Journal Articles

Permanent URI for this collectionhttps://mro.massey.ac.nz/handle/10179/7915

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    How Lazy Are Pet Cats Really? Using Machine Learning and Accelerometry to Get a Glimpse into the Behaviour of Privately Owned Cats in Different Households
    (MDPI (Basel, Switzerland), 2024-04-19) Smit M; Corner-Thomas R; Draganova I; Andrews C; Thomas D; Friedrich CM
    Surprisingly little is known about how the home environment influences the behaviour of pet cats. This study aimed to determine how factors in the home environment (e.g., with or without outdoor access, urban vs. rural, presence of a child) and the season influences the daily behaviour of cats. Using accelerometer data and a validated machine learning model, behaviours including being active, eating, grooming, littering, lying, scratching, sitting, and standing were quantified for 28 pet cats. Generalized estimating equation models were used to determine the effects of different environmental conditions. Increasing cat age was negatively correlated with time spent active (p < 0.05). Cats with outdoor access (n = 18) were less active in winter than in summer (p < 0.05), but no differences were observed between seasons for indoor-only (n = 10) cats. Cats living in rural areas (n = 7) spent more time eating than cats in urban areas (n = 21; p < 0.05). Cats living in single-cat households (n = 12) spent more time lying but less time sitting than cats living in multi-cat households (n = 16; p < 0.05). Cats in households with at least one child (n = 20) spent more time standing in winter (p < 0.05), and more time lying but less time sitting in summer compared to cats in households with no children (n = 8; p < 0.05). This study clearly shows that the home environment has a major impact on cat behaviour.
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    Use of a Collar-Mounted Triaxial Accelerometer to Predict Speed and Gait in Dogs
    (MDPI (Basel, Switzerland), 2021-05) Bolton S; Cave N; Cogger N; Colborne GR; Gaunet F
    Accelerometry has been used to measure treatment efficacy in dogs with osteoarthritis, although interpretation is difficult. Simplification of the output into speed or gait categories could simplify interpretation. We aimed to determine whether collar-mounted accelerometry could estimate the speed and categorise dogs' gait on a treadmill. Eight Huntaway dogs were fitted with a triaxial accelerometer and then recorded using high-speed video on a treadmill at a slow and fast walk, trot, and canter. The accelerometer data (delta-G) was aligned with the video data and records of the treadmill speed and gait. Mixed linear and logistic regression models that included delta-G and a term accounting for the dogs' skeletal sizes were used to predict speed and gait, respectively, from the accelerometer signal. Gait could be categorised (pseudo-R2 = 0.87) into binary categories of walking and faster (trot or canter), but not into the separate faster gaits. The estimation of speed above 3 m/s was inaccurate, though it is not clear whether that inaccuracy was due to the sampling frequency of the particular device, or whether that is an inherent limitation of collar-mounted accelerometers in dogs. Thus, collar-mounted accelerometry can reliably categorise dogs' gaits into two categories, but finer gait descriptions or speed estimates require individual dog modelling and validation. Nonetheless, this accelerometry method could improve the use of accelerometry to detect treatment effects in osteoarthritis by allowing the selection of periods of activity that are most affected by treatment.
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    Replacing Sedentary Time with Physically Active Behaviour Predicts Improved Body Composition and Metabolic Health Outcomes
    (MDPI (Basel, Switzerland), 2022-07) O'Brien WJ; Rauff EL; Shultz SP; Sloughter M; Fink PW; Breier B; Kruger R
    Background: Discretionary leisure time for health-promoting physical activity (PA) is limited. This study aimed to predict body composition and metabolic health marker changes from PA reallocation using isotemporal substitution analysis. Methods: Healthy New Zealand women (n = 175; 16–45 y) with high BMI (≥25 kg/m2) and high body fat percentage (≥30%) were divided into three groups by ethnicity (Māori n = 37, Pacific n = 54, and New Zealand European n = 84). PA, fat mass, lean mass, and metabolic health were assessed. Isotemporal substitution paradigms reallocated 30 min/day of sedentary behaviour to varying PA intensities. Results: Reallocating sedentary behaviour with moderate intensity, PA predicted Māori women would have improved body fat% (14.83%), android fat% (10.74%), and insulin levels (55.27%) while the model predicted Pacific women would have improved waist-to-hip (6.40%) and android-to-gynoid (19.48%) ratios. Replacing sedentary time with moderate-vigorous PA predicted Māori women to have improved BMI (15.33%), waist circumference (9.98%), body fat% (16.16%), android fat% (12.54%), gynoid fat% (10.04%), insulin (55.58%), and leptin (43.86%) levels; for Pacific women, improvement of waist-to-hip-ratio (5.30%) was predicted. Conclusions: Sedentary behaviour must be substituted with PA of at least moderate intensity to reap benefits. Māori women received the greatest benefits when reallocating PA. PA recommendations to improve health should reflect the needs and current activity levels of specific populations.
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    Fundamental Movement Skills and Physical Activity of 3-4-Year-Old Children within Early Childhood Centers in New Zealand
    (MDPI (Basel, Switzerland), 2021-08-27) Ali A; McLachlan C; McLaughlin T; Mugridge O; Conlon C; Mumme K; Knightbridge-Eager T
    We sought to describe and explore relationships between fundamental movement skills (FMS) and level of physical activity (PA; light-, medium-, vigorous, and kCal/hour) in preschool children, aged 3-4-years-old, across four early childhood education (ECE) settings. Children's FMS were assessed using the Test for Gross Motor Development-2 (TGMD-2; n = 81) and PA via accelerometers (S = 53). Eighty-four children participated, with 50 in both assessments. The TGMD-2 showed as the children got older, their locomotor skills (p < 0.001, r = 0.512) and object control motor skills (p < 0.001, r = 0.383) improved. Accelerometry showed children were primarily inactive at ECE (78.3% of the time). There were significant correlations between kCal/hour and light (p < 0.001, r = -0.688), moderate (p < 0.001, r = 0.599) and vigorous (p < 0.001, rs = 0.707) activity, and between gross motor quotient and locomotor (p < 0.001, r = 0.798) and object control (p < 0.001, r = 0.367) skills. No correlation was observed between gross motor quotient and kCal/hour. To conclude, children in this cohort were primarily inactive during ECE center hours. Moreover, gross motor quotient was significantly correlated to locomotor and object control skills.