Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress
Clinical Collections
Advances in Alzheimer’s

At a glance: The STEP trials

A round-up of the STEP phase 3 clinical trials evaluating semaglutide for weight loss in people with overweight or obesity.
ADVANCED SEARCH
Log in
Top
BMC Public Health
Published in: BMC Public Health 1/2018

Open Access 01-12-2018 | Research article

Tailoring lifestyle interventions to low socio-economic populations: a qualitative study

Authors: Nia Coupe, Sarah Cotterill, Sarah Peters

Published in: BMC Public Health | Issue 1/2018

Login to get access

Abstract

Background

People living in deprived areas are more likely to be overweight or obese, have poorer health outcomes, and tend to benefit less from interventions than those from more affluent backgrounds. One approach to address such health inequalities is to tailor existing interventions to low socio-economic populations, yet there is limited evidence to inform their design. This study aims to identify how best to tailor lifestyle interventions to low socio-economic populations to improve outcomes.

Methods

Following direct observations of community-run weight loss groups, we interviewed 11 group facilitators and 14 service users from a health improvement service in a low socio-economic area in the North West of England. Audio-recorded interviews were transcribed verbatim and analysed thematically.

Results

We identified two overarching themes within the data. The first theme, managing diversity, included challenges faced in delivering a generic intervention to a diverse population in terms of knowledge, language and literacy skills, and cultural diversity. The second theme incorporated all issues relating to the environment, such as cost, access and availability of food and leisure facilities, and ‘life gets in the way’.

Conclusions

Tailoring interventions for this population is necessary, and more attention is needed to develop ways to ensure service providers and users engage with behaviour change techniques such as goal setting, rather than focusing on information provision alone. Interventions should also be mindful of cost, cultural diversity, and language and literacy barriers, as well as potential for disengaging this hard to reach population.
Footnotes
1
Rating 1–10, where 1 is in the 10% most deprived areas in England.
 
