Real-World Gait Detection Using a Wrist-Worn Inertial Sensor: Validation Study

BACKGROUND

Wrist-worn inertial sensors are used in digital health for evaluating mobility in real-world environments. Preceding the estimation of spatiotemporal gait parameters within long-term recordings, gait detection is an important step to identify regions of interest where gait occurs, which requires robust algorithms due to the complexity of arm movements. While algorithms exist for other sensor positions, a comparative validation of algorithms applied to the wrist position on real-world data sets across different disease populations is missing. Furthermore, gait detection performance differences between the wrist and lower back position have not yet been explored but could yield valuable information regarding sensor position choice in clinical studies.

OBJECTIVE

The aim of this study was to validate gait sequence (GS) detection algorithms developed for the wrist position against reference data acquired in a real-world context. In addition, this study aimed to compare the performance of algorithms applied to the wrist position to those applied to lower back-worn inertial sensors.

METHODS

Participants with Parkinson disease, multiple sclerosis, proximal femoral fracture (hip fracture recovery), chronic obstructive pulmonary disease, and congestive heart failure and healthy older adults (N=83) were monitored for 2.5 hours in the real-world using inertial sensors on the wrist, lower back, and feet including pressure insoles and infrared distance sensors as reference. In total, 10 algorithms for wrist-based gait detection were validated against a multisensor reference system and compared to gait detection performance using lower back-worn inertial sensors.

RESULTS

The best-performing GS detection algorithm for the wrist showed a mean (per disease group) sensitivity ranging between 0.55 (SD 0.29) and 0.81 (SD 0.09) and a mean (per disease group) specificity ranging between 0.95 (SD 0.06) and 0.98 (SD 0.02). The mean relative absolute error of estimated walking time ranged between 8.9% (SD 7.1%) and 32.7% (SD 19.2%) per disease group for this algorithm as compared to the reference system. Gait detection performance from the best algorithm applied to the wrist inertial sensors was lower than for the best algorithms applied to the lower back, which yielded mean sensitivity between 0.71 (SD 0.12) and 0.91 (SD 0.04), mean specificity between 0.96 (SD 0.03) and 0.99 (SD 0.01), and a mean relative absolute error of estimated walking time between 6.3% (SD 5.4%) and 23.5% (SD 13%). Performance was lower in disease groups with major gait impairments (eg, patients recovering from hip fracture) and for patients using bilateral walking aids.

CONCLUSIONS

Algorithms applied to the wrist position can detect GSs with high performance in real-world environments. Those periods of interest in real-world recordings can facilitate gait parameter extraction and allow the quantification of gait duration distribution in everyday life. Our findings allow taking informed decisions on alternative positions for gait recording in clinical studies and public health.

TRIAL REGISTRATION

ISRCTN Registry 12246987; https://www.isrctn.com/ISRCTN12246987.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.1136/bmjopen-2021-050785.

Ecological validity of a deep learning algorithm to detect gait events from real-life walking bouts in mobility-limiting diseases

Introduction

The clinical assessment of mobility, and walking specifically, is still mainly based on functional tests that lack ecological validity. Thanks to inertial measurement units (IMUs), gait analysis is shifting to unsupervised monitoring in naturalistic and unconstrained settings. However, the extraction of clinically relevant gait parameters from IMU data often depends on heuristics-based algorithms that rely on empirically determined thresholds. These were mainly validated on small cohorts in supervised settings.

Methods

Here, a deep learning (DL) algorithm was developed and validated for gait event detection in a heterogeneous population of different mobility-limiting disease cohorts and a cohort of healthy adults. Participants wore pressure insoles and IMUs on both feet for 2.5 h in their habitual environment. The raw accelerometer and gyroscope data from both feet were used as input to a deep convolutional neural network, while reference timings for gait events were based on the combined IMU and pressure insoles data.

Results and discussion

The results showed a high-detection performance for initial contacts (ICs) (recall: 98%, precision: 96%) and final contacts (FCs) (recall: 99%, precision: 94%) and a maximum median time error of -0.02 s for ICs and 0.03 s for FCs. Subsequently derived temporal gait parameters were in good agreement with a pressure insoles-based reference with a maximum mean difference of 0.07, -0.07, and <0.01 s for stance, swing, and stride time, respectively. Thus, the DL algorithm is considered successful in detecting gait events in ecologically valid environments across different mobility-limiting diseases.

