Diabetes may induce multiple organ damage; therefore, early detection of individuals at high-risk of incident diabetes is important for timely risk assessment and intervention. Arterial stiffness (AS) occurs as a result of functional and structural changes in the arterial wall. Growing body of evidence suggests that AS is a risk factor for incident diabetes. Although each study could use different indicators for AS (ex cf-PWV, baPWV, etc.), they came to similar conclusion that AS was associated with higher risk of incident diabetes. The underlying mechanisms for the relationship of AS with risk of diabetes remain to be elucidated, but there could be several potential mechanisms. Diabetes and AS are expected to share common risk factors and influence each other, but recent research showed some evidence that AS can directly increase the risk of diabetes. The link between AS and incident diabetes has important clinical implications. First, it suggests that AS might be a useful marker for identifying people at high risk for developing diabetes. Second, it suggests that reducing AS may prevent or delay the onset of diabetes. Early detection and possible slowing of the vascular stiffening process with pharmacological agents and lifestyle interventions may reduce associated risks for diabetes.

Diabetes can induce multiple organ damage, leading to kidney disease, cerebrovascular complications, and cardiovascular events [1]. Therefore, early detection of individuals at high-risk of incident diabetes is important for timely risk assessment and intervention. Early detection of high-risk individuals can help prevent the onset and slow the progress of diabetes.

Arterial stiffness (AS) occurs as a result of functional and structural changes in the arterial wall. As the artery stiffens, its cushioning function is impaired, leading to increased flow pulsatility that is transmitted to the microvasculature of vascular beds with low-resistance due to high-flow needs such as the kidney, the brain, the liver, and the pancreas. In these organs, effects of systemic large artery stiffening and associated pulsatile hemodynamic abnormalities might lead to increases of pulsatile pressure and pulsatile flow [2‒5]. One very important person in this field, Doctor O’Rourke and Hashimoto [6], reported and emphasized that increased AS could lead to extension of pressure and flow pulsations into smaller arteries, arterioles, and even capillaries of vasodilated organs, especially the brain and kidneys. Indeed, increased AS could induce renal impairment [7] and intellectual decline [8, 9]. Recently, AS has also been reported to be associated with the risk of incident diabetes [10, 11]. A growing body of evidence suggests that AS is a risk factor for incident diabetes. This brief review paper aimed to provide a comprehensive understanding of the evidence and underlying mechanisms of incident diabetes associated with AS.

More than 10 years ago, some studies found that AS might be a risk factor for diabetes [12, 13]. Although previous studies used different indicators for AS, they came to the similar conclusion that AS was associated with a higher risk of incident diabetes. Muhammad et al. [10] have reported that the third carotid-femoral pulse wave velocity (CF-PWV) quartile has three times higher risk for incident diabetes compared with the first CF-PWV quartile [10]. This study was consistent with a previous large study demonstrating that pulse pressure was independently associated with incident diabetes among hypertensive patients, with each 1 SD increase in pulse pressure associated with 44% higher risk for incident diabetes [13].

