Abstract
We examined the distribution of quantitative heel ultrasound (QUS) parameters in population samples of European men, and looked at the influence of lifestyle factors on the occurrence of these parameters.
Men aged between 40 and 79 years were recruited from eight European centres and invited to attend for an interviewer-assisted questionnaire, assessment of physical performance and quantitative ultrasound (QUS) of the calcaneus (Hologic - SAHARA). The relationships between QUS parameters and lifestyle variables were assessed using linear regression with adjustments for age, centre and weight.
3,258 men, mean age 60.0 years were included in the analysis. A higher PASE score (upper vs lower tertile) was associated with higher BUA (β coefficient = 2.44 dB/Mhz), SOS (β coefficient = 6.83 m/s) and QUI (β coefficient = 3.87). Compared to those who were inactive, those who walked or cycled more than an hour per day had a higher BUA (β coeff =3.71 dB/Mhz), SOS (β coeff = 6.97 m/s) and QUI (β coeff = 4.50). A longer time to walk 50 feet was linked with lower BUA (β coeff = −0.62 dB/Mhz), SOS (β coeff = −1.06 m/s) and QUI (β coeff = −0.69). Smoking was associated with a reduction in BUA, SOS and QUI. There was a U shaped association with frequency of alcohol consumption.
Modification of lifestyle, including increasing physical activity and stopping smoking may help optimise bone strength and reduce the risk of fracture in middle aged and elderly European men.
Keywords: Epidemiology, Ultrasound, Bone mineral density, Risk factors, Exercise
INTRODUCTION
Quantitative heel ultrasound (QUS) measurements at the heel have been shown to be associated with risk of spine and non spine fracture in men and women [1-9]. The strength of prediction has been reported to be at least as strong as that for bone mineral density (BMDa) measurements assessed using dual energy x-ray absorptiometry (DXA) and, to be independent of DXA BMDa. There is evidence that fracture rates in men and women vary across Europe with rates higher in northern than southern Europe [10,11]. Whether or not such geographic variation can be explained by variation in the level of ultrasound parameters in these populations is unknown. Furthermore, compared to data using DXA, relatively less is known about the lifestyle factors which influence heel ultrasound parameters in men. There is some evidence that physical activity and smoking may influence heel ultrasound broadband ultrasound attenuation (BUA) and speed of sound (SOS) in men, however, the findings are not always consistent [12-20]. Such data are important - knowledge of risk factors is the first step in the development of effective population wide strategies to optimise bone health.
The European Male Ageing Study is a multicentre population based study of ageing in men aged 40 to 79 years. We used data from the study to determine the distribution of ultrasound parameters BUA, SOS and the derived quantitative ultrasound index (QUI) across different European populations, and to explore the association between lifestyle factors and these parameters.
METHODS
Subjects
The subjects included in this analysis were recruited for participation in the European Male Ageing Study. Men were recruited from population based sampling frames in 8 centres: Florence (Italy), Leuven (Belgium), Lodz (Poland), Malmo (Sweden), Manchester (UK) Santiago del Compostella (Spain), Szeged (Hungary), Tartu (Estonia). Details regarding recruitment, response rates and assessments have been described previously [21]. Participating centres were selected to provide geographical and socioeconomic diversity within Europe, and facilities to perform epidemiological surveys. Stratified random sampling was performed in each centre with the aim of recruiting one hundred men in each of four 10-year age bands: 40-49 years, 50-59 years, 60-69 years, and 70-79 years. Subjects were invited by letter to complete a postal questionnaire and attend for an interviewer-assisted questionnaire, assessment of physical performance and ultrasound of the heel. Subjects were recontacted usually within 4 weeks if they did not reply following a first letter. Ethical approval for the study was obtained in accordance with local institutional requirements in each centre.
