Region-level obesity projections and an examination of its correlates in Quebec

Jahagirdar, Deepa; Lo, Ernest

doi:10.17269/cjph.108.5677

Cited by 3 publications

(5 citation statements)

References 30 publications

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“…By design, participants in this cohort had at least one parent with obesity, a strong risk factor for childhood obesity 38 . In Quebec, it is expected that the prevalence of adults with obesity will increase to 23% by 2023 39 . As such, a growing proportion of children will grow up in households including a parent with obesity.…”

Section: Discussionmentioning

confidence: 99%

“…38 In Quebec, it is expected that the prevalence of adults with obesity will increase to 23% by 2023. 39 As such, a growing proportion of children will grow up in households including a parent with obesity. Examining associations between adherence to the 24-hour movement guidelines and adiposity in this unique cohort of children at high risk of obesity highlights a need for early interventions specifically among these high-risk youth.…”

Section: Discussionmentioning

confidence: 99%

“…38 In Quebec, it is expected that the prevalence of adults with obesity will increase to 23% by 2023. 39 As such, a growing proportion of children…”

Section: Discussionmentioning

confidence: 99%

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Adherence to the 24‐hour movement guidelines and adiposity in a cohort of at risk youth: A longitudinal analysis

et al. 2020

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Summary Background The 24‐hour movement guidelines provide recommendations for physical activity, screen time and sleep duration for children. Objectives Describe adherence to the guidelines and their cross‐sectional and longitudinal associations with adiposity from childhood to adolescence. Methods Data are from the QUALITY Cohort. Children were followed at 8 to 10 years (childhood; n = 630), 10 to 12 years (early adolescence; n = 564) and 15 to 17 years (adolescence; n = 377). Physical activity, screen time, and sleep duration were measured by accelerometry and questionnaires. Body mass index z‐scores (zBMI), waist circumference, waist‐to‐height ratio and percent body fat were based on clinical measurements. Multiple linear regressions estimated associations. Results In childhood, early adolescence and adolescence, 14%, 6%, and 0% of participants met the 24‐hour movement guidelines, respectively. Meeting fewer guideline components was cross‐sectionally associated with higher adiposity at each visit. Meeting fewer guideline components in childhood was longitudinally associated with higher adiposity at later visits. For example, those meeting none of the guideline components (vs all) in childhood had a 1.66 SD (95% CI: 0.42, 2.89) higher zBMI in early adolescence. Conclusion Few participants met the guidelines. Not meeting the guidelines in childhood is associated with higher adiposity 2 and 7 years later. Interventions are needed to increase adherence to the 24‐hour movement guidelines across childhood and adolescence.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Adherence to the 24‐hour movement guidelines and adiposity in a cohort of at risk youth: A longitudinal analysis

et al. 2020

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“…In addition to SES indicators and PA, we have collected for other variables associated with obesity: region ( 30 ), age, gender, marital status, smoking, alcohol consumption, adequate fruit and vegetable intake, and high-fat diet ( 18 , 25 ). All variables were collected by trained interviewers through face-to-face interviews.…”

Section: Methodsmentioning

confidence: 99%

Associations of Socioeconomic Status and Physical Activity With Obesity Measures in Rural Chinese Adults

Pan

et al. 2021

Front. Public Health

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Background: Although independent association of socioeconomic status (SES) or physical activity (PA) with obesity has been well-documented in urban settings, their independent and joint associations on obesity measures are limited in rural regions.Methods: Almost 38,000 (n = 37,922) individuals were included from the Henan Rural Cohort Study. The International Physical Activity Questionnaire (IPAQ) was used to evaluate PA. Obesity was reflected by body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), body fat percentage (BFP), and visceral fat index (VFI). The independent and interactive effects of SES and PA on obesity were analyzed by logistic regression models and generalized linear regression models, respectively.Results: Compared with high education level, the OR (95%CI) of obesity defined by BMI with low education level was 1.466 (1.337, 1.608), 1.064 (0.924, 1.225), and 1.853 (1.625, 2.114) in total population, men and women, respectively. Besides, the OR (95%CI) of obesity defined by BMI associated with per capita monthly income were 1.089 (1.015, 1.170), 1.192 (1.055, 1.347), 1.038 (0.951, 1.133) in total population, men and women, respectively. Similar results had been observed in other obesity measures. Negative interactive association of low education level and PA on obesity measures were observed only in women (all P < 0.05).Conclusions: This study suggests that women are more susceptible to obesity concerning low SES and that adequate PA may be a potential target for mitigating the negative effect of low SES on obesity in women.Clinical Trial Registration: The Henan Rural Cohort Study has been registered at Chinese Clinical Trial Register (Registration number: ChiCTR-OOC-15006699) http://www.chictr.org.cn/showproj.aspx?proj=11375.

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“…Factors beyond genetics play a central role in the likelihood of an individual becoming obese. Such factors include those primarily related to lifestyle (e.g., diet and physical activity) and social networks (e.g., media and peer pressure) [6][7][8][9], as well as other geographic considerations (e.g., urban areas vs. rural areas and accessibility) and the role of the built environment [10][11][12][13][14]. An enormous body of literature exists that examines the factors associated with obesity and potential approaches to mitigate the issue (e.g., [15,16]).…”

Section: Introductionmentioning

confidence: 99%

Targeting the spatial context of obesity determinants via multiscale geographically weighted regression

2020

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Background: Obesity rates are recognized to be at epidemic levels throughout much of the world, posing significant threats to both the health and financial security of many nations. The causes of obesity can vary but are often complex and multifactorial, and while many contributing factors can be targeted for intervention, an understanding of where these interventions are needed is necessary in order to implement effective policy. This has prompted an interest in incorporating spatial context into the analysis and modeling of obesity determinants, especially through the use of geographically weighted regression (GWR). Method: This paper provides a critical review of previous GWR models of obesogenic processes and then presents a novel application of multiscale (M)GWR using the Phoenix metropolitan area as a case study. Results: Though the MGWR model consumes more degrees of freedom than OLS, it consumes far fewer degrees of freedom than GWR, ultimately resulting in a more nuanced analysis that can incorporate spatial context but does not force every relationship to become local a priori. In addition, MGWR yields a lower AIC and AICc value than GWR and is also less prone to issues of multicollinearity. Consequently, MGWR is able to improve our understanding of the factors that influence obesity rates by providing determinant-specific spatial contexts. Conclusion: The results show that a mix of global and local processes are able to best model obesity rates and that MGWR provides a richer yet more parsimonious quantitative representation of obesity rate determinants compared to both GWR and ordinary least squares.

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Region-level obesity projections and an examination of its correlates in Quebec

Cited by 3 publications

References 30 publications

Adherence to the 24‐hour movement guidelines and adiposity in a cohort of at risk youth: A longitudinal analysis

Adherence to the 24‐hour movement guidelines and adiposity in a cohort of at risk youth: A longitudinal analysis

Associations of Socioeconomic Status and Physical Activity With Obesity Measures in Rural Chinese Adults

Targeting the spatial context of obesity determinants via multiscale geographically weighted regression

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