Recently, Zheng et al. [11] have observed that AS could be a risk factor for diabetes, independent of traditional risk factors in their community-based cohort study including 14,159 adult participants free of diabetes, cardiovascular, cerebrovascular, and chronic kidney disease who have undergone brachial-ankle pulse wave velocity (baPWV) and fasting blood glucose (FBG) measurements at baseline. Results from temporal analysis suggested that change of AS might precede change of FBG, rather than vice versa. They demonstrated that the risk of incident diabetes over a mean follow-up of 3.72 years was more than two times (hazard ratio [HR] = 2.28) in people with elevated baPWV (≥18 m/s) compared with those with low baPWV values (<14 m/s). Moreover, the authors reported that baseline baPWV was associated with follow-up FBG. However, there was no significant relationship between baseline FBG and follow-up baPWV. The observation that participants with higher baseline baPWV had higher future diabetes risk is consistent with previous studies [10, 12, 13]. Vasan et al. [14] have used Framingham Study participants with CF-PWV and a median follow-up of 15 years and found that each SD increment in CF-PWV is associated with an increased risk of diabetes (HR: 1.32 [95% CI: 1.11–1.58]). Cohen et al. [15] have studied the Framingham Heart Study and the UK Biobank for Mendelian randomization and found that the risk of diabetes (per SD) is increased in those with CF-PWV (HR: 1.36 [95% CI: 1.03–1.76]; p = 0.030); central pulse pressure (HR: 1.26 [95% CI: 1.08–1.48]; p = 0.004). In the UK Biobank, genetically predicted brachial pulse pressure was associated with the risk of diabetes, independent of mean arterial pressure (adjusted odds ratio, 1.16 [95% CI: 1.00–1.35]; p = 0.049). They found “evidence supporting that greater AS is associated with increased risk of developing diabetes, and AS may play an important role in glucose homeostasis and may serve as a useful marker of future diabetes risk.” Tian et al. [16] have used baPWV and reported data after a follow-up of 6.16 years. Those with hypertension and elevated AS had the highest risk of diabetes (baPWV ≥1,400 cm/s) (HR: 2.42 [95% CI: 1.93–3.03]), followed by those with normotension and elevated AS (HR: 2.11 [95% CI: 1.68–2.66]). Those with hypertension and normal AS exhibited the lowest risk of diabetes (HR: 1.48 [95% CI: 1.08–2.02]. They concluded that “Diabetes is associated with not only hypertension but also AS and AS shows a better predictive ability than hypertension in predicting diabetes.” Using different makers of AS, Wang et al. [17] have shown arterial stiffness index (ASI), pulse pressure, and incident diabetes using a large cohort (152,611 [66,698/85,913]) of the UK Biobank with 9.5 years of follow-up. They found that ASI was associated with a 3% higher diabetes risk (95% CI: 2–4%). The HR (95% CI) of diabetes was 1.58 (1.39–1.80) in the highest quintile group compared with the lowest quintile group of ASI. The association between pulse pressure and diabetes was nonlinear. Very recently, Bao et al. [18] found that higher estimated pulse wave velocity (ePWV) was associated with an increased risk of diabetes (HR: 1.233; 95% CI: 1.198–1.269; p < 0.001). (Table 1).

Table 1.