Acceptability of wearable devices for measuring mobility remotely: Observations from the Mobilise-D technical validation study

Background

This study aimed to explore the acceptability of a wearable device for remotely measuring mobility in the Mobilise-D technical validation study (TVS), and to explore the acceptability of using digital tools to monitor health.

Methods

Participants (N = 106) in the TVS wore a waist-worn device (McRoberts Dynaport MM + ) for one week. Following this, acceptability of the device was measured using two questionnaires: The Comfort Rating Scale (CRS) and a previously validated questionnaire. A subset of participants (n = 36) also completed semi-structured interviews to further determine device acceptability and to explore their opinions of the use of digital tools to monitor their health. Questionnaire results were analysed descriptively and interviews using a content analysis.

Results

The device was considered both comfortable (median CRS (IQR; min-max) = 0.0 (0.0; 0-20) on a scale from 0-20 where lower scores signify better comfort) and acceptable (5.0 (0.5; 3.0-5.0) on a scale from 1-5 where higher scores signify better acceptability). Interviews showed it was easy to use, did not interfere with daily activities, and was comfortable. The following themes emerged from participants' as being important to digital technology: altered expectations for themselves, the use of technology, trust, and communication with healthcare professionals.

Conclusions

Digital tools may bridge existing communication gaps between patients and clinicians and participants are open to this. This work indicates that waist-worn devices are supported, but further work with patient advisors should be undertaken to understand some of the key issues highlighted. This will form part of the ongoing work of the Mobilise-D consortium.

Design and validation of a multi-task, multi-context protocol for real-world gait simulation

BACKGROUND

Measuring mobility in daily life entails dealing with confounding factors arising from multiple sources, including pathological characteristics, patient specific walking strategies, environment/context, and purpose of the task. The primary aim of this study is to propose and validate a protocol for simulating real-world gait accounting for all these factors within a single set of observations, while ensuring minimisation of participant burden and safety.

METHODS

The protocol included eight motor tasks at varying speed, incline/steps, surface, path shape, cognitive demand, and included postures that may abruptly alter the participants' strategy of walking. It was deployed in a convenience sample of 108 participants recruited from six cohorts that included older healthy adults (HA) and participants with potentially altered mobility due to Parkinson's disease (PD), multiple sclerosis (MS), proximal femoral fracture (PFF), chronic obstructive pulmonary disease (COPD) or congestive heart failure (CHF). A novelty introduced in the protocol was the tiered approach to increase difficulty both within the same task (e.g., by allowing use of aids or armrests) and across tasks.

RESULTS

The protocol proved to be safe and feasible (all participants could complete it and no adverse events were recorded) and the addition of the more complex tasks allowed a much greater spread in walking speeds to be achieved compared to standard straight walking trials. Furthermore, it allowed a representation of a variety of daily life relevant mobility aspects and can therefore be used for the validation of monitoring devices used in real life.

CONCLUSIONS

The protocol allowed for measuring gait in a variety of pathological conditions suggests that it can also be used to detect changes in gait due to, for example, the onset or progression of a disease, or due to therapy.

TRIAL REGISTRATION

ISRCTN-12246987.

Feasibility, reliability and safety of self-assessed orthostatic blood pressure at home

BACKGROUND

A postural blood pressure assessment is required to diagnose Orthostatic Hypotension. With increasing remote consultations, alternative methods of performing postural blood pressure assessment are required.

OBJECTIVE

Determine whether postural blood pressure measurement at home, without a clinician, is reliable, feasible and safe.

DESIGN

Service improvement project within a falls and syncope service in Northeast England.

SUBJECTS

Eligibility criteria: aged ≥60 years; postural blood pressure measurement is indicated and is physically and cognitively able to perform. Exclusion criteria: nursing home residents, attending clinic in person.

METHODS

Postural blood pressure measurements were performed in patients' homes under clinical observation. Patient-led assessments were performed independent of the clinician, following written guidance. This was followed by a clinical-led assessment after 10-minute supine rest.

OUTCOMES

Agreement between patient and clinician derived postural blood pressure values and diagnosis of Orthostatic Hypotension; intervention safety, feasibility and acceptability.

