that working TKA patients have distinct preoperative characteristics, including a majority with overweight/obesity, a high number of comorbidities, a large amount of light-intensity physical activity and few depressive symptoms. The high number of comorbidities and the overweight/obesity increases the chances of poor postoperative outcomes and delays recovery [49, 61, 62]. Comorbidities should therefore be assessed and treated, and more emphasis on promoting health should take place early on. The health-promoting focus needs to be on lowering the caloric intake of working patients in order to lose weight and thereby improve physical functioning [47]. Better physical functioning preoperatively will increase the chances of successful postoperative recovery [6365]. Successful recovery is important for personal reasons but also from employers’ perspective, while return to work after surgery needs to be facilitated and preoperative loss of productivity at the workplace needs to be improved postoperatively to decrease indirect societal costs [66].

Further research is needed to identify the links between preoperative characteristics of working patients and postoperative outcomes. These relationships have been examined mainly in retired patients, but studies of working TKA patients are lacking. Moreover, studies that assess preoperative characteristics objectively are needed to prevent the overestimation of outcomes from self-reported questionnaires.

Supporting information

S1 Table. Mean values of the RAND-36 of a Dutch sample of healthy persons per age class [31].

(DOCX)

S2 Table. Mean values for the PHQ-9 (Patient Health Questionnaire 9) of a German population per age class [38].

(DOCX)

S3 Table. Mean values for the WOMAC (Western Ontario and McMaster Osteoarthritis Index) of an Australian population per age class[29].

(DOCX)

Data Availability

All database (SPSS) files are available from the Dryad database (url: http://datadryad.org/review?doi=doi:10.5061/dryad.kc260).

Funding Statement

The authors received no specific funding for this work.

