Literature DB >> 24504360

Using population segmentation to inform local obesity strategy in England.

Jane Wills1, Nicola Crichton2, Ava Lorenc2, Muireann Kelly2.   

Abstract

Little is known about the views of obese people and how best to meet their needs. Amongst London boroughs Barking and Dagenham has the highest prevalence of adult obesity at 28.7%; the lowest level of healthy eating and of physical activity; and is the 22nd most deprived area of England. The study aimed to gain insight into the attitudes, motivations and priorities of people who are obese or overweight to inform the social marketing of an obesity strategy. Two hundred and ten obese or overweight adults were recruited through visual identification in public thoroughfares to attempt to recruit those seldom seen in primary care. One hundred and eighty-one street-intercept and 52 in-depth interviews were conducted. Thematic analysis was followed by psychographic segmentation. Eleven population segments were identified based on their readiness to change, the value accorded to tackling obesity, identified enabling factors and barriers to weight management and perceived self-efficacy. This population showed considerable variation in its readiness to change and perceived control over obesity but considerable similarity in the exchange value they attributed to tackling their obesity. Even within a relatively homogenous socio-demographic community, there needs to be a range of interventions and messages tailored for different population segments that vary in their readiness to change and confidence about tackling obesity. The dominant emphasis of policy and practice on the health consequences of obesity does not reflect the priorities of this obese population for whom the exchange value of addressing obesity was daily functioning especially in relation to family life.
© The Author (2014). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Entities:  

Keywords:  adult obesity; behaviour; segmentation; social marketing

Mesh:

Year:  2014        PMID: 24504360     DOI: 10.1093/heapro/dau004

Source DB:  PubMed          Journal:  Health Promot Int        ISSN: 0957-4824            Impact factor:   2.483


  5 in total

1.  Population segments as a tool for health care performance reporting: an exploratory study in the Canadian province of British Columbia.

Authors:  Julia M Langton; Sabrina T Wong; Fred Burge; Alexandra Choi; Niloufar Ghaseminejad-Tafreshi; Sharon Johnston; Alan Katz; Ruth Lavergne; Dawn Mooney; Sandra Peterson; Kimberlyn McGrail
Journal:  BMC Fam Pract       Date:  2020-05-31       Impact factor: 2.497

2.  Psychographic segmentation to identify higher-risk teen peer crowds for health communications: Validation of Virginia's Mindset Lens Survey.

Authors:  Carolyn A Stalgaitis; Jeffrey W Jordan; Mayo Djakaria; Daniel J Saggese; Hannah Robbins Bruce
Journal:  Front Public Health       Date:  2022-07-22

3.  Psychographic Profiling for Effective Health Behavior Change Interventions.

Authors:  Sarah J Hardcastle; Martin S Hagger
Journal:  Front Psychol       Date:  2016-01-06

Review 4.  Opportunities for intervention strategies for weight management: global actions on fluid intake patterns.

Authors:  Max Lafontan; Tommy L S Visscher; Nathalie Farpour-Lambert; Volkan Yumuk
Journal:  Obes Facts       Date:  2015-01-29       Impact factor: 3.942

5.  A method for assessing links between objectively measured food store scores and store & neighborhood favorability.

Authors:  Richard C Sadler; Ashley N Sanders-Jackson; Josh Introne; Robyn Adams
Journal:  Int J Health Geogr       Date:  2019-12-27       Impact factor: 3.918

  5 in total

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