Epidemiologic evidence

Author [ref], yearStudy type and Fu durationTarget populationSample size N (male/female) and age (SD)Adjusted forResults
Muhammad et al. [10], 2017 cf PWV, 4.4 (1.4) years Malmö Diet and Cancer Cardiovascular Cohort 2,450 (905/1,545) mean age; 71.9 (5.6) Age, sex, mean arterial pressure, average heart rate, waist circumference, smoking habits, fasting plasma glucose, LDL cholesterol, and antihypertensive drug medication Hazard ratio (HR) of diabetes was 1.00 (reference), 1.83 (95% CI: 0.88–3.8), and 3.24 (95% CI: 1.51–6.97), respectively, for the tertiles of CF-PWV (p for trend = 0.002) 
Zhang et al. [19], 2019 baPWV The China Stroke Primary Prevention Trial 2,429 (1,380/1,049) mean age; 59.7 (7.4) Age, sex, study center, study treatment group, body mass index, heart rate, smoking, systolic blood pressure, fasting glucose, total cholesterol, creatinine, and folate at baseline, as well as time-averaged systolic blood pressure during the treatment period In quartiles, 2–4 (≥15.9 m/s) HR was 1.80; 95% CI: 1.22, 2.65) compared with those in quartile 1 (<15.9 m/s) of baPWV 
4.5 years Hypertensive patients 
Zheng et al. [11], 2020 baPWV Participants of the Kailuan study 14,159 (9,238/4,921) Age, sex, mean arterial pressure, heart rate, log-transformed hs-CRP, FBG, uric acid, eGFR, waist circumference, BMI, LDL-C, HDL-C, triglycerides, smoking habits, alcohol consumption, lipid-lowering, and antihypertensive drug use Risk of diabetes was 1.59 (1.34–1.88) for the borderline group (1,400 ≤ baPWV <1,800 cm/s) and 2.11 (1.71–2.61) for the elevated group (≥1,800 cm/s), compared with the reference group (<1,400 cm/s). Baseline baPWV was associated with follow-up FBG (the standard regression coefficient was 0.09 [95% CI: 0.05–0.10]). In contrast, baseline FBG for follow-up baPWV (β = 0.00 [95% CI: −0.02 to 0.02]) was not significant 
3.72 years 48.3 (12.0) 
Tian et al. [16], 2022 baPWV The Kailuan study 11,156 (6,380/4,776) Age, sex, body mass index, heart rate, smoking status, and alcohol consumption, dyslipidemia, total cholesterol, LDL-C, HDL-C, serum uric acid, hs-CRP, and eGFR, mean arterial pressure, and diastolic blood pressure, separately The highest risk of diabetes was observed in hypertension with elevated AS group (baPWV ≥1,400 cm/s) (HR: 2.42 [95% CI: 1.93–3.03]), followed by normotension with elevated AS group (HR, 2.11 [95% CI: 1.68–2.66]), hypertension with normal AS group exhibited the lowest risk of diabetes (HR, 1.48 [95% CI: 1.08–2.02]) 
6.16 years 51.5 (11.6) 
Vasan et al. [14], 2022 cf PWV Framingham Study participants 7,283 (3,392/3,891) Age, sex, current smoking, total cholesterol/HDL cholesterol, systolic blood pressure, and hypertensive treatment Each SD increment in CF-PWV was associated with increased risk of diabetes (HR: 1.32 [95% CI: 1.11–1.58]) 
Median of 15 years 50.3 (14.5) 
Cohen et al. [15], 2022 cf-PWV and brachial and central pulse pressure 5,676 5,676 (2,615/3,061) Age, sex, and body mass index, mean arterial pressure, heart rate, eGFR, smoking, total cholesterol, high-density lipoprotein, thiazide diuretic, beta-blocker total antihypertensive medications, C-reactive protein, family history of diabetes. (for Framingham Heart Study/0 Risk of diabetes (per SD) increase, CF-PWV (HR, 1.36 [95% CI: 1.03–1.76]; p = 0.030); central pulse pressure 1.26 ([95% CI: 1.08–1.48]; p = 0.004). In UK Biobank, genetically predicted brachial pulse pressure was associated with risk of diabetes, independent of mean arterial pressure (adjusted odds ratio, 1.16 [95% CI: 1.00–1.35]; p = 0.049) 
Framingham Heart Study 46 (37–55) 
Median of 7 years 
The UK Biobank for Mendelian randomization Framingham Heart Study 
Yasuno et al. [13], 2010 Pulse pressure Candesartan Antihypertensive Survival Evaluation in Japan (CASE-J) trial, high-risk Japanese hypertensive patients 2,685 (1,471/1,214) Prior antihypertensive treatment, allocated drug, age, sex, BMI, heart rate, history of cerebrovascular events, LVH, history of ischemic heart disease, renal dysfunction, peripheral vascular disease, hyperlipidemia, and smoking) as standard covariates and additional drugs (diuretics, α-blockers, and β-blockers) as time-varying covariates Pulse pressure was an independent predictor for new-onset diabetes (HR per 1 SD increase 1.44 [95% CI: 1.15–1.79]) 
3.3±0.8 years 63.7 (11.1) 
Wang et al. [17], 2022 Arterial stiffness index (ASI) and pulse pressure (PP) The UK Biobank 152,611 (66,698/85,913) Age, sex, UK Biobank assessment center, race, Townsend deprivation index, alcohol consumption, smoking status, BMI, physical activity, healthy diet score, use of antihypertensive drugs, use of lipid-lowering drugs, LDL cholesterol, and family history of diabetes, SBP ASI was associated with a 3% higher diabetes risk (95% CI: 2–4%). The HR (95% CI) of diabetes was 1.58 (1.39–1.80) in the highest quintile group compared with the lowest quintile group of ASI. The association between PP and diabetes was nonlinear 
9.5 years 56.3 (8.2) 
Bao et al. [18], 2023 Estimated pulse wave velocity (ePWV) Chinese Rich Health Care Group’s cohort study, 211,809 participants 211,809 (116,112/95,697) Sex, body mass index, smoking drinking, family history of diabetes Risk of diabetes (hazard ratio, 1.233; 95% confidence interval, 1.198–1.269; p < 0.001) 
3.12 years 42.1 (12.6) 
