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Musculoskeletal phenotype through the life course: the role of nutrition

Published online by Cambridge University Press:  05 December 2011

Kate Ward*
Affiliation:
MRC Human Nutrition Research, Elsie Widdowson Laboratory, 120 Fulbourn Road, Cambridge CB1 9NL, UK
*
Corresponding author: Dr Kate Ward, fax +44 1223 437515, email kate.ward@mrc-hnr.cam.ac.uk
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Abstract

This review considers the definition of a healthy bone phenotype through the life course and the modulating effects of muscle function and nutrition. In particular, it will emphasise that optimal bone strength (and how that is regulated) is more important than simple measures of bone mass. The forces imposed on bone by muscle loading are the primary determinants of musculoskeletal health. Any factor that changes muscle loading on the bone, or the response of bone to loading results in alterations of bone strength. Advances in technology have enhanced the understanding of a healthy bone phenotype in different skeletal compartments. Multiple components of muscle strength can also be quantified. The critical evaluation of emerging technologies for assessment of bone and muscle phenotype is vital. Populations with low and moderate/high daily Ca intakes and/or different vitamin D status illustrate the importance of nutrition in determining musculoskeletal phenotype. Changes in mass and architecture maintain strength despite low Ca intake or vitamin D status. There is a complex interaction between body fat and bone which, in addition to protein intake, is emerging as a key area of research. Muscle and bone should be considered as an integrative unit; the role of body fat requires definition. There remains a lack of longitudinal evidence to understand how nutrition and lifestyle define musculoskeletal health. In conclusion, a life-course approach is required to understand the definition of healthy skeletal phenotype in different populations and at different stages of life.

Type
70th Anniversary Conference on ‘Vitamins in early development and healthy aging: impact on infectious and chronic disease’
Copyright
Copyright © The Author 2011

Abbreviations:
BMC

bone mineral content

BMD

bone mineral density

CSMA

cross-sectional muscle area

25(OH)D

25-hydroxy-vitamin D

DXA

dual energy X-ray absorptiometry

QCT

quantitative computed tomography

A healthy bone is one that is fit-for-purpose, has mechanisms for maintenance and repair, is responsive to changes in musculoskeletal environment and will not fail during normal physiological activities. To assess bone health, measures have been developed to quantify the amount of mineral within the bone (bone mineral density (BMD) or bone mineral content (BMC)). However, it has become increasingly important to move beyond a definition of bone health only in terms of BMD/BMC to one of ‘optimal bone strength’ that encapsulates the contributions from multiple components such as bone shape and size, internal structure and metabolism and loading conditions( Reference Prentice 1 ). Bone strength in later life may depend on optimal skeletal growth and development during childhood, adolescence and reproduction. Over the last decade the focus of research in human bone strength has altered to include early life and childhood in addition to aging, and to prevention rather than treatment of bone disease. Bone strength may be compromised at different times in the life-course (Fig. 1). It is during periods of rapid growth that the developing skeleton is at most risk. Conditions that may manifest during childhood are rickets (failure of mineralisation of the growing bone) and osteomalacia (weak and soft bones), low trauma fractures and stunting (failure or delayed longitudinal growth). Peak bone strength is reached at the end of longitudinal growth. In young adulthood, bone is in a steady state of maintenance with no net loss or gain of strength. The menopause and aging in women and aging in men lead to bone loss and increased susceptibility of the skeleton to fragility fracture (osteoporosis); osteomalacia is also a common disease of the elderly. The aim of this review is to consider the definition of a healthy bone phenotype through the life course and the modulating effects of muscle function, Ca, vitamin D and other nutritional factors.

Fig. 1. A conceptual diagram of bone health through the life course: the solid line denotes male, dashed female and dotted the consequence of not achieving peak bone strength at the end of development.

Definition of healthy skeletal phenotype

Changes in biomechanical environment through the life-course require bone to be a dynamic, modifiable tissue capable of sensing and responding to these changes. As muscles contract and relax, the bone is loaded, which changes the shape and length of the bone and induces strain. Strain is defined as the change in length divided by original length of the structure. It is generally accepted that a change in bone strain is one of the key mechanisms for adapting skeletal mass and architecture so that the skeleton is as light as possible for normal daily activities with a sufficient margin of error to avoid failure (fracture). During a 24 h period, the bone is subjected to a characteristic range of strains of defined magnitude and is adapted to this range( Reference Rubin 2 , Reference Frost 3 ). Strain sensing cells (osteocytes) detect any changes in strain outside of the ‘steady state’ and drive bone gain (modelling by osteoblasts) or loss (resorption by osteoclasts) in response to this. Where no gain or loss is necessary, a steady state is maintained through remodelling, a balance of osteoblast and osteoclast activity. The mechanostat describes the mechanism by which bone strength is maintained as ‘fit-for-purpose’ for daily living (Fig. 2)( Reference Frost 3 ). Together, the response of the mechanostat to muscular loading and/or external modulators, form a functional model of bone development and aging, referred to in this review as the mechanostat model( Reference Frost 4 , Reference Frost 5 ). Nutrition and lifestyle factors are key examples of external modulators and interact with the mechanostat model through muscle and bone (Fig. 2).

Fig. 2. A summary diagram of the Mechanostat model: the grey boxes indicate non-mechanical factors, including nutrition, and where they may interact with the Mechanostat. These interactions may be through alterations in the ability of muscle to generate forces (load), the bone ability to detect or respond to changes in load. For example, vitamin D causes proximal muscle weakness, which would reduce loading to bone and from this ‘sub-optimal’ bone accretion or increased bone loss may occur. At the bone level, vitamin D causes under-mineralisation of bone which would change the way it responds to loading. Both of these examples would result in changes in bone phenotype and strength. Adapted from Frost( Reference Frost 3 ).

The mechanostat model describes how bone strength is modified in response to changes in strains. The four main determinants of bone strength are (i) material properties, (ii) bone mass, (iii) structural (shape and geometry) design and (iv) the loading conditions (including the direction of load) to which the bone is subjected.

Material properties: A bone is composed of organic and inorganic matter, collagen and ground substance (osteoid) and mineral (hydroxyapatite), respectively. The ratio and arrangement of osteoid and hydroxyapatite determine the mechanical quality, or stiffness, of bone and describes the ability to withstand strain without permanent deformation or damage, i.e. an elastic material. The material properties also determine bone toughness, which describes the energy required to break the bone( Reference Currey 6 ).

Fig. 3 illustrates how stiffness contributes to the bone phenotype. Changes in stiffness of the bone alter the elastic, plastic and fracture thresholds of the bone. Nutrition, lifestyle status or certain conditions may change the stiffness of a bone. For example, in severe vitamin D deficiency there is bone formation without adequate mineralisation and the bone deforms easily due to low stiffness. Toughness is high compared to a healthy bone, meaning more energy would be required to break the bone. The structural changes in response to low stiffness are driven by overestimation by the mechanostat of the loads applied. Increases in cross section are required to maintain the bone strains within the elastic range and not cause damage. In contrast, excessive mineralisation increases stiffness and decreases toughness, creating a brittle structure( Reference Rauch 7 ). In this situation, strains are underestimated by the mechanostat; as the material is not able to deform to the same degree as the healthy bone the cross section is smaller than a bone with ‘healthy stiffness’ (Fig. 3). An analogy would be two tubes of pasta, one cooked and one uncooked, if the same load were applied to each the cooked tube would deform easily (overestimation of load by mechanostat), while the uncooked tube would break easily (underestimation of load by mechanostat).

Fig. 3. Schematic stress–strain curve to demonstrate how phenotype may respond to changes in stiffness: the solid line denotes a healthy skeleton 1. Elastic portion of the curve where load does not permanently deform the bone or induce damage, 2. Plastic region where damage is starting to accumulate, Fx=fracture load; note there is a long period before the fracture load is reached under normal circumstances. The dash-dot line is a bone with high stiffness (mechanostat underestimates loads from muscle) and the dotted line is low stiffness (mechanostat overestimates loads from muscle); note the differing length of the elastic and plastic regions in each of these situations.

