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Associations of cardiovascular risk factors, carotid intima-media thickness and manifest atherosclerotic vascular disease with carpal tunnel syndrome

  • Rahman Shiri1Email author,
  • Markku Heliövaara2,
  • Leena Moilanen3,
  • Jorma Viikari4,
  • Helena Liira5, 6 and
  • Eira Viikari-Juntura1
BMC Musculoskeletal Disorders201112:80

https://doi.org/10.1186/1471-2474-12-80

Received: 8 September 2010

Accepted: 26 April 2011

Published: 26 April 2011

Abstract

Background

The role of atherosclerosis in carpal tunnel syndrome (CTS) has not previously been addressed in population studies. The aim of this study was to investigate the associations of cardiovascular risk factors, carotid artery intima-media thickness (IMT), and clinical atherosclerotic diseases with CTS.

Methods

In this cross sectional study, the target population consisted of subjects aged 30 or over who had participated in the national Finnish Health Survey in 2000-2001. Of the 7977 eligible subjects, 6254 (78.4%) were included in our study. Carotid IMT was measured in a sub-sample of subjects aged 45 to 74 (N = 1353).

Results

Obesity (adjusted odds ratio (OR) 2.4, 95% confidence interval (CI) 1.1-5.4), high LDL cholesterol (OR 3.8, 95% CI 1.6-9.1 for >190 vs. <129 mg/dL), high triglycerides (OR 2.7, 95% CI 1.2-6.1 for >200 vs. <150 mg/dL), hypertension (OR 3.4, 95% CI 1.6-7.4) and cardiac arrhythmia (OR 10.2, 95% CI 2.7-38.4) were associated with CTS in subjects aged 30-44. In the age group of 60 years or over, coronary artery disease (OR 1.9, 95% CI 1.1-3.5), valvular heart disease (OR 2.3, 95% CI 1.0-5.0) and carotid IMT (1.4, 95% CI 0.9-2.1 for each 0.23 mm increase) were associated with CTS. Carotid IMT was associated with CTS only in subjects with hypertension or clinical atherosclerotic vascular disease, or in those who were exposed to physical workload factors.

Conclusions

Our findings suggest an association between CTS and cardiovascular risk factors in young people, and carotid IMT and clinical atherosclerotic vascular disease in older people. CTS may either be a manifestation of atherosclerosis, or both conditions may share similar risk factors.

Keywords

Atherosclerosiscarotid arterycoronary artery diseasehypertensionobesitysmokingwrist

Background

Carpal tunnel syndrome (CTS) is the most common nerve entrapment [1, 2]. It can cause major work disability and incur considerable costs to society [3]. Epidemiological studies have reported a higher risk of CTS among women than among men [1, 46]. It is common in the third trimester of pregnancy, and in cases of hypothyroidism [7, 8] and renal disease [9]. Among men [4, 5, 10] and women [4, 10], the age distribution of CTS is bimodal, with a peak between the ages of 50 and 59 and a second peak among those aged 70 or over.

Symptoms of CTS may appear when there is edema in the carpal tunnel, the volume of the contents of the tunnel is increased, the vulnerability of the nerve is increased, or the blood supply of the nerve is impaired. Endothelial damage may increase vascular permeability and cause edema in the carpal tunnel [11, 12]. Increased interstitial fluid pressure in the carpal tunnel causes compression of the carpal tunnel contents, especially the median nerve. This may lead to poor blood circulation in the flexor synovial cells and the median nerve. Histological studies have shown edema, vascular sclerosis and fibrous tissue in the flexor tenosynovium [13, 14].

Conditions that may increase the vulnerability of the median nerve include diabetes [7, 8, 15], renal disease [9], smoking [1618] and the toxic effects of alcohol [19]. Impairment of vascular supply may increase the vulnerability of the nerve to mechanical loads, and prolonged tissue ischemia can lead to degeneration of the nerve and intraneural fibrosis [12, 20]. Tenosynovitis of the finger flexor tendons is the most common cause for increases in the contents of the carpal tunnel. It occurs commonly in rheumatoid arthritis [21] and as a result of high physical workload exposure [22]. Mechanical stress may play a greater role among young rather than old people [6]. In contrast, ischemia caused by cardiovascular diseases or atherosclerosis may play a major role among elderly people.

Some evidence exists on the role of atherosclerosis risk factors such as obesity, smoking, LDL cholesterol and metabolic syndrome in CTS [16, 17, 2327]. However, there is no evidence so far to support an association between atherosclerosis and CTS. In this study, we investigated the associations of atherosclerosis risk factors, carotid intima-media thickness (IMT), a surrogate marker of early atherosclerosis, and clinical atherosclerotic diseases with CTS. We hypothesized that atherosclerosis plays a larger role in the pathogenesis of CTS among older people rather than among younger individuals. The higher prevalence of CTS among elderly people - the second peak of the bimodal age distribution of CTS - may be due to atherosclerotic vascular disease. Moreover, we hypothesized that the presence of atherosclerotic disease increases the vulnerability of the median nerve to mechanical stress due to physical exposures.

Methods

Population

In the national health examination survey, Health 2000, the target population comprised men and women aged 30 or over residing in Finland between the fall of 2000 and the spring of 2001 [6]. To obtain a representative sample of the whole Finnish population, a two-stage stratified cluster sampling design was used and sample stratified according to the five university hospital regions, each containing roughly one million inhabitants. From each university hospital region, 16 health care districts were sampled as clusters.

