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Height reduction, determined using knee height measurement as a risk factor or predictive sign for osteoporosis in elderly women
Nutrition 23 (2007) 794 –797 www.elsevier.com/locate/nut
Applied nutritional investigation
Height reduction, determined using knee height measurement as a risk factor or predictive sign for osteoporosis in elderly women Daniel Bunout, M.D.a,b,*, Gladys Barrera, R.N.a, María Pía de la Maza, M.D., M.Sc.a, Laura Leivaa, Vivien Gattas, R.D.a, and Sandra Hirsch, M.D., M.Sc.a a
b
INTA, University of Chile, Santiago, Chile Department of Medicine, Central Campus Faculty of Medicine, University of Chile, Santiago, Chile Manuscript received January 8, 2007; accepted August 19, 2007.
Abstract
Objective: We assessed the value of height reduction, calculated using knee height measurement, as a risk factor or predictive sign for osteoporosis in healthy elderly women. Methods: In 181 healthy women 76 ⫾ 5 y of age, height, weight, and knee height were evaluated. Femoral and spine bone mineral densities and body compositions were measured using dual-energy X-ray absorptiometry. In 76 young women 27 ⫾ 4 y of age, a regression equation to predict height, based on knee height, was derived. Using this equation, maximum attained height and height loss were calculated in elderly women, which was correlated to bone mineral density. Results: The equation to predict height was height (cm) ⫽ knee height (cm) ⫻ 2.22 ⫹ 50.54. The calculated height loss in elderly women was ⫺6.1 ⫾ 3.8 cm or ⫺0.08 ⫾ 0.05 cm/y of age. Height loss and hip circumference were significant predictors of spine bone mineral density. In the case of femoral bone mineral density, to the same predictors, a negative effect of waist circumference was added. Women in the highest quintile of height reduction (⬎0.199 cm/y) had an odds ratio of 4.5 (95% confidence interval 1.56 –13.3, P ⬍ 0.02) for femoral osteoporosis. Conclusion: Knee height can be used as an accurate measurement of height loss in the elderly, which is a significant predictor of femur and spine bone mineral densities, in addition to hip circumference. © 2007 Elsevier Inc. All rights reserved.
Keywords:
Osteoporosis; Knee height; Height loss; Hip circumference; Bone mineral density
Introduction Height reduction in the elderly is caused by a decrease in the height of vertebral bodies as a consequence of osteoporosis and disc degeneration. Therefore, this phenomenon is considered a risk factor or predictive sign for the presence of osteoporosis and disc degeneration [1,2]. However, the precise determination of height loss over time is complicated. Selfreports of height reduction are inaccurate and overestimate the true loss [3]. On very few occasions, there is reliable longitudinal information to estimate the reduction and usually the data available are for relatively short lapses, such as ⱕ3 y [4]. Others have used information about height that appears in drivers’ licenses, which can also be inaccurate [5]. This work was financed by Fondecyt grant 1040905. * Corresponding author. Tel.: ⫹56-2-678-1485; fax: ⫹56-2-221-4030. E-mail address: [email protected] (D. Bunout). 0899-9007/07/$ – see front matter © 2007 Elsevier Inc. All rights reserved. doi:10.1016/j.nut.2007.08.012
Another approach to estimate height reduction is the prediction of the maximum attained height, using anthropometric variables. One of the most commonly used measurements is knee height, and several regression equations, in different populations, have been published to predict stature from this measurement [6 – 8]. However, the diversity of regression equations reported indicates that these are dependent on local factors and that the ideal is to measure a representative sample of young subjects to obtain regression values that can be applied with greater accuracy in elderly subjects of the same community. All these regression equations to predict height reduction would be valid only if the knee height/stature ratio remained constant for ⱖ50 y. This study assessed the value of height reduction, calculated using knee height measurement, as a risk factor or predictive sign for osteoporosis in healthy elderly women.
