Development and evaluation of a community-based approach to promote health-related
behaviour among older adults in a socioeconomically disadvantaged community
Luten, Karla
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Development and evaluation of a community-based approach
to promote health-related behaviour among older adults
in a socioeconomically disadvantaged community
Colofon
This study was conducted within the Research Institute SHARE of the Graduate School of Medical Sciences, University Medical Center Groningen, University of Groningen and under auspices of the research program Public Health Research (PHR). The study was funded by the Netherlands Organisation for Health Research and Development (ZonMw). The printing of this thesis was financially supported by the Graduate School of Medical Sciences, Research Institute SHARE, University Medical Center Groningen, and the University of Groningen.
Printed by: Gildeprint - Enschede Cover image: iStockphoto.com
Cover lay-out: Maaike Disco - Groningen ISBN: 978-90-367-9511-1 © 2017 Karlien Luten, the Netherlands
All rights reserved. No part of this thesis may be reproduced or transmitted, in any form or by any means, without permission of the author.
Development and evaluation of
a community-based approach to promote
health-related behaviour among older adults
in a socioeconomically disadvantaged community
Proefschrift
ter verkrijging van de graad van doctor aan de Rijksuniversiteit Groningen
op gezag van de
rector magnificus prof. dr. E. Sterken en volgens besluit van het College voor Promoties.
De openbare verdediging zal plaatsvinden op maandag 27 februari 2017 om 11:00 uur
door
Karla Alien Luten
geboren op 9 februari 1982 te Meppel
Promotores
Prof. dr. A. Dijkstra Prof. dr. S.A. Reijneveld
Copromotor
Dr. A.F. de Winter
Beoordelingscommissie
Prof. dr. H.W. van den Borne Prof. dr. A.J. Schuit
Paranimfen
Aafke Hoekstra Erika Boers
Contents
Chapter 1 General introduction 9
Chapter 2 Correlates of physical activity among older adults in a
socioeconomically disadvantaged rural area in the Netherlands
19
Chapter 3 Developing a community-based intervention on physical activity and healthy eating of older adults in a socioeconomically disadvantaged community: an Intervention Mapping approach
35
Chapter 4 Reach and effectiveness of a community-based intervention on physical activity and healthy eating of older adults in a
socioeconomically disadvantaged community
55
Chapter 5 Moderators of physical activity and healthy eating in a community-based intervention for older adults
71
Chapter 6 Combining interventions in home healthcare and community settings: effects on health-related behaviours of older adults
87
Chapter 7 General discussion 101
Summary 119
Samenvatting 125
Dankwoord 131
Curriculum Vitae 135
1
Physical activity and healthy eating are health-related behaviours, contributing to overall health and quality of life.1,2 However, although the benefits of these behaviours have been
proven, it has been found that older adults and especially those with lower socioeconomic status (SES) are prone to unfavourable health-related behaviour.3,4 This thesis describes the
development and evaluation of a community-based approach to promote health-related behaviour among older adults in a socioeconomically disadvantaged community. This introductory chapter provides background information on the key concepts and context of the thesis, and presents the research objectives and an outline of the further contents.
Health and health-related behaviour in older adults
Chronic diseases, like cardiovascular diseases, type 2 diabetes, and cancer, are now by far the leading causes of death, and their impact is steadily growing.5 Half of Dutch elderly
people who live independently suffer from one or more chronic diseases6 which might
result in disabilities and reduce quality of life.7 While the proportion of older adults
continues to grow, their average life expectancy also increases. As a result, the incidence of health problems and related demands for care, as well as the complexity of individual health problems, are expected to increase.8
Health-related behaviours, such as sufficient physical activity and healthy diet, can help to improve health in older people, thereby promoting the maintenance of physical and social independence, active participation in social life, life expectancy, quality of life, and ultimately reduction of socioeconomic health differences.1,5,7 However, currently a large
proportion of older adults have unhealthy diets as well as low levels of physical activity;9-11
moreover, levels of physical activity continue to decline with increasing age.4 To illustrate,
over 40% of the older people studied did not meet the guidelines for sufficient levels of physical activity,6 more than 70% did not meet the guidelines for fruit consumption, and
nearly 50% did not meet the guidelines for vegetable consumption.9 These figures are even
more unfavourable among those with lower SES,3,12,13 which is one explanation for
socioeconomic health differences.
