Rural versus nonrural differences in BMC, volumetric BMD, and bone size: a population-based cross-sectional study

Specker, Bonny; Binkley, Teresa L.; Fahrenwald, Nancy L.

doi:10.1016/j.bone.2004.09.005

Cited by 51 publications

(54 citation statements)

References 31 publications

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“…These findings are in line with previous studies by Specker et al (2004) who found strength as an explaining factor in bone structural differences between rural and non-rural people with comparable body size and with MacDonald et al (2006) who saw a significant effect of muscle cross-sectional area on bone bending and compressive strength indexes in pre-pubertal boys and girls when body size was accounted for by bone length. In our study variables of muscular force production, muscle volume, specific tension and activation level (Fukunaga et al 2001) were used in the regression model to explain bone strength.…”

Section: Discussionsupporting

confidence: 94%

“…From these parameters the specific tension came out as a new predictor variable in addition to the other variables, which have been previously shown to be importantly involved in muscle-bone interplay (Blain et al 2001;Calbet et al 1999;Calmels et al 1995;Ducher et al 2005;Macdonald et al 2006;Nordstrom et al 1996;Pettersson et al 1999;Pettersson et al 2000;Ribom et al 2004;Sandstrom et al 2000;Specker et al 2004;Taaffe and Marcus 2004). The results thus further support the suggestion that appropriate neuromuscular loading is related to bone strength (Burr 1997;Ferretti et al 2003;Frost 2000).…”

Section: Discussionmentioning

confidence: 99%

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Neuromuscular performance and bone structural characteristics in young healthy men and women

et al. 2007

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Muscle mass and strength have been shown to be important factors in bone strength. Low muscular force predisposes to falling especially among elderly. Regular exercise helps to prevent falls and resulting bone fractures. Better understanding of muscle function and its importance on bone properties may thus add information to fracture prevention. Therefore the purpose of this study was to examine the relationship between bone strength and muscular force production. Twenty-young men [24 (2) years] and 20 [24 (3) years] women served as subjects. Bone compressive (BSI(d)) and bending strength indices (50 Imax) were measured with peripheral quantitative computed tomography (pQCT) at tibial mid-shaft and at distal tibia. Ankle plantarflexor muscle volume (MV) was estimated from muscle thickness measured with ultrasonography. Neuromuscular performance was evaluated from the measurements of maximal ground reaction force (GRF) in bilateral jumping and of eccentric maximal voluntary ankle plantarflexor torque (MVC). Specific tension (ST) of the plantarflexors was calculated by dividing the MVC with the muscle volume. Activation level (AL) was measured with superimposed twitch method. Distal tibia BSI(d) and tibial mid-shaft 50 Imax correlated positively with GRF, MVC and MV in men (r = 0.45-0.67, P < 0.05). Tibial mid-shaft 50 Imax and neuromuscular performance variables were correlated in women (r = 0.46-0.59, P < 0.05), whereas no correlation was seen in distal tibia. In the regression analysis, MV and ST could explain 64% of the variance in tibial mid-shaft bone strength and 41% of the variation in distal tibia bone strength. The study emphasizes that tibial strength is related to maximal neuromuscular performance. In addition, tibial mid-shaft seems to be more dependent on the neuromuscular performance, than distal tibia. In young adults, the association between bone adaptation and neuromuscular performance seems to be moderate and also site and loading specific.

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Section: Discussionsupporting

confidence: 94%

Section: Discussionmentioning

confidence: 99%

Neuromuscular performance and bone structural characteristics in young healthy men and women

et al. 2007

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“…This trend, small though it may be, may represent changes in lifestyle over the past 3 generations in this area of the midwestern United States. With a shift from rural to urban life and changes in physical activity and nutrition of young children, we may expect to see a slight change in childhood bone mass [60], which may eventually affect patterns of bone mass in adulthood.…”

Section: Discussionmentioning

confidence: 99%

Quantitative genetics of cortical bone mass in healthy 10-year-old children from the Fels Longitudinal Study

