Frailty and its components and cardiovascular outcomes in older adults: A nationwide epidemiological study

Abstract

Aim

Although frailty is the result of multifactorial vulnerability, such as physical, cognitive, and socio‐psychological factors, the association of multifactor‐defined frailty and its components with cardiovascular disease (CVD) has not been investigated. The goal of this paper is to clarify the association between multifactor‐defined frailty and its components and CVD in older adults.

Methods

Using a nationwide claims database, we included 66 948 participants aged ≥65 years without a history of CVD who were assessed using a simple questionnaire‐based approach covering physical, cognitive, oral, nutritional, and social aspects of frailty. The primary outcome was composite CVD events, including ischemic heart disease, heart failure, and stroke.

Results

During a mean follow‐up period of 280 ± 153 days, 3721 CVD events were observed. Compared with robust individuals, frailty was associated with an increased risk of developing CVD (adjusted hazard ratio [HR] 1.41, 95% confidence interval [CI] 1.31–1.52). This association was consistent across CVD subtypes. All components of comprehensive measures of frailty, such as physical function (HR 2.32, 95% CI 1.85–2.91), nutritional status (HR 1.46, 95% CI 1.10–1.93), oral function (HR 1.18, 95% CI 1.05–1.32), cognitive function (HR 1.44, 95% CI 1.30–1.60), and social aspects (HR 1.39, 95% CI 1.13–1.72), were also associated with an increased risk of developing CVD.

Conclusions

The multifactorial assessment of frailty significantly stratifies CVD risk in Japanese older adults. Moreover, each component of frailty independently contributes to the likelihood of CVD, underscoring the importance of comprehensive frailty evaluations in preventive care for the aging population. Geriatr Gerontol Int 2025; 25: 1239–1246.

The multifactorial assessment of frailty significantly stratifies cardiovascular disease risk in Japanese older adults. Moreover, each component of frailty independently contributes to the likelihood of cardiovascular disease, underscoring the importance of comprehensive frailty evaluations in preventive care for the aging population.

Introduction

Frailty is a state of increased vulnerability and increased susceptibility to various health problems (disease onset, physical dysfunction, and need for care) due to a decline in physical functions, physiological systems, and reserve capacity to respond to external stressors as a result of aging and other factors. Frailty has been reported to be a strong predictor of the development of various diseases, poor surgical outcomes, and death. ¹ , ² , ³ , ⁴ , ⁵ , ⁶ Thus, among older populations, geriatric assessments such as for frailty have been found to help determine appropriate care and treatment. ⁷

Frailty has been reported as a significant risk factor for the development of CVD in many studies, including meta‐analyses. ¹ , ² , ⁸ , ⁹ , ¹⁰ Among older adults without a prior history of CVD, frailty as defined by the Fried criteria, the gold standard for frailty assessment, has been associated with a higher incidence of various cardiovascular outcomes. ¹ In addition, frailty as defined using the lower‐extremity performance test has been shown to be a strong risk factor for developing subsequent heart failure. ² Most reports examining the relationship between frailty and CVD, such as those mentioned above, have utilized assessment tools that emphasize physical aspects, such as the Fried criteria. However, in recent years, frailty has increasingly been recognized as having a multifactorial etiology. In addition to the physical dimension, traditionally considered central, social and cognitive factors, as well as nutritional status, have been identified as key components of frailty. ¹¹ In addition, the Fried criteria involve objective measures such as gait speed. ¹² However, they require specialized equipment and testing, which increases the time and resources needed, making them less convenient for widespread use. Given the aging population in modern society, a frailty assessment tool that can be accurately scored through a simple questionnaire, requiring only minimal space and training, would be especially practical.