RESULTS

Twenty-eight patients were eligible and 25 participated (mean age 75, median Clinical Frailty Score five).There was 95% agreement (Cohen's kappa 0.90 (0.70, 1.00)) between patient and clinician derived readings to diagnose orthostatic hypotension.Postural systolic blood pressure drop correlated strongly (r = 0.80), with patient derived readings overestimating by 1 (-6, 3) mmHg. Limits of agreement, determined via Bland Altman analysis, were +17 and -20 mmHg, greater than pre-determined maximum clinically important difference (±5 mmHg).Twenty participants performed valid postural blood pressure assessments without clinical assistance.

CONCLUSIONS

Patient-led postural blood pressure assessment at home is a reliable, safe and acceptable method for diagnosing Orthostatic Hypotension.

Technical validation of real-world monitoring of gait: a multicentric observational study

INTRODUCTION

Existing mobility endpoints based on functional performance, physical assessments and patient self-reporting are often affected by lack of sensitivity, limiting their utility in clinical practice. Wearable devices including inertial measurement units (IMUs) can overcome these limitations by quantifying digital mobility outcomes (DMOs) both during supervised structured assessments and in real-world conditions. The validity of IMU-based methods in the real-world, however, is still limited in patient populations. Rigorous validation procedures should cover the device metrological verification, the validation of the algorithms for the DMOs computation specifically for the population of interest and in daily life situations, and the users' perspective on the device.

METHODS AND ANALYSIS

This protocol was designed to establish the technical validity and patient acceptability of the approach used to quantify digital mobility in the real world by Mobilise-D, a consortium funded by the European Union (EU) as part of the Innovative Medicine Initiative, aiming at fostering regulatory approval and clinical adoption of DMOs.After defining the procedures for the metrological verification of an IMU-based device, the experimental procedures for the validation of algorithms used to calculate the DMOs are presented. These include laboratory and real-world assessment in 120 participants from five groups: healthy older adults; chronic obstructive pulmonary disease, Parkinson's disease, multiple sclerosis, proximal femoral fracture and congestive heart failure. DMOs extracted from the monitoring device will be compared with those from different reference systems, chosen according to the contexts of observation. Questionnaires and interviews will evaluate the users' perspective on the deployed technology and relevance of the mobility assessment.

ETHICS AND DISSEMINATION

The study has been granted ethics approval by the centre's committees (London-Bloomsbury Research Ethics committee; Helsinki Committee, Tel Aviv Sourasky Medical Centre; Medical Faculties of The University of Tübingen and of the University of Kiel). Data and algorithms will be made publicly available.

TRIAL REGISTRATION NUMBER

ISRCTN (12246987).

Walking on common ground: a cross-disciplinary scoping review on the clinical utility of digital mobility outcomes

Physical mobility is essential to health, and patients often rate it as a high-priority clinical outcome. Digital mobility outcomes (DMOs), such as real-world gait speed or step count, show promise as clinical measures in many medical conditions. However, current research is nascent and fragmented by discipline. This scoping review maps existing evidence on the clinical utility of DMOs, identifying commonalities across traditional disciplinary divides. In November 2019, 11 databases were searched for records investigating the validity and responsiveness of 34 DMOs in four diverse medical conditions (Parkinson's disease, multiple sclerosis, chronic obstructive pulmonary disease, hip fracture). Searches yielded 19,672 unique records. After screening, 855 records representing 775 studies were included and charted in systematic maps. Studies frequently investigated gait speed (70.4% of studies), step length (30.7%), cadence (21.4%), and daily step count (20.7%). They studied differences between healthy and pathological gait (36.4%), associations between DMOs and clinical measures (48.8%) or outcomes (4.3%), and responsiveness to interventions (26.8%). Gait speed, step length, cadence, step time and step count exhibited consistent evidence of validity and responsiveness in multiple conditions, although the evidence was inconsistent or lacking for other DMOs. If DMOs are to be adopted as mainstream tools, further work is needed to establish their predictive validity, responsiveness, and ecological validity. Cross-disciplinary efforts to align methodology and validate DMOs may facilitate their adoption into clinical practice.

