Race/ethnicity and fracture risk assessment: an issue that is more than skin deep

Bone Mineral Density in Older U.S. Filipino, Chinese, Japanese, and White Women

BACKGROUND/OBJECTIVES

Bone mineral density (BMD) reference data exist for U.S. White, Black, and Hispanic (Mexican American) populations but not for U.S. Asians. Few studies have compared BMD findings among different U.S. Asian ethnicities.

DESIGN

Retrospective observational study.

SETTING

Large northern California healthcare system.

PARTICIPANTS

Asian and White women aged 50 to 79 years with BMD testing from 1998 to 2017 excluding those with estrogen or osteoporosis treatment, recent fracture, or select disorders affecting skeletal health.

MEASUREMENTS

Femoral neck (FN)-BMD and height data.

METHODS

Differences in FN-BMD were examined by ethnicity and age, comparing Filipino, Chinese, and Japanese women and non-Hispanic White women. Differences in BMD were also examined after adjustment for height.

RESULTS

There were 37,224 Asian women (including 11,147 Filipino, 10,648 Chinese, and 2,519 Japanese) and 115,318 non-Hispanic White women. Mean height was similar among the Asian subgroups and about 6 to 8 cm lower than Whites. Mean FN-BMDs differed by less than 3% for Filipino, Chinese, and Japanese and all were lower than Whites, with smaller Asian-White differences among younger women (<3%; ages 50-59) and larger differences among older women (6-8%; ages 65-79). Adjusting FN-BMD for height reduced White-Asian differences by about 30% to 40%.

CONCLUSION

Mean FN-BMD and height for Filipino, Chinese, and Japanese women were similar but consistently lower than White women, especially among older women. Although Asian-White BMD differences were substantially attenuated after height adjustment; some differences persisted for older women. Future studies should investigate potential age-cohort effects and the extent to which these BMD differences influence fracture risk and clinical care.

Fractures in indigenous compared to non-indigenous populations: A systematic review of rates and aetiology

BACKGROUND

Compared to non-indigenous populations, indigenous populations experience disproportionately greater morbidity, and a reduced life expectancy; however, conflicting data exist regarding whether a higher risk of fracture is experienced by either population. We systematically evaluate evidence for whether differences in fracture rates at any skeletal site exist between indigenous and non-indigenous populations of any age, and to identify potential risk factors that might explain these differences.

METHODS

On 31 August 2016 we conducted a comprehensive computer-aided search of peer-reviewed literature without date limits. We searched PubMed, OVID, MEDLINE, CINAHL, EMBASE, and reference lists of relevant publications. The protocol for this systematic review is registered in PROSPERO, the International Prospective Register of systematic reviews (CRD42016043215). Using the World Health Organization reference population as standard, hip fracture incidence rates were re-standardized for comparability between countries.

RESULTS

Our search yielded 3227 articles; 283 potentially eligible articles were cross-referenced against predetermined criteria, leaving 27 articles for final inclusion. Differences in hip fracture rates appeared as continent-specific, with lower rates observed for indigenous persons in all countries except for Canada and Australia where the opposite was observed. Indigenous persons consistently had higher rates of trauma-related fractures; the highest were observed in Australia where craniofacial fracture rates were 22-times greater for indigenous compared to non-indigenous women. After adjustment for socio-demographic and clinical risk factors, approximately a three-fold greater risk of osteoporotic fracture and five-fold greater risk of craniofacial fractures was observed for indigenous compared to non-indigenous persons; diabetes, substance abuse, comorbidity, lower income, locality, and fracture history were independently associated with an increased risk of fracture.

CONCLUSIONS

The observed paucity of data and suggestion of continent-specific differences indicate an urgent need for further research regarding indigenous status and fracture epidemiology and aetiology. Our findings also have implications for communities, governments and healthcare professionals to enhance the prevention of trauma-related fractures in indigenous persons, and an increased focus on modifiable lifestyle behaviours to prevent osteoporotic fractures in all populations.

