Open Access
Open Peer Review

This article has Open Peer Review reports available.

How does Open Peer Review work?

No long-term impact of low-energy distal radius fracture on health-related quality of life and global quality of life: a case-control study

  • Gudrun Rohde1, 2Email author,
  • Glenn Haugeberg1,
  • Anne Marit Mengshoel2,
  • Torbjorn Moum3 and
  • Astrid K Wahl2, 4
BMC Musculoskeletal Disorders200910:106

https://doi.org/10.1186/1471-2474-10-106

Received: 29 March 2009

Accepted: 25 August 2009

Published: 25 August 2009

Abstract

Background

Changes in patient-reported outcomes like health related quality of life (HRQOL) and global quality of life (GQOL) in patients with low-energy distal radius fracture might be related to fracture, or be within the normal range of variation in an elderly population. Hence, the present study aims to examine: Whether patients with low-energy distal radius fracture attain their pre-fracture levels in HRQOL and GQOL one year after the fracture and compare these levels with age- and sex-matched controls; and whether objective factors predict changes in HRQOL and GQOL during the same one year period.

Methods

We examined 160 patients and 169 age- and sex matched controls, respectively (mean ± SD) 67 ± 9 and 66 ± 9 years of age. HRQOL was assessed by the Modified Health Assessment Questionnaire (MHAQ) and the Short–Form 36 (SF-36). The Quality of Life Scale (QOLS) assessed GQOL. Paired sample t-tests and multiple linear regression analyses were applied.

Results

After one year no differences were found in HRQOL (assessed as arm functions, physical health and mental health) compared to pre-fracture level in the patient group. Both patients with distal radius fracture and controls reported a reduced GQOL after one year (p < 0.001). Low-energy distal radius fracture did not predict worsened HRQOL or GQOL one year after inclusion, and few predictors of changes were identified. Worsened arm function was predicted by low BMI (B = -0.20, p = 0.019) at baseline, worsened physical health was predicted by low education (B = 1.37, p = 0.017) at baseline, and living with someone predicted worsened mental health (B = 2.85, p = 0.009)

Conclusion

Patients with a distal radius fracture seem to manage well despite the fracture, and distal radius fracture is not an independent predictor of worsened HRQOL and GQOL.

Background

The distal radius is a frequent site of osteoporotic fractures in elderly and seems to occur most frequently among relatively healthy elderly people [1, 2]. Distal radius fractures do also occur about 15 years earlier in life than other osteoporotic fractures like hip fractures [3, 4]. Furthermore, a low-energy distal radius fracture has been identified as a predictor of future fracture of both hip and spine [4]. Patients with low-energy distal radius fractures report reduced arm functions and pain the first weeks after the fracture, and some patients may never regain pre-fracture arm functions [57]. This may impact quality of life (QOL).

QOL cover different physical, psychological and social aspects, and emphasize the patients' perception of these aspects. QOL comprises both health-related quality of life (HRQOL) defined as an individuals' experience of their general state of health, such as physical, social, and mental well-being [8] and global quality of life (GQOL) reflecting an individuals' satisfaction with life, and has a meaning beyond an individuals' health [9].

To identify changes in subjective outcomes such as HRQOL and GQOL after a fracture might give patients and their caregivers a better understanding of expected recovery. Previous studies of HRQOL after distal radius fractures have shown that most recovery in arm functions occurs during the first 6 months after the fracture, and at one year follow-up most patients report no or minimal pain and disability [6, 1012]. Furthermore, patients with a distal radius fracture seem to reach population-based levels of HRQOL some time after the fracture, although numerous patients report remaining symptoms from the fracture [5, 7]. Education, co-morbidities and injury compensation at baseline seem to be covariates of how patients report their pain and disability one year after a distal radius fracture, indicating that also factors independent of the injury play a role in self-reported arm functions after the fracture [13]. In other studies, low bone mineral density (BMD) and low body mass index (BMI) are identified as determinants of reduced HRQOL two years after a distal radius fracture [7].

Previous research on patients with low-energy fracture seems to lack a broader perspective in one and the same study, including both objective factors, such as BMD, BMI and other demographic and clinical measures, as well as patient-reported outcome like HRQOL and GQOL. Presently, all these variables are assessed. Furthermore, we ask whether the changes in HRQOL and GQOL in patients with low-energy distal radius fracture are related to the fracture or within the normal range of variation in an elderly population [14]. Hence, the present study aims to examine:
  1. 1)

    Whether patients with low-energy distal radius fracture attain their pre-fracture levels in HRQOL and GQOL one year after the fracture, and compare these levels with age- and sex-matched controls;

     
  2. 2)

    Whether objective factors predict changes in HRQOL and GQOL during the same one year period.

     

Methods

Study design, patients and controls

To study one-year changes in HRQOL and GQOL in patients with low-energy distal radius fracture we applied a case-control, prospective longitudinal study design. The study was recommended by the Regional Committee for Medical Research Ethics and approved by the National Data Inspectorate.

Patients with low-energy distal radius fracture aged 50 years and older were consecutively recruited from an osteoporosis centre at a regional hospital in southern Norway in 2004 and 2005. A low-energy fracture was defined as a minimal trauma falling from standing height or less [15], and a distal radius fracture was defined as located within 3 cm of the radio-carpal joint [16]. The distal radius fractures were closed injuries, and the fractures were treated conservatively by stabilising the fracture by a plaster cast or by external fixation. Patients were assessed and data collected in median 10 days (interquartile range 13) after fracture and reassessed one year after fracture. With regard to demographical and clinical variables, HRQOL and GQOL the patients were asked to report their status prior to fracture. The patients also were asked to report their exercise habits, falls and the use of health care recourses during the year before fracture. The controls were asked about their status and habits prior to inclusion. The same data collection performed at baseline was repeated after one year.

The included patients comprised 56% of all 324 patients with low-energy distal radius fracture treated at the hospital, and 73% of 249 patients examined at the osteoporosis centre. Before inclusion in this study, we confirmed that the fracture was not a result of high-energy trauma and was caused only by minimal trauma according to the definition of low-energy fracture [17]. Patients who were excluded comprised a total of 51 patients with confusion or dementia, serious infection, patients not capable of giving informed consent, patients not capable of speaking Norwegian or tourists and 92 patients who did not want to participate in the study.

