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Cardiometabolic disease has been an increasing trend globally and remains the major cause of morbidity and mortality in Hong Kong. Health coaching intervention are generally effective for managing chronic disease and prevention of complication. However, there is fewer attention on the effects of health coaching in primary disease prevention. This study aims to evaluate the effects of health coaching programme on increasing health promoting behaviours in middle-aged adults with cardiometabolic risk.
Cardiometabolic disease, including metabolic syndrome, prediabetes, type 2 diabetes mellitus, coronary heart disease, myocardial infarction and stroke, has been an increasing trend globally, and increased more than double over 5 years in China [1].
Cardiometabolic disease remains the major cause of morbidity and mortality in Hong Kong [2]. Type 2 diabetes mellitus is associated with increased risk for morbidity and mortality [3]. Ischaemic heart disease and stroke were the major cause of disability-adjusted life years (DALYs) worldwide, resulting in dependence, disability and cognitive impairment [4]. Moreover, midlife stroke risk is associated with cognitive decline within 10 years [5].
A local population health survey has reported that 41.1% of persons between the ages of 45 and 64 are at medium-to-high risk of developing cardiovascular diseases over the next 10 years [6]. Most of the cardiometabolic diseases are attributable to health behaviours. An international study identified risk factors for coronary heart disease and validated the non-laboratory INTERHEART Risk Score (IHRS), which is mainly calculated based on behavioural risk factors, including smoking, stress and physical activity [7]. Also, another study among 32 countries in Asia, Africa, Australia, Europe, the Middle East and USA reported that over 90% of the population attributable risks of stroke could be explained by behavioural risk factors measured by IHRS [8]. Proactive measures to moderate these modifiable risk factors are crucial to halt the increasing trend of cardiometabolic disease.
Health coaching interventions are generally effective for managing chronic diseases, including cancer, heart disease, diabetes and hypertension [9]. A systematic review reported health coaching significantly increased physical activity, improved physical and mental health status in patients with chronic disease [10]. Health coaching interventions assist patients to participate actively in their health care, and health coaches collaborate with patients by giving support and promoting self-efficacy in disease management [11]. Despite the widespread use of evidence based health coaching in chronic disease management and prevention of complication, there is fewer attention on the effects of health coaching in primary disease prevention.
Therefore, a large-scale, robust clinical trial examining the effects of health coaching in reducing the cardiometabolic risk in middle-aged adults is warranted. The purpose of this study is to address the research gap by evaluating the effects of health coaching programme on increasing health promoting behaviours in middle-aged adults with cardiometabolic risk.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Health coaching | Experimental | Health coaching |
|
| Usual care | No Intervention | Usual care |
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Health coaching | Behavioral | The health coaching program includes four monthly health coaching sessions for three months. |
|
| Measure | Description | Time Frame |
|---|---|---|
| Change in health promoting behaviours | The Chinese version of Health Promoting Lifestyle Profile II (HPLP II) , including health responsibility (9 items), nutrition (9 items), physical activity (8 items) and stress management (8 items), measure the practice of health-promoting behaviours | Change from baseline at 3 months and 6 months post allocation |
| Measure | Description | Time Frame |
|---|---|---|
