Introduction
Heart failure (HF) is a public health burden in ageing populations.1 Severe HF is related to higher risks of cognitive impairment2 and worsened functional outcomes.3 Previous studies reported associations between cognitive impairment and poor functional outcomes4,5 and mortality,6,7 specifically after index HF-related hospitalization.8,9 Conversely, functional status is also associated with incident HF, cognitive decline, and mortality in HF.10,11 However, a gap exists in the literature about the relationship between functional status and subsequent risks of cognitive changes in HF.
Cognitive impairment and functional status are both important determinants of outcomes in HF, but accurate assessments of these subjective elements are challenging. Adding on to its complicated nature of evaluation, subtleties in changes of these elements, supposedly impacted by both HF and intrinsic ageing process, are more difficult to capture. Multi-state modelling using repeated measurements may provide opportunities to capture and reflect sensitive and delicate transitions of cognitive impairments in the longitudinal analysis of patients with HF and further elaborate its associations with underlying functional status. This study aimed to (i) describe the cognitive changes in older individuals with International Classification of Diseases-10 (ICD-10) codes for HF and (ii) examine the association between baseline functional status and subsequent cognitive transitions.
Methods
Study design and data source
We conducted a retrospective, longitudinal cohort study using long-term care insurance (LTCI) and medical insurance databases from Nobeoka city, Southwest Japan.12 In 2015, the population of Nobeoka city was estimated at 125 159 persons with 31.2% aged 65 years or older.13 LTCI system assists older adults with various limitations including cognitive impairment and/or functional dependence.
Study subjects
This study included residents 65 years or older with ICD-10 of acute or chronic HF (Codes I50.0, I50.1, I50.9, and I11.0) between October 2015 and December 2017. Individuals with ICD-10 codes given with probable diagnosis were excluded from the analysis. Patients with ICD-10 code for acute HF were considered those with hospital admission for HF. A 24 month follow-up was defined from the baseline where ICD-10 codes for HF were assigned for the first time using residents' medical claims data. We extracted comorbidities within 6 months and cognitive measurements up to 2 years before the ICD-10 codes for HF were assigned. Figure 1 shows the flow diagram of the study subjects. Individuals with a history of stroke (I60–I63), Alzheimer's disease, or dementia (F00–F03 and G30) were excluded. The study was approved by the institutional ethics committee (Authorization Number R20063), and ethical considerations were examined in accordance with the Declaration of Helsinki and Ethical Guidelines for Medical and Health Research Involving Human Subjects.14
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Measurements
Cognitive status
Cognitive status was measured using seven items from the LTCI assessment, validated in a previous study for construct validity and internal consistency.12 These items were communication, understanding daily routine work, remembering one's birthday, short-term memory, remembering one's name, understanding the current season, and understanding the current place. Cognitive score ranges from 0 to 9, and higher scores suggested worsened cognitive status.12 Cognitive status was classified into normal (cognitive score 0), mild (cognitive score 1), moderate (cognitive scores 2–3), and severe (cognitive scores 4–9). Cognitive status was assessed at baseline and 6, 12, 18, and 24 months.
Functional status
Activities of daily living (ADL) status assessed with the Independence of Disabled Elderly Score was used as an indicator of functional measurement.15 This index indicates the level of independence in daily living in older adults with disabilities and is designated by the Ministry of Health, Labour and Welfare of Japan (MHLW). Severity is graded as follows: independent, Rank J, Rank A, Rank B, and Rank C (Supporting Information, Methods). Studied patients were categorized into patients with independent ADL (independent and Rank J) and dependent ADL (Ranks A–C) at baseline.
Other variables
Death and relocation to other cities (lost to follow-up) were also identified using the LTCI database. HF-related comorbidities were defined as follows16: atrial fibrillation (I48), anaemia (D50–D53 and D55–D64), hypertension (I10–I15), hyperlipidaemia (E78), diabetes (E10–E14), chronic obstructive pulmonary disease (COPD) (J43.1 and J44), cardiomyopathy (I42 and I43), ischaemic heart diseases (I20–I25), mood disorders including depression (F30–F39), and renal diseases (E102, E112, I129, N030, N03.2–N03.4, N03.6, N03.7, N03.9–N04.4, N04.6–N05, N18.3–N18.5, N18.9, and N19). Other comorbidities of interest were malignancy (C00–C97 and D00–D09) and musculoskeletal disease (M00–M99).