D. Bunout et al. / Nutrition 23 (2007) 794 –797
Materials and methods We studied healthy elderly women living in the community who had participated in research protocols or preventive medical examinations at Instituto de Nutrición y Technologia de los Alimentos (INTA). We excluded women with chronic diseases such as diabetes mellitus, cardiac or renal failure, or malignant tumors, those taking medications that could interfere with bone metabolism (such as steroids or biphosphonate), and those with inadequate cognitive function, defined as a Mini-Mental State score ⬍20 [9]. All signed an informed consent for the specific projects in which they participated, allowing us to use the gathered information. This study was approved by INTA’s ethics committee. All women underwent a comprehensive medical examination performed at INTA, which included the measurement of weight on a digital scale, stature using a wallmounted stadiometer and midarm circumference using an inextensible and flexible tape. Knee height (the distance from the heels to the thigh, above the femoral condyles, next to the patella) was measured using a Ross caliper with a non-fixed base in the sitting position, with the legs bent at a 90-degree angle. Right quadriceps strength was measured on a quadriceps table and expressed in kilograms. Bone mineral density (BMD) at the spine and femoral neck and body composition was measured using a LUNAR Prodigy dual-energy X-ray absorptiometer (General Electric Medical Systems, Madison, WI, USA). The same observers performed all the measurements and the interassay coefficients of variation of the equipment are 0.6% for BMD, 2.9% for boy fat, and 1.4% for lean body mass [10]. Weight, height, midarm circumference, and knee height were also measured in healthy young women of the same socioeconomic level, 21 to 38 y of age, without osteoporosis or taking medications that could interfere with bone metabolism, to obtain a regression equation to predict stature from the measurement of knee height. We considered that, in this age range, these women had ended their growth period and had not developed a significant height reduction. To test if knee height/stature had remained constant in time, we used historical anatomic data reported for subjects
795
living in India in 1924 [11]. The researcher measured height and tibia length in 142 subjects, of whom 56 were women. To account for the height of the thigh and the heel, included in knee height measurements with the caliper, 12 cm was added to the length of the tibia and calculated the ratio between knee height and stature. The same ratio was calculated in the young women included in this study. All statistical analyses were done using STATA 7.0 for Windows (STATA Corp., College Station, TX, USA). Using anthropometric data from young women, a regression equation was derived to predict their stature using knee height. This equation was used among elderly women to calculate their maximum attained stature. The difference between the latter and the actual stature was considered as the height reduction experienced throughout life. The criteria proposed by the World Health Organization were used to diagnose osteoporosis (a BMD ⬍2.5 SDs of the value for a young population of the same ethnic background or a value ⬍1 SD and a history of a non-traumatic fracture) [12]. Concordance between measured and estimated heights in young women was assessed using Pearson’s correlation coefficient and Bland-Altman plots [13]. Results are expressed as mean ⫾ SD. Forward stepwise regressions were used to evaluate the association among multiple variables.
Results We studied 181 elderly women 76 ⫾ 5 y of age and 76 young women 27 ⫾ 4 y of age. Among young women, the regression equation to predict stature was height (cm) ⫽ knee height (cm) ⫻ 2.22 ⫹ 50.54. The predicted stature using the equation had a correlation coefficient of 0.84 and a good concordance with measured height (Fig. 1). The calculated height loss among elderly women, using this equation to predict maximum attained height, was ⫺6.1 ⫾ 3.8 cm or ⫺0.08 ⫾ 0.05 cm/y of age. Femoral and spine BMDs correlated significantly with height loss, body mass index, waist and hip circumferences, fat and fat-free masses, and right quadriceps strength (Table 1). A regression equation using these variables accepted hip circumference and height loss as significant predictors of spine BMD.
Fig. 1. (A) Scatterplot of measured versus estimated stature using knee height and (B) Bland-Altman concordance plot of measured versus estimated height.