Assessments
The postal questionnaire included questions concerning time spent walking or on a bicycle out of doors each day (response set = none / less than 30 minutes / 30 minutes to 1 hour / more than 1 hour), smoking - both ever and currently, alcohol consumption in the previous year (response set = every day / 5-6 days per week / 3-4 days per week / 1-2 days per week / less than once a week / not at all). There was a question also about prior fracture since the age of 25 years (response set = no / yes / don’t know). The main study questionnaire included the physical activity scale for the elderly (PASE) and the SF36 quality of life questionnaire [22, 23]. Subjects were asked also whether they were currently being treated for any of a list of fourteen morbidities: heart conditions, high blood pressure, pituitary disease, testicular disease, chronic bronchitis, asthma, peptic ulcer, epilepsy, diabetes, liver conditions, kidney conditions, prostate disease, adrenal disease, thyroid disease. A number of performance measures were undertaken including the Tinetti assessment of balance and gait which included the time taken to sit to stand five times, and also the time taken to walk 50 feet [24, 25]. In addition, height and weight were measured in a standardised fashion.
Quantitative heel ultrasound
Quantitative ultrasound of the heel was performed using the Sahara Clinical Sonometer (Hologic, Bedford, Massachusetts) using a standardised protocol. Each centre used the same machine model, and each calibrated daily with the physical phantom provided by the manufacturer. Outputs included broadband ultrasound attenuation (BUA) and speed of sound (SOS). In addition, machine derived parameters were quantitative ultrasound index (QUI), a measure of stiffness: QUI = 0.41(SOS) + 0.41(BUA) − 571 and estimated heel bone mineral density (eBMD) in g/cm2, eBMD = 0.002592 × (BUA+SOS) − 3.687. Quality control (QC) was performed in each centre as per manufacturers instructions. All QC results were sent to Leuven and compiled and checked for stability throughout the study. To establish the short-term precision of the method in this population, duplicate measurements were performed in 20 randomly selected cohort members in one of the centres (Leuven, Belgium). The in vivo coefficient of variations (CV) were 2.8% and 0.3% for BUA and SOS, respectively, and 2.3% and 3.4% for QUI and eBMD, respectively. Repeat measurements (10) were performed on a roving phantom at each of the eight centres. Standardised CVs (SCVs) [26] for within machine variability ranged by centre: for SOS, from 1.0% to 5.6%, and BUA from 0.7% to 2.7%. SCVs for between machine variability were 4.8% for BUA and 9.7% for SOS.
Analysis
Descriptive statistics were used to characterize the distribution of the heel ultrasound parameters (BUA, SOS, QUI and eBMD) by age and centre. In the analysis of risk factors PASE & SF36 physical component score (PCS) were categorized into tertiles. We grouped comorbidities by number (none, one, two or more) though we looked also separately at the more frequent individual comorbidities including heart disease, hypertension, cardiovascular disease, bronchitis, diabetes and prostate disease. Body mass index (BMI) was calculated by dividing weight (Kgs) by height squared (m2).
Linear regression was used to determine the association between each of the measured ultrasound parameters and also QUI, and the various putative risk factors (including age) with the ultrasound parameters as the dependent variables. The results are expressed as absolute differences (β coefficients) and 95% confidence intervals (CI). Adjustments were made initially for age, weight and centre. A multivariable analysis was then performed with statistical models including all the lifestyle factors that were significantly associated with the QUS parameters, and age, weight and centre. We looked also at the association between prior fracture and the ultrasound parameters. Statistical analysis was performed using STATA version 9.2.
RESULTS
Subjects
A total of 3,258 men with a mean age of 60.0 years (SD=11.0) had QUS measurements performed. There were 772 men aged 40-49 years, 874 aged 50-59 years, 816 aged 60-69 years and 796 over 70 years. The number of men in each centre ranged from 388 to 427. Characteristics of the subjects are shown in Table 1. Mean BMI was 27.6 kg/m2 (SD=4.0), PASE score 196.2 (SD=91.7) and SF36 physical score 50.0 (SD=8.2). 65% of subjects reported walking or cycling for more than 1/2 hour per day. 70% reported having ever smoked, with 21% reporting that they currently smoke. 56% of the men reported consuming alcohol at least one day per week. 23% reported two or more comorbidities and 26% reported a previous fracture. Mean BUA was 80.2 dB/MHz, SOS 1550.7 m/s, and the derived indices, eBMD 0.542 g/cm2 and QUI 97.7. Characteristics of the subjects by centre are shown in Table 2. There were significant differences in weight, PASE score, SF36 physical score, time taken to go from a sitting to a standing position, time taken to walk 50 feet, time spent walking / cycling, smoking status, alcohol consumption, number of comorbidities and self reported previous fracture by centre.
