Literature review for a research Proposal assignment

Original Article

Examination of a Nurse-led Community-based Education and Coaching Intervention for Coronary Heart Disease High-risk Individuals in China

Yan-Jin Huang, RN, PhD, 1 Monica Parry, NP-Adult, PhD, CCN(C), 2 Ying Zeng, RN, PhD, 3

Yan Luo, RN, PhD, 4 Jing Yang, RN, 5 Guo-Ping He, B.S.Med 1, * 1 Department of Community Nursing, Xiangya Nursing School, Central South University, Changsha, PR China 2 Department of Nurse Practitioner Field of Study, Lawrence S. Bloomberg Faculty of Nursing, University of Toronto, Toronto, Canada 3 Department of International and Humanistic Nursing, School of Nursing, University of South China, Hengyang, PR China 4 Department of Surgical Nursing, School of Nursing, Xi'an Jiaotong University, Xi'an, PR China 5 Department of Nursing, The Second Affiliated Hospital of University of South China, Hengyang, PR China

a r t i c l e i n f o

Article history: Received 11 November 2016 Received in revised form 18 July 2017 Accepted 24 July 2017

Keywords: coronary heart disease intervention study primary prevention

a b s t r a c t

Purpose: Early detection and management of coronary heart disease (CHD) are embedded into many community health service and primary care practices in western countries. The Framingham CHD risk score has been used to predict CHD and mortality for nearly 20 years, and it has predicted CHD event risk accurately in multiethnic populations. The aim of this study was to access the effect of a 6-month community-based intervention on CHD risk in individuals at high risk. Methods: A randomized controlled trial of individuals with a high 10-year CHD risk were recruited from two communities in China. Individuals in the intervention group (n ¼ 53) received a 3-month group education and a 3-month coaching session. Physical examination and self-report questionnaires were used to collect both pre- and postintervention data on blood pressure, glucose, cholesterol, body mass index, smoking, depression, and health-related quality of life (HRQoL). Results: A total of 102 participants (85.0%) completed the 6-month study. Compared with the usual care group, the intervention group had a 5 mmHg greater reduction in systolic blood pressure (t ¼ 2.01, p ¼ .047), larger declines in glucose (t ¼ �2.49, p ¼ .015), cholesterol (t ¼ �2.44, p ¼ .017), body mass index (t ¼ �2.58, p ¼ .011), and depression (t ¼ �2.05, p ¼ .043), and better reports of HRQoL (t ¼ 3.36, p ¼ .001). No significant group differences in smoking behaviors were reported. Conclusion: A 6-month community-based intervention in a CHD high-risk population improved disease- related risk factors, depression, and HRQoL. Results provide preliminary evidence for primary prevention of cardiovascular disease risk in a community high-risk population. © 2017 Korean Society of Nursing Science, Published by Elsevier Korea LLC. This is an open access article

under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Introduction

Coronary heart disease (CHD), a main component and leading cause of cardiovascular disease (CVD), contributed nearly half of all CVD deaths worldwide. CHD is a significant public health problem, with a high morbidity and mortality among adults, and it causes a substantial economic burden to societies. Globally, the mortality

attributable to CHD was 7.2 million in 2012, and it is estimated that by 2020, the number will exceed 11.1 million [1]. In developing countries such as China, more than 10 million people have expe- rienced at least one CHD event, and more than 1.3 million have died of CHD [2]. CHD presents a large and growing burden to the Chinese government, with treatment costs exceeding 20 billion dollars in 2013 [2].

CHD is a multifactorial disease with worldwide regional varia- tions, influenced in part by income and exposure [3]. Hypertension, diabetes, high cholesterol, obesity, smoking, and other unhealthy lifestyle behaviors have been widely accepted as modifiable risk factors [4]. Generally, risk-factor burden is lowest and coronary

* Correspondence to: Guo-Ping He, Xiangya Nursing School, Central South University, 172 Tongzipo Road, Changsha, Hunan 410013, PR China.

E-mail address: [email protected]

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Asian Nursing Research

journal homepage: www.asian-nursingresearch.com

https://doi.org/10.1016/j.anr.2017.07.004 p1976-1317 e2093-7482/© 2017 Korean Society of Nursing Science, Published by Elsevier Korea LLC. This is an open access article under the CC BY-NC-ND license (http:// creativecommons.org/licenses/by-nc-nd/4.0/).

Asian Nursing Research 11 (2017) 187e193

event occurrence is highest in less developed countries [5]. The leading risk factor for cardiovascular mortality in both men and women in China and even in East Asia area is hypertension [1]. In addition to hypertension and other physiological risk factors identified in the Sino-MONICA Project [6], the INTER-HEART China study [7] suggests that psychological risk factors (stress and depression) are associated with an increased risk of CHD in China. People with depression fear stigmatization, avoid professional counseling, and suffer from a poor health-related quality of life (HRQoL). Early detection and management of physiological and psychological risks in a high-risk population may reduce the burden of CHD and its associated complications.