At baseline 181 patients with distal radius fracture were included along with 181 age- and sex-matched controls. The age- and sex-matched controls were randomly allocated from the national registry for the catchment area and invited by mail to participate in the study. The controls were identified consecutively along with patient recruitement. If a potential control refused to participate or did not respond to the invitation, a new control was invited. Overall, 131 potential controls refused to participate or did not respond to the invitation. We aimed an age match of ± 1 year in the patients with distal radius fracture; however, this was a challenge for some of the patients aged 80 years and older. In these patients we accepted a match of ± 5 years, except for one woman aged 96 years who was matched with an 86 years old control.

Demographical and clinical variables

Demographical and clinical data (listed in table 1) were collected, and included also exercise, smoking habits, medication, previous fracture, number of falls the year before the fracture, and co-morbidity. Furthermore, patients and controls reported their use of health care resources; like visiting general practitioners, medical specialists, physiotherapists, and hospitalization the year prior to the fracture or prior to inclusion in the control group. Regular exercise was defined as walking or doing more intensive exercise more than 30 minutes three times a week. Previous fracture was defined as a low-energy trauma fracture after the age of 50. Co-morbidity included heart diseases, pulmonary diseases, neurological disorders, urogenital disorders, gastrointestinal disorders, endocrine disorders, inflammatory joint disorders and connective tissue disorders, cancer, mental disorders. For co-morbidity, we also computed a sum score of the number of diseases in each patient and control, which was used in the multivariate analyses.
Table 1

Baseline demographical and clinical characteristics in patients with low-energy distal radius fracture and controls who visited the osteoporosis centre at both inclusion and at one year follow up.

 

Distal radius fracture

Controls

p*

 

n = 160

n = 169

 

Demographics

   

Age (years; mean (SD))

67 (9)

66 (9)

0.457

Females

144 (90)

151 (89)

0.846

BMI (kg/m2)

25.7 (4.3)

26.7 (4.3)

0.027

Menarche (years; mean (SD))

13.9 (1.5)

13.6 (1.4)

0.066

Menopause (years; mean (SD))

48.9 (4.5)

49.6 (4.1)

0.086

Education

  

0.011

< 10 years

56 (38)

70 (42)

 

11–13 years

61 (42)

45 (27)

 

> 13 years

30 (20)

53 (31)

 

Co-habiting

84(53)

112 (67)

0.011

Regular exercise**

119 (74)

126 (74)

0.970

Current smoker

23 (14)

21 (12)

0.604

Clinical characteristics

   

Current calcium and/or vitamin D treatment

39 (24)

41 (24)

0.981

Current ART

28 (18)

22 (13)

0.258

Previous fractures

83 (52)

77 (47)

0.319

≥ 1 fall in the previous year

68 (47)

48 (36)

0.054

Osteoporosis

52 (32)

30 (18)

<0.001

Osteopenia

83 (52)

74 (44)

 

Normal BMD

25 (16)

64 (38)

 

Heart diseases

48 (30)

58 (34)

0.402

Pulmonary diseases

19 (12)

12 (7)

0.138

Neurological diseases

12 (8)

14 (8)

0.792

Endocrine disorders

14 (9)

20 (12)

0.358

Gastrointestinal disorders

8 (5)

21 (12)

0.018

Urogenital disorders

5 (3)

1 (1)

0.086

Inflammatory joint disorders and connective tissue disorders

36 (23)

45 (26)

0.385

Cancer

16 (10)

19 (11)

0.715

Mental disorders

7 (4)

11 (7)

0.395

Co-morbidities (range 0–6)

1.0 (1.0)

1.2 (1.1)

0.191

Mean (SD) for continuous variables and numbers (%) for categorical variables.

*Bold p-values indicate significant differences between the groups

** Exercise more than 30 minutes three times a week.

BMI, body mass index; ART, antiresorptive treatment, a specific osteoporosis treatment comprising biphosphonates, or selective oestrogen-receptor modulators.

Bone density measurements

Standardized BMD measurements at lumbar spine L2-4 and both hips were performed by four trained nurses using the same dual energy X-ray absorptiometry (DXA) equipment (General Electric, Lunar Prodigy) at baseline and at one year follow-up. The machine was stable over the entire measurement period. Long term spine phantom in-vitro coefficient of variation (CV) for the whole period was 0.62%. The in-vivo CV for the measurement procedure was 1.19% at lumbar spine L2-4, 0.95% at right total hip and 0.89% at left total hip. The BMD measurements were expressed as T-scores (SD) calculated on the basis of the reference value in the DXA machine provided by the manufacturer. Osteoporosis was defined as T-score ≤ -2.5 SD, osteopeniae as T-score > -2.5 and < -1.0 and normal BMD as T-score > -1.0, according to the WHO definition for osteoporosis [17].

Modified Health Assessment Questionnaire (MHAQ)

Modified Health Assessment Questionnaire (MHAQ) measures a patients ability to perform activities of daily living [18, 19]. Although primarily developed as a measure for use in rheumatoid arthritis, MHAQ has been used across a variety of diseases [20]. The MHAQ consists of 8 items covering daily activities including skills that demand a good arm function e.g. dressing, lift a full cup or glass to the mouth, wash and dry the entire body [18, 19]. The total mean scores range from 1–4, with 1 representing "without any difficulty". For incomplete questionnaires, the missing values were replaced with the mean value of the answered questions of the respondent when at least 6 out of 8 items had valid response, which is based on the scale instructions given by the developers of the questionnair [20, 21]. At baseline all the the patients and controls had valid responses. At one year follow-up 1,5% of the patients and 1% of the controls had one or two missing responses. In the multivariate analyses, which were performed to identify if a low-energy distal radius fracture was a predictor of worsened arm functions, we rescaled MHAQ from 0 to 100, with 100 representing "without any difficulty" in accordance with prior studies [21, 22].