The health assessment questionnaire used in the national screening program in Japan consists of 12 questions addressing various aspects of frailty, including not only physical function but also nutritional status, oral function, cognitive function, and social aspects, referred to as the 12 frailty‐related items. ¹³ It has been reported that the 12 frailty‐related items can predict frailty, as defined by the Japanese version of the Cardiovascular Health Study (J‐CHS)—the Japanese version of the Fried criteria—with high accuracy. ¹⁴ Therefore, this study aimed to investigate the association between multifactor‐defined frailty as identified using the 12 frailty‐related items and each frailty component with the development of CVD using a large‐scale health checkup and administrative claims dataset.

Methods

Study population

This was a retrospective cohort study using data from the DeSC database (DeSC Healthcare Inc., Tokyo, Japan) between April 2014 and November 2022. ¹⁵ The DeSC database is a large administrative health claims database derived from three types of health insurers as follows: (i) health insurance for employees working for relatively large companies in Japan; (ii) the National Health Insurance for individual proprietors and non‐employees aged <75 years; and (iii) the Advanced Medical Service System for older individuals aged 65–74 years with certain disabilities and those aged ≥75 years. Anonymized individual‐level administrative data from both outpatient and inpatient settings were recorded in the database. Diagnoses were recorded using the International Classification of Diseases, 10th Revision (ICD‐10) coding. This database also includes annual health checkup data on registered individuals, such as blood pressure, body mass index (BMI), and laboratory data. Additionally, older individuals aged ≥75 years in the Advanced Medical Service System complete a unique 15‐item brief questionnaire, including 12 questions addressing various aspects of frailty.

Because this study aimed to examine the association between frailty identified using 12 frailty‐related items and the development of CVD, we extracted data on 102 164 individuals aged ≥65 years in the Advanced Medical Service System who underwent annual health checkups for more than 6 months after insurance enrollment (a 6‐month look‐back period). From this population, we excluded those with a prior history of CVD (n = 35 167), those with a prior history of renal replacement therapy (n = 25), and those with missing data on cigarette smoking (n = 24). Our final analytic sample included 66 948 participants (Fig. 1).

Figure 1.

Flowchart.

Ethics

The University of Tokyo Ethics Committee approved the study (approval number: 2021010NI). This study was conducted in accordance with the Declaration of Helsinki. Because all data recorded in the DeSC database were anonymized and de‐identified, the requirement for individuals' informed consent was waived.

Measurements and definitions

We defined frailty status using 12 questions addressing various aspects of frailty (the 12 frailty‐related items) (Table S1). ¹³ , ¹⁴ , ¹⁶ The questionnaire consisted of five frailty‐related components: physical function, nutritional status, oral function, cognitive function, and social aspects. ¹³ The 12 questions were scored such that higher scores indicated a greater likelihood of frailty. The 12 frailty‐related items were developed as a simplified assessment tool intended for administrative use, such as in health checkups for old‐old adults (aged ≥75 years). While the questionnaire includes several items similar to those in the widely used and validated Kihon Checklist, ¹⁷ it is more concise than the Kihon Checklist and does not include items assessing instrumental activities of daily living or depressive symptoms. The Septuagenarians, Octogenarians, Nonagenarians Investigation with Centenarians (SONIC) study has shown that 12 questions demonstrated acceptable discriminative power for identifying frailty. ¹⁴ Using the J‐CHS criteria, a cutoff score of 4 was determined, with sensitivity and specificity for frailty of 55.9% and 85.8%, respectively. ¹⁴

We defined hypertension as systolic blood pressure ≥140 mmHg, diastolic blood pressure ≥90 mmHg, or use of blood pressure‐lowering medications. We classified individuals as having diabetes mellitus based on a hemoglobin A1c level of ≥6.5% or the use of glucose‐lowering medications. Dyslipidemia was defined as a low‐density lipoprotein cholesterol level of ≥140 mg/dL, high‐density lipoprotein cholesterol level of <40 mg/dL, triglyceride level of ≥150 mg/dL, or the use of lipid‐lowering medications. Information on cigarette smoking (current/non‐current) was obtained through a self‐reported questionnaire.