There are several multirisk assessment tools used to identify peopleathighriskofCHD[8,9],includingthe:(1)AmericanCollege of Cardiology/American Heart Association Cardiovascular Risk Calcu- lator 2013 (ACC/AHA 2013), (2) National Cholesterol Education Pro- gram Adult Treatment Panel IV (NCEP ATP-IV), (3) European System for Cardiac Operative Risk Evaluation (EURO-SCORE), (4) WHO/In- ternational Society of Hypertension (ISH) Prevention of Cardiovas- cular Disease, and (5) Framingham CHD risk score. The ACC/AHA Calculator 2013 has been primarily used to detect CVD risk in Caucasian and African-American populations; its accuracy in detect- ing CVD risk in other populations has not been reliably demonstrated [10]. The ATP-IV tool assesses risk of CVD in adults by screening for dyslipidemia, and has not been used by nonprofessionals with little knowledge of CHD [11]. The EURO-SCORE estimates CVD death rate, and results generally overestimate risk of CVD [12]. The WHO/ISH CVD tool assesses the 10-year risk of any CVD event and is not specific forCHD[13]. The Framingham CHD riskscore has beenused topredict CHD and mortalityfor nearly20years.Existingevidence suggests that theFraminghamCHDriskscoremoreaccuratelypredicts10-yearCHD events in multiple ethnic populations.

Early detection and management of CHD are embedded into many community health service (CHS) and primary care practices. ‘The Check It, Change It’ program proved that CHS could strengthen knowledge and skills in a community population to enhance blood pressure control [14]. The Coronary Health Improvement Project assisted a US community population to lower rates of depression via a series of community-based interventions [15]. Health education is a necessary first step to disease prevention and management; however, variations in participant demographics affect learning and engagement in disease prevention strategies [16]. Knowledge is essential, but not sufficient to change health behaviors. Coaching is a person-centered process that combines health education and health promotion within a coaching context, telephone and face-to-face coaching interventions of 6 to 8 months have improved outcomes for individuals with chronic disease [16].

CHD is a national burden in China. It causes significant suffering, disability, and death; and costs related to the treatment of com- plications related to CHD are escalating [17]. The primary goal of this randomized controlled trial was to examine the impact of a community-based education and coaching intervention on systolic blood pressure (SBP) in individuals at high risk of CHD. Secondary goals were to examine the impact of a community-based education and coaching intervention on clinical characteristics (glucose, cholesterol, body mass index (BMI), and smoking), depression, and HRQoL.

Methods

Study design

This prospective, quasi experimental study was conducted at two CHS centers in Hengyang, China. Using health information

systems and the Framingham CHD risk score, 120 individuals with high 10-year risk of CHD were recruited to participate in the study.

Setting and sample

Individuals were eligible for inclusion if they were 30 to 79 years of age, had a CHD event or death risk more than 20%, and able to give informed consent and participate in the research. They were excluded if they had been clinically diagnosed with a neuropsy- chiatric disorder, peripheral vascular disease, liver disease, CHD, acute inflammation or another immunologic disorder, malignancy, or chronic renal failure. Individuals were also excluded if they had received previous medical education or had participated in similar research in past 6 months.

The sample size was calculated using the formula N ¼ (ma þ mb)2 � sd2/d2, where sd is the estimated standard deviation (SD), d is the mean difference between two groups, a is the significance level, and b is the power of test. Assuming a mean group difference of 9 mmHg in SBP [18], an a of .05, and a b of .05, the value of ma and mb are 1.96 and 1.64, respectively. Based on this data, and an attrition of 15%, a sample size of 60 in each group was required.

Ethical consideration

All individuals were recruited to participate in the study following ethics approval at Xiangya Nursing School of Central South University (Approval no. 2015023). Before data collection, two community nurses were trained by researcher to explain the study purpose, methods, benefits, and risks in detail to individuals. Interested participants were invited to the CHS to obtain informed consent.

Measurement

Demographics The following demographics of the sample collected by partic-

ipant interview and chart review were used to describe the sample: age, education, occupation, income, family history of CHD, and risk factors.

Systolic blood pressure SBPs were taken in the morning, in community health centers,

using Omron HEM-1000electronic (oscillometric) device and an appropriately sized cuff after 5 minutes of rest. The cuff was placed on the upper arm so that the bladder of the cuff centered over the brachial artery. Measurements were taken on the arm with the highest blood pressure measurement, and participants were encouraged to refrain from eating or smoking for at least 30 mi- nutes before blood pressure measurements were obtained. Three blood pressure readings were taken at 1-minute intervals and averaged to obtain the final SBP value.

