chd knowledge and risk factors among filipino-americans connected to primary care services

ORIGINAL RESEARCH

CHD knowledge and risk factors among Filipino-Americansconnected to primary care servicesAlona Dalusung-Angosta, PhD, APN, FNP, NP-C (Assistant Professor, Board-Certified Family Nurse Practitioner)

University of Nevada, Las Vegas, School of Nursing, Las Vegas, Nevada

KeywordsCoronary heart disease; risk factors, Asians;

Filipino Americans.

CorrespondenceAlona Dalusung-Angosta, PhD, APN, FNP, NP-C,

University of Nevada, Las Vegas School of

Nursing, 4505 Maryland Parkway, Las Vegas,

NV 89154. Tel: (702) 895–3360 (work) x1218;

Fax: (702) 895–4807 (work); E-mail:

[email protected]

Received: November 2011;

accepted: January 2012

doi: 10.1002/2327-6924.12039

Abstract

Purpose: To examine the baseline knowledge and risk factors of coronaryheart disease (CHD) among Filipino-Americans (FAs), and to identify the pre-dictors of CHD knowledge.Data Sources: A convenience sample of 120 FAs recruited from three pri-mary care clinics in Las Vegas, Nevada between May and July, 2010. Partic-ipants were asked about their demographic data and presence of CHD riskfactors using the Demographics questionnaire. CHD knowledge was examinedusing the Heart Disease Fact questionnaire.Conclusions: FAs connected to primary care services are knowledgeableabout CHD. Predictors of CHD knowledge include: gender and education. CHDrisk factors common to FAs include: hypertension, diabetes mellitus type 2,dyslipidemia, abdominal adiposity, overweight, lack of exercise, and smoking.Implications for Practice: Knowledge on CHD alone may not help preventheart disease among FAs. Behavioral and cultural factors may play a major rolein the development of CHD and CHD risk factors among FAs. NPs and otherhealth care providers serve a vital role on health promotion, disease preven-tion, and management of patients. The use of the Neuman’s systems model canserve as a guide when caring for FAs because of its emphasis in primary andsecondary prevention interventions. Nurse practitioners must provide holisticand culturally sensitive care when managing their FA patients.

Introduction

Coronary heart disease (CHD) is the leading cause ofdeath in the United States. Every 25 seconds, an Ameri-can will have a coronary event related to CHD, and everyminute someone will die from CHD (American Heart As-sociation, 2011). Among those most affected are Filipino-Americans (FAs), whose leading cause of death is CHD(National Vital Statistics Reports, 2009; Ryan et al., 2000).

FAs, who are citizens of the United States (U.S.) bybirth or naturalization (Dela Cruz, McBride, Compas, Cal-izto, & Van Derveer, 2002), are the second largest Asiansubgroup and the fastest growing Asian immigrants in theU.S. (Camarota, 2007; U.S. Census, 2011). According tothe most recent census, California and Hawaii have thelargest number of FAs in the United States and manymove to Nevada. In fact, Nevada has the highest growthof Filipinos between the years of 2000 and 2010 (UnitedStates Census, 2011). However, FAs know little abouttheir CHD risk factors, and it is crucial to address their

cardiac health issues because the number of FAs dyingfrom CHD can add to the overall morbidity and mortal-ity of cardiovascular disease (CVD) in the U.S. and to theglobal burden of heart disease.

Therefore, the purposes of this study were twofold: toexamine the baseline knowledge and risk factors of CHDamong FAs living in Las Vegas, Nevada, and to identifythe predictors of CHD knowledge.

Theoretical framework

Neuman’s systems model

The theoretical framework utilized in this study is theNeuman’s systems model (NSM) because of its wholis-tic focus. CHD is a complex condition that requires com-prehensive and wholistic care. The major concepts of theNSM are stressors and the utilization of the three preven-tions (primary, secondary, and tertiary) as interventions.According to this model, stressors are environmental

503Journal of the American Association of Nurse Practitioners 25 (2013) 503–512 C©2013 The Author(s)C©2013 American Association of Nurse Practitioners

CHD knowledge and risk factors among Filipino-Americans A. Dalusung-Angosta

forces that impact a person’s health. One example is thelack of knowledge about CHD and the presence of CHDrisk factors.

