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The Journals of Gerontology Series A: Biological Sciences and Medical Sciences 56:B248-B253 (2001)
© 2001 The Gerontological Society of America

Differential Influence of Physical Activity on Lumbar Spine and Femoral Neck Bone Mineral Density in the Elderly Population

A. Vuillemina,b, F. Guilleminb, P. Jouannyc, G. Denisa and C. Jeandeld

a Faculty of Sport, University of Henri Poincaré, Nancy, France
b School of Public Health, Faculty of Medicine, Nancy, France
c Department of Geriatrics, Centre Hospitalier Universitaire, Rennes, France
d Antonin Balmès Gerontology Center, Montpellier, France

A. Vuillemin, Faculté du Sport, Université Henri Poincaré—Nancy 1, 30 rue du Jardin Botanique, 54600 Villers-les-Nancy, France E-mail: anne.vuillemin{at}staps.uhp-nancy.fr.

Decision Editor: John A. Faulkner, PhD


   Abstract
Top
 Abstract
Methods
 Results
 Discussion
 References
 
This study investigates the relationship between lifetime physical activity and bone mineral density (BMD) at various sites in 129 healthy men and women aged 72.1 ± 6.5 years. BMD was measured by dual energy x-ray absorptiometry, and physical activity was assessed by using the QUANTAP system (Quantification de l'Activité Physique), a standardized and structured computer-assisted interview tool designed to assess lifetime physical activity. Linear regression models controlling for age, gender, height, body mass, lean mass, and smoking habits were performed. Higher levels of sporting activity during youth were associated with greater lumbar spine BMD ( p < .001). Similarly, femoral neck BMD was greatest in subjects who reported regularly taking part in sports over the previous 20 years ( p < .05) and during their whole lifetime ( p < 0.05). Sporting activity at the time of bone mass development increases subsequent lumbar spine BMD, and more recent sporting activity contributes to the preservation of femoral neck BMD. These results suggest that physical activity has a differential influence on BMD at different sites and at different ages, possibly related to the processes of bone construction and bone aging taking place at the time.

BONE mineral density (BMD) is affected by both genetic and environmental factors (1)(2)(3)(4)(5)(6). Among the latter, physical activity is thought to help prevent bone loss (7)(8)(9), and it may be therapeutic in osteoporosis (10). The consequences of low BMD, such as osteoporosis, are well documented and represent a major public health problem (11)(12).

Most studies looking at the relationship between BMD and physical activity have used either an interventional or an observational approach. A typical interventional study might, for example, investigate the effects of a training program on BMD (13)(14)(15)(16)(17). In contrast, observational techniques might be used to compare physically active people with sedentary or minimally active controls in terms of their BMD (18)(19)(20)(21), or to elucidate the relationship between physical activity and BMD in the general population. The increasing research attention being paid to the effects on BMD of physical activity as practiced over a lifetime or at specific ages (22)(23)(24)(25)(26)(27) may help identify periods of particular importance for bone-loss prevention. The aim of the present study was to assess the relationship between lifetime physical activity and BMD as measured at various sites.


   Methods
Top
 Abstract
 Methods
Results
 Discussion
 References
 
Subjects
The study was conducted at Nancy University Hospital (France) from 1995 to 1997 and was approved by the Lorraine County ethics committee. The study involved 129 urban independently living subjects: 40 males and 89 females aged between 60 and 90 years (mean 72.1 ± 6.5 years). They were recruited through various community associations and gave their written informed consent prior to enrollment. In France, osteodensitometry is not funded by the health care system. Therefore, a free absorptiometry and its interpretation including some recommendations were the incentive to enroll in the study.

Inclusion criteria stipulated that subjects should be Caucasian, in apparent good health, and aged 60 years or more. Individuals with relevant medical histories, particularly of an endocrine or rheumatological disorder, were excluded, as were those receiving medication known to influence BMD (such as fluoride, calcium, corticosteroids, vitamin D, calcitonin, antivitamin K, and diuretics). Hormone replacement therapy (HRT) or contraceptive pill use did not cause the exclusion of any subjects.

Eligible subjects attended the study center for clinical examination, an interview to assess physical activity, and BMD measurement.