The purpose of this survey was to provide up-to-date information on major public health problems in Finland, their causes and treatment, as well as functional capacity and work ability [28]. Information was gathered by means of interview and clinical health examination. At the comprehensive health examination, specially trained nurses carried out a symptom interview on cardiovascular and musculoskeletal complaints, and physicians performed a standardized physical examination, which included assessing the status of the upper extremity.

The original sample consisted of 8028 subjects aged 30 or over. Of these, 51 died before the interview, 6986 (87.6%) were interviewed, and 6354 (79.7%) participated in the health examinations. Subjects with missing CTS information (n = 100) were excluded, leaving 6254 (78.4%) subjects eligible for the analysis [6].

The Ethical Committee of Epidemiology and National Welfare of the Helsinki University Hospital District approved the Health 2000 survey on the 21st of September 1999. All participants gave their informed consent.

Outcome

The diagnosis of possible CTS was based on 1) possible or classic/probable Katz hand diagrams (pain or paraesthesia or decreased sensitivity present in the thumb or index or middle finger during the preceding seven days), plus 2) either a positive Tinel's test result, combined wrist flexion and carpal compression, decreased sensation in the median nerve distribution, or weakness of thumb abduction or wasting of the thenar eminence [29]. A probable case of CTS was defined as a classic/probable Katz hand diagram (symptoms in two of the three radial fingers), and positive findings in at least two of the four clinical tests. We also gathered information regarding surgery due to CTS.

Determinants

Atherosclerosis risk factors

Smoking status was assessed by a home interview and the subjects were defined as 1) current smokers if they smoked cigarettes, cigars or a pipe at the time of the interview; 2) former smokers if they had smoked for at least one year in the past and were not current smokers; 3) occasional smokers; and 4) never smokers. For current smokers, pack years were estimated and grouped into three levels (<10, 10-20, >20). Leisure-time physical activity was assessed by a single global question; "How often do you exercise so that you are short of breath or sweating?" We classified physical activity into three levels: ≤ 1, 2-3, and ≥ 4 times per week.

Weekly consumption of alcohol was recorded in units (drinks, serving portions) and converted into grams of absolute alcohol. Alcohol consumption was grouped into 4 levels, none (0 grams of alcohol), light, moderate, or heavy (the three latter were based on tertiles of the distribution).

Height, weight, waist circumference and hip circumference were measured. Body mass index (BMI) was classified into underweight (BMI <18.5 kg/m2), normal weight (BMI 18.5-24.9 kg/m2), overweight (BMI 25-29.9 kg/m2) and obesity (BMI ≥30 kg/m2). Waist circumference was grouped into three levels; for men <94 cm, 94-101.9 cm, and ≥102 cm, and for women <80 cm, 80-87.9 cm and ≥88 cm. Waist-to-hip ratio was classified into three groups: for men <0.9, 0.9-1.0, and >1.0, and for women <0.8, 0.8-0.9, and >0.9.

The diagnosis of hypertension was based on a systolic blood pressure of ≥140 mm Hg or a diastolic blood pressure of ≥90 mm Hg, or a previous diagnosis of hypertension together with the use of blood pressure lowering medication. The diagnosis of diabetes was based on elevated fasting blood glucose, and/or a known previous diagnosis of diabetes, or glucose lowering medication.

Fasting blood samples were collected for the analysis of serum glucose, insulin, cholesterol, and triglycerides. We defined metabolic syndrome according to the criteria of the American Association of Clinical Endocrinologists [30], i.e. when at least three of the following criteria were present: 1) Central obesity, defined as waist circumference >102 cm for men and >88 cm for women; 2) high fasting triglycerides, defined as ≥151 mg/dl; 3) low high-density lipoprotein cholesterol defined as <40 mg/dl for men and <50 mg/dl for women; 4) elevated blood pressure, defined as a systolic blood pressure of ≥130 mm Hg or a diastolic blood pressure of ≥85 mm Hg; and 5) impaired fasting glucose, defined as a fasting glucose of ≥110 mg/dl. The homeostasis model assessment of insulin resistance was defined as serum insulin × glucose/22.5. High-sensitive serum C-reactive protein was defined as ≥ 3 mg/l.

Atherosclerotic diseases

Information on cardiovascular diseases was obtained through interview and clinical examination. The diagnosis of coronary artery disease was based on a physician ascertained diagnosis of previous angina pectoris, myocardial infarction, coronary angioplasty or a by-pass operation. The diagnosis of cerebrovascular disease was based on a history of previous stroke or a transient ischemic attack. Other heart or vascular diseases were heart failure, cardiac arrhythmia, valvular disease, or intermittent claudication, and the diagnoses were based on history.

Carotid artery intima-media thickness

Earlier [31] we described the details of ultrasound measures of carotid artery intima-media thickness (IMT). Ultrasound measures of carotid IMT were performed in a sub-sample of men and women aged 45 to 74 who resided within 200 kilometers of the six study clinics that had cardiovascular ultrasound equipment with a linear array transducer available. The six study clinics covered six Finnish towns and their surrounding areas (Helsinki, Turku, Tampere, Kuopio, Joensuu, and Oulu). Subjects (N = 1867) who fulfilled these eligibility criteria were invited and 1526 (82%) of them participated in the carotid artery ultrasound study. We assessed the relation between IMT and CTS among 1353 (72%) subjects whose data on both carotid artery ultrasound and CTS was available.