796
D. Bunout et al. / Nutrition 23 (2007) 794 –797
Table 1 Correlation between bone mineral density at femur and spine and anthropometry, body composition, and muscle strength Bone mineral density (g/cm2)
Height reduction (cm/y) Body mass index (kg/m2) Waist circumference (cm) Hip circumference (cm) Fat-free mass (kg) Fat mass (kg) Right quadriceps strength (kg)
Femur
Spine
0.34* ⬍0.001† 0.31 ⬍0.001 0.21 0.005 0.47 ⬍0.001 0.34 ⬍0.001 0.38 ⬍0.001 ⫺0.22 0.003
0.25 ⬍0.001 0.28 ⬍0.001 0.27 ⬍0.001 0.41 ⬍0.001 0.25 ⬍0.001 0.34 ⬍0.001 ⫺0.18 0.018
* Pearson’s correlation coefficient. Probability.
†
The predictors for femoral BMD were the above-mentioned variables plus a negative effect of waist circumference (Table 2). Compared with women in the lowest quintile of height reduction (⬍0.035 cm/y), women in the highest quintile (⬎0.199 cm/y) had an odds ratio of 4.5 (95% confidence interval 1.56 –13.3, P ⬍ 0.02) for femoral osteoporosis and an odds ratio of 2.2 (95% confidence interval 0.84 –5.8, P ⫽ 0.1) for spine osteoporosis. The knee height/stature ratios were 0.307 ⫾ 0.001 and 0.304 ⫾ 0.002 in young women studied by us and women from India studied in 1924, respectively (P ⫽ 0.222).
Discussion These results show that height loss, derived from an objective parameter such as knee height, is a risk factor and that a larger hip circumference is protective against osteoporosis in healthy elderly women. Many studies had addressed the usefulness of height reduction as an indicator for osteoporosis but all concluded
that it was difficult to obtain an objective estimate of height loss unless a long-term follow-up was carried out [3–5]. Obviously, this type of longitudinal information is seldom available when elderly subjects are evaluated. Measuring knee height would fill this gap because it is a simple measurement and accurately predicts maximum attained height as shown by the high correlation and concordance between measured and estimated heights. It is important to underscore that the regression equation must be obtained from young subjects because, if it is derived from measurements made in elderly subjects who have lost height, it will be invariably inaccurate. This bias has been observed in several studies that have used knee height to predict stature [14,15]. The association of hip circumference with BMD is not surprising. We and others have previously reported that elderly subjects with a higher body mass index have a significantly lower risk of osteoporosis [16,17], and there is a high correlation between hip circumference and body mass index. The fact that waist circumference did not enter the equation for the spine and had a negative impact on the femur may indicate that fat accumulated in the buttocks is more protective than abdominal fat. However, other investigators have found exactly the opposite, suggesting that android distribution of fat is protective against osteoporosis [18]. Moreover, others have suggested that visceral fat accumulation decreases adiponectin levels, an adipokine that has deleterious effects on bone [19]. There is only one report showing that waist fat accumulation deteriorates bone health [20]. Moreover, waist circumference correlates with low vitamin D levels in elderly subjects and this alteration may also have a deleterious influence on bone mineralization [21]. The odds ratio for femoral osteoporosis increased fourfold in subjects in the highest quintile of stature reduction. However, the odds ratio for the spine was not significant. This may indicate that trabecular (spine) and cortical (femur) bones have different responses to environmental, nutritional, and metabolic mediators of bone metabolism. For example, we previously reported that femoral but not spine BMD improved after a period of supplementation with vitamin D in elderly subjects [22]. Other studies have also reported the same difference between the femur and the
Table 2 Multiple regression models for femur and spine bone mineral density
Femur bone mineral density (R of model ⫽ 0.336) Height reduction (cm/y) Hip circumference (cm) Waist circumference (cm) Constant Spine bone mineral density (R2 of model ⫽ 0.20) Height reduction (cm/year) Hip circumference (cm) Constant
Coefficient
SE
t
P
0.474 0.008 ⫺0.004 0.343
0.139 0.001 0.001 0.071
3.420 6.860 ⫺3.530 4.800
0.001 0.000 0.001 0.000
0.688 0.007 0.307
0.241 0.001 0.126
2.860 5.520 2.440
0.005 0.000 0.016
2
D. Bunout et al. / Nutrition 23 (2007) 794 –797
spine in response to vitamin D [23]. However, this is not the case for biphosphonates, which induce a similar improvement in BMD of the femur and spine [24]. The lack of a significant association between height reduction and spine osteoporosis could also be related to a reduction of the intervertebral disc height due to a degenerative process, which is more marked in untreated menopausal women [25]. Another explanation is that an artifact from sclerotic facets or vertebral compression could have spuriously increased BMD measurements in the spine [26]. The lack of differences in knee height/stature ratio between the young women studied by us and the women from India studied in 1924 confirms that this ratio remains constant not only over time but also in different ethnic groups and further validates the use of knee height to calculate height reduction in elderly subjects.