References

  • 1.Arden N, Nevitt MC. Osteoarthritis: epidemiology. Best Pract Res Clin Rheumatol. 2006;20(1):3–25. doi: 10.1016/j.berh.2005.09.007 [DOI] [PubMed] [Google Scholar]
  • 2.Poos MJJC, Gommer AM, Uiters E, Zantinge EM. Hoe vaak komt artrose voor en hoeveel mensen sterven eraan? [What is the prevalence of osteoarthritis and how many people die of it?]: Bilthoven: Health Council of the Netherlands (RIVM); 2009. [Google Scholar]
  • 3.Neogi T, Zhang Y. Epidemiology of osteoarthritis. Rheum Dis Clin North Am. 2013;39(1):1–19. doi: 10.1016/j.rdc.2012.10.004 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Culliford DJ, Maskell J, Beard DJ, Murray DW, Price AJ, Arden NK. Temporal trends in hip and knee replacement in the United Kingdom: 1991 to 2006. J Bone Joint Surg Br. 2010;92(1):130–135. doi: 10.1302/0301-620X.92B1.22654 [DOI] [PubMed] [Google Scholar]
  • 5.Otten R, van Roermund PM, Picavet HS. Trends in the number of knee and hip arthroplasties: considerably more knee and hip prostheses due to osteoarthritis in 2030. Ned Tijdschr Geneeskd. 2010;154:A1534 [PubMed] [Google Scholar]
  • 6.Felson DT, Lawrence RC, Dieppe PA, Hirsch R, Helmick CG, Jordan JM, Kington RS, Lane NE, Nevitt MC, Zhang Y, Sowers M, McAlindon T, Spector TD, Poole AR, Yanovski SZ, Ateshian G, Sharma L, Buckwalter JA, Brandt KD, Fries JF. Osteoarthritis: new insights. Part 1: the disease and its risk factors. Ann Intern Med. 2000;133(8):635–646. [DOI] [PubMed] [Google Scholar]
  • 7.Statistics Netherlands. Levensverwachting naar geslacht, 2010–2060 [life expectancy according to sexe, 2010–2060]. http://statline.cbs.nl/StatWeb/publication/?VW=T&DM=SLNL&PA=80757NED&LA=NL. Accessed 10/27/2014.
  • 8.Heck DA, Robinson RL, Partridge CM, Lubitz RM, Freund DA. Patient outcomes after knee replacement. Clin Orthop Relat Res. 1998;(356)(356):93–110. [DOI] [PubMed] [Google Scholar]
  • 9.Ethgen O, Bruyere O, Richy F, Dardennes C, Reginster JY. Health-related quality of life in total hip and total knee arthroplasty. A qualitative and systematic review of the literature. J Bone Joint Surg Am. 2004;86-A(5):963–974. [DOI] [PubMed] [Google Scholar]
  • 10.Long WJ, Bryce CD, Hollenbeak CS, Benner RW, Scott WN. Total Knee Replacement in Young, Active Patients: Long-Term Follow-up and Functional Outcome: A Concise Follow-up of a Previous Report . J Bone Joint Surg Am. 2014;96(18):e159 [DOI] [PubMed] [Google Scholar]
  • 11.Scuderi GR, Clarke HD. Cemented posterior stabilized total knee arthroplasty. J Arthroplasty. 2004;19(4 Suppl 1):17–21. [DOI] [PubMed] [Google Scholar]
  • 12.Kurtz SM, Lau E, Ong K, Zhao K, Kelly M, Bozic KJ. Future young patient demand for primary and revision joint replacement: national projections from 2010 to 2030. Clin Orthop Relat Res. 2009;467(10):2606–2612. doi: 10.1007/s11999-009-0834-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Ravi B, Croxford R, Reichmann WM, Losina E, Katz JN, Hawker GA. The changing demographics of total joint arthroplasty recipients in the United States and Ontario from 2001 to 2007. Best Pract Res Clin Rheumatol. 2012;26(5):637–647. doi: 10.1016/j.berh.2012.07.014 [DOI] [PubMed] [Google Scholar]
  • 14.Leskinen J, Eskelinen A, Huhtala H, Paavolainen P, Remes V. The incidence of knee arthroplasty for primary osteoarthritis grows rapidly among baby boomers: a population-based study in Finland. Arthritis Rheum. 2012;64(2):423–428. doi: 10.1002/art.33367 [DOI] [PubMed] [Google Scholar]
  • 15.Kim S. Changes in surgical loads and economic burden of hip and knee replacements in the US: 1997–2004. Arthritis Rheum. 2008;59(4):481–488. doi: 10.1002/art.23525 [DOI] [PubMed] [Google Scholar]
  • 16.Khatod M, Inacio M, Paxton EW, Bini SA, Namba RS, Burchette RJ, Fithian DC. Knee replacement: epidemiology, outcomes, and trends in Southern California: 17,080 replacements from 1995 through 2004. Acta Orthop. 2008;79(6):812–819. doi: 10.1080/17453670810016902 [DOI] [PubMed] [Google Scholar]
  • 17.W-Dahl A, Robertsson O, Lidgren L. Surgery for knee osteoarthritis in younger patients. Acta Orthop. 2010;81(2):161–164. doi: 10.3109/17453670903413186 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Kim SH, Gaiser S, Meehan JP. Epidemiology of primary hip and knee arthroplasties in Germany: 2004 to 2008. J Arthroplasty. 2012;27(10):1777–1782. doi: 10.1016/j.arth.2012.06.017 [DOI] [PubMed] [Google Scholar]