Duren

Sherwood

Choh

et al. 2007

Bone

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The genetic influences on bone mass likely change throughout the life span, but most genetic studies of bone mass regulation have focused on adults. There is, however, a growing awareness of the importance of genes influencing the acquisition of bone mass during childhood on lifelong bone health. The present investigation examines genetic influences on childhood bone mass by estimating the residual heritabilities of different measures of second metacarpal bone mass in a sample of 600 10-year-old participants from 144 families in the Fels Longitudinal Study. Bivariate quantitative genetic analyses were conducted to estimate genetic correlations between cortical bone mass measures, and measures of bone growth and development. Using a maximum likelihood-based variance components method for pedigree data, we found a residual heritability estimate of 0.71 for second metacarpal cortical index. Residual heritability estimates for individual measures of cortical bone (e.g., lateral cortical thickness, medial cortical thickness) ranged from 0.47 to 0.58, at this prepubertal childhood age. Low genetic correlations were found between cortical bone measures and both bone length and skeletal age. However, after Bonferonni adjustment for multiple testing, ρ G was not significantly different from 0 for any of these pairs of traits. Results of this investigation provide evidence of significant genetic control over bone mass largely independent of maturation while bones are actively growing and before rapid accrual of bone that typically occurs during puberty.

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“…The South Dakota Rural Bone Health Study is a 7.5-year population-based longitudinal study of three distinct populations distinguished by lifestyle (Hutterite, rural nonHutterite [NH], nonrural NH) [13]. Both the Hutterite and rural NH populations live a similar rural farming lifestyle, but their social structure is significantly different (Hutterites have a religion-based communal lifestyle).…”

Section: Methodsmentioning

confidence: 99%

“…To be considered nonrural the participant could never have lived on a working farm. Methods for recruiting and enrolling participants are described in greater detail elsewhere [13]. Of the 1271 participants, 585 (226 males) were Hutterite, 350 (184 males) were rural NH, and 336 (134 males) had never lived on an active farm (nonrural).…”

Section: Methodsmentioning

confidence: 99%

Do Sex Differences Exist in Rates of Falls and Fractures in Hutterite, Rural, and Nonrural Populations, Aged 20 to 66 Years?

Weidauer

Binkley

Beare

et al. 2015

Clinical Orthopaedics &Amp; Related Research

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Background Falls and fractures are a major public health concern with an economic impact of more than USD 19 billion per year. Extensive research into the risk of falls and fractures in elderly populations has been performed; however, little is known about fall or fracture risk in younger populations. Additionally, sex-and population-specific (rural versus nonrural) fall and fracture risk may be important in identifying groups most at risk in an effort to develop preventive measures. Questions/purposes The purpose of this study was to determine whether sex and population (rural versus nonrural) differences exist in fall and fracture rates.Methods Data from 1256 (538 men) participants of the South Dakota Rural Bone Health Study, a population-based cohort study, including those living a rural lifestyle (n = 349 non-Hutterites and 572 Hutterites) and a nonrural lifestyle (n = 335), were used to address our a priori hypotheses. Health histories, physical activity recall, anthropometric measurements, and dual-energy xray absorptiometry measurements of body composition were obtained longitudinally from participants every 18 months for 7.5 years. Falls and fractures were self-reported and fractures were confirmed through medical record review. Incidence rates were calculated as the number of falls or fractures per 1000 person-years and generalized estimating equations determined the association of sex and population group with fall and fractures rates while accounting for the repeated longitudinal measurements on the same person. All models adjusted for age group, percent time in moderate and vigorous physical activity, lean and fat mass, grip strength, and previous diagnosis of osteoarthritis. Results Males aged 39 years and younger had a 135% greater fall risk than females in the same age category (p = 0.03), but there was no differences between males and females 40 years of age or older (p = 0.26; age-by-sex interaction, p = 0.05). No sex differences were observed for fracture risk. After controlling for covariates, rural and nonrural individuals fell at higher rates than Hutterites (84% and 50%, respectively, p \ 0.001). Additionally,

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Rural versus nonrural differences in BMC, volumetric BMD, and bone size: a population-based cross-sectional study

Cited by 51 publications

References 31 publications

Neuromuscular performance and bone structural characteristics in young healthy men and women

Neuromuscular performance and bone structural characteristics in young healthy men and women

Quantitative genetics of cortical bone mass in healthy 10-year-old children from the Fels Longitudinal Study

Do Sex Differences Exist in Rates of Falls and Fractures in Hutterite, Rural, and Nonrural Populations, Aged 20 to 66 Years?

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