Gait analysis as a clinical tool for dementia: current perspectives and future challenges

Gait, the way that we walk, requires complex cognitive functions. Gait may be a useful early marker for dementia diagnosis, as gait impairments precede and reflect cognitive decline. Early diagnosis of dementia enables individuals and their families to make informed decisions about their care plans, and allows researchers to understand preclinical and prodromal disease stages, providing novel targets for drug therapies. As such, a range of biomarkers are being developed to improve early and accurate diagnosis, including gait analysis. This editorial will outline how gait analysis can support the clinical diagnosis of dementia, including evidence of unique signatures of gait which can aid the identification of cognitive impairment and discrete dementia disease subtypes, the potential use of wearable technology to assess gait in the clinic and the real world, and key recommendations for the future implementation of gait into the diagnostic toolkit for dementia.

Walking-related digital mobility outcomes as clinical trial endpoint measures: protocol for a scoping review

INTRODUCTION

Advances in wearable sensor technology now enable frequent, objective monitoring of real-world walking. Walking-related digital mobility outcomes (DMOs), such as real-world walking speed, have the potential to be more sensitive to mobility changes than traditional clinical assessments. However, it is not yet clear which DMOs are most suitable for formal validation. In this review, we will explore the evidence on discriminant ability, construct validity, prognostic value and responsiveness of walking-related DMOs in four disease areas: Parkinson's disease, multiple sclerosis, chronic obstructive pulmonary disease and proximal femoral fracture.

METHODS AND ANALYSIS

Arksey and O'Malley's methodological framework for scoping reviews will guide study conduct. We will search seven databases (Medline, CINAHL, Scopus, Web of Science, EMBASE, IEEE Digital Library and Cochrane Library) and grey literature for studies which (1) measure differences in DMOs between healthy and pathological walking, (2) assess relationships between DMOs and traditional clinical measures, (3) assess the prognostic value of DMOs and (4) use DMOs as endpoints in interventional clinical trials. Two reviewers will screen each abstract and full-text manuscript according to predefined eligibility criteria. We will then chart extracted data, map the literature, perform a narrative synthesis and identify gaps.

ETHICS AND DISSEMINATION

As this review is limited to publicly available materials, it does not require ethical approval. This work is part of Mobilise-D, an Innovative Medicines Initiative Joint Undertaking which aims to deliver, validate and obtain regulatory approval for DMOs. Results will be shared with the scientific community and general public in cooperation with the Mobilise-D communication team.

REGISTRATION

Study materials and updates will be made available through the Center for Open Science's OSFRegistry (https://osf.io/k7395).

Growing research in geriatric medicine

Academic geriatric medicine activity lags behind the scale of clinical activity in the specialty. A meeting of UK academic geriatricians was convened in March 2018 to consider causes and solutions to this problem. The meeting highlighted a lack of research-active clinicians, a perception that research is not central to the practice of geriatric medicine and a failure to translate discovery science to clinical studies. Solutions proposed included better support for early-career clinical researchers, schemes to encourage non-University clinicians to be research-active, wider collaboration with organ specialists to broaden the funding envelope, and the need to co-produce research programmes with end-users. Solutions to grow academic geriatric medicine are essential if we are to provide the best care for the growing older population.

Postural Dynamics Are Associated With Cognitive Decline in Parkinson's Disease

Early features of Parkinson's disease (PD) include both motor and cognitive changes, suggesting shared common pathways. A common motor dysfunction is postural instability, a known predictor of falls, which have a major impact on quality of life. Understanding mechanisms of postural dynamics in PD and specifically how they relate to cognitive changes is essential for developing effective interventions. The aims of this study were to examine the changes that occur in postural metrics over time and explore the relationship between postural and cognitive dysfunction. The study group consisted of 35 people (66 ± 8years, 12 female, UPDRS III: 22.5 ± 9.6) diagnosed with PD who were recruited as part of the Incidence of Cognitive Impairment in Cohorts with Longitudinal Evaluation—PD Gait (ICICLE-GAIT) study. Postural and cognitive assessments were performed at 18, 36, and 54 months after enrolment. Participants stood still for 120 s, eyes open and arms by their side. Postural dynamics were measured using metrics derived from a single tri-axial accelerometer (Axivity AX3, York, UK) on the lower back. Accelerometry metrics included jerk (derivative of acceleration), root mean square, frequency, and ellipsis (acceleration area). Cognition was evaluated by neuropsychological tests including the Montreal Cognitive Assessment (MoCA) and digit span. There was a significant decrease in accelerometry parameters, greater in the anteroposterior direction, and a decline in cognitive function over time. Accelerometry metrics were positively correlated with lower cognitive function and increased geriatric depression score and negatively associated with a qualitative measure of balance confidence. In conclusion, people with PD showed reduced postural dynamics that may represent a postural safety strategy. Associations with cognitive function and depression, both symptoms that may pre-empt motor symptoms, suggest shared neural pathways. Further studies, involving neuroimaging, may determine how these postural parameters relate to underlying neural and clinical correlates.