Outcomes

The primary outcome for our analysis was a composite CVD endpoint that included ischemic heart disease (ICD‐10 codes: I200, I201, I208, I209, I210–I214 and I219), heart failure (ICD‐10 codes: I500, I501, I509, and I110), and stroke (ICD‐10 codes: I630, I631–I636, I638, I639, I600–I611, I613–I616, I619, I629, and G459). We analyzed ischemic heart disease, heart failure, stroke, and all‐cause death as secondary endpoints. Data for each endpoint were collected between April 2014 and November 2022. Study participants were followed up from the initial health check‐up (i.e., the 12 frailty‐related items assessment) until the endpoints, namely death, discontinuation of insurance coverage, or study end date (November 2022).

Statistical analysis

We categorized study participants into three groups based on the score for the 12 frailty‐related items: 0–3, 4–7, and 8–12 points. Continuous variables are reported as medians (Q1–Q3); categorical variables are reported as numbers (percentages). In the comparison of subgroups, the Kruskal–Wallis test or chi‐square test was used. Cox proportional hazards regression analysis was performed to evaluate the association between the 12 frailty‐related items category and outcomes of interest. Model 1 represented the crude association. Model 2 was adjusted for age and sex. Model 3 was adjusted for age, sex, BMI, hypertension, diabetes mellitus, dyslipidemia, and cigarette smoking. Subsequently, we used Cox proportional hazards regression analysis to examine the association of each component of the 12 frailty‐related items, including physical function, nutritional status, oral function, cognitive function, and social aspects, with the risk of composite CVD outcome.

Four sensitivity analyses were performed. First, we analyzed the association of each component of the 12 frailty‐related items with the risk of ischemic heart disease, heart failure, stroke, and all‐cause death. Second, we examined the association between the 12 frailty‐related items category and CVD outcomes using Fine and Gray competing risk regression to estimate the sub‐distribution hazard, while accounting for the competing risk of mortality. Third, we also examined the association between each component of the 12 frailty‐related items and CVD outcomes using Fine and Gray competing risk regression. Fourth, with the exception of ICD‐10 codes I201 for coronary vasospastic angina and I208 for coronary microvascular angina, we redefined the outcomes of CVD and ischemic heart disease and examined the association between frailty and CVD and ischemic heart disease using Cox proportional hazards regression analysis.

All analyses were conducted using STATA v18 (StataCorp LLC, College Station, TX, USA) with a two‐tailed P‐value of 0.05.

Results

Background characteristics

Table 1 shows the background characteristics. Overall, the median age was 78 (interquartile range: 76–81) years, and 28 786 (43.0%) were male. We classified participants into three groups based on their scores on the 12 frailty‐related items: robust individuals (n = 52 943), frailty (n = 13 442), and severe frailty (n = 563). Participants with higher scores on the 12 frailty‐related items were more likely to be older, have a lower BMI, have a lower prevalence of dyslipidemia, and have a higher percentage of smoking.

Table 1.

