A cross-sectional and 6-year follow-up study of associations between leisure time physical activity and vertebral fracture in adults

Introduction: Vertebral fractures are common osteoporotic fractures, affecting 2–46% of the population, causing morbidity and increased risk of mortality. Physical activity has beneficial effects for bone health, including increased bone mineral density and reduced hip fractures. However, evidence concerning prevention of vertebral fractures is scarce. Therefore, the aim of this study was to investigate the association between leisure time physical activity and vertebral fracture risk. Methods: The data were retrieved from the 2001 and 2007–2008 surveys of the Tromsø Study, a longitudinal population study in Norway. A total of 1904 participants (1030 women and 874 men, age 38–87 yr and 40–87 yr respectively) were included in the cross-sectional analysis (2007–2008). Prospective follow-up data (2001 to 2007) on physical activity were available for 1131 participants (636 women and 495 men, age 32–69 yr and 33–69 yr respectively). Physical activity was assessed by a questionnaire and vertebral fracture by lateral vertebral fracture assessment from dual-energy x-ray absorptiometry scans. Logistic regression was used to examine associations between physical activity and vertebral fracture. Results: After controlling for confounders (age, height, weight, smoking, osteoporosis, osteoporosis medication, left hip total bone mineral density, and use of hormones in women only), no cross-sectional associations between physical activity levels and vertebral fracture were observed, OR 1.13 (95% CI: 0.59–2.13), for moderately active women and 1.44 (0.61–3.42) for highly active women, compared with sedentary women. In men, the respective ORs were 1.74 (95% CI: 0.91–3.35) and 1.64 (0.78–3.41). In the prospective analyses, OR for vertebral fracture in women with reduced physical activity was 0.81 (95% CI: 0.18–3.62), 1.24 (95% CI: 0.29–5.26) for increased physical activity and 1.54 (95% CI: 0.43–5.50) for active unchanged physical activity pattern, compared with sedentary unchanged physical activity. In men, the respective ORs were 2.05 (95% CI: 0.57–7.42), 2.23 (95% CI: 0.63–7.87), and 1.81 (95% CI: 0.54–6.02). Subanalyses of women and men ≥50 yr showed similar results. Conclusions: Our findings suggest that physical activity does not play a major role in preventing vertebral fractures in Norwegian adults. Future studies may benefit from data on incident vertebral fracture, and objectively measured physical activity. Keywords: Epidemiology, Osteoporosis, ExercisepublishedVersionsubmittedVersio

Are Physical Activity and Benefits Maintained After Long-Term Telerehabilitation in COPD?

This study investigated whether physical activity levels and other outcomes were maintained at 1-year from completion of a 2-year telerehabilitation intervention in COPD. During the post-intervention year, nine patients with COPD (FEV1 % of pred. 42.4±19.8%; age 58.1±6 years) were encouraged to exercise on a treadmill at home and monitor daily symptoms and training sessions on a webpage as during the intervention. Participants were not provided supervision or motivational support. Physical activity levels decreased from 3,806 steps/day to 2,817 steps/day (p= 0.039). There was a decline in time spent on light physical activity (p=0.009), but not on moderate-to-vigorous activity (p=0.053). Adherence to registration of symptoms and training sessions decreased significantly. Other outcomes including health status, quality of life, anxiety and depression, self-efficacy, and healthcare utilization did not change significantly. In conclusion, provision of equipment for self-management and unsupervised home exercise might not be enough to maintain physical activity levels

General and local predictors of mandibular cortical bone morphology in adult females and males: the seventh survey of the Tromsø Study

Objectives To analyze factors predicting mandibular cortical width (MCW) and mandibular cortical index (MCI) in adult females and males. Material and methods Data on 427 females and 335 males aged 40–84 from The Tromsø study: Tromsø7 were used. T-score, age, menopausal status (for females), remaining teeth, and periodontal status were analyzed in linear and logistic regression analyses as predictors of MCW and MCI, respectively. Results T-score, age, and the number of remaining teeth significantly predicted MCW in females but not males. Standardized β coefficients were 0.286, −0.231, and 0.131, respectively. The linear regression model explained 24% of MCW variation in females. MCI in females was significantly predicted by T-score, age, and remaining teeth with the Wald values of 9.65, 6.17, and 5.83, respectively. The logistic regression model explained 16.3−23% of the variation in MCI in females. In males, T-score was the only significant predictor of the eroded cortex, and the logistic model explained only 4.3–5.8% of the variation in MCI. Conclusions The T-score demonstrated a stronger relationship with MCW and MCI than other factors in females, which supports the usefulness of those indices for osteoporosis screening. Conversely, the T-score exhibited no association with MCW and remained the only significant predictor of MCI in males, yet to a lesser extent than in females. Clinical relevance Understanding factors affecting mandibular cortical morphology is essential for further investigations of MCW and MCI usefulness for osteoporosis screening in females and males