Socioeconomic health differences
Socioeconomic health differences are systematic differences in health and mortality between people with a high and with a low SES.14 SES is usually measured by education,
occupation, employment, income and/ or wealth.15 In health research, educational level is
the most commonly used indicator of SES.16 Significant socioeconomic health differences
are observed, for example, in life expectancy, healthy life expectancy, and health problems.17 In the Netherlands, low-educated people live about seven years shorter than
high-educated people, and the difference in healthy life expectancy can be as high as fourteen years.18 In addition, considerable differences in the prevalence of risk factors are
G e n e r a l i n t r o d u c t i o n | 11
people running greater risks.17-18 Poor health can also put a person in a more unfavourable
social position and therefore contribute to further socioeconomic health differences.18-19
A socioeconomically disadvantaged region: Eastern Groningen
Socioeconomic health differences are often found more intensely in regions with a declining population. This can be explained in at least two ways. First, people who live in regions with a declining population are generally less healthy than residents of other areas, partly due to the less favourable socioeconomic conditions in these regions.19-21 The resulting relatively
higher proportion of people with a lower SES in these regions leads to more unhealthy lifestyles, in particular lower levels of physical activity and less healthy diet, that may contribute to health concerns.22-23 Second, as younger, healthier people migrate to more
urban areas, the proportion of older and less healthy adults increases in non-urban regions with a declining population.20-21
In the Netherlands, attention to socioeconomic health differences has largely focused on socioeconomically disadvantaged neighbourhoods in medium- and large-sized cities. Only recently is attention directed at the more rural areas and borders of the country. One of these rural areas with a declining population in the Netherlands is Eastern Groningen, characterised by an ageing population, a high percentage of people with low SES and a relatively high prevalence of health problems compared to other regions in the Netherlands.20-21 More than 40% of the population in this region is aged 50 or over,
compared to 35% in the wider Dutch population.24 Groningen is one of the Dutch regions
with the highest mortality due to cardiovascular diseases and cancer.25 With respect to SES,
more than 55% of people in Eastern Groningen achieved only low or medium-low educational levels, compared to nearly 40% nationwide.26 Thus, when it comes to investing
in the reduction of socioeconomic health differences, the population of Eastern Groningen is an obvious target. One rational way to approach health problems in a socioeconomically disadvantaged region is to focus more on their prevention through interventions and policies to decrease major risk factors.18
Prevention: a community-based approach
Preventive interventions can help older adults to improve their health-related behaviours, for example, levels of physical activity and healthy eating, to prevent chronic diseases like cardiovascular diseases, type 2 diabetes, and some types of cancer.11,27 Overall health can
thereby be expected to improve, thus positively influencing life expectancy. In addition, preventive interventions can result in longer participation in social activities, maintenance of physical and social independence, and improvement in quality of life in an ageing population.1,11
To change people’s health-related behaviour a broad range of intervention components is needed. These components are aimed at creating a supportive environment for the individual and can be offered through a community-based approach.28,29 Common
components of community-based approaches include: a tailored multi-component approach, intersectoral cooperation, participation of the community, and changes in the social and physical environment.28-30 Community-based approaches are a feasible and
cost-effective way to achieve relatively large health gains, because they reach substantial numbers of people by means of limited resources.31 Such an approach would seem
particularly appropriate for disadvantaged groups with specific needs and barriers,22,29 like
older adults in a socioeconomically disadvantaged community. This group is therefore an important target population for community-based preventive interventions.6
Care for older adults
In recent years, due to changes in needs and social structures, a different approach to health is required since a disease-oriented approach alone is no longer appropriate.32
Industrialized societies are in a transition stage from disease and care to health and behaviour.33 Care is not only about treating but also about preventing diseases and
promoting health-related behaviour in order to improve health, independent living, active participation in social life, and quality of life during old age. Moreover, this policy has been introduced to relieve the expected pressure on the healthcare system.8
Various sectors and professionals are involved in the care of older adults. One sector is home healthcare, whereby care is provided at home by professionals whose main focus is care for older adults and their problems. Home healthcare is a sustainable alternative to unnecessary acute or long-term institutionalisation and makes it possible for individuals to remain in their home and community as long as possible.32 Because they
frequently visit vulnerable older adults in their own environment and have gained their trust, professionals in home healthcare are in a good position to influence health-related behaviours.34 Therefore, home healthcare professionals can be appropriate intermediaries
to enhance the health-related behaviours of their clients. Ideally, vulnerable older adults as yet without home healthcare could also become the focus of a community team and a nearby home healthcare organisation.
Combining interventions in the general community with interventions in the home healthcare setting could have the added value of targeting different levels, using a wider range of strategies. In addition, this combination may better reach target populations like vulnerable older adults. To promote long-term changes in health-related behaviours, combined interventions at multiple levels may be necessary.35
G e n e r a l i n t r o d u c t i o n | 13
Academic Collaborative Centre for Home Healthcare
Academic collaborative centres aim to improve cooperation between research, education, practice, and policy so as to increase the quality of life of citizens; they do this by collecting new knowledge and evidence and translating this to daily practice. In such collaboration the focus is on generating practice-based evidence and evidence-based practice related to home healthcare-related issues. The new evidence should contribute to more effective practices and policies.
The Netherlands Organisation for Health Research and Development (ZonMw), initiated the research program ‘PreventieKracht dicht bij Huis’ (2009-2012). As part of this research program, the Academic Collaborative Centre for Home Healthcare (AWT) Eastern Groningen was established, a collaboration between the University Medical Centre Groningen, the Hanze University of Applied Sciences Groningen, the University of Groningen, and Zorggroep Meander. The AWT Eastern Groningen focuses on preventing dependency and decreased quality of life due to health problems and disabilities in older adults. However, evidence-based practice of such prevention in home healthcare is limited and practical knowledge is badly needed. The knowledge obtained in the AWT will contribute to evidence-based home healthcare aimed at improving health-related behaviours in older adults, enabling them to maintain independent living, social participation, and quality of life.
Objectives of this thesis
The overall aim of this thesis is to report on the development and evaluation of a community-based approach to promote health-related behaviours among older adults in a socioeconomically disadvantaged area in the Netherlands. This aim has been translated into six research objectives, divided into two main themes:
1. Development of a community-based approach:
- To identify sociodemographic, health-related, cultural, and psychological correlates of physical activity among older adults;
- To assess whether correlates of physical activity differ by SES;
- To describe the development of a community-based intervention aimed at promoting physical activity and healthy eating among older adults.
2. Evaluation of a community-based approach:
- To assess the reach and effectiveness of a community-based intervention on physical activity and healthy eating among older adults;
- To evaluate whether the effects of such an intervention vary by sociodemographic, psychosocial, and health-related variables;
- To assess the effects of combining a home healthcare intervention and a
community-based intervention on health-related behaviours of independent-living older adults receiving home healthcare.
