Are associations between physical activity and bone mineral density in adults sex- and age-dependent? An analysis of the UK Biobank study

Although physical activity (PA) is recognized as a key bone mass determinant across life, athlete studies suggest that it may be less effective in women and older individuals. This has not been explored within the general population. We aimed to address this knowledge gap using data from the UK Biobank Study, a large population-based study of middle-aged and older adults. Free-living PA data collected at 100 Hz for 7 d using wrist-worn accelerometers were classified as sedentary behavior (0-29 milligravities [mg]), light (30-124 mg), or moderate-to-vigorous PA (125 + mg). LS and FN-BMD were assessed using DXA. The associations between PA and BMD were assessed using linear regression models, with formal assessments of sex and age interactions undertaken and adjustments made for accelerometer wear time, height, body mass index, education, ethnicity, disability, and (in women only) menopausal status. In total, 15 133 UK Biobank participants (52% women) had complete PA, bone, and covariate data. In this sample, greater overall and moderate-to-vigorous PA was associated with higher LS BMD. In women, these associations were typically weaker in older individuals, for example, regression coefficients in women aged 70 yr or older were ~50% lower than at 45-54 yr (age-by-PA interactions P < .01 in all models). Similar associations were observed in basic but not full models for FN BMD. Greater sedentary time was associated with lower LS BMD in men only, and greater light PA and sedentary time were associated with higher and lower FN BMD, respectively, in both sexes. These results suggest that associations between PA and bone health at clinically-relevant sites are weaker in older than younger women. That positive associations are evident between overall and moderate-vigorous PA and FN BMD even in women ≥70 yr suggests that PA for bone health should still be promoted in older women.

Monitoring real-time junior doctor sentiment from comments on a public social media platform: a retrospective observational study

OBJECTIVES

To investigate whether sentiment analysis and topic modelling can be used to monitor the sentiment and opinions of junior doctors.

DESIGN

Retrospective observational study based on comments on a social media website.

SETTING

Every publicly available comment in r/JuniorDoctorsUK on Reddit from 1 January 2018 to 31 December 2021.

PARTICIPANTS

7707 Reddit users who commented in the r/JuniorDoctorsUK subreddit.

MAIN OUTCOME MEASURE

Sentiment (scored -1 to +1) of comments compared with results of surveys conducted by the General Medical Council.

RESULTS

Average comment sentiment was positive but varied significantly during the study period. Fourteen topics of discussion were identified, each associated with a different pattern of sentiment. The topic with the highest proportion of negative comments was the role of a doctor (38%), and the topic with the most positive sentiment was hospital reviews (72%).

CONCLUSION

Some topics discussed in social media are comparable to those queried in traditional questionnaires, whereas other topics are distinctive and offer insight into what themes junior doctors care about. Events during the coronavirus pandemic may explain the sentiment trends in the junior doctor community. Natural language processing shows significant potential in generating insights into junior doctors' opinions and sentiment.

Monitoring real-time junior doctor sentiment from comments on a public social media platform: a retrospective observational study

OBJECTIVES

To investigate whether sentiment analysis and topic modelling can be used to monitor the sentiment and opinions of junior doctors.

DESIGN

Retrospective observational study based on comments on a social media website.

SETTING

Every publicly available comment in r/JuniorDoctorsUK on Reddit from 1 January 2018 to 31 December 2021.

PARTICIPANTS

7707 Reddit users who commented in the r/JuniorDoctorsUK subreddit.

MAIN OUTCOME MEASURE

Sentiment (scored -1 to +1) of comments compared with results of surveys conducted by the General Medical Council.

RESULTS

Average comment sentiment was positive but varied significantly during the study period. Fourteen topics of discussion were identified, each associated with a different pattern of sentiment. The topic with the highest proportion of negative comments was the role of a doctor (38%), and the topic with the most positive sentiment was hospital reviews (72%).

CONCLUSION

Some topics discussed in social media are comparable to those queried in traditional questionnaires, whereas other topics are distinctive and offer insight into what themes junior doctors care about. Events during the coronavirus pandemic may explain the sentiment trends in the junior doctor community. Natural language processing shows significant potential in generating insights into junior doctors' opinions and sentiment.