Short Form – 36 (SF-36)

The Short- Form 36 (SF-36) was used to assess HRQOL (physical and mental health) [23, 24]. The SF-36 includes eight domains (general health, bodily pain, physical functioning, physical role limitations, mental health, vitality, social functioning, and emotional role limitations), which can be combined into a physical health summary scale and a mental health summary scale. The physical component summary (PCS) and mental component summary (MCS) scales were used in this study. The SF-36 scales were scored according to published scoring procedures, and each was expressed as a value from 0 to 100, with 100 representing "excellent health". For incomplete questionnaires substitution of missing values is based on the scale instructions given by the developers of the questionnaire [23, 24]. At baseline 5.6% of the patients and 13.5% of the controls had one or more missing responses. At one year follow-up 18.8% of the patients and 14% of the controls had one or more missing responses. The questionnaire has been thoroughly tested for psychometric properties in other studies, within several countries, including Norway [2326].

Quality of Life Scale (QOLS)

The Quality of Life Scale (QOLS), a 16-item, domain-specific instrument adapted by Burckhardt et al. for people with chronic conditions, was used to assess GQOL [9, 27, 28]. In this questionnaire GQOL is understood as a broad range of human experiences related to one's overall well-being and satisfaction. The QOLS is a self-administered questionnaire [27, 29]. The items are rated at a 7-point satisfaction scale. For incomplete questionnaires, the missing values were replaced with the mean value of the answered questions of the respondent when at least 80% of the items had a valid response. The substitution of missing values is based on the scale instructions given by the developers of the questionnaire [9, 27]. At baseline 26% of the patients and 23% of the controls had one or more missing responses. At one year follow-up 35% of the patients and 33% of the controls had one or more missing responses. The items with most missing responses were QOLS item number four (having and rearing children) and item five (close relationship with spouse or other significant other).

The questionnaire is scored by adding up the items to obtain a total score from a minimum of 16 to a maximum of 112. Higher scores indicate better GQOL. Burckhardt et al. [28] suggested that the QOLS comprising three sub-dimensions: relationship and marital well-being (items 3, 4, 5, 6, and 14); health and functioning (items 1, 2, 11, 15, and 16); and personal, social, and community commitment (items 7, 8, 9, 10, 12, and 13) [28, 30]. The three dimensions are scored by summing the scores for each item in the dimension. The questionnaire has been thoroughly tested for psychometric properties in other studies, within several countries [28, 3032].

Statistical analysis

Statistical analyses were carried out using the Statistical Package for Social Sciences (SPSS) for Windows (version 16.0). Chi-square tests and t-tests were used to compare differences between subgroups. Wilcoxon rank tests were used to compare continuous health care resources data between inclusion and one year follow-up, and paired samples t-tests were used to compare HRQOL and GQOL at inclusion and one year follow-up within the patients with distal radius fracture and within the controls. Furthermore, standard difference scores (s-scores) were calculated by subtracting the mean MHAQ, SF-36 or QOLS scores at baseline from the mean score of one year follow-up, and then dividing by the standard deviation (SD) at baseline [33]. To estimate the proportion of patients and controls with clinically significant changes in HRQOL and GQOL, we also identified participants with modest changes (between -5 and -10%), moderate changes (between -10 and -20%) and substantial changes (more than -20%) between baseline and one year follow-up [33, 34]

Multiple linear regression analyses (procedure GLM in the SPSS) were used to identify significant predictors of worsened HRQOL (delta total mean MHAQ, SF-36; delta PCS and delta MCS) or GQOL (delta QOLS) in the study-population (both patients and controls). The regression analyses were adjusted for baseline total mean MHAQ (rescaled), PCS, MCS or QOLS respectively, at inclusion. The independent variables in the multiple regression analyses were selected based on results from earlier studies which show that age, sex, education level, marital status, BMD, falls, BMI, co-morbidity and osteoporotic fractures appear to be associated with HRQOL and/or GQOL, and these variables were all included in the regression model [14]. To test if the effects of predictors of change in our dependent variables were significantly different for patients and controls, interaction terms involving the patient/control dichotomy and each of the predictors were entered one pair at a time, while retaining main effects in the model. The level of significance was set at 0.05.

Results

Respondents

The patients in the study were significantly (p < 0.001) younger (67 ± 9 years) than the excluded patients (76 ± 12 years) and those who did not want to participate (72 ± 11 years). Among the 181 patients with distal radius fracture and 181 controls included at baseline, 160 patients and 169 controls attended the osteoporosis-centre at one year follow-up. There were minor differences between participants at one year follow-up and participants who were lost to follow-up. Among patients with distal radius fracture a statistically significant difference was only reported for gastrointestinal disorders (p = 0.015). Among controls, those who were lost to follow-up were significantly older (p = 0.046), and reported significantly lower SF-36 score in vitality (p = 0.014).

Demographical and clinical characteristics and use of health care resources

Socio-demographical and clinical characteristics at baseline of those participants who completed both baseline and one year follow-up assessments are shown in table 1.

Patients with distal radius fracture more often were living alone (p = 0.011), had fewer years of education (p = 0.011), had lower BMI (p = 0.027), and were more frequently classified with osteoporosis (p < 0.001) compared to the controls. The distal radius fracture occurred indoors in 31 (19%) patients and outdoors in 129 patients (81%). Mean age in patients whose fracture occurred indoors was 70 ± 11 years old and outdoors 66 ± 9 years old (p = 0.074).

At one year follow-up, the patients with distal radius fracture compared with controls were also more frequent user of calcium and/or vitamin D treatment (103 vs. 88, p = 0.024) and antiresorbtive treatment (ART) (52 vs. 27, p < 0.001). Four patients with distal radius fracture and no controls got a new fracture between inclusion and one-year follow-up (p = 0.069).

During the one year follow-up, patients with distal radius fracture on average visited their general practitioner more frequently than the year before fracture (3.9 vs. 3.4, p = 0.006). There were no significant differences with regard to the number of visits to other health care providers, like medical specialists (p = 0.083), physiotherapist (p = 0.139) or number of days hospitalized the last year (p = 0.581), the year following the fracture compared to number of visits the year before fracture. There were no significant changes in the controls.