Clinical characteristics The researchers collected plasma glucose and lipid profiles after

a 10-hour fast, and BMI was computed from height and weight measurements taken at the CHS center. Smoking behavior was defined as current smoker, nonsmoker, or an ex-smoker (absti- nence for at least 1 year).

Depression Depression was assessed using the self-rating depression scale

(SDS), a 20-item scale that has been translated into several lan- guages and used worldwide. Total scores range from 20 to 80, and scores can be standardized (0e100) to facilitate comparisons across populations. Standardized scores for the Chinese population can be

Y.-J. Huang et al. / Asian Nursing Research 11 (2017) 187e193188

categorized as normal (25e52), mildly depressed (53e62), moderately depressed (63e72), and severely depressed (>72) [19]. SDS is a valid and sensitive measure of clinical severity in depres- sion, with a reported reliability of .73 and Cronbach a is .82.

Health-related quality of life The Quality of Life Instrument for Chronic Diseases was used to

assess participants' HRQoL across three function domains: physi- ological, psychological, and social. It has been developed for use in the Chinese population, and contains 32 items, total scores range from 32 to 160, with total subscale scores for physiological function 10 to 50, psychological function 12 to 60, and social function 10 to

50. Higher scores represent better HRQoL. Cronbach a is .77 and reliability is reported above .7. For comparisons, standardized values of 0 to 100 were calculated for this sample.

Procedure

Participants were recruited and enrolled from two CHS, they signed an informed consent and were randomized to either inter- vention group or usual care group. To avoid treatment contami- nation, efforts were made to make participants from different groups knowing each other's assignment. Trained community nurses collected baseline and outcome data at 6 months (Figure 1).

Target popula on screened out N = 378

Invited to par cipate N = 120

Informed consent

Pre-test data collec on N = 120

SBP Clinic characteris cs

Depression HRQoL

Usual care group n = 60

Usual care group n = 60

Rou ne care 6-month

n = 49

Group educa on session

3-month n = 57

Follow-up coaching support

session 3-month

n = 53

1. Two lectures/month 2. CHD primary preven on materials

Exclusion: ----Lost to follow-up (n = 1) ----Withdrawn (n = 2)

1. A home visit and two telephone calls/month 2. Health consulta on

Exclusion: ----Diagnosed with CHD (n = 1) ----Lost to follow-up (n = 2) ----Withdrawn (n = 1)

SBP Clinic characteris cs

Depression HRQoL

1. Brochures about CHD primary preven on 2. Health consulta on

Exclusion: ----Diagnosed with CHD (n = 2) ----Withdrawn (n = 9)

Post-test data Collec on N = 102

Figure 1. Participant flow diagram. Note. HRQoL ¼ health-related quality of life; SBP ¼ systolic blood pressure.

Y.-J. Huang et al. / Asian Nursing Research 11 (2017) 187e193 189

Intervention group Participants in the intervention group received a 6-month inter-

vention,dividedintotwo3-monthsessions.Duringthefirst3months, participants received group education, which consisted of two 30- minute health-related lectures conducted by the principal investi- gator each month. Topics of the group education lectures included healthy eating, exercise advice, mood, medications, and CHD signs and symptoms. In addition, materials related to CHD primary pre- vention were provided to participants after each lecture. During the last 3 months, participants received a coaching support intervention, consisting of a monthly follow-up home visit and two telephone calls. The purpose of the first home visit was to provide an individualized management plan for healthy eating and exercise based on the par- ticipant's specific health problem, economic background, family support, and emotional state. The purpose of the second and third home visits and the follow-up telephone calls was to reinforce the individualized management plan and to suggest alternatives if spe- cific deficiencies existed. Clarification regarding medications and discussions about mood state also occurred during the home visits and the telephone calls. Participants were also encouraged to contact the research team if there were concerns or questions.

Usual care Participants in the usual care group received routine care pro-

vided by the CHS, including brochures containing information about CHD primary prevention, health information consultation within the CHS, and telephone follow-up by the CHS as required.

Data analysis

Two research assistants input data independently into two da- tabases and the databases were compared for consistency using EpiData (Clarivate Analytics, Philadelphia, PA, USA). Inconsistencies were reported to the principal investigator who checked original data collection forms and contacted participants for clarification as necessary. Once accuracy of the data was confirmed, statistical an- alyses were performed using SPSS version 13.0 (SPSS Inc., Chicago, IL, USA). Descriptive statistics were computed for all demographic variables, and group differences were assessed using t tests for continuous variables and c2 statistics for categorical variables.

