Midnight salivary cortisol secretion associated with high systolic blood pressure in type 1 diabetes

in Endocrine Connections

Correspondence should be addressed to E O Melin: eva.o.melin@gmail.com

Objective

To explore associations between high midnight salivary cortisol (MSC) secretion and high blood pressure (BP) in type 1 diabetes (T1D).

Methods

Cross-sectional study of 196 adult patients with T1D (54% men). Associations between high MSC (≥9.3 nmol/L) and high systolic BP (>130 mmHg), and high diastolic BP (>80 mmHg) were explored for all patients, users and non-users of antihypertensive drugs (AHD). Adjustments were performed for age, sex, diabetes-related variables, p-creatinine, smoking, physical inactivity, depression and medication.

Results

The prevalence of high MSC differed between patients with high and low systolic BP in all 196 patients: 39 vs 13% (P = 0.001); in 60 users of AHD: 37 vs 12% (P = 0.039), and in 136 non-users of AHD: 43 vs 13% (P = 0.012). Significant associations with high systolic BP were for all patients: physical inactivity (adjusted odds ratio (AOR) 6.5), high MSC (AOR 3.9), abdominal obesity (AOR 3.7), AHD (AOR 2.9), age (per year) (AOR 1.07), and p-creatinine (per µmol/L) (AOR 1.03); for 60 users of AHD: high MSC (AOR 4.1) and age (per year) (AOR 1.11); for 136 non-users of AHD: abdominal obesity (AOR 27.4), physical inactivity (AOR 14.7), male sex (AOR 9.0), smoking (AOR 7.9), and age (per year) (AOR 1.08). High MSC was not associated with high DBP.

Conclusions

In adult patients with T1D, high systolic BP was associated with physical inactivity, high MSC secretion, abdominal obesity, p-creatinine, age, and AHD, the latter indicating treatment failure.

Abstract

Objective

To explore associations between high midnight salivary cortisol (MSC) secretion and high blood pressure (BP) in type 1 diabetes (T1D).

Methods

Cross-sectional study of 196 adult patients with T1D (54% men). Associations between high MSC (≥9.3 nmol/L) and high systolic BP (>130 mmHg), and high diastolic BP (>80 mmHg) were explored for all patients, users and non-users of antihypertensive drugs (AHD). Adjustments were performed for age, sex, diabetes-related variables, p-creatinine, smoking, physical inactivity, depression and medication.

Results

The prevalence of high MSC differed between patients with high and low systolic BP in all 196 patients: 39 vs 13% (P = 0.001); in 60 users of AHD: 37 vs 12% (P = 0.039), and in 136 non-users of AHD: 43 vs 13% (P = 0.012). Significant associations with high systolic BP were for all patients: physical inactivity (adjusted odds ratio (AOR) 6.5), high MSC (AOR 3.9), abdominal obesity (AOR 3.7), AHD (AOR 2.9), age (per year) (AOR 1.07), and p-creatinine (per µmol/L) (AOR 1.03); for 60 users of AHD: high MSC (AOR 4.1) and age (per year) (AOR 1.11); for 136 non-users of AHD: abdominal obesity (AOR 27.4), physical inactivity (AOR 14.7), male sex (AOR 9.0), smoking (AOR 7.9), and age (per year) (AOR 1.08). High MSC was not associated with high DBP.

Conclusions

In adult patients with T1D, high systolic BP was associated with physical inactivity, high MSC secretion, abdominal obesity, p-creatinine, age, and AHD, the latter indicating treatment failure.

Introduction

Type 1 diabetes (T1D) is an autoimmune disease, characterised by insulin deficiency due to pancreatic β-cell loss leading to hyperglycaemia (1). T1D is associated with increased risk for myocardial infarction, heart failure and ischemic stroke (2). Hypertension is a major risk factor for cardiovascular disease (CVD), and antihypertensive therapy reduces atherosclerotic CVD and heart failure (3). In a large Swedish population study the prevalence of hypertension in patients with T1D was 35%, almost twice as high as in the non-diabetic population (2). Several factors might contribute to the development of hypertension, such as increased cortisol secretion (4, 5, 6, 7, 8, 9), obesity (8, 9), physical inactivity (10), smoking (11), and depression (12), and higher blood pressure (BP) have been observed in men (13). Increased cortisol secretion is one factor that might contribute to treatment-resistant hypertension (14).

Increased cortisol secretion is implicated in the development of atherosclerosis, CVD and CV mortality (15, 16, 17). Several disturbances of the hypothalamus–pituitary–adrenal (HPA) axis in patients with T1D have been demonstrated. The disturbances include increased basal hyperactivity (18), exaggerated nocturnal rise in plasma cortisol (19), greater cortisol responses to corticotropin-releasing hormone (CRH) stimulation (20), and impaired glucocorticoid negative feedback (18, 21). Impaired glycaemic control, hypoinsulinaemia, hypoglycaemia episodes, impaired kidney function, depression, physical inactivity, smoking and other types of substance abuse, all affect the levels of cortisol secretion (21, 22, 23, 24, 25, 26, 27, 28).

In our previous research we showed that high systolic BP was associated with abdominal obesity (9), and with the macrophage-derived inflammatory marker soluble 163 (29). We also previously found that depression, smoking and physical inactivity were associated with high midnight salivary cortisol (MSC) secretion (≥9.3 nmol/L) in these patients with T1D (22).

We hypothesise that high MSC secretion contributes to hypertension and to treatment failure of antihypertensive drugs (AHDs). The main aims were to explore whether high MSC (≥9.3 nmol/L) was associated with systolic BP >130 mmHg and/or diastolic BP >80 mg. We controlled for potential covariates such as age, diabetes duration, sex, abdominal obesity, HbA1c, hypoglycaemia episodes, depression, physical inactivity, smoking, plasma-creatinine, AHD, and the use of antidepressants.

Materials and methods

This study had a cross-sectional design. The patients were recruited by specialist diabetes physicians or diabetes nurses at regular follow-up visits at one outpatient’s diabetes clinic in southern Sweden during the period 03/25/2009 to 12/28/2009. The catchment population was 125,000. Inclusion criteria were T1D, age 18–59 years, diabetes duration ≥1 year, and performed measurements of MSC (Fig. 1). Exclusion criteria were systemic corticosteroid treatment; pregnancy; severe comorbidities or cognitive deficiency (cancer, hepatic failure, end-stage