Changes in HRQOL and GQOL

No significant changes in arm function as assessed by MHAQ were identified in patients with distal radius fracture at one year follow-up compared to the baseline (prior to fracture) assessment (p = 0.202) (table 2). Only ten patients (6%) with a distal radius fracture did not attain their pre-fracture arm functions one year after fracture.
Table 2

Health-related quality of life in patients with low-energy distal radius fracture and controls at baseline and after one year.

 

Patients with distal radius fracture (n = 160)

Controls (n = 169)

 

Baseline

One year

p

Effect size

Mean change (SD)

Baseline

One year

p

Effect size

Mean change (SD)

MHAQ*

1.04 (0.16)

1.05 (0.21)

0.202

0.06

0.01 (0.1)

1.06 (0.22)

1.06 (0.20)

0.802

0.01

0.0 (0.2)

SF-36 **

          

PCS

51.2 (9.4)

50.4 (9.8)

0.209

-0.1

-0.8 (7.6)

51.2 (8.4)

51.3 (8.6)

0.846

0.1

0.1 (5.9)

MCS

50.2 (9.9)

50.3 (10.5)

0.840

0.01

0.2 (9.2)

51.7 (8.4)

51.7 (8.6)

0.908

0.1

0.1 (7.2)

Data are given as means with standard deviation, and paired sample t-tests were applied to detect significant differences between baseline and follow-up.

* the MHAQ scores range from 1 to 4, where 1 means high perception of their ability to perform activities of daily living.

** The score for SF-36 ranges from 0 to 100, where 100 means high HRQOL.

PCS = physical component summary, MCS = mental component summary, MHAQ = The Modified Health Assessment Questionnaire.

Furthermore, no significant changes were identified in HRQOL as assessed by the SF-36; physical health (p = 0.209) and mental health (p = 0.840) from pre-fracture to one year after the fracture in the patients with a distal radius fracture. The same pattern was seen in controls (table 2).

With regard to GQOL, the patients with distal radius fracture reported significantly lower total GQOL score (p < 0.001, s-score = -0.4) and for the sub-dimensions; relationship and marital well-being (p = 0.015, s-score = -0.2), health and functioning (p = 0.001, s-score = -0.2) and personal, social and community commitment (p < 0.001, s-score = -0.3) at one year follow-up compared to the baseline assessment (table 3). In the controls we also found significant changes in GQOL scores within both the overall score and the three sub-dimensions (p < 0.001) one year after inclusion, with s-score = -0.6 in QOLS, s-score = -0.3 for relationship and marital well being, s-score = -0.4, s-score = -0.4 for health and functioning and s-score = -0.6 in personal, social and community commitment (table 3).
Table 3

Global quality of life in the patients with low-energy distal radius fracture and controls at baseline and after one year.

 

Patients with distal radius fracture (n = 160)

Controls (n = 169)

 

Baseline

After one year

P****

Effect size

Mean

change(SD)

Baseline

After one year

P****

Effect size

Mean

change(SD)

Total QOLS-score *

94.4 (10.5)

90.8 (12.6)

<0.001

-0.4

-4.0

(8.9)

97.3 (8.4)

92.7 (10.2)

<0.001

-0.4

-4.9

(7.8)

Relationship and Marital Well-being**

31.5 (3.0)

30.9 (3.2)

0.015

-0.2

-0.7

(3.0)

32.1 (2.9)

31.1 (3.0)

0.015

-0.2

-1.0

(2.4)

Health and Functioning**

29.1 (3.9)

28.2 (4.5)

0.001

-0.2

-0.9

(3.2)

30.0 (3.4)

28.7 (4.0)

0.001

-0.2

-1.3

(3.1)

Personal, Social and Community Commitment***

34.0 (5.0)

32.3 (5.8)

<0.001

-0.3

-1.8

(4.7)

35.2 (3.8)

33.0 (5.0)

<0.001

-0.3

-2.1

(4.6)

Data are given as means with standard deviation, and paired sample t-tests were applied to detect significant differences between baseline and follow-up.

* Range from 16 to 112, where 112 means high GQOL.

**Range 5–35, where 35 means high GQOL.

***Range 6–42, where 42 means high GQOL.

**** P-values marked with bold indicate statistically significant p-values.

QOLS = quality of life scale.

Modest (-5 to -10) or moderate (-10 to -20) worsening arm functions between baseline and one year follow up were reported by 2.5% of the patients and 3% of the controls and substantial change (-20 or more) in 2 patients and one control. Modest or moderate worsening of physical health was reported by 20% of the patients and 10% of the controls, and substantial changes in one patient. Modest or moderate worsening of mental health was reported by 19% of the patients and 14% of the controls and substantial changes in four patients and in one control. Furthermore, modest or moderate worsening of GQOL was reported by 35% of the patients and 42% of the controls.

No significant differences between the patients with distal radius fracture and controls were identified in HRQOL and GQOL at one year follow-up.

Prediction of changes in HRQOL and GQOL

A low-energy distal radius fracture did not predict worsened HRQOL or GQOL one year after inclusion, and few predictors of changes were identified. Worsened arm function was predicted by low BMI (B = -0.20, p = 0.019) at baseline, worsened physical health was predicted by low education (B = 1.37, p = 0.017) at baseline, and living with someone predicted worsened mental health (B = 2.85, p = 0.009) (table 4).
Table 4

Predictors of change in health-related quality of life (delta MHAQ, delta PCS, and delta MCS) and global quality of life (delta QOLS) in both patients with low-energy distal radius fracture (n = 160) and controls (n = 169).