The NSM views a person as a client system surroundedby several concentric circles known as lines of defenses.The client system can be a single person or a group of peo-ple. The lines of defenses surrounding the client systemare used as protection from the environmental stressors.When stressors penetrate the lines of defense, health iscompromised and instability occurs (Figure 1). For exam-ple, lack of CHD knowledge and its risk factors are ma-jor stressors that can penetrate through the FAs’ lines ofdefense. If no interventions are provided, developmentof CHD and its complications or even death from CHDmay occur. Interventions that focus on preventing stres-sors that affect FAs’ state of wellness are crucial in thereduction and treatment of CHD and its risk factors.

As illustrated in Figure 1, the nurse practitioner (NP)approaches the FA patient by way of the preventions asinterventions for the retention, attainment, and mainte-nance of optimal wellness (Neuman & Fawcett, 2002).In the NSM, primary prevention occurs prior to the per-son’s reaction to a stressor. Interventions at this levelare aimed at strengthening the outermost circle line ofdefense called the flexible line of defense (FLD). Ex-amples of primary prevention are education about CHDand CHD risk factors, counseling about health promotion,and disease prevention. Secondary prevention occurs af-ter the stressors penetrate the FLD and the lines of re-sistance (LR), such as the presence of actual CHD riskfactor(s): hypertension (HTN), diabetes mellitus, dyslipi-demia, and obesity. Interventions at this level are focusedon strengthening the normal line of defense (NLD), alsoknown as the client’s usual wellness state (health), or byremoving the stressor (CHD risk factor) to prevent furtherillness or complications from CHD. Examples include be-havioral modifications related to lifestyle changes, phar-macological management of HTN, diabetes mellitus, dys-lipidemia, obesity, and nicotine addiction. Tertiary pre-vention is witnessed when all lines of defenses have beendisrupted by stressors and complications from CHD havebeen developed, such as myocardial infarction (MI). In-terventions at this level are focused on regaining stabilityof the patient. However, the emphasis of this study is noton tertiary, but on primary and secondary prevention asinterventions.

Background and supporting literature

The two main goals of Healthy People 2020 are to in-crease the quality and years of healthy life of all Amer-icans and to eliminate health disparities. Initial strategiesto improve quality of life and to reduce health inequities

of FAs are to: (a) assess and understand their health risks,(b) increase awareness about heart disease, (c) includethem in research, and (d) inspire minority advocates andresearchers to focus on the CV health of FAs. Lack ofdata concerning FAs may limit the assessment of their CVhealth status, may impact their treatment and manage-ment, and affect the ability to plan programs that reduceCHD.

According to Glanz, Rimer, and Lewis (2002), aware-ness of risk in relation to CHD may result in heart dis-ease prevention. Studies show individuals who are notaware of their risk for developing a disease are less likelyto adopt preventive behaviors (King et al., 2002). Giventhe serious impact of this disease, it is important that FAsknow CHD and its risk factors before they can engagein effective health promotion activities, for these indi-viduals will engage in these health-promoting activitieswhen they understand their benefits (Pender, Murdaugh,& Parson, 2006).

The literature indicates FAs are at risk of CHD becausemany of them have HTN (Dela Cruz & Galang, 2008;NHLBI & API Health Forum, 2000; Ryan et al., 2000)and many have diabetes mellitus type 2 (DMT2; Araneta& Barrett-Connor, 2005; Kim, Park, Grandinetti, Hock,& Waslien, 2008; Magno, Araneta, Macera, & Anderson,2008; Ryan et al., 2000). These risk factors are consid-ered major risk factors for CHD by the National Choles-terol Education Program Adult Treatment Panel III (NCEPATP III) and by the Seventh Report of the Joint Na-tional Committee on Prevention, Detection, Evaluation,and Treatment of High Blood Pressure (JNC7). Accord-ing to Grundy et al. (2004), most patients with diabetesare at high risk for a future CV event even in the absenceof established CHD. They further concluded individualswith diabetes have a relatively high 10-year risk for de-veloping CVD, and the onset of CVD in patients with di-abetes carries a poor prognosis at the time of an acutecoronary event and in the postevent period (Grundy etal., 2004). Reports from the JNC7 show that individualswith HTN are associated with two to threefold increaserisk from CV events compare to those without HTN. Nocurrent data are available examining the prevalence ofother CHD risk factors, such as obesity (including centralobesity), dyslipidemia, smoking, and lack of exercise inthe FA population.