Outline of the thesis
The outline of the thesis is based on the sequential steps of the Intervention Mapping protocol based on evidence- and practice-based input.36 Chapter 2 describes the results of
the quantitative cross-sectional study as input for the needs assessment. Six-hundred older adults were invited to participate in this study, 244 (40.6%) of whom participated. This study focused specifically on the correlates of physical activity. Chapter 3 provides an overview of the development of a community-based intervention using the procedure of Intervention Mapping. Chapter 4 presents the reach as well as the short- and medium-term effects of the community-based intervention on physical activity and healthy eating. The pre- and post-test quasi-experimental study design included a baseline and two follow-up measurements. In total, 1500 older adults were invited to participate, 643 (42.9%) of whom participated at baseline: 430 in the intervention condition and 213 in the control condition. Retention at up was 88.5% for the first up and 87.7% for the second follow-up. Chapter 5 describes the potential moderators of physical activity and healthy eating in the community-based intervention. In this study we used the data from the baseline and the second follow-up measurement of the effectiveness study. We tested sociodemographic, psychosocial, and health-related variables at baseline as potential moderators of the effects of the conditions. Chapter 6 reports the effects of a combined home healthcare and community-based intervention on physical activity and healthy eating of home healthcare clients. In total, we approached 699 clients, of whom 304 (44%) provided short-term data, and 196 (28%) provided medium-term data. We used a 3-arm pre- and post-test quasi-experimental study design with a combined intervention (baseline n=98), a single home healthcare intervention (baseline n=111), and a control group (baseline n=95). Participant retention rates in the conditions ranged from 55% to 79%. The last chapter, Chapter 7, summarises and discusses the main results and proposes implications for practice and policy, future research, and the AWT.
G e n e r a l i n t r o d u c t i o n | 15
References
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2. Nelson ME, Rejeski WJ, Blair SN, Duncan PW, Judge JO, King AC, Macera CA, Castaneda-Sceppa C. Physical activity and public health in older adults: recommendation from the American college of sports medicine and the American heart association. Circulation. 2007; 116: 1094-1105.
3. Everson-Hock ES, Johnson M, Jones R, Woods HB, Goyder E, Payne N, Chilcott J. Community-based dietary and physical activity interventions in low socioeconomic groups in the UK: A mixed methods systematic review. Prev Med. 2013; 56: 265-272.
4. Koeneman MA, Verheijden MW, Chinapaw MJM, Hopman-Rock M. Determinants of physical activity and exercise in healthy older adults: A systematic review. Int J Behav Nutr Phys Act. 2011; 8: 142-156.
5. World Health Organization. Global status report on noncommunicable diseases 2014. Geneva: World Health Organization, 2014.
6. Zantinge EM, van der Wilk EA, van Wieren S, Schoemaker CG. Gezond ouder worden in Nederland. Bilthoven: Rijksinstituut voor Volksgezondheid en Milieu (RIVM), 2011.
7. Sun F, Norman IJ, While AE. Physical activity in older people: a systematic review. BMC Public Health. 2013; 13: 449-465.
8. Van den Berg M, Post NAM, Hamberg-van Reenen HH, Baan CA, Schoemaker CG. Preventie in de zorg. Themarapport Volksgezondheid Toekomst Verkenningen 2014. Bilthoven: Rijksinstituut voor Volksgezondheid en Milieu (RIVM), 2013.
9. Ocké MC, Buurma-Rethans EJM, de Boer EJ, Wilson-van den Hooven C, Etemad-Ghameslou Z, Drijvers JJMM, van Rossum CTM. Diet of community-dwelling older adults: Dutch National Food Consumption Survey Older Adults 2010-2012. Bilthoven: Rijksinstituut voor Volksgezondheid en Milieu (RIVM), 2013.
10. Ooijendonk WTM, Hildebrandt VH, Hopman-Rock M. Bewegen in Nederland 2000-2005. In: Hildebrandt VH, Ooijendonk WTM, Hopman-Rock M. (Red.). Trendrapport Bewegen en Gezondheid 2004/2005. Hoofddorp/Leiden: TNO, 2007.
11. Van den Berg Jeths A, Timmermans JM, Hoeymans N, Woittiez IB. Ouderen nu en in de toekomst. Gezondheid, verpleging en verzorging 2000-2020. Bilthoven: Rijksinstituut voor Volksgezondheid en Milieu (RIVM), 2004.
12. Van Rossum CTM, Fransen HP, Verkaik-Kloosterman J, Rethans-Buurma EJM, Ocke MC. Dutch National Food Consumption Survey 2007-2010: Diet of children and adults aged 7 to 69 years. Bilthoven: Rijksinstituut voor Volksgezondheid en Milieu (RIVM), 2011.
13. Giskes K, Turrell G, van Lenthe FJ, Brug J, Mackenbach JP. A multilevel study of socio-economic inequalities in food choice behaviour and dietary intake among the Dutch population: the GLOBE study. Public Health Nutr. 2006; 9(1): 75-83.
14. Verweij A. Wat zijn sociaaleconomische gezondheidsverschillen? In: Volksgezondheid Toekomst Verkenning, Nationaal Kompas Volksgezondheid. Bilthoven: Rijksinstituut voor Volksgezondheid en Milieu (RIVM). http://www.nationaalkompas.nl. Accessed May 18, 2015.
15. Pampel FC, Krueger PM, Denney JT. Socioeconomic Disparities in Health Behaviors. Annu Rev Sociol. 2010; 36: 349-370.
16. Verweij A, van der Lucht F. Wat is sociaaleconomische status? In: Volksgezondheid Toekomst Verkenning, Nationaal Kompas Volksgezondheid. Bilthoven: Rijksinstituut voor Volksgezondheid en Milieu (RIVM). http://www.nationaalkompas.nl. Accessed May 18, 2015.
17. Verweij A, van der Lucht F. Wat is de omvang van sociaaleconomische gezondheidsverschillen? In: Volksgezondheid Toekomst Verkenning, Nationaal Kompas Volksgezondheid. Bilthoven: Rijksinstituut voor Volksgezondheid en Milieu (RIVM). http://www.nationaalkompas.nl. Accessed May 18, 2015.
18. Van der Lucht F, Polder JJ. Van gezond naar beter. Kernrapport van de Volksgezondheid Toekomst Verkenning 2010. Bilthoven: Rijksinstituut voor Volksgezondheid en Milieu (RIVM), 2010.