A novel algorithm to detect non-wear time from raw accelerometer data using deep convolutional neural networks

To date, non-wear detection algorithms commonly employ a 30, 60, or even 90 mins interval or window in which acceleration values need to be below a threshold value. A major drawback of such intervals is that they need to be long enough to prevent false positives (type I errors), while short enough to prevent false negatives (type II errors), which limits detecting both short and longer episodes of non-wear time. In this paper, we propose a novel non-wear detection algorithm that eliminates the need for an interval. Rather than inspecting acceleration within intervals, we explore acceleration right before and right after an episode of non-wear time. We trained a deep convolutional neural network that was able to infer non-wear time by detecting when the accelerometer was removed and when it was placed back on again. We evaluate our algorithm against several baseline and existing non-wear algorithms, and our algorithm achieves a perfect precision, a recall of 0.9962, and an F1 score of 0.9981, outperforming all evaluated algorithms. Although our algorithm was developed using patterns learned from a hip-worn accelerometer, we propose algorithmic steps that can easily be applied to a wrist-worn accelerometer and a retrained classification model

Vertebral fractures assessed by dual-energy X-ray absorptiometry and all-cause mortality. The Tromsø Study 2007-2020

Vertebral fractures have been associated with increased mortality, but findings are inconclusive, and many vertebral fractures avoid clinical attention. We investigated this association in a general population of 2,476 older adults aged ≥55 years from Tromsø, Norway, who were followed over 2007–2020, using dual-energy x-ray absorptiometry (DXA) at baseline to evaluate vertebral fractures (mild, moderate, or severe). We used multiple Cox regression models to estimate hazard ratios (HRs) for all-cause mortality, adjusted for age, sex, body mass index, education, smoking, alcohol intake, cardiovascular disease, and respiratory disease. Mean follow-up in the cohort was 11.2 (standard deviation, 2.7) years; 341 participants (13.8%) had ≥1 vertebral fracture at baseline, and 636 participants (25.7%) died between baseline and follow-up. Full-adjustment models showed a nonsignificant association between vertebral fracture status (yes/no) and mortality. Participants with ≥3 vertebral fractures (HR = 2.43, 95% confidence interval: 1.57, 3.78) or ≥1 severe vertebral fracture (HR = 1.65, 95% confidence interval: 1.26, 2.15) had increased mortality compared with those with no vertebral fractures. Dual-energy x-ray absorptiometry–based screening could be a potent and feasible tool in detecting vertebral fractures that are often clinically silent yet independently associated with premature death. Our data indicated that detailed vertebral assessment could be warranted for a more accurate survival estimation

Cross-sectional associations between prevalent vertebral fracture and pulmonary function. The sixth Tromso Study

Persons with vertebral fracture may have reduced pulmonary function, but this association has not been much studied. The aim of this cross-sectional study was therefore to examine the relationship between vertebral fracture and pulmonary function in a general, elderly population. Vertebral morphometry was used for vertebral fracture assessment in 2132 elderly men (n = 892) and women (n = 1240) aged 55 to 87 years in the population-based Tromsø Study 2007–08. Pulmonary function was examined by spirometry. Pulmonary function was expressed as FVC% predicted, FEV1% predicted, and FEV1/FVC% predicted values, adjusted FVC, FEV1, and FEV1/FVC, and obstructive and restrictive ventilatory impairment. Vertebral fracture was classified according to appearance, number, severity, and location of fractures. Associations were analyzed using general linear and logistic models. FVC% predicted and FEV1% predicted values were not associated with vertebral fracture (P > 0.05), whereas FEV1/FVC% predicted ratio was associated with both prevalent fracture, number of fractures, severity of fractures, and fracture site in men (P < 0.05), but not in women. When FVC, FEV1, and FEV1/FVC values were adjusted for multiple covariates, we found no significant association with vertebral fracture. Obstructive and restrictive ventilatory impairment was not associated with prevalent vertebral fracture. In conclusion, this study did not confirm any clinically relevant associations between prevalent vertebral fracture and ventilatory impairment in elderly individuals

Physical capability, physical activity, and their association with femoral bone mineral density in adults aged 40 years and older: The Tromsø study 2015–2016