[9]
[10]
[11] [12]
[13]
[14]
[15]
Conclusion We have identified another predictor for osteoporosis, specifically femoral osteoporosis. Although a universal screening for osteoporosis in persons older than 64 y [27] is recommended, this may not be accomplished in places where health care resources are limited. A stratified screening in such individuals who have developed an important stature reduction or have a small hip circumference could be cost effective.
[16]
[17]
[18]
[19]
[20]
References [1] Versluis RG, Papapoulos SE, de Bock GH, Zwinderman AH, Petri H, van de Ven CM. Clinical risk factors as predictors of postmenopausal osteoporosis in general practice. Br J Gen Pract 2001;51:806 –10. [2] Pfirrmann CW, Metzdorf A, Elfering A, Hodler J, Boos N. Effect of aging and degeneration on disc volume and shape: a quantitative study in asymptomatic volunteers. J Orthop Res 2006;24:1086 –94. [3] Birrell F, Pearce MS, Francis RM, Parker L. Self-report overestimates true height loss: implications for diagnosis of osteoporosis. Clin Rheumatol 2005;24:590 –2. [4] Siminoski K, Jiang G, Adachi JD, Hanley DA, Cline G, Ioannidis G, et al. Accuracy of height loss during prospective monitoring for detection of incident vertebral fractures. Osteoporos Int 2005;16: 403–10. [5] Thornton MJ, Sedlak CA, Doheny MO. Height change and bone mineral density: revisited. Orthop Nurs 2004;23:315–20. [6] Chumlea WC, Guo SS, Steinbaugh ML. Prediction of stature from knee height for black and white adults and children with application to mobility-impaired or handicapped persons. J Am Diet Assoc 1994; 94:1385– 8. [7] Knous L and Arisawa M. Estimation of height in elderly Japanese using region-specific knee equations. Am J Hum Biol 2002;14: 300 –7. [8] Pini R, Tonon E, Cavallini MC, Bencini F, Di Bari M, Masotti G, et al. Accuracy of equations for predicting stature from knee height,
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and assessment of statural loss in an older Italian population. J Gerontol A Biol Sci Med Sci 2001;56:B3–7. Folstein MF, Folstein SE, McHugh PR. “Mini mental state”: a practical method for grading the cognitive state of patients fro the clinician. J Psychiatr Res 1975;12:189 –98. Gajardo H, Barrera G. Control de calidad de la densitometría ósea: precisión, reproducibilidad y aplicación clínica. Rev Med Chile 1998; 126:56 – 62. Pan N. Length of long bones and their proportion to body height in Hindis. J Anat 1924;58:374 – 8. The World Health Organization (WHO) Study Group on Osteoporosis. Assessment of fracture risk and its application to screening for osteoporosis. Geneva: World Health Organization; 1994. Bland JM, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurements. Lancet 1986;8: 307–10. Donini LM, de Felice MR, de Bernardini L, Ferrari G, Rosano A, de Medici M, et al. Prediction of stature in the Italian elderly. J Nutr Health Aging 2000;4:72– 6. Palloni A, Guend A. Stature prediction equations for elderly Hispanics in Latin