  • 19.Sutton PM, Holloway ES. The young osteoarthritic knee: dilemmas in management. BMC Med. 2013;11:14-7015-11-14. doi: 10.1186/1741-7015-11-14 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Diduch DR, Insall JN, Scott WN, Scuderi GR, Font-Rodriguez D. Total knee replacement in young, active patients. Long-term follow-up and functional outcome. J Bone Joint Surg Am. 1997;79(4):575–582. [DOI] [PubMed] [Google Scholar]
  • 21.Klit J, Jacobsen S, Rosenlund S, Sonne-Holm S, Troelsen A. Total knee arthroplasty in younger patients evaluated by alternative outcome measures. J Arthroplasty. 2014;29(5):912–917. doi: 10.1016/j.arth.2013.09.035 [DOI] [PubMed] [Google Scholar]
  • 22.Keeney JA, Nunley RM, Wright RW, Barrack RL, Clohisy JC. Are younger patients undergoing TKAs appropriately characterized as active? Clin Orthop Relat Res. 2014;472(4):1210–1216. doi: 10.1007/s11999-013-3376-x [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Singh JA, Lewallen DG. Time trends in the characteristics of patients undergoing primary total knee arthroplasty. Arthritis Care Res (Hoboken). 2014;66(6):897–906. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Health Council of the Netherlands (RIVM). Hoeveel mensen hebben overgewicht? [how many people have overweight?]. http://www.nationaalkompas.nl/gezondheidsdeterminanten/persoonsgebonden/overgewicht/hoeveel-mensen-hebben-overgewicht/. Accessed 01/09/2015.
  • 25.Statistics Netherlands. Health questionnaire 1989. Voorburg/Heerlen. 1989.
  • 26.Roorda LD, Jones CA, Waltz M, Lankhorst GJ, Bouter LM, van der Eijken JW, Willems WJ, Heyligers IC, Voaklander DC, Kelly KD, Suarez-Almazor ME. Satisfactory cross cultural equivalence of the Dutch WOMAC in patients with hip osteoarthritis waiting for arthroplasty. Ann Rheum Dis. 2004;63(1):36–42. doi: 10.1136/ard.2002.001784 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.McConnell S, Kolopack P, Davis AM. The Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC): a review of its utility and measurement properties. Arthritis Rheum. 2001;45(5):453–461. [DOI] [PubMed] [Google Scholar]
  • 28.Roos EM, Klassbo M, Lohmander LS. WOMAC osteoarthritis index. Reliability, validity, and responsiveness in patients with arthroscopically assessed osteoarthritis. Western Ontario and MacMaster Universities. Scand J Rheumatol. 1999;28(4):210–215. [DOI] [PubMed] [Google Scholar]
  • 29.Bellamy N, Wilson C, Hendrikz J. Population-based normative values for the Western Ontario and McMaster (WOMAC) Osteoarthritis Index: part I. Semin Arthritis Rheum. 2011;41(2):139–148. doi: 10.1016/j.semarthrit.2011.03.002 [DOI] [PubMed] [Google Scholar]
  • 30.van der Zee KI, Sanderman R. Het meten van de algemene gezondheidstoestand met de RAND-36: een handleiding. [measuring general health with the RAND-36: a manual]. Groningen: Noordelijk Centrum voor Gezondheidsvraagstukken, NCG:; 1993.
  • 31.Aaronson NK, Muller M, Cohen PD, Essink-Bot ML, Fekkes M, Sanderman R, Sprangers MA, te Velde A, Verrips E. Translation, validation, and norming of the Dutch language version of the SF-36 Health Survey in community and chronic disease populations. J Clin Epidemiol. 1998;51(11):1055–1068. [DOI] [PubMed] [Google Scholar]
  • 32.Wendel-Vos GC, Schuit AJ, Saris WH, Kromhout D. Reproducibility and relative validity of the short questionnaire to assess health-enhancing physical activity. J Clin Epidemiol. 2003;56(12):1163–1169. [DOI] [PubMed] [Google Scholar]
  • 33.Pate RR, Pratt M, Blair SN, Haskell WL, Macera CA, Bouchard C, Buchner D, Ettinger W, Heath GW, King AC. Physical activity and public health. A recommendation from the Centers for Disease Control and Prevention and the American College of Sports Medicine. JAMA. 1995;273(5):402–407. [DOI] [PubMed] [Google Scholar]
  • 34.Wagenmakers R, van den Akker-Scheek I, Groothoff JW, Zijlstra W, Bulstra SK, Kootstra JW, Wendel-Vos GC, van Raaij JJ, Stevens M. Reliability and validity of the short questionnaire to assess health-enhancing physical activity (SQUASH) in patients after total hip arthroplasty. BMC Musculoskelet Disord. 2008;9:141-2474-9-141. doi: 10.1186/1471-2474-9-141 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Wagenmakers R, Stevens M, Zijlstra W, Jacobs ML, van den Akker-Scheek I, Groothoff JW, Bulstra SK. Habitual physical activity behavior of patients after primary total hip arthroplasty. Phys Ther. 2008;88(9):1039–1048. doi: 10.2522/ptj.20070375 [DOI] [PubMed] [Google Scholar]