Summary: Since muscles can influence bone growth and vice versa, we examined if level of physical activity and physical capability tests can predict areal bone mineral density (aBMD). Both high activity level and good test performance were associated with higher aBMD, especially in women. Introduction: Muscle influences bone formation and vice versa. Tests of physical capability and level of physical activity reflect various muscle qualities. We assessed the associations between total hip aBMD and physical activity as well as a range of standardized physical capability tests in an adult general population. Methods: A total of 3 533 women and men aged 40-84 years, participating in the population-based cross-sectional Tromsø study in Norway in 2015-2016, were included. Linear regression was used to assess associations between aBMD and physical activity and the physical capability tests grip strength, Timed Up and Go (TUG), Short Physical Performance Battery (SPPB), and standing balance. Non-linear associations were examined in cubic spline models. Standardized regression coefficients were calculated to compare effect sizes across physical capability measures. Results: In fully adjusted models, higher physical activity was positively associated with total hip aBMD in both sexes compared to a sedentary lifestyle. All tests of physical capability were associated with aBMD in women, SPPB showing the strongest association although effect sizes were too small to indicate clinically significant differences (1 point increase corresponded to an aBMD increase of 0.009 g/cm2, CI = 0.005 to 0.012). In men, SPPB and its subtests were associated with aBMD with chair rises showing the strongest association (1 s increase in execution time corresponded to an aBMD decrease of 0.005 g/cm2, CI = 0.008 to 0.002). Conclusion: Physical activity was associated with aBMD, and tests of physical capability can account for some of the aBMD variations in adults aged 40 years and older, especially in women

The bidirectional associations between leisure time physical activity change and body mass index gain. The Tromsø Study 1974–2016

Objectives: To examine whether leisure time physical activity changes predict subsequent body mass index (BMI) changes, and conversely, whether BMI changes predict subsequent leisure time physical activity changes. Methods: This prospective cohort study included adults attending ≥3 consecutive Tromsø Study surveys (time: T1, T2, T3) during 1974–2016 (n = 10779). If participants attended >3 surveys, we used the three most recent surveys. We computed physical activity change (assessed by the Saltin-Grimby Physical Activity Level Scale) from T1 to T2, categorized as Persistently Inactive (n = 992), Persistently Active (n = 7314), Active to Inactive (n = 1167) and Inactive to Active (n = 1306). We computed BMI change from T2 to T3, which regressed on preceding physical activity changes using analyses of covariance. The reverse association (BMI change from T1 to T2 and physical activity change from T2 to T3; n = 4385) was assessed using multinomial regression. Results: Average BMI increase was 0.86 kg/m2 (95% CI: 0.82–0.90) from T2 to T3. With adjustment for sex, birth year, education, smoking and BMI at T2, there was no association between physical activity change from T1 to T2 and BMI change from T2 to T3 (Persistently Inactive: 0.89 kg/m2 (95% CI: 0.77–1.00), Persistently Active: 0.85 kg/m2 (95% CI: 0.81–0.89), Active to Inactive: 0.90 kg/m2 (95% CI: 0.79–1.00), Inactive to Active 0.85 kg/m2 (95% CI: 0.75–0.95), p = 0.84). Conversely, increasing BMI was associated with Persistently Inactive (odds ratio (OR): 1.17, 95% CI: 1.08–1.27, p  Conclusions: We found no association between leisure time physical activity changes and subsequent BMI changes, whereas BMI change predicted subsequent physical activity change. These findings indicate that BMI change predicts subsequent physical activity change at population level and not vice versa

Criterion validity of two physical activity and one sedentary time questionnaire against accelerometry in a large cohort of adults and older adults.

OBJECTIVES: We compared the ability of physical activity and sitting time questionnaires (PAQ) for ranking individuals versus continuous volume calculations (physical activity level (PAL), metabolic equivalents of task (MET), sitting hours) against accelerometry measured physical activity as our criterion. METHODS: Participants in a cohort from the Tromsø Study completed three questionnaires; (1) The Saltin-Grimby Physical Activity Level Scale (SGPALS) (n=4040); (2) The Physical Activity Frequency, Intensity and Duration (PAFID) questionnaire (n=5902)) calculated as MET-hours·week-1 and (3) The International Physical Activity questionnaire (IPAQ) short-form sitting question (n=4896). We validated the questionnaires against the following accelerometry (Actigraph wGT3X-BT) estimates: vector magnitude counts per minute, steps∙day-1, time (minutes·day-1) in sedentary behaviour, light physical activity, moderate and vigorous physical activity (MVPA) non-bouted and ≥10 min bouted MVPA. RESULTS: Ranking of physical activity according to the SGPALS and quartiles (Q) of MET-hours∙week-1 from the PAFID were both positively associated with accelerometry estimates of physical activity (p<0.001) but correlations with accelerometry estimates were weak (SGPALS (PAL): r=0.11 to 0.26, p<0.001) and weak-to-moderate (PAFID: r=0.39 to 0.44, p<0.01). There was 1 hour of accelerometry measured sedentary time from Q1 to Q4 in the IPAQ sitting question (p<0.001) and also weak correlations (r=0.22, p<0.01). CONCLUSION: Ranking of physical activity levels measured with PAQs appears to have higher validity than energy expenditure calculations. Self-reported sedentary time poorly reflects accelerometry measured sedentary time. These two PAQs can be used for ranking individuals into different physical activity categories supporting previous studies using these instruments when assessing associations with health outcomes