Table 1. Subject characteristics.
| Variable | N=3,258 |
|---|---|
| Mean (SD) | |
| Age at interview (years) | 60.0 (11.0) |
| Height (cm) | 173.6 (7.3) |
| Weight (kg) | 83.3 (13.7) |
| Body mass index (kg/m2) | 27.6 (4.0) |
| PASE score (0-1100) | 196.2 (91.7) |
| SF36 Physical score (0-100) | 50.0 (8.2) |
| Tinetti: time taken from sitting to standing (s) | 12.7 (4.2) |
| PPT: time taken to walk 50 feet (s) | 13.6 (3.4) |
| Broadband ultrasound attenuation (dB/MHz) | 80.2 (19.0) |
| Speed of sound (m/s) | 1550.7 (34.1) |
| Bone mineral density (g/cm2) | 0.542 (0.137) |
| Quantitative ultrasound index | 97.7 (21.2) |
| % | |
| Walking or cycling for ½ hour or more / day | 65.3 |
| Ever smoked (yes vs no) | 70.1 |
| Currently smoke (yes vs no) | 21.0 |
| Alcohol consumption ≥ 1day / week | 56.2 |
| Comorbidities: None | 49.8 |
| One | 27.7 |
| Two or more | 22.6 |
| Previous fracture since 25 (yes vs no) | 25.9 |
Table 2. Subject characteristics by centre.
| Overall | North/West |
East |
South |
|||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Leuven | Malmo | Manchester | Lodz | Szeged | Tartu | Florence | Santiago | |||
| Mean (SD) | P valuea | |||||||||
| Weight (kg) | 83.3 (13.7) | 82.1 (13.0) | 85.4 (13.2) | 84.1 (13.3) | 82.1 (12.8) | 86.5 (14.2) | 87.2 (16.2) | 79.7 (13.3) | 79.8 (11.5) | <0.001 |
| PASE score (0-1100) | 196.2 (91.7) | 191.7 (86.7) | 180.3 (80.1) | 219.6 (84.0) | 181.5 (93.6) | 252.6 (96.2) | 204.0 (84.8) | 155.3 (76.3) | 184.0 (95.6) | <0.001 |
| SF36 Physical score (0-100) | 50.0 (8.2) | 50.0 (7.9) | 51.8 (7.7) | 51.2 (7.6) | 47.9 (8.3) | 49.8 (8.4) | 45.6 (9.7) | 52.6 (6.1) | 51.3 (6.9) | <0.001 |
| Tinetti: time taken from sitting to standing (s) | 12.7 (4.2) | 12.9 (3.3) | 13.4 (5.8) | 12.0 (3.2) | 12.9 (6.1) | 11.7 (3.2) | 13.5 (4.0) | 10.7 (2.6) | 14.4 (3.1) | <0.001 |
| PPT: time taken to walk 50 feet (s) | 13.6 (3.4) | 13.7 (2.3) | 13.4 (3.1) | 13.9 (3.0) | 14.2 (3.4) | 13.8 (3.3) | 14.6 (3.9) | 10.5 (1.9) | 14.7 (3.8) | <0.001 |
| % | ||||||||||
| Walking or cycling for ½ hour or more / day | 65.3 | 47.7 | 78.9 | 65.1 | 70.9 | 76.1 | 63.7 | 54.1 | 67.6 | <0.001 |
| Ever smoked (yes vs no) | 70.1 | 64.4 | 68.8 | 56.6 | 82.1 | 64.9 | 74.5 | 77.1 | 72.5 | <0.001 |
| Currently smoke (yes vs no) | 21.0 | 17.2 | 16.5 | 11.4 | 25.7 | 21.3 | 29.2 | 23.1 | 23.0 | <0.001 |
| Alcohol consumption ≥ 1day/week | 56.2 | 73.3 | 64.7 | 76.7 | 23.7 | 56.7 | 31.3 | 54.3 | 68.0 | <0.001 |
| At least one comorbidity | 50.3 | 46.1 | 38.6 | 39.0 | 66.7 | 58.9 | 48.7 | 50.5 | 52.9 | <0.001 |
| Previous fracture since 25 (yes vs no) | 25.9 | 22.6 | 21.3 | 25.0 | 26.6 | 30.6 | 35.8 | 22.7 | 22.5 | <0.001 |
Test for differences between centres. ANOVA for continuous, chi-squared test for dichotomous measures