Bone mass: It is the amount of matter within the whole bone (i.e. collagen, mineral and extracellular fluid). By definition mass is the product of volume (cm3 or mm3) and density (g/cm3 or mg/mm3). The ‘mineral mass’ or BMC (g or mg/mm) is the amount of mineral within the tissue and is quantified by bone measurement techniques that are discussed later.

Structural properties: The shape, spatial distribution and internal organisation of the bone are also important determinants of strength. The different bone compartments adapt in different ways to increase, maintain or lose strength throughout the life course( Reference Garn, Poznanski and Nagy 8 Reference Seeman 11 ). The observed sexual dimorphism in the changes in structure are thought to explain differences in fracture rates in males and females and have evolutionary significance for the demands of pregnancy, lactation, menopause and aging( Reference Seeman 11 Reference Riggs, Melton and Robb 13 ).

For cortical bone, the further away that bone mineral is distributed from the axis of the bone, the greater the strength. Therefore, two long bones of differing cross-sectional area with identical amounts of mineral distributed in different ways will have markedly different moments of inertia, or resistance to bending, which are proportional to the radius of the cross section of bone. Redistribution of mineral within bone when cross-section remains the same may also increase bone strength, but to a lesser degree.

In trabecular bone, the arrangement and interconnectivity of the trabeculae are important for strength. Trabeculae thicken and change orientation during growth and development. As trabecular bone is lost during aging, the most supporting trabeculae to the direction of load are maintained to prevent fracture for as long as possible, for example, trabeculae in the vertebrae, radius or tibia( Reference Jensen, Mosekilde and Mosekilde 14 , Reference Liu, Walker and McMahon 15 ).

Loading conditions: Increases or decreases in muscle strength will drive a modification of bone by the mechanostat. For example, during growth, peak height velocity is followed by peak muscle mass velocity and then peak bone mineral accumulation; during aging, declining muscle function precedes bone loss.

Imaging and musculoskeletal phenotype

The direct measurement of bone strength, resistance to fracture load, is not possible in vivo. Quantification of the skeleton using imaging is thus based upon measurement of parameters related to bone strength. Currently, the most common measurements are BMD or BMC, which only act as proxies for bone strength, but are related to fracture risk in populations at high risk of fracture( Reference Clark, Ness and Bishop 16 Reference Goulding, Jones and Taylor 18 ).

When using imaging methods to measure the skeleton, it is important to consider the measurements being taken and the information they actually provide about the bone as an organ both as a whole and constituent compartments. BMD, by definition, is the mass of mineral divided by volume (g/cm3). There are two types of BMD that can be measured in vivo: BMDTOTAL measures everything within the periosteal envelope, including bone marrow, cortical and trabecular bone; BMDCOMPARTMENT is the BMD of the separate compartments of bone, for cortical bone this includes the pores and Haversian canals, for trabecular bone this also includes bone marrow( Reference Rauch and Schonau 19 ).

As a two-dimensional measurement, dual energy X-ray absorptiometry (DXA) estimates both areal BMDTOTAL (g/cm2) of the axial and peripheral skeleton and BMDCOMPARTMENT of cortical bone at sites where little trabecular bone is present, e.g. midshaft femur and radius. DXA cannot take into account the depth of the bone and data acquired are thus size dependent; considerations must be made when using the technique in the growing skeleton and when measuring populations which may differ in size( Reference Prentice 1 , Reference Crabtree and Ward 20 , Reference Prentice, Schoenmakers and Laskey 21 ). DXA images have vastly improved in quality in recent years and the method now provides assessment of vertebral fracture, bone structure and detailed body composition.

Areal BMDTOTAL by DXA has been used for many years as a predictor of fracture risk and diagnosis of osteoporosis, predominantly based on evidence in post-menopausal populations. The method is now used in males, pre-menopausal females and children and is considered the gold standard in terms of clinical practice. However, there are limitations to DXA both for clinical and research applications( Reference Prentice 1 , Reference Crabtree and Ward 20 , Reference Gordon, Bachrach and Carpenter 22 , Reference Lewiecki, Gordon and Baim 23 ). Clinically, not all people with fracture have low BMDTOTAL or BMC indicating that factors other than bone mass are important( Reference Wainwright, Marshall and Ensrud 24 ). More recently, an audit of fracture cases in UK showed obese people who fracture do not have a low BMDTOTAL ( Reference Premaor, Pilbrow and Tonkin 25 ). Research in females from The Gambia and China found that they had low BMDTOTAL/BMC in comparison with an age-matched UK population, yet these populations are known to have lower fracture risk( Reference Aspray, Prentice and Cole 26 , Reference Yan, Crabtree and Reeve 27 ). The Gambian population still had lower BMC after adjustment for their smaller bone size and lower body weight, contradicting the assumption that low BMDTOTAL equals higher fracture risk( Reference Aspray, Prentice and Cole 28 ). Therefore, although DXA measures of BMC/BMDTOTAL are strong predictors of fracture risk in older people and children in populations at high risk of osteoporosis these measures are of limited value in different populations and at different times of life.

Quantitative computed tomography (QCT) is a three-dimensional technique providing size-independent measures of volumetric BMD (g/cm3). QCT is the forerunner in three-dimensional assessment of the axial and peripheral skeleton being the only technique to measure volumetric BMDTOTAL and BMDCOMPARTMENT of trabecular and cortical bone. QCT also provides measures of multiple components of cortical and trabecular bone (shape and geometry), which allow the measurement of some parameters of bone strength( Reference Boutroy, Bouxsein and Munoz 29 Reference Krug, Burghardt and Majumdar 36 ). The use of QCT to measure the spine and hip is limited due to radiation dose considerations and accessibility of scanners; although radiation dose is considerably less than diagnostic computed tomography( Reference Cann 37 Reference Genant, Cann and Ettinger 39 ). The invention of peripheral (p) QCT and more recently high-resolution pQCT, has led to wider application of QCT to define phenotype including assessment of trabecular microarchitecture and metaphyseal cortical bone( Reference Burghardt, Buie and Laib 35 , Reference Krug, Burghardt and Majumdar 36 , Reference Macdonald, Nishiyama and Kang 40 Reference Schneider, Reiners, Genant, Guglielmi and Jergas 42 ).

The utility of axial and peripheral QCT has been shown in studies investigating differences in bone phenotype related to nutrition, aging, hormone status, chronic disease and treatment, i.e. the external modulators of bone and muscle; DXA has not always had the sensitivity to such detect differences( Reference Poole, Mayhew and Rose 34 , Reference Ward, Roberts and Adams 43 Reference Laskey, de Bono and Zhu 47 ). The agreement between DXA and QCT is generally poor( Reference Grampp, Genant and Mathur 48 , Reference Kroger, Lunt and Reeve 49 ). This is due to the ability of each technique to measure estimated or actual BMDTOTAL and BMDCOMPARTMENT; different patterns of regional bone loss (e.g. spine v. hip); and the disease-specific effects on bone compartments. The selection of scan site and measurement method is therefore extremely important when designing study protocols.

Body composition: Muscle strength is a composite term and is determined by muscle mass (e.g. volume, composition, fibre number and size) and structure (e.g. fibre type and pennation angle), which in turn determine force-generating capacity and power. Muscle force is a measure of the load applied to bone, whereas power is a measure of function( Reference Runge, Rittweger and Russo 50 , Reference Fricke, Weidler and Tutlewski 51 ). A full assessment of body composition methodology, particularly the measurement of muscle mass, density and function, is beyond the scope of this review. Lean tissue mass by DXA and cross-sectional muscle area (CSMA) from pQCT or MRI have been used as proxies for muscle strength in a similar way to BMD/BMC being proxies for bone strength. The acquisition of data at the same time as skeletal assessment is a particular advantage of these techniques, yet the sensitivity of measurement of muscle mass or CSMA to detect changes in muscle function has been questioned( Reference Runge, Rittweger and Russo 50 , Reference Ward, Pye and Adams 52 , Reference Ward, Das and Roberts 53 ). For example, CSMA measured by pQCT showed less decline with age than functional tests such as chair rising and jumping mechanography (which measures lower-limb muscle function using a ground reaction force platform)( Reference Runge, Rittweger and Russo 50 ). Infiltration of muscle with fat is another reason for the lack of sensitivity of CSMA or lean mass measurements. For example, CSMA by pQCT did not change in response to vitamin D supplementation, whereas lower-limb power improved, likely due to changes in intramuscular fat not being detected by CSMA measurements( Reference Ward, Das and Roberts 53 ). Measurement of intramuscular fat is possible with some techniques and may provide vital information regarding muscle development and aging and the effects of nutrition( Reference Lang, Cauley and Tylavsky 54 Reference Gilsanz, Kremer and Mo 56 ).