A high-resolution B-mode carotid ultrasound examination of the right carotid artery was performed first on the distal 1 cm of the common carotid artery and then on the carotid artery bulb. The IMT was measured from three digitized end diastole images of the common carotid artery (lateral angle) and the carotid bulb (three interrogation angles). We used an average of these six measures in the analysis of this study.

Covariates

The home interview elicited information on age, gender, years of education, and work-related physical load factors. The presence of the following physical exposures in the current job was elicited (frequency or duration per day); working with hands above the shoulder plane, manual handling of loads over 5 kg, manual handling of loads over 20 kg, working with a vibrating tool, work demanding high handgrip forces, and repetitive movements of the hands or wrists [6]. In our previous report [6] we showed that in the presence of all physical load factors in the model, only high handgrip forces for at least one hour and using vibrating tools for at least two hours were associated with CTS. Therefore in the current study we controlled the obtained odds ratios of CTS for high handgrip forces and using vibrating tools.

The presence of somatization was assessed using the 13-item somatization part of Symptom Check List-90 [32]. We excluded three questions on pain and scored the remaining 10 items on a five-point Likert scale. The total score for each subject ranged from 0 to 40, with higher scores reflecting higher levels of somatization. In our earlier report, we tested a range of psychological and psychosocial factors. In the presence of all these factors we found an association with somatisation only. We therefore controlled for only this factor.

Statistical methods

The statistical significance level was set at P < 0.05. We adjusted P-values for multiple testing using Bonferroni correction and set statistical significance level at P-value ≤ 0.003 for 15 subgroup analyses. Logistic regression models were run to study the associations of atherosclerosis risk factors, carotid IMT, and clinical vascular diseases with CTS. We used three outcomes (possible and probable CTS combined, probable CTS, surgery due to CTS) to take into consideration the severity of the disorder and the likelihood of correct diagnosis. We performed survey data analysis by using Stata's svy prefix command. Survey data analysis considers the weighting, clustering, and stratification of the survey design to correct imbalances in the probabilities of selection and to estimate the right standard errors. Stata's default svy variance estimator, the linearized variance estimator, was used to compute standard errors [33]. In the nonsurvey data analysis, this variance estimator refers to as the robust variance estimator. Confidence intervals were calculated based on the number of observations in the specific group being analysed. Age (continuous), gender, years of education (continuous), somatization (continuous), high handgrip forces and using vibrating tools were included in the logistic regression models as confounders. Gender- and age-specific analyses were also carried out. Effect modification was studied using stratified analysis. Multiplicative interactions were tested by including product terms in the multivariable models between physical load factors, risk factors of atherosclerosis, carotid IMT (categorized into two groups using the median) and clinical atherosclerotic disease.

Results

Background characteristics

The mean age of the study population was 52 and 48% were men. One-fourth of the population was current smokers and the mean BMI was 26.2 kg/m2 (Table 1). The most common cardiovascular diseases were hypertension and coronary artery disease. The mean carotid IMT was 0.93 mm (range 0.5-2.5 mm). The prevalence of possible and probable CTS combined was 3.8%, probable CTS 1.0%, and operated CTS 1.3%.
Table 1

Background characteristics of study subjects (weighted proportion or mean), Health 2000 Survey, 2000-2001.

Characteristic

Mean (SD)

% (95% CI)

Age (years)

51.9 (13.9)

 

Years of education

11.3 (4.0)

 

Smoking status

  

   Former

 

31 (30-32)

   Current

 

26 (24-27)

Weight-related

  

Body mass index (kg/m2)

26.2 (4.3)

 

Waist circumference (cm)

93 (13.3)

 

Hip circumference (cm)

102 (9.5)

 

Serum lipids

  

LDL cholesterol (mg/dL)

148 (46)

 

HDL cholesterol (mg/dL)

52 (15)

 

Total cholesterol (mg/dL)

232 (44)

 

Metabolic factors

  

Metabolic syndrome

 

30 (29-32)

Diabetes

 

5.2 (4.6-5.9)

Hypertension

 

20 (18-21)

Cardiovascular diseases

  

Coronary artery disease

 

7.1 (6.4-7.8)

Heart failure

 

1.7 (1.3-2.0)

Arrhythmia

 

5.1 (4.5-5.7)

Valvular heart disease

 

2.5 (2.1-3.0)

Cerebrovascular disease

 

2.7 (2.3-3.1)

Intermittent claudication

 

1.2 (0.9-1.5)

Atherosclerosis

  

Carotid intima-media thickness (mm)

0.93 (0.23)

 

Individual psychological factor

  

Somatization (score 0-40)

6.7 (5.8)

 

Carpal tunnel syndrome

  

   Possible or probable

 

3.8 (3.3-4.4)

   Probable

 

1.0 (0.7-1.3)

   Operated

 

1.3 (1.0-1.6)

Men had higher BMI, waist circumference and carotid IMT and lower HDL cholesterol than women. They were more frequently smokers and more commonly had coronary artery disease and intermittent claudication compared to women. In contrast, hypertension, heart failure, somatization and CTS were more common among women than among men.