 

MHAQ Adj B (95% CI)

p

PCS Adj B (95% CI)

p

MCS Adj B (95% CI)

p

QOLS Adj B (95% CI)

P

Demographic

        

Age*

-0.06

0.878

-0.90

0.101

-0.09

0.885

-0.48

0.520

 

(-0.90, 0.77)

 

(-1.97, 0.18)

 

(-0.14, 0.12)

 

(-1.74, 0.88)

 

Male

-0.24

0.840

0.03

0.984

-0.77

0.662

-2.16

0.222

 

(-2.56, 2.08)

 

(-2.87, 2.93)

 

(-4.24, 2.70)

 

(-5.62, 1.32)

 

Female

Ref

 

Ref

 

Ref

 

Ref

 

Education

0.83

0.060

1.37

0.017

-0.27

0.690

0.57

0.390

 

(-0.04, 1.69)

 

(0.25, 2.48)

 

(-1.60, 1.06)

 

(-0.74, 1.88)

 

Living alone

-0.11

0.877

-0.59

0.517

2.85

0.009

0.22

0.837

 

(-1.51, 1.29)

 

(-2.37, 1.20)

 

(0.71, 4.99)

 

(-1. 92, 2.37)

 

Living together

Ref

 

Ref

 

Ref

 

Ref

 

Clinical

        

Radius patients

-0.23

0.744

-0.51

0.574

-1.24

0.258

0.53

0.619

 

(-1.62, 1.16)

 

(-0.56, 0.57)

 

(-3.39, 0.91)

 

(-1.58, 2.65)

 

Controls

Ref

 

Ref

 

Ref

 

Ref

 

Osteopenia**

-1.22

0.143

-1.08

0.301

-0.76

0.547

-2.41

0.051

 

(-2.85, 0.41)

 

(-3.14, 0.97)

 

(-3.21, 1.71)

 

(-4.82, 0.01)

 

Osteoporosis**

-1.59

0.118

-0.69

0.597

0.98

0.531

-2.35

0.131

 

(-3.58, 0.41)

 

(-3.26, 1.88)

 

(-2.1 0, 4.05)

 

(-5.39, 0.70)

 

Normal BMD

Ref

 

Ref

 

Ref

 

Ref

 

BMI

-0.20

0.019

-0.15

0.178

-0.06

0.630

-0.25

0.054

 

(-0.37, -0.03)

 

(-0.36, 0.07)

 

(-0.19, 0.32)

 

(-0.51, -0.01)

 

Co-morbidity

-0.01

0.965

-0.77

0.112

-0.92

0.075

-0.92

0.077

 

(-0.67, 0.64)

 

(-1.71, 0.18)

 

(-1.24, 1.97)

 

(-1.94, 0.10)

 

≥ 1 fall in the last year

-1.04 (-2.39, 0.32)

0.132

-1.13 (-2.86, 0.60)

0.201

0.67 (-1.42, 2.76)

0.527

-0.06 (-2.10, 1.98)

0.953

No fall

Ref

 

Ref

 

Ref

 

Ref

 

HRQOL/GQOL

        

MHAQ incl

-0.31

<0.001

      
 

(-0.41, 0.14)

       

PCS incl

  

-0.39 (-0.50, -0.28)

<0.001

    

MCS incl

    

-0.36 (-0.47, -0.25)

<0.001

  

QOLS incl

      

-0.25 (-0.36, -0.13)

<0.001

R 2 adj

15.5%

 

17.7%

 

16.9%

 

11.0%

 

Regression analyses of demographics, clinical characteristics, and rescaled MHAQ at inclusion of changes in MHAQ/SF-36 at inclusion on change in SF-36/QOLS at inclusion of changes in QOLS. Adjusted unstandardized regression coefficients, 95% CI, p values.

P-values marked with bold indicate statistically significance.

* Age in decades.

** Osteopenia/osteoporosis at total hip and/or spine L2-L4.

BMD = bone mineral density, BMI = body mass index, MHAQ = Mean total MHAQ (rescaled MHAQ, range 0–100, where 100 means favourable perception of ability to perform activities of daily living), PCS = physical component summary, MCS = mental component summary (range 0 – 100, where 100 means perfect health), QOLS = quality of life scale (range 16 – 112), where 112 means high GQOL

Interaction terms between pairs of each independent variable and the patients/controls dichotomy (tested one pair at a time, with main effects retained) revealed no significantly different effects between the patients with wrist fracture and the controls in the regression analyses.

Discussion

A low-energy distal radius fracture was not identified as a significant predictor of worsened HRQOL or GQOL one year after fracture, and the changes in HRQOL and GQOL in patients with low-energy distal radius fracture seem to be within the normal range of variation in an elderly population. Only a small proportion of the patients with a distal radius fracture did not attain their prefracture arm functions one year after fracture, even when using a modest change or slightly decreased function to identify this group [35].

The proportion of patients with distal radius fracture who did not attain their pre-fracture level of physical health (as assessed by the SF-36) was larger than the proportion of patients who did not attain their pre-fracture arm functions (as assessed by the MHAQ). The same pattern of changes was reported by the controls. This might reflect the fact that SF-36, which was used to measure physical health, is comprised of different items or skills than those included in MHAQ, e.g. walking long distances and doing outdoor activities [18, 23, 24]. Such skills deteriorate with aging [36], and the changes in physical health might therefore reflect normal changes or be within the normal range of variation appearing in this age-group.

Despite high levels of GQOL, significantly worsened GQOL was found in both fracture and control group. However, it should be added that separate analyses using comparative data from a nationwide sample indicate that the mean GQOL scores reported at inclusion as well as at one year follow-up by the patients and the controls in the present study were significantly higher than the scores observed in the general Norwegian population [37]. The same pattern of decrease in GQOL over a one year period has been observed within other patient groups [38, 39]. Furthermore, it might be that those patients and controls who agreed to participate did so at a point in time when their GQOL was better than their own typical (long-term) level, thus creating a "regression to mean" effect when one year later that had returned to their usual level of GQOL [14]. The decreased GQOL scores in both patients with distal radius fracture and controls might be explained by the influence of non-medical factors such as characteristics of the individual and the environment like coping and retirement [4045], – factors which have not been focused in this study.