In summary, measurements of BMD/BMC provide information about the amount of mineral within a given volume or area of bone and thus provide some indication of bone strength. However, bone strength is also determined by shape, geometry and loading conditions. The separate measurement of cortical and trabecular bone compartments in respect of all these aspects of bone strength is important to fully understand the definition of a healthy bone phenotype. This requires technologies that move beyond BMC/BMD by DXA. The critical evaluation of the existing and newer technologies for assessing bone and muscle in vivo is a research priority in order to fully determine their potential, appropriate use and interpretation.

Nutrition and musculoskeletal health though the life course

The dietary factors and lifestyle determinants that have been associated with bone strength and with longitudinal growth include the bone-forming minerals (Ca, P, Mn and Zn); vitamins involved in Ca–P homoeostasis and/or bone metabolism (e.g. vitamins D, K and C); energy, amino acids and ions (e.g. Cu, Mn, CO3 and citrate)( Reference Prentice, Ward and Schoenmakers 57 ). Either the bone matrix and composition is altered (Ca, P, vitamin D, vitamin C and vitamin K) or deficiencies in single nutrients or food groups result in poor bone development and longitudinal growth (e.g. protein, Ca and Zn)( Reference Prentice 1 , Reference Prentice and Bates 58 ). The majority of these nutrients are also associated with muscle strength, including protein and vitamin D( Reference Pfeifer, Begerow and Minne 59 Reference Heaney and Layman 61 ). There is also emerging evidence for an interaction between the musculoskeletal system and adipose tissue( Reference Premaor, Pilbrow and Tonkin 25 , Reference Dimitri, Wales and Bishop 62 Reference Skaggs, Loro and Pitukcheewanont 64 ).

Therefore, nutrition may influence bone strength at several points in the mechanostat model through changes in muscle strength, longitudinal growth, bone stiffness and consequent response to strain or through the function of the cells which drive the response (Fig. 2)( Reference Frost 5 ). Most of the evidence of the effects of nutrition on bone strength is for Ca and/or vitamin D. Protein intake and adiposity are emerging areas of research. These four areas will be the focus of this review.

Ca

Ca is the most abundant bone-forming mineral in the diet. As such, the role of Ca, in the tempo of bone growth and development, and the timing and level of peak bone strength, has been widely studied( Reference Prentice, Schoenmakers and Laskey 21 , Reference Heaney, Abrams and Dawson-Highes 65 ). The assumption that increased dietary Ca intake translates into sustained benefit for bone health has been challenged by the many published supplementation trials( Reference Prentice 1 , Reference Lambert, Eastell and Karnik 66 Reference Specker, Binkley and Fahrenwald 69 ). There are several reasons for this. Increased Ca may temporarily increase BMD/BMC through a slowing of bone turnover known as a remodelling transient. The transient effect is related to the amount of mineral being quantified by DXA or QCT. Slowing of bone turnover would result in fewer bone sites undergoing resorption and more mineralised or mature bone being measured, temporarily increasing BMD/BMC. When normal bone turnover resumes, the increased number of bone sites undergoing resorption and the less mineralised new immature bone would result in a lower BMD/BMC( Reference Prentice, Schoenmakers and Laskey 21 , Reference Lambert, Eastell and Karnik 66 ). Secondly, evidence from a pQCT study showed extra Ca may be deposited on the endosteal surface; once the source of Ca was removed the effect was lost( Reference Specker, Binkley and Fahrenwald 69 ). If extra Ca was required to increase bone strength, bone would be laid down on periosteal not endosteal surface. Finally, the type of supplementation is crucial for the maintenance of effects whereby Ca salts do not always provide sustained changes in bone and dairy sources of Ca show lasting benefit( Reference Prentice, Schoenmakers and Laskey 21 , Reference Eastell and Lambert 70 Reference Cadogen, Eastell and Jones 72 ). It is important to note, dairy sources also contain growth factors such as insulin-like growth factor 1 and protein and therefore the observed effects of the intervention might be through increases in intakes of all of these factors rather than Ca per se ( Reference Prentice, Schoenmakers and Laskey 21 ). The assessment of whole diet rather than single nutrients is important to determine relative contributions of the single nutrients. Combined benefits of Ca and physical activity interventions have been found at some skeletal sites( Reference Specker 73 Reference Prentice, Stear and Ginty 75 ), but again there is lack of evidence for maintenance of effect of the Ca supplement, whereas physical activity effects remain once the intervention stops( Reference Specker, Binkley and Fahrenwald 69 ). These observations of a sustained effect of childhood physical activity on bone are consistent with the studies of adults( Reference Bass, Pearce and Bradney 76 Reference Kontulainen, Kannus and Haapasalo 79 ).

The majority of evidence for the association between a high Ca intake and greater BMD is based on studies from countries with moderate to high Ca intake. Low Ca intake is characteristic of some population groups. Increasing Ca intake from 300 to 700 mg/d increased BMC and size adjusted BMD, but not bone width (perhaps indicating deposition of Ca on endosteal surface), growth rate or pubertal stage in a group of Gambian children( Reference Dibba, Prentice and Ceesay 80 ). Bone turnover was reduced and parathyroid hormone lowered in the Ca group, indicative of a bone remodelling transient effect( Reference Prentice, Burckhardt, Dawson-Hughes and Heaney 81 ). However, after a year, the differences in size-adjusted BMC remained despite normalisation of bone turnover( Reference Dibba, Prentice and Ceesay 82 ). These data suggest a sustained effect of Ca salt on the skeleton; if, as the continued suppression of parathyroid harmone levels suggest, there is permanent disruption of the adaptation to low Ca intake in these children, this may not be beneficial for future growth and development( Reference Prentice, Burckhardt, Dawson-Hughes and Heaney 81 ).

The long-term role of Ca in skeletal health in adults with low Ca intakes has also been challenged by previous studies from The Gambia( Reference Aspray, Prentice and Cole 28 , Reference Aspray, Yan and Prentice 83 ). In an older population of Gambian women, significant age-related decreases in lumbar spine BMC were observed; these were of similar magnitude to those in Western populations( Reference Aspray, Prentice and Cole 28 ). Differences in body segment proportions (lower ratio of sitting:standing height) and bone biochemistry (increased parathyroid hormone in response to low Ca intake) were proposed as possible explanations for the lower incidence of fracture in Gambian women( Reference Aspray, Prentice and Cole 26 ). Another explanation is provided in Fig. 4(a), which illustrates how phenotype may alter, to maintain strength in response to long-term low Ca intake. Pre-menopausal Gambian females had lower BMC and thinner cortices, yet higher cortical BMD and rounder bones in comparison with a group of age-matched UK women( Reference Laskey, de Bono and Zhu 47 ). These data illustrate discrepancies between measurements by DXA and pQCT, DXA measures lower aBMDTOTAL in spine and forearm, whereas pQCT measured higher cortical BMDCOMPARTMENT. Despite the differences in geometry and lower BMC, there were no differences in bone strength; in the long term these data may explain lower fracture risk in the Gambian population. Causality cannot be inferred from these cross-sectional data; however, they highlight the importance of using techniques to measure more than BMD/BMC when exploring population differences.

Fig. 4. Overview of how nutrition may alter phenotype at age of peak bone strength: (a) low Ca intake – comparing Gambian to European Caucasian tibia; (b) vitamin D status – comparing British Asian compared to European Caucasian radius. The table summarises the differences. vBMD, volumetric bone mineral density; BMC, bone mineral content; Med area, medullary area; Cort thk, cortical thickness; SSI, bone strength.