Methods

Research design, sample, and settings

This study was based on a descriptive design with aconvenience sample of 120 FAs recruited from three pri-vate primary care clinics in Las Vegas, Nevada. Approval

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A. Dalusung-Angosta CHD knowledge and risk factors among Filipino-Americans

Legend:

FAs = Filipino-Americans FLD = Flexible Line of Defense NLD = Normal Line of Defense LR = Lines of Resistance

Basic Core:FAs

Secondary Prevention Goal: prevent further illness or complications from CHD. -Decrease stressors to strengthen LR,protects Basic Core (FAs).

Examples: Behavioral modification related to lifestyle changes, nonpharmacological & pharmacological treatment for HTN, DMT2, dyslipidemia, obesity, nicotine addiction. Encourage exercise, weight loss, medication compliance, regular follow up with health care provider.

Primary Prevention Goal: decrease stressors and strengthen FLD.

Examples: Education on CHD and its risk factors, counseling about health promotion and disease prevention, increasing awareness on heart disease.

When NLD isdisrupted by stressors, LR is activated.

Stressors

- Knowledge deficit about CHD & its risk factors

- Presence of CHD risk factors

LR is disrupted by actual presence of CHD risk factors (HTN, DMT2, dyslipidemia, obesity, nicotine addiction).

-Reaction to stressorsoccurs.

Figure 1 Application of the NSM: CHD in FAs with emphasis on primary and secondary prevention as interventions.

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from the University of Hawaii at Manoa’s InstitutionalReview Board was secured. Data were collected fromMay through July, 2010. The inclusion criteria for thisstudy were (a) 35–75 years old, (b) able to speak, under-stand, and communicate in English, and (c) able to write.Exclusion criteria were (a) history of MI and (b) thosewith memory and neurological impairments or any otherhealth condition that prohibits participants from talkingor writing.

Data collection procedures

Flyers containing specific information about this re-search were posted in the clinic lobbies and examinationrooms. The primary investigator (PI) visited each clinic ondifferent days of the week to recruit participants. Whilepotential participants waited for their doctor’s appoint-ment, the PI would approach them and ask if they wereinterested in joining the study. The PI discussed the re-search plan and purpose of the study, sought consentfrom the participants, and provided the questionnaires.

Measures

Heart Disease Fact questionnaire

CHD knowledge was measured using the modified ver-sion of the Heart Disease Fact questionnaire (HDFQ). Thistool was designed by Wagner, Lacey, Chyun, and Abbott(2005), and it originally had 25 true or false questionsabout patients’ CHD knowledge. Most of the questionswere related to CHD, and they were easy to read. Accord-ing to the Flesch–Kincaid reading test, the HDFQ tool isequivalent to a U.S. eighth grade reading level (Wagner,Lacey et al., 2005b), which is the average grade readinglevel in the United States (National Center for EducationStatistics, 2007). Additionally, this tool demonstrated agood internal consistency (KR-20 = .77; Wagner, Ab-bott, & Lacey, 2005a; Wagner, Lacey, Abbott, Groot, &Chyun, 2006), which is above the minimum coefficientof .70 suggested by De Vellis (2003). Criterion validity ofthe HDFQ tool was established by Wagner, Lacey et al.(2005a,b) using discriminant function analyses (DFAs).

Because the HDFQ has not been used in FA patientsand in patients without diabetes, minor modificationswere made to the tool for the present study. Out of the25 original questions, 18 questions were retained becausethey pertained directly to the knowledge of CHD and itsrisk factors, seven questions were removed because theywere related to diabetes, and three new questions wereadded. The new questions were related to other CHD riskfactors identified in the NCEP ATP III, such as age, familyhistory, and abdominal obesity. Therefore, the new ver-sion of the HDFQ tool had 21 true or false questions. Ex-

Table 1 Demographic characteristics of FAs (N = 120)

Variable M (SD) Frequency Percent

Age 54.0 (10.04)

Length of stay 18.8 (10.83)