19. Busch MCM, van der Lucht F. Effecten van preventieve interventies: zijn er verschillen tussen mensen met een lage en een hoge sociaaleconomische status. Bilthoven: Rijksinstituut voor Volksgezondheid en Milieu (RIVM), 2012.
20. Verweij A, van der Lucht F. Gezondheid in krimpregio’s. Verdiepingsstudie. Bilthoven: Rijksinstituut voor Volksgezondheid en Milieu (RIVM), 2014.
21. Verweij A, van der Lucht F. Gezondheid in krimpregio’s. Bilthoven: Rijksinstituut voor Volksgezondheid en Milieu (RIVM), 2011.
22. Cleland V, Granados A, Crawford D, Winzenberg T, Ball K. Effectiveness of interventions to promote physical activity among socioeconomically disadvantaged women: a systematic review and meta-analysis. Obes Rev. 2012; 14(3): 197-212.
23. Van Hooijdonk C, Droomers M, van Loon JAM, van der Lucht F, Kunst AE. Exceptions to the rule: Healthy deprived areas and unhealthy wealthy areas. Soc Sci Med. 2007; 64: 1326-1342.
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24. Broer J, Kuiper J, Spijkers W. Gezondheidsprofiel Groningen 2010. Groningen: GGD Groningen, 2011.
25. CBS Doodsoorzakenstatistiek. http://www.volksgezondheidenzorg.info. Accessed June 6, 2016. 26. Broer J, Kuiper J, Spijkers W. Gezondheidsprofiel Groningen 2006. Groningen: GGD Groningen,
2006.
27. Van den Berg M, Schoemaker CG. Effecten van preventie. Deelrapport van de VTV 2010: Van gezond naar beter. Bilthoven: Rijksinstituut voor Volksgezondheid en Milieu (RIVM), 2010. 28. Mummery WK, Brown WJ. Whole of community physical activity interventions: easier said than
done. Br J Sports Med. 2009; 43(1): 39-43.
29. Jansen J, Schuit AJ, van der Lucht F. Tijd voor gezond gedrag. Bevordering van gezond gedrag bij specifieke groepen. Bilthoven: Rijksinstituut voor Volksgezondheid en Milieu (RIVM), 2002. 30. World Health Organization. Interventions on diet and physical activity: what works: summary
report. Geneva: World Health Organization, 2009.
31. Garrett S, Elley CR, Rose SB, O’Dea D, Lawton BA, Dowell AC. Are physical activity interventions in primary care and the community cost-effective? A systematic review of the evidence. Br J Gen Pract. 2011; 61(584): e125-133.
32. Tarricone R, Tsouros A. Home care in Europe. the solid facts. Copenhagen: WHO Regional Office for Europe, 2008.
33. RVZ. Zorg voor je gezondheid! Gedrag en gezondheid: de nieuwe ordening. Den Haag: Raad voor de Volksgezondheid & Zorg, 2010.
34. ZonMw/Actiz. Preventie door de thuiszorg. Analyse van ontwikkelingen en kansen. Den Haag/Utrecht: ZonMw/Actiz, 2011.
35. Taylor AH, Cable NT, Faulkner G, Millsdon M, Narici M, van der Bij AK. Physical activity and older adults: a review of health benefits and the effectiveness of interventions. J Sport Sci. 2004; 22(8): 703-725.
36. Bartholomew LK, Parcel GS, Kok G, Gottlieb NH, Fernández ME. Planning Health Promotion Programs: An Intervention Mapping Approach. 3rd edition. San Francisco, CA: Jossey-Bass, 2011.
2
Correlates of physical activity
among older adults
in a socioeconomically disadvantaged
rural area in the Netherlands
Karla A. Luten Andrea F. de Winter Arie Dijkstra Sijmen A. Reijneveld
Abstract
Objective: To identify sociodemographic, health-related, cultural, and psychological
correlates of physical activity (total and per type of physical activity) in older adults in a socioeconomically disadvantaged rural area, and to assess whether their socioeconomic status (SES) affected the correlates of physical activity.
Methods: We conducted a cross-sectional study among 244 adults. Physical activity, total
and transport-related, household-related, and leisure-time, was measured with the Short QUestionnaire to ASsess Health-enhancing physical activity (SQUASH).
Results: We found significant correlates from different clusters of variables per type of
physical activity. Having a partner and higher self-efficacy were related to more total physical activity. Younger age, better physical fitness, and being less happy to be a person from this region were associated with more transport-related physical activity. Being female, having no (paid) work, less physical fitness, and feeling less connected to the region were related to more household-related physical activity. Being male, having a partner, better physical fitness, better overall health, being born and having lived in the region, being happy to be a person from this region, and feeling connected to the region were associated with more leisure-time physical activity. Associations between low and higher older SES adults hardly differed.
Conclusions: Our findings imply that in general strategies to improve physical activity are
C o r r e l a t e s o f p h y s i c a l a c t i v i t y | 21
Introduction
It is well known that regular physical activity can reduce the risks of health problems like cardiovascular diseases, type 2 diabetes, and obesity.1-3 However, despite these beneficial
effects of physical activity on general health, less than half of the adult population engages in sufficient physical activity.2,4 The prevalence of physical inactivity is especially high among
older people,4,5 people with a low socioeconomic status (SES),6-8 and those living in rural
areas.7 Thus older adults with a low SES living in a rural area represent a major risk group
for problems resulting from physical inactivity.
