JOURNAL OF BONE AND MINERAL RESEARCH Volume 5, Number 4,1990 Mary Ann Liebert, h e . , Publishers

Effect of Season on Physical Activity Score, Back Extensor Muscle Strength, and Lumbar Bone Mineral Density ERIK J. BERGSTRALH,' MEHRSHEED SINAKI,' KENNETH P. OFFORD,' HEINZ W. WAHNER,3 and L. JOSEPH MELTON 1114

ABSTRACT Seasonal variation in physical activity, back extensor muscle strength (BES), and bone mineral density (BMD) of the lumbar spine was studied in 65 healthy postmenopausal women. Physical activity score (PAS) was assessed with an ordinal scale (0-18); this score and the BES were obtained monthly for 2 years (25 readings). BMD values were obtained semiannually (5 readings). A periodic (cosine) regression model was fit to each subject's PAS and BES data to obtain individual estimates of the annual peak day d and the average annual range due to seasonality. There was a strong ( P < 0.001) seasonal pattern in physical activity; August 3 was the average peak day, and the seasonal range was 2.0 PAS units. There was modest ( P = 0.047) seasonality in BES; June 6 was the estimated peak day, and the seasonal range was 8.22 pounds (about 7% of the mean). BMD averaged 0.015 g/cm2 higher in August through November than February through May ( P = 0.002), and the highest monthly average BMD was in August. This seasonal range of 1.4% is larger than the average annual decline with age in BMD observed in longitudinal studies of postmenopausal women. The results of this study have important implications for the planning of longitudinal studies involving changes in physical activity or bone mass in geographic areas with diverse seasons.

INTRODUCTION show a continuous decline of bone mineral density (BMD) with age that averages about l%/year over life,''.') although a period of accelerated bone loss may be superimposed for several years after menopause. Given a precision of 2-3% (coefficient of variation) for the commonly used dual-photon absorptiometry measurements, bone loss of this magnitude is difficult to assess accurately when measurements are made on individual patients over a period of a few months or even a year.(3) However, observations over such relatively short periods have often been used for evaluating the effectiveness of various interventions on bone loss, especially in studies of exercise in elderly subjects. In general, bone loss is also assumed to be constant

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ROSS-SECTIONAL STUDIES

throughout the observation period. Yet in temperate zones, seasonal variations in calcium metabolism(') and possibly also in physical exercise(s)could influence bone mineral density. Indeed, seasonal variations in bone mineral density have been reported by but not allf8) investigators. Such seasonal changes in bone mineral density, if unrecognized, might invalidate the results of shortterm (1-5 years) studies. This study examines seasonal variation in physical activity level, back extensor muscle strength, and bone mineral density of the lumbar spine in postmenopausal women from Minnesota, where the weather changes dramatically through the year. Seasonality was analyzed with a simple periodic regression (cosine) model, with an attempt to identify the magnitude and timing of annual troughs and peaks.

'Section of Biostatistics, Mayo Clinic and Mayo Foundation, Rochester, MN 55905. 'Department of Physical Medicine and Rehabilitation, Mayo Clinic and Mayo Foundation, Rochester, MN 55905. 'Section of Diagnostic Radiology, Mayo Clinic and Mayo Foundation, Rochester, MN 55905. 'Section of Clinical Epidemiology, Mayo Clinic and Mayo Foundation, Rochester, MN 55905.

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SUBJECTS AND METHODS Selection of subjects The 65 healthy, nonsmoking, postmenopausal white women analyzed in this study were enrolled in a clinical trial on the effect of nonloading exercise on bone mineral density of the lumbar spine.(91All subjects were considered “normal” insofar as they had no history of metabolic bone disease and were not on any medication (including estrogen) believed to affect bone metabolism. The subjects had no history of significant back pain and no radiographic evidence of compression fractures or osteoporosis. Their median age was 54 years (range 48-65 years). A total of 11 subjects had had a hysterectomy without an oophorectomy. The remaining subjects had experienced natural menopause from 6 months to 22 years (median 6.5 years) before entry into the study and had no history of oophorectomy. Informed consent was obtained from all subjects.