Gender Male 49 40.8

Female 71 59.2

Education College graduate 61 50.8

Some college 25 20.8

Postgraduate 8 6.7

Grade school 4 3.3

High school graduate 19 15.8

Some high school 3 2.5

Employment Employed 94 78.2

Unemployed 16 13.3

Retired 10 8.3

Number of jobs 1 81 86.2

2 14 14.9

3 1 1.1

4 1 1.1

Annual income <$20,000 29 24.2

$20,000–$29,999 15 12.5

$30,000–$39,999 24 20.0

$40,000–$49,999 12 10.0

$50,000–$59,999 13 10.8

$60,000–$69,999 10 8.3

>$70,000 17 14.2

Marital status Divorced 8 6.7

Married 90 74.2

Never married 5 4.2

Separated 11 9.2

Widowed 6 5.0

Residence Own home 65 54.2

Rented home 55 45.7

or apartment

Living with: Children, spouse 52 43.3

Other (relatives) 58 48.3

Other (friends) 4 3.2

Alone 6 5.0

Insurance Medicare, Medicaid 18 15.0

Other (private) 89 74.1

None 13 10.8

amples of questions are provided in Table 2; questionsnumber 2, 3, and 19 are the new questions that wereadded to the original tool for the purposes of this study.In all cases, participants were asked to respond to thesequestions with “true,” “false,” or “I don’t know.” TotalCHD scores were calculated by summing the total num-ber of correct responses, with higher scores indicatingmore knowledge.

Demographics questionnaire

The demographic characteristics of the sample wereobtained from the Demographics form developed by thePI. These are sociodemographic (SD) characteristics (age,

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Table 2 CHD knowledge scores of FAs in percent (N = 120)

Question Truea Falsea I don’t knowa

1. A person always knows when they have CHD 14 66 20

2. If you have a family history of CHD, you are at risk for developing heart disease 72 11 17

3. The older a person is, the greater their risk of having CHD 57 25 18

4. Smoking is a risk factor for CHD 93 2 5

5. A person who stops smoking will lower their risk of developing CHD 75 13 12

6. High blood pressure is a risk factor for developing CHD 85 3 12

7. Keeping blood pressure under control will reduce a person’s risk for developing heart disease 88 5 7

8. High cholesterol is a risk factor for developing CHD 88 3 9

9. If your “good” cholesterol (HDL) is high, you are at risk for heart disease 21 49 30

10. If your “bad” cholesterol (LDL) is high, you are at risk for heart disease 67 5 28

11. Eating fatty foods does not affect blood cholesterol levels 8 84 8

12. Being overweight increases a person’s risk for CHD 84 3 13

13. Regular physical activity will lower a person’s chance of getting heart disease 88 5 7

14. Only exercising at a gym or in an exercise class will lower a person’s chance of developing heart disease 15 73 12

15. Walking and gardening are considered exercise that will help lower a person’s chance of developing heart disease 83 6 11

16. Diabetes is a risk factor for developing CHD 73 2 25

17. High blood sugar makes the heart work harder 73 5 23

18. A person who has diabetes can reduce their risk of developing CHD if they keep their blood sugar levels under control 60 18 22

19. Abdominal obesity (fat belly) is a risk factor for developing CHD 59 13 28

20. Stress may cause an increase in blood sugar, blood pressure, and cholesterol levels 87 4 9

21. Slow deep breaths, counting to 10 before speaking, going for a walk, are examples of stress stoppers 69 8 23

aData shown as frequency (%).

gender, education) and socioeconomic (SE; employmentand income) variables. The presence of CHD risk factorswere also measured using the Demographics form. In thisform, participants were asked to “check all that apply”if they had been diagnosed, or were categorized, withthe following: HTN, DMT1 or DMT2, dyslipidemia, over-weight, obesity, abdominal adiposity, smoking history, orif they did not exercise. These variables were extractedfrom the American Heart Association’s website. The par-ticipants completed the Demographics questionnaire andHDFQ forms in the clinic lobby. As an incentive, a $5.00telephone card was given to each participant who com-pleted both forms.