American countries by sex and ethnic background. J Gerontol A Biol Sci Med Sci 2005;60:804 –10. Barrera G, Bunout D, Gattas V, de la Maza MP, Leiva L, Hirsch S. A high body mass index protects against femoral neck osteoporosis in healthy elderly subjects. Nutrition 2004;20:769 –71. Albala C, Yanez M, Devoto E, Sostin C, Zeballos L, Santos JL. Obesity as a protective factor for postmenopausal osteoporosis. Int J Obes Relat Metab Disord 1996;20:1027–32. Tarquini B, Navari N, Perfetto F, Piluso A, Romano S, Tarquini R. Evidence for bone mass and body fat distribution relationship in postmenopausal obese women. Arch Gerontol Geriatr 1997;24:15–21. Lenchik L, Register TC, Hsu FC, Lohman K, Nicklas BJ, Freedman BI, et al. Adiponectin as a novel determinant of bone mineral density and visceral fat. Bone 2003;33:646 –51. Blaauw R, Albertse EC, Hough S. Body fat distribution as a risk factor for osteoporosis. S Afr Med J 1996;86:1081– 4. Snijder MB, van Dam RM, Visser M, Deeg DJ, Dekker JM, Bouter LM, et al. Adiposity in relation to vitamin D status and parathyroid hormone levels: a population-based study in older men and women. J Clin Endocrinol Metab 2005;90:4119 –23. Bunout D, Barrera G, Leiva L, Gattas V, de la Maza MP, Avendano M, et al. Effects of vitamin D supplementation and exercise training on physical performance in Chilean vitamin D deficient elderly subjects. Exp Gerontol 2006;41:746 –52. Jackson RD, LaCroix AZ, Gass M, Wallace RB, Robbins J, Lewis CE, et al. Calcium plus vitamin D supplementation and the risk of fractures. N Engl J Med 2006;354:669 – 83. Liberman UA, Weiss SR, Broll J, Minne HW, Quan H, Bell NH, et al. Effect of oral alendronate on bone mineral density and the incidence of fractures in postmenopausal osteoporosis. The Alendronate Phase III Osteoporosis Treatment Study Group. N Engl J Med 1995; 333:1437– 43. Baron YM, Brincat MP, Galea R, Calleja N. Intervertebral disc height in treated and untreated overweight post-menopausal women. Hum Reprod 2005;20:3566 –70. Mazess RB, Barden HS, Ettinger M, Johnston C, Dawson-Hughes B, Baran D, et al. Spine and femur density using dual-photon absorptiometry in US white women. Bone Miner 1987;2:211–9. The guide to clinical preventive services 2006. Recommendations of the U.S. Preventive Services Task Force. U.S. Department of Health and Human Services Agency for Healthcare Research and Quality AHRQ publication number 06-0588. Baltimore, MD, USA: Williams & Wilkins; 2006.
Applied nutritional investigation
Height reduction, determined using knee height measurement as a risk factor or predictive sign for osteoporosis in elderly women Daniel Bunout, M.D.a,b,*, Gladys Barrera, R.N.a, María Pía de la Maza, M.D., M.Sc.a, Laura Leivaa, Vivien Gattas, R.D.a, and Sandra Hirsch, M.D., M.Sc.a a
b
INTA, University of Chile, Santiago, Chile Department of Medicine, Central Campus Faculty of Medicine, University of Chile, Santiago, Chile Manuscript received January 8, 2007; accepted August 19, 2007.