Vitamin D

Vitamin D has a role in Ca homoeostasis and skeletal mineralisation through endocrine effects on bone, intestine and kidney. Vitamin D also promotes protein synthesis and Ca and PO4 transport in muscle, thus influencing muscle strength( Reference Pfeifer, Begerow and Minne 59 ). Given these multi-factorial effects, vitamin D may interact with the mechanostat model at multiple levels (Fig. 2): directly, through bone mineralisation and muscle strength; and, indirectly, through decreases in physical activity due to muscle weakness and fatigue caused by deficiency. Through these mechanisms vitamin D may have a role in prevention of falls and subsequently fractures in older people, although evidence does not conclusively support this( Reference Bischoff-Ferrari, Dawson-Hughes and Staehelin 84 86 ).

The possible implications of poor vitamin D status for long-term musculoskeletal health and rising incidence of vitamin D deficiency in teenagers in the UK prompted a study into the effects of vitamin D supplementation in adolescent South-Asian girls in Manchester( Reference Ward, Das and Roberts 53 , Reference Das, Crocombe and McGrath 87 ). Over 60% had serum 25-hydroxy-vitamin D (25(OH)D) levels less than 25 nmol/l( Reference Das, Crocombe and McGrath 87 ). 25(OH)D is a measure of an individual's vitamin D status, 25 nmol/l is the current cut-off for serum 25(OH)D level to prevent the occurrence of rickets and osteomalacia. Despite this, none had symptoms associated with vitamin D deficiency, although muscle function was related to 25(OH)D status( Reference Ward, Das and Berry 60 ). After supplementation with ergocalciferol 3579 μg ((150 000 IU) every 3 months equivalent to 35 μg (1400 IU) per day), 25(OH)D levels rose from 18 to 56 nmol/l. However, there were no effects on BMD/BMC, geometry or strength( Reference Ward, Das and Roberts 53 ). Muscle function improved, with greater response in those who had the lower baseline 25(OH)D. In general, the evidence for positive effects of increases in serum 25(OH)D on the developing musculoskeletal system is inconclusive( Reference Ward, Das and Roberts 53 , Reference El-Hajj Fuleihan, Nabulsi and Tamim 88 , Reference Winzenberg, Powell and Shaw 89 ). The baseline 25(OH)D levels, timing and dose of intervention could be crucial for sustained, positive effects( Reference Ward, Das and Roberts 53 , Reference El-Hajj Fuleihan, Nabulsi and Tamim 88 Reference Molgaard, Larnkjaer and Cashman 90 ).

Fig. 4(b) illustrates how low vitamin D status may contribute to bone phenotype through the life course. South Asians had lower volumetric BMD, BMC and cortical thickness compared to age-matched Caucasians. The South Asians had slightly larger bones suggesting that the bone mineral was distributed further from the bone axis. The consequence of this was that despite lower BMC in South Asians, bone strength was not different between the groups( Reference Ward, Roy and Pye 46 ). Longitudinal data are required to confirm these observations and the multi-factorial role of vitamin D status on the mechanostat model.

Protein

Dietary protein intake has been shown to have positive associations on bone and muscle by increasing serum insulin-like growth factor 1, Ca absorption and bioavailability( Reference Prentice 1 , Reference Heaney and Layman 61 , Reference Surdykowski, Kenny and Insogna 91 ). During childhood and adolescence these positive associations may be through effects on growth or mineral acquisition( Reference Prentice 1 , Reference Bonjour 92 , Reference Ginty 93 ). Reductions in protein intake during aging have been linked to loss of muscle mass and an increased number of falls, both of which contribute to fracture risk( Reference Heaney and Layman 61 , Reference Ginty 93 ). In contrast, animal protein may promote an acidic environment, which may lead to bone loss through CaPO4 being released as a buffer( Reference Prentice 1 , Reference Ginty 93 ). Consistent with this, large amounts of animal and dairy protein have been associated with increased risk of hip fracture( Reference Heaney and Layman 61 , Reference Chevalley, Bonjour and Ferrari 94 ). The complexity of the differential effects of the type of dietary protein and how they interact with bone and muscle at different times during life requires further study.

Adiposity

Although low body weight, including anorexia nervosa, is well recognised as a strong risk factor for fracture, and higher body weight associated with protection, there is emerging evidence that obesity may also be a risk factor for fracture( Reference Premaor, Pilbrow and Tonkin 25 , Reference Dimitri, Wales and Bishop 62 ). The rising levels of obesity and evidence for an interaction between skeletal and adipose tissue is of increasing importance within musculoskeletal research( Reference Premaor, Pilbrow and Tonkin 25 , Reference Dimitri, Wales and Bishop 62 , Reference Goulding, Grant and Williams 63 , Reference Reid 95 , Reference Rosen and Bouxsein 96 ).

The amount and distribution of the adipose tissue are important in determining fracture risk in children and adults, with visceral rather than subcutaneous fat being a risk factor for fracture( Reference Gilsanz, Chalfant and Mo 97 ). The interaction between adiposity and other nutrition and lifestyle components, for example, vitamin D status, gives added complexity to the understanding of the relationship between adipose tissue, muscle and bone.

Adipokines are the secretory products of adipose tissue; adiponectin is inversely and leptin positively related to fat mass( Reference Reid 95 ). The potential role of circulating adipokines in fracture risk has not been clearly described or elucidated. The majority of evidence is for positive associations between leptin and BMD/BMC, which would support the observations that higher body weight (greater fat mass) is protective of the skeleton. Other studies suggest leptin acts as a marker of fat mass with little extra independent effect on the bone. However, infusion of leptin into the central nervous system of leptin deficient and wild-type mice-induced bone loss( Reference Reid 95 , Reference Dimitri, Wales and Bishop 98 ). Recent data from our group showed negative associations between skeletal shape, geometry and strength and leptin, independently of fat mass( Reference Ward, Webb and Prentice 99 ). Higher circulating leptin was associated with smaller bones, thinner cortices and lower strength. These data provide supporting evidence for increased fracture risk in overweight or obese individuals, irrespective of BMD/BMC. Adiponectin, a marker of insulin sensitivity, was negatively related to body mass, BMD and bone shape. This is supported by work from other groups and may explain increased fracture risk in low-body-weight individuals( Reference Barbour, Zmuda and Boudreau 100 , Reference Sayers, Timpson and Sattar 101 ). Longitudinal data are required to substantiate these observations.

In summary, Ca and vitamin D have been the most widely studied nutrients but many questions remain unanswered to be able to define how Ca intake or vitamin D status over the long term may determine bone and muscle phenotype in later life. The inclusion of follow-up measurements after cessation of Ca or vitamin D supplementation is vital to understand whether effects of an intervention are sustained. Longitudinal bone, muscle, dietary and/or biomarker data (e.g. 25(OH)D status) are required to understand how and where nutrition may contribute to the relationship between muscle and bone. Fat and bone have a complex inter-relationship with multiple pathways implicated; these require confirmation in human studies. Including the effects of adipose tissue in the mechanostat is an important focus moving forward.

Perspectives on future research

The preceding section illustrates how differences in dietary intake and lifestyle may challenge the ability of the mechanostat to successfully modify bone strength to cope with daily physiological demands. Current evidence highlights the need to define phenotype at different stages of life and in different populations. For nutrition and the mechanostat model, there is an inconsistency of evidence between males and females, age groups, limited data for muscle and many studies do not investigate the interactive effects on muscle and bone. One reason for this may be the reliance on studying the effects of single nutrients rather than taking a whole diet approach. In comparison with analysing individual foods and nutrients, dietary patterns have the advantage of taking account of total food intake and the potential synergies between foods and nutrients consumed together. Furthermore, public health messages about overall dietary patterns may be easier for the public to interpret.