Data analysis

Data were analyzed using SPSS 17.0 and SAS 9.2.In order to address internal consistency with the mod-ified HDFQ, Cronbach’s alpha was calculated for theinstrument. Further, item-total correlations using apoint-biserial correlation of correct/incorrect responsesand total score on the instrument were calculated. CHDknowledge scores, CHD risk factors, and demographiccharacteristics of FAs were summarized using descrip-tive statistics. The mean scores of CHD knowledge usingthe SD and SE variables as factors were compared us-ing ANOVA. Owing to the small sample sizes in the in-come and education groups, data were recoded prior to

analysis. For income level, data were recoded into sevengroups: 1 = $20,000; 2–6 = $20,000–$29,999 through$60,000–$69,999 in 10,000 increments; 7 = $70,000. Foreducation level, data were also recoded into three groups:1 = grade school graduate/and or some high school; 2 =high school graduate and/or some college; 3 = collegegraduate and/or postgraduate. Where appropriate, corre-lation was also used to examine the relationship betweenCHD knowledge and continuous SD and SE characteristicvariables. The variables that significantly correlated withCHD knowledge and that were found to be significant inthe ANOVA were subsequently used in a general linearmodel in order to investigate which variables were signif-icant predictors of the total CHD knowledge score.

Results

Demographic characteristics of study participants(n = 120)

The mean age of the sample was 54 years (SD = 10.04).There were more women (n = 71) than men (n = 49).The sample was highly educated and many were em-ployed having only one job. Almost half of the samplehad a household annual income <$39,999 (Table 1). Allparticipants (100%) were born in the Philippines, makingthem first-generation FAs (Dela Cruz & Galang, 2008).The average length of stay in the United States was 18years.

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Most participants were married (74.2%) and the restwere separated (9.2%), divorced (6.7%), widowed (5%),or have never been married (4.2%). More than half(54.2%) had their own home and 45.7% were eitherliving in a rented home or in an apartment and 40%were living with their children and spouse. Almost half(48.3%) were living with their relatives and the rest wereeither living with their friends (3.2%) or living alone(5%). Among the 120 participants, 74.1% had privatehealth insurance, 15% were on government assistanceprograms, such as Medicare and Medicaid, and 10.8%had no insurance.

HDFQ analysis

To establish internal consistency for the modified HDFQinstrument, it was first established that each of the ques-tion included on the questionnaire was, in fact, relatedto the total score. All items were significantly (p < .001)related to the total score on the instrument. The modifiedinstrument also demonstrated very high internal consis-tency, with a Cronbach’s alpha of .84. Hence, all items onthe modified questionnaire were retained for the calcula-tion of the total CHD knowledge score used in the otheranalyses.

CHD knowledge scores and CHD risk factors ofparticipants

The mean CHD knowledge scores of the sample was15.8 (SD = 4.26) out of a total of 21 points; this equatesto a correct response rate of approximately 75% (SD =20.27%). Table 2 illustrates the HDFQ scores on each ofthe items asked. Shaded areas indicate the correct answerfor a given question, and hence are the number (%) ofparticipants who answered each question correctly.

Although most participants scored well on the CHDknowledge test based on their mean score, their responsesto the following questions are noteworthy. On question9: If your “good” cholesterol (HDL) is high, you are at risk forheart disease. Only half of the sample answered this ques-tion correctly. Question 18: A person who has diabetes canreduce their risk of developing coronary heart disease if they

keep their blood sugar levels under control. Although 60% ofthe sample answered this question correctly, 40% did notknow that control of diabetes reduced CHD risk. Question19: Abdominal obesity (fat belly) is a risk factor for developingcoronary heart disease. While 59% of the sample answeredthis question correctly, 41% did not know that abdomi-nal obesity was a risk factor of heart disease.

Based on the Demographics questionnaire on CHD riskfactors, the risk factors prevalent in FAs were lack of ex-

Table 3 CHD risk factors prevalent among FAs (N = 120)

Variable Frequency Percent

No exercise 79 65.8

HTN 60 50.0

Dyslipidemia 44 36.7

Abdominal obesity 33 27.5

DMT2 30 25.0

Smoking 12 10.0

ercise, followed by HTN, dyslipidemia, abdominal obesity,DMT2, and smoking. These data are presented in Table 3.

