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

Megyesi, Mary S.; Hunt, Linda M.; Brody, Howard

doi:10.1007/s00198-010-1503-z

Cited by 31 publications

(28 citation statements)

References 40 publications

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“…Internationally, previous studies show that demographic and socio-economic characteristics affect the prevalence of the elderly fall (Andersen 2008;Cakar et al 2011;Cauley 2011;Dhanwal et al 2011;Galizia et al 2008;Graham et al 2008;Haan et al 1987;Hokby et al 2003;Jacobsen et al 1992;Kannus et al 1999;Landi et al 2001;Lopata 1982;Luukinen et al 1996;Megyesi et al 2011;Nguyen-Oghalai et al 2009;Penrod et al 2008;Reimers and Laflamme 2007;Sandberg et al 2012;Tinetti et al 1988;Trujillo et al 2011;Van Rossum et al 2000). Based on this literature, it is suggested that counties that have higher rates of falls are expected to be associated with one or more of these factors: lower proportion of nonSwedes, greater proportion of non-active population, larger share of low income earners, and single individuals.…”

Section: Theoretical Background and Hypothesesmentioning

confidence: 91%

“…This ethnic and geographic variation may be explained by differences in genetic factors, lifestyle, behavioral, and environmental characteristics (Dhanwal et al 2010). The relationship between fall incidents and ethnical variations has been reported in a number of studies (Cauley 2011;Megyesi et al 2011;Jacobsen et al 1992;Penrod et al 2008;Graham et al 2008;Nguyen-Oghalai et al 2009;Dhanwal et al 2011). The income of the individual may be another important factor suggested by scholars as an implication for fall-related injuries (Kannus et al 1999;Tinetti et al 1988;Galizia et al 2008;Luukinen et al 1996).…”

Section: Theoretical Background and Hypothesesmentioning

confidence: 91%

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The regional ecology of elderly falls in Sweden

Bamzar

Ceccato

2014

GeoJournal

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The study assesses exploratory the geography of the elderly fall in Sweden in relation to the ecology of the socio-demographic characteristics of the Swedes older population. Kendall Test is used to measure the association between elderly fall rates and demographic, socio-economic characteristics of the population, costs of elderly care and accessibility measures at county level. Results show a number of significant associations: high rates of the elderly fall are associated with high cost of the elderly care but also low rate of elderly fall and good accessibility to basic services (e.g., grocery store, health care and cash machines). The articles finalizes with reflections of the results and suggestions for future research.

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Section: Theoretical Background and Hypothesesmentioning

confidence: 91%

Section: Theoretical Background and Hypothesesmentioning

confidence: 91%

The regional ecology of elderly falls in Sweden

Bamzar

Ceccato

2014

GeoJournal

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“…Many studies have shown that there exists substantial difference in BMD among different ethnic groups and even within a group of the same ethnic origin [135][136][137][138][139]. For example, black men have greater BMD than Hispanic or white men.…”

Section: Racementioning

confidence: 97%

A biomechanical sorting of clinical risk factors affecting osteoporotic hip fracture

Luo

2015

Osteoporos Int

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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.

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“…Assessment of ethnic differences in BMD has recently been the subject of some controversy [26,27]. The strengths of our study include detailed body composition assessment as well as hip and spine BMD measurement.…”

Section: Indigenous Men and Women In This Study Our Finding Of Highementioning

confidence: 99%

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

Maple-Brown

Hughes

Piers

et al. 2012

Bone

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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 (BMDH) and body composition measurements for comparison.Femoral neck (FN) and lumbar spine Z-scores were high in Indigenous participants (mean FN Zscore: Indigenous men +0.98, p<0.0001 vs. mean zero; Indigenous women +0.82, p<0.0001 vs. mean zero). FN BMDH 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

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

Cited by 31 publications

References 40 publications

The regional ecology of elderly falls in Sweden

The regional ecology of elderly falls in Sweden

A biomechanical sorting of clinical risk factors affecting osteoporotic hip fracture

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

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