Moving forward, there is therefore a need to understand how the interaction between muscle and bone drives bone development and aging, to identify factors that modulate this, and to obtain more detailed characterisation of a healthy skeletal phenotype using existing and novel technology. The following text provides an overview of the author's research approach within the Nutrition and Bone Health Group at MRC Human Nutrition Research which aims to achieve this objective. Skeletal health is most likely to be determined during childhood and adolescence and aging, when growth rates are highest, and bone loss greatest. Studies of bone health often focus on a particular life stage, such as pre-puberty, post-menopause or aging. Although these data provide invaluable insights about the determinants and definition of a healthy bone, there are limitations. It is not necessarily correct to assume that these factors are the same at different times through life or between populations. This is illustrated by considering the differences in the response of the developing skeleton to physical activity or nutritional interventions( Reference Bass, Pearce and Bradney 76 , Reference El-Hajj Fuleihan, Nabulsi and Tamim 88 , Reference Bassey, Rothwell and Littlewood 102 ). Therefore, to address on-going research needs, a threefold approach is being taken to study childhood and adolescence, aging and life-course data.

During childhood and adolescence, the longitudinal effects of low Ca intake and poor vitamin D status on peak bone strength are still not clearly defined. Using comparative populations of differing Ca intake or D status provides to possibility to study the effects of each on phenotype.

For aging, the aim is to characterise bone and muscle phenotype within and between populations to study the interactive effects between muscle and bone and modulators to this relationship: the European Male Ageing Study studies musculoskeletal aging in different ethnic groups during early to late adulthood( Reference Ward, Pye and Adams 52 , Reference Ward, Jeffrey and Adams 103 ); The Gambian Bone Ageing Study is being carried out in a country of characteristically low Ca intake and currently rapidly transitioning towards a more Western diet and lifestyle; the National Survey for Health and Development is a birth cohort in whom bone mass has been gathered at age 60–64 years( Reference Kuh, Pierce and Adams 104 ).

Birth cohorts provide prospective data through the life-course: the National Survey for Health and Development has collected growth, nutrition and physical capability data through the life course, providing the opportunity for the study of the relationship between bone and dietary patterns through adulthood( Reference Kuh, Hardy and Butterworth 105 Reference Prynne, Thane and Prentice 108 ), the Hertfordshire Cohort provides information on early life (pre- and post-natal) determinants of osteoporosis( Reference Oliver, Jameson and Sayer 109 Reference Cooper, Fall and Egger 112 ); ongoing longitudinal studies of bone development in children and young adults in The Gambia to study the impact of poor growth, delayed puberty and nutrition on peak bone strength( Reference Prentice, Schoenmakers and Laskey 21 , Reference Prentice, Ward and Schoenmakers 57 ).

By taking an approach to study the interaction between muscle, bone and nutrition at defined time points and throughout the life course a better understanding of the definition of a healthy bone phenotype should lead to effective strategies for prevention of bone disease during childhood and aging.

Key messages

A healthy bone is one that is fit-for-purpose that does not fail under normal physiological loading. The response of bone to muscle loading is the primary determinant of a healthy bone phenotype and is described by a functional feedback model that incorporates the mechanostat.

The study of different life stages and populations is important when defining a healthy skeletal phenotype which should be defined by bone strength rather than bone mass. The shape, geometry, mineral content and turnover of bone determine bone strength. Although all techniques have strengths and limitations, the ability to refine the definition of bone phenotype is increasing as developments allow better resolution, separate assessment of bone compartments, measurements of most aspects of bone strength and body composition. Techniques are also readily available to quantify muscle function. The critical evaluation and interpretation of newer technologies is important.

Nutrition acts as a modulator of the mechanostat through effects on bone and/or muscle, inadequate or excess nutrition may alter the bones response to loading altering phenotype.

For public health messages to be developed, it is important to understand the relative contribution of diet across life stage, between sexes and different populations.

For lifestyle and dietary recommendations, a life-course approach in different populations and age groups and not a ‘one size fits all’ approach should be used. Collection of longitudinal data is vital. The definition of a healthy phenotype and interaction between bone, muscle and nutrition require further study.

Acknowledgements

The author is grateful for the contributions to her research of Dr Ann Prentice, Dr Inez Schoenmakers, Dr Gail Goldberg and other colleagues in the Nutrition and Bone Health Group in MRC Human Nutrition Research, Cambridge and MRC Keneba, The Gambia; Dr Zulf Mughal and Professor Judith Adams and European Male Ageing Study Team, University of Manchester and Dr Nigel Loveridge, University of Cambridge for his comments on this manuscript. The author declares no conflicts of interest. This work was conducted within the core programme of the MRC Nutrition and Bone Health Group at MRC Human Nutrition Research, funded by the UK Medical Research Council (Grant codes U105960371 and U123261351). There was no other specific grant from any funding agency in the public, commercial or not-for-profit sectors.