Predictors of CHD knowledge

An ANOVA examining the relationship between CHDknowledge, SD, and SE characteristic variables indicatedthat gender (F = 5.94, p = .016), education (F = 7.95,p = .001), and income level (F = 2.67, p = .018)were significantly related to CHD knowledge individu-ally; hence, these variables were used in a general lin-ear model in order to develop a predictive model for totalCHD knowledge scores using all three variables simulta-neously. However, when they were all added into a singlepredictive model, gender and education remained signif-icant, but income level was not. This is because of theinteraction effect between education and income level(F = 2.64, p = .015). In fact, as education level increases,so does income level (rs = .010, p = .001). Hence, ed-ucation and income level cannot be separated becauseone is significantly related to the other. Either one servesas a surrogate variable for the other. Therefore, the finalmodel is presented using only gender and education levelas illustrated in Table 4.

Discussion

Although this study revealed a higher mean score ofCHD knowledge among participants, many had one ormore CHD risk factors. One possible reason for the highknowledge scores is that the sample was highly educated.Furthermore, participants may have received counselingor formal education about CHD from their healthcareproviders (HCPs). What is concerning, however, is halfof the sample did not know about the impact of diabetescontrol on CHD, that abdominal obesity was a risk factorof heart disease, and the benefits of “good” cholesterol—high density lipoprotein (HDL). These findings indicatethat the level of awareness concerning diabetes, choles-terol, and abdominal obesity are still lacking. According toAlm-Roijer, Fridlund, Stamgo, and Erhardt (2006), indi-viduals who possess knowledge regarding their own CHD

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Table 4 Final regression model predicting total CHD knowledge score

95% Confidence interval

Parameter B SE t Significance Lower bound Upper bound

Intercept 15.871 .671 23.641 .000 14.541 17.200

Gender = female 1.635 .741 2.207 .029 .168 3.101

Education = grade school/ some high school − 4.805 1.573 − 3.055 .003 − 7.920 − 1.690

Education = high school /some college − 2.202 .769 − 2.863 .005 − 3.726 − .679

Note that estimates are not needed for “gender = male” or “education = college/postgraduate” as these are redundant in the model.

risk factors are likely to adhere to their treatment goals,medications, and advice regarding lifestyle changes.

This study also revealed that lack of exercise is a ma-jor problem among FAs. Although the literature reports astrong link between lack of exercise and the developmentof CHD and CHD risk factors (American Heart Associa-tion, 2011), the majority of the FAs did not engage inregular exercise. This finding is consistent with the litera-ture. According to the NHLBI & API Health Forum (2000)reports, barriers to exercise among FAs are work, school,caring for family and children, and money. Other possibleexplanations for lack of exercise might be not knowingthe definition of exercise, transportation issues, weatherchanges, and increasing age. FAs may have a differentdefinition of exercise. They may regard household choresor occupational activities as exercise or they may dismissleisure walking or gardening as a form of exercise. Exer-cise is a subcategory of physical activity and is definedas a “physical activity that is planned, structured, andrepetitive activities and has a final or intermediate objec-tive in the improvement or maintenance of physical fit-ness,” such as walking or gardening (Caspersen, Powell, &Christenson, 1985). Transportation issues have been doc-umented to be a problem for FAs (MAAHS & Universityof Maryland College Park School of Public Health, 2011)regarding exercise. This could be because of financial orother personal reasons. Additionally, many FAs, the el-derly in particular, do not drive. They rely mostly fromtheir family members for transportation. The weatherconditions may contribute to exercise problems amongFAs. The extreme heat and cold temperatures may bea barrier to regular exercise. Exercising during extremetemperatures may lead to fatigability, exhaustion, andeven dehydration. Therefore, individuals will less likelyto exercise during these times. Age could be another bar-rier to exercise. The average age of the sample was 54years old—middle adulthood age. King et al. (2001) re-ported middle-adulthood aged people are the least activegroup when it comes to physical exercises. Furthermore,as the body ages, its metabolic needs decline. If exerciseand diet are not part of a healthy lifestyle, excess weight

begins to accumulate and health problems occur (Leifer& Hartson, 2004).

This study also revealed that many FAs had HTN. Thisis consistent with previous research (Dela Cruz & Galang,2008; Klatsky & Armstrong, 1991; NHLBI & API HealthForum, 2000; Ryan et al., 2000). Two of the major causesof HTN among FAs could be their diet and dietary prac-tices. The Filipino diet is high in salt and high in saturatedfats (Dela Cruz & Galang, 2008, Filipino Food Recipes,2006; NHLBI & API Health Forum, 2000; The GlobalGourmet, 2010). It is customary for Filipinos to add saltand seasonings to their cooking and food. Additionally,many like to eat fried fish, meat, and poultry (Dela Cruz& Galang, 2008; Ryan et al., 2000). It is well documentedthat regular physical activity in the form of exercise pre-vents and even reverses CHD risk factors, including HTN(American Heart Association, 2011; Apullan et al., 2008;Booth, 2000; Freeman, 2009).