Basic characteristics

	The 12 frailty‐related items category
	Overall (n = 66 948)	0–3 (n = 52 943)	4–7 (n = 13 442)	8–12 (n = 563)	P‐value
Age (years)	78 (76–81)	77 (76–80)	79 (76–83)	82 (77–86)	<0.001
Men, n (%)	28 786 (43.0)	23 212 (43.8)	5335 (39.7)	239 (42.5)	<0.001
BMI (kg/m2)	22.7 (20.6–24.8)	22.7 (20.7–24.7)	22.7 (20.4–25.0)	21.8 (19.2–24.5)	<0.001
SBP (mmHg)	134 (124–146)	134 (124–146)	134 (124–146)	133 (121–146)	0.003
DBP (mmHg)	74 (67–80)	74 (68–81)	73 (66–80)	73 (65–81)	<0.001
Hypertension, n (%)	45 341 (67.7)	35 662 (67.4)	9298 (69.2)	381 (67.7)	<0.001
Diabetes mellitus, n (%)	10 309 (15.4)	8012 (15.1)	2209 (16.4)	88 (15.6)	<0.001
Dyslipidemia, n (%)	42 143 (62.9)	33 482 (63.2)	8341 (62.1)	320 (56.8)	<0.001
Cigarette smoking, n (%)	4323 (6.5)	3179 (6.0)	1073 (8.0)	71 (12.6)	<0.001
Laboratory data
HbA1c (%)	5.7 (5.5–6.0)	5.7 (5.5–6.0)	5.7 (5.5–6.0)	5.6 (5.4–6.0)	<0.001
LDL‐C (mg/dL)	119 (100–139)	119 (100–139)	117 (98–138)	116 (94–138)	<0.001
HDL‐C (mg/dL)	62 (51–73)	62 (52–74)	60 (50–72)	59 (48–72)	<0.001
Triglycerides (mg/dL)	99 (73–138)	99 (73–138)	100 (73–140)	95 (71–137)	0.025
The 12 frailty‐related items score
0	11 763 (17.6)	11 763 (22.2)	0 (0.0)	0 (0.0)	<0.001
1	15 505 (23.2)	15 505 (29.3)	0 (0.0)	0 (0.0)
2	14 774 (22.1)	14 774 (27.9)	0 (0.0)	0 (0.0)
3	10 901 (16.3)	10 901 (20.6)	0 (0.0)	0 (0.0)
4	6802 (10.2)	0 (0.0)	6802 (50.6)	0 (0.0)
5	3847 (5.7)	0 (0.0)	3847 (28.6)	0 (0.0)
6	1908 (2.8)	0 (0.0)	1908 (14.2)	0 (0.0)
7	885 (1.3)	0 (0.0)	885 (6.6)	0 (0.0)
8	373 (0.6)	0 (0.0)	0 (0.0)	373 (66.3)
9	135 (0.2)	0 (0.0)	0 (0.0)	135 (24.0)
10	43 (0.1)	0 (0.0)	0 (0.0)	43 (7.6)
11	11 (0.0)	0 (0.0)	0 (0.0)	11 (2.0)
12	1 (0.0)	0 (0.0)	0 (0.0)	1 (0.2)

Data are expressed as median (interquartile range) or number (percentage). P‐values were calculated using the Kruskal‐Wallis test for continuous variables and χ ² tests for categorical variables.

Abbreviations: BMI, body mass index; DBP, diastolic blood pressure; HDL‐C, high‐density lipoprotein cholesterol; LDL‐C, low‐density lipoprotein cholesterol; SBP, systolic blood pressure.

Association of the 12 frailty‐related items category with the risk for CVD

During a mean follow‐up period of 280 ± 153 days, 3721 (5.6%) CVD events were observed. The incidence of CVD per 10 000 person‐years was 674.2 (649.0–700.3) in robust individuals, 1031.5 (969.6–1097.2) in frailty, and 1806.9 (1427.2–2287.8) in severe frailty (Table 2). After multivariate adjustment (Model 3), the hazard ratio [HR] (95% confidence interval [CI]) for developing CVD was 1.41 (1.31–1.52) for frailty and 2.28 (1.79–2.90) for severe frailty compared with robust individuals (Table 2).

Table 2.

Association of the 12 frailty‐related items category with the risk for all‐cause death and cardiovascular disease