For targeted public health prevention, insight into the correlates of physical activity is needed to effectively promote an active lifestyle.9 The number of older adults is growing
and physical activity is essential for them to maintain physical independence and preserve health as they age.10 Correlates of physical activity have been investigated among various
populations in socioeconomically disadvantaged parts of cities. For people from socioeconomically disadvantaged rural areas few data are available, but rural populations seem to show lower levels of physical activity when compared to urban populations.11 That
implies that correlates of physical activity for older adults in socioeconomically disadvantaged rural areas are likely to differ from those from urban areas, due for example to differences in physical or social environment.12 Correlates of physical activity have indeed
been shown to differ between geographical areas,7 although results among (older) women
were mixed.11,12 A lower physical activity is in particular likely when people are socially and
culturally embedded in a socioeconomically disadvantaged rural area in which structural neighbourhood factors influence activity behaviour negatively. This may for instance regard a lack of care and physical activity facilities, and the interacting social and cultural norms against physical activity.13 Correlates of physical activity can also vary among socioeconomic
subgroups as a result of differences in financial circumstances and perceived health.14
However, so far hardly any study has specifically assessed correlates of physical activity among older adults living in a socioeconomically disadvantaged rural area.
We need insight into the correlates of physical activity among these older adults in order to develop effective, segmented, and tailored strategies to increase their physical activity.15 We have therefore chosen for our research the I-Change model, which integrates
concepts of various cognitive models including the Theory of Reasoned Action,16 Bandura’s
Social Learning Theory,17 the Transtheoretical Model,18 the Health Belief Model19 and the
Precaution Adoption Model.20 The I-Change model provides a useful framework for
understanding behaviours like physical activity.21 It distinguishes between different types
and levels of correlates of health-related behaviours, such as predisposing, preceding, and motivation factors. In the present study we focus concretely on sociodemographic, health-related, cultural, and psychological variables in relation to physical activity.
The first aim of this paper is to identify and describe sociodemographic, health-related, cultural, and psychological correlates of physical activity among older adults in a socioeconomically disadvantaged rural area in the Netherlands. While most studies focus only on total physical activity or leisure-time physical activity, our study distinguishes two additional types: transport-related physical activity and household-related physical activity to provide a broader perspective on physical activity.22 The second aim of this paper is to
assess whether correlates of physical activity in older adults vary between low and higher SES people in a socioeconomically disadvantaged community. Our study sample was recruited from Eastern Groningen, a rural area in the northeastern part of the Netherlands, and one with relatively high percentages of unemployment and social problems (e.g., poverty). This area also has a high percentage of older adults as well as people with low SES, and the reported prevalence of health problems among inhabitants of this area is greater than in other areas in the Netherlands.23
Methods
Procedure and recruitment
We conducted a cross-sectional study among adults aged 55 years and older living in the municipality of Vlagtwedde in Eastern Groningen, in 2010. Six-hundred inhabitants were randomly selected from population registers of the municipality and invited for the study by letter; the letter explained the purpose, content and procedure of the study and offered participants the chance to win a prize (vouchers worth twenty and fifty euros). They received a postal questionnaire; this was returned by a total of 244 respondents (40.6%). The response to the reminder was about 6%. Participants gave consent to participate in the study by completing and returning the questionnaire. After two weeks, non-responders received a reminder by post. From these participants (the total sample) we obtained data on physical activity, sociodemographic, health-related, and cultural variables, using a self-report questionnaire. In addition, half of the sample (the subsample; n=135) answered a supplement to the questionnaire dealing with psychological variables related to physical activity. After evaluating our study protocol the Medical Ethical Committee of the University Medical Centre Groningen found it unnecessary to file it for ethical approval.
Measures
Sociodemographic variables
We assessed sociodemographic variables as gender, age, marital status, employment status, and SES. For marital status we distinguished ‘married’(1), ‘cohabiting’(2), ‘divorced’(3), ‘single’(4), and ‘widowed’(5). We recoded these categories into ‘having a partner’(1-2), and ‘single’(3-5). For employment status the answering options were ‘paid work, 32 hours or more’(1), ‘paid work, between 20 and 32 hours’(2), ‘paid work, between
C o r r e l a t e s o f p h y s i c a l a c t i v i t y | 23
12 and 20 hours’(3), ‘paid work, less than 12 hours’(4), ‘(early) retired’(5), ‘unemployed/ looking for a job’(6), ‘disabled’(7), ‘social welfare’(8), ‘housekeeping’(9), ‘study’(10). We dichotomised employment status into ‘paid work’(1-4) and ‘no (paid) work’(5-10). We assessed SES according to educational level using the following categories: ‘no education’(1), ‘primary education’(2), ‘lower general or professional education’(3), ‘intermediate general education’(4), ‘intermediate professional education’(5), ‘higher general education’(6), ‘higher professional education’(7), and ‘university’(8). Categories 1 to 3 were recoded as ‘low’ and categories 4 to 8 were recoded as ‘higher’.
Health-related variables
Health-related variables were operationalised as functional health status measured by three items taken from the COOP/WONCA charts: physical fitness, emotional feelings, and overall health.24 Each item was scored on a five-point Likert scale. Physical fitness was
assessed by asking ‘During the past 2 weeks…. what was the hardest physical activity you were able to do for at least 2 minutes?’; answering options went from ‘very light, for example walk at a slow pace or not able to walk’(1) to ‘very heavy, for example run at fast pace’(5). Emotional feelings were assessed by the question ‘During the past 2 weeks…. how much have you been bothered by emotional problems such as feeling anxious, depressed, irritable or downhearted and sad?’; answering options went from ‘not at all’(1) to ‘extremely’(5). Overall health was assessed by asking ‘During the past 2 weeks…. how would you rate your health in general?’; answering options went from ‘poor’(1) to ‘excellent’(5). A higher score on each item indicates a higher level of fitness, more emotional problems, and a better overall health, respectively.