Results

Homogeniety of samples

A total of 378 individuals were identified with a high 10-year CHD risk. Of 284 individuals who met the inclusion criteria and expressed an interest to participate in the study, 60 were invited from each CHS to complete the informed consent process and baseline assessment and questionnaires. Eighty five percent of participants (n ¼ 102) completed the 6-month study, with an attrition of 18.3% (n ¼ 11) in the intervention group and 11.7% (n ¼ 7) in the usual care group. There were no significant baseline group differences. The mean age of the sample was 57.71 years (SD ¼ 11.32 years), most received primary education or less, and most had moderate incomes. Although over 65.7% of the sample did not have a family history of heart disease, they had a high 10-year CHD risk (Table 1).

Intervention effects

There was a high prevalence of hypertension among the par- ticipants in our study, with baseline SBP values of 147.29 mmHg (SD ¼ 15.36) in intervention group and 146.88 mmHg (SD ¼ 15.64) in the usual care group. The SBP of participants in the intervention

group decreased by 5 mmHg (p < .001) and there were no changes in SBP of participants in the usual care group (p ¼ .169). Compared with the usual care group, the intervention group decreased 5 mmHg more on SBP (t ¼ 2.01, p ¼ .047).

The within and between group effects for glucose, cholesterol, BMI, and smoking are detailed in Table 2. Compared with the usual care group, participants in the intervention group had a significant reduction in glucose (t ¼ �2.49, p ¼ .015), cholesterol (t ¼ �2.44, p ¼ .017), and BMI (t ¼ �2.58, p ¼ .011). Three participants in the intervention group stopped smoking; however, this was not sta- tistically significant (c2 ¼ 0.02, p ¼ .882).

The change in depression scores from baseline to 6 months is reported in Table 2. Before the study, participants in both intervention and control groups were mildly depressed, with total mean SDS scores in intervention group of 56.02 (SD ¼ 14.43) and the usualcaregroupof55.61(SD¼ 13.11).Participants inthe intervention group had a significant reduction in total SDS scores postintervention (t ¼ 7.64, p < .001), and there were no significant changes in total mean SDS scores in the usual care group (t ¼ �1.49, p ¼ .143). Compared with the usual care group, participants in the intervention group had a significant improvement in depression scores from baseline to postintervention (t ¼ �2.05, p ¼ .043) (Table 2).

Baseline mean total HRQoL scores for the intervention and usual care groups were 60.96 (SD ¼ 10.20) and 61.02 (SD ¼ 9.25), respectively. For both groups, mean total HRQoL scores increased from baseline to 6 months, but this change was only significant for the intervention group (t ¼ �8.00, p < .001), and it was significant across all three function domains: physiologic (t ¼ �6.45, p < .001), psychologic (t ¼ �5.57, p < .001) and social (t ¼ �8.65, p < .001). There were no significant changes in total or function domain scores for participants in the usual care group. Compared with the

Table 1 Baseline Characteristics of Participants (N ¼ 102).

Characteristics Total Usual care group (n ¼ 49)

Intervention group

(n ¼ 53) n (%) or Mean ± SD

Gendery Male 55 (53.9) 27 (55.1) 28 (52.8) Female 47 (46.1) 22 (44.9) 25 (47.2)

Age (yr)y 57.71 ± 11.32 57.67 ± 12.79 57.87 ± 9.53 Educationy Primary school

or less 45 (44.1) 23 (46.9) 22 (41.5)

High school 34 (33.3) 16 (32.7) 18 (34.0) At least college 23 (22.5) 10 (20.4) 13 (24.5)

Occupation statusy Employed 43 (42.2) 22 (44.9) 21 (39.6) Retired 59 (57.8) 27 (55.1) 32 (60.4)

Income (individual/mo)y <￥1500

(<250 USD) 14 (13.7) 6 (12.3) 8 (15.1)

￥1500e￥5000 (250e800 USD)

54 (52.9) 26 (53.1) 28 (52.8)

>￥5000 (>800 USD)

34 (33.3) 17 (34.7) 17 (32.1)

Family history of heart diseasey With 35 (34.3) 16 (32.7) 19 (35.9) Without 67 (65.7) 33 (67.4) 34 (64.2)

Risk factorsy Hypertension 43 (42.2) 20 (40.8) 23 (43.4) T2DM 32 (31.4) 15 (30.6) 15 (28.3) Hyperlipoidemia 19 (18.6) 9 (18.4) 10 (18.9) Smoking 24 (23.5) 11 (22.5) 13 (24.5) BMI (kg/m2) 24.58 ± 2.59 24.61 ± 2.83 24.57 ± 2.29

y The baseline characteristics and risk factors of two groups were similar for all parameters (all p's > .05, by c2 or t test analyses). Note. BMI ¼ body mass index; SD ¼ standard deviation; T2DM ¼ type 2 diabetes mellitus.