	0–3 (n = 52 943)	4–7 (n = 13 442)	8–12 (n = 563)
Composite CVD endpoint
Number of events	2647	1005	69
Incidence (per 10 000 person‐years)	674.2 (649.0–700.3)	1031.5 (969.6–1097.2)	1806.9 (1427.2–2287.8)
Model 1 (Unadjusted)	1 [Reference]	1.53 (1.42–1.64)	2.67 (2.10–3.39)
Model 2	1 [Reference]	1.41 (1.31–1.52)	2.22 (1.75–2.83)
Model 3	1 [Reference]	1.41 (1.31–1.52)	2.28 (1.79–2.90)
Ischemic heart disease
Number of events	692	231	18
Incidence (per 10 000 person‐years)	171.6 (159.3–184.9)	228.3 (200.6–259.7)	443.8 (279.6–704.4)
Model 1 (unadjusted)	1 [Reference]	1.33 (1.14–1.54)	2.57 (1.61–4.11)
Model 2	1 [Reference]	1.30 (1.12–1.52)	2.42 (1.51–3.87)
Model 3	1 [Reference]	1.29 (1.11–1.51)	2.48 (1.54–3.97)
Heart failure
Number of events	1525	620	37
Incidence (per 10 000 person‐years)	382.2 (363.4–401.8)	622.6 (575.4–673.5)	928.0 (672.4–1280.9)
Model 1 (unadjusted)	1 [Reference]	1.63 (1.48–1.79)	2.42 (1.75–3.35)
Model 2	1 [Reference]	1.42 (1.29–1.57)	1.81 (1.30–2.52)
Model 3	1 [Reference]	1.42 (1.29–1.56)	1.83 (1.32–2.55)
Stroke
Number of events	812	289	24
Incidence (per 10 000 person‐years)	201.9 (188.4–216.2)	286.3 (255.1–321.3)	597.1 (400.2–890.8)
Model 1 (unadjusted)	1 [Reference]	1.42 (1.24–1.62)	2.97 (1.98–4.45)
Model 2	1 [Reference]	1.38 (1.21–1.59)	2.78 (1.85–4.19)
Model 3	1 [Reference]	1.39 (1.21–1.59)	2.85 (1.89–4.30)
All‐cause death
Number of events	245	179	25
Incidence (per 10 000 person‐years)	60.2 (53.1–68.3)	174.8 (150.9–202.3)	603.4 (407.7–893.0)
Model 1 (Unadjusted)	1 [Reference]	2.93 (2.42–3.55)	10.41 (6.89–15.71)
Model 2	1 [Reference]	2.24 (1.83–2.74)	5.77 (3.78–8.82)
Model 3	1 [Reference]	2.17 (1.77–2.65)	4.91 (3.20–7.52)

Model 1 is unadjusted. Model 2 includes adjustment for age and sex. Model 3 includes adjustment for age, sex, body mass index, hypertension, diabetes mellitus, dyslipidemia, and cigarette smoking. The incidence rate was per 10 000 person‐years.

CVD, cardiovascular disease.

Association of the 12 frailty‐related items category with the risk for CVD subtypes and all‐cause death

During the follow‐up period, 941 ischemic heart disease, 2182 heart failure, 1125 stroke, and 449 all‐cause deaths were observed. Table 2 shows the association between frailty and CVD subtypes, including ischemic heart disease, heart failure, and stroke, and all‐cause death. The HR (95% CI) for developing ischemic heart disease was 1.29 (1.11–1.51) for frailty and 2.48 (1.54–3.97) for severe frailty. The HR (95% CI) for developing heart failure was 1.42 (1.29–1.56) for frailty and 1.83 (1.32–2.55) for severe frailty. The HR (95% CI) for developing stroke was 1.39 (1.21–1.59) for frailty and 2.85 (1.89–4.30) for severe frailty. The HR (95% CI) for all‐cause death was 2.17 (1.77–2.65) for frailty and 4.91 (3.20–7.52) for severe frailty.

Association of components of the 12 frailty‐related items, such as physical function, nutritional status, oral function, cognitive function, and social aspects, with the risk for CVD and all‐cause death

Figure 2 shows the association between each component of the 12 frailty‐related items and CVD outcomes. The 12 frailty‐related items were categorized into physical function, nutritional status, oral function, cognitive function, and social aspects. The risk of CVD increased with an increasing number of physical function problems. Compared with ideal physical function (none of the physical function problems), the adjusted HR (95%) for developing CVD was 1.31 (1.20–1.43) for one physical function problem, 1.51 (1.38–1.66) for two problems, 1.82 (1.61–2.05) for three problems, and 2.32 (1.85–2.91) for four problems. This association was also observed for nutritional status, oral function, cognitive function, and social aspect, with the risk of CVD increasing with an increasing number of problems in each of these functions.