Statistical analysis
Categorical and continuous variables are shown as percentages and mean values, respectively. Analysis of variance (ANOVA) was used to test differences between categorical variables. χ2 test was used for dichotomous variables.
We used alluvial diagrams to describe the cognitive changes in patients with HF from baseline and 6, 12, 18, and 24 months. Cognitive transitions were categorized into cognitive decline (from normal/mild to moderate/severe cognitive status) and cognitive improvement (from moderate/severe to normal/mild cognitive status). Deceased patients were categorized into death at the subsequent time point. Unavailable observations were imputed with the most recent assessment of functional and cognitive status based on the assumption that the status was unchanged (i.e. carried forward). Patients without any assessments of cognitive or functional status at baseline or at 6 months were assumed to have normal cognitive status and independent ADL. Patients with dependent ADL at 6 months were assumed to be dependent at the baseline.
A generalized estimating equation (GEE) for repeated measurements was used to examine the association between baseline ADL and cognitive decline. Death was treated as missing values in this analysis. Baseline cognition and interaction terms between baseline ADL and time interval were included in the GEE model. The model was adjusted for age, sex, acute HF, atrial fibrillation, anaemia, ischaemic heart disease, mood disorder, renal disease, and musculoskeletal disease at baseline.
A Markov multi-state continuous-time model was used to determine the probabilities of cognitive/mortality transition in relation to baseline ADL. Multi-state models can be used to model the hazards of multiple outcomes such as cognitive impairment (normal/mild to moderate/severe), improvement (moderate/severe to normal/mild), and mortality (death) probabilities while considering baseline and time-varying covariates (Supporting Information, Figure S1).
Finally, we examined the association between baseline ADL and cognitive/mortality transitions using discrete time points. For model improvement, we used the Broyden–Fletcher–Goldfarb–Shanno (BFGS) algorithm as a quasi-Newton optimizer. Adjusted comorbidities were selected based on scientific knowledge in this study area. Using a two-state model (normal/mild and moderate/severe), sensitivity analysis was conducted with patients who survived during the follow-up (a total of 1416 patients, 1138 with independent and 278 with dependent ADL) to compare the estimates for cognitive transitions without the influence of death. Data analyses were conducted in R v4.0.1. A P value of 0.05 was considered statistically significant.
Results
Changes in cognitive state
A total of 1764 patients had ICD-10 codes for HF, of which 685 (39%) were male (Table 1). The mean age was 82.3 ± 7.9 years at baseline. Of these patients at baseline, 1656 (94%) patients had a normal/mild cognitive status and 108 (6%) patients had a moderate/severe cognitive status (Figure 2A). At 6 months, 46 (3%) patients experienced cognitive decline from normal/mild to moderate/severe and 101 (6%) patients died. Over 24 months, 1274 (72%) patients maintained a normal/mild cognitive status and 115 (7%) patients experienced cognitive decline for at least once during the follow-up. Among those with moderate/severe cognitive status at baseline, only 9 (0.5%) patients experienced a cognitive improvement (i.e. improvement from moderate/severe to normal/mild) at any time point during the 24 months.