Author [ref], yearStudy type and Fu durationTarget populationSample size N (male/female) and age (SD)Adjusted forResults
Muhammad et al. [10], 2017 cf PWV, 4.4 (1.4) years Malmö Diet and Cancer Cardiovascular Cohort 2,450 (905/1,545) mean age; 71.9 (5.6) Age, sex, mean arterial pressure, average heart rate, waist circumference, smoking habits, fasting plasma glucose, LDL cholesterol, and antihypertensive drug medication Hazard ratio (HR) of diabetes was 1.00 (reference), 1.83 (95% CI: 0.88–3.8), and 3.24 (95% CI: 1.51–6.97), respectively, for the tertiles of CF-PWV (p for trend = 0.002) 
Zhang et al. [19], 2019 baPWV The China Stroke Primary Prevention Trial 2,429 (1,380/1,049) mean age; 59.7 (7.4) Age, sex, study center, study treatment group, body mass index, heart rate, smoking, systolic blood pressure, fasting glucose, total cholesterol, creatinine, and folate at baseline, as well as time-averaged systolic blood pressure during the treatment period In quartiles, 2–4 (≥15.9 m/s) HR was 1.80; 95% CI: 1.22, 2.65) compared with those in quartile 1 (<15.9 m/s) of baPWV 
4.5 years Hypertensive patients 
Zheng et al. [11], 2020 baPWV Participants of the Kailuan study 14,159 (9,238/4,921) Age, sex, mean arterial pressure, heart rate, log-transformed hs-CRP, FBG, uric acid, eGFR, waist circumference, BMI, LDL-C, HDL-C, triglycerides, smoking habits, alcohol consumption, lipid-lowering, and antihypertensive drug use Risk of diabetes was 1.59 (1.34–1.88) for the borderline group (1,400 ≤ baPWV <1,800 cm/s) and 2.11 (1.71–2.61) for the elevated group (≥1,800 cm/s), compared with the reference group (<1,400 cm/s). Baseline baPWV was associated with follow-up FBG (the standard regression coefficient was 0.09 [95% CI: 0.05–0.10]). In contrast, baseline FBG for follow-up baPWV (β = 0.00 [95% CI: −0.02 to 0.02]) was not significant 
3.72 years 48.3 (12.0) 
Tian et al. [16], 2022 baPWV The Kailuan study 11,156 (6,380/4,776) Age, sex, body mass index, heart rate, smoking status, and alcohol consumption, dyslipidemia, total cholesterol, LDL-C, HDL-C, serum uric acid, hs-CRP, and eGFR, mean arterial pressure, and diastolic blood pressure, separately The highest risk of diabetes was observed in hypertension with elevated AS group (baPWV ≥1,400 cm/s) (HR: 2.42 [95% CI: 1.93–3.03]), followed by normotension with elevated AS group (HR, 2.11 [95% CI: 1.68–2.66]), hypertension with normal AS group exhibited the lowest risk of diabetes (HR, 1.48 [95% CI: 1.08–2.02]) 
6.16 years 51.5 (11.6) 
Vasan et al. [14], 2022 cf PWV Framingham Study participants 7,283 (3,392/3,891) Age, sex, current smoking, total cholesterol/HDL cholesterol, systolic blood pressure, and hypertensive treatment Each SD increment in CF-PWV was associated with increased risk of diabetes (HR: 1.32 [95% CI: 1.11–1.58]) 
Median of 15 years 50.3 (14.5) 
Cohen et al. [15], 2022 cf-PWV and brachial and central pulse pressure 5,676 5,676 (2,615/3,061) Age, sex, and body mass index, mean arterial pressure, heart rate, eGFR, smoking, total cholesterol, high-density lipoprotein, thiazide diuretic, beta-blocker total antihypertensive medications, C-reactive protein, family history of diabetes. (for Framingham Heart Study/0 Risk of diabetes (per SD) increase, CF-PWV (HR, 1.36 [95% CI: 1.03–1.76]; p = 0.030); central pulse pressure 1.26 ([95% CI: 1.08–1.48]; p = 0.004). In UK Biobank, genetically predicted brachial pulse pressure was associated with risk of diabetes, independent of mean arterial pressure (adjusted odds ratio, 1.16 [95% CI: 1.00–1.35]; p = 0.049) 
Framingham Heart Study 46 (37–55) 
Median of 7 years 
The UK Biobank for Mendelian randomization Framingham Heart Study 
Yasuno et al. [13], 2010 Pulse pressure Candesartan Antihypertensive Survival Evaluation in Japan (CASE-J) trial, high-risk Japanese hypertensive patients 2,685 (1,471/1,214) Prior antihypertensive treatment, allocated drug, age, sex, BMI, heart rate, history of cerebrovascular events, LVH, history of ischemic heart disease, renal dysfunction, peripheral vascular disease, hyperlipidemia, and smoking) as standard covariates and additional drugs (diuretics, α-blockers, and β-blockers) as time-varying covariates Pulse pressure was an independent predictor for new-onset diabetes (HR per 1 SD increase 1.44 [95% CI: 1.15–1.79]) 
3.3±0.8 years 63.7 (11.1) 
Wang et al. [17], 2022 Arterial stiffness index (ASI) and pulse pressure (PP) The UK Biobank 152,611 (66,698/85,913) Age, sex, UK Biobank assessment center, race, Townsend deprivation index, alcohol consumption, smoking status, BMI, physical activity, healthy diet score, use of antihypertensive drugs, use of lipid-lowering drugs, LDL cholesterol, and family history of diabetes, SBP ASI was associated with a 3% higher diabetes risk (95% CI: 2–4%). The HR (95% CI) of diabetes was 1.58 (1.39–1.80) in the highest quintile group compared with the lowest quintile group of ASI. The association between PP and diabetes was nonlinear 
9.5 years 56.3 (8.2) 
Bao et al. [18], 2023 Estimated pulse wave velocity (ePWV) Chinese Rich Health Care Group’s cohort study, 211,809 participants 211,809 (116,112/95,697) Sex, body mass index, smoking drinking, family history of diabetes Risk of diabetes (hazard ratio, 1.233; 95% confidence interval, 1.198–1.269; p < 0.001) 
3.12 years 42.1 (12.6) 

