Imputing accelerometer non-wear time when assessing children's moderate-to-vigorous physical activity

BACKGROUND: Moderate-to-vigorous physical activity (MVPA) is an important determinant of children’s physical health, and is commonly measured using accelerometers. A major limitation of accelerometers is non-wear time, which is the time the participant did not wear their device. Given that non-wear time is traditionally discarded from the dataset prior to estimating MVPA, final estimates of MVPA may be biased. Therefore, alternate approaches should be explored. OBJECTIVES: The objectives of this thesis were to 1) develop and describe an imputation approach that uses the socio-demographic, time, health, and behavioural data from participants to replace non-wear time accelerometer data, 2) determine the extent to which imputation of non-wear time data influences estimates of MVPA, and 3) determine if imputation of non-wear time data influences the associations between MVPA, body mass index (BMI), and systolic blood pressure (SBP). METHODS: Seven days of accelerometer data were collected using Actical accelerometers from 332 children aged 10-13. Three methods for handling missing accelerometer data were compared: 1) the “non-imputed” method wherein non-wear time was deleted from the dataset, 2) imputation dataset I, wherein the imputation of MVPA during non-wear time was based upon socio-demographic factors of the participant (e.g., age), health information (e.g., BMI), and time characteristics of the non-wear period (e.g., season), and 3) imputation dataset II wherein the imputation of MVPA was based upon the same variables as imputation dataset I, plus organized sport information. Associations between MVPA and health outcomes in each method were assessed using linear regression. RESULTS: Non-wear time accounted for 7.5% of epochs during waking hours. The average minutes/day of MVPA was 56.8 (95% CI: 54.2, 59.5) in the non-imputed dataset, 58.4 (95% CI: 55.8, 61.0) in imputed dataset I, and 59.0 (95% CI: 56.3, 61.5) in imputed dataset II. Estimates between datasets were not significantly different. The strength of the relationship between MVPA with BMI and SBP were comparable between all three datasets. CONCLUSION: These findings suggest that studies that achieve high accelerometer compliance with unsystematic patterns of missing data can use the traditional approach of deleting non-wear time from the dataset to obtain MVPA measures without substantial bias.

Monitoring of Dynamic Bridge Behaviour Using Digital Image Correlation

Bridges are a critical part of North America’s transportation network that need to be assessed frequently to inform bridge management decision making. Visual inspections are usually implemented for this purpose, during which inspectors must observe and report any excess displacements or vibrations. Unfortunately, these visual inspections are subjective and often highly variable and so a monitoring technology that can provide quantitative measurements to supplement inspections is needed. Digital Image Correlation (DIC) is a novel monitoring technology that uses digital images to measure displacement fields without any contact with the bridge. In this research, DIC and accelerometers were used to investigate the dynamic response of a railway bridge reported to experience large lateral displacements. Displacements were estimated using accelerometer measurements and were compared to DIC measurements. It was shown that accelerometers can provide reasonable estimates of displacement for zero-mean lateral displacements. By comparing measurements in the girder and in the piers, it was shown that for the bridge monitored, the large lateral displacements originated in the steel casting bearings positioned above the piers, and not in the piers themselves. The use of DIC for evaluating the effectiveness of rehabilitation of the LaSalle Causeway lift bridge in Kingston, Ontario was also investigated. Vertical displacements were measured at midspan and at the lifting end of the bridge during a static test and under dynamic live loading. The bridge displacements were well within the operating limits, however a gap at the lifting end of the bridge was identified. Rehabilitation of the bridge was conducted and by comparing measurements before and after rehabilitation, it was shown that the gap was successfully closed. Finally, DIC was used to monitor the midspan vertical and lateral displacements in a monitoring campaign of five steel rail bridges. DIC was also used to evaluate the effectiveness of structural rehabilitation of the lateral bracing of a bridge. Simple finite element models are developed using DIC measurements of displacement. Several lessons learned throughout this monitoring campaign are discussed in the hope of aiding future researchers.

Shiftwork, sleep disturbance and the metabolic syndrome among female hospital workers

Background: Shiftwork is associated with increased sleep disturbance and cardiovascular and metabolic disease risk. This thesis will focus on shiftwork-related sleep disturbance and the potential mediating role of reduced sleep duration in the relationship between a current rotational shiftwork schedule and the metabolic syndrome among female hospital employees. Objectives: 1) To describe sleep patterns in relation to different shiftwork exposure metrics (current status, cumulative exposure, number of consecutive night shifts); 2) To assess the association between shiftwork metrics and sleep duration; 3) To determine whether sleep duration on work shifts mediates the relationship between a current rotational shiftwork pattern and the metabolic syndrome; and 4) To assess whether cumulative shiftwork exposure and the number of consecutive night shifts are associated with the metabolic syndrome. Methods: 294 female hospital employees (142 rotating shiftworkers, 152 dayworkers) participated in a cross-sectional study. Shiftwork parameters were determined through self-report. Sleep was measured for one week with the ActiGraph GT3X+, a tri-axial accelerometer. The metabolic syndrome was defined according to the Joint Interim Studies Consensus Statement. Sleep was described by shiftwork exposure parameters, and multivariable linear regression was used to determine associations between shiftwork variables and sleep duration. Regression path analysis was used to assess whether sleep duration was a mediator between a current shiftwork schedule and the metabolic syndrome, and the significance of the indirect (mediating) effect was tested with bootstrap confidence intervals. Logistic regression was used to determine associations between cumulative shiftwork exposure, number of consecutive night shifts, and the metabolic syndrome. Results: Current shiftworkers slept less on work shifts, more on free days, and were more likely to nap compared to dayworkers. Sleep duration on work shifts was a strong intermediate in the relationship between a current shiftwork pattern and the metabolic syndrome. Cumulative shiftwork exposure and the number of consecutive night shifts did not affect sleep or the metabolic syndrome. Conclusions: A current shiftwork pattern disrupts sleep, and reduced sleep duration is an important intermediate between shiftwork and the metabolic syndrome among female hospital employees.