metabolic profiling of Parkinson's disease and mild cognitive impairment

BACKGROUND

Early diagnosis of Parkinson's disease and mild cognitive impairment is important to enable prompt treatment and improve patient welfare, yet no standard diagnostic test is available. Metabolomics is a powerful tool used to elucidate disease mechanisms and identify potential biomarkers.

OBJECTIVES

The objective of this study was to use metabolic profiling to understand the pathoetiology of Parkinson's disease and to identify potential disease biomarkers.

METHODS

This study compared the serological metabolomic profiles of early-stage Parkinson's patients (diagnosed < 12 months) to asymptomatic matched controls using an established array based detection system (DiscoveryHD4™, Metabolon, UK), correlating metabolite levels to clinical measurements of cognitive impairment.

RESULTS

A total of 1434 serological metabolites were assessed in early-stage Parkinson's disease cases (n = 41) and asymptomatic matched controls (n = 40). Post-quality control, statistical analysis identified n = 20 metabolites, predominantly metabolites of the fatty acid oxidation pathway, associated with Parkinson's disease and mild cognitive impairment. Receiver operator curve assessment confirmed that the nine fatty acid oxidation metabolites had good predictive accuracy (area under curve = 0.857) for early-stage Parkinson's disease and mild cognitive impairment (area under curve = 0.759).

CONCLUSIONS

Our study indicates that fatty acid oxidation may be an important component in the pathophysiology of Parkinson's disease and may have potential as a diagnostic biomarker for disease onset and mild cognitive impairment. © 2017 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

The Role of Vitamin D in Disease Progression in Early Parkinson's Disease

BACKGROUND

Previous cross-sectional studies have shown that Parkinson's disease (PD) patients have lower serum 25-hydroxy vitamin D (25(OH)D) concentrations than controls. Vitamin D deficiency was associated with increased disease severity and cognitive impairment in prevalent PD patients.

OBJECTIVE

The aim of the study was to determine 25(OH)D in newly diagnosed PD and age-matched controls and to assess if there was an association with clinical outcomes (disease severity, cognition and falls) over the 36-month follow up period.

METHODS

A prospective observational study of newly diagnosed PD patients in the North East of England with age-matched controls (PD, n = 145; control, n = 94). Serum 25(OH)D was assessed at baseline and 18 months. Participants underwent clinical assessment at baseline, 18 and 36 months. One hundred and ten participants with PD also took part in a prospective falls study.

RESULTS

Mean serum 25(OH)D concentrations were lower in PD than control participants at baseline (44.1±21.7 vs. 52.2±22.1 nmol/L, p < 0.05) and 18 months (44.2±23.6 vs. 55.7±28.8 nmol/L, p < 0.05). Baseline serum 25(OH)D concentration, age, motor score and dosage of dopaminergic medication were significant predictors of variance of motor severity at 36 months ((ΔR2 = 0.039, F = 6.6, p < 0.01). Serum 25(OH)D was not associated with cognition or falls during the follow up period.

CONCLUSIONS

Patients with incident PD had significantly lower serum 25(OH)D concentrations than age-matched controls, which may have implications in terms of bone health and fracture risk. There was a small but significant association between vitamin D status at baseline and disease motor severity at 36 months.

Reduced cerebrospinal fluid mitochondrial DNA is a biomarker for early-stage Parkinson's disease

The identification of cell-free circulating mitochondrial DNA (ccf-mtDNA) in early-stage Alzheimer's disease (AD) raised the possibility that the same neurodegenerative effect could be observed in Parkinson's disease (PD). Here, and for the first time, we investigated the role of ccf-mtDNA in PD, identifying a significant reduction of ccf-mtDNA in PD patient cerebrospinal fluid (CSF) when compared to controls. Our data demonstrates that CSF ccf-mtDNA is not only a powerful biomarker for PD, but, given that the effect is also observed in AD, is likely a biomarker for neurodegeneration.