Table 1 Baseline characteristics of patients with HF stratified by ADL status
| Baseline ADL status | ||||
| Overall ( |
Independent ( |
Dependent ( |
||
| Age, mean (SD) | 82.31 (7.90) | 80.28 (7.26) | 87.67 (6.95) | <0.001 |
| Male, n (%) | 685 (38.8) | 537 (42.0) | 148 (30.5) | <0.001 |
| Acute HF, n (%) | 191 (10.8) | 94 (7.3) | 97 (20.0) | <0.001 |
| Comorbidities, n (%) | ||||
| Atrial fibrillation | 514 (29.1) | 363 (28.4) | 151 (31.1) | 0.281 |
| Anaemia | 395 (22.4) | 219 (17.1) | 176 (36.3) | <0.001 |
| Cardiomyopathy | 118 (6.7) | 89 (7.0) | 29 (6.0) | 0.53 |
| COPD | 76 (4.3) | 52 (4.1) | 24 (4.9) | 0.494 |
| Diabetes | 735 (41.7) | 576 (45.0) | 159 (32.8) | <0.001 |
| Hyperlipidaemia | 916 (51.9) | 717 (56.1) | 199 (41.0) | <0.001 |
| Hypertension | 1436 (81.4) | 1047 (81.9) | 389 (80.2) | 0.466 |
| Malignancy | 396 (22.4) | 314 (24.6) | 82 (16.9) | 0.001 |
| Musculoskeletal disease | 1364 (77.3) | 970 (75.8) | 394 (81.2) | 0.019 |
| Mood disorders | 190 (10.8) | 99 (7.7) | 91 (18.8) | <0.001 |
| Ischaemic heart disease | 561 (31.8) | 393 (30.7) | 168 (34.6) | 0.129 |
| Renal disease | 336 (19.0) | 183 (14.3) | 153 (31.5) | <0.001 |
| Baseline cognition, n (%) | <0.001 | |||
| Normal/mild | 1656 (93.9) | 1275 (99.7) | 381 (78.6) | |
| Moderate/severe | 108 (6.1) | 4 (0.4) | 104 (21.4) | |
| 6 month cognition, n (%) | <0.001 | |||
| Normal/mild | 1513 (85.8) | 1211 (94.7) | 302 (62.3) | |
| Moderate/severe | 130 (7.3) | 11 (0.9) | 119 (24.5) | |
| Cumulative death | 121 (6.9) | 57 (4.5) | 64 (13.2) | |
| 12 month cognition, n (%) | <0.001 | |||
| Normal/mild | 1437 (81.5) | 1179 (92.1) | 258 (53.2) | |
| Moderate/severe | 128 (7.3) | 14 (1.1) | 114 (23.5) | |
| Cumulative death | 199 (11.3) | 86 (6.7) | 113 (23.3) | |
| 18 month cognition, n (%) | <0.001 | |||
| Normal/mild | 1360 (77.1) | 1137 (88.9) | 223 (46) | |
| Moderate/severe | 125 (7.1) | 29 (2.3) | 96 (19.8) | |
| Cumulative death | 279 (15.8) | 113 (8.8) | 166 (34.2) | |
| 24 month cognition, n (%) | <0.001 | |||
| Normal/mild | 1284 (72.8) | 1093 (85.5) | 191 (39.4) | |
| Moderate/severe | 132 (7.5) | 45 (3.5) | 87 (17.9) | |
| Cumulative death | 348 (19.7) | 141 (11.0) | 207 (42.7) |
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At baseline, there were 485 (28%) patients with dependent ADL and 1279 (72%) with independent ADL (Table 1). Patients with dependent ADL were significantly older (88 vs. 80 years), were less males (31% vs. 42%), and were more likely to have HF admission at baseline (i.e. acute HF; 20% vs. 7%). In the independent ADL group, 1275 (99.7%) patients had a normal/mild cognitive status at the baseline (Figure 2B). At 24 months, 1091 (85%) patients with independent ADL maintained a normal/mild cognitive status and 53 (4%) patients experienced cognitive decline for at least once. In patients with dependent ADL, there were 381 (79%) patients with normal/mild cognitive status and 104 (21%) with moderate/severe cognitive status at baseline (Figure 2C). At 24 months, 226 (47%) patients maintained their cognitive status [183 (38%) patients for normal/mild and 43 (9%) patients for moderate/severe] and 77 (16%) patients experienced cognitive decline for at least once. Mortality was greater for patients with dependent ADL at all time points for 24 months compared with those with independent ADL (all P values <0.001).
Estimated probabilities of cognitive decline and death
Table 2 shows the estimated probabilities of cognitive/mortality transition for patients with independent and dependent ADL within 6, 12, and 24 month intervals. At 24 months, patients with dependent ADL and normal/mild cognitive status at baseline would have 47% chance of maintaining their cognitive status while patients with independent ADL and normal/mild cognitive status at baseline would have 86% chance of maintaining their cognitive status. Similarly, patients with dependent ADL and normal/mild cognitive status at baseline have a 14% chance of cognitive decline at 24 months while patients with independent ADL and normal/mild cognitive status at baseline have a 3% chance of cognitive decline. Sensitivity analysis shows a similar pattern at 24 months (dependent ADL: 20% vs. independent ADL: 4%; Supporting Information, Table S1).