Literature
1.
2.
Di Angelantonio E, Bhupathiraju SN, Wormser D, Gao P, Kaptoge S, de Gonzalez AB, Cairns BJ, Huxley R, Jackson CL, Joshy G, Lewington S, Manson JE, Murphy N, Patel AV, Samet JM, Woodward M, Zheng W, Zhou M, Bansal N, Barricarte A, Carter B, Cerhan JR, Collins R, Smith GD, Fang X, Franco OH, Green J, Halsey J, Hildebrand JS, Jung KJ, Korda RJ, DF ML, Moore SC, O'Keeffe LM, Paige E, Ramond A, Reeves GK, Rolland B, Sacerdote C, Sattar N, Sofianopoulou E, Stevens J, Thun M, Ueshima H, Yang L, Yun YD, Willeit P, Banks E, Beral V, Chen Z, Gapstur SM, Gunter MJ, Hartge P, Jee SH, Lam T-H, Peto R, Potter JD, Willett WC, Thompson SG, Danesh J, Hu FB. Body-mass index and all-cause mortality: individual-participant-data meta-analysis of 239 prospective studies in four continents. The Lancet. 2016;388(10046):776–86.CrossRef
3.
Drewnowski A, Moudon AV, Jiao J, Aggarwal A, Charreire H, Chaix B. Food environment and socioeconomic status influence obesity rates in Seattle and in Paris. Int J Obes. 2014;38(2):306–14.CrossRef
4.
5.
Miner L, Bolding P, Hilbe J, Goldstein M, Hill T, Nisbet R, Walton N, Miner G. Practical predictive analytics and Decisioning Systems for Medicine: Academic Press; 2014.
6.
7.
8.
Giskes K, Avendaňo M, Brug J, Kunst AE. A systematic review of studies on socioeconomic inequalities in dietary intakes associated with weight gain and overweight/obesity conducted among European adults. Obes Rev. 2010;11(6):413–29.CrossRefPubMed
9.
Stringhini S, Sabia S, Shipley M, Brunner E, Nabi H, Kivimaki M, Singh-Manoux A. Association of socioeconomic position with health behaviors and mortality. JAMA. 2010;303(12):1159–66.CrossRefPubMedPubMedCentral
10.
Pechey R, Jebb SA, Kelly MP, Almiron-Roig E, Conde S, Nakamura R, Shemilt I, Suhrcke M, Marteau TM. Socioeconomic differences in purchases of more vs. less healthy foods and beverages: Analysis of over 25,000 British households in 2010. Soc Sci Med. 2013;92:22–6.CrossRefPubMedPubMedCentral
11.
Wagner Cv, Knight K, Steptoe A, Wardle J. Functional health literacy and health-promoting behaviour in a national sample of British adults. J Epidemiol Community Health. 2007;61(12):1086–90.CrossRef
12.
Kennen EM, Davis TC, Huang J, Yu H, Carden D, Bass R, Arnold C. Tipping the scales: the effect of literacy on obese patients' knowledge and readiness to lose weight. South Med J. 2005;98(1):15–8.CrossRefPubMed
13.
Hiscock R, Judge K, Bauld L. Social inequalities in quitting smoking: what factors mediate the relationship between socioeconomic position and smoking cessation? J Public Health (Oxf). 2011;33(1):39–47.CrossRef
14.
Buck, D. and F. Frosini, Clustering of unhealthy behaviours over time. The King’s Fund, 2012.
15.
Bull ER, Dombrowski SU, McCleary N, Johnston M. Are interventions for low-income groups effective in changing healthy eating, physical activity and smoking behaviours? A systematic review and meta-analysis. BMJ Open. 2014;4(11):e006046.CrossRefPubMedPubMedCentral
16.
Michie S, Jochelson K, Markham WA, Bridle C. Low income groups and behaviour change interventions: a review of intervention content, effectiveness and theoretical frameworks. J Epidemiol Community Health. 2009;63:610–22.CrossRefPubMed
17.
White, M., J. Adams, and P. Heywood, How and why do interventions that increase health overall widen inequalities within populations, in Social inequality and public health, S.J. Babones, Editor. Policy Press Scholarship Online. 2009. p. 65–82.
18.
Ockene IS, Tellez TL, Rosal MC, Reed GW, Mordes J, Merriam PA, Olendzki BC, Handelman G, Nicolosi R, Ma Y. Outcomes of a Latino community-based intervention for the prevention of diabetes: the Lawrence Latino diabetes prevention project. Am J Public Health. 2012;102(2):336–42.CrossRefPubMedPubMedCentral
19.
Tobin K, Kuramoto SJ, German D, Fields E, Spikes PS, Patterson J, Latkin C. Unity in diversity: results of a randomized clinical culturally tailored pilot HIV prevention intervention trial in Baltimore, Maryland, for African American men who have sex with men. Health Educ Behav. 2013;40(3):286–95.CrossRefPubMed
20.
Brown J, Michie S, Geraghty AW, Yardley L, Gardner B, Shahab L, Stapleton JA, West R. Internet-based intervention for smoking cessation (StopAdvisor) in people with low and high socioeconomic status: a randomised controlled trial. Lancet Respir Med. 2014;2(12):997–1006.CrossRefPubMed
21.
Garip G, Yardley L. A synthesis of qualitative research on overweight and obese people's views and experiences of weight management. Clinical Obesity. 2011;1(2–3):110–26.CrossRefPubMed
22.
Davis EM, Clark JM, Carrese JA, Gary TL, Cooper LA. Racial and socioeconomic differences in the weight-loss experiences of obese women. Am J Public Health. 2005;95(9):1539–43.CrossRefPubMedPubMedCentral
23.
Miles R, Panton L. The influence of the perceived quality of community environments on low-income women’s efforts to walk more. J Community Health. 2006;31(5):379–92.CrossRefPubMed
24.
Bukman AJ, Teuscher D, Feskens EJ, van Baak MA, Meershoek A, Renes RJ. Perceptions on healthy eating, physical activity and lifestyle advice: opportunities for adapting lifestyle interventions to individuals with low socioeconomic status. BMC Public Health. 2014;14(1):1036.CrossRefPubMedPubMedCentral
25.
Greener J, Douglas F, van Teijlingen E. More of the same? Conflicting perspectives of obesity causation and intervention amongst overweight people, health professionals and policy makers. Soc Sci Med. 2010;70(7):1042–9.CrossRefPubMed
26.
27.
Braun V, Clarke V. Using thematic analysis in psychology. Qual Res Psychol. 2006;3(2):77–101.CrossRef
28.