  • 36.Kemper H, Ooijendijk W, Stiggelbout M. Consensus about the Dutch physical activity guideline. Tijdschrift Voor Sociale Geneeskunde. 2000;78:180–183. [Google Scholar]
  • 37.Kroenke K, Spitzer RL, Williams JB. The PHQ-9: validity of a brief depression severity measure. J Gen Intern Med. 2001;16(9):606–613. doi: 10.1046/j.1525-1497.2001.016009606.x [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Kocalevent RD, Hinz A, Brahler E. Standardization of the depression screener patient health questionnaire (PHQ-9) in the general population. Gen Hosp Psychiatry. 2013;35(5):551–555. [DOI] [PubMed] [Google Scholar]
  • 39.Statistics Netherlands. Gemiddelde arbeidsduur afgelopen jaren nauwelijks veranderd [average working time did not change in the past years]. http://www.cbs.nl/nl-NL/menu/themas/arbeid-sociale-zekerheid/publicaties/artikelen/archief/2011/2011-3356-wm.htm. Accessed 12/19/2014.
  • 40.Statistics Netherlands. Werkloze en werkzame beroepsbevolking per maand [unemployed and employed labor force per month]. http://statline.cbs.nl/StatWeb/publication/?VW=T&DM=SLNL&PA=80479NED&LA=NL. Accessed 12/19/2014.
  • 41.Statistics Netherlands. Toename ondernemerschap in Nederland [increase of entrepeneurship in the Netherlands]. http://www.cbs.nl/nl-NL/menu/themas/dossiers/ondernemingsklimaat/publicaties/artikelen/archief/2012/2012-ondernemerschap-zzp-art.htm. Accessed 12/19/2014.
  • 42.Rubin DB, Schenker N. Multiple imputation in health-care databases: an overview and some applications. Stat Med. 1991;10(4):585–598. [DOI] [PubMed] [Google Scholar]
  • 43.Rubin DB. Multiple Imputation for Nonresponse in Surveys. New York, John Wiley & Sons; Vol. 307 2009. [Google Scholar]
  • 44.Vos T, Flaxman AD, Naghavi M, Lozano R, Michaud C, Ezzati M, et al. Years lived with disability (YLDs) for 1160 sequelae of 289 diseases and injuries 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet. 2012;380(9859):2163–2196. doi: 10.1016/S0140-6736(12)61729-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45.Zambon S, Siviero P, Denkinger M, Limongi F, Victoria Castell M, et al. , Eposa Research Group. Role of Osteoarthritis, Comorbidity, and Pain in Determining Functional Limitations in Older Populations: European Project on Osteoarthritis. Arthritis Care Res (Hoboken). 2016;68(6):801–810. [DOI] [PubMed] [Google Scholar]
  • 46.Wesseling J, Welsing PM, Bierma-Zeinstra SM, Dekker J, Gorter KJ, Kloppenburg M, Roorda LD, Bijlsma JW. Impact of self-reported comorbidity on physical and mental health status in early symptomatic osteoarthritis: the CHECK (Cohort Hip and Cohort Knee) study. Rheumatology (Oxford). 2013;52(1):180–188. [DOI] [PubMed] [Google Scholar]
  • 47.Bliddal H, Leeds AR, Stigsgaard L, Astrup A, Christensen R. Weight loss as treatment for knee osteoarthritis symptoms in obese patients: 1-year results from a randomised controlled trial. Ann Rheum Dis. 2011;70(10):1798–1803. doi: 10.1136/ard.2010.142018 [DOI] [PubMed] [Google Scholar]
  • 48.Lutzner C, Kirschner S, Lutzner J. Patient activity after TKA depends on patient-specific parameters. Clin Orthop Relat Res. 2014;472(12):3933–3940. doi: 10.1007/s11999-014-3813-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 49.Friedman RJ, Hess S, Berkowitz SD, Homering M. Complication rates after hip or knee arthroplasty in morbidly obese patients. Clin Orthop Relat Res. 2013;471(10):3358–3366. doi: 10.1007/s11999-013-3049-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 50.Jarvenpaa J, Kettunen J, Kroger H, Miettinen H. Obesity may impair the early outcome of total knee arthroplasty. Scand J Surg. 2010;99(1):45–49. doi: 10.1177/145749691009900110 [DOI] [PubMed] [Google Scholar]
  • 51.Kiebzak GM, Campbell M, Mauerhan DR. The SF-36 general health status survey documents the burden of osteoarthritis and the benefits of total joint arthroplasty: but why should we use it? Am J Manag Care. 2002;8(5):463–474. [PubMed] [Google Scholar]
  • 52.De Filippis LG, Gulli S, Caliri A, D'Avola G, Lo Gullo R, Morgante S, Romano C, Munao F, Trimarchi G, La Torre D, Fichera C, Pappalardo A, Triolo G, Gallo M, Valentini G, Bagnato G, Osteoarthritis South Italy Study (OASIS) Group. Factors influencing pain, physical function and social functioning in patients with osteoarthritis in southern Italy. Int J Clin Pharmacol Res. 2004;24(4):103–109. [PubMed] [Google Scholar]