| Change in cardiometabolic risk | Non-laboratory INTERHEART Risk Score (IHRS) assess the risk of cardiometabolic disease | Change from baseline at 3 months and 6 months post allocation |
| Change in stroke risk |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Zoe Kwok | Contact | 3943 9928 | zoekwok@cuhk.edu.hk |
| Name | Affiliation | Role |
|---|---|---|
| Zoe Kwok | Chinese University of Hong Kong | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| The Chinese University of Hong Kong | Recruiting | Hong Kong | Hong Kong |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 30833320 | Background | Zhang D, Tang X, Shen P, Si Y, Liu X, Xu Z, Wu J, Zhang J, Lu P, Lin H, Gao P. Multimorbidity of cardiometabolic diseases: prevalence and risk for mortality from one million Chinese adults in a longitudinal cohort study. BMJ Open. 2019 Mar 3;9(3):e024476. doi: 10.1136/bmjopen-2018-024476. | |
| Background | 2. Centre of Health Protection. Death rates by leading causes of death, 2001-2019. Hong Kong SAR government: 2020. | ||
| 23894121 |
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| ID | Term |
|---|---|
| D002318 | Cardiovascular Diseases |
| D008659 | Metabolic Diseases |
| D015438 | Health Behavior |
| ID | Term |
|---|---|
| D009750 | Nutritional and Metabolic Diseases |
| D001519 | Behavior |
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Automatic retinal image analysis (ARIA)-stroke will be used to quantify stroke risk
| Change from baseline at 3 months and 6 months post allocation |
| Change in self-efficacy of adopting health promoting behaviours | Adapted version of the Diabetes Mellitus Type II Self Efficacy Scale will be used to rate the participants level of confidence in various behaviours | Change from baseline at 3 months and 6 months post allocation |
| Change in psychological distress | The Chinese version of the shorter version of Depression Anxiety Stress Scales (DASS) developed by Lovibond and Lovibond in 1995 will be used | Change from baseline at 3 months and 6 months post allocation |
| Change in sleep quality | The Chinese version of the Pittsburg Sleep Quality Index developed by Buysse and team in 1988 will be used | Change from baseline at 3 months and 6 months post allocation |
| Change in physical activities | International Physical Activity Questionnaire - Chinese (IPAQ-C), a short version, 9-item scale, will be used to assess the level of physical activities | Change from baseline at 3 months and 6 months post allocation |
| Change in systolic blood pressure | Blood pressure measurement using an electronic sphygmomanometer | Change from baseline at 3 months and 6 months post allocation |
| Change in diastolic blood pressure | Blood pressure measurement using an electronic sphygmomanometer | Change from baseline at 3 months and 6 months post allocation |
| Change in Body Mass Index | Body Mass Index will be calculated by the measured height and weight | Change from baseline at 3 months and 6 months post allocation |
| Change in waist-hip-ratio | Waist-hip-ration will be calculated by the measured waist and hip circumference | Change from baseline at 3 months and 6 months post allocation |
| Change in blood glucose | Point of care testing of blood for glucose | Change from baseline at 3 months and 6 months post allocation |
| Change in blood total cholesterol | Point of care testing of blood for total cholesterol | Change from baseline at 3 months and 6 months post allocation |
| Change in blood urate | Point of care testing of blood for urate | Change from baseline at 3 months and 6 months post allocation |
| Background |
| Guo F, Moellering DR, Garvey WT. The progression of cardiometabolic disease: validation of a new cardiometabolic disease staging system applicable to obesity. Obesity (Silver Spring). 2014 Jan;22(1):110-8. doi: 10.1002/oby.20585. Epub 2013 Sep 5. |
| 33069326 | Background | GBD 2019 Diseases and Injuries Collaborators. Global burden of 369 diseases and injuries in 204 countries and territories, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet. 2020 Oct 17;396(10258):1204-1222. doi: 10.1016/S0140-6736(20)30925-9. |