Atherosclerosis risk factors and CTS

After adjustment for potential confounders, current smoking was associated with possible and probable CTS combined (OR 2.1, 95% 1.4-3.1) and probable CTS (OR 2.9, 95% CI 1.3-6.4). Among current smokers, there was no dose-response relationship between the number of pack-years smoked and CTS (Table 2). BMI, waist circumference and high-sensitive C-reactive protein were associated with operated CTS only. Leisure-time physical activity, alcohol consumption, waist-to-hip ratio, LDL and HDL cholesterol were not associated with CTS. Subjects with type 1 diabetes or metabolic syndrome had a higher prevalence of CTS than those without the condition. Furthermore, the prevalence of operated CTS was higher among subjects with high triglycerides, insulin resistance, or hypertension compared with those without such conditions. None of these associations, however, was statistically significant.
Table 2

Adjusted odds ratios (OR) of carpal tunnel syndrome (CTS) according to cardiovascular risk factors.

Characteristic

Sample

Possible and probable CTS combined

Probable CTS

Operated CTS

  

Cases

OR

95% CI

Cases

OR

95% CI

Cases

OR

95% CI

Smoking status

          

   Never smoker

2062

84

1

 

20

1

 

29

1

 

   Former smoker

1649

51

1.2

0.8-1.6

11

1.0

0.4-2.3

15

1.0

0.5-1.8

   Occasional smoker

333

9

1.2

0.5-2.6

3

2.0

0.6-6.8

5

2.4

0.9-6.3

   Current smoker

          

<10 pack-years

501

26

2.0

1.2-3.5

3

1.1

0.3-3.9

6

1.4

0.5-3.7

10-20 pack-years

400

26

2.6

1.5-4.4

12

5.7

2.3-14.1

6

1.8

0.6-4.7

>20 pack-years

429

19

1.7

0.9-3.1

7

2.7

0.9-8.0

6

1.5

0.6-3.7

Exercise (times/week)

          

   ≤1

2496

96

1

 

21

1

 

29

1

 

   2-3

1973

68

1.0

0.7-1.5

15

1.0

0.5-1.8

25

1.1

0.6-1.9

   ≥ 4

1621

69

1.2

0.8-1.6

23

1.6

0.9-3.0

24

1.2

0.6-2.0

Alcohol consumption

          

   None

1237

67

1

 

19

1

 

22

1

 

   Light

972

31

1.0

0.6-1.6

5

0.6

0.2-1.7

9

0.9

0.3-2.2

   Moderate

978

25

0.9

0.5-1.5

8

1.1

0.4-2.8

7

0.8

0.3-2.0

   Excessive

987

30

1.5

0.8-2.7

6

1.1

0.4-2.9

8

1.3

0.5-3.3

Body mass index

          

   Normal

2514

82

1

 

18

1

 

17

1

 

   Underweight

61

0

  

0

  

1

1.9

0.2-15.1

   Overweight

2288

82

1.1

0.7-1.5

20

1.1

0.5-2.0

33

2.0

1.1-3.7

   Obese

1002

58

1.3

0.8-1.9

19

1.6

0.8-3.0

24

2.8

1.3-5.8

Waist circumference

          

   Normal

2019

59

1

 

15

1

 

6

1

 

   Increased

1684

44

0.8

0.4-1.2

9

0.6

0.2-1.8

20

3.7

1.5-9.0

   Obese

2509

137

1.1

0.7-1.6

36

1.1

0.5-2.1

52

4.8

1.9-12.1

Waist-to-hip ratio

          

   Normal

922

24

1

 

5

1

 

9

1

 

   Increased

3554

135

1.3

0.8-2.1

29

1.3

0.5-3.2

38

0.9

0.4-2.2

   Obese

1735

81

1.3

0.7-2.2

26

1.6

0.6-4.4

31

1.4

0.5-3.2

LDL cholesterol (mg/dL)

          

   ≤129

2072

69

1

 

23

1

 

22

1

 

   130-189

3132

125

1.2

0.8-1.7

26

0.7

0.4-1.2

38

1.1

0.6-1.9

   ≥190

1032

49

1.4

0.9-2.2

13

1.0

0.5-1.9

19

1.5

0.8-2.9

HDL cholesterol (mg/dL)

          

   ≥60

1689

77

1

 

21

1

 

22

1

 

   40-60

3207

119

0.8

0.6-1.2

24

0.7

0.3-1.2

36

0.9

0.5-1.7

   ≤40

1340

47

0.8

0.5-1.2

17

1.1

0.5-2.2

21

1.5

0.7-2.8

Total cholesterol (mg/dL)

          

   >200

1543

45

1

 

15

1

 

12

1

 

   200-239

2206

91

1.4

0.9-2.3

18

0.8

0.4-1.8

27

1.5

0.7-3.0

   ≤240

2487

107

1.4

0.9-2.3

29

1.1

0.5-2.2

40

1.8

0.9-3.6

Triglycerides (mg/dL)

          

   ≤150

4186

163

1

 

39

1

 

46

1

 

   151-199

1069

42

0.8

0.6-1.1

13

1.0

0.5-1.8

16

1.1

0.5-2.3

   ≥ 200

981

38

1.0

0.6-1.5

10

1.0

0.4-2.3

17

1.7

0.9-3.1

High-sensitive C-reactive protein

          

   Low (≤3 mg/L)

5117

195

1

 

46

1

 

54

1

 

   High (>3 mg/L)

1062

47

0.9

0.6-1.3

16

1.2

0.6-2.3

25

1.7

1.1-2.8

Insulin resistance (tertile)

          

   1st

2077

68

1

 

18

1

 

18

1

 

   2nd

2072

83

1.0

0.7-1.4

17

0.8

0.4-1.5

24

1.2

0.7-2.2

   3rd

2083

92

1.1

0.8-1.6

27

1.1

0.6-1.9

37

1.7

0.9-3.3

Metabolic syndrome

          