Known correlates/covariates of HRQOL and GQOL like demographical and clinical variables could only to a limited extent predict changes in HRQOL and GQOL. Different methods of fracture treatment might have explained some of the changes in HRQOL. However, the methods of treatment used in each case have unfortunately not been included in the study, and Handoll et al [16] showed insufficient evidence to confirm differences in functional outcome between plaster cast and external fixation treatment [16]. Moreover, several studies have shown that diseases or injuries (e.g. a wrist fracture), and HRQOL and GQOL have bidirectional relationships, though all are influenced by characteristics of the individual and the environment [40, 4346]. Furthermore, the studies have shown that characteristics of the individuals and the environment influence HRQOL and GQOL differently, and non-medical factors seem to influence GQOL more than HRQOL [40, 4345]. In line with earlier studies, low education seems to be a predictor of changes in self-reported health outcomes [13, 47]. However, in general it seems difficult to give a plausible substantive explanation of the worsening in HRQOL and GQOL observed in our elderly study-population.

The population-based and unselected group of patients with distal radius fracture along with matched controls may be seen as strengths of the present study. However, this study has some limitations, which should be considered when interpreting the findings. When included in the study briefly after the fracture had occurred, the patients were asked to evaluate their "pre-fracture" HRQOL and GQOL. Changes in health, such as having experienced a fracture, might cause a shift in how the patients perceived their prefracture HRQOL and GQOL (selective reporting bias and response shift) [48]. On the other hand, patients who have experienced a recent change in health have been found to be more likely to give accurate responses [33, 49, 50]. The patients were asked to think of the period before the fracture, and in most of the patients, HRQOL and GQOL were assessed within the first two weeks after the fracture. It seems unlikely that the patients at this point were unable to accurately recall their HRQOL and GQOL immediately before and at the time of the fracture.

We probably reached the healthiest patients with distal radius fracture in our region in our study. The patients unwilling to participate and the excluded patients were significantly older and probably less healthy than the patients included in the study [51]. Our finding might therefore be applied to other relatively healthy patients with distal radius fracture aged 50 years and older.

Conclusion

Patients with a low-energy distal radius fracture seem to manage well one year after the fracture, and the distal radius fracture is not an independent predictor of worsened HRQOL or GQOL. This might be attributed to the fracture being experienced as a minor trauma and to the successful treatment. The proportion of patients with distal radius fracture who did not attain their pre-fracture HRQOL and GQOL seems to be comparable with the normal range of variation in this age-group. A low-energy distal radius fracture might not be considered a substantial trauma with consequences in the long run, and hence not calling for additional health care efforts.

Abbreviations

ART: 

antiresorptive treatment

BMD: 

bone mineral density

BMI: 

body mass index

DXA: 

dual-energy X-ray absorptiometry

GLM: 

General Linear Model

GQOL: 

global quality of life

HRQOL: 

health related quality of life

MCS: 

mental component summary

MHAQ: 

Modified Health Assessment Questionnaire

PCS: 

physical component summary

SF-36: 

Short Form-36

s-score: 

standard difference score

QOLS: 

The Quality of Life Scale

WHO: 

World Health Organization.

Declarations

Acknowledgements

We appreciate the expert technical assistance and help with the data collection of our osteoporosis nurses Hanne Vestaby, Ann Haestad and Tove Kjoestvedt. This work has been supported and funded by The Competence Development Fund of Southern Norway and Sørlandet Hospital HF. Gudrun Rohde is a recipient of a research career grant from The Competence Development Fund of Southern Norway, Sorlandet Hospital HF and Health Southern Norway Regional Trut.

Authors’ Affiliations

(1)
Department of Rheumatology, Sorlandet Hospital
(2)
Institute of Nursing and Health Sciences, Medical Faculty, University of Oslo
(3)
Department of Behavioural Sciences in Medicine, Medical Faculty, University of Oslo
(4)
Centre for Shared Decision Making and Nursing Research Rikshospitalet