| 23199495 | Background | Kaffashian S, Dugravot A, Brunner EJ, Sabia S, Ankri J, Kivimaki M, Singh-Manoux A. Midlife stroke risk and cognitive decline: a 10-year follow-up of the Whitehall II cohort study. Alzheimers Dement. 2013 Sep;9(5):572-9. doi: 10.1016/j.jalz.2012.07.001. Epub 2012 Nov 28. |
| Background | 6. Centre for Health Protection. Population Health Survey 2014/2015. Hong Kong SAR Government.: 2017. |
| 21177699 | Background | McGorrian C, Yusuf S, Islam S, Jung H, Rangarajan S, Avezum A, Prabhakaran D, Almahmeed W, Rumboldt Z, Budaj A, Dans AL, Gerstein HC, Teo K, Anand SS; INTERHEART Investigators. Estimating modifiable coronary heart disease risk in multiple regions of the world: the INTERHEART Modifiable Risk Score. Eur Heart J. 2011 Mar;32(5):581-9. doi: 10.1093/eurheartj/ehq448. Epub 2010 Dec 22. |
| 27431356 | Background | O'Donnell MJ, Chin SL, Rangarajan S, Xavier D, Liu L, Zhang H, Rao-Melacini P, Zhang X, Pais P, Agapay S, Lopez-Jaramillo P, Damasceno A, Langhorne P, McQueen MJ, Rosengren A, Dehghan M, Hankey GJ, Dans AL, Elsayed A, Avezum A, Mondo C, Diener HC, Ryglewicz D, Czlonkowska A, Pogosova N, Weimar C, Iqbal R, Diaz R, Yusoff K, Yusufali A, Oguz A, Wang X, Penaherrera E, Lanas F, Ogah OS, Ogunniyi A, Iversen HK, Malaga G, Rumboldt Z, Oveisgharan S, Al Hussain F, Magazi D, Nilanont Y, Ferguson J, Pare G, Yusuf S; INTERSTROKE investigators. Global and regional effects of potentially modifiable risk factors associated with acute stroke in 32 countries (INTERSTROKE): a case-control study. Lancet. 2016 Aug 20;388(10046):761-75. doi: 10.1016/S0140-6736(16)30506-2. Epub 2016 Jul 16. |
| 24416684 | Background | Wolever RQ, Simmons LA, Sforzo GA, Dill D, Kaye M, Bechard EM, Southard ME, Kennedy M, Vosloo J, Yang N. A Systematic Review of the Literature on Health and Wellness Coaching: Defining a Key Behavioral intervention in Healthcare. Glob Adv Health Med. 2013 Jul;2(4):38-57. doi: 10.7453/gahmj.2013.042. |
| 25127667 | Background | Kivela K, Elo S, Kyngas H, Kaariainen M. The effects of health coaching on adult patients with chronic diseases: a systematic review. Patient Educ Couns. 2014 Nov;97(2):147-57. doi: 10.1016/j.pec.2014.07.026. Epub 2014 Aug 1. |
| Background | 11. UCSF Center for Excellence in Primary Care. Health coach curriculum. University of California: 2014. |
| Background | 12. WalkerSN, Hill-PolereckyDM. Psychometric evaluation of the Health-Promoting Lifestyle Profile II. Unpublished manuscript, University of Nebraska Medical Center 1996. |
| 15982194 | Background | Lee RL, Loke AJ. Health-promoting behaviors and psychosocial well-being of university students in Hong Kong. Public Health Nurs. 2005 May-Jun;22(3):209-20. doi: 10.1111/j.0737-1209.2005.220304.x. |
| Background | 14. ZeeB, LeeJ, LiQ, MokV, KongA, ChiangL, et al. Stroke risk assessment for the community by automatic retinal image analysis using fundus photograph. Qual Prim Care 2016;24:114-24. |
| 30596258 | Background | Brouwer-Goossensen D, van Genugten L, Lingsma HF, Dippel DWJ, Koudstaal PJ, den Hertog HM. Self-efficacy for health-related behaviour change in patients with TIA or minor ischemic stroke. Psychol Health. 2018 Dec;33(12):1490-1501. doi: 10.1080/08870446.2018.1508686. Epub 2018 Dec 30. |
| Background | 16. CheungAKY, ToriCD, LamCLK. Psychosocial correlates of medically unexplained physical symptoms in primary care settings: a cross-sectional study in Hong Kong. Hong Kong Pract 2012;34:99-105. |
| 16155782 | Background | Tsai PS, Wang SY, Wang MY, Su CT, Yang TT, Huang CJ, Fang SC. Psychometric evaluation of the Chinese version of the Pittsburgh Sleep Quality Index (CPSQI) in primary insomnia and control subjects. Qual Life Res. 2005 Oct;14(8):1943-52. doi: 10.1007/s11136-005-4346-x. |
| 16807105 | Background | Macfarlane DJ, Lee CC, Ho EY, Chan KL, Chan DT. Reliability and validity of the Chinese version of IPAQ (short, last 7 days). J Sci Med Sport. 2007 Feb;10(1):45-51. doi: 10.1016/j.jsams.2006.05.003. Epub 2006 Jun 30. |