Identifying Latent Classes of Risk Factors for Coronary Artery Disease

Eunsil Ju; JiSun Choi

doi:10.4040/jkan.2017.47.6.817

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Ju and Choi: Identifying Latent Classes of Risk Factors for Coronary Artery Disease

Original Article

J Korean Acad Nurs 2017;47(6):817-827.

Published online: 15 January 2017

DOI: https://doi.org/10.4040/jkan.2017.47.6.817

Identifying Latent Classes of Risk Factors for Coronary Artery Disease

Eunsil Ju¹, JiSun Choi^2,

¹Kyung Hee University Hospital at Gangdong, Seoul

²College of Nursing Science · East-West Nursing Research Institute, Kyung Hee University, Seoul, Korea

Address reprint requests to : Choi, JiSun College of Nursing Science · East-West Nursing Research Institute, Kyung Hee University, 26 Kyunghee-daero, Dongdaemun-gu, Seoul 02447, Korea Tel: +82-2-961-0306 Fax: +82-2-961-9398 E-mail: jchoi14@khu.ac.kr

Received 28 September 2017 Revised 28 November 2017 Accepted 2 December 2017

This is an Open Access article distributed under the terms of the Creative Commons Attribution NoDerivs License. (http://creativecommons.org/licenses/by-nd/4.0) If the original work is properly cited and retained without any modification or reproduction, it can be used and re-distributed in any format and medium.

Abstract

Purpose

This study aimed to identify latent classes based on major modifiable risk factors for coronary artery disease.

Methods

This was a secondary analysis using data from the electronic medical records of 2,022 patients, who were newly diagnosed with coronary artery disease at a university medical center, from January 2010 to December 2015. Data were analyzed using SPSS version 20.0 for descriptive analysis and Mplus version 7.4 for latent class analysis.

Results

Four latent classes of risk factors for coronary artery disease were identified in the final model: ‘smoking-drinking’, ‘high-risk for dyslipidemia’, ‘high-risk for metabolic syndrome’, and ‘high-risk for diabetes and malnutrition’. The likelihood of these latent classes varied significantly based on socio-demographic characteristics, including age, gender, educational level, and occupation.

Conclusion

The results showed significant heterogeneity in the pattern of risk factors for coronary artery disease. These findings provide helpful data to develop intervention strategies for the effective prevention of coronary artery disease. Specific characteristics depending on the subpopulation should be considered during the development of interventions.

Keywords: Coronary artery disease, Dyslipidemia, Metabolic syndrome, Risk factors, Statistical models

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Figure 1.

Class membership probability of latent classes.

Table 1.

General Characteristics of the Sample (N=2,022)

Variable	Category	n (%)
Age (yr)	<50	220 (10.8)
	50~59	532 (26.3)
	60~69	545 (27.0)
	≥70	725 (35.9)
Gender	Men	1,277 (63.2)
	Women	745 (36.8)
Educational level	Elementary school	468 (23.1)
	Middle & high school	944 (46.7)
	College or higher	445 (22.0)
Marital status	Single	128 (6.3)
	Married	1,851 (91.5)
Occupation	Office job	236 (11.7)
	Housewife	412 (20.4)
	General labor job	247 (12.2)
	Service job	158 (7.8)
	None	587 (29.0)
	Other*	208 (10.3)
Family history related	Yes	526 (26.0)
to CAD	No	1,463 (72.4)

^*Other includes soldier, student, & professional technician etc. Family history related to CAD refers to information on family morbidity of particular diseases (hypertension, diabetes mellitus, hyperlipidemia or cardiovascular disease). The sample size varies due to missing data.

CAD=Coronary artery disease.

Table 2.

Descriptive Statistics on Indicator Variables of Coronary Heart Disease Risk Factors of the Sample (N=2,022)