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A total of 34 of the women were randomly assigned to an exercise regimen designed to strengthen the back extensors, and 31 subjects (the control group) were not prescribed back-strengthening exercises. The study was conducted over 2 years, and the subjects were seen monthly. At each visit, the subject’s physical activity during the previous 30 days was rated with a physical activity score (PAS) on a scale from 0 to 18; the score was the sum of three activity components (housework, job, and sports), each of which contributed 0-6 In addition, at each visit the back extensor muscle strength (BES) was measured (in pounds) with a strain-gauge dynamometer; quality control procedures and performance characteristics have been described previously. ( I 1 ) Every 6 months (baseline, 6, 12, 18, and 24 months), bone mineral density of the lumbar spine (L2-4) was measured (in grams per square centimeter) with dual-photon absorptiometry. ( I 2 ) The measurement precision, determined by repeated measurements in the same patients, was 2% (coefficient of variation).“] PAS and BES assessments were all made by the same person (Sinaki). All subjects entered the study in 1984, and the monthly distribution was as follows: February (3 subjects), March (27), April (8), May (2), August (18), and September (7). This distribution is pertinent to the semiannual data for BMD because there were some calendar months for which no measurements were available.

Statktical methods Both PAS and BES increased during the 2 year study period in both the control and the exercise group, but BMD declined (Fig. 1). Because we did not want follow-up time or group effects to influence the seasonality analyses, we chose to analyze “detrended” values of PAS, BES, and BMD. The detrended values were the residuals (observed

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FIG. 1. Mean physical activity score (PAS, A), back extensor muscle strength (BES, B), and lumbar spine bone mineral density (BMD, C) for 34 subjects in exercise group and 31 control subjects, plotted against months after randomization. Horizontal lines are a visual reference for time changes.

- predicted) from the linear regressions of PAS, BES, and BMD on follow-up time ( x ) fit separately for each subject. Because of the curvilinear relationship between BES and follow-up time, the natural logarithm of follow-up time was used for x. The mean of the detrended values for each subject is zero. For PAS and BES, each subject had a potential for 25 monthly readings over the 2 year study. To assess the presence of periodicity, we fit a simple periodic regression model (which assumes one annual peak followed 6 months later by the annual low with equal deflection above and below an individual’s mean) to each subject’s detrended data points.(13)From this model we es-

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timated for each subject the day of the year d o n which the variable of interest peaked and the height or amplitude A of the peak above the individual’s mean. Details of the model are given in the Appendix. The SAS procedure REG was used to fit the individual periodic regression models.(14’Figure 2 illustrates the fit of the model for one subject’s detrended PAS data. To estimate the average day of the peak across all subjects (average d value), one must consider that d is a circular variable.‘1J’ For example, d = 1 (January 1) is only 1 day away from d = 365 (December 31). Simply taking the mean of the 65 individually estimated d values could be misleading because it does not take into account the circular nature of d. The specific method used is given in the Appendix. The Rayleigh test was used to assess whether the 65 d values were randomly distributed throughout the year.(*31 This test is based on the r statistic, which has a value of 0 for randomness and a value of 1 if all of the individual peaks fall on the same day of the year. A P value < 0.05 signified that the measurement had a significant seasonal component. Because the distribution of estimated amplitudes is skewed, they were summarized using median values rather than means. A nonparametric 95% confidence interval for the true median amplitude was calculated using the values corresponding to the 38.5 and 63.1 percentiles.(151 Seasonality analyses were done separately for control and exercise groups, and no significant differences were found. In view of this, only the results for the combined sample are presented.

exceeded the mean for that individual (that is, the amplitude) were estimated using the cosine model. The “average” peak day across subjects was estimated to be August 18 (d = 230); the distribution of peak days is shown in Table 1. The peak days clumped around the month of August (Fig. 3A), a suggestion that the data are highly seasonal (Rayleigh test, r = 0.70, P < 0.001). Elecause the PAS readings represent the average score for the previous 30 days, the true peak is probably about 15 days before August 18 (that is, August 3). with the corresponding low value occurring in early February. The median of the individual amplitudes was 0.98 (95% confidence interval, 0.78-1.27), which implies an average annual range in PAS due to seasonality of 1.% (= 2 x 0.98). or approximately 21% of the raw PAS mean score of 9.3 (calculated over all subjects and readings). The marked seasonality of PAS was also noted by plotting the monthly mean PAS against calendar time (Fig. 3B).