Figure 2.

Association of the components of the 12 frailty‐related items with the risk for cardiovascular disease. Model 1 is unadjusted. Model 2 includes adjustment for age and sex. Model 3 includes adjustment for age, sex, body mass index, hypertension, diabetes mellitus, dyslipidemia, and cigarette smoking. The incidence rate was per 10 000 person‐years. CVD, cardiovascular disease.

Sensitivity analysis

We performed four sensitivity analyses. First, the association between each component of the 12 frailty‐related items (i.e., physical function and nutritional status, oral function, cognitive function, and social aspects) and CVD subtypes (i.e., ischemic heart disease, heart failure, and stroke) and all‐cause death is consistent, with the risk of CVD subtypes and all‐cause death increasing with an increasing number of problems in each of these functions (Fig. S1). Second, the association between the 12 frailty‐related items category and the development of CVD did not change even when competing risks of death were taken into account (Table S2). Third, the association between each of the components of the 12 frailty‐related items and the development of CVD did not change even when competing risks of death were taken into account (Fig. S2). Fourth, even when we removed the ICD‐10 codes I201 and I208, which indicate coronary vasospastic angina and coronary microvascular angina, respectively, from the definition of CVD and ischemic heart disease as outcomes, the association between frailty and CVD and ischemic heart disease remained consistent (Table S3).

Discussion

In the present study, we examined the association between frailty as defined by the 12 frailty‐related items—a comprehensive measure that includes physical, oral, and cognitive function, as well as social and nutritional status—and the development of CVD in 66 948 older adults using a nationwide health check‐up and insurance claims database. After adjustment for traditional CVD risk factors, frailty was associated with an increased risk of CVD. This association was consistent across CVD subtypes, including ischemic heart disease, heart failure, and stroke. Moreover, each component of frailty—physical function, nutritional status, oral function, cognitive function, and social aspects—was also associated with an increased risk of developing CVD. To our knowledge, this is the first study to clarify the association between frailty, as defined by a comprehensive frailty assessment tool, and CVD.

The results of this study showing that frailty is associated with the development of CVD in older adults are consistent with the results of previous studies. In a prospective cohort study of 3259 older adults without a history of CHD or stroke, frailty as defined by the Fried criteria was associated with major adverse cardiovascular outcomes (HR 1.77, 95% CI 1.53–2.06), acute myocardial infarction (HR 1.95, 95% CI 1.31–2.90), stroke (HR 1.71, 95% CI 1.34–2.17), peripheral vascular disease (HR 1.80, 95% CI 1.44–2.27), and coronary artery disease (HR 1.35, 95% CI 1.11–1.65). ¹ In a study using the Health ABC Study of 2825 older adults, frailty as defined by physical performance was associated with a higher risk of developing heart failure (HR 1.36, 95% CI 1.08–1.71 and HR 1.88, 95% CI 1.02–3.47, for moderate and severe frailty, respectively). ² However, the result of the present study differs from previous research in several aspects. Our study found that frailty, as defined by a multifactorial frailty assessment tool, was consistently associated with the development of CVD across various subtypes, including ischemic heart disease, heart failure, and stroke. Additionally, we identified that each component of frailty was also independently associated with the development of CVD.