Underlying mechanisms for the relationship of AS with risk of diabetes remain to be elucidated. There could be several potential mechanisms which may underlie the observed association between AS and the risk of developing diabetes. Diabetes and AS might share common risk factors and influence each other. However, recent research showed some evidence that AS can directly increase the risk of diabetes (Fig. 1).

Fig. 1.

Target organs by AS. Increased AS could induce myocardial dysfunction, renal impairment, and intellectual decline. AS has also been reported to be associated with the risk of incident diabetes, by insulin resistance/impaired glucose metabolism. The pancreas, liver, and skeletal muscles are key organs that play a major role incident diabetes and can be considered new metabolic target by AS.

Fig. 1.

Target organs by AS. Increased AS could induce myocardial dysfunction, renal impairment, and intellectual decline. AS has also been reported to be associated with the risk of incident diabetes, by insulin resistance/impaired glucose metabolism. The pancreas, liver, and skeletal muscles are key organs that play a major role incident diabetes and can be considered new metabolic target by AS.

Close modal

There are several pieces of evidence that AS and diabetes share common risk factors and influence or induce each other. First, it is known that individuals with established diabetes exhibit higher AS compared with their nondiabetic counterparts [20], even in heart failure patients with preserved ejection fraction [21] or established chronic kidney disease [22, 23]. Second, metabolic syndrome is associated with an increased progression of AS with age [24]. It may increase the risk for both diabetes and AS. Third, AS and diabetes could share the same genetic background. A Mendelian randomization study showed that genetically determined decrease in insulin secretion was associated with AS [25]. Finally, chronic low-grade inflammation and increased oxidative stress might be common risk factors for diabetes and AS [26].

The pathogenesis of diabetes involves the development of insulin resistance and compensatory hyperinsulinemia, followed by beta-cell impairment that can result in hyperglycemia. The pancreas, liver, and skeletal muscles are essential for the regulation of glucose homeostasis. Although the exact underlying mechanisms for why AS is a risk factor for diabetes remain to be elucidated, several potential mechanisms have been suggested.