Y.-J. Huang et al. / Asian Nursing Research 11 (2017) 187e193190

usual care group, participants in the intervention group had a sig- nificant improvement in total HRQoL scores from baseline to postintervention (t ¼ 3.36, p ¼ .001) (Table 3).

Discussion

The primary goal of this randomized controlled trial was to examine the impact of a community-based education and coaching intervention on SBP in individuals with high CHD risk in China. Study results suggest that there is a high prevalence of hyperten- sion based on the Framingham risk score. Compared with the usual care group who had no change in SBP, the decrease in SBP for participants in the intervention group was statistically and clini- cally significant. A meta-analysis of 464,000 individuals reported that a 10 mmHg decrease in SBP would lead to a 22% reduction in CHD events, and a 41% reduction in mortality from stroke [20]. Existing studies confirm that community-based interventions lead to positive effects on reducing blood pressure. ‘The Check It, Change It’ program results showed that a 6-month community-based intervention could reduce SBP by more than 10 mmHg in community-dwelling adults [14], and Zoellner et al [21] found that a 6-month community-based intervention reduced SBP and other disease-related factors, supporting the results in our study. Results of our study reported a smaller reduction in SBP compared with

others, likely due to the high prevalence of hypertension among the high-risk Chinese population.

Results also suggest that this nurse-led community-based edu- cation and coaching intervention reduced glucose, cholesterol, and BMI for participants in the intervention group and that these re- ductions have a positive effect on CHD prevention. The South Asian Heart Lifestyle Intervention (SAHELI) study demonstrated that South Asians could experience a significant change in weight and other clinical risk factors after a series of community-based in- terventions [22]. The SAHELI study, with 6 weeks of group educa- tion and 12 weeks of an individualized intervention in a community setting, reported that the cardiovascular risk factors of a community population also decreased significantly. However, our results did not show a statistically significant reduction in smoking in either the intervention or the usual care group. Smoking is the second main risk factor to CHD in China, with nearly 30% of the population reporting daily smoking behaviors [23]. Almost 24% of our sample were smokers; smoking is an addictive behavior, and it appears that a 6-month community-based intervention was not enough to help participants withdraw from their nicotine addiction. Future studies should consider an interdisciplinary approach, with physician, pharmacist, and psychologist input to smoking cessation.

Depression is an independent risk factor for CVD, one of the main causes of poor HRQoL, and a significant complication of

Table 2 Intervention Effects on SBP, Glucose, Cholesterol, BMI, Smoking, and Depression.

Risk factors Preintervention Postintervention Within group difference Between group difference

n (%) or Mean ± SD n (%) or Mean ± SD Mean or n 95% CI/(%) t or c2 p t or c2 p

SBP (mmHg) �2.01 .047 Intervention group (n ¼ 53) 147.29 ± 15.36 141.96 ± 15.23 �5.29 (�7.45, 5.12) 15.83 .001 Usual care group (n ¼ 49) 146.88 ± 15.64 146.86 ± 14.91 �1.17 (�0.51, 2.86) 1.40 .169

FPG (mmol/L) �2.49 .015 Intervention group (n ¼ 53) 6.42 ± 1.63 5.80 ± 1.35 �0.62 (�0.77, �0.47) 8.06 <.001 Usual care group (n ¼ 49) 6.39 ± 0.91 6.37 ± 0.87 �0.02 (�0.11, 0.14) 0.34 .739

TC (mmol/L) �2.44 .017 Intervention group (n ¼ 53) 6.27 ± 1.21 5.63 ± 1.07 �0.371 (�0.76, 0.51) 10.29 <.001 Usual care group (n ¼ 49) 6.33 ± 1.27 6.21 ± 1.29 �0.121 (�0.22, 0.26) 1.70 .096

BMI (kg/m2) �2.58 .011 Intervention group (n ¼ 53) 24.57 ± 2.01 23.56 ± 1.85 �0.35 (�1.24, 0.76) 8.42 <.001 Usual care group (n ¼ 49) 24.61 ± 2.52 24.64 ± 2.31 0.03 (�0.25, 0.19) �0.26 .800

Smoking 0.02 .882 Intervention group (n ¼ 53) 13 (24.5) 10 (18.9) 3 (�0.13, 0.08) �1.77 .083 Usual care group (n ¼ 49) 11 (22.5) 10 (20.4) 1 (�0.05, 0.19) �1.00 .322

Self-rating depressiona �2.05 .043 Intervention group (n ¼ 53) 56.02 ± 14.43 51.28 ± 15.16 �4.72 (�5.96, 3.48) 7.64 .001 Usual care group (n ¼ 49) 55.61 ± 13.11 56.88 ± 12.17 1.27 (�0.44, 2.97) �1.49 .143

Note. BMI ¼ body mass index; CI ¼ confidence interval; FPG ¼ fasting plasma glucose; SBP ¼ systolic blood pressure; SD ¼ standard deviation; TC ¼ total cholesterol. a Standardization value: for easy comparison, all scores were converted to standardization value of 0e100. Standardization value ¼ original score*1.25.