Cultural variables
Cultural variables refer to the extent to which a person is embedded in the culture in a geographically defined area; these consisted of one self-descriptive history item and two identity evaluation items. Self-descriptive history concerns a person’s level of perception of common heritage after living a longer time in a certain area. Answering options ranged from ‘yes, I was born here and have always lived in Eastern Groningen’(1) to ‘no, I was born outside the Netherlands, but I now live in Eastern Groningen’(4). The categories were merged into ‘being born and having lived in Eastern Groningen’(1) and ’not being born or not always having lived in Eastern Groningen’(2-4). Identity evaluation was a person’s perception of his relationship with his sociocultural environment. This consisted of two items scored on a five-point Likert scale: ‘Feeling happy to be a person from Eastern Groningen’ with answers from ‘totally disagree’(1) to ‘totally agree’(5) and ‘feeling connected to Eastern Groningen’ with answers from ‘I don’t feel at all connected’(1) to ‘I feel very connected’(5). A higher score indicates that a person is more regionally embedded.
Psychological variables
Psychological variables related to physical activity included attitude, perceived advantages, perceived disadvantages, self-efficacy, and social norms, based on the I-Change Model representing an integrated framework of individual factors of health-related behaviour.21
Attitude towards physical activity was measured by one item that asked: ‘How
important is sufficient physical activity to you?’ The question was rated on a five-point Likert scale from ‘not important at all’(1) to ‘very important’(5). A higher score indicates a more positive attitude towards physical activity.
Perceived advantages were what a person regarded as benefits of physical activity;
these consisted of nine items: ‘keeping my weight under control’; ‘taking care that I live longer’; ‘feeling more relaxed’; ‘giving me more energy’; ‘giving me a better condition’; ‘keeping me healthy’; ‘getting a disease less soon’; ‘making me feel more fit’; ‘making me feel good about myself’. The items were scored on a five-point Likert scale (α=.89) from ‘totally disagree’(1) to ‘totally agree’(5) and were averaged into one score. A higher score indicates perception of more advantages.
Perceived disadvantages were negative consequences, experienced or expected,
related to physical activity; these were measured by four items: ‘is painful’; ‘makes me too exhausted’; ‘takes a lot of time’; ‘makes me afraid to fall’. The items were scored on a five-point Likert scale (α=.72) from ‘totally disagree’(1) to ‘totally agree’(5) and were averaged in one score. A higher score indicates perception of more disadvantages.
Self-efficacy is a person’s confidence in his or her ability to be physically active in
specified situations. This was assessed using 12 items about expectations to succeed in various difficult situations. The items concerned ‘bad weather circumstances’; ‘having no partner in physical activity’; ‘lacking safety’; ‘not liking physical activity’; ‘feeling tired’; ‘having little time’; ‘not feeling well’; ‘suffering physical complaints’; ‘suffering physical complaints afterwards’; ‘lacking facilities’; ‘lacking contact with people of one’s own age’; ‘lacking acquaintances’. The items were scored on a five-point Likert scale (α=.87) from ‘very difficult’(1) to ‘very easy’(5) and were averaged in one score. A higher score indicates a higher self-efficacy.
The social norm regarding physical activity was measured by one item: ‘How important is physical activity for people in your direct social environment?’ This question was rated on a five-point Likert scale from ‘very unimportant’(1) to ‘very important’(5). A higher score indicates a stronger social norm, thus more social pressure/support to engage in physical activity.
Physical activity
We measured physical activity with the Short QUestionnaire to ASsess Health-enhancing physical activity (SQUASH), a validated Dutch questionnaire to measure physical activity in an adult population.25 The questionnaire includes four types of physical activity:
household-C o r r e l a t e s o f p h y s i c a l a c t i v i t y | 25
related physical activity, and leisure-time physical activity. The overall hours per week of physical activity and the three separate physical activity types (transport-related physical activity, household-related physical activity, and leisure-time physical activity) were calculated. Because only 21% of the participants population had not retired from work, we excluded work-related physical activity in this paper.
Statistical analyses
Three of the four physical activity measures (the subscales transport-related, household-related, and leisure-time physical activity) showed a skewed distribution; only total physical activity was approximately normally distributed. We therefore decided to dichotomise the subscales of physical activity measures to study their associations. We dichotomised household-related physical activity and leisure-time physical activity, using a median-split. Because more than 50% of the participants filled in no transport-related physical activity, we dichotomised this variable into ‘no’ versus ‘yes’. Total physical activity was presented as a continuous-level outcome variable.
We first described the background characteristics of our sample. Then we assessed the associations of our four measures of physical activity with sociodemographic (gender, age, marital status, employment status, and SES), health-related (physical fitness, emotional feelings, and overall health), cultural (historical area identity and identity evaluation), and psychological variables related to physical activity (attitude, perceived advantages, perceived disadvantages, self-efficacy, and social norms). Because the aim was not to test a conceptual model or mediational relations among variables, only univariate (no multivariate) analyses were conducted. We did so using linear regression analyses for total physical activity and logistic regression analyses for transport-related, household-related, and leisure-time physical activity. Finally, we separately assessed the associations within the two SES groups. To determine whether correlates of physical activity differed between the level of SES, interaction effects between each of the potential correlates on the one hand and level of SES on the other hand were analysed. In the case of a statistically significant interaction, the relation of the interacting variable with physical activity was assessed separately within low SES and within higher SES participants. Statistical tests were considered to be significant when p<0.05. All analyses were performed using SPSS version 20.0.
Results
Sample characteristics
Characteristics of the study participants, including level of SES, appear in Table 1. The mean age of the total sample was 66.7 years and 41% of the sample had a low SES. The data reveal
some clear differences between low and higher SES participants. About 64% of the low SES older adults were born and had remained in Eastern Groningen compared to only 32% of those with a higher SES. Regarding physical fitness, 27% of the low SES but 43% of higher SES older adults had a higher score, meaning that they had engaged in ‘heavy’ or ‘very heavy’ physical activity during the past 2 weeks.
Correlates of physical activity
Table 2 shows the results of regressing total, transport-related, household-related, and leisure-time physical activity on sociodemographic, health-related, cultural, and psychological variables. More total physical activity was associated to having a partner and higher self-efficacy. Higher scores on transport-related physical activity were related to younger age, better physical fitness, and being less happy to be a person from this region. More household-related physical activity was associated to being female, having no (paid) work, less physical fitness, and feeling less connected to this region. Higher scores on leisure-time physical activity were related to being male, having a partner, reporting better physical fitness, reporting better overall health, being born and having lived in the region, being happy to be a person from this region, and feeling connected to the region.