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With the cosine model fit to individuals, August was the month of peak strengh in 11 subjects, followed by March in 9 (Table 1 and Fig. 4A). The data exhibit some evidence of seasonality (Rayleigh test, r = 0.22, P = 0.047); June 6 (d = 157) was the estimated average peak day, although the months of March through August all seemed to be elevated. The median estimated amplitude was 4.11 pounds (95% confidence interval, 3.47-5.28). This suggests an anRESULTS nual range in BES due to seasonality of 8.22 pounds, or PAS about 7% of the overall mean of 116 pounds. A plot of the The day of the year on which the modeled peak PAS oc- monthly mean BES versus calendar time demonstrates that curred for each subject and the amount by which the peak seasonality is not nearly as strong as for PAS (Fig. 4B). I

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TABLE1 . DISTRIBUTION OF INDIVIDUALLY ESTIMATED PEAKDAYS ~~

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FIG. 3. (A) Circular histogram of predicted month of peak physical activity score. The circle at frequency 05 crudely represents the expected number of patients per month if the data are not seasonal. Numbers in parentheses are the numbers of subjects with predicted peak in the indicated month. (B) Monthly mean of detrended physical activity score with horizontal reference lines at - 1 .O, 0.0, and 1.0. Mean values from fewer than five subjects are connected with dashed lines.

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FIG. 4. (A) Circular histogram of predicted month of peak back muscle extensor strength. The circle at frequency 05 crudely represents the expected number of patients per month if the data are not seasonal. Numbers in parentheses are number of subjects with predicted peak in the indicated month. (B) Monthly mean of detrended back extensor muscle strength (BES) with horizontal reference lines at -2, 0, and 2. Mean values from fewer than five subjects are connected with dashed lines.

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EFFECT OF SEASON ON ACTIVITY AND BMD

tomy, found that the bone mineral content of the third metacarpal was lower in winter, whereas Hyldstrup et Because only five evaluations (at baseline, 6, 12, 18, and al.(", found that the bone mass of the distal forearm was 24 months) of BMD were available for each subject, we 2.5% higher in the summer in 10 healthy men. In the axial were unable to fit individual cosine models reliably.('31 skeleton, Krdlner(') found that the BMD of the lumber Overall, we had no BMD readings in January, July, or De- spine also varied seasonally in a longitudinal study in Dencember and only two readings in June. In view of this, we mark, and a study from Belgium('*' performed on a small chose to look at seasonality by subtracting the late winter number of postmenopausal women confirms these obserthrough spring (February through May) within-subject de- vations. However, a recent study by Overgaard et al.(*' of trended BMD means from the late summer through fall healthy premenopausal women in Denmark found that spi(August through November) within-subject means. The nal BMD levels were significantly higher in winter than in late summer readings averaged 0.015 g/cm2 higher than the summer. However, the authors noted that the changes late winter values, and 54% of the subjects had values at were so small that they could be explained by chance varialeast 0.01 g/cm' higher. Of the subjects, 48 (74%) had tion in measurement procedures. higher mean levels in late summar (P = 0.0002, sign test). In our study, the average BMD of the lumbar spine was Although this estimate of seasonal fluctuation (0.015 1.4% higher in the late summer than in the winter months. g/cm2) is only 1.4% of the mean, which was 1.05 g/cm2 This finding is similar to the result found by Krdlner") in over all subjects and readings, it is slightly higher than the Danish women, in which lumbar spine density values from average annual decrease in BMD of 1.3% found over the July to September were 1.7% higher than those from Janentire 2 year study period. Because we had to average over uary to March. Using the same monthly groupings as KrBIa 4 month period, the true range in BMD due to seasonal- ner, we found a 1.6% increase in summer over winter in 41 ity is likely to be somewhat larger than 0.015 g/cm2. subjects. Krdlner estimated the peak day to be August 15. Monthly mean detrended BMD values throughout the 2 We also found the highest mean BMD in August, although year study are presented in Fig. 5 . August had the highest we had little data for June or July. Thus, the range in mean detrended BMD (0.016 g/cm2, n = 30 readings) and BMD due to seasonality is conservatively estimated as February the lowest (-0.011 g/cm2, n = 24 readings). about 1.4% of the overall mean, which is slightly larger than the average annual decrease of 1.3% seen in this study and also higher than the 1% annual decrease found by both Riggs et al."' and Krdlner.") DISCUSSION Seasonal changes in vitamin D metabolism, as well as in Three studies have shown seasonal changes in bone physical exercise, have been implicated as possible causes mineral density in which the values were highest in the for these seasonal changes in bone mass. Seasonal changes summer and lowest in the winter. In their assessment of in vitamin D metabolism (25-hydroxyvitamin D) have been .~~~ studies in young resiappendicular cortical bone, Aitken et al.,'"' in a 2 year well d o ~ u m e n t e d . ( ' ~However, study of 48 women in Scotland who had had oophorec- dents of Wisconsin suggested that decreased endogenous