Table 2 Estimated probabilities of cognitive transition
| To | ||||||
| Independent ADL | Dependent ADL | |||||
| Normal/mild | Moderate/severe | Death | Normal/mild | Moderate/severe | Death | |
| 6 month PoT from: | ||||||
| Normal/mild | 96 (96, 97) | 1 (1, 1) | 3 (2, 3) | 82 (82, 82) | 7 (6, 9) | 11 (9, 13) |
| Moderate/severe | 3 (1, 12) | 79 (66, 87) | 17 (10, 29) | 3 (3, 3) | 78 (73, 81) | 19 (16, 23) |
| 12 month PoT from: | ||||||
| Normal/mild | 93 (91, 93) | 2 (1, 3) | 6 (5, 7) | 68 (65, 72) | 11 (9, 14) | 21 (18, 24) |
| Moderate/severe | 6 (1, 21) | 63 (42, 76) | 31 (18, 49) | 5 (3, 8) | 60 (54, 67) | 34 (29, 41) |
| 24 month PoT from: | ||||||
| Normal/mild | 86 (84, 88) | 3 (2, 4) | 11 (10, 13) | 47 (42, 52) | 14 (11, 17) | 39 (35, 43) |
| Moderate/severe | 9 (2, 32) | 40 (19, 59) | 51 (32, 70) | 7 (4, 11) | 37 (30, 44) | 56 (49, 64) |
Patients with dependent ADL have higher probability of normal/mild to death transitions without experiencing cognitive impairment within 24 months (Table 3; 39% vs. 11%, respectively). Patients with dependent ADL have modestly higher probability of moderate/severe to death transition compared with those with independent ADL (56% vs. 51%, respectively).
Table 3 Risk of cognitive transitions estimated with multi-state modelling
| From normal/mild to | From moderate/severe to | |||
| Moderate/severe | Death | Normal/mild | Death | |
| Dependent ADL | 5.24 (3.47, 7.90) | 2.21 (1.62, 3.00) | 0.94 (0.20, 4.40) | 1.21 (0.61, 2.40) |
| Age groupa | 1.66 (1.21, 2.30) | 1.60 (1.27, 2.00) | 0.74 (0.29, 1.90) | 0.94 (0.63, 1.40) |
| Male sex | 1.20 (0.82, 1.80) | 1.70 (1.27, 2.20) | 1.30 (0.37, 4.70) | 1.70 (1.01, 2.90) |
| Acute HF (vs. chronic) | 1.51 (0.93, 2.50) | 3.20 (2.35, 4.40) | 0.31 (0.04, 2.60) | 2.14 (1.32, 3.50) |
The risk of cognitive decline
Patients with dependent ADL have a greater risk of cognitive decline compared with those with independent ADL at any time point of follow-up {adjusted relative risk [RR] 23.94 [95% confidence interval (CI) 10.39–55.13]; Supporting Information, Table S2}. Multi-state modelling also showed that dependent ADL at baseline is associated with cognitive decline over 24 months [Table 3; adjusted hazard ratio (HR) 5.24 (95% CI 3.47–7.90)]. Dependent ADL was also associated with a higher risk of transition from normal/mild to death [HR 2.21 (95% CI 1.62–3.00)]. The ADL dependency at baseline was not associated with cognitive improvement (i.e. transitions from moderate/severe to normal/mild) over 24 months [Table 3; adjusted HR 0.94 (95% CI 0.20–4.40)]. Sensitivity analysis yielded similar results for cognitive transitions from normal/mild to moderate/severe for dependent ADL (Supporting Information, Table S3).
Discussion
Using long-term care and medical insurance data of older adults from a suburban city of western Japan, cognitive transitions in patients with HF (those with ICD-10 codes for HF) and its association with functional status were studied over 24 months. More than 70% of patients maintained a normal/mild cognitive status over 24 months; yet a small but notable number of patients experienced cognitive decline at least once during the follow-up. Patients with dependent ADL at baseline were particularly vulnerable to cognitive decline during the follow-up with almost five times higher risk of experiencing cognitive decline at 24 months. ADL dependency was an important determinant of cognitive decline in patients with HF when accounted for serial observations. In aggregate, these findings indicate the strong link between changes in cognitive status and ADL dependency in elderlies with HF and underscore significant lack of effective approach during the disease course.