This research also showed that dyslipidemia is a com-mon problem among FAs. This is consistent with the re-sults found in Araneta and Barrett-Connor (2004) andthe NHLBI & API Health Forum (2000) research. Thetype of diet, their dietary practices, and lack of exercisecould be the major contributing factors for the develop-ment of dyslipidemia in this population. As outlined pre-viously, the Filipino diet is rich in saturated fats. Addi-tionally, FAs like to get together and eat (called “salo salo”in Filipino language) with their family and friends, part ofthe Filipino tradition. Lack of regular exercise is directlylinked to dyslipidemia. Because many FAs do not engagein regular exercise, it is not uncommon to see dyslipi-demia as one of their health problems. In addition to theaforementioned factors, genetics may also play a majorrole in the development of dyslipidemia among FAs. De-fects in lipid-metabolizing enzymes and abnormal cellularlipid receptors may cause familial dyslipidemia (McCanceet al., 2010).

This study also found that many FAs had DMT2. Thisfinding is in concordance with research previously cited(Araneta & Barrett-Connor, 2004; NHLBI & API HealthForum, 2000). Obesity (including abdominal adiposity),

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type of diet, dietary lifestyle, lack of exercise, and geneticsusceptibility are also responsible for the development ofDMT2 in this population.

It has also been documented that smoking leads toCVD. Previous studies indicate smoking rates among FAswere higher when compared to other ethnic groups(Maxwell, Bernaards, & McCarthy, 2007), which is con-sistent with the findings of this research. Lack of knowl-edge and understanding of tobacco effects on CV healthand the FAs’ belief that smoking alleviates stress, bore-dom, and depression (Maxwell, Garcia, & Berman, 2005)might be the reasons for the high prevalence of smokingin FAs in this study.

In addition, gender was found to be a significant pre-dictor of CHD knowledge. Possible explanations for thiscould be because of research efforts on increasing aware-ness of heart disease in women and through the use ofmass media. Education was also found to be a significantpredictor of CHD knowledge. Most participants scoredwell on the HDFQ. It might be because the sample washighly educated, Wagner et al. (2005a) posited that in-dividuals with higher educational attainment have moreknowledge about heart disease. And, according to Kang,Yang, and Kim (2010), higher education level correlateswith higher cognitive function and better comprehensioncapability.

Relationship of findings to the Neuman systemsmodel

Findings from this study revealed that FAs’ flexible andnormal lines of defenses have been disrupted by the pres-ence of HTN, dyslipidemia, DMT2, abdominal obesity,lack of exercise, and smoking. Further, lack of knowledgeabout CHD and its risk factors causes FAs’ flexible line ofresistance unstable. This study showed many FAs werenot even aware that diabetes control reduces CHD risk.Additionally, they were not aware about the benefits of“good” cholesterol (HDL) and they did not know aboutabdominal obesity and its impact on heart disease. With-out appropriate interventions, FAs’ LR will further dete-riorate, causing symptomatology and even death. Basedon the NSM, interventions at this level are aimed atsecondary prevention. The main focus is on preventingdamage to the central core by strengthening the LR orby removing the stressor(s) to prevent further illness orcomplications from CHD. Examples of interventions thatwill help strengthen the LR include lifestyle modifica-tion, dietary changes, and pharmacological management.Other examples include smoking cessation, weight loss,and medication compliance, regular follow-up with HCP,and education on CHD prevention.

Limitations

This study cannot be generalized to the entire FA popu-lation because the sample was (a) not randomly selected,(b) small (N = 120), (c) drawn from a geographically lim-ited setting (in primary care clinics), and (d) highly edu-cated sample.