References

  1. Cummings SR, Melton LJ: Epidemiology and outcomes of osteoporotic fractures. Lancet. 2002, 359: 1761-1767. 10.1016/S0140-6736(02)08657-9.View ArticlePubMedGoogle Scholar
  2. O'neill TW, Cooper C, Finn JD, Lunt M, Purdie D, Reid DM, Rowe R, Woolf AD, Wallace WA: Incidence of distal forearm fracture in British men and women. Osteoporos Int. 2001, 12: 555-558. 10.1007/s001980170076.View ArticlePubMedGoogle Scholar
  3. Finsen V, Benum P: Colles' fracture as an indicator of increased risk of hip fracture. An epidemiological study. Ann Chir Gynaecol. 1987, 76: 114-118.PubMedGoogle Scholar
  4. Mallmin H, Ljunghall S, Persson I, Naessen T, Krusemo UB, Bergstrom R: Fracture of the distal forearm as a forecaster of subsequent hip fracture: a population-based cohort study with 24 years of follow-up. Calcif Tissue Int. 1993, 52: 269-272. 10.1007/BF00296650.View ArticlePubMedGoogle Scholar
  5. Brenneman SK, Barrett-Connor E, Sajjan S, Markson LE, Siris ES: Impact of recent fracture on health-related quality of life in postmenopausal women. J Bone Miner Res. 2006, 21: 809-816. 10.1359/jbmr.060301.View ArticlePubMedGoogle Scholar
  6. MacDermid JC, Roth JH, Richards RS: Pain and disability reported in the year following a distal radius fracture: a cohort study. BMC Musculoskelet Disord. 2003, 4: 24-10.1186/1471-2474-4-24.View ArticlePubMedPubMed CentralGoogle Scholar
  7. Hallberg I, Rosenqvist AM, Kartous L, Lofman O, Wahlstrom O, Toss G: Health-related quality of life after osteoporotic fractures. Osteoporos Int. 2004, 15: 834-841. 10.1007/s00198-004-1622-5.View ArticlePubMedGoogle Scholar
  8. WHO: ICF: International Classification of Functioning, Disability and health. Geneva. 2001, [http://www.who.int/classification/icf]Google Scholar
  9. Burckhardt CS, Anderson KL: The Quality of Life Scale (QOLS): Reliability, Validity, and Utilization. Health Qual Life Outcomes. 2003, 1: 60-10.1016/j.jhsa.2004.07.002.View ArticlePubMedPubMed CentralGoogle Scholar
  10. Anzarut A, Johnson JA, Rowe BH, Lambert RG, Blitz S, Majumdar SR: Radiologic and patient-reported functional outcomes in an elderly cohort with conservatively treated distal radius fractures. J Hand Surg [Am]. 2004, 29: 1121-1127. 10.1016/j.crad.2006.08.013.View ArticleGoogle Scholar
  11. Jaremko JL, Lambert RG, Rowe BH, Johnson JA, Majumdar SR: Do radiographic indices of distal radius fracture reduction predict outcomes in older adults receiving conservative treatment?. Clin Radiol. 2007, 62: 65-72. 10.1302/0301-620X.82B7.10377.View ArticlePubMedGoogle Scholar
  12. Wakefield AE, McQueen MM: The role of physiotherapy and clinical predictors of outcome after fracture of the distal radius. J Bone Joint Surg Br. 2000, 82: 972-976. 10.1007/s11552-007-9030-x.View ArticlePubMedGoogle Scholar
  13. Grewal R, MacDermid JC, Pope J, Chesworth BM: Baseline predictors of pain and disability one year following extra-articular distal radius fractures. Hand. 2007, 2: 104-111. 10.1007/s00198-003-1507-z.View ArticlePubMedPubMed CentralGoogle Scholar
  14. Altman DG: Practical statistics for medical research. 2006, London; New York: Chapman and HallGoogle Scholar
  15. McLellan AR, Gallacher SJ, Fraser M, McQuillian C: The fracture liaison service: success of a program for the evaluation and management of patients with osteoporotic fracture. Osteoporos Int. 2003, 14: 1028-1034. 10.1007/s00198-003-1507-z.View ArticlePubMedGoogle Scholar
  16. Handoll HH, Huntley JS, Madhok R: External fixation versus conservative treatment for distal radial fractures in adults. Cochrane Database Syst Rev. 2007, 18 (3): CD006194-10.1016/0002-9343(93)90218-E.Google Scholar
  17. Consensus development conference: diagnosis, prophylaxis, and treatment of osteoporosis. Am J Med. 1993, 94: 646-650. 10.1002/art.1780261107.Google Scholar
  18. Pincus T, Summey JA, Soraci SA, Wallston KA, Hummon NP: Assessment of patient satisfaction in activities of daily living using a modified Stanford Health Assessment Questionnaire. Arthritis Rheum. 1983, 26: 1346-1353. 10.1002/art.1780261107.View ArticlePubMedGoogle Scholar
  19. Pincus T, Callahan LF, Brooks RH, Fuchs HA, Olsen NJ, Kaye JJ: Self-report questionnaire scores in rheumatoid arthritis compared with traditional physical, radiographic, and laboratory measures. Ann Intern Med. 1989, 110: 259-266. 10.1002/1529-0131(199910)42:10<2220::AID-ANR26>3.0.CO;2-5.View ArticlePubMedGoogle Scholar
  20. Pincus T, Swearingen C, Wolfe F: Toward a multidimensional Health Assessment Questionnaire (MDHAQ): assessment of advanced activities of daily living and psychological status in the patient-friendly health assessment questionnaire format. Arthritis Rheum. 1999, 42: 2220-2230. 10.1016/S0895-4356(98)00099-7.View ArticlePubMedGoogle Scholar
  21. Kvien TK, Kaasa S, Smedstad LM: Performance of the Norwegian SF-36 Health Survey in patients with rheumatoid arthritis. II. A comparison of the SF-36 with disease-specific measures. J Clin Epidemiol. 1998, 51: 1077-1086. 10.1016/S0895-4356(98)00099-7.View ArticlePubMedGoogle Scholar
  22. Haavardsholm EA, Kvien TK, Uhlig T, Smedstad LM, Guillemin F: A comparison of agreement and sensitivity to change between AIMS2 and a short form of AIMS2 (AIMS2-SF) in more than 1,000 rheumatoid arthritis patients. J Rheumatol. 2000, 27: 2810-2816.PubMedGoogle Scholar
  23. Ware JE, Snow KK, Kosinski MA, Gandek MS: SF-36 Health Survey Manual & Interpretation Guide. 1993, Boston: Massachusetts: New England Medical Centre, The Health InstituteGoogle Scholar
  24. Ware JE, Kosinski MA, Keller SD: SF-36 Physical and Mental health Summery Scale: A User's Manual. 1994, Boston: Massachusetts: New England Medical Centre, The Health InstituteGoogle Scholar
  25. Loge JH, Kaasa S: Short form 36 (SF-36) health survey: normative data from the general Norwegian population. Scand J Soc Med. 1998, 26: 250-258. 10.1016/S0895-4356(98)00098-5.PubMedGoogle Scholar
  26. Loge JH, Kaasa S, Hjermstad MJ, Kvien TK: Translation and performance of the Norwegian SF-36 Health Survey in patients with rheumatoid arthritis. I. Data quality, scaling assumptions, reliability, and construct validity. J Clin Epidemiol. 1998, 51: 1069-1076. 10.1002/nur.4770120604.View ArticlePubMedGoogle Scholar