Correlates of physical activity per SES group
The univariate results for the low and higher SES participants separately are presented in Table 3. No significant interaction effects of total physical activity were found. Concerning transport-related physical activity, significant interaction effects were found for feelings and overall health: Only in higher SES participants, a lower score on emotional feelings was significantly associated with more physical activity. In low SES participants, overall health was related negatively to physical activity while in higher SES participants it was related positively to physical activity, but both relations were not significant. Regarding household-related physical activity, a significant interaction effect was found only for emotional feelings: In low SES participants, less emotional feelings was significantly associated with higher physical activity scores. Concerning leisure-time physical activity, only a significant interaction effect was found for being born and having lived in the region: For low SES participants, being born and having lived in the region was significantly associated with more physical activity.
C o r r e l a t e s o f p h y s i c a l a c t i v i t y | 27
Table 1. Characteristics of the participants.
Total Low SES Higher SES
Total samplea n=244 n=100 n=143
Gender (% male) 41.4 38.0 44.1
Age (mean (SD) in years) 66.7 (8.6) 67.7 (9.7) 66.4 (7.7)
Marital status (% having a partner) 74.6 70.0 77.6
Employment status (% paid work) 20.6 16.0 23.9
Physical fitness (% (very) heavy) 36.8 27.1 42.8
Emotional feelings (% not at all/ slightly) 88.2 87.6 88.7 Overall health (% excellent/ very good) 29.0 19.6 35.5 Being born and having lived in region (% yes) 44.4 63.6 31.5 Feeling happy to be a person from EG (% (very) happy) 75.8 79.0 74.1 Feeling connected to EG (% feeling (very connected) 80.7 82.0 79.7 Total PA (mean (SD))b 29.2 (17.2) 27.6 (17.0) 30.3 (17.3) Low (n=112) 15.9 (7.1) 15.1 (7.6) 16.5 (6.6) High (n=111) 42.6 (13.6) 43.5 (11.5) 42.1 (14.7) Transport-related PA (mean (SD))b 2.5 (4.7) 2.6 (5.0) 2.4 (4.5) No (n=123) 0.0 (0.0) 0.0 (0.0) 0.0 (0.0) Yes (n=102) 5.5 (5.7) 6.9 (6.2) 4.8 (5.4) Household-related PA (mean (SD))b 11.0 (10.7) 10.1 (9.5) 11.6 (11.3) Low (n=113) 2.8 (2.9) 2.3 (2.8) 3.2 (3.0) High (n=111) 19.4 (9.1) 18.2 (7.0) 20.1 (10.2) Leisure-time PA (mean (SD))b 10.3 (8.3) 9.5 (8.3) 10.8 (8.3) Low (n=114) 3.9 (2.7) 3.5 (2.7) 4.2 (2.7) High (n=113) 16.7 (7.0) 16.9 (6.7) 16.6 (7.1) Subsample n=137 n=54 n=82
Attitude (mean; range 1-5) 3.83 3.87 3.80
Social norm (mean; range 1-5) 3.73 3.74 3.72
Advantages (mean; range 1-5) 3.73 3.66 3.78
Disadvantages (mean; range 1-5) 2.39 2.48 2.33
Self-efficacy (mean; range 1-5) 2.97 2.84 3.07
SES: socioeconomic status; SD: standard deviation; EG: Eastern Groningen; PA: physical activity in hours/week; a For one respondent the SES classification was missing; b PA outcome missing: Total PA: n=21,
C o r r e l a t e s o f p h y s i c a l a c t i v i t y | 29
Table 3. Associations of health-related and cultural variables with transport-related
physical activity (PA), household-related PA, and leisure-time PA (hours/week) for older adults with low and with higher socioeconomic status (SES): odds ratios (95% confidence intervals), resulting from logistic regression analyses.
Transport-related PA Household-related PA Leisure-time PA
Low SES Higher SES Low SES Higher SES Low SES Higher SES Health-related Emotional feelings 1.38 (0.85-2.22) 0.58 (0.36-0.93)* 0.55 (0.32-0.95)* 1.24 (0.79-1.94) - - Overall health 0.58 (0.31-1.07) 1.23 (0.84-1.82) - - - - Cultural Being born and having lived in region (vs. not) - - - - 5.11 (1.91-13.70)** 1.25 (0.60-2.60) * p<0.05; ** p<0.01
Discussion
This study aimed to identify correlates of physical activity among older adults in a socioeconomically disadvantaged rural area in the Netherlands, and to assess whether the correlates of physical activity differed by SES. We found significant correlates from different clusters of variables of different types of physical activity: gender, age, marital status, social situation, physical fitness, overall health, self-efficacy, and cultural variables. However, the associations hardly differed between older adults with low and higher SES.
Among older adults in a socioeconomically disadvantaged rural area correlates vary for the different types of physical activity; this is in line with studies made of other target populations.26,27 Lumping all physical activities together may have blurred some
relations: for example, higher total physical activity score was related only to having a partner and higher self-efficacy, while some specific types of physical activity had more significant associations. More transport-related and household-related physical activity were both significantly related to sociodemographic variables, a health-related, and a cultural variable. However, more leisure-time physical activity was related to seven variables: male gender, having a partner, better physical fitness and overall health, and three cultural variables.
First of all, these findings show that the type of physical activity is important: although using total physical activity may indicate physical importance, its use may obscure the relations with potential predictors of physical activity. Leisure-time physical activity, on the other hand, showed several meaningful associations. This could reflect that people have more freedom in how they spend their leisure time than in how they travel (transport).