Table 3 Within Group and Between Group Effects on HRQoL.

HRQoL Preintervention Postintervention Within group difference Between group difference

Mean ± SD Mean ± SD Mean 95% CI/(%) t p t p

Total scorea 3.36 .001 Intervention group (n ¼ 53) 60.96 ± 10.20 68.21 ± 11.39 7.25 (5.43, 9.07) �8.00 <.001 Usual care group (n ¼ 49) 61.02 ± 9.25 61.41 ± 9.13 0.38 (�0.06, 0.84) �1.72 .092

Physiological function 2.65 .009 Intervention group (n ¼ 53) 21.37 ± 4.34 23.46 ± 2.45 2.10 (1.44, 2.75) �6.45 <.001 Usual care group (n ¼ 49) 22.33 ± 3.53 21.55 ± 3.86 0.22 (�0.13, 0.58) �1.28 .207

Psychological function 2.17 .032 Intervention group (n ¼ 53) 20.56 ± 5.22 22.08 ± 4.26 1.52 (0.97, 2.07) �5.57 <.001 Usual care group (n ¼ 49) 20.55 ± 3.85 20.41 ± 3.43 �0.25 (�0.74, 0.25) �0.99 .329

Social function 4.18 <.001 Intervention group (n ¼ 53) 19.08 ± 4.16 23.01 ± 5.11 3.83 (�2.94, 4.72) �8.65 <.001 Usual care group (n ¼ 49) 19.04 ± 3.21 19.44 ± 4.01 0.41 (�0.34, 1.16) �1.10 .278

Note. CI ¼ confidence interval; HRQoL ¼ health-related quality of life; SD ¼ standard deviation. a Standardization value: For easy to compare, all the scores were converted to standardization value of 0e100 by range transfer. S ¼ (X � MIN)*100/R, where X is for original

score, MIN is for the minimum score of the domain or scale, R is for range of the domain or scale (scoremax � scoremin).

Y.-J. Huang et al. / Asian Nursing Research 11 (2017) 187e193 191

chronic disease [24]. Participants in our study were mildly depressed at baseline, and participants in the intervention group had a significant reduction in their depressive symptoms after the 6-month community-based education and coaching intervention. The Coronary Heart Improvement Project found that a community- based primary prevention intervention lowered depressive symp- toms [15], and Rost et al [25] report similar findings in a 6-month community-based intervention in which participants were taught how to adjust negative emotions through increased physical activity.

Individuals at risk for chronic disease generally have a lower HRQoL than healthy populations [26]. The results of this present study illustrate that a 6-month nurse-led community-based inter- vention can improve HRQoL for individuals with a high 10-year CHD risk. Moreover, improvements in HRQoL were seen across all three domains of function: physiologic, psychologic, and social. Eaglehouse [27] reported similarity results with a 12-month community-based intervention in individuals with CVD, predia- betes, and metabolic syndrome.

With a broad scope of health service needs and limited financial government supports, the delivery of CHS has progressed more slowly in less developed areas of China compared with developed countries [28]. This is not unlike the progress reported in other high-risk racially and ethnically diverse populations, such as indigenous populations in the United States [29]. An intervention consisting of group education and individualized coaching sessions delivered in a community setting suggests this may be an effective strategy to deliver chronic disease education. Group education has effectively been used to enhance awareness and to promote healthy lifestyle behaviors to lower disease-related risk factors and to improve self-management capabilities [22].

Unfortunately, the translation of group education interventions into everyday practice has been difficult because of varying health statuses and preferences of individuals living in the community [30]. Group education alone does not produce sustainable behavior change required for chronic disease prevention and management. Coaching strategies have successfully been used to translate health promotion strategies into practice [30], and the integration of a group education intervention with coaching intervention may be a feasible and cost-effective primary intervention for individual with a high CHD risk. A systematic review by Kivel€a reported coaching to be a rapidly emerging strategy to help individuals manage CHD risk factors and enhance wellbeing. Coaching resulted in statistically significant improvements in physiological, behavioral, psychologi- cal, and social outcomes [16].

Potential study limitation

There were several limitations in this study. First, we used a quasi experimental study design and allocated participants to the intervention or usual care group by the community in which they lived. This design was chosen to respect that the normal social activities of people living in the same community might lead to treatment contamination. There were no significant baseline dif- ferences, so any group differences at 6 months were assumed to be a result of the intervention. Second, we used self-report question- naires to measure changes in depression, and existing literature suggests that self-report measures might lead to an overestimation of results. Future trials should consider more objective assessment methods, such as evaluating depression by registered psycholo- gists. Third, the sample size was relatively small, and participants were recruited primarily from urban communities. Considering different levels of CHD prevalence and CHS accessibility between urban and rural areas in China, future trials should include a high 10-year CHD risk population from rural areas.

