Neurodegenerative disorders (NDDs) constitute an increasing global burden and can significantly impair an individual’s mobility, physical activity (PA), and independence. Remote monitoring has been difficult without relying on diaries/questionnaires which are more challenging for people with dementia to complete. Wearable global positioning system (GPS) sensors and accelerometers present a cost-effective and noninvasive way to passively monitor mobility and PA. In addition, changes in sensor-derived outcomes (such as walking behaviour, sedentary, and active activity) may serve as potential biomarkers of disease onset, progression, and response to treatment. We performed a systematic search across four databases to identify papers published within the past 5 years, in which wearable GPS or accelerometers were used to monitor mobility or PA in patients with common NDDs (Parkinson’s disease, Alzheimer’s disease, motor neuron diseases/amyotrophic lateral sclerosis, vascular parkinsonism, and vascular dementia). Disease and technology-specific vocabulary were searched singly, and then in combination, identifying 4985 papers. Following deduplication, we screened 3115 papers and retained 28 studies following a full text review. One study used wearable GPS and accelerometers, while 27 studies used solely accelerometers in NDDs. GPS-derived measures had been validated against current gold standard measures in one Parkinson’s cohort, suggesting that the technology may be applicable to other NDDs. In contrast, accelerometers are widely utilised in NDDs and have been operationalised in well-designed clinical trials.

Dementia is the most common neurodegenerative disorder globally. Disease progression is marked by declining cognitive function accompanied by changes in mobility. Increased sedentary behaviour and, conversely, wandering and becoming lost are common. Global positioning system (GPS) solutions are increasingly used by caregivers to locate missing people with dementia (PwD) but also offer a non-invasive means of monitoring mobility patterns in PwD. We performed a systematic search across five databases to identify papers published since 2000, where wearable or portable GPS was used to monitor mobility in patients with common dementias or mild cognitive impairment (MCI). Disease and GPS-specific vocabulary were searched singly, and then in combination, identifying 3004 papers. Following deduplication, we screened 1972 papers and retained 17 studies after a full-text review. Only 1/17 studies used a wrist-worn GPS solution, while all others were variously located on the patient. We characterised the studies using a conceptual framework, finding marked heterogeneity in the number and complexity of reported GPS-derived mobility outcomes. Duration was the most frequently reported category of mobility reported (15/17), followed by out of home (14/17), and stop and trajectory (both 10/17). Future research would benefit from greater standardisation and harmonisation of reporting which would enable GPS-derived measures of mobility to be incorporated more robustly into clinical trials.

At birth, the neonatal skeleton contains 20 to 30 g calcium (Ca). It is hypothesized maternal bone mineral may be mobilized to support fetal skeletal development, although evidence of pregnancy-induced mineral mobilization is limited. We recruited healthy pregnant (n = 53) and non-pregnant non-lactating (NPNL; n = 37) women aged 30 to 45 years (mean age 35.4 ± 3.8 years) and obtained peripheral quantitative computed tomography (pQCT) and high-resolution pQCT (HR-pQCT) scans from the tibia and radius at 14 to 16 and 34 to 36 weeks of pregnancy, with a similar scan interval for NPNL. Multiple linear regression models were used to assess group differences in change between baseline and follow-up; differences are expressed as standard deviation scores (SDS) ± SEM. Decreases in volumetric bone mineral density (vBMD) outcomes were found in both groups; however, pregnancy-related decreases for pQCT total and trabecular vBMD were −0.65 ± 0.22 SDS and −0.50 ± 0.23 SDS greater (p < .05). HR-pQCT total and cortical vBMD decreased compared with NPNL by −0.49 ± 0.24 SDS and −0.67 ± 0.23 SDS, respectively; trabecular vBMD decreased in both groups to a similar magnitude. Pregnancy-related changes in bone microarchitecture significantly exceeded NPNL change for trabecular number (0.47 ± 0.23 SDS), trabecular separation (−0.54 ± 0.24 SDS), cortical thickness (−1.01 ± 0.21 SDS), and cortical perimeter (0.78 ± 0.23 SDS). At the proximal radius, cortical vBMD and endosteal circumference increased by 0.50 ± 0.23 SDS and 0.46 ± 0.23 SDS, respectively, compared with NPNL, whereas cortical thickness decreased −0.50 ± 0.22 SDS. Pregnancy-related decreases in total and compartment-specific vBMD exceed age-related change at the distal tibia. Changes at the radius were only evident with pQCT at the cortical-rich proximal site and suggest endosteal resorption. Although the magnitude of these pregnancy-related changes in the appendicular skeleton are small, if they reflect global changes across the skeleton at large, they may contribute substantially to the Ca requirements of the fetus. © 2020 Crown copyright. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR). This article is published with the permission of the Controller of HMSO and the Queen's Printer for Scotland.

Parkinson's disease (PD) is the second most common neurodegenerative disease after Alzheimer's disease and affects about 1% of the population over the age of 60 years in industrialised countries. The aim of this review is to examine nutrition in PD across three domains: dietary intake and the development of PD; whole body metabolism in PD and the effects of PD symptoms and treatment on nutritional status. In most cases, PD is believed to be caused by a combination of genetic and environmental factors and although there has been much research in the area, evidence suggests that poor dietary intake is not a risk factor for the development of PD. The evidence about body weight changes in both the prodromal and symptomatic phases of PD is inconclusive and is confounded by many factors. Malnutrition in PD has been documented as has sarcopaenia, although the prevalence of the latter remains uncertain due to a lack of consensus in the definition of sarcopaenia. PD symptoms, including those which are gastrointestinal and non-gastrointestinal, are known to adversely affect nutritional status. Similarly, PD treatments can cause nausea, vomiting and constipation, all of which can adversely affect nutritional status. Given that the prevalence of PD will increase as the population ages, it is important to understand the interplay between PD, comorbidities and nutritional status. Further research may contribute to the development of interventional strategies to improve symptoms, augment care and importantly, enhance the quality of life for patients living with this complex neurodegenerative disease.