Second, in our target population we found gender and health-related variables to be associated to household-related and leisure-time physical activity: women engaged in more physical activity in the household, and men during their leisure time. This may represent classical gender role differences in this older population: women take care of the household while men tend to the garden and do odd jobs. Physical fitness was positively related to transport-related physical activity and leisure-time physical activity. The negative relationship between physical fitness and household-related physical activity could be due to confounding by gender.
Third, a novel finding was that one’s regional background was related to physical activity: being born and having lived in the region, feeling happy about coming from the region, and feeling more connected to the region were associated with more leisure-time physical activity. This shows the relevance of a person’s embedding in the physical and social environment of his region.28 We must, however, still establish the direction and meaning of
these relationships. While leisure-time physical activity was related to feeling more connected to the region, household physical activity was related to feeling less connected, and transport-related physical activity was related to feeling less happy to be from the region. “Regional identity” would therefore be an interesting topic for further study.
The second aim of our study was to test whether the correlates of physical activity differed between participants with low or with higher SES; we found only a few differences in correlates of physical activity between these participants. Regarding the total physical activity measure, the lack of a significant interaction between any of the variables and SES indicates that there were no SES differences. Concerning household-related and leisure-time physical activity, participants with low versus higher SES differed only regarding one association. Regarding transport-related, we found differing associations of two variables. Associations thus mostly do not differ between low and higher SES participants in this socioeconomically disadvantaged area. A lower statistical power might explain this finding if looking at subsamples of people with low and higher SES. However, the socioeconomically disadvantaged nature of the total area might offer an alternative explanation; that context may affect all residents, independent of their own SES.
Although most guidelines only concern moderate or high intensive activities, in the present study light physical activity was also included in the physical activity measures. This led to relatively high mean scores regarding minutes of physical activity. Evidence is increasing that not only moderate and heavy exercise are beneficial. For example, Buman et al. showed light-intensity physical activity to be associated with physical health and well-being in older adults.29 This effect may partially be caused by less sedentary behaviour;
recent research has shown that sedentary behaviour (i.e., prolonged sitting) increases the risk of mortality.30-32 In addition, light-intensity physical activity may empower people to
stay socially active and able to live independently longer. Thus, maintaining light-intensity physical activity might be a meaningful component of an active lifestyle.
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Strengths and limitations
A first strength of our study is that, based on the I-Change model, we assessed a wide range of variables potentially associated with physical activity. We identified significant correlates from all four clusters: sociodemographic, health-related status, cultural, and psychological variables. Another strength of our study was that, besides testing different clusters of variables, we included and compared different types of physical activity, providing more insights into these complex associations. Finally, older people and people with a low SES are subgroups hard to reach for prevention; 33 our study adds to the hitherto limited knowledge
of an important health-related behaviour of older people from a relatively disadvantaged rural area.
We must also acknowledge some limitations of the present study. First, the low response rate of subjects may have influenced the representativeness of the study. The adults aged 75 years and older in our sample were slightly less than representative when compared to objective figures taken from the municipality of Vlagtwedde.34 In addition,
over 40% of our study sample had a low SES (from no education to lower professional education), suggesting that the educational level of the sample was representative for the region. However, we cannot fully rule out some selection bias. A second limitation is the cross-sectional design, which limits the potential for inferences on causality. However, the I-Change model provides a theoretical background against which relationships can be interpreted. For example, sociodemographic variables (e.g., age) are themselves not causes of physical activity but may be related to causes, whereas perceived advantages may be a primary cause of leisure-time physical activity. Third, our measurement of SES was based on educational level, which represents just one aspect of SES.35 However, this regards the
most frequently used indicator of SES in the Netherlands.36 Finally, we used short measures
to assess the psychological variables. Although even one-item measures are often valid, 37-39 our psychological measures may have lacked sufficient reliability.
Conclusions
This study contributes to the understanding of different clusters of correlates of types of physical activity among older adults in a socioeconomically disadvantaged rural area. We found relevant correlates of physical activity in our sample. These findings can help in the development of effective intervention strategies to promote physical activity among this target population. They may be valued as calling for a multi-component perspective for intervention development, taking into account different types of physical activity. In the end, we hope that such well-informed interventions will help to stimulate people in socioeconomically disadvantaged areas to engage in more physical activity.
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3
Developing a community-based intervention
on physical activity and healthy eating
of older adults in a socioeconomically
disadvantaged community:
an Intervention Mapping approach
Karla A. Luten Arie Dijkstra Andrea F. de Winter Sijmen A. Reijneveld
Abstract
Objective: Low levels of physical activity and unhealthy eating are major health risks,
especially for older adults and those with a low socioeconomic status. The aim is to describe the development of a community-based intervention aimed at promoting physical activity and healthy eating among older people in a socioeconomically disadvantaged community.
Methods: The Intervention Mapping protocol was used to develop the intervention. We
conducted a literature search, consultation with community partners and inhabitants, and a quantitative study, in order to obtain insight into the determinants of the target population and to identify appropriate theory-based methods and practical strategies for behavioural change. The I-Change Model and ANGELO framework served as theoretical bases.
Results: An assessment was performed of the problem with respect to health-related
behaviour and the underlying determinants. Findings were translated into program and change objectives which specify determinants related to behavioural change. Theory-based methods and practical applications were selected, resulting in a plan for adoption and implementation of the community-based intervention. The intervention included a local media campaign, social environmental approaches, and physical environmental activities in the community, with an intermediating role for inhabitants and health professionals in the promotion of the campaign. An evaluation plan was produced to evaluate the effectiveness of the intervention.
Conclusions: The Intervention Mapping protocol was a helpful instrument in developing a
feasible, theory- and evidence-based health promotion intervention tailored to a specific target population. The systematic and structured approach provided insight into the relationship between the objectives, methods, and strategies used to achieve a multi-component intervention aimed at reaching and having impact on the individual and creating a supportive environment, which can be regarded as adding value to the subject.