Recent studies have reported increased prevalence and risks of cognitive status in HF. The prevalence of cognitive dysfunction in HF varies from 39% in community-based cohort in the United States17 to 80% in prospectively studied patients of acute HF,18 depending on the studied population and diagnostic/measurement tools used to define cognitive impairment. Merely 6% of moderate/severe cognitive status found in the present study appears lower compared with the prevalence reported elsewhere. Differences in assessment tools may have largely influenced its prevalence; however, it is important to note that the prevalence of cognitive impairment correlates with the severity of HF in which the patients with acute decompensated HF18 or end-stage HF are more likely to suffer from cognitive impairment.19 It is thus remarkable to find patients requiring special attention to their cognitive status from an inclusive community-based individuals with ICD-10 codes for HF irrespective of their severity.
In addition to its overwhelming prevalence of cognitive impairment in HF, mounting evidence suggests concerning risks of cognitive impairment in HF.4 Additionally, transitions of cognitive status in HF have been extensively studied. Patients with HF progressively experience cognitive decline over the course of disease progression,11,20 incurring accumulating risk of poor outcomes eventually leading to death. Clinical benefits of HF therapies on cognitive impairment remain inconclusive; however, recent studies report a remarkable cognitive improvement associated with sodium–glucose cotransporter 2 inhibitors in HF and type 2 diabetes, which may involve neuroprotective mechanisms and endothelial regulations.21–23 Further details on the mechanisms of clinical benefits are warranted; however, to date, effective treatments are limited for cognitive decline in HF.
The determinants of cognitive impairment in HF and their impact on further deterioration are keys to limiting cognitive decline. Established clinical factors of cognitive impairment in HF include hypertension, atrial fibrillation, and stroke.4,11,17 Previous studies suggest that impaired functional status, for example, advanced New York Heart Association class and reduced 6 min walk distance, is associated with cognitive impairment in HF.11,24–26 As found in this study, ADL dependency retrieved from LTCI data was associated with changes in cognitive status, specifically the deterioration of cognitive function over time. Importantly, there is more than five-fold risk of cognitive decline in patients with dependent ADL compared with independent ADL. Moreover, the patients with moderate/severe cognitive status constantly account for 20–25% of those with dependent ADL over 24 months and even much higher proportion when deaths are omitted from the total number of patients at each time point (Figure 2). Furthermore, as opposed to patients with independent ADL, in those with dependent ADL, cognitive decline was constantly observed over 24 months after given an ICD-10 code. These findings highlight the lack of effective intervention in delaying cognitive deterioration and underscore substantial impact of ADL dependency on changes in cognitive status throughout the course of HF.
In the present study, the use of a multi-state modelling approach has enabled a simultaneous modelling of multiple observations and focuses on transitions between cognitive statuses. This approach included subtle and fluctuating cognitive changes during HF management by utilizing multiple observations that were systematically acquired as part of the medical system. Including death as the final state further allows us to analyse cognitive transitions involving ADL dependency.27,28 Similarly with previous studies reporting functional status as a mortality risk in HF,3 we report that deterioration in functional status in HF bears a substantial risk of cognitive transition from normal/mild to death independent of confounding factors including atrial fibrillation, anaemia, and ischaemic heart disease. Whether the improvements of functional status with proactive intervention mitigate further cognitive declines or even death remains unanswered; however, literature exists reporting promising clinical benefits of using angiotensin-converting enzyme inhibitors, physical therapy, and cardiac resynchronization therapy on cognitive function in HF.29–32
Our study has some limitations. Most importantly, the study result must be interpreted in the context of specific cohort of patients analysed in the present study. Specifically, studied patients consisted of old individuals with ICD-10 codes for HF but had relatively independent ADL compared with those from typical HF cohort studies. Lack of information on potential confounding factors such as HF severity, precise aetiologies of HF, medication use, and other important comorbidities may have also influenced the results. However, it is important to recognize the relevant association between ADL dependency and cognitive transition in the present study, which included more inclusive and diverse population of HF. Much greater extent of associations would be expected in a cohort with definitive diagnosis of HF. Importantly, measurement tools of cognitive and functional status widely vary in this research area. Our group previously proposed a simple and feasible measurement of cognitive status using seven items from LTCI system.12 Similarly, functional status was also collected from the Independence of Disabled Elderly Score. In exchange with technical feasibility in obtaining these measurements, subtle changes in cognitive function may have been discounted, leading to possible underestimation of the results.12 Applying multi-state modelling using repeated measurements has adopted a robust and reliable model of cognitive transition; however, assumptions on stable conditions for unavailable observations may have overestimated the ADL dependency and cognitive function particularly in patients with advanced frailty.