22
Associations with age, centre and previous fracture
There were significant differences in the measured parameters BUA and SOS and the derived parameter QUI by centre, see Table 3. BUA was lowest in Szeged, Hungary and highest in Manchester, UK (70.4dB/MHz vs 87.7dB/MHz), as was QUI (90.4 vs 104.9). SOS values were lowest in Florence, Italy and highest in Leuven, Belgium (1542.5m/s vs 1561.2m/s). There was no evidence of any consistent geographic trend towards higher or lower levels in northwestern (Leuven, Malmo, Manchester), southern (Florence, Santiago) or eastern Europe (Lodz, Tartu, Szeged). The variation by centre was similar in those aged above and below 65 years. There was an apparent decline in BUA, SOS and QUI with age, see Figures 1-3, though given the cross-sectional nature of the data this needs to be interpreted with some caution. There was no evidence of any significant age centre interaction for BUA (p value= 0.49), SOS (p value= 0.24) or QUI (p value = 0.33). After adjustment for age, an increase in weight was significantly associated with an increase in all three QUS parameters: BUA (β coefficient=0.21 dB/Mhz), SOS (β coefficient=0.17 m/s) and QUI (β coefficient=0.16). Significant centre differences in the ultrasound parameters persisted after adjustment for age, weight and also number and type of comorbidities. Also after further adjustment for frequency of alcohol intake, smoking and physical activity. After adjustment for age, weight and centre, compared to those without, those with a history of self reported fracture since age 25 years had significantly lower ultrasound values: BUA (β coefficient= −5.4 dB/Mhz), SOS (β coefficient= −10.4 m/s) and QUI (β coefficient= −6.5).
Table 3. Quantitative ultrasound parameters by centre.
| Region | Centre | n | Broadband Attenuation (dB/MHz) mean (SD) |
Speed of Sound (m/s) mean (SD) |
Quantitative Ultrasound Index mean (SD) |
|---|---|---|---|---|---|
| North/West | Leuven | 424 | 82.4 (18.3) | 1561.2 (32.9) | 102.9 (20.5) |
| Malmo | 389 | 81.4 (16.4) | 1549.3 (29.8) | 97.5 (18.2) | |
| Manchester | 388 | 87.7 (17.1) | 1560.8 (34.5) | 104.9 (20.6) | |
| East | Lodz | 403 | 79.9 (18.4) | 1547.1 (32.6) | 96.1 (20.3) |
| Szeged | 425 | 70.4 (19.0) | 1542.7 (30.1) | 90.4 (19.7) | |
| Tartu | 397 | 79.3 (17.9) | 1544.5 (33.6) | 94.8 (20.7) | |
| South | Florence | 427 | 77.0 (17.6) | 1542.5 (32.6) | 93.0 (20.0) |
| Santiago | 405 | 84.1 (21.5) | 1557.7 (39.5) | 102.3 (24.5) |
Figure 1. Association between broadband ultrasound attenuation (BUA) and age.
Figure 2. Association between speed of sound (SOS) and age.
Figure 3. Association between quantitative ultrasound index (QUI) and age.