BMD Measurement
BMD was assessed by using dual-energy x-ray absorptiometry (DEXA; Norland XR-26, Software Version 2.5.2). Measurements were taken at the lumbar spine (L2–L4), femoral neck, and total body, and they were expressed in grams per square centimeter. The osteodensitometer calibration was made each day (morning) on a standard phantom. The coefficient of variation for our machine during measurement on a standard phantom is less than 1%. In our center, the coefficient of variation of BMD measurement in human subjects is less than 3%. The procedure (28) takes approximately 20–30 minutes, involves minimal radiation exposure, and provides precise body composition data (fat mass and lean mass).

Physical Activity Assessment
The QUANTAP system (Quantification de l'Activité Physique), a standardized and structured computer-assisted interview tool (29), was used to gather data on four dimensions of lifetime physical activity: sport at school; leisure sport (recreational or competitive); occupational activity; and daily activity (gardening, odd jobs, housework, travel on foot or by bicycle, and musical and artistic activities). Information recorded for each type of activity included the number of years for which it had been performed, the number of months per year, the number of sessions per month, and the average duration of each session. A trained interviewer collected the data.

Indicators of energy expenditure were calculated for each above dimension and expressed in METs (metabolic equivalents), minutes per year. Two combined indicators were then derived for use in the subsequent analysis. The first covered sport at school and leisure sport (sporting activity), and the second covered occupational and daily activities (other activity). Each was calculated over the whole lifetime and for up to four 20-year periods prior to interview (the previous 20 years, 21–40 years, 41–60 years, and 61–80 years).

QUANTAP is reliable and valid to assess lifetime physical activity (29). Briefly, intraclass correlation coefficients for intraobserver and interobserver reliability varied from 0.56 to 0.96 and from 0.42 to 0.99, respectively, according to the dimensions and indicators considered. Energy expenditure was not statistically significantly different from recommended nutritional intake in either males or females. Percent body fat at the time of the survey correlated with leisure sport (particularly in recent periods of practice): age-adjusted correlation coefficients varied from -0.23 to -0.45 among males, and from -0.19 to -0.31 among females.

Other Variables
Subjects were assessed for their body mass index (BMI), expressed as mass (in kilograms) per square height (in square meters), and lean mass (kilograms; as measured during absorptiometry). Dietary calcium intake (milligrams per day) over the week prior to interview was estimated by using a self-administered food-frequency questionnaire (30) adapted from Cummings and coworkers (31). During the clinical examination, a medical doctor asked female subjects about the number of pregnancies they had had, and whether they had ever received HRT or the contraceptive pill (the latter for 1 year or more). Information was also gathered concerning alcohol consumption and smoking habits. Both were recorded in two categories: smoking as ever smoked (current and past) and never smoked; and daily alcohol consumption as light (less than 0.25 l of wine or beer, or less than one glass of spirits) and heavy (more than 0.25 l of wine or beer, or more than one glass of spirits).

Statistical Analysis
Data were analyzed using the Biomedical Data Processing (BMDP) statistical package (BMDP Statistical Software, Saugus, MA), and descriptive statistics (mean ± standard deviation) were calculated for subject characteristics. Relationships among BMD, subject variables, and physical activity indicators were estimated using Pearson's correlation coefficient. Univariate differences in means between gender were tested by using Student's t test. Variables associated with BMD in univariate analysis ( p < .05) were candidates for stepwise multiple linear regressions in which lumbar, femoral neck, and total body BMD values were dependent variables. Calcium intake appeared to be significantly associated with BMD in univariate analysis and was initially included in the model, but it did not emerge as an independent predictor and was excluded because it did not help explain the variance in BMD. Physical activity variables were candidates for multiple regression whatever their univariate significance level. Two types of model were fitted: for lifetime physical activity, and by years prior to assessment. The final models retained variables at p < .05. Gender and age were forced in each model. After gender was controlled for, an interaction term (gender times age) was introduced in the multiple linear regression on the basis that gender might modify the relationship of BMD with age. In addition, interaction terms (gender times sporting activity of the previous 20 years and gender times other activity of the previous 20 years for femoral neck BMD; gender times sporting activity 61–80 years previously for lumbar spine BMD; gender times lifetime sporting activity for femoral neck BMD) were introduced in the multiple linear regressions on the basis that gender might modify the relationship of BMD with physical activity. The validity of the models retained was expressed by the multiple R2 coefficient, which represents that part of the variance of the dependent variable explained by the covariates entered in the model. The reported R2 values were adjusted for multiple variables when appropriate.