  • 53.Ethgen O, Vanparijs P, Delhalle S, Rosant S, Bruyere O, Reginster JY. Social support and health-related quality of life in hip and knee osteoarthritis. Qual Life Res. 2004;13(2):321–330. doi: 10.1023/B:QURE.0000018492.40262.d1 [DOI] [PubMed] [Google Scholar]
  • 54.Zhang W, Gignac MA, Beaton D, Tang K, Anis AH, Canadian Arthritis Network Work Productivity Group. Productivity loss due to presenteeism among patients with arthritis: estimates from 4 instruments. J Rheumatol. 2010;37(9):1805–1814. doi: 10.3899/jrheum.100123 [DOI] [PubMed] [Google Scholar]
  • 55.Mathew J, Singh SB, Garis S, Diwan AD. Backing up the stories: The psychological and social costs of chronic low-back pain. Int J Spine Surg. 2013;7:e29–38. doi: 10.1016/j.ijsp.2013.02.001 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 56.Hermans J, Koopmanschap MA, Bierma-Zeinstra SM, van Linge JH, Verhaar JA, Reijman M, Burdorf A. Productivity costs and medical costs among working patients with knee osteoarthritis. Arthritis Care Res (Hoboken). 2012;64(6):853–861. [DOI] [PubMed] [Google Scholar]
  • 57.Anema JR, Schellart AJ, Cassidy JD, Loisel P, Veerman TJ, van der Beek AJ. Can cross country differences in return-to-work after chronic occupational back pain be explained? An exploratory analysis on disability policies in a six country cohort study. J Occup Rehabil. 2009;19(4):419–426. doi: 10.1007/s10926-009-9202-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 58.Bieleman HJ, Oosterveld FG, Oostveen JC, Reneman MF, Groothoff JW. Work participation and health status in early osteoarthritis of the hip and/or knee: a comparison between the Cohort Hip and Cohort Knee and the Osteoarthritis Initiative. Arthritis Care Res (Hoboken). 2010;62(5):683–689. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 59.Craig CL, Marshall AL, Sjostrom M, Bauman AE, Booth ML, Ainsworth BE, Pratt M, Ekelund U, Yngve A, Sallis JF, Oja P. International physical activity questionnaire: 12-country reliability and validity. Med Sci Sports Exerc. 2003;35(8):1381–1395. doi: 10.1249/01.MSS.0000078924.61453.FB [DOI] [PubMed] [Google Scholar]
  • 60.Bauman A, Ainsworth BE, Bull F, Craig CL, Hagstromer M, Sallis JF, Pratt M, Sjostrom M. Progress and pitfalls in the use of the International Physical Activity Questionnaire (IPAQ) for adult physical activity surveillance. J Phys Act Health. 2009;6 Suppl 1:S5–8. [DOI] [PubMed] [Google Scholar]
  • 61.Gandhi R, Dhotar H, Razak F, Tso P, Davey JR, Mahomed NN. Predicting the longer term outcomes of total knee arthroplasty. Knee. 2010;17(1):15–18. doi: 10.1016/j.knee.2009.06.003 [DOI] [PubMed] [Google Scholar]
  • 62.Odum SM, Springer BD, Dennos AC, Fehring TK. National obesity trends in total knee arthroplasty. J Arthroplasty. 2013;28(8 Suppl):148–151. doi: 10.1016/j.arth.2013.02.036 [DOI] [PubMed] [Google Scholar]
  • 63.Hoogeboom TJ, Dronkers JJ, van den Ende CH, Oosting E, van Meeteren NL. Preoperative therapeutic exercise in frail elderly scheduled for total hip replacement: a randomized pilot trial. Clin Rehabil. 2010;24(10):901–910. doi: 10.1177/0269215510371427 [DOI] [PubMed] [Google Scholar]
  • 64.Dauty M, Genty M, Ribinik P. Physical training in rehabilitation programs before and after total hip and knee arthroplasty. Ann Readapt Med Phys. 2007;50(6):462–8, 455–61. doi: 10.1016/j.annrmp.2007.04.011 [DOI] [PubMed] [Google Scholar]
  • 65.Stevenson JD, Roach R. The benefits and barriers to physical activity and lifestyle interventions for osteoarthritis affecting the adult knee. J Orthop Surg Res. 2012;7:15-799X-7-15. doi: 10.1186/1749-799X-7-15 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 66.Bedair H, Cha TD, Hansen VJ. Economic benefit to society at large of total knee arthroplasty in younger patients: a Markov analysis. J Bone Joint Surg Am. 2014;96(2):119–126. [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 Table. Mean values of the RAND-36 of a Dutch sample of healthy persons per age class [31].

(DOCX)

S2 Table. Mean values for the PHQ-9 (Patient Health Questionnaire 9) of a German population per age class [38].

(DOCX)

S3 Table. Mean values for the WOMAC (Western Ontario and McMaster Osteoarthritis Index) of an Australian population per age class[29].

(DOCX)

Data Availability Statement

All database (SPSS) files are available from the Dryad database (url: http://datadryad.org/review?doi=doi:10.5061/dryad.kc260).


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