Dementia with Lewy bodies: association of Alzheimer pathology with functional connectivity networks

Dementia with Lewy bodies (DLB) is neuropathologically defined by the presence of α-synuclein aggregates, but many DLB cases show concurrent Alzheimer's disease pathology in the form of amyloid-β plaques and tau neurofibrillary tangles. The first objective of this study was to investigate the effect of Alzheimer's disease co-pathology on functional network changes within the default mode network (DMN) in DLB. Second, we studied how the distribution of tau pathology measured with PET relates to functional connectivity in DLB. Twenty-seven DLB, 26 Alzheimer's disease and 99 cognitively unimpaired participants (balanced on age and sex to the DLB group) underwent tau-PET with AV-1451 (flortaucipir), amyloid-β-PET with Pittsburgh compound-B (PiB) and resting-state functional MRI scans. The resing-state functional MRI data were used to assess functional connectivity within the posterior DMN. This was then correlated with overall cortical flortaucipir PET and PiB PET standardized uptake value ratio (SUVr). The strength of interregional functional connectivity was assessed using the Schaefer atlas. Tau-PET covariance was measured as the correlation in flortaucipir SUVr between any two regions across participants. The association between region-to-region functional connectivity and tau-PET covariance was assessed using linear regression. Additionally, we identified the region with highest and the region with lowest tau SUVrs (tau hot- and cold spots) and tested whether tau SUVr in all other brain regions was associated with the strength of functional connectivity to these tau hot and cold spots. A reduction in posterior DMN connectivity correlated with overall higher cortical tau- (r = -0.39, P = 0.04) and amyloid-PET uptake (r = -0.41, P = 0.03) in the DLB group, i.e. patients with DLB who have more concurrent Alzheimer's disease pathology showed a more severe loss of DMN connectivity. Higher functional connectivity between regions was associated with higher tau covariance in cognitively unimpaired, Alzheimer's disease and DLB. Furthermore, higher functional connectivity of a target region to the tau hotspot (i.e. inferior/medial temporal cortex) was related to higher flortaucipir SUVrs in the target region, whereas higher functional connectivity to the tau cold spot (i.e. sensory-motor cortex) was related to lower flortaucipir SUVr in the target region. Our findings suggest that a higher burden of Alzheimer's disease co-pathology in patients with DLB is associated with more Alzheimer's disease-like changes in functional connectivity. Furthermore, we found an association between the brain's functional network architecture and the distribution of tau pathology that has recently been described in Alzheimer's disease. We show that this relationship also exists in patients with DLB, indicating that similar mechanisms of connectivity-dependent occurrence of tau pathology might be at work in both diseases.

New Horizons in the use of routine data for ageing research

The past three decades have seen a steady increase in the availability of routinely collected health and social care data and the processing power to analyse it. These developments represent a major opportunity for ageing research, especially with the integration of different datasets across traditional boundaries of health and social care, for prognostic research and novel evaluations of interventions with representative populations of older people. However, there are considerable challenges in using routine data at the level of coding, data analysis and in the application of findings to everyday care. New Horizons in applying routine data to investigate novel questions in ageing research require a collaborative approach between clinicians, data scientists, biostatisticians, epidemiologists and trial methodologists. This requires building capacity for the next generation of research leaders in this important area. There is a need to develop consensus code lists and standardised, validated algorithms for common conditions and outcomes that are relevant for older people to maximise the potential of routine data research in this group. Lastly, we must help drive the application of routine data to improve the care of older people, through the development of novel methods for evaluation of interventions using routine data infrastructure. We believe that harnessing routine data can help address knowledge gaps for older people living with multiple conditions and frailty, and design interventions and pathways of care to address the complex health issues we face in caring for older people.

Structural correlates of attention dysfunction in Lewy body dementia and Alzheimer's disease: an ex-Gaussian analysis

BACKGROUND

Lewy body dementia (LBD) and Alzheimer's disease (AD) are common forms of degenerative dementia. While they are characterized by different clinical profiles, attentional deficits are a common feature. The objective of this study was to investigate how attentional problems in LBD and AD differentially affect different aspects of reaction time performance and to identify possible structural neural correlates.

METHODS

We studied reaction time data from an attention task comparing 39 LBD patients, 28 AD patients, and 22 age-matched healthy controls. Data were fitted to an ex-Gaussian model to characterize different facets of the reaction time distribution (mean reaction time, reaction time variability, and the subset of extremely slow responses). Correlations between ex-Gaussian parameters and grey and white matter volume were assessed by voxel-based morphometry.

RESULTS

Both dementia groups showed an increase in extremely slow responses. While there was no difference between AD and controls with respect to mean reaction time and variability, both were significantly increased in LBD patients compared to controls and AD. There were widespread correlations between mean reaction time and variability and grey matter loss in AD, but not in LBD.

CONCLUSIONS

This study shows that different aspects of reaction time performance are differentially affected by AD and LBD, with a difference in structural neural correlates underlying the observed behavioural deficits. While impaired attentional performance is linked to brain atrophy in AD, in LBD it might be related to functional or microstructural rather than macrostructural changes.