Guest G, Bunce A, Johnson L. How many interviews are enough? An experiment with data saturation and variability. Field methods. 2006;18(1):59–82.CrossRef
29.
Albarracín D, Gillette JC, Earl AN, Glasman LR, Durantini MR, Ho M-H. A test of major assumptions about behavior change: a comprehensive look at the effects of passive and active HIV-prevention interventions since the beginning of the epidemic. Psychol Bull. 2005;131(6):856–97.CrossRefPubMedPubMedCentral
30.
Dombrowski SU, Sniehotta FF, Avenell A, Johnston M, MacLennan G, Araújo-Soares V. Identifying active ingredients in complex behavioural interventions for obese adults with obesity-related co-morbidities or additional risk factors for co-morbidities: a systematic review. Health Psychol Rev. 2010;6(1):7–32.CrossRef
31.
Hankonen N, Sutton S, Prevost AT, Simmons RK, Griffin SJ, Kinmonth AL, Hardeman W. Which behavior change techniques are associated with changes in physical activity, diet and body mass index in people with recently diagnosed diabetes? Ann Behav Med. 2015;49(1):7–17.CrossRefPubMed
32.
Dombrowski SU, O'Carroll RE, Williams B. Form of delivery as a key ‘active ingredient' in behaviour change interventions. Br J Health Psychol. 2016;21(4):733–40.CrossRefPubMed
33.
Inglis V, Ball K, Crawford D. Why do women of low socioeconomic status have poorer dietary behaviours than women of higher socioeconomic status? A qualitative exploration. Appetite. 2005;45(3):334–43.CrossRefPubMed
34.
Larson NI, Story MT, Nelson MC. Neighborhood environments: disparities in access to healthy foods in the US. American Journal of Preventive Medicine. 2009;36(1):74–81. e10.CrossRefPubMed
35.
Shaw H. Food access, diet and health in the UK: an empirical study of Birmingham. Br Food J. 2012;114(4):598–616.CrossRef
36.
Burgoine T, Forouhi NG, Griffin SJ, Wareham NJ, Monsivais P. Associations between exposure to takeaway food outlets, takeaway food consumption, and body weight in Cambridgeshire, UK: population based, cross sectional study. BMJ. 2014;348:g1464.CrossRefPubMedPubMedCentral
37.
Escobar MAC, Veerman JL, Tollman SM, Bertram MY, Hofman KJ. Evidence that a tax on sugar sweetened beverages reduces the obesity rate: a meta-analysis. BMC Public Health. 2013;13(1):1072.CrossRef
38.
Briggs AD, Mytton OT, Kehlbacher A, Tiffin R, Rayner M, Scarborough P. Overall and income specific effect on prevalence of overweight and obesity of 20% sugar sweetened drink tax in UK: econometric and comparative risk assessment modelling study. BMJ. 2013;347:f6189.CrossRefPubMedPubMedCentral
39.
Chambers SA, Rowa-Dewar N, Radley A, Dobbie F. A systematic review of grandparents’ influence on grandchildren’s cancer risk factors. PLoS One. 2017;12(11):e0185420.CrossRefPubMedPubMedCentral
40.
Harkins C, Shaw R, Gillies M, Sloan H, MacIntyre K, Scoular A, Morrison C, MacKay F, Cunningham H, Docherty P. Overcoming barriers to engaging socio-economically disadvantaged populations in CHD primary prevention: a qualitative study. BMC Public Health. 2010;10(1):391.CrossRefPubMedPubMedCentral
41.
Horne M, Tierney S. What are the barriers and facilitators to exercise and physical activity uptake and adherence among south Asian older adults: a systematic review of qualitative studies. Prev Med. 2012;55(4):276–84.CrossRefPubMed
42.
Jebb SA, Ahern AL, Olson AD, Aston LM, Holzapfel C, Stoll J, Amann-Gassner U, Simpson AE, Fuller NR, Pearson S. Primary care referral to a commercial provider for weight loss treatment versus standard care: a randomised controlled trial. Lancet. 2011;378(9801):1485–92.CrossRefPubMedPubMedCentral
43.
Ross H, Laws R, Reckless J, Lean M. Evaluation of the counterweight Programme for obesity management in primary care: a starting point for continuous improvement. Br J Gen Pract. 2008;58(553):548–54.CrossRefPubMedCentral
44.
Hunt K, Wyke S, Gray CM, Anderson AS, Brady A, Bunn C, Donnan PT, Fenwick E, Grieve E, Leishman J. A gender-sensitised weight loss and healthy living programme for overweight and obese men delivered by Scottish premier league football clubs (FFIT): a pragmatic randomised controlled trial. Lancet. 2014;383(9924):1211–21.CrossRefPubMedPubMedCentral
45.
Hunt K, Gray CM, Maclean A, Smillie S, Bunn C, Wyke S. Do weight management programmes delivered at professional football clubs attract and engage high risk men? A mixed-methods study. BMC Public Health. 2014;14(1):50.CrossRefPubMedPubMedCentral
Metadata
Title
Tailoring lifestyle interventions to low socio-economic populations: a qualitative study
Authors
Nia Coupe
Sarah Cotterill
Sarah Peters
Publication date
01-12-2018
Publisher
BioMed Central
Published in
BMC Public Health / Issue 1/2018
Electronic ISSN: 1471-2458
DOI
https://doi.org/10.1186/s12889-018-5877-8

Other articles of this Issue 1/2018

BMC Public Health 1/2018 Go to the issue

Research article

Do sex differences in reported weight loss intentions and behaviours persist across demographic characteristics and weight status in youth? A systematic review

Research article

Yarning about fall prevention: community consultation to discuss falls and appropriate approaches to fall prevention with older Aboriginal and Torres Strait Islander people

Research article

Severity and susceptibility: measuring the perceived effectiveness and believability of tobacco health warnings

Research article

An assessment of public health surveillance of Zika virus infection and potentially associated outcomes in Latin America

Research article

Beyond the parish pump: what next for public health?

Study protocol

Longitudinal study of health, disease and access to care in rural Victoria: the Crossroads-II study: methods