In our study, frailty was assessed using a questionnaire‐based tool. In general, objective assessments are considered more accurate than questionnaire‐based assessments. Therefore, an important issue is the extent to which questionnaire‐based frailty assessments align with objective measures. Previous studies have reported that frailty assessed by questionnaire can reliably predict frailty identified by objective measures, such as the Fried criteria. In a validation study of the 12 frailty‐related items used in our study, as defined by the J‐CHS, the area under the receiver operator characteristic (ROC) curve for predicting frailty was 0.79. ¹⁴

There are several possible mechanisms underlying the association between frailty and the subsequent development of CVD. First, each component of frailty is a known risk factor for CVD. For example, physical functions such as gait speed and skeletal muscle strength are strong risk factors for CVD. ¹⁸ , ¹⁹ , ²⁰ , ²¹ Second, frailty may reflect chronic low‐grade inflammation, which is a recognized risk factor for CVD. Frail older adults are also more likely to experience autonomic nervous dysfunction, ²² which increases the risk of cardiovascular events. ²³ , ²⁴ Third, frailty is often associated with multiple comorbidities that are risk factors for CVD. Hypertension and diabetes are typical examples. ²⁵ , ²⁶ , ²⁷ , ²⁸ However, in our study, frailty was a strong risk factor for CVD even after adjusting for those comorbidities, suggesting the potential impact of frailty for the pathogenesis of CVD. Fourth, physical frailty is closely linked to skeletal muscle function, which has been reported to show cardioprotective effects in previous studies. ²⁹ , ³⁰ The typical example concerns myonectin, which is secreted by skeletal muscle and suppresses inflammation and cardiomyocyte apoptosis. ³⁰ We have previously reported that greater skeletal muscle strength is associated with a lower risk of developing heart failure. ³¹ Further research into the cardioprotective role of skeletal muscle may help clarify whether frailty contributes to CVD independently of traditional risk factors.

The results of this study have several clinical implications. Frailty is considered a reversible condition: with early detection and appropriate intervention, it is not only preventable but also treatable. ³² , ³³ The Sarcopenia and Physical fRailty IN older people: multi‐componenT Treatment strategies (SPRINTT) project, a multicenter randomized controlled trial conducted in 11 European countries, examined whether a multicomponent intervention—combining physical activities such as aerobic, strength, flexibility, and balance exercises, along with technological support and nutritional counseling—could prevent mobility impairment in 1519 frail, community‐dwelling older adults. ³⁴ The result showed that the multicomponent intervention reduced the incidence of mobility disability in older adults with frailty. ³⁴ A systematic review and network meta‐analysis of 69 randomized controlled trials reported that various exercise interventions, including aerobic exercise and resistance training, are effective in reducing frailty. ³⁵ Because interventions aimed at improving frailty also reduce the risk of developing CVD, ⁸ , ³⁵ , ³⁶ it is crucial to verify whether addressing specific frailty components can lower the risk of CVD. Our study used a questionnaire‐based frailty assessment tool, which is simple and does not require specialized equipment or skills, making it particularly suitable for clinical settings with an increasing older population. Notably, frailty remained a significant risk factor for CVD even after adjusting for traditional modifiable risk factors, supporting previous findings. Therefore, our results highlight the importance of incorporating geriatric assessment alongside traditional risk factors, such as hypertension and diabetes, for the prevention of CVD.

Our findings emphasize the important role of frailty in the occurrence of cardiovascular events. However, our findings do not imply that conventional cardiovascular risk factors such as diabetes, hypertension, and dyslipidemia should be uniformly and aggressively managed in all frail individuals. Given that frailty reduces tolerance to treatment and increases the risk of adverse events due to polypharmacy, management strategies may need to be carefully tailored to the individual patient, with a strong emphasis on balancing risks and benefits. Future studies that evaluate not only cardiovascular outcomes, but also quality of life, will help establish clearer clinical guidelines for managing cardiovascular risk in frail populations.