Conclusion

In summary, a nurse-led community-based education and coaching intervention in a CHD high-risk population had beneficial effects on reducing CHD risk and improving depression and HRQoL outcome. Coaching strategies improve knowledge uptake and should be considered as adjuncts to behavior change interventions. Community-based interventions can be integrated into CHD pri- mary prevention in CHSs.

Conflict of interest

The authors declare no conflict of interest.

Acknowledgments

This study was supported by the Central South University Innovation Foundation for Postgraduate, China (grant number: 2015zzts106) and the Chinese Scholarship Council, China (grant number: 201506370141). The authors also gratefully thank all the study participants for their participation.

References

1. Roth GA, Nguyen G, Forouzanfar MH, Mokdad AH, Naghavi M, Murray CJ. Es- timates of global and regional premature cardiovascular mortality in 2025. Circulation. 2015;132(13):1270e82. https://doi.org/10.1161/CIRCULATIONAHA.115.016021

2. National center for cardiovascular disease, China. Report on cardiovascular diseases in China 2014. Beijing: Encyclopedia of China Publishing House; 2015. p. 11.

3. Gaziano TA, Bitton A, Anand S, Abrahams-Gessel S, Murphy A. Growing epidemic of coronary heart disease in low- and middle-income countries. Curr Probl Cardiol. 2010;35(2):72e115. https://doi.org/10.1016/j.cpcardiol.2009.10.002

4. Kreatsoulas C, Anand SS. The impact of social determinants on cardiovascular disease. Can J Cardiol. 2010;26(Suppl C):6.

5. Yusuf S, Rangarajan S, Teo K, Islam S, Li W, Liu L, et al. Cardiovascular risk and events in 17 low-, middle-, and high-income countries. N. Engl Journal Med. 2014;371(9):818e27. https://doi.org/10.1056/NEJMoa1311890

6. Wu Z, Yao C, Zhao D, Wu G, Wang W, Liu J, et al. Cardiovascular disease risk factor levels and their relations to CVD rates in China - results of Sino-MONICA project. Eur J Cardiovasc Prev Rehabil. 2004;11(4):275e83. https://doi.org/10.1097/01.hjr.0000136566.89429.63

7. Xu T, Li W, Teo K, Wang XY, Liu LS, Yusuf S. Association of psychological risk factors and acute myocardial infarction in China: the INTER-HEART China study. Chin Med J Engl. 2011;124(14):6. https://doi.org/10.3760/cma.j.issn.0366-6999.2011.14.001

8. Wilson PW. Estimation of cardiovascular risk in an individual patient without known cardiovascular disease [Internet] The Netherlands: UpToDate; 2016 [cited 2016 02e01]. Available from: http://www.uptodate.com/contents/ estimation-of-cardiovascular-risk-in-an-individual-patient-without-known- cardiovascular-disease.

9. Li XP, Xi Y, Xu ZX, Wang YQ. Survey of the risk assessment of cardiovascular disease. Adv Clin Med. 2015;05(03):177e82. https://doi.org/10.12677/acm.2015.53028. Chinese.

10. Kavousi M, Leening MJ, Nanchen D, Greenland P, Graham IM, Steyerberg EW, et al. Comparison of application of the ACC/AHA guidelines, Adult Treatment Panel III guidelines, and European Society of Cardiology guidelines for car- diovascular disease prevention in a European cohort. JAMA. 2014;311(14): 1416e23. https://doi.org/10.1001/jama.2014.2632

11. Martin SS. Hyperlipidemia: how to optimize risk while waiting for NCEP ATP IV guidelines. Phys Pract. 2012.

12. van Straten AH, Tan EM, Hamad MA, Martens EJ, van Zundert AA. Evaluation of the EuroSCORE risk scoring model for patients undergoing coronary artery bypass graft surgery: a word of caution. Neth Heart J. 2010;18(7e8):5.

13. WHO. Prevention of cardiovascular disease: guidelines for assessment and management of total cardiovascular risk [Internet]. Geneva: World Health Organization; 2007 [cited 2017 March 23]. Available from http://apps.who.int/ iris/bitstream/10665/43685/1/9789241547178_eng.pdf

14. Tillin T, Hughes AD, Whincup P, Mayet J, Sattar N, McKeigue PM, et al. Ethnicity and prediction of cardiovascular disease: performance of QRISK2 and Fra- mingham scores in a U.K. tri-ethnic prospective cohort study (SABREeSouthall And Brent REvisited). Heart. 2014;100(1):60e7. https://doi.org/10.1136/heartjnl-2013-304474