References

1. Prentice, A (2004) Diet, nutrition and the prevention of osteoporosis. Public Health Nutr 7, 227243.CrossRefGoogle ScholarPubMed
2. Rubin, CT (1984) Skeletal strain and the functional significance of bone architecture. Calcified Tissue Int 36, Suppl. 1:S11S18.CrossRefGoogle ScholarPubMed
3. Frost, H (1987) Bone “mass” and the “mechanostat”: A proposal. Anat Rec 219, 19.CrossRefGoogle ScholarPubMed
4. Frost, HM (2000) Muscle, bone, and the Utah paradigm: A 1999 overview. Med Sci Sports Exerc 32, 911917.CrossRefGoogle ScholarPubMed
5. Frost, HM (2004) The Utah Paradigm of Skeletal Physiology. International Society of Musculoskeletal and Neuronal Interactions.Google Scholar
6. Currey, JD (1984) Effects of differences in mineralization on the mechanical properties of bone. Phil Trans R Soc Lond 304, 509518.Google ScholarPubMed
7. Rauch, F (2006) Material matters: A mechanostat-based perspective on bone development in osteogenesis imperfecta and hypophosphatemic rickets. J Musculoskelet Neuronal Interact 6, 142146.Google Scholar
8. Garn, S, Poznanski, A & Nagy, J (1971) Bone measurement in the differential diagnosis of osteopenia and osteoporosis. Radiology 100, 509518.CrossRefGoogle ScholarPubMed
9. Schonau, E, Neu, C, Rauch, F et al. (2001) The development of bone strength at the proximal radius during childhood and adolescence. J Clin Endocrinol Metab 86, 613618.CrossRefGoogle Scholar
10. Ashby, RL, Adams, JE, Roberts, SA et al. (2011) The muscle-bone unit of peripheral and central skeletal sites in children and young adults. Osteoporos Int 22, 121132.CrossRefGoogle ScholarPubMed
11. Seeman, E (2001) Sexual dimorphism in skeletal size, density and strength. J Clin Endocrinol Metab 86, 45764584.CrossRefGoogle ScholarPubMed
12. Riggs, BL, Melton Iii, LJ III, Robb, RA et al. (2004) Population-based study of age and sex differences in bone volumetric density, size, geometry, and structure at different skeletal sites. J Bone Miner Res 19, 19451954.CrossRefGoogle ScholarPubMed
13. Riggs, BL, Melton, LJ III, Robb, RA et al. (2006) Population-based analysis of the relationship of whole bone strength indices and fall-related loads to age- and sex-specific patterns of hip and wrist fractures. J Bone Miner Res 21, 315323.CrossRefGoogle ScholarPubMed
14. Jensen, KS, Mosekilde, L & Mosekilde, L (1990) A model of vertebral trabecular bone architecture and its mechanical properties. Bone 11, 417423.CrossRefGoogle Scholar
15. Liu, XS, Walker, MD, McMahon, DJ et al. (2011) Better skeletal microstructure confers greater mechanical advantages in Chinese-American women versus white women. J Bone Miner Res 26, 17831792.CrossRefGoogle ScholarPubMed
16. Clark, EM, Ness, AR, Bishop, NJ et al. (2006) Association between bone mass and fractures in children: A prospective cohort study. J Bone Miner Res 21, 14891495.CrossRefGoogle ScholarPubMed
17. Marshall, D, Johnell, O & Wedel, H (1996) Meta-analysis of how well measures of bone mineral density predict occurrence of osteoporotic fractures. Br Med J 312, 12541259.CrossRefGoogle ScholarPubMed
18. Goulding, A, Jones, I, Taylor, R et al. (2000) More broken bones: A 4-year double cohort study of young girls with and without distal forearm fractures. J Bone Miner Res 15, 20112018.CrossRefGoogle ScholarPubMed
19. Rauch, F & Schonau, E (2001) Changes in bone density during childhood and adolescence: An approach based on bone's biological organization. J Bone Miner Res 16, 597604.CrossRefGoogle ScholarPubMed
20. Crabtree, N & Ward, K (2009) Bone densitometry: current status and future perspectives. Endocr Dev 16, 5872.CrossRefGoogle ScholarPubMed
21. Prentice, A, Schoenmakers, I, Laskey, MA et al. (2006) Nutrition and bone growth and development. Proc Nutr Soc 65, 348360.CrossRefGoogle ScholarPubMed
22. Gordon, CM, Bachrach, LK, Carpenter, TO et al. (2008) Dual energy X-ray absorptiometry interpretation and reporting in children and adolescents: The 2007 ISCD Pediatric Official Positions. J Clin Densitom 11, 4358.CrossRefGoogle ScholarPubMed
23. Lewiecki, EM, Gordon, CM, Baim, S et al. (2008) International Society for Clinical Densitometry 2007 Adult and Pediatric Official Positions. Bone 13, 115121.Google Scholar
24. Wainwright, SA, Marshall, LM, Ensrud, KE et al. (2005) Hip fracture in women without osteoporosis. J Clin Endocrinol Metab 90, 27872793.CrossRefGoogle ScholarPubMed
25. Premaor, MO, Pilbrow, L, Tonkin, C et al. (2010) Obesity and fractures in postmenopausal women. J Bone Miner Res 25, 292297.CrossRefGoogle ScholarPubMed
26. Aspray, TJ, Prentice, A & Cole, TJ (1995) The bone mineral content of weight-bearing bones is influenced by the ratio of sitting to standing height in elderly Gambian women. Bone 17, 261263.CrossRefGoogle ScholarPubMed
27. Yan, L, Crabtree, NJ, Reeve, J et al. (2004) Does hip strength analysis explain the lower incidence of hip fracture in the People's Republic of China? Bone 34, 584588.CrossRefGoogle ScholarPubMed
28. Aspray, TJ, Prentice, A, Cole, TJ et al. (1996) Low bone mineral content is common but osteoporotic fractures are rare in elderly rural Gambian women. J Bone Miner Res 11, 10191025.CrossRefGoogle ScholarPubMed
29. Boutroy, S, Bouxsein, ML, Munoz, F et al. (2005) In vivo assessment of trabecular bone microarchitecture by high-resolution peripheral quantitative computed tomography. J Clin Endocrinol Metab 90, 65086515.CrossRefGoogle ScholarPubMed
30. Bouxsein, ML, Melton, LJ III, Riggs, BL et al. (2006) Age- and sex-specific differences in the factor of risk for vertebral fracture: A population-based study using QCT. J Bone Miner Res 21, 14751482.CrossRefGoogle ScholarPubMed
31. Genant, HK, Engelke, K & Prevrhal, S (2008) Advanced CT bone imaging in osteoporosis. Rheumatology (Oxford) 47 Suppl 4, iv9–i16.CrossRefGoogle ScholarPubMed
32. Gilsanz, V, Skaggs, D, Kovanlikaya, A et al. (1998) Differential effect of race on the axial and appendicular skeletons of children. J Clin Endocrinol Metab 83, 14201427.Google ScholarPubMed
33. Lang, TF, Leblanc, AD, Evans, HJ et al. (2006) Adaptation of the proximal femur to skeletal reloading after long-duration spaceflight. J Bone Miner Res 21, 12241230.CrossRefGoogle ScholarPubMed
34. Poole, KE, Mayhew, PM, Rose, CM et al. (2010) Changing structure of the femoral neck across the adult female lifespan. J Bone Miner Res 25, 482491.CrossRefGoogle ScholarPubMed
35. Burghardt, AJ, Buie, HR, Laib, A et al. (2010) Reproducibility of direct quantitative measures of cortical bone microarchitecture of the distal radius and tibia by HR-pQCT. Bone 47, 519528.CrossRefGoogle ScholarPubMed
36. Krug, R, Burghardt, AJ, Majumdar, S et al. (2010) High-resolution imaging techniques for the assessment of osteoporosis. Radiol Clin North Am 48, 601621.CrossRefGoogle ScholarPubMed
37. Cann, C (1981) Low dose CT scanning for quantitative spinal bone mineral analysis. Radiology 140, 813815.CrossRefGoogle Scholar
38. Cann, CE & Genant, H (1980) Precision measurement of vertebral mineral content using computed tomography. J Comput Assist Tomogr 4, 493500.CrossRefGoogle ScholarPubMed
39. Genant, H, Cann, C, Ettinger, B et al. (1982) Quantitative computed tomography of vertebral spongiosa: A sensitive method for detecting early bone loss after oophorectomy. Ann Intern Med 97, 699705.CrossRefGoogle ScholarPubMed
40. Macdonald, HM, Nishiyama, KK, Kang, J et al. (2011) Age-related patterns of trabecular and cortical bone loss differ between sexes and skeletal sites: A population-based HR-pQCT study. J Bone Miner Res 26, 5062.CrossRefGoogle Scholar
41. Khosla, S, Riggs, BL, Atkinson, EJ et al. (2006) Effects of sex and age on bone microstructure at the ultradistal radius: A population-based noninvasive in vivo assessment. J Bone Miner Res 21, 124131.CrossRefGoogle Scholar
42. Schneider, P & Reiners, C (1998) Peripheral quantitative computed tomography. In Bone Densitometry and Osteoporosis , pp. 349363 [Genant, H, Guglielmi, G & Jergas, M]. Berlin: Springer-Verlag.CrossRefGoogle Scholar
43. Ward, KA, Roberts, SA, Adams, JE et al. (2005) Bone geometry and density in the skeleton of pre-pubertal gymnasts and school children. Bone 36, 10121018.CrossRefGoogle ScholarPubMed
44. Brennan, BM, Mughal, Z, Roberts, SA et al. (2005) Bone mineral density in childhood survivors of acute lymphoblastic leukemia treated without cranial irradiation. J Clin Endocrinol Metab 90, 689694.CrossRefGoogle ScholarPubMed
45. Quick, JL, Ward, KA, Adams, JE et al. (2006) Cortical bone geometry in asthmatic children. Arch Dis Child 91, 346348.CrossRefGoogle ScholarPubMed
46. Ward, KA, Roy, DK, Pye, SR et al. (2007) Forearm bone geometry and mineral content in UK women of European and South-Asian origin. Bone 41, 117121.CrossRefGoogle ScholarPubMed
47. Laskey, MA, de Bono, S, Zhu, D et al. (2009) Evidence for enhanced characterization of cortical bone using novel pQCT shape software. J Clin Densitom 13, 247255.CrossRefGoogle Scholar
48. Grampp, S, Genant, HK, Mathur, A et al. (1997) Comparisons of noninvasive bone mineral measurements in assessing age-related loss, fracture discrimination, and diagnostic classification. J Bone Miner Res 12, 697711.CrossRefGoogle ScholarPubMed
49. Kroger, H, Lunt, M, Reeve, J et al. (1999) Bone density reduction in various measurement sites in men and women with osteoporotic fractures of spine and hip: The European quantitation of osteoporosis study. Calc Tissue Int 64, 191199.CrossRefGoogle ScholarPubMed
50. Runge, M, Rittweger, J, Russo, CR et al. (2004) Is muscle power output a key factor in the age-related decline in physical performance? A comparison of muscle cross section, chair-rising test and jumping power. Clin Physiol Funct Imag 24, 335340.CrossRefGoogle ScholarPubMed
51. Fricke, O, Weidler, J, Tutlewski, B et al. (2006) Mechanography – a new device for the assessment of muscle function in pediatrics. Pediatr Res 59, 4649.CrossRefGoogle ScholarPubMed
52. Ward, K, Pye, S, Adams, J et al. (2011) Influence of age and sex steroids on bone density and geometry in middle-aged and elderly European men. Osteoporos Int 22, 15131523.CrossRefGoogle Scholar
53. Ward, KA, Das, G, Roberts, SA et al. (2010) A randomized, controlled trial of vitamin D supplementation upon musculoskeletal health in postmenarchal females. J Clin Endocrinol Metab 95, 46434651.CrossRefGoogle ScholarPubMed
54. Lang, T, Cauley, JA, Tylavsky, F et al. (2010) Computed tomographic measurements of thigh muscle cross-sectional area and attenuation coefficient predict hip fracture: The health, aging, and body composition study. J Bone Miner Res 25, 513519.CrossRefGoogle ScholarPubMed
55. Schafer, AL, Vittinghoff, E, Lang, TF et al. (2010) Fat infiltration of muscle, diabetes, and clinical fracture risk in older adults. J Clin Endocrinol Metab 95, E368E372.CrossRefGoogle ScholarPubMed
56. Gilsanz, V, Kremer, A, Mo, AO et al. (2010) Vitamin D status and its relation to muscle mass and muscle fat in young women. J Clin Endocrinol Metab 95, 15951601.CrossRefGoogle ScholarPubMed