Increased arterial pulse pressure caused by AS could lead to endothelial dysfunction [27]. Endothelial dysfunction and impaired endothelium-dependent vasodilation could then exacerbate insulin resistance by impaired glucose delivery to key target tissues (pancreas, liver and muscle), which precede the development of diabetes [28]. AS could cause damage to capillary diastolic dysfunction, which then leads to damage of low-resistance organs such as the pancreas [11]. AS could impact microvascular health in pancreatic islets, which may lead to dysfunctional or dysregulated endocrine function. Although type 2 diabetes is primarily associated with insulin resistance, insufficient insulin secretion and an imbalance in insulin versus glucagon secretion due to damaged small vessels play a key role in its pathogenesis [29].

Microvascular dysfunction and remodeling of skeletal muscle might contribute to insulin resistance [30]. Microvascular alterations in association with increased AS could lead to impaired insulin-mediated changes in muscle perfusion and glucose metabolism [31].

Liver also exhibits low-resistance arterial hemodynamics as the hepatic artery provides approximately one-third of the liver blood flow [3]. Hepatic arterial buffer responses important for metabolic homeostasis could be deteriorated by AS. There also seems to be a relationship between AS and nonalcoholic fatty liver disease, a strongly associated and highly prevalent disease in diabetes [3].

The link between AS and incident diabetes has important clinical implications. First, it suggests that AS might be a useful marker for identifying people at high risk for developing diabetes. Second, it suggests that reducing AS may prevent or delay the onset of diabetes. Early detection and possible slowing of the vascular stiffening process with pharmacological agents and lifestyle interventions may reduce associated risks for diabetes. Although there is still no specific protective prescription for AS, weight loss [32], exercise [33], and smoking cessation [34] are known to exert a modulatory effect on AS. Among antihypertensive medications, ARB, ACEI, and calcium channel blocker compared with β-receptor blocker and diuretics can lower AS. Further study would be needed to determine whether these drugs could lower the risk of incident diabetes.

The authors have no conflicts of interest to declare.

This study was not supported by any sponsor or funder.

Ki-Chul Sung contributed to the concept and design of this review and critical revision of the manuscript for important intellectual content and read and approved the final version of the manuscript.

The paper is not under consideration elsewhere. None of the paper’s contents have been previously published.