To conclude, functional dependence plays an essential role in cognitive transition in old patients with HF in which preceding functional deterioration associates with further declines in cognitive status over time. Despite recent therapeutic advancements in HF management, cognitive function in individuals with reduced functional status continuously deteriorates with limited improvements, ultimately linked with death. Early interventions to such patients may hold the key to averting the risks of poor outcomes.
Acknowledgements
We thank the municipal staff of Nobeoka city for their unwavering support and assistance throughout this study.
Conflict of interest
None declared.
Funding
This study was supported by the Japan Society for the Promotion of Science Grants-in-Aid for Scientific Research C (Grant/Award Number 20K10548) and Grant-in-Aid for Young Scientists (Grant/Award Number 20K19476).
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Abstract
Aims
Cognitive impairment and functional status are both important determinants of poor outcomes in heart failure (HF). However, little is known about how functional status impacts the changes in cognitive status during the disease course. This study aimed to describe the cognitive transitions in patients with HF and assess the relationship of these transitions to functional status, which was assessed by the dependency of activities of daily living (ADL).
Methods and results
This retrospective cohort study included 1764 patients with an International Classification of Diseases‐10 code of HF (≥65 years, mean age 82.3 ± 7.9 years, 39% male) from a long‐term care and medical insurance database from Nobeoka city, a rural city of south‐western Japan. Cognitive status at baseline and 6, 12, 18, and 24 month time points was collected, and participants were stratified based on ADL status at baseline. Generalized estimating equations and multi‐state modelling were used to examine associations between ADL dependency and cognitive changes/mortality. Transition probabilities were estimated using multi‐state modelling. At baseline, there were 1279 (73%) and 485 (27%) patients with independent and dependent ADL, respectively. In overall patients, 1656 (93.9%) patients had normal/mild cognitive status and 108 (6%) patients had a moderate/severe cognitive status at baseline. The majority [104 (96%) patients] of patients with moderate/severe cognitive status at baseline had dependent ADL. In patients with moderate/severe cognitive status, the number of patients with dependent ADL always outnumbered that of the independent ADL throughout the follow‐up. Multi‐state modelling estimated that patients with dependent ADL and normal/mild cognitive status at baseline had 47% probability of maintaining the same cognitive status at 24 months, while the probability of maintaining the same cognitive status was 86% for those with independent ADL. Patients with normal/mild cognitive status in the dependent ADL group at baseline had a higher risk of experiencing a transition to moderate/severe cognitive status at any time point during 24 months compared with those with independent ADL [hazard ratio 5.24 (95% confidence interval 3.47–7.90)].
Conclusions
In older patients with HF, the prevalence of cognitive impairment was always higher for those with reduced functional status. Despite having a normal/mild cognitive status at baseline, patients with dependent ADL are at high risk of experiencing cognitive decline over 24 months with substantially less chance of maintaining their cognitive status. ADL dependency was an important risk factor of cognitive decline in patients with HF.
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Details
; Takegami, Misa 2
; Teramoto, Kanako 3
; Murata, Shunsuke 4 ; Nakatsuka, Kiyomasa 5 ; Ogata, Soshiro 1 ; Nishimura, Kunihiro 1 1 Department of Preventive Medicine and Epidemiology, National Cerebral and Cardiovascular Center, Suita, Japan
2 Department of Preventive Medicine and Epidemiology, National Cerebral and Cardiovascular Center, Suita, Japan, Department of Public Health and Health Policy, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
3 Department of Biostatistics, National Cerebral and Cardiovascular Center, Suita, Japan
4 Department of Preventive Medicine and Epidemiology, National Cerebral and Cardiovascular Center, Suita, Japan, Department of Public Health, Graduate School of Health Sciences, Kobe University, Kobe, Japan, Japan Society for the Promotion of Science, Tokyo, Japan
5 Department of Preventive Medicine and Epidemiology, National Cerebral and Cardiovascular Center, Suita, Japan, Department of Public Health, Graduate School of Health Sciences, Kobe University, Kobe, Japan