Variable	Category	n (%)
Hypertension	Yes	788 (39.0)
	No	1,234 (61.0)
Diabetes	Yes	575 (28.4)
	No	1,447 (71.6)
Blood glucose	Normal (<100)	174 (8.6)
(mg/dL)	Impaired fasting glucose (100~125)	1,060 (52.4)
	Diabetes (≥126)	788 (39.0)
Dyslipidemia	Yes	371 (18.3)
	No	1,651 (81.7)
Total cholesterol	Desirable (<200)	1,873 (92.6)
(mg/dL)	Borderline risk (200~239)	113 (5.6)
	High risk (≥240)	36 (1.8)
HDL cholesterol	Desirable (≥60)	134 (6.6)
(mg/dL)	Borderline risk (M: 41~59, F: 51~59)	608 (30.1)
	High risk (M: ≤40, F: ≤50)	1,280 (63.3)
LDL cholesterol	Desirable (<100)	1,020 (50.4)
(mg/dL)	Borderline risk (100~159)	886 (43.8)
	High risk (≥160)	116 (5.8)
Smoking	Yes	614 (30.4)
	No	1,408 (69.6)
Drinking	Yes	686 (33.9)
	No	1,336 (66.1)
BMI (kg/m²)	Underweight (<18.5)	78 (3.9)
	Normal weight (18.5~24.9)	1,064 (52.6)
	Overweight/Obesity (≥25)	880 (43.5)
Malnutrition risk	Yes	261 (12.9)
	No	1,761 (87.1)

M=Male; F=Female; HDL=High density lipoprotein; LDL=Low density lipoprotein; BMI=Body mass index.

Table 3.

Criteria for Model Fit by Different Number of Classes

Number of classes	Model Fit Criteria
	AIC	BIC	Adjusted BIC	LMR-LRT (p value)	BLRT (p value)	Entropy
1	28,861.43	28,951.27	28,900.38
2	28,432.70	28,617.88	28,513.04	.012	<.001	0.49
3	28,183.18	28,463.77	28,304.91	.312	<.001	0.57
4	27,961.44	28,337.44	28,124.57	.018	<.001	0.60
5	27,834.42	28,305.81	28,038.94	.064	<.001	0.64

AIC=Akaike information criterion; BIC=Bayesian information criteria; LMR=Lo-mendell-rubin likelihood ratio test; BLRT=Bootstrapped likelihood ratio test.

Table 4.

Differences in General Characteristics and the Incidence of Percutaneous Coronary Intervention (PCI) among Four Latent Classes (N=2,022)

Variables	Categories	Smoking drinking (n=525)	High–risk for dyslipidemia (n=356)	High–risk for metabolic syndrome (n=629)	High–risk for diabetes & malnutrition (n=512)	χ² (p)
Age (yr)	<50	106 (20.2)	48 (13.5)	31 (4.9)	35 (6.8)	249.73 (<.001)
	50~59	204 (38.9)	115 (32.3)	115 (18.3)	98 (19.1)
	60~69	140 (26.7)	83 (23.3)	186 (29.6)	136 (26.6)
	≥70	75 (14.3)	110 (30.9)	297 (47.2)	243 (47.5)
	Mean±SD	57.9±10.5	61.0±11.7	68.1±10.9	68.0±11.5
Gender	Man	487 (92.8)	196 (55.1)	294 (46.7)	300 (58.6)	285.21 (<.001)
	Women	38 (7.2)	160 (44.9)	335 (53.3)	212 (41.4)
Educational	Elementary	71 (14.2)	75 (23.7)	188 (32.9)	134 (28.7)	66.06 (<.001)
level	Middle & High	272 (54.3)	157 (49.5)	285 (49.8)	230 (49.3)
	College or higher	158 (31.5)	85 (26.8)	99 (17.3)	103 (22.1)
Marital status	Single	42 (8.2)	30 (8.5)	34 (5.5)	22 (4.4)	9.51 (.023)
	Married	470 (91.8)	321 (91.5)	582 (94.5)	478 (95.6)
Occupation	Office job	115 (21.9)	50 (14.0)	27 (4.3)	44 (8.6)	307.02 (<.001)
	Housewife	21 (4.0)	92 (25.8)	186 (29.6)	113 (22.1)
	General labor job	103 (19.6)	37 (10.4)	58 (9.2)	49 (9.6)
	Service job	65 (12.4)	26 (7.3)	35 (5.6)	32 (6.2)
	None	109 (20.8)	80 (22.5)	215 (34.2)	183 (35.7)
	Other*	85 (16.2)	41 (11.5)	42 (6.7)	40 (7.8)
Family history	Yes	164 (31.7)	97 (27.6)	177 (28.7)	88 (17.5)	30.20 (<.001)
related to CAD	No	353 (68.3)	255 (72.4)	439 (71.3)	416 (82.5)
PCI	Yes	291 (55.4)	147 (41.3)	326 (51.8)	243 (47.5)	19.12 (<.001)
	No	234 (44.6)	209 (58.7)	303 (48.2)	269 (52.5)

SD=Standard deviation; PCI=Percutaneous coronary intervention; CAD=Coronary artery disease.

^*Other includes soldier, student, & professional technician etc; The sample size varies due to missing data.

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