4 resultados para multiple linear regression models

em Brock University, Canada


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Background: The purpose of this study was to examine the relationships between physical activity and healthy eating behaviour with the participant's motives and goals for each health behaviour. Methods: Participants (N 121; 93.2% female) enrolled in commercial weightloss programs at the time of data collection, completed self-reported instruments using a web-based interface that were in accordance with Deci and Ryan's (2002) Self-Determination Theory (SDT). Results: Multiple linear regression models revealed that motivation and goals collectively accounted for between 0.21 to 0.29 percent and 0.03 to 0.16 percent of the variance in physical and healthy eating behaviours in this sample. In general, goals regarding either behaviour did not appear to have strong predictive relationships with each health behaviour beyond the contributions of motives. Discussion: Overall, findings from this study suggest that motives seem to mattermore than goals for both physical activity and healthy eating behaviour in clientele of commercial weight-loss programs. Therefore commercial weight-loss program implementers may want to consider placing more attention on motives I than goals for their clientele when designing weight-loss and weight-maintenance initiatives.

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To examine the association between sleep disorders, obesity status, and the risk of diabetes in adults, a total of 3668 individuals aged 40+ years fromtheNHANES 2009-2010 withoutmissing information on sleep-related questions,measurements related to diabetes, and BMI were included in this analysis. Subjects were categorized into three sleep groups based on two sleep questions: (a) no sleep problems; (b) sleep disturbance; and (c) sleep disorder. Diabetes was defined as having one of a diagnosis from a physician; an overnight fasting glucose > 125 mg/dL; Glycohemoglobin > 6.4%; or an oral glucose tolerance test > 199mg/dL. Overall, 19% of subjects were diabetics, 37% were obese, and 32% had either sleep disturbance or sleep disorder. Using multiple logistic regression models adjusting for covariates without including BMI, the odds ratios (OR, (95% CI)) of diabetes were 1.40 (1.06, 1.84) and 2.04 (1.40, 2.95) for those with sleep disturbance and with sleep disorder, respectively. When further adjusting for BMI, the ORs were similar for those with sleep disturbance 1.36 (1.06, 1.73) but greatly attenuated for those with sleep disorders (1.38 [0.95, 2.00]). In conclusion, the impact of sleep disorders on diabetes may be explained through the individuals’ obesity status.

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Children with developmental coordination disorder (DCD) are often referred to as clumsy because of their compromised motor coordination. Clumsiness and slow movement performances while scripting in children with DCD often result in poor academic performance and a diminished sense of scholastic competence. This study purported to examine the mediating role of perceived scholastic competence in the relationship between motor coordination and academic performance in children in grade six. Children receive a great deal of comparative information on their academic performances, which influence a student's sense of scholastic competence and self-efficacy. The amount of perceived academic self-efficacy has significant impact on academic performance, their willingness to complete academic tasks, and their self-motivation to improve where necessary. Independent t-tests reveal a significant difference (p < .001) between DCD and non-DCD groups when compared against their overall grade six average with the DCD group performing significantly lower. Independent t-tests found no significant difference between DCD and non-DCD groups for perceived scholastic competence. However, multiple linear regression analysis revealed a significant mediating role of 15% by perceived scholastic competence when examining the relationship between motor coordination and academic performance. While children with probable DCD may not rate their perceived scholastic competence as less than their healthy peers, there is a significant mediating effect on their academic performance.

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Relationships between surface sediment diatom assemblages and lake trophic status were studied in 50 Canadian Precambrian Shield lakes in the Muskoka-Haliburton and southern Ontario regions. The purpose of this study was to develop mathematical regression models to infer lake trophic status from diatom assemblage data. To achieve this goal, however, additional investigations dealing with the evaluation of lake trophic status and the autecological features of key diatom species were carried out. Because a unifying index and classification for lake trophic status was not available, a new multiple index was developed in this study, by the computation of the physical, chemical and biological data from 85 south Ontario lakes. By using the new trophic parameter, the lake trophic level (TL) was determined: TL = 1.37 In[1 +(TP x Chl-a / SD)], where, TP=total phosphorus, Chl-a=chlorophyll-a and SD=Secchi depth. The boundaries between 7 lake trophic categories (Ultra-oligotrophic lakes: 0-0.24; Oligotrophic lakes: 0.241-1.8; Oligomesotrophic lakes: 1.813.0; Mesotrophic lakes: 3.01-4.20; Mesoeutrophic lakes: 4.21-5.4; Eutrophic lakes: 5.41-10 and Hyper-eutrophic lakes: above 10) were established. The new trophic parameter was more convenient for management of water quality, communication to the public and comparison with other lake trophic status indices than many of the previously published indices because the TL index attempts to Increase understanding of the characteristics of lakes and their comprehensive trophic states. It is more reasonable and clear for a unifying determination of true trophic states of lakes. Diatom specIes autecology analysis was central to this thesis. However, the autecological relationship of diatom species and lake trophic status had not previously been well documented. Based on the investigation of the diatom composition and variety of species abundance in 30 study lakes, the distribution optima of diatom species were determined. These determinations were based on a quantitative method called "weighted average" (Charles 1985). On this basis, the diatom species were classified into five trophic categories (oligotrophic, oligomesotrophic, mesotrophic, mesoeutrophic and eutrophic species groups). The resulting diatom trophic status autecological features were used in the regressIon analysis between diatom assemblages and lake trophic status. When the TL trophic level values of the 30 lakes were regressed against their fi ve corresponding diatom trophic groups, the two mathematical equations for expressing the assumed linear relationship between the diatom assemblages composition were determined by (1) uSIng a single regression technique: Trophic level of lake (TL) = 2.643 - 7.575 log (Index D) (r = 0.88 r2 = 0.77 P = 0.0001; n = 30) Where, Index D = (0% + OM% + M%)/(E% + ME% + M%); 4 (2) uSIng a' multiple regressIon technique: TL=4.285-0.076 0%- 0.055 OM% - 0.026 M% + 0.033 ME% + 0.065 E% (r=0.89, r2=0.792, P=O.OOOl, n=30) There was a significant correlation between measured and diatom inferred trophic levels both by single and multiple regressIon methods (P < 0.0001, n=20), when both models were applied to another 20 test lakes. Their correlation coefficients (r2 ) were also statistically significant (r2 >0.68, n=20). As such, the two transfer function models between diatoms and lake trophic status were validated. The two models obtained as noted above were developed using one group of lakes and then tested using an entirely different group of lakes. This study indicated that diatom assemblages are sensitive to lake trophic status. As indicators of lake trophic status, diatoms are especially useful in situations where no local trophic information is available and in studies of the paleotrophic history of lakes. Diatom autecological information was used to develop a theory assessing water quality and lake trophic status.