Abstract
Objective: We assessed the value of height reduction, calculated using knee height measurement, as a risk factor or predictive sign for osteoporosis in healthy elderly women. Methods: In 181 healthy women 76 ⫾ 5 y of age, height, weight, and knee height were evaluated. Femoral and spine bone mineral densities and body compositions were measured using dual-energy X-ray absorptiometry. In 76 young women 27 ⫾ 4 y of age, a regression equation to predict height, based on knee height, was derived. Using this equation, maximum attained height and height loss were calculated in elderly women, which was correlated to bone mineral density. Results: The equation to predict height was height (cm) ⫽ knee height (cm) ⫻ 2.22 ⫹ 50.54. The calculated height loss in elderly women was ⫺6.1 ⫾ 3.8 cm or ⫺0.08 ⫾ 0.05 cm/y of age. Height loss and hip circumference were significant predictors of spine bone mineral density. In the case of femoral bone mineral density, to the same predictors, a negative effect of waist circumference was added. Women in the highest quintile of height reduction (⬎0.199 cm/y) had an odds ratio of 4.5 (95% confidence interval 1.56 –13.3, P ⬍ 0.02) for femoral osteoporosis. Conclusion: Knee height can be used as an accurate measurement of height loss in the elderly, which is a significant predictor of femur and spine bone mineral densities, in addition to hip circumference. © 2007 Elsevier Inc. All rights reserved.
Keywords:
Osteoporosis; Knee height; Height loss; Hip circumference; Bone mineral density
Introduction Height reduction in the elderly is caused by a decrease in the height of vertebral bodies as a consequence of osteoporosis and disc degeneration. Therefore, this phenomenon is considered a risk factor or predictive sign for the presence of osteoporosis and disc degeneration [1,2]. However, the precise determination of height loss over time is complicated. Selfreports of height reduction are inaccurate and overestimate the true loss [3]. On very few occasions, there is reliable longitudinal information to estimate the reduction and usually the data available are for relatively short lapses, such as ⱕ3 y [4]. Others have used information about height that appears in drivers’ licenses, which can also be inaccurate [5]. This work was financed by Fondecyt grant 1040905. * Corresponding author. Tel.: ⫹56-2-678-1485; fax: ⫹56-2-221-4030. E-mail address: [email protected] (D. Bunout). 0899-9007/07/$ – see front matter © 2007 Elsevier Inc. All rights reserved. doi:10.1016/j.nut.2007.08.012
Another approach to estimate height reduction is the prediction of the maximum attained height, using anthropometric variables. One of the most commonly used measurements is knee height, and several regression equations, in different populations, have been published to predict stature from this measurement [6 – 8]. However, the diversity of regression equations reported indicates that these are dependent on local factors and that the ideal is to measure a representative sample of young subjects to obtain regression values that can be applied with greater accuracy in elderly subjects of the same community. All these regression equations to predict height reduction would be valid only if the knee height/stature ratio remained constant for ⱖ50 y. This study assessed the value of height reduction, calculated using knee height measurement, as a risk factor or predictive sign for osteoporosis in healthy elderly women.
D. Bunout et al. / Nutrition 23 (2007) 794 –797
Materials and methods We studied healthy elderly women living in the community who had participated in research protocols or preventive medical examinations at Instituto de Nutrición y Technologia de los Alimentos (INTA). We excluded women with chronic diseases such as diabetes mellitus, cardiac or renal failure, or malignant tumors, those taking medications that could interfere with bone metabolism (such as steroids or biphosphonate), and those with inadequate cognitive function, defined as a Mini-Mental State score ⬍20 [9]. All signed an informed consent for the specific projects in which they participated, allowing us to use the gathered information. This study was approved by INTA’s ethics committee. All women underwent a comprehensive medical examination performed at INTA, which included the measurement of weight on a digital scale, stature using a wallmounted stadiometer and midarm circumference using an inextensible and flexible tape. Knee height (the distance from the heels to the thigh, above the femoral condyles, next to the patella) was measured using a Ross caliper with a