Traditional analysis of High Resolution peripheral Quantitative Computed Tomography (HR-pQCT) images results in a multitude of cortical and trabecular parameters which would be potentially cumbersome to interpret for clinicians compared to user-friendly tools utilising clinical parameters. A computer vision approach (by which the entire scan is 'read' by a computer algorithm) to ascertain fracture risk, would be far simpler. We therefore investigated whether a computer vision and machine learning technique could improve upon selected clinical parameters in assessing fracture risk. Participants of the Hertfordshire Cohort Study (HCS) attended research visits at which height and weight were measured; fracture history was determined via self-report and vertebral fracture assessment. Bone microarchitecture was assessed via HR-pQCT scans of the non-dominant distal tibia (Scanco XtremeCT), and bone mineral density measurement and lateral vertebral assessment were performed using dual-energy X-ray absorptiometry (DXA) (Lunar Prodigy Advanced). Images were cropped, pre-processed and texture analysis was performed using a three-dimensional local binary pattern method. These image data, together with age, sex, height, weight, BMI, dietary calcium and femoral neck BMD, were used in a random-forest classification algorithm. Receiver operating characteristic (ROC) analysis was used to compare fracture risk identification methods. Overall, 180 males and 165 females were included in this study with a mean age of approximately 76 years and 97 (28 %) participants had sustained a previous fracture. Using clinical risk factors alone resulted in an area under the curve (AUC) of 0.70 (95 % CI: 0.56-0.84), which improved to 0.71 (0.57-0.85) with the addition of DXA-measured BMD. The addition of HR-pQCT image data to the machine learning classifier with clinical risk factors and DXA-measured BMD as inputs led to an improved AUC of 0.90 (0.83-0.96) with a sensitivity of 0.83 and specificity of 0.74. These results suggest that using a three-dimensional computer vision method to HR-pQCT scanning may enhance the identification of those at risk of fracture beyond that afforded by clinical risk factors and DXA-measured BMD. This approach has the potential to make the information offered by HR-pQCT more accessible (and therefore) applicable to healthcare professionals in the clinic if the technology becomes more widely available.

Antiretroviral therapy roll-out has dramatically reduced HIV related-mortality; more women are living to reach menopause. Menopausal estrogen loss causes bone loss, as does HIV and some of its treatments. However, data describing HIV’s impact on osteoporosis prevalence and fracture risk are scarce in southern Africa. A cross-sectional study of women aged 40-60 years (49% women living with HIV (WLH)) was conducted in Harare, Zimbabwe. Menopause, fracture and HIV history were collected, and anthropometry and bone mineral density (BMD, by dual-energy x-ray absorptiometry (DXA)) measured, and FRAX® 10-year fracture probabilities quantified. The FRAX® probability of a major osteoporotic fracture (MOF) included HIV as a risk factor for secondary osteoporosis. Linear and Poisson regression determined the relationships between clinical risk factors and both femoral neck (FN) BMD and the 10-year FRAX® probability of MOF respectively. The 393 participants had mean(SD) age of 49.6(SD = 5.8) years and mean(SD) BMI 29.1(6) kg/m². 95% of WLH were ART established (85% TDF) and 81% had a viral load <50 copies/mL. A BMD T-Score ≤ -2.5 was more common in WLH than those without, at both FN and lumbar spine (LS) (FN 22[11.4%] vs 5[2.5%], LS 40[20.8%] vs 9[4.5%]; respectively). Prior fracture was more prevalent in WLH: any fracture type (27[14%] vs. 14[7%]); MOF (14[7.3%] vs. 5[2.5%]). WLH had a higher 10-year MOF probability [median 1.2%; IQR: 0.9-1.8] compared with those without HIV [1.0%; IQR: 0.9-1.5] (P<.001), although probabilities were low. Older age, low weight, and HIV infection were strongly associated with lower FN BMD. Higher probability of MOF was associated with older age, HIV infection, parental hip fracture and prior fracture, though adjustment attenuated the association with HIV. No woman reported anti-osteoporosis medication use. While osteoporosis and previous fractures were common and untreated in this relatively young population, particularly in WLH, the FRAX® predicted 10-year MOF risk was low. Clinical risk factors considered in fracture risk prediction tools in Zimbabwe may need contextual modification. Improved access to treatment for HIV now means women living with HIV are able to live well into older adulthood; however, this puts them at risk of age-related diseases such as osteoporosis. HIV and some of its treatments are known to cause bone loss, as does menopause, but studies on osteoporosis and fracture risk are scarce in southern Africa, where most people with HIV live. In this study in Zimbabwe, we found women with HIV were more likely to have osteoporosis and to have had a fracture, and a higher risk of having a major osteoporotic fracture over the next 10 years, compared with women without HIV (calculated using FRAX®: a fracture risk prediction tool), although the risk was surprisingly low. Older age, being underweight, and having HIV were strongly related to lower bone density at hip (an important site for fractures). Higher risk of future fracture was associated with older age, previous fracture, having HIV, and having a parent who had a hip fracture. Despite these findings, no woman had ever been offered any anti-osteoporosis medication. Our findings suggest that osteoporosis is under-recognized and undertreated in Zimbabwe, where clinical fracture risk prediction tools need to be modified for the specific context.