  27. Burckhardt CS, Woods SL, Schultz AA, Ziebarth DM: Quality of life of adults with chronic illness: a psychometric study. Res Nurs Health. 1989, 12: 347-354. 10.1186/1477-7525-1-59.View ArticlePubMedGoogle Scholar
  28. Burckhardt CS, Anderson KL, Archenholtz B, Hagg O: The Flanagan Quality of Life Scale: Evidence of Construct Validity. Health Qual Life Outcomes. 2003, 1: 59-10.1186/1477-7525-1-59.View ArticlePubMedPubMed CentralGoogle Scholar
  29. Burckhardt CS, Archenholtz B, Bjelle A: Quality of life of women with systemic lupus erythematosus: a comparison with women with rheumatoid arthritis. J Rheumatol. 1993, 20: 977-981. 10.1111/j.1471-6712.2004.00311.x.PubMedGoogle Scholar
  30. Liedberg GM, Burckhardt CS, Henriksson CM: Validity and reliability testing of the Quality of Life Scale, Swedish version in women with fibromyalgia – statistical analyses. Scand J Caring Sci. 2005, 19: 64-70. 10.1007/s00520-006-0026-9.View ArticlePubMedGoogle Scholar
  31. Grov EK, Dahl AA, Fossa SD, Wahl AK, Moum T: Global quality of life in primary caregivers of patients with cancer in palliative phase staying at home. Support Care Cancer. 2006, 14: 943-951. 10.1080/02839319850162823.View ArticlePubMedGoogle Scholar
  32. Wahl A, Burckhardt C, Wiklund I, Hanestad BR: The Norwegian version of the Quality of Life Scale (QOLS-N). A validation and reliability study in patients suffering from psoriasis. Scand J Caring Sci. 1998, 12: 215-222. 10.1023/A:1008996223999.PubMedGoogle Scholar
  33. Fayers PM, Machin D: Quality of life: the assessment, analysis and interpretation of patient-reported outcomes. 2007, Chichester: John WileyView ArticleGoogle Scholar
  34. Revicki DA, Osoba D, Fairclough D, Barofsky I, Berzon R, Leidy NK, Rothman M: Recommendations on health-related quality of life research to support labeling and promotional claims in the United States. Qual Life Res. 2000, 9: 887-900. 10.1023/A:1008996223999.View ArticlePubMedGoogle Scholar
  35. Kosinski M, Kujawski SC, Martin R, Wanke LA, Buatti MC, Ware JE Jr, Perfetto EM: Health-related quality of life in early rheumatoid arthritis: impact of disease and treatment response. Am J Manag Care. 2002, 8: 231-240. 10.1023/B:QURE.0000025583.28948.5b.PubMedGoogle Scholar
  36. Spirduso W: Physical dimentions of Aging. 1995, Human Kinitics, USAGoogle Scholar
  37. Wahl AK, Rustoen T, Hanestad BR, Lerdal A, Moum T: Quality of life in the general Norwegian population, measured by the Quality of Life Scale (QOLS-N). Qual Life Res. 2004, 13: 1001-1009. 10.1097/01.tp.0000268071.63977.42.View ArticlePubMedGoogle Scholar
  38. Andersen MH, Mathisen L, Veenstra M, Oyen O, Edwin B, Digernes R, Kvarstein G, Tonnessen TO, Wahl AK, Hanestad BR, Fosse E: Quality of life after randomization to laparoscopic versus open living donor nephrectomy: long-term follow-up. Transplantation. 2007, 84: 64-69. 10.1034/j.1600-0412.2000.079007598.x.View ArticlePubMedGoogle Scholar
  39. Bo K, Talseth T, Vinsnes A: Randomized controlled trial on the effect of pelvic floor muscle training on quality of life and sexual problems in genuine stress incontinent women. Acta Obstet Gynecol Scand. 2000, 79: 598-603. 10.1111/j.1547-5069.2005.00058.x.View ArticlePubMedGoogle Scholar
  40. Ferrans CE, Zerwic JJ, Wilbur JE, Larson JL: Conceptual model of health-related quality of life. J Nurs Scholarsh. 2005, 37: 336-342. 10.1093/jncimonographs/lgm008.View ArticlePubMedGoogle Scholar
  41. Ferrans CE: Differences in what quality-of-life instruments measure. J Natl Cancer Inst Monogr. 2007, 37: 22-26. 10.1016/S0002-9343(99)00052-2.View ArticlePubMedGoogle Scholar
  42. Covinsky KE, Wu AW, Landefeld CS, Connors AF Jr, Phillips RS, Tsevat J, Dawson NV, Lynn J, Fortinsky RH: Health status versus quality of life in older patients: does the distinction matter?. Am J Med. 1999, 106: 435-440. 10.1093/jncimonographs/lgm002.View ArticlePubMedGoogle Scholar
  43. Osoba D: Translating the science of patient-reported outcomes assessment into clinical practice. J Natl Cancer Inst Monogr. 2007, 37: 5-11. 10.1001/jama.273.1.59.View ArticlePubMedGoogle Scholar
  44. Spilker B: Quality of life and pharmacoeconomics in clinical trials. 1996, Philadelphia: Lippincott-RavenGoogle Scholar
  45. Wilson IB, Cleary PD: Linking clinical variables with health-related quality of life. A conceptual model of patient outcomes. JAMA. 1995, 273: 59-65. 10.1186/1477-7525-5-27.View ArticlePubMedGoogle Scholar
  46. Mathisen L, Andersen MH, Veenstra M, Wahl AK, Hanestad BR, Fosse E: Quality of life can both influence and be an outcome of general health perceptions after heart surgery. Health Qual Life Outcomes. 2007, 5: 27-10.1016/S0277-9536(99)00129-X.View ArticlePubMedPubMed CentralGoogle Scholar
  47. Kempen GI, Brilman EI, Ranchor AV, Ormel J: Morbidity and quality of life and the moderating effects of level of education in the elderly. Soc Sci Med. 1999, 49: 143-149. 10.1016/S0277-9536(99)00045-3.View ArticlePubMedGoogle Scholar
  48. Sprangers MA, Schwartz CE: Integrating response shift into health-related quality of life research: a theoretical model. Soc Sci Med. 1999, 48: 1507-1515. 10.1097/00005650-199205000-00003.View ArticlePubMedGoogle Scholar
  49. Brown JB, Adams ME: Patients as reliable reporters of medical care process. Recall of ambulatory encounter events. Med Care. 1992, 30: 400-411. 10.1586/14737167.4.2.159.View ArticlePubMedGoogle Scholar
  50. Schmier JK, Halpern MT: Patient recall and recall bias of health state and health status. Pharmacoeconomics Outcome Res. 2004, 2: 159-163. 10.1046/j.1365-2753.2001.00296.x.View ArticleGoogle Scholar
  51. Seymour DG, Ball AE, Russell EM, Primrose WR, Garratt AM, Crawford JR: Problems in using health survey questionnaires in older patients with physical disabilities. The reliability and validity of the SF-36 and the effect of cognitive impairment. J Eval Clin Pract. 2001, 7: 411-418. 10.1046/j.1365-2753.2001.00296.x.View ArticlePubMedGoogle Scholar
  52. Pre-publication history

    1. The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2474/10/106/prepub

Copyright

© Rohde et al; licensee BioMed Central Ltd. 2009

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Advertisement