1.
Sukkar
L
,
Kang
A
,
Hockham
C
,
Young
T
,
Jun
M
,
Foote
C
et al
.
Incidence and associations of chronic kidney disease in community participants with diabetes: a 5-year prospective analysis of the EXTEND45 study
.
Diabetes Care
.
2020
;
43
(
5
):
982
90
.
2.
Townsend
RR
,
Wilkinson
IB
,
Schiffrin
EL
,
Avolio
AP
,
Chirinos
JA
,
Cockcroft
JR
et al
.
Recommendations for improving and standardizing vascular research on arterial stiffness: a scientific statement from the American heart association
.
Hypertension
.
2015
;
66
(
3
):
698
722
.
3.
Chirinos
JA
,
Segers
P
,
Hughes
T
,
Townsend
R
.
Large-artery stiffness in health and disease: JACC state-of-the-art review
.
J Am Coll Cardiol
.
2019
;
74
(
9
):
1237
63
.
4.
Park
JB
,
Sharman
JE
,
Li
Y
,
Munakata
M
,
Shirai
K
,
Chen
CH
et al
.
Expert consensus on the clinical use of pulse wave velocity in asia
.
Pulse
.
2022
10
1–4
1
18
.
5.
Park
JB
,
Avolio
A
.
Arteriosclerosis and atherosclerosis assessment in clinical practice: methods and significance
.
Pulse
.
2023
;
11
(
1
):
1
8
.
6.
O’Rourke
MF
,
Hashimoto
J
.
Mechanical factors in arterial aging: a clinical perspective
.
J Am Coll Cardiol
.
2007
;
50
(
1
):
1
13
.
7.
Ford
ML
,
Tomlinson
LA
,
Chapman
TP
,
Rajkumar
C
,
Holt
SG
.
Aortic stiffness is independently associated with rate of renal function decline in chronic kidney disease stages 3 and 4
.
Hypertension
.
2010
;
55
(
5
):
1110
5
.
8.
Scuteri
A
,
Brancati
AM
,
Gianni
W
,
Assisi
A
,
Volpe
M
.
Arterial stiffness is an independent risk factor for cognitive impairment in the elderly: a pilot study
.
J Hypertens
.
2005
;
23
(
6
):
1211
6
.
9.
Wang
WT
,
Chang
WL
,
Cheng
HM
.
The relationship of vascular aging to reduced cognitive function: pulsatile and steady state arterial hemodynamics
.
Pulse
.
2022
10
1–4
19
25
.
10.
Muhammad
IF
,
Borne
Y
,
Ostling
G
,
Kennback
C
,
Gottsater
M
,
Persson
M
et al
.
Arterial stiffness and incidence of diabetes: a population-based cohort study
.
Diabetes Care
.
2017
;
40
(
12
):
1739
45
.
11.
Zheng
M
,
Zhang
X
,
Chen
S
,
Song
Y
,
Zhao
Q
,
Gao
X
et al
.
Arterial stiffness preceding diabetes: a longitudinal study
.
Circ Res
.
2020
;
127
(
12
):
1491
8
.
12.
Chen
JY
,
Chou
CH
,
Lee
YL
,
Tsai
WC
,
Lin
CC
,
Huang
YY
et al
.
Association of central aortic pressures indexes with development of diabetes mellitus in essential hypertension
.
Am J Hypertens
.
2010
;
23
(
10
):
1069
73
.
13.
Yasuno
S
,
Ueshima
K
,
Oba
K
,
Fujimoto
A
,
Hirata
M
,
Ogihara
T
et al
.
Is pulse pressure a predictor of new-onset diabetes in high-risk hypertensive patients? a subanalysis of the Candesartan Antihypertensive Survival Evaluation in Japan (CASE-J) trial
.
Diabetes Care
.
2010
;
33
(
5
):
1122
7
.
14.
Vasan
RS
,
Pan
S
,
Xanthakis
V
,
Beiser
A
,
Larson
MG
,
Seshadri
S
et al
.
Arterial stiffness and long-term risk of health outcomes: the Framingham heart study
.
Hypertension
.
2022
;
79
(
5
):
1045
56
.
15.
Cohen
JB
,
Mitchell
GF
,
Gill
D
,
Burgess
S
,
Rahman
M
,
Hanff
TC
et al
.
Arterial stiffness and diabetes risk in Framingham heart study and UK Biobank
.
Circ Res
.
2022
;
131
(
6
):
545
54
.
16.
Tian
X
,
Zuo
Y
,
Chen
S
,
Zhang
Y
,
Zhang
X
,
Xu
Q
et al
.
Hypertension, arterial stiffness, and diabetes: a prospective cohort study
.
Hypertension
.
2022
;
79
(
7
):
1487
96
.
17.
Wang
M
,
Huang
J
,
Wu
T
,
Qi
L
.
Arterial stiffness, genetic risk, and type 2 diabetes: a prospective cohort study
.
Diabetes Care
.
2022
;
45
(
4
):
957
64
.
18.
Bao
W
,