57. Prentice, A, Ward, KA, Schoenmakers, I et al. (editors) (2011) Bone Growth in African Children and Adolescents. Florida, USA: CRC Press, Taylor Francis Group.CrossRefGoogle Scholar
58. Prentice, A & Bates, CJ (1994) Adequacy of dietary mineral supply for human bone growth and mineralisation. Eur J Clin Nutr 48, Suppl. 1, S161S176; discussion S77.Google ScholarPubMed
59. Pfeifer, M, Begerow, B & Minne, HW (2002) Vitamin D and muscle function. Osteoporos Int 13, 187194.CrossRefGoogle ScholarPubMed
60. Ward, KA, Das, G, Berry, JL et al. (2009) Vitamin D status and muscle function in post-menarchal adolescent girls. J Clin Endocrinol Metab 94, 559563.CrossRefGoogle ScholarPubMed
61. Heaney, RP & Layman, DK (2008) Amount and type of protein influences bone health. Am J Clin Nutr 87, 1567S1570S.CrossRefGoogle ScholarPubMed
62. Dimitri, P, Wales, JK & Bishop, N (2010) Fat and bone in children: Differential effects of obesity on bone size and mass according to fracture history. J Bone Miner Res 25, 527536.CrossRefGoogle Scholar
63. Goulding, A, Grant, AM & Williams, SM (2005) Bone and body composition of children and adolescents with repeated forearm fractures. J Bone Miner Res 20, 20902096.CrossRefGoogle ScholarPubMed
64. Skaggs, DL, Loro, ML, Pitukcheewanont, P et al. (2001) Increased body weight and decreased radial cross-sectional dimensions in girls with forearm fractures. J Bone Miner Res 16, 13371342.CrossRefGoogle ScholarPubMed
65. Heaney, R, Abrams, S, Dawson-Highes, B et al. (2000) Peak bone mass. Osteoporos Int 11, 985–1009.CrossRefGoogle ScholarPubMed
66. Lambert, HL, Eastell, R, Karnik, K et al. (2008) Calcium supplementation and bone mineral accretion in adolescent girls: An 18-mo randomized controlled trial with 2-y follow-up. Am J Clin Nutr 87, 455462.CrossRefGoogle ScholarPubMed
67. Jarjou, LM, Laskey, MA, Sawo, Y et al. (2010) Effect of calcium supplementation in pregnancy on maternal bone outcomes in women with a low calcium intake. Am J Clin Nutr 92, 450457.CrossRefGoogle ScholarPubMed
68. Ward, KA, Roberts, SA, Adams, JE et al. (2007) Calcium supplementation and weight bearing physical activity – do they have a combined effect on the bone density of pre-pubertal children? Bone 41, 496504.CrossRefGoogle ScholarPubMed
69. Specker, B, Binkley, T & Fahrenwald, N (2004) Increased periosteal circumference remains present 12 months after an exercise intervention in preschool children. Bone 35, 13831388.Google ScholarPubMed
70. Eastell, R & Lambert, H (2002) Diet and healthy bones. Calc Tissue Int 70, 400404.CrossRefGoogle ScholarPubMed
71. Bonjour, J, Carrie, A, Ferrari, S et al. (1997) Calcium-enriched foods and bone mass growth in prepubertal girls: A randomized, double blind, placebo-controlled trial. J Clin Invest 99, 12871294.CrossRefGoogle ScholarPubMed
72. Cadogen, J, Eastell, R, Jones, N et al. (1997) Milk intake and bone mineral acquisition in adolescent girls: Randomised, controlled intervention trial. Br Med J 315, 12551260.CrossRefGoogle Scholar
73. Specker, BL (1996) Evidence for an interaction between calcium intake and physical activity on changes in bone mineral density. J Bone Miner Res 11, 15391544.CrossRefGoogle ScholarPubMed
74. Bass, SL, Naughton, G, Saxon, L et al. (2007) Exercise and calcium combined results in a greater osteogenic effect than either factor alone: A blinded randomized placebo-controlled trial in boys. J Bone Miner Res 22, 458464.CrossRefGoogle Scholar
75. Prentice, A, Stear, S, Ginty, F et al. (2002) Calcium supplementation increases height and bone mass of 16–18 year old boys. J Bone Miner Res 17, S1, S967.Google Scholar
76. Bass, S, Pearce, G, Bradney, M et al. (1998) Exercise before puberty may confer residual benefits in bone density in adulthood: Studies in active prepubertal and retired female gymnasts. J Bone Miner Res 13, 500507.CrossRefGoogle ScholarPubMed
77. Uusi-Rasi, K, Sievanen, H, Heinonen, A et al. (2006) Long-term recreational gymnastics provides a clear benefit in age-related functional decline and bone loss. A prospective 6-year study. Osteoporos Int 17, 11541164.CrossRefGoogle ScholarPubMed
78. Eser, P, Hill, B, Ducher, G et al. (2009) Skeletal benefits after long-term retirement in former elite female gymnasts. J Bone Miner Res 24, 19811988.CrossRefGoogle ScholarPubMed
79. Kontulainen, S, Kannus, P, Haapasalo, H et al. (2001) Good maintenance of exercise induced bone gain with decreased training of female tennis and squash players: A prospective 5-year follow-up study of young and old starters and controls. J Bone Miner Res 16, 195201.CrossRefGoogle Scholar
80. Dibba, B, Prentice, A, Ceesay, M et al. (2000) Effect of calcium supplementation on bone mineral accretion in gambian children accustomed to a low-calcium diet. Am J Clin Nutr 71, 544549.CrossRefGoogle Scholar
81. Prentice, A (2007) Studies of Gambian and UK children and adolescents: Insights into calcium requirements and adaptation to a low calcium intake. In Nutritional Aspects of Osteoporosis 2006 International Congress Series 1297 , 1524 [Burckhardt, P, Dawson-Hughes, B & Heaney, RP]. Amsterdam: Elsevier.Google Scholar
82. Dibba, B, Prentice, A, Ceesay, M et al. (2002) Bone mineral contents and plasma osteocalcin concentrations of Gambian children 12 and 24 mo after the withdrawal of a calcium supplement. Am J Clin Nutr 76, 681686.CrossRefGoogle ScholarPubMed
83. Aspray, TJ, Yan, L & Prentice, A (2005) Parathyroid hormone and rates of bone formation are raised in perimenopausal rural Gambian women. Bone 36, 710720.CrossRefGoogle ScholarPubMed
84. Bischoff-Ferrari, HA, Dawson-Hughes, B, Staehelin, HB et al. (2009) Fall prevention with supplemental and active forms of vitamin D: A meta-analysis of randomised controlled trials. Br Med J 339, b3692.CrossRefGoogle ScholarPubMed
85. Gallagher, JC & Rosen, C (2011) Institute of Medicine responds. Br Med J 342, d4046.CrossRefGoogle ScholarPubMed
86. Institutes of Medicine (2010) Dietary Reference Ranges for calcium and vitamin D: http://www.iom.edu/Reports/2010/Dietary-Reference-Intakes-for-Calcium-and-Vitamin-D Google Scholar
87. Das, G, Crocombe, S, McGrath, M et al. (2006) Hypovitaminosis D among healthy adolescent girls attending an inner city school. Arch Dis Child 91, 569572.CrossRefGoogle ScholarPubMed
88. El-Hajj Fuleihan, G, Nabulsi, M, Tamim, H et al. (2006) Effect of vitamin D replacement on musculoskeletal parameters in school children: A randomized controlled trial. J Clin Endocrinol Metab 91, 405412.CrossRefGoogle ScholarPubMed
89. Winzenberg, T, Powell, S, Shaw, KA et al. (2011) Effects of vitamin D supplementation on bone density in healthy children: Systematic review and meta-analysis. Br Med J 342, c7254.CrossRefGoogle Scholar
90. Molgaard, C, Larnkjaer, A, Cashman, KD et al. (2010) Does vitamin D supplementation of healthy Danish Caucasian girls affect bone turnover and bone mineralization? Bone 46, 432439.CrossRefGoogle ScholarPubMed
91. Surdykowski, AK, Kenny, AM, Insogna, KL et al. (2010) Optimizing bone health in older adults: The importance of dietary protein. Aging Health 6, 345357.CrossRefGoogle ScholarPubMed
92. Bonjour, JP (2005) Dietary protein: An essential nutrient for bone health. J Am Coll Nutr 24, 6 Suppl., 526S536S.CrossRefGoogle ScholarPubMed
93. Ginty, F (2003) Dietary protein and bone health. Proc Nutr Soc 62, 867876.CrossRefGoogle ScholarPubMed
94. Chevalley, T, Bonjour, JP, Ferrari, S et al. (2008) High-protein intake enhances the positive impact of physical activity on BMC in prepubertal boys. J Bone Miner Res 23, 131142.CrossRefGoogle ScholarPubMed
95. Reid, I (2010) Fat and Bone. Arch Biochem Biophys 503, 2027.CrossRefGoogle ScholarPubMed
96. Rosen, CJ & Bouxsein, ML (2006) Mechanisms of disease: Is osteoporosis the obesity of bone? Nat Clin Pract Rheumatol 2, 3543.CrossRefGoogle ScholarPubMed
97. Gilsanz, V, Chalfant, J, Mo, AO et al. (2009) Reciprocal relations of subcutaneous and visceral fat to bone structure and strength. J Clin Endocrinol Metab 94, 33873393.CrossRefGoogle ScholarPubMed
98. Dimitri, P, Wales, JK & Bishop, N (2011) Adipokines, bone-derived factors and bone turnover in obese children; evidence for altered fat-bone signalling resulting in reduced bone mass. Bone 48, 189196.CrossRefGoogle ScholarPubMed
99. Ward, KA, Webb, REB, Prentice, A et al. (2011) Relationships between fat mass, plasma adipokines and bone in post-menopausal caucasian women. Front Endocrinol (In the Press).Google Scholar
100. Barbour, KE, Zmuda, JM, Boudreau, R et al. (2011) Adipokines and the risk of fracture in older adults. J Bone Miner Res 26, 15681576.CrossRefGoogle ScholarPubMed
101. Sayers, A, Timpson, NJ, Sattar, N et al. (2010) Adiponectin and its association with bone mass accrual in childhood. J Bone Miner Res 25, 22122220.CrossRefGoogle ScholarPubMed
102. Bassey, E, Rothwell, M, Littlewood, J et al. (1998) Pre- and postmenopausal women have different bone mineral density responses to the same high impact exercise. J Bone Miner Res 13, 18051813.CrossRefGoogle Scholar
103. Ward, KA, Jeffrey, M, Adams, JE et al. (2010) Sarcopenia in ageing males: Results from the European Male Ageing Study (EMAS). Osteoporos Int 21, S3.Google Scholar
104. Kuh, D, Pierce, M, Adams, J et al. (2011) Cohort profile: Updating the cohort profile for the MRC National Survey of Health and Development: A new clinic-based data collection for ageing research. Int J Epidemiol 40, e1e9.CrossRefGoogle ScholarPubMed
105. Kuh, D, Hardy, R, Butterworth, S et al. (2006) Developmental origins of midlife grip strength: Findings from a birth cohort study. J Gerontol A Biol Sci Med Sci 61, 702706.CrossRefGoogle ScholarPubMed
106. Kuh, D, Hardy, R, Butterworth, S et al. (2006) Developmental origins of midlife physical performance: Evidence from a British birth cohort. Am J Epidemiol 164, 110121.CrossRefGoogle ScholarPubMed
107. Kuh, D, Bassey, J, Hardy, R et al. (2002) Birth weight, childhood size, and muscle strength in adult life: Evidence from a birth cohort study. Am J Epidemiol 156, 627633.CrossRefGoogle ScholarPubMed
108. Prynne, CJ, Thane, CW, Prentice, A et al. (2005) Intake and sources of phylloquinone (vitamin K(1)) in 4-year-old British children: Comparison between 1950 and the 1990s. Public Health Nutr 8, 171180.CrossRefGoogle Scholar
109. Oliver, H, Jameson, KA, Sayer, AA et al. (2007) Growth in early life predicts bone strength in late adulthood: The Hertfordshire Cohort Study. Bone 41, 400405.CrossRefGoogle ScholarPubMed
110. Javaid, MK, Lekamwasam, S, Clark, J et al. (2006) Infant growth influences proximal femoral geometry in adulthood. J Bone Miner Res 21, 508512.CrossRefGoogle ScholarPubMed
111. Cooper, C, Eriksson, JG, Forsen, T et al. (2001) Maternal height, childhood growth and risk of hip fracture in later life: A longitudinal study. Osteoporos Int 12, 623629.CrossRefGoogle ScholarPubMed
112. Cooper, C, Fall, C, Egger, P et al. (1997) Growth in infancy and bone mass in later life. Ann Rheum Dis 56, 1721.CrossRefGoogle ScholarPubMed
Figure 0