   No

4313

145

1

 

32

1

 

41

1

 

   Yes

1902

96

1.1

0.8-1.5

30

1.6

0.98-2.6

36

1.5

0.9-2.5

Diabetes

          

   No

5880

222

1

 

55

1

 

71

1

 

   Type 1

34

2

1.9

0.4-8.5

1

3.5

0.4-29.0

1

-

-

   Type 2

319

19

1.0

0.5-1.8

6

1.2

0.4-3.5

7

1.1

0.5-2.6

Hypertension

          

   No

5017

174

1

 

43

1

 

52

  

   Yes

1237

69

1.2

0.8-1.6

19

1.2

0.6-2.1

27

1.6

0.9-2.7

A separate model was run for each characteristic and the odds ratios obtained were adjusted for age, sex, education, somatization, handgrip with high forces and work using vibrating tools

Atherosclerotic disease and CTS

Subjects with coronary artery disease, valvular heart disease, intermittent claudication, or cerebrovascular disease had a higher prevalence of possible and probable CTS combined (Table 3, Figure 1) or probable CTS (Table 3) compared with those without such a condition. However, none of these associations was statistically significant. Carotid IMT was associated with an increased prevalence of CTS; the odds ratio (OR) was only statistically significant for probable CTS (OR 1.7, 95% CI 1.1-2.6 for each standard deviation (0.23 mm) increase in IMT). Heart failure and arrhythmia were not associated with CTS. Subjects with coronary artery disease were less likely to be operated on for CTS than those without such a condition.
Table 3

Adjusted odds ratios (OR) of carpal tunnel syndrome (CTS) according to vascular disease and carotid intima-media thickness.

Cardiovascular disease

Sample

Possible and probable CTS combined

Probable CTS

Operated

  

Cases

OR

95% CI

Cases

OR

95% CI

Cases

OR

95% CI

Coronary artery disease

          

   No

5774

209

1

 

52

1

 

75

  

   Yes

480

34

1.3

0.7-2.2

10

1.5

0.6-3.4

4

0.3

0.1-0.9

Intermittent claudication

          

   No

6175

237

1

 

60

1

 

78

1

 

   Yes

79

6

1.4

0.5-3.6

2

2.1

0.4-9.0

1

0.4

0.1-2.7

Cerebrovascular disease

          

   No

6073

230

1

 

56

1

 

78

1

 

   Yes

181

13

1.2

0.5-2.4

6

2.4

0.8-7.1

1

0.3

0.1-2.3

Heart failure

          

   No

6126

230

1

 

59

1

 

77

1

 

   Yes

128

13

1.2

0.5-2.7

3

1.1

0.3-4.2

2

0.6

0.1-2.6

Arrhythmia

          

   No

5916

221

1

 

56

1

 

75

1

 

   Yes

338

22

1.0

0.6-1.8

6

1.2

0.4-3.4

4

0.6

0.2-1.9

Valvular heart disease

          

   No

6078

229

1

 

57

1

 

77

1

 

   Yes

176

14

1.6

0.7-3.4

5

2.3

0.7-6.4

2

0.7

0.1-3.2

Carotid intima-media thickness

          

Mean IMT, per each standard deviation (0.23 mm) increase

1353

55

1.3

0.99-1.8

14

1.7

1.1-2.6

16

1.4

0.9-2.2

A separate model was run for each characteristic and the odds ratios obtained were adjusted for age, sex, education, somatization, handgrip with high forces and work using vibrating tools

Figure 1

Age-specific prevalence of possible and probable carpal tunnel syndrome combined according to vascular disease (coronary artery disease, cerebrovascular disease, or intermittent claudication). The difference in prevalence between the two groups was statistically significant for the 50-59, 60-69 and 70-79 year age groups.

Age-specific analyses

Possible and probable CTS combined

BMI, waist-to-hip ratio, LDL cholesterol, triglycerides, hypertension, and arrhythmia were associated with possible and probable CTS combined in subjects aged 30-44 (Table 4). In the age group of 60 years or over, leisure-time physical activity, coronary artery disease, and valvular heart disease were associated with CTS. The association between current smoking and CTS was only statistically significant in subjects aged 45-59. Alcohol consumption, C-reactive protein, metabolic syndrome, and insulin resistance were not associated with CTS in any age group.
Table 4

Age-specific adjusted odds ratio of possible and probable carpal tunnel syndrome combined, Health 2000 survey, 2000-2001.

Characteristic

30-44 yrs (N = 2132)

45-59 yrs (N = 2190)

60+ yrs (N = 1932)

 

Sample

Cases

OR

95% CI

Sample

Cases

OR

95% CI

Sample

Cases

OR

95% CI

Smoking status

            

   Never smoker

522

9

1

 

593

29

1

 

947

46

1

 

   Former smoker

465

8

0.9

0.3-2.4

649

23

1.0

0.6-1.7

535

20

1.6

0.9-3.0

   Occasional smoker

194

3

0.8

0.2-3.2

105

6

1.8

0.6-4.8

34

0

-

 

   Current smoker

601

22

1.8

0.8-3.6

553

42

1.9

1.1-3.3

193

8

1.8

0.7-4.4

Exercise (times/week)

            

   ≤1

915

23

1

 

916

45

1

 

665

28

1

 

