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Background: Few studies have examined the associations between changes in depressive symptoms and handgrip strength in older people. This study aimed to examine the magnitude of the association between depressive symptoms over 2 years and weak handgrip strength on the 4 years of follow-up.Methods: We conducted a longitudinal study using data from the English Longitudinal Study of Aging, a nationally representative panel survey of older adults in England. Data were derived from waves 4 (2008-2009), 5 (2010-2011), and 6 (2012-2013). A total of 5,080 participants were included in the analysis. Depressive symptoms were dichotomized using the eight-item Center for Epidemiological Studies Depression Scale in waves 4 and 5 and were regarded as the exposure. Handgrip strength measurements objectively measured in wave 6 were dichotomized according to the 25th percentile of the British norm and used as the outcome. The targeted maximum likelihood estimation model was utilized to assess time-variant depressive symptoms on handgrip strength, adjusted for time-variant and time-invariant covariates.Results: The maintenance of non-depressive symptoms (relative risk [RR], 0.72; 95% confidence interval [CI], 0.59-0.87) or improvement of depressive symptoms (RR, 0.71; 95% CI, 0.55-0.91) had a protective effect on weak handgrip strength compared with the persistence of depressive symptoms.Limitation: This study is not a randomized control trial but a longitudinal observational study, indicating that our study finding may still have been affected by unknown confounders.Conclusion: Our findings suggest the importance of managing depressive symptoms to prevent poor physical function. [ABSTRACT FROM AUTHOR]

Objectives: This study aimed to determine whether responses to Patient-Reported Outcomes Measurement Information System Short Form v2.0 - Physical Function 8c (PROMIS PF8c) items differed when the use of a 7-day recall period was compared with no specified recall period.Methods: Using a within-subject design, we surveyed 1810 individuals from the US general population, administering PROMIS PF8c at survey beginning and end. The order of measure presentation was randomly assigned. We calculated recall difference scores (RDSs) as no recall score minus 7-day recall score using both item response theory-based T scores and raw summed scores. We examined the distribution and created Bland-Altman plots for both RDSTscore and RDSRaw. We also calculated correlations between no recall versus 7-day recall T score and raw scores. Finally, we determined whether differences in no recall versus 7-day recall scores were associated with patient-reported PF.Results: RDSTscore and RDSRaw had means (root mean square differences) of 0.00 (5.43) and -0.04 (3.79), respectively. The vast majority (%) of RDSTscore and RDSRaw values fell between the Bland-Altman limits of agreement (-10.65 to 10.66 and -7.46 to 7.38, respectively). Pearson's correlations between no recall and 7-day recall for T scores and raw scores were 0.88 and 0.87, respectively. Effect sizes for mean RDSTscore and RDSRaw compared across level of Eastern Oncology Cooperative Group performance status, patient global impression of PF severity, and single PF items were near 0.Conclusions: We did not find any significant recall period effect on PF8c responses. Therefore, we recommend the use of the PROMIS physical function standard, with no specified recall time period. [ABSTRACT FROM AUTHOR]

Context: Sickle cell disease (SCD) is associated with recurrent pain that could lead to abnormal sensory patterns (ASPs).Objectives: The purpose of this study is to compare children with SCD who had normal sensory patterns (NSPs) and ASPs in pain experience, physical function, pain coping, and pain catastrophizing.Methods: Children with quantitative sensory testing data were selected from a larger study that examined pain and symptoms in children with SCD. Comparisons were made between children with NSP (n = 35; 13.9 ± 1.9 years) and ASP (n = 13; 12.8 ± 1.9 years). Children completed the Adolescent Pediatric Pain Tool, Functional Disability Inventory, Pain Coping Questionnaire, and Pain Catastrophizing Scale.Results: No significant differences were found in pain intensity (2.9 ± 3.0 vs. 2.6 ± 2.8 on 0-10 Visual Analogue Scale) between the NSP and ASP, respectively. The most common marked pain sites for both groups were lower extremities (22.9%), head and neck (20.8%), and upper extremities (20.8%). Functional Disability Inventory scores were significantly worse in ASP (38.5%) compared with NSP (11.4%). The ASP group had significantly worse scores in emotion-focused pain coping subscales.Conclusion: Children with SCD with ASP had worse functional disability, were expressing more affective pain quality, and had emotion-focused pain coping compared with NSP. Future studies are needed to examine the effectiveness of physical activities on the physical function as well as psychosocial interventions such as peer support and creative arts expression to minimize development of ASP in children with SCD. [ABSTRACT FROM AUTHOR]

Linking geospatial neighbourhood design characteristics to health and behavioural data from population-representative cohorts is limited by data availability and difficulty collecting information on environmental characteristics (e.g. greenery, building setbacks, dwelling structure). As an alternative, this study examined the feasibility of Generative Adversarial Networks (GANs) - machine learning - to measure neighbourhood design using 'street view' and aerial imagery to explore the relationship between the built environment and physical function. This study included 3102 adults aged 45 years and older clustered in 200 neighbourhoods in 2016 from the How Areas in Brisbane Influence Health and Activity (HABITAT) project in Brisbane, Australia. Exposure data were Google Street View and Google Maps images from within the 200 neighbourhoods, and outcome data were self-reported physical function using the PF-10 (a subset of the SF-36). Physical function scores were aggregated to the neighbourhood level, and the highest and lowest 20 neighbourhoods respectively were used in analysis. We found that the aerial imagery retrieved was unable to be used to adequately train the model, meaning that aerial imagery failed to produce meaningful results. Of the street view images, n = 56,330 images were downloaded and used to train the GAN model. Model outputs included augmented street view images between neighbourhoods classed as having high function and low function residents. The GAN model detected differences in neighbourhood design characteristics between neighbourhoods classed as high and low physical function at the aggregate level. Specifically, differences were identified in urban greenery (including tree heights) and dwelling structure (e.g. building height). This study provides important lessons for future work in this field, especially related to the uniqueness, diversity and amount of imagery required for successful applications of deep learning methods. [ABSTRACT FROM AUTHOR]