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production of vitamin D in winter was offset by increased vitamin D supplementation, so that total vitamin D stores remained relatively constant throughout the year.(21)previous reports indicate little correlation between vitamin D levels and bone mass in southeastern Minnesota women,(2z)and the higher dietary vitamin D intake”” makes it somewhat unlikely that subclinical vitamin D deficiency is an explanation for the Danish findings.(’) KrBlner et a l . I s ) showed that physical exercise, in addition to increasing BMD, also tended to neutralize seasonal variations, and they suggested that the winter decline in BMD was due to a seasonal decrease in physical activity. We estimated physical activity and found it exhibited distinct seasonal patterns. The activity score peaked in early August and was lowest in early February. Both housework and job-related activities demonstrated winter lows and summer peaks. Housework included garden activities and yard maintenance, which are primarily summer activities in Minnesota, although fall leaf raking and winter snow shoveling are also included in this category. Seasonal trends in the job component of the score probably reflect that many of the women were involved in farming and did a considerable amount of outside work during the summer. The average range in physical activity due to seasonality was estimated as 21% of the mean in this group of women. A slight seasonal trend was also noted for BES, and June was the suggested peak month. However, the predicted annual range in BES due to seasonality was only 7% of the mean. This result was somewhat surprising in view of the physical activity data. Possibly, the additional activities done in the summer were not of the type necessary to produce a measurable increase in BES. The results of this study have important implications for the planning of longitudinal studies of physical activity level or BMD in geographic areas with distinct seasons. For example, a study with only 6 months’ follow-up and with all subjects entered in March could find an increase in BMD of 0.015 g/cm2 due entirely to seasonality. This points out the need to do well-controlled studies and to give careful attention to the timing of repeated assessments obtained in longitudinal studies. Indeed, efforts to enter subjects uniformly over the course of a year might be appropriate for some trials. In observational studies, it might be prudent to adjust for the effect of season by including it as a covariate in the analysis. Any effects of seasonality would be most pronounced for uncontrolled studies. However, even in controlled studies with more than one measurement per year, one might obtain more precise (smaller variance) estimates of the change in BMD over time by taking into account seasonality. This could result in an increase in the power t o detect group differences.

where f = calendar time of reading (number of days after 12/31/83), M = subject’s overall mean y , A = estimated amplitude (distance from M to the annual peak or M to the low), d = estimated day of the year on which the peak occurs (1 5 d 5 365)’ and k = (360/365) is the scaling constant required to produce a 365 day cycle. This model assumes that for each calendar year there is an annual “low” day followed 6 months later by the annual “peak” (or high) day. Furthermore, it is assumed that the transition from the low (high) to the high (low) follows the cosine function. The model is symmetrical in that predicted values for days equidistant before and after the peak day are identical. Note that any multiple of 365 days before or after any arbitrary time yields the same predicted y because of the periodic nature of the cosine function. An appropriate estimate of the mean peak day is 365 360 arctan

ACKNOWLEDGMENT Supported by a grant from the Mayo Foundation.