   Results
Top
 Abstract
 Methods
 Results
Discussion
 References
 
Characteristics of the subjects were as presented in Table 1 . BMD values, smoking, and alcohol consumption were significantly higher in males than in females ( p < .0001). Fifteen of the women had received HRT, but none reported taking the contraceptive pill. Overall, sporting activity increased with age, as evidenced by greater participation over the 20 years prior to interview; however, other activities decreased during the same period, primarily as a result of retirement.


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  		Table 1. Subject Characteristics

 
Significant correlations were observed between BMD and physical characteristics (age, height, body mass, BMI, and lean mass; see Table 2 ). In females, BMD decreased significantly with age, but measurements at all three sites tended to be greater among subjects with higher body mass, BMI, or lean mass. In males, femoral neck BMD was significantly higher among taller individuals, and greater body mass and lean mass were associated with greater total body and femoral neck values. A higher BMI was only associated with a higher value of total body BMD. Increased calcium intake was significantly associated with higher BMD at all three sites in females, but with lower femoral neck BMD in males.


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  		Table 2. Correlation between Subject Characteristics and BMD

 
Mean values of total body, femoral neck, and lumbar spine BMD were significantly higher in smokers or former smokers (n = 39) than in nonsmokers (n = 89), but the relationship was not significant after controlling for gender. No significant difference was found in BMD between light (n = 62) and heavy (n = 66) drinkers. Multiple pregnancies were not significantly associated with a lower BMD.

With regard to physical activity indicators in males, a higher lumbar spine BMD was associated with more participation in sports 61–80 years previously (r = .39, p < .05). High levels of other activity up to 60 years previously were associated with a higher BMD at total body (r = .37, p < .05; r = .40, p < .01; r = .33, p < .05, for the three 20-year periods backward in time, respectively). In females, the only such association was a moderate one between other activity 61–80 years previously and lower total body BMD (r = -.27, p < .01). Concerning lifetime physical activity, higher total body BMD was significantly associated with more other activity in males (r = .44, p < .01).

Table 3 and Table 4 present multiple linear regression models fitted to data for total body, femoral neck, and lumbar spine BMD for males and females combined. Whatever the model considered, BMD was lower in subjects who were female, older, and lower in body mass.


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  		Table 3. Significant and Independent Predictors of BMD, Considering Physical Activity in Defined Periods

 

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  		Table 4. Significant and Independent Predictors of BMD, Considering Lifetime Physical Activity

 
Neither sporting nor other activities influenced the total body BMD after controlling for gender, age, and body mass, which together explained 62% of the variance in total BMD (R2 = .62).

Lower femoral neck BMD was associated with lower levels of sporting activity in the previous 20 years. A regression analysis revealed a complex relationship between femoral neck BMD and other activity in late adulthood (total R2 = .497). Lower femoral neck BMD values were associated with higher levels of other activity in the previous 20 years. Coincidentally with the reduction in other activity (particularly occupational activity) that occurs with aging (r = -.386, p < .001), there is an increase in sporting activity with aging (r = .321, p = .026). When lifetime indicators were used, a lower femoral neck BMD was associated with a lower level of lifetime sporting activity (R2 = .471).

Lower lumbar spine BMD was observed in subjects who reported less sporting activity 61–80 years previously (R2 = .383), that is, during their youth.

Whatever the model considered, interaction terms never appeared significantly associated with BMD.


   Discussion
Top
 Abstract
 Methods
 Results
 Discussion
References
 
The findings of the present study indicate that physical activity during two major periods of life is associated with increased BMD at the age of 60 years and beyond. Participation in sports as a child or teenager (61–80 years prior to interview) appears to be a good predictor of BMD at the lumbar spine, though not at the femoral neck or total body. Sporting activity in the previous 20 years is associated with BMD at the femoral neck, as does lifetime participation in sport. These results suggest that physical activity has a differential influence on BMD at different sites and at different ages, possibly related to the processes of bone construction and bone aging taking place at the time.

Assessment of lifetime physical activity relies on a strongly structured, computer-assisted interview in which subjects are asked to recall what they were doing sometimes several decades previously. In the absence of prospective objective measures, potential memory bias is inevitable. It can be minimized by framing the questions in such a way that all subjects are required to cast their minds back by the same amount of time (20 years, for example), however old they are, but that approach sheds no light on the benefits of physical activity at particular ages (such as between 1 and 19 or 20 and 39 years). Clearly, asking subjects to remember what their activity levels were like at a particular age (one option offered by the QUANTAP system) increases differential memory bias between younger and older individuals.