Chen
C
,
Chen
C
,
Zhang
X
,
Miao
H
,
Zhao
X
et al
.
Association between estimated pulse wave velocity and risk of diabetes: a large sample size cohort study
.
Nutr Metab Cardiovasc Dis
.
2023
;
33
(
9
):
1716
24
.
19.
Qin
Z
,
Zhou
K
,
Li
YP
,
Wang
JL
,
Cheng
WJ
,
Hu
CP
et al
.
Remnant lipoproteins play an important role of in-stent restenosis in type 2 diabetes undergoing percutaneous coronary intervention: a single-centre observational cohort study
.
Cardiovasc Diabetol
.
2019
;
18
(
1
):
11
.
20.
Prenner
SB
,
Chirinos
JA
.
Arterial stiffness in diabetes mellitus
.
Atherosclerosis
.
2015
;
238
(
2
):
370
9
.
21.
Chirinos
JA
,
Bhattacharya
P
,
Kumar
A
,
Proto
E
,
Konda
P
,
Segers
P
et al
.
Impact of diabetes mellitus on ventricular structure, arterial stiffness, and pulsatile hemodynamics in heart failure with preserved ejection fraction
.
J Am Heart Assoc
.
2019
;
8
(
4
):
e011457
.
22.
Townsend
RR
,
Wimmer
NJ
,
Chirinos
JA
,
Parsa
A
,
Weir
M
,
Perumal
K
et al
.
Aortic PWV in chronic kidney disease: a CRIC ancillary study
.
Am J Hypertens
.
2010
;
23
(
3
):
282
9
.
23.
Briet
M
,
Boutouyrie
P
,
Laurent
S
,
London
GM
.
Arterial stiffness and pulse pressure in CKD and ESRD
.
Kidney Int
.
2012
;
82
(
4
):
388
400
.
24.
Safar
ME
,
Thomas
F
,
Blacher
J
,
Nzietchueng
R
,
Bureau
JM
,
Pannier
B
et al
.
Metabolic syndrome and age-related progression of aortic stiffness
.
J Am Coll Cardiol
.
2006
;
47
(
1
):
72
5
.
25.
Xu
M
,
Huang
Y
,
Xie
L
,
Peng
K
,
Ding
L
,
Lin
L
et al
.
Diabetes and risk of arterial stiffness: a mendelian randomization analysis
.
Diabetes
.
2016
;
65
(
6
):
1731
40
.
26.
Wang
X
,
Bao
W
,
Liu
J
,
Ouyang
YY
,
Wang
D
,
Rong
S
et al
.
Inflammatory markers and risk of type 2 diabetes: a systematic review and meta-analysis
.
Diabetes Care
.
2013
;
36
(
1
):
166
75
.
27.
Petrie
JR
,
Guzik
TJ
,
Touyz
RM
.
Diabetes, hypertension, and cardiovascular disease: clinical insights and vascular mechanisms
.
Can J Cardiol
.
2018
;
34
(
5
):
575
84
.
28.
Balletshofer
BM
,
Rittig
K
,
Enderle
MD
,
Volk
A
,
Maerker
E
,
Jacob
S
et al
.
Endothelial dysfunction is detectable in young normotensive first-degree relatives of subjects with type 2 diabetes in association with insulin resistance
.
Circulation
.
2000
;
101
(
15
):
1780
4
.
29.
Chirinos
JA
.
Large artery stiffness and new-onset diabetes
.
Circ Res
.
2020
;
127
(
12
):
1499
501
.
30.
Barrett
EJ
,
Liu
Z
,
Khamaisi
M
,
King
GL
,
Klein
R
,
Klein
BEK
et al
.
Diabetic microvascular disease: an endocrine society scientific statement
.
J Clin Endocrinol Metab
.
2017
;
102
(
12
):
4343
410
.
31.
Cardoso
CR
,
Ferreira
MT
,
Leite
NC
,
Barros
PN
,
Conte
PH
,
Salles
GF
.
Microvascular degenerative complications are associated with increased aortic stiffness in type 2 diabetic patients
.
Atherosclerosis
.
2009
;
205
(
2
):
472
6
.
32.
Yamada
J
,
Tomiyama
H
,
Matsumoto
C
,
Yoshida
M
,
Koji
Y
,
Shiina
K
et al
.
Overweight body mass index classification modifies arterial stiffening associated with weight gain in healthy middle-aged Japanese men
.
Hypertens Res
.
2008
;
31
(
6
):
1087
92
.
33.
Cavero-Redondo
I
,
Tudor-Locke
C
,
Alvarez-Bueno
C
,
Cunha
PG
,
Aguiar
EJ
,
Martinez-Vizcaino
V
.
Steps per day and arterial stiffness
.
Hypertension
.
2019
;
73
(
2
):
350
63
.
34.
Tomiyama
H
,
Hashimoto
H
,
Tanaka
H
,
Matsumoto
C
,
Odaira
M
,
Yamada
J
et al
.
Continuous smoking and progression of arterial stiffening: a prospective study
.
J Am Coll Cardiol
.
2010
;
55
(
18
):
1979
87
.