   2-3

775

16

0.8

0.4-1.6

717

35

1.0

0.6-1.7

481

17

1.2

0.6-2.4

   ≥ 4

427

9

0.9

0.4-1.8

526

27

1.1

0.6-1.8

668

33

1.7

1.0-2.7

Body mass index

            

   Normal

1065

18

1

 

815

34

1

 

634

30

1

 

   Overweight

688

15

1.4

0.7-2.7

848

43

1.1

0.6-1.8

752

24

0.7

0.4-1.3

   Obese

264

14

2.4

1.1-5.4

413

27

1.2

0.6-2.2

325

17

0.7

0.3-1.5

Waist circumference

            

   Normal

1015

18

1

 

617

26

1

 

387

15

1

 

   Increased

562

9

0.8

0.3-2.2

614

22

0.7

0.4-1.3

508

13

0.6

0.2-1.2

   Obese

535

22

1.5

0.8-2.9

954

62

0.9

0.5-1.6

1020

53

0.8

0.4-1.5

Waist-hip ratio

            

   Normal

484

4

1

 

281

11

1

 

157

9

1

 

   Increased

1271

32

2.7

0.9-7.8

1202

64

1.5

0.7-2.9

1081

39

0.5

0.2-1.2

   Obese

357

13

3.0

1.0-9.0

702

35

1.1

0.5-2.3

676

33

0.7

0.3-1.5

LDL cholesterol (mg/dL)

            

   <129

951

16

1

 

604

28

1

 

517

25

1

 

   130-189

973

23

1.6

0.8-3.2

1163

62

1.2

0.7-2.0

996

40

0.8

0.4-1.4

   ≥190

198

10

3.8

1.6-9.1

419

20

1.1

0.5-2.3

415

19

0.8

0.4-1.6

HDL cholesterol (mg/dL)

            

   >60

590

15

1

 

609

41

1

 

490

21

1

 

   40-60

1121

22

0.7

0.3-1.4

1129

52

0.7

0.4-1.2

957

45

1.2

0.6-2.1

   ≤40

411

12

1.3

0.6-2.9

448

17

0.6

0.3-1.0

481

18

1.0

0.4-2.2

Total cholesterol (mg/dL)

            

   >200

759

13

1

 

393

18

1

 

391

14

1

 

   200-239

797

16

1.1

0.4-2.5

785

44

1.3

0.6-2.5

624

31

1.6

0.7-3.4

   ≤240

566

20

2.3

0.97-5.5

1008

48

1.1

0.5-2.2

913

39

1.2

0.5-2.3

Triglycerides (mg/dL)

            

   ≤150

1562

32

1

 

1435

78

1

 

1189

53

1

 

   151-199

281

4

0.6

0.2-1.8

395

21

0.8

0.5-1.3

393

17

0.7

0.4-1.3

   >200

279

13

2.7

1.2-6.1

356

11

0.6

0.3-1.1

346

14

0.9

0.5-1.9

Hypertension

            

   No

2028

41

  

1748

83

  

1241

50

  

   Yes

104

8

3.4

1.6-7.4

442

27

1.0

0.6-1.7

691

34

1.0

0.6-1.5

Coronary artery disease

            

   No

2127

49

  

2141

107

  

1506

53

  

   Yes

5

0

-

-

49

3

1.2

0.3-3.8

426

31

1.9

1.1-3.5

Heart failure

            

   No

2131

49

  

2184

109

1

 

1811

72

1

 

   Yes

1

0

-

-

6

1

2.0

0.2-15.0

121

12

1.6

0.6-3.8

Arrhythmia

            

   No

2118

47

1

 

2118

103

1

 

1680

71

1

 

   Yes

14

2

10.2

2.7-38.4

72

7

1.6

0.6-3.8

252

13

0.8

0.4-1.8

Valvular heart disease

            

   No

2122

49

  

2161

108

  

1795

72

  

   Yes

10

0

-

-

29

2

1.0

0.2-4.8

137

12

2.3

1.0-5.0

Mean IMT, per each standard deviation (0.23 mm) increase

    

876

38

1.2

0.8-1.9

477

17

1.4

0.9-2.1

A separate model was run for each characteristic and the odds ratios obtained were adjusted for age, sex, education, somatization, handgrip with high forces and work using vibrating tools

Probable CTS

The results remained consistent using probable CTS as outcome. The prevalence of probable CTS increased two-fold (OR 2.1, 95% CI 1.4-3.1) for each standard deviation increase in IMT for subjects aged 60-74. The association was weak and non-significant among those aged 45-59 (OR 1.4, 95% CI 0.9-2.1). The prevalence of probable CTS was higher among subjects with vascular disease (coronary artery disease, cerebrovascular disease or intermittent claudication) aged 50 or over, and among subjects with hypertension aged 30-39 or over 70, compared with those without such a condition (data not shown).

Operated CTS

Metabolic syndrome, C-reactive protein, LDL and HDL cholesterol, and insulin resistance were associated with operated CTS only in subjects aged 45-59 (data not shown). BMI was associated with CTS among subjects aged 30-44 as well as among those aged 45-59. Former smoking and physical activity were associated with operated CTS among those aged 60 or over. Among subjects with hypertension, operated CTS had a bimodal age distribution with a first peak in those aged 50-59 and a second peak in those aged 70-79.

Gender-specific analyses

In gender-specific analyses, the associations of atherosclerosis risk factors with possible and probable CTS combined did not differ between men and women. After adjustment for potential confounders, carotid IMT was associated with possible and probable CTS combined (OR 1.7, 95% CI 1.1.2.6 for each 0.23 mm increase), probable CTS (OR 2.2, 95% CI 1.2-4.0), and operated CTS (OR 2.3, 95% CI 1.1-4.8) among men only.