In the present study, measures of BMD were, as in most other reports (32)(33), strongly associated with current body mass. There was also a clear relationship between BMD and lean mass, as previously reported elsewhere (6). The results of the univariate analysis were in accord with the findings of other investigations into the effects on BMD of physical activity over a lifetime or during defined periods (22)(23)(24)(25)(26)(27). Previous studies have demonstrated that sporting activity at the age of ~16 years is important (22)(26), as is other activity at most times of life (past 20 years, 21–40 years previously, 41–60 years previously), as shown in this study.

In the present study, physical activity accounts for less of the variance in lumbar spine BMD than in total body and femoral neck BMD, probably reflecting the influence of genetic or environmental factors not considered here. One twin study (6) estimated the heritabilities of lumbar spine, femoral neck, and total body BMD to be 78%, 76%, and 79%, respectively (leaving only 22%, 14%, and 21% caused by other factors).

Physical activity in youth appears to be important for bone mass acquisition and essential for the maintenance of BMD throughout life. Nevertheless, the results of investigations into the effects of current and/or past physical activity on BMD remain inconsistent. For example, one recent study failed to demonstrate a major effect of lifetime physical activity (occupational, sport) on BMD (27), whereas another reported current and lifelong exercise to protect hip BMD, but not to reduce osteoporotic fracture (23); again inconsistently, current and past physical activity have also been shown to independently reduce the risk of hip fracture (24). The present results tend to demonstrate that sporting activity has a differential influence on lumbar spine and femoral neck BMD, depending on when in life it is participated in.

The results of interventional studies in subjects undergoing training programs also vary, but the majority report physical activity to reduce bone loss, or even maintain bone mass, in both males and females (15)(16)(17)(34)(35).

Reports concerning athletes or former athletes are unclear. One study of former weightlifters found that between the ages of 50 and 64 years, there was a difference compared with controls in favor of the exathletes, but by 65 years and beyond there were no significant differences in total body and spine BMD (18). Another group demonstrated that former competitive distance runners who have continued to train exhibit no significant differences in lumbar vertebrae or hip region BMD compared with individuals who run less or not at all (20). However, cross-sectional studies comparing athletes or regular exercisers with controls have shown higher levels of BMD in more active subjects (21)(36)(37)(38).

There are several limitations to this study that may affect the inferences derived from these data. First, because the results are cross sectional, a cause-and-effect relationship between physical activity and BMD can only be suggested. Second, because the subjects in our sample were Caucasian, in apparent good health, and independently living, these results cannot be generalized to subjects of other races or ethnic groups or to subjects living in institutions or with health problems. Third, it could be interesting to explore if the differential effect of exercise is more or less pronounced between forearm (cortical components) and femoral neck or lumbar spine BMD (cortical and trabecular components) compared to femoral neck and lumbar spine BMD, because of bone composition. Fourth, we can wonder about memory bias that is due to the quantification of physical activity over lifetime. Although memory changes occur as a part of normal aging, the different types of memory are not affected in the same way. Short-term memory is more affected by aging than long-term memory, but difficulties depend on how information was encoded and retrieved (39). These difficulties can be reduced if people are assisted to encode and retrieve information as is done with QUANTAP. It is also important to mention the influence of subject's characteristics in this memory aging process (40).

In conclusion, although several studies have found physical activity to have a positive effect on BMD, none has reported that lifetime activity may have a differential influence depending on the site under consideration. Further investigations should be conducted to determine whether the effects on BMD of participation in sports at various times of life help prevent lumbar and hip fractures in different age groups. Determination of the optimal type, frequency, intensity, and timing of physical activity would clearly aid in the design of programs intended to optimize bone mass acquisition during youth and maintain it throughout adult life.


   Acknowledgments
 
This work was funded by program Projet Hospitalier de Recherche Clinique, 1995, from the French Ministry of Health.

We are very grateful to Prof. D. Regent, H. Blain, F. Decottignies, and J. Huot for patient records, and to B. Martin for assistance in data collection.

Received May 8, 2000

Accepted December 12, 2000


   References
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 Abstract
 Methods
 Results
 Discussion
 References
 

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