15. Thomas KL, Shah BR, Elliot-Bynum S, Thomas KD, Damon K, Allen LaPointe NM, et al. Check it, change it: a community-based, multifaceted intervention to

Y.-J. Huang et al. / Asian Nursing Research 11 (2017) 187e193192

improve blood pressure control. Circ Cardiovasc Qual Outcomes. 2014;7(6): 828e34. https://doi.org/10.1161/CIRCOUTCOMES.114.001039

16. Merrill RM, Taylor P, Aldana SG. Coronary Health Improvement Project (CHIP) is associated with improved nutrient intake and decreased depres- sion. Nutrition. 2008;24(4):314e21. https://doi.org/10.1016/j.nut.2007.12.011

17. Kivel€a KES, Kyng€as H, K€a€ari€ainen M. The effects of health coaching on adult patients with chronic diseases: a systematic review. Patient Educ Couns. 2014;97(2):10. https://doi.org/10.1016/j.pec.2014.07.026

18. Wang CF, Xu Q. Analysis of the assessment on 1340 individuals with self-rating depression scale. Chin J Nerv Ment Dis. 1986;12(5):2.

19. Zeng Y. Study on cardiovascular risk assessment and comprehensive inter- vention in older adults [dissertation]. Changsha (China): Central South Uni- versity; 2012. p. 84.

20. Law MR, Morris JK, Wald NJ. Use of blood pressure lowering drugs in the prevention of cardiovascular disease: meta-analysis of 147 randomised trials in the context of expectations from prospective epidemiological studies. BMJ. 2009;338:b1665. https://doi.org/10.1136/bmj.b1665

21. Zoellner J, Connell C, Madson MB, Thomson JL, Landry AS, Fontenot Molaison E, et al. HUB city steps: a 6-month lifestyle intervention improves blood pressure among a primarily African-American community. J Acad Nutr Dietetics. 2014;114(4):603e12. https://doi.org/10.1016/j.jand.2013.11.020

22. Kandula NR, Patel Y, Dave S, Seguil P, Kumar S, Baker DW, et al. The South Asian Heart Lifestyle Intervention (SAHELI) study to improve cardiovascular risk factors in a community setting: design and methods. Contemp Clinical Trials. 2013;36(2):479e87. https://doi.org/10.1016/j.cct.2013.09.007

23. Yang GH. Global Adult Tobacco Survey (GATS) China 2010 country report [Internet]. Beijing: World Health Organization; 2010 [cited 2016 August 31].

Available form https://www.who.int/tobacco/surveillance/survey/gats/en_ gats_china_report.pdf?ua=1

24. Michal MWJ, Lackner K, Wild PS, Zwiener I, Blettner M, Münzel T, et al. As- sociation of hypertension with depression in the community: results from the Gutenberg Health Study. J Hypertens. 2013;31(5):893e9. https://doi.org/10.1097/HJH.0b013e32835f5768

25. Rost KNP, Smith J, Werner J, Duan N. Improving depression outcomes in community primary care practice: a randomized trial of the quEST interven- tion. Quality Enhancement by Strategic Teaming. J General Internal Medicine. 2001;16(3):143e9. https://doi.org/10.1111/j.1525-1497.2001.00537.x

26. WHO. Preventing chronic diseases. A vital investment: WHO global report [Internet]. Geneva: World Health Organization; 2005 [cited 2016 July 1]. Available from: http://www.who.int/chp/chronic_disease_report/en/

27. Eaglehouse YL, Schafer GL, Arena VC, Kramer MK, Miller RG, Kriska AM. Impact of a community-based lifestyle intervention program on health-related quality of life. Qual Life Res An Int J Qual Life Aspects Treat Care Rehabil. 2016. https://doi.org/10.1007/s11136-016-1240-7

28. Zhao Y, Cui S, Yang J, Wang W, Guo A, Liu Y, et al. Basic public health services delivered in an urban community: a qualitative study. Public Health. 2011;125(1):37e45. https://doi.org/10.1016/j.puhe.2010.09.003

29. Ton TG, Steinman L, Yip MP, Ly KA, Sin MK, Fitzpatrick AL, et al. Knowledge of cardiovascular health among Chinese, Korean and Vietnamese immigrants to the US. J Immigr Minor Health/Center Minor Public Health. 2011;13(1): 127e39. https://doi.org/10.1007/s10903-010-9340-x

30. Baker R,Camosso-StefinovicJ,Gillies C,ShawEJ,CheaterF,FlottorpS,etal. Tailored interventions to overcome identified barriers to change: effects on professional practice and health care outcomes. Cochrane Database Systematic Reviews. 2010;3:CD005470. https://doi.org/10.1002/14651858.CD005470.pub2

Y.-J. Huang et al. / Asian Nursing Research 11 (2017) 187e193 193