REFERENCES 1. Riggs BL, Wahner HW, Dunn WL, Mazess RB, Offord KP,

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APPENDIX

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Melton LJ I11 1981 Differential changes in bone mineral density of the appendicular and axial skeleton with aging. J Clin Invest 67:328-335. Krdlner B, Nielsen S P 1982 Bone mineral content of the lumbar spine in normal and osteoporotic women: Cross-sectional and longitudinal studies. Clin Sci 62:329-336. Riggs BL, Wahner HW, Melton LJ 111, Richelson LS, Judd HL, Offord KP 1986 Rates of bone loss in the appendicular and axial skeletons of women: Evidence of substantial vertebral bone loss before menopause. J Clin Invest 77:14871491. Aitken JM, Gordon S, Anderson JB, Hart DM, Lindsay R, Horton PW, Smith CB, Smith DA, Shimmins J 1973 Seasonal variations in calcium and phosphorus homeostasis in man. In: Frame B, Parfitt AM, Duncan H (eds) Clinical aspects of metabolic bone disease. Excerpta-Medica International Congress Series No. 270, Amsterdam, pp. 80-83. KrBlner B, Toft B, Nielsen SP, Tdndevold E 1983 Physical exercise as prophylaxis against involutional vertebral bone loss: A controlled trial. Clin Sci 64:541-546. Aaron JE, Gallagher JC, Nordin BE 1974 Seasonal variation of histological osteomalacia in femoral-neck fractures. Lancet 2:84-85. Krdlner B 1983 Seasonal variation of lumbar spine bone mineral content in normal women. Calcif Tissue Int 35145-147. Overgaard K. Nilas L, Johansen JS, Christiansen C 1988 Lack of seasonal variation in bone mass and biochemical estimates of bone turnover. Bone 9:285-288. Sinaki M, Wahner HW, Offord KP, Hodgson SF 1989 Effi-

EFFEm OF SEASON ON ACTIVITY A N D BMD

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cacy of nonloading exercises in prevention of vertebral bone loss in postmenopausal women: A controlled trial. Mayo Clin Proc 64:762-769. Sinaki M, Offord KP 1988 Physical activity in postmenopausal women: Effect on back muscle strength and bone mineral density of the spine. Arch Phys Med Rehabil 69277-280. Sinaki M, McPhee MC, Hodgson SF, Merritt JM, Offord KP 1986 Relationship between bone mineral density of spine and strength of back extensors in healthy postmenopausal women. Mayo Clin Proc 61:116-122. Dunn WL, Wahner HW, Riggs BL 1980 Measurement of bone mineral content in human vertebrae and hip by dual photon absorptiometry. Radiology 1x485-487. Batschelet E 1981 Circular Statistics in Biology. Academic Press, New York. SAS Institute 1985 SAS User’s Guide: Statistics, Version, 5th ed. SAS Institute, Cary, NC. Snedecor GW, Cochran WG 1967 Statistical Methods, 6th ed. Iowa State University Press, Ames. Aitken JM, Anderson JB, Horton PW 1973 Seasonal variations in bone mineral content after the menopause. Nature 241~59-60. Hyldstrup L, McNair P, Jensen GF, TransbBl I 1986 Seasonal variations in indices of bone formation precede appropriate bone mineral changes in normal men. Bone 7:167-170. Devogelear JP, Depresseux G, Lethic ND 1988 Seasonal variation in bone mineral content in postmenopausal women. In: DeQueker JV, Geusens P, Wahner HW (eds) Bone Mineral Measurements by Photon Absorptiometry: Methodological

377 Problems. University Press, Leuven, Belgium, p. 225. 19. Stamp TCB, Round JM 1974 Seasonal changes in human plasma levels of 25-hydroxyvitamin D. Nature 247563-565. 20. Devgun MS, Paterson CR, Johnson BE, Cohen C 1981 Vitamin D nutrition in relation to season and occupation. Am J Clin Nutr 341501-1504. 21. Chesney RW, Rosen JF, Hamstra AJ, Smith C, Mahaffey K, DeLuca HF 1981 Absence of seasonal variation in serum concentrations of 1,25-dihydroxyvitarnin D despite a rise in 25-hydroxyvitamin D in summer. J Clin Endocrinol Metab 53:139-142. 22. Tsai K-S, Wahner HW, Offord KP, Melton LJ 111, Kumar R, Riggs BL 1987 Effect of aging on vitamin D stores and bone density in women. Calcif Tissue Int 40:241-243. 23. Lund B, SBrensen OH 1979 Measurement of 25-hydroxyvitamin D in serum and its relation to sunshine, age and vitamin D intake in the Danish population. Scand J Clin Lab Invest 39~23-30.

Address reprint requests to: Erik J. Bergstralh c / o Section of Publications Mayo Clinic 200 First Street S W Rochester, MN 55905 Received for publication April 6, 1989; in revised form July 27, 1989; accepted September 5 , 1989.

Effect of season on physical activity score, back extensor muscle strength, and lumbar bone mineral density.

Seasonal variation in physical activity, back extensor muscle strength (BES), and bone mineral density (BMD) of the lumbar spine was studied in 65 hea...
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