non-fixed base in the sitting position, with the legs bent at a 90-degree angle. Right quadriceps strength was measured on a quadriceps table and expressed in kilograms. Bone mineral density (BMD) at the spine and femoral neck and body composition was measured using a LUNAR Prodigy dual-energy X-ray absorptiometer (General Electric Medical Systems, Madison, WI, USA). The same observers performed all the measurements and the interassay coefficients of variation of the equipment are 0.6% for BMD, 2.9% for boy fat, and 1.4% for lean body mass [10]. Weight, height, midarm circumference, and knee height were also measured in healthy young women of the same socioeconomic level, 21 to 38 y of age, without osteoporosis or taking medications that could interfere with bone metabolism, to obtain a regression equation to predict stature from the measurement of knee height. We considered that, in this age range, these women had ended their growth period and had not developed a significant height reduction. To test if knee height/stature had remained constant in time, we used historical anatomic data reported for subjects
795
living in India in 1924 [11]. The researcher measured height and tibia length in 142 subjects, of whom 56 were women. To account for the height of the thigh and the heel, included in knee height measurements with the caliper, 12 cm was added to the length of the tibia and calculated the ratio between knee height and stature. The same ratio was calculated in the young women included in this study. All statistical analyses were done using STATA 7.0 for Windows (STATA Corp., College Station, TX, USA). Using anthropometric data from young women, a regression equation was derived to predict their stature using knee height. This equation was used among elderly women to calculate their maximum attained stature. The difference between the latter and the actual stature was considered as the height reduction experienced throughout life. The criteria proposed by the World Health Organization were used to diagnose osteoporosis (a BMD ⬍2.5 SDs of the value for a young population of the same ethnic background or a value ⬍1 SD and a history of a non-traumatic fracture) [12]. Concordance between measured and estimated heights in young women was assessed using Pearson’s correlation coefficient and Bland-Altman plots [13]. Results are expressed as mean ⫾ SD. Forward stepwise regressions were used to evaluate the association among multiple variables.
Results We studied 181 elderly women 76 ⫾ 5 y of age and 76 young women 27 ⫾ 4 y of age. Among young women, the regression equation to predict stature was height (cm) ⫽ knee height (cm) ⫻ 2.22 ⫹ 50.54. The predicted stature using the equation had a correlation coefficient of 0.84 and a good concordance with measured height (Fig. 1). The calculated height loss among elderly women, using this equation to predict maximum attained height, was ⫺6.1 ⫾ 3.8 cm or ⫺0.08 ⫾ 0.05 cm/y of age. Femoral and spine BMDs correlated significantly with height loss, body mass index, waist and hip circumferences, fat and fat-free masses, and right quadriceps strength (Table 1). A regression equation using these variables accepted hip circumference and height loss as significant predictors of spine BMD.
Fig. 1. (A) Scatterplot of measured versus estimated stature using knee height and (B) Bland-Altman concordance plot of measured versus estimated height.
796
D. Bunout et al. / Nutrition 23 (2007) 794 –797
Table 1 Correlation between bone mineral density at femur and spine and anthropometry, body composition, and muscle strength Bone mineral density (g/cm2)
Height reduction (cm/y) Body mass index (kg/m2) Waist circumference (cm) Hip circumference (cm) Fat-free mass (kg) Fat mass (kg) Right quadriceps strength (kg)
Femur
Spine
0.34* ⬍0.001† 0.31 ⬍0.001 0.21 0.005 0.47 ⬍0.001 0.34 ⬍0.001 0.38 ⬍0.001 ⫺0.22 0.003
0.25 ⬍0.001 0.28 ⬍0.001 0.27 ⬍0.001 0.41 ⬍0.001 0.25 ⬍0.001 0.34 ⬍0.001 ⫺0.18 0.018
* Pearson’s correlation coefficient. Probability.
†
The predictors for femoral BMD were the above-mentioned variables plus a negative effect of waist circumference (Table 2). Compared with women in the lowest quintile of height reduction (⬍0.035 cm/y), women in the highest quintile (⬎0.199 cm/y) had an odds ratio of 4.5 (95% confidence interval 1.56 –13.3, P ⬍ 0.02) for femoral osteoporosis and an odds ratio of 2.2 (95% confidence interval 0.84 –5.8, P ⫽ 0.1) for spine osteoporosis. The knee height/stature ratios were 0.307 ⫾ 0.001 and 0.304 ⫾ 0.002 in young women studied by us and women from India studied in 1924, respectively (P ⫽ 0.222).