Fig. 1. A conceptual diagram of bone health through the life course: the solid line denotes male, dashed female and dotted the consequence of not achieving peak bone strength at the end of development.

Figure 1

Fig. 2. A summary diagram of the Mechanostat model: the grey boxes indicate non-mechanical factors, including nutrition, and where they may interact with the Mechanostat. These interactions may be through alterations in the ability of muscle to generate forces (load), the bone ability to detect or respond to changes in load. For example, vitamin D causes proximal muscle weakness, which would reduce loading to bone and from this ‘sub-optimal’ bone accretion or increased bone loss may occur. At the bone level, vitamin D causes under-mineralisation of bone which would change the way it responds to loading. Both of these examples would result in changes in bone phenotype and strength. Adapted from Frost(3).

Figure 2

Fig. 3. Schematic stress–strain curve to demonstrate how phenotype may respond to changes in stiffness: the solid line denotes a healthy skeleton 1. Elastic portion of the curve where load does not permanently deform the bone or induce damage, 2. Plastic region where damage is starting to accumulate, Fx=fracture load; note there is a long period before the fracture load is reached under normal circumstances. The dash-dot line is a bone with high stiffness (mechanostat underestimates loads from muscle) and the dotted line is low stiffness (mechanostat overestimates loads from muscle); note the differing length of the elastic and plastic regions in each of these situations.

Figure 3

Fig. 4. Overview of how nutrition may alter phenotype at age of peak bone strength: (a) low Ca intake – comparing Gambian to European Caucasian tibia; (b) vitamin D status – comparing British Asian compared to European Caucasian radius. The table summarises the differences. vBMD, volumetric bone mineral density; BMC, bone mineral content; Med area, medullary area; Cort thk, cortical thickness; SSI, bone strength.