Effect modification

In subjects aged 30-44, stratified analyses controlled for potential confounders showed that high LDL cholesterol, high triglycerides, hypertension, and insulin resistance were associated with CTS in overweight or obese subjects, but not in normal-weight subjects (Table 5). Mean BMI did not differ in overweight/obese subjects with an LDL of >130 vs. ≤129 (28.9 vs. 28.6 kg/m2). It was higher in overweight/obese subjects with triglycerides of >150 vs. <150 (29.6 vs. 28.2 kg/m2), overweight/obese subjects with vs. without hypertension (30.9 vs. 28.6 kg/m2), and in overweight/obese subjects with high vs. low insulin resistance (29.7 vs. 27.4 kg/m2). Among subjects aged 60 or over, the association of vascular disease with CTS was independent of BMI level.
Table 5

Odds ratio of possible and probable carpal tunnel syndrome combined for joint effects of body mass index and serum lipids or hypertension in subjects aged 30-44 (N = 2132)

Characteristic

Sample

Cases

OR

95% CI

BMI (kg/m2) and LDL cholesterol (mg/dL)

    

   BMI <25 and LDL cholesterol <129

550

8

1

 

   BMI ≥25 and LDL cholesterol <129

355

8

1.5

0.5-4.1

   BMI <25 and LDL cholesterol ≥130

532

10

1.2

0.4-3.3

   BMI ≥25 and LDL cholesterol ≥130

594

21

2.7

1.2-6.4

BMI (kg/m2) and triglycerides (mg/dL)

    

   BMI <25 and triglycerides ≤150

945

16

1

 

   BMI ≥25 and triglycerides ≤150

550

14

1.5

0.7-3.4

   BMI <25 and triglycerides >150

137

2

0.9

0.2-4.7

   BMI ≥25 and triglycerides >150

399

15

2.9

1.3-6.4

BMI (kg/m2) and blood pressure

    

   BMI <25 and normal blood pressure

1062

17

1

 

   BMI ≥25 and normal blood pressure

881

23

1.8

0.9-3.4

   BMI <25 and high blood pressure

27

1

2.2

0.2-19.0

   BMI ≥25 and high blood pressure

71

6

5.9

2.1-16.3

BMI (kg/m2) and insulin resistance *

    

   BMI <25 and low insulin resistance

1819

55

1

 

   BMI ≥25 and low insulin resistance

1057

42

1.5

0.6-3.2

   BMI <25 and high insulin resistance

745

27

0.6

0.2-2.0

   BMI ≥25 and high insulin resistance

2225

98

2.1

1.1-4.0

* Insulin resistance (serum insulin × glucose/22.5) was dichotomized using the median

Odds ratios are adjusted for age, sex, education, handgrip with high forces and work using vibrating tools

After adjustment for age, gender and education, carotid IMT was only associated with possible and probable CTS combined in subjects with hypertension (OR 1.6, 95% CI 1.1-2.4 for each 0.23 mm increase in IMT), and not in those with normal blood pressure. This association did not differ between men (OR 1.6, 95% CI 0.9-2.6) and women (OR 1.6, 95% CI 0.8-2.8). Furthermore, carotid IMT was associated with possible and probable CTS combined only in subjects with vascular disease (coronary artery disease, intermittent claudication or cerebrovascular disease) (OR 2.1, 95% CI 1.1-4.0). Finally, carotid IMT was associated with CTS only among subjects who were exposed to physical workload factors (Table 6). The odds ratio was 1.5 (95% CI 1.0 -2.2) for subjects exposed to handgrip with high forces, 2.1 (95% CI 1.2-3.7) for those exposed to manual handling of loads over 20 kg, and 2.6 (95% CI 1.4-4.8) for subjects exposed to both high handgrip forces and manual handling of loads over 20 kg.
Table 6

Odds ratio of possible and probable carpal tunnel syndrome combined for each standard deviation (0.23 mm) increase in mean carotid intima-media thickness according to exposure to physical workload factors in subjects aged 45-74.

Physical workload factor

Sample

Cases

OR *

95% CI

Handgrip with high forces

    

   No

979

26

1.1

0.6-1.7

   Yes

363

29

1.5

1.0-2.2

Manual handling of loads >20 kg

    

   No

1091

39

1.1

0.7-1.6

   Yes

253

16

2.1

1.2-3.7

Use of vibrating tools

    

   No

1233

49

1.3

0.9-1.8

   Yes

111

6

1.4

0.7-2.5

Handgrip with high forces and handling of loads >20 kg

    

   None

908

25

1.1

0.7-1.8

   Only handgrip with high forces

182

14

1.1

0.5-2.0

   Only handling of loads >20 kg

71

1

-

-

   Both

181

15

2.6

1.4-4.8

* Adjustment for age, gender and education

There was no interaction between smoking and obesity, between smoking and physical workload factors, and between obesity and physical workload factors.

Discussion

Our findings showed that obesity, dyslipidemia, and hypertension are associated with CTS in people aged 30-44, while coronary artery disease and carotid IMT are associated with CTS in those aged 60 or over. An association between carotid IMT and CTS was found only in subjects exposed to physical load factors and in those with hypertension or atherosclerotic disease. Our study [10] is in line with other studies [4, 5] showing a bimodal age distribution for CTS among men [4, 5] and women [4], which may partly be due to atherosclerosis and its risk factors.

