Edache, Iyoma Yvonne (2019) Weight Bias and Support of Public Health Policies. Masters thesis, Concordia University.
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Abstract
Background. Public explicit weight bias attitudes have yet to be assessed in a Canadian representative sample. It is unknown if explicit weight bias negatively influences Canadian public perceptions of public health policies aimed at addressing obesity.
Objectives. To examine: (1) explicit weight bias, (2) public support of the Canadian Federal Government’s public health policy recommendations to address obesity, and (3) the association between explicit weight bias and policy support in Canada.
Methods. Canadian adults (N=1003; 51% female; BMI=27.37.0 kg/m2) completed an online survey in October 2018. Weight bias was measured with the Anti-Fat Attitudes Questionnaire in three subscales: Willpower, Fear of fat, and Dislike. Support of policy recommendations was measured on 4-point Likert scales. Logistic regressions (support vs oppose) were conducted after adjusting for age, race, gender and income.
Results. Support of policy recommendations ranged from 53% to 90%. Willpower was associated with support of 10 policies (e.g. changing infrastructure to encourage physical activity, OR=1.28, CI=1.14-1.43, P<0.01). Dislike was associated with support of three policies (e.g. taxation of sugar and artificially sweetened beverages, OR=1.19, CI=1.08-1.31, P<0.01). However, Fear of fat was negatively associated with support of two policies (e.g. mandating the use of front-of-package nutrition labelling, OR=0.82, CI=0.73-0.94, P<0.01)
Conclusions. Weight bias is associated with Canadian support of public health policies aimed at addressing obesity. Future studies should examine the influence of weight bias reduction interventions on policy support.
Divisions: | Concordia University > Faculty of Arts and Science > Health, Kinesiology and Applied Physiology |
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Item Type: | Thesis (Masters) |
Authors: | Edache, Iyoma Yvonne |
Institution: | Concordia University |
Degree Name: | M. Sc. |
Program: | Exercise Science |
Date: | 5 August 2019 |
Thesis Supervisor(s): | Alberga, Angela S |
ID Code: | 985644 |
Deposited By: | Iyoma Yvonne Edache |
Deposited On: | 05 Feb 2020 02:32 |
Last Modified: | 05 Feb 2020 02:32 |
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