A biomechanical sorting of clinical risk factors affecting osteoporotic hip fracture

Osteoporotic fracture has been found associated with many clinical risk factors, and the associations have been explored dominantly by evidence-based and case-control approaches. The major challenges emerging from the studies are the large number of the risk factors, the difficulty in quantification, the incomplete list, and the interdependence of the risk factors. A biomechanical sorting of the risk factors may shed lights on resolving the above issues. Based on the definition of load-strength ratio (LSR), we first identified the four biomechanical variables determining fracture risk, i.e., the risk of fall, impact force, bone quality, and bone geometry. Then, we explored the links between the FRAX clinical risk factors and the biomechanical variables by looking for evidences in the literature. To accurately assess fracture risk, none of the four biomechanical variables can be ignored and their values must be subject-specific. A clinical risk factor contributes to osteoporotic fracture by affecting one or more of the biomechanical variables. A biomechanical variable represents the integral effect from all the clinical risk factors linked to the variable. The clinical risk factors in FRAX mostly stand for bone quality. The other three biomechanical variables are not adequately represented by the clinical risk factors. From the biomechanical viewpoint, most clinical risk factors are interdependent to each other as they affect the same biomechanical variable(s). As biomechanical variables must be expressed in numbers before their use in calculating LSR, the numerical value of a biomechanical variable can be used as a gauge of the linked clinical risk factors to measure their integral effect on fracture risk, which may be more efficient than to study each individual risk factor.

Clinical review: Ethnic differences in bone mass--clinical implications

CONTEXT

Differences in bone mineral density (BMD) as assessed with dual-energy x-ray absorptiometry are observed between geographic and ethnic groups, with important implications in clinical practice.

EVIDENCE ACQUISITION

PubMed was employed to identify relevant studies. A review of the literature was conducted, and data were summarized and integrated.

EVIDENCE SYNTHESIS

The available data highlight the complex ethnic variations in BMD, which only partially account for observed variations in fracture rates. Factors contributing to ethnic differences include genetics, skeletal size, body size and composition, lifestyle, and social determinants. Despite BMD differences, the gradient of risk for fracture from BMD and other clinical risk factors appears to be similar across ethnic groups. Furthermore, BMD variation is greater within an ethnic population than between ethnic populations. New imaging technologies have identified ethnic differences in bone geometry, volumetric density, microarchitecture, and estimated bone strength that may contribute to a better understanding of ethnic differences in fracture risk.

CONCLUSIONS

Factors associated with ethnicity affect BMD and fracture risk through direct and indirect mechanisms.

Increased bone mineral density in Aboriginal and Torres Strait Islander Australians: impact of body composition differences

Bone mineral density (BMD) has been reported to be both higher and lower in Indigenous women from different populations. Body composition data have been reported for Indigenous Australians, but there are few published BMD data in this population. We assessed BMD in 161 Indigenous Australians, identified as Aboriginal (n=70), Torres Strait Islander (n=68) or both (n=23). BMD measurements were made on Norland-XR46 (n=107) and Hologic (n=90) dual-energy X-ray absorptiometry (DXA) machines. Norland BMD and body composition measurements in these individuals, and also in 36 Caucasian Australians, were converted to equivalent Hologic BMD (BMD(H)) and body composition measurements for comparison. Femoral neck (FN) and lumbar spine Z-scores were high in Indigenous participants (mean FN Z-score: Indigenous men +0.98, p<0.0001 vs. mean zero; Indigenous women +0.82, p<0.0001 vs. mean zero). FN BMD(H) was higher in Aboriginal and/or Torres Strait Islander than Caucasian participants, after adjusting for age, gender, diabetes and height and remained higher in men after addition of lean mass to the model. We conclude that FN BMD is higher in Aboriginal and/or Torres Strait Islander Australians than Caucasian Australian reference ranges and these differences still remained significant in men after adjustment for lean mass. It remains to be seen whether these BMD differences translate to differences in fracture rates.