The aetiology of CTS is multifactorial. Some studies have shown associations between cardiovascular risk factors such as obesity, smoking, LDL cholesterol and metabolic syndrome, and CTS [16, 17, 2327]. We found associations of atherosclerosis risk factors with CTS in young adults. Other studies [24, 34] have also reported a stronger association of obesity with CTS in younger than older subjects. Overweight/obesity with hypertension or metabolic disturbances such as dyslipidemia and insulin resistance may play a role in CTS among young adults. Subjects with hypertension or dyslipidemia are more likely to have a higher BMI than those with normal blood pressure or normal serum lipid levels. Moreover, for women, hormonal factors may also play a role in CTS [8]. Therefore, the associations of hypertension, LDL cholesterol and triglycerides with CTS could be confounded by BMI, oral contraceptive use, or hormone replacement therapy. However, in the current study, after further adjustment for BMI (both in total population and in women) and history of oral contraceptive use or hormone replacement therapy (in women), these associations remained statistically significant in subjects aged 30-44 (data not shown). The use of oral contraceptives only slightly attenuated the association between triglycerides and CTS.

So far, there is no strong evidence to support an association between atherosclerosis and CTS. Carotid artery IMT is used as a surrogate marker of early atherosclerosis or a measure of asymptomatic atherosclerotic vascular disease [35]. We found a stronger association of carotid IMT with CTS in older than younger subjects. This may be due to the fact that atherosclerosis was more advanced among subjects aged 60-74 (Mean IMT 1.06, SD 0.25) than among those aged 45-59 (Mean IMT 0.87, SD 0.18). Moreover, there was an association between carotid IMT and CTS only in subjects with atherosclerotic vascular disease or in those exposed to physical load factors. In subjects with vascular disease, carotid IMT may also be associated with obliterative changes in arteries supplying the carpal tunnel contents. Impairment of vascular supply could render the median nerve more vulnerable to mechanical loads.

Ischemic endothelial damage leads to increased vascular permeability and increased interstitial fluid pressure [11, 12]. This may render the median nerve vulnerable to damage especially when the oxygen demands of the carpal tunnel contents due to physical stress are increased. The ischemia of the median nerve produces neuronal edema and subsequently leads to intraneural fibrosis. The association between carotid IMT and CTS in those suffering from vascular disease may be related to the severity of such a disease. In other analyses, we found that subjects with a thicker carotid intima-media have several coexisting vascular diseases or risk factors (data not shown).

The advantages of the current study include a population-based sample with a high response rate, face-to-face interviews, comprehensive physical examinations, laboratory tests, and the advanced imaging method. The study population was interviewed on two separate occasions and by different interviewers in order to gather information on both exposure history and musculoskeletal symptoms. Therefore, those who assessed exposures were not aware of musculoskeletal symptoms [28]. The limitations of this study are its cross-sectional nature and its reliance on CTS diagnosed primarily by physical examination. We did not use nerve conduction studies to confirm the diagnosis of CTS. Considering nerve conduction studies as a golden standard test, a combination of a classic/probable hand diagram and either a positive Tinel's or Phalen's test result can correctly diagnose 79% of CTS cases [36]. Our prevalence estimate (3.8%) was also close to those obtained in a Swedish population-based study [1] through a clinical examination (3.8%) or electrodiagnostic measurements (4.9%).

The results of subgroup analyses should be interpreted cautiously, as the sample size was relatively small. Some of the observed associations, however, are less likely to be due to chance. Most of the common atherosclerosis risk factors were associated with CTS among young subjects. Moreover, after correcting for multiple testing (Bonferroni correction), the associations of high LDL cholesterol, hypertension and cardiac arrhythmia with CTS remained statistically significant in subjects aged 30-44. In those aged 45-74, the joint effect of forceful activities and thick carotid intima-media remained statistically significant. Furthermore, other comorbid conditions such as cancer, psychosis, osteoporosis, allergy, dementia and a chronic illness or inflammation of the bowel were not associated with CTS.

Conclusions

The current study may support the role of atherosclerosis and its risk factors in the aetiology of CTS. Of the two peaks in the age-specific prevalence of CTS, the first, occurring after the age of 40, may largely be due to work-related factors and the risk factors of atherosclerosis. The second peak in those aged 70 or over [4, 5, 10], may be explained by ischemic vascular disease and atherosclerosis. Our findings suggest that CTS may be a manifestation of atherosclerosis, or that both conditions may have common risk factors. Therefore, effective population-level health promotion activities against cardiovascular risk factors may reduce the risk not only of atherosclerosis and vascular diseases, but also of CTS.

Conflict of interests

The authors declare that they have no competing interests.

Declarations

Authors’ Affiliations

(1)
Centre of Expertise for Health and Work Ability, Finnish Institute of Occupational Health, Helsinki, Finland
(2)
Department of Health and Functional Capacity, National Institute for Health and Welfare, Helsinki, Finland
(3)
Department of Medicine, Kuopio University Hospital, and University of Kuopio, Kuopio, Finland
(4)
Department of Medicine, University of Turku, and Turku University Hospital, Turku, Finland
(5)
Unit of General Practice, Helsinki University Central Hospital, University of Helsinki, Helsinki, Finland
(6)
Kirkkonummi Health Centre, Kirkkonummi, Finland

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  37. Pre-publication history

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© Shiri et al; licensee BioMed Central Ltd. 2011

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.

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