Discussion These results show that height loss, derived from an objective parameter such as knee height, is a risk factor and that a larger hip circumference is protective against osteoporosis in healthy elderly women. Many studies had addressed the usefulness of height reduction as an indicator for osteoporosis but all concluded
that it was difficult to obtain an objective estimate of height loss unless a long-term follow-up was carried out [3–5]. Obviously, this type of longitudinal information is seldom available when elderly subjects are evaluated. Measuring knee height would fill this gap because it is a simple measurement and accurately predicts maximum attained height as shown by the high correlation and concordance between measured and estimated heights. It is important to underscore that the regression equation must be obtained from young subjects because, if it is derived from measurements made in elderly subjects who have lost height, it will be invariably inaccurate. This bias has been observed in several studies that have used knee height to predict stature [14,15]. The association of hip circumference with BMD is not surprising. We and others have previously reported that elderly subjects with a higher body mass index have a significantly lower risk of osteoporosis [16,17], and there is a high correlation between hip circumference and body mass index. The fact that waist circumference did not enter the equation for the spine and had a negative impact on the femur may indicate that fat accumulated in the buttocks is more protective than abdominal fat. However, other investigators have found exactly the opposite, suggesting that android distribution of fat is protective against osteoporosis [18]. Moreover, others have suggested that visceral fat accumulation decreases adiponectin levels, an adipokine that has deleterious effects on bone [19]. There is only one report showing that waist fat accumulation deteriorates bone health [20]. Moreover, waist circumference correlates with low vitamin D levels in elderly subjects and this alteration may also have a deleterious influence on bone mineralization [21]. The odds ratio for femoral osteoporosis increased fourfold in subjects in the highest quintile of stature reduction. However, the odds ratio for the spine was not significant. This may indicate that trabecular (spine) and cortical (femur) bones have different responses to environmental, nutritional, and metabolic mediators of bone metabolism. For example, we previously reported that femoral but not spine BMD improved after a period of supplementation with vitamin D in elderly subjects [22]. Other studies have also reported the same difference between the femur and the
Table 2 Multiple regression models for femur and spine bone mineral density
Femur bone mineral density (R of model ⫽ 0.336) Height reduction (cm/y) Hip circumference (cm) Waist circumference (cm) Constant Spine bone mineral density (R2 of model ⫽ 0.20) Height reduction (cm/year) Hip circumference (cm) Constant
Coefficient
SE
t
P
0.474 0.008 ⫺0.004 0.343
0.139 0.001 0.001 0.071
3.420 6.860 ⫺3.530 4.800
0.001 0.000 0.001 0.000
0.688 0.007 0.307
0.241 0.001 0.126
2.860 5.520 2.440
0.005 0.000 0.016
2
D. Bunout et al. / Nutrition 23 (2007) 794 –797
spine in response to vitamin D [23]. However, this is not the case for biphosphonates, which induce a similar improvement in BMD of the femur and spine [24]. The lack of a significant association between height reduction and spine osteoporosis could also be related to a reduction of the intervertebral disc height due to a degenerative process, which is more marked in untreated menopausal women [25]. Another explanation is that an artifact from sclerotic facets or vertebral compression could have spuriously increased BMD measurements in the spine [26]. The lack of differences in knee height/stature ratio between the young women studied by us and the women from India studied in 1924 confirms that this ratio remains constant not only over time but also in different ethnic groups and further validates the use of knee height to calculate height reduction in elderly subjects.
[9]
[10]
[11] [12]
[13]
[14]
[15]
Conclusion We have identified another predictor for osteoporosis, specifically femoral osteoporosis. Although a universal screening for osteoporosis in persons older than 64 y [27] is recommended, this may not be accomplished in places where health care resources are limited. A stratified screening in such individuals who have developed an important stature reduction or have a small hip circumference could be cost effective.
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