A critical review of racial/ethnic variables in osteoporosis and bone density research

Racial and ethnic variables are common in research on variation in bone density. This literature review describes some of the common flaws associated with the use of these variables and provides some suggestions for how bone density research may be able to better document and address skeletal health disparities.

INTRODUCTION

Racial/ethnic differences in bone density have been commonly documented in the research literature. While effective identification of the specific factors underlying these trends might go a long way in informing treatment and screening for osteoporosis, this would require careful consideration of exactly what these variables are capturing. However, the basis and implications of what racial/ethnic variables represent have not carefully been examined in bone density research.

METHODS

For this paper, we systematically reviewed 55 articles that included bone density and race/ethnicity as key variables. Our analysis reveals that racial/ethnic terminology in these articles is highly variable, and discussion of how race/ethnicity is determined is often vague and idiosyncratic. Racial/ethnic variables are being used for a wide range of analytical purposes in statistical tests, which may not be appropriate for such a complex and poorly defined variable.

RESULTS

Many articles attribute racial/ethnic differences in bone mass/bone density to genetic causes, although few studies actually examine genetic data.

CONCLUSION

This analysis indicates that more rigorous examination of what race/ethnicity actually captures, more careful definitions of group labels and the procedures for assigning them, and attention to the limitations of how such variables can reliably be used in data analyses is needed to help address the problems and issues outlined in this review.

Clinical risk factors for recurrent fracture after hip fracture: a prospective study

Additional fractures after hip fracture are common, but little is known about the risk factors associated with these events. We determined the clinical risk factors associated with fracture following a low-trauma hip fracture and whether clinical risk factors for subsequent fracture were modified by zoledronic acid (ZOL). In this post hoc analysis of the HORIZON Recurrent Fracture trial, 2,127 men and women were randomized within 90 days of surgical hip fracture repair to receive intravenous ZOL 5 mg yearly or placebo. All patients received a loading dose of vitamin D and daily oral calcium and vitamin D supplements. In the multivariable model age, sex, BMI, femoral neck T score, and one or more fall risk factors were significant predictors of subsequent fracture. Race, history of prior fracture other than the index hip fracture, T score < -2.5 as a dichotomous variable, and type of index hip fracture were not associated with a different risk of subsequent fractures. Treatment with ZOL did not modify the impact of these risk factors. Well-established risk factors for fracture risk such as age, sex, BMI, and fall risk factors will also contribute to fracture risk in patients who have already suffered a hip fracture, while other prior fractures and T score < -2.5 are not predictive of subsequent fractures. Baseline risk factors in hip fracture patients were predictive of fracture in both ZOL- and placebo-treated participants, and there is no difference in the risk of subsequent fractures based on index hip fracture type.

Guidelines for the diagnosis of osteoporosis: T-scores vs fractures

The development of bone mineral densitimometry methodologies, especially central dual energy X-ray absorptiometry (DXA) methods have allowed this quantitative tool to be used to diagnose osteoporosis before the first fragility fracture has occurred. The World Health Organization osteoporosis working group set the stage for the BMD cut-off criteria development. The wide application of DXA has brought the treatment of osteoporosis to the primary care level, a very necessary step if this increasingly prevalent disease is to have a decline in its incidence. The most difficult osteoporosis cases, for which there are many and their associated difficult DXA results and interpretation will always require specialists' involvement. In particular, the embracement of the WHO absolute fracture risk validated project will take DXA to a much greater level of value in making management decisions. In particular, the WHO absolute risk data will allow physicians, health-economic policy makers, and payors of medical services to come closer together to decide which patients are at a level of unacceptable fracture risk that justifies treatment intervention. The implementation of this validated project will also remove the unacceptable subjective computer printouts on DXA reports that often lead to the over-treatment of low risk patients and at times the under-treatment of high risk patients. The evolution of the clinical interpretation of bone densitometry has been a work in progress. Challenges in the clinical measurement of bone strength remain and will also evolve. The field of osteoporosis has grown with the use of DXA and will continue to embrace this technology as other technologies to measure fracture risk become applied in clinical practice.