The present study has several limitations. First, as a retrospective cohort study, it is subject to potential biases, despite various sensitivity analyses. Unmeasured confounders, such as cardiorespiratory fitness and cardiac biomarkers such as high‐sensitivity cardiac troponin and B‐type natriuretic peptide, which are strong predictors of CVD, ³⁷ , ³⁸ could have influenced the observed association between frailty and CVD development. Second, there is a concern about external validity because the present study was conducted exclusively on Japanese individuals. Third, although the accuracy (particularly, specificity) of insurance claims records in Japan has been reported to be high, ³⁹ because CVD outcomes were defined based on the ICD‐10 code, concerns about diagnostic accuracy remain. Although defining outcomes such as hospitalized heart failure is generally preferred, our database does not allow us to reliably distinguish whether a CVD diagnosis occurred during hospitalization. Therefore, we counted all clinically diagnosed CVD events, including those identified in outpatient settings. Fourth, although our study assessed the cognitive and social domains using two questionnaire items each, this may not adequately capture the multidimensional nature of these factors. There is no doubt that the Mini‐Mental State Examination and Makizako's five items are the preferred methods for detailed assessments of cognitive function and social aspects. It should also be noted that, although the questionnaire used in our study has been reported to reflect frailty as defined by the frailty phenotype model with relatively high accuracy, ¹⁴ the frailty phenotype model is generally considered preferable for assessing physical frailty. Fifth, the follow‐up period in our study was relatively short, and it may not be sufficient to fully evaluate the long‐term association between frailty and the incidence of CVD, which requires further investigation. In particular, considering that frailty is potentially reversible, it would be meaningful to verify the effects of improvement in frailty on long‐term CVD risk.

Conclusions

Frailty, as defined by a comprehensive frailty assessment tool that includes various components, was associated with an increased risk of developing CVD in older adults. Each component of frailty, such as physical function, nutritional status, oral function, cognitive function, and social aspects, was independently associated with an increased risk of developing CVD. This study, which utilizes valuable data from Japan—the country with the most rapidly aging population—underscores the importance of assessing comprehensive frailty‐related indicators alongside traditional risk factors to more accurately evaluate the risk of CVD in older adults.

Funding information

This work was supported by grants from the Ministry of Health Labor and Welfare Japan (23AA2003) and the Ministry of Education, Culture, Sports, Science and Technology, Japan (20H03907, 21H03159, and 21K08123). The funding sources had nothing regarding the current study.

Disclosure statement

Research funding and scholarship funds (Hidehiro Kaneko and Katsuhito Fujiu) were provided by Medtronic Japan, Biotronik Japan, SIMPLEX QUANTUM, Boston Scientific Japan, and UT‐Heart Inc. Akira Okada is a member of the Department of Prevention of Diabetes and Lifestyle‐related Diseases, a cooperative program between the University of Tokyo and the Asahi Mutual Life Insurance Company. Hidehiro Kaneko holds shares in PrevMed Co., Ltd. and Japan Preventive Medicine Development Institute Co., Ltd. The other authors have no conflicts of interest to declare.

Author contributions

Conception and design: H. Kaneko, K. Ueno, T. Ko, Y. Suzuki, A. Okada, K. Kamiya, N. Takeda, H. Morita, K. Node, and N. Takeda. Analysis of data: Y. Suzuki, A. Okada, K. Fujiu, and H. Yasunaga. Interpretation of data: H. Kaneko, K. Ueno, K. Kamiya, Y. Suzuki, K. Fujiu, N. Takeda, H. Morita, K. Node, and N. Takeda. Drafting of the manuscript: H. Kaneko, K. Ueno, T. Ko, Y. Suzuki, A. Okada, N. Takeda, H. Morita, and H. Yasunaga. Critical revision for important intellectual content: N. Takeda, H. Morita, K. Node, and N. Takeda. All authors gave final approval and agree to be accountable for all aspects of the work ensuring integrity and accuracy.

Supporting information

Data S1. Supporting Information.

Ueno K, Ko T, Suzuki Y, et al. Frailty and its components and cardiovascular outcomes in older adults: A nationwide epidemiological study. Geriatr. Gerontol. Int. 2025;25:1239–1246. 10.1111/ggi.70139

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.