Reduced mitochondrial DNA copy number is a biomarker of Parkinson's disease

Like any organ, the brain is susceptible to the march of time and a reduction in mitochondrial biogenesis is a hallmark of the aging process. In the largest investigation of mitochondrial copy number in Parkinson's disease (PD) to date and by using multiple tissues, we demonstrate that reduced Parkinson DNA (mitochondrial DNA mtDNA) copy number is a biomarker for the etiology of PD. We used established methods of mtDNA quantification to assess the copy number of mtDNA in n = 363 peripheral blood samples, n = 151 substantia nigra pars compacta tissue samples and n = 120 frontal cortex tissue samples from community-based PD cases fulfilling UK-PD Society brain bank criteria for the diagnosis of PD. Accepting technical limitations, our data show that PD patients suffer a significant reduction in mtDNA copy number in both peripheral blood and the vulnerable substantia nigra pars compacta when compared to matched controls. Our study indicates that reduced mtDNA copy number is restricted to the affected brain tissue, but is also reflected in the peripheral blood, suggesting that mtDNA copy number may be a viable diagnostic predictor of PD.

Variation in complement protein C1q is not a major contributor to cognitive impairment in Parkinson's disease

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Cognitive decline is a strong hallmark of PD.

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Genetic variation in C1Q – does not account for the cognitive decline seen in PD.

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Genetic variation in C1Q – is unlikely to contribute to PD aetiology.

Traditional dogma regarding the brain as an immune exempt organ has changed in recent years. New research has highlighted the role of the classical complement cascade in both synaptic elimination and function, driven largely by the role of the pathway initiating protein C1q. Given the links between C1q and cognitive function we assessed the genetic variability of the C1q encoding genes: C1QA, C1QB and C1QC between PD patients and matched controls. Despite a strong link between C1Q/cognitive decline and PD/cognitive decline we were unable to find a link between common C1Q variation and PD. We conclude that common C1Q-A/B/C genetic variation is unlikely to contribute to cognitive decline or the missing heritability in PD.

Cognition and gait show a selective pattern of association dominated by phenotype in incident Parkinson's disease

Reports outlining the association between gait and cognition in Parkinson’s disease (PD) are limited because of methodological issues and a bias toward studying advanced disease. This study examines the association between gait and cognition in 121 early PD who were characterized according to motor phenotype, and 184 healthy older adults. Quantitative gait was captured using a 7 m GAITrite walkway while walking for 2 min under single-task conditions and described by five domains (pace, rhythm, variability, asymmetry, and postural control). Cognitive outcomes were summarized by six domains (attention, working memory, visual memory, executive function, visuospatial function, and global cognition). Partial correlations and multivariate linear regression were used to determine independent associations for all participants and for PD tremor-dominant (TD) and postural instability and gait disorder (PIGD) phenotypes, controlling for age, sex, and premorbid intelligence using the national adult reading test. Cognitive and gait outcomes were significantly worse for PD. Gait, but not cognitive outcomes, was selectively worse for the PIGD phenotype compared with TD. Significant associations emerged for two gait domains for controls (pace and postural control) and four gait domains for PD (pace, rhythm, variability, and postural control). The strongest correlation was for pace and attention for PD and controls. Associations were not significant for participants with the TD phenotype. In early PD, the cognitive correlates of gait are predominantly with fronto-executive functions, and are characterized by the PIGD PD phenotype. These associations provide a basis for understanding the complex role of cognition in parkinsonian gait.

Vitamin D supplementation in older people (VDOP): Study protocol for a randomised controlled intervention trial with monthly oral dosing with 12,000 IU, 24,000 IU or 48,000 IU of vitamin D₃

The randomised, double blind intervention trial ‘Optimising Vitamin D Status in Older People’ (VDOP) will test the effect of three oral dosages of vitamin D given for one year on bone mineral density (BMD) and biochemical markers of vitamin D metabolism, bone turnover and safety in older people. VDOP is funded by Arthritis Research UK, supported through Newcastle University and MRC Human Nutrition Research and sponsored by the Newcastle upon Tyne Hospitals NHS Foundation Trust.^a