Implications for advanced practice nurses

It is well documented that having knowledge alone re-garding CHD does not make an individual less susceptibleto developing heart disease. However, knowledge is animportant first step when making lifestyle changes. Edu-cation targeting the specific CHD risk factors of FAs mayhelp them adhere to their treatment goals and lifestylechanges. FAs are at risk of CHD because of the presence ofmultiple CHD risk factors, major stressors that can causemorbidity and mortality. Because of the complexity ofthis disease, a comprehensive model, such as the NSM,can be used as a guide when caring for the FA patientswith CHD risk factors. In the NSM, primary preventioninterventions can be applied to patients with or withoutactual CHD risk factors. Emphasizing interventions thatfocus on preventing stressors are crucial in the reduc-tion and treatment of CHD and its risk factors. Educationabout healthy lifestyle, including diet and exercise, areexamples of primary prevention interventions that NPscan implement. Thorough assessment including identi-fication of individuals at risk of CHD is also of the ex-amples of primary prevention interventions. With earlycase finding, appropriate and aggressive treatments maybe provided to avoid or delay the development of CHD.Utilization of community-based screening programs, theuse of mass media to promote heart health, and the in-clusion of FAs in CV research are also crucial. These helpraise awareness regarding the overall cardiac health sta-tus among FAs.

In secondary prevention, NPs approach their patientswho have actual cardiac risk factors (HTN, DMT2, dyslipi-demia, nicotine addiction). Furthermore, nonpharmaco-logical and pharmacological treatments, such as behav-ioral modification regarding dietary and lifestyle changes,use of antihypertensive, hypoglycemic, and antilipidemicagents, smoking cessation, and dietary counseling, arehelpful in the management of patients with actual CHDrisk factors. These interventions help prevent the devel-opment of CHD and prevent complications from CHD,such as MI. Lastly, family relationships are important toFAs. NPs and other HCPs should include family mem-bers when educating their FA patients about lifestyle anddietary modifications. Because dietary lifestyle is such ahuge factor in the development of CHD risk, a referral to

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a certified dietitian who understands the Filipino cultureand dietary practices of FAs should be considered.

Caring for FA patients or any other patients who comefrom different ethnic backgrounds is a challenge. Listen-ing and understanding their cultural health beliefs andpractices may help build trust and provide knowledge tocare for them appropriately. NPs and other HCPs shouldbe aware that cultural and health beliefs and practices canimpact patient care and compliance. They should be cul-turally sensitive when caring for their FA patients to beable to provide quality care. If patients feel they are notwell understood, they may not comply with their treat-ment regimen. An HCP who takes time to listen, who isrespectful, and who understands their patients’ culturewill have a positive impact on their patients’ health out-come.

Conclusions

This study provides insight into the CV health of FAs.Based on the literature and findings from this study, FAsare at an increased risk of developing CHD because manyof them have one or more CHD risk factors. NPs andother HCPs serve a vital role on health promotion, dis-ease prevention, and management of patients. The use ofthe NSM may serve as a guide when caring for the FA pa-tients at risk of CHD. This study suggests that knowledgeof CHD alone may not help decrease the high prevalenceof CHD and its risk factors among FAs. Focusing on FAs’behaviors and their understanding about CHD and devel-oping strategies to help change their lifestyle may helpdecrease their CHD risk. For further research, this studyrecommends the following: (a) replicate the present studyusing a larger sample in more than three clinics and fromvarious geographical regions, (b) replicate the study usinga larger sample outside primary care services, (c) comparethe CHD risk factors between the first generation and thesecond generation FAs, (c) examine the impact of dietarylifestyle (acculturation, Westernization of diet) on CHDand its risk factors among FAs, (d) examine the barriersof physical activity among FAs and its impact on CHD,(e) compare the CHD risk factors between FAs and otherethnic groups (i.e., African Americans), (f) examine theimpact of health behaviors and beliefs of FAs on CHD de-velopment, and (g) examine self-efficacy and risk percep-tion of FAs related to CHD.

Acknowledgments

The author would like to thank the following: Dr. ChadCross, for his statistical assistance; Dr. Clementina Ceria-Ulep, Associate Professor at the University of Hawaii atManoa School of Nursing for her guidance throughout

the dissertation journey; Mr. Jeff Kurrus for reviewingthis manuscript; Dr. Benito Calderon, MD, Dr. RomualdoAragon, MD, and Dr. Maria Faylona, MD, for their sup-port with subject recruitment.

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