Association with lifestyle factors
The association between SOS, BUA and QUI and lifestyle factors is shown in Table 4. The major finding was that increasing levels of physical activity were associated with an increase in all three QUS parameters. After adjustment for age, weight and centre, compared to those in the lowest tertile of PASE score, those in the upper tertile had an increased BUA (β coefficient= 2.44 dB/Mhz), SOS (β coefficient=6.83 m/s) and QUI (β coefficient=3.87). Similarly, compared to those who did no walking or cycling, those that walked or cycled for more than 1 hour per day had an increased BUA (β coefficient=3.71 dB/MHz), SOS (β coefficient=6.97 m/s) and QUI (β coefficient=4.50). A longer time taken to perform sitting to standing (five times) was associated with a reduced BUA (β coefficient = −0.19 dB/MHz), SOS (β coefficient= −0.53 m/s) and QUI (β coefficient= −0.29), as was a longer time taken to walk 50 feet (β coefficient = −0.62 dB/MHz, −1.06 m/s and −0.69 for BUA, SOS and QUI respectively). Compared to those in the lowest tertile of SF36 physical component score, those in the upper tertile had an increased BUA (β coefficient= 2.80 dB/MHz), SOS (β coefficient=5.75 m/s) and QUI (β coefficient=3.44). Further adjustment for individual comorbid conditions (heart disease, hypertension, cardiovascular disease, bronchitis, diabetes, prostate disease) or by number of comorbidities did not attenuate the association between QUS parameters and the physical activity measures suggesting the association is not explained by the presence of underlying comorbid disease.
Table 4. Influence of lifestyle factors on ultrasound parameters (with adjustments for age, centre and weight).
| Broadband Attenuation (dB/Mhz) | Speed of Sound (m/s) | Quantitative Ultrasound Index | |
|---|---|---|---|
| β co-efficient1 (95% CI) | β co-efficient1 (95% CI) | β co-efficient1 (95% CI) | |
| Ever smoked (yes vs no) | −4.551 (−5.923, −3.179)* | −10.319 (−12.811, −7.826)* | −6.007 (−7.553, −4.461)* |
| Current smoker (yes vs no) | −4.959 (−6.517, −3.401)* | −11.444 (−14.277, −8.611)* | −6.565 (−8.322, −4.809)* |
| Alcohol consumption (days/week) | |||
| None | −3.186 (−5.292, −1.081)* | −4.923 (−8.770, −1.076)* | −3.427 (−5.809, −1.046)* |
| < 1 | −0.950 (−2.798, 0.898) | −2.029 (−5.406, 1.348) | −1.337 (−3.427, 0.753) |
| 1-2 | Referent | Referent | Referent |
| 3-4 | −2.318 (−4.545, −0.091)* | −4.705 (−8.774, −0.635)* | −2.976 (−5.495, −0.457)* |
| 5-6 | −2.870 (−5.600, −0.140)* | −5.383 (−10.371, −0.395)* | −3.469 (−6.557, −0.382)* |
| Every day | −3.730 (−5.876, −1.584)* | −7.631 (−11.551, −3.710)* | −4.733 (−7.159, −2.306)* |
| PASE score per 100 (0-1100) | 1.547 (0.727, 2.366)* | 3.727 (2.237, 5.218)* | 2.197 (1.273, 3.121)* |
| PASE score: tertiles | |||
| Lower | Referent | Referent | Referent |
| Mid | 1.983 (0.326, 3.641)* | 4.659 (1.645, 7.674)* | 2.837 (0.968, 4.705)* |
| Upper | 2.442 (0.604, 4.281)* | 6.829 (3.484, 10.173)* | 3.865 (1.792, 5.938)* |
| Walking or cycling/day | |||
| None | Referent | Referent | Referent |
| < ½ hour | 3.046 (0.827, 5.264)* | 5.298 (1.248, 9.348)* | 3.509 (1.002, 6.016)* |
| ½ hour – 1 hour | 3.042 (0.946, 5.138)* | 5.835 (2.008, 9.662)* | 3.850 (1.481, 6.220)* |
| > 1hour | 3.711 (1.539, 5.883)* | 6.972 (3.006, 10.938)* | 4.500 (2.045, 6.955)* |
| Walking or cycling (<1/2 hour vs ≥1/2 hour) | 1.355 (−0.017, 2.727) | 2.890 (0.385, 5.395)* | 1.856 (0.305, 3.407)* |
| Tinetti: time taken from sitting to standing (s) | −0.187 (−0.343, −0.030)* | −0.526 (−0.811, −0.241)* | −0.294 (−0.470, −0.117)* |
| PPT: time taken to walk 50 feet (s) | −0.615 (−0.825, −0.404)* | −1.056 (−1.439, −0.672)* | −0.690 (−0.927, −0.452)* |
| SF36 physical component score (0-100) | 0.261 (0.177, 0.345)* | 0.503 (0.350, 0.656)* | 0.312 (0.218, 0.407)* |
| SF36 physical component score: tertiles | |||
| Lower | Referent | Referent | Referent |
| Mid | 2.995 (1.407, 4.584)* | 5.300 (2.409, 8.191)* | 3.435 (1.643, 5.227)* |
| Upper | 2.796 (1.139, 4.452)* | 5.754 (2.739, 8.769)* | 3.440 (1.571, 5.309)* |
p<0.05
adjusted for age, centre and weight
Other lifestyle factors were associated with the ultrasound parameters. After adjustment for age, centre and weight, compared to those that have never smoked, those who ever smoked had a lower BUA (β coefficient=−4.55 dB/MHz), SOS (β coefficient = −10.32 m/s) and QUI (β coefficient= −6.01). Similarly, those who currently smoke had a lower BUA (β coefficient =−4.96 dB/MHz), SOS (β coefficient= −11.44 m/s) and QUI (β coefficient=−6.57). There was a U shaped association with frequency of alcohol consumption. Compared to those who drank 1-2 times per week, those who did not drink at all had a lower BUA (β coefficient =−3.19 dB/MHz), SOS (β coefficient= −4.92 m/s) and QUI (β coefficient=−3.43). Also, compared to those who drank 1-2 times per week, those who consumed alcohol every day had a lower BUA (β coefficient =−3.73 dB/MHz), SOS (β coefficient= −7.63 m/s) and QUI (β coefficient=−4.73). Further adjustment for individual comorbid conditions (heart disease, hypertension, cardiovascular disease, bronchitis, diabetes, prostate disease) or number of comorbidities did not attenuate the association between QUS parameters and smoking (ever or current) or alcohol consumption.
When all the lifestyle factors that were associated with the ultrasound parameters were included in a multivariable model, BUA remained positively associated with measures of physical activity including time spent walking or cycling and SF36 physical score, and negatively associated with time taken to walk 50 feet, current smoking and alcohol consumption, see Table 5. Similarly, SOS and QUI remained positively associated with PASE score, time spent walking or cycling and SF36 physical score, and negatively associated with time taken to walk 50 feet, current smoking and alcohol consumption.
Table 5. Influence of lifestyle factors on ultrasound parameters (with adjustments for age, centre, weight, and other lifestyle variables in model).
| Broadband Attenuation (dB/Mhz) | Speed of Sound (m/s) | Quantitative Ultrasound Index | |
|---|---|---|---|
| β co-efficient1 (95% CI) | β co-efficient1 (95% CI) | β co-efficient1 (95% CI) | |
| Current smoker (yes vs no) | −4.613 (−6.255, −2.971)* | −10.399 (−13.372, −7.426)* | −5.974 (−7.819, −4.130)* |
| Alcohol consumption (days / week) | |||
| None | −2.105 (−4.303, 0.094) | −2.621 (−6.601, 1.359) | −2.043 (−4.512, 0.426) |
| < 1 | −0.059 (−1.988, 1.869) | −0.537 (−4.029, 2.954) | −0.338 (−2.504, 1.828) |
| 1-2 | Referent | Referent | Referent |
| 3-4 | −2.034 (−4.328, 0.260) | −4.551 (−8.704, −0.397)* | −2.836 (−5.413, −0.260)* |
| 5-6 | −2.219 (−5.045, 0.606) | −4.387 (−9.504, 0.729) | −2.819 (−5.993, 0.355) |
| Every day | −3.162 (−5.386, −0.937)* | −6.265 (−10.293, −2.238)* | −3.955 (−6.454, −1.456)* |
| PASE score per 100 (0-1100) | 0.692 (−0.174, 1.557) | 2.066 (0.499, 3.633)* | 1.176 (0.204, 2.148)* |
| Walking or cycling / day | |||
| None | Referent | Referent | Referent |
| <½ hour | 2.549 (0.245, 4.853)* | 4.690 (0.519, 8.861)* | 3.082 (0.495, 5.670)* |
| ½hour – 1 hour | 2.101 (−0.092, 4.293) | 3.698 (−0.272, 7.668) | 2.612 (0.149, 5.075)* |
| > 1hour | 2.123 (−0.173, 4.419) | 3.490 (−0.667, 7.648) | 2.467 (−0.112, 5.046) |
| Tinetti: time taken from sitting to standing (s) | 0.039 (−0.132, 0.210) | −0.121 (−0.430, 0.189) | −0.037 (−0.229, 0.155) |
| PPT: time taken to walk 50 feet (s) | −0.608 (−0.878, −0.337)* | −0.832 (−1.322, −0.343)* | −0.596 (−0.900, −0.293)* |
| SF36 physical component score (0-100) | 0.173 (0.078, 0.268)* | 0.343 (0.171, 0.515)* | 0.208 (0.101, 0.315)* |
p<0.05
adjusted for age, centre, weight, and other lifestyle variables in model
DISCUSSION
In this population survey, there was evidence of variation in levels of measured heel ultrasound parameters, BUA, SOS and also QUI across Europe. The ultrasound parameters decreased with age with no evidence, however, of any important age centre interaction. Increased levels of physical activity, and physical performance were associated with higher BUA and SOS while smoking was associated with lower values. There was a U shaped association with frequency of alcohol intake.
Our study was population based, and used standardised methods in assessment of QUS and of lifestyle and other characteristics. There are, however, limitations which need to be considered when interpreting the results. The overall response rate for participation was 45%. It is possible that those invited but who did not take part may have differed with respect to levels of the ultrasound parameters. Assessment for possible response bias requires some auxiliary data about non-responders. In EMAS a sample of non-responders was contacted by telephone and invited to complete a short survey. Compared to EMAS participants, those who took part in the telephone survey (n = 361) were more likely to be current smokers (33 vs. 21%; p < 0.001). No differences were found, however, in general health, time spent walking or cycling per day, or the proportion who had ever smoked [21]. While some caution is needed in interpreting the data, factors influencing participation are unlikely to have influenced the results of the risk factor analysis which was based on an internal comparison of those who participated. Questionnaires and other instruments used in the study were translated from English into the seven European languages in which their use was intended. Given concerns that subtle differences in the translation process may have influenced questionnaire responses, the questionnaire was back-translated by language experts from the relevant European language back into English. Given that the subjects were unaware of their bone ultrasound measurement results, any misclassification related to questionnaire response is likely, however, to be random and therefore would tend to reduce the likelihood of finding significant biological associations. There are no published methods for cross-calibration of QUS [27] and the results reported are the data as obtained at each centre. Any errors related to measurement, however, are likely to be non-directional and would tend to reduce the risk of finding significant biological associations. Given the cross-sectional design of the study it is not possible to determine the temporal nature of the observed relationships, for which prospective data are needed, although it seems unlikely that lower ultrasound parameters would lead to a reduction in levels of physical activity. Finally, the study was based on assessment of middle aged and elderly European men and extrapolation beyond this group should be undertaken with caution.
In the analyses there was variation in the distribution of the ultrasound parameters across Europe. There was no consistent geographic pattern towards higher or lower levels in northern or southern Europe. There is evidence from epidemiological studies that fracture rates are higher in Scandinavia than elsewhere in Europe [10,11], however, in our study mean BUA and SOS in Malmo, Sweden, were close to the average in these European men. As discussed, however, we did not undertake any cross-calibration and some caution is required in interpreting this data. Our data show a decline in bone ultrasound parameters with age with no evidence of any important centre difference in the rate of decline. Over the four decade span of those who participated, the average annual decline amounted to 0.16% for BUA, 0.03% for SOS and 0.23% for QUI. In an observational study of 1,138 Spanish men aged 18-99, using the same measurement device, the QUS parameters declined by between 0.08 and 0.41% per year [28]. A decrease in the parameters with age has been observed using other sonometers [17,19,29-32].
In our study physical activity was positively associated with the bone ultrasound parameters. The activity measures which we studied, however, primarily assessed the amount or volume of activity rather than loading, which may be more important to bone health. Most, though not all, studies which have examined the impact of physical activity on heel ultrasound parameters in men suggest a beneficial effect [12-20]. In one of the largest studies of 4981 men, aged 60-80 years, recalled physical activity was linked with increased QUI as measured using a Lunar Achilles device [17]. Most studies though have focused on historical or self report of physical activity linked with ultrasound measures. In our study we observed an association also with two physical performance measures, including the time taken to sit and stand five times, and the time to walk 50 feet test; those who took longer to perform these activities having lower ultrasound parameters. It seems likely that these are a proxy for higher levels of physical activity including higher intensity activities and consequent bone loading though we can not confirm or refute this [33]. Also our assessment of bone health was restricted to the heel and it is possible that the effect may differ at other skeletal sites. In women, for example, walking has a greater impact on the calcaneus than the hip and spine [34].
Other lifestyle factors were important in men. Smoking, both ever and current, was linked with a reduction in all ultrasound parameters. Previous studies using both the Sahara device and other sonometers provide somewhat discrepant findings, with some though not all reporting a negative association [12-13,15-17,19,29,32,35]. There are fewer data concerning the impact of alcohol consumption with most suggesting no association [12,15,17,36-40]. In our study we found a U-shaped association between alcohol consumption and the QUS measures, where compared to moderate drinking, both light and heavy drinking was associated with a reduction in QUS. This is consistent with some data from bone mass measurement studies finding that social drinking is associated with beneficial effects on bone mass [41].
What is the potential impact of our findings in relation to fracture occurrence? QUS parameters have been linked with fracture in previous studies in both men and women [1-9]. In our study a self reported history of fracture was associated with a reduction in BUA, SOS and QUI. Data from a large prospective study showed that the risk of both hip and non hip fracture increased by a factor of two fold for each unit (SD) change in BUA and SOS [5]. In our study the difference in SOS between those who did and did not smoke amounted to an approximate one third of a standard deviation of the measurement, while for the physical activity scores (PASE and SF36 PCS) the difference in SOS between those in the lowest and highest tertiles of activity was about one fifth of a standard deviation. Although the risk of fracture attributable to the different exposures is relatively small, given that they are potentially modifiable and common they would certainly be potential candidates for inclusion in a population strategy for fracture prevention to optimise bone health in middle age and elderly men with the ultimate aim of reducing fracture occurrence. Some caution, however, is needed in interpreting the data in relation to physical activity as physical activity may influence fracture risk by influencing susceptibility to and also risk of falls [33,42].
In this population survey of European men, QUS parameters declined with age and varied by centre across Europe. Lifestyle factors including physical activity, smoking and alcohol intake influenced bone health.
Acknowledgements
The European Male Ageing Study (EMAS) is funded by the Commission of the European Communities Fifth Framework Programme “Quality of Life and Management of Living Resources” Grant QLK6-CT-2001-00258 and supported by funding from the UK Arthritis Research Campaign. For additional information regarding EMAS contact Frederick Wu, MD; Dept of Endocrinology, Manchester Royal Infirmary, UK. The authors wish to thank the men who participated in the eight countries, the research/nursing staff in the eight centres: C Pott, Manchester, E Wouters, Leuven, M Nilsson, Malmö, M del Mar Fernandez, Santiago de Compostela, M Jedrzejowska, Lodz, H-M Tabo, Tartu, A Heredi, Szeged for their data collection and C Moseley, Manchester for data entry and project coordination. Dr. Vanderschueren and Dr. Boonen are senior clinical investigators of the Fund for Scientific Research-Flanders, Belgium (F.W.O.-Vlaanderen). Dr. Boonen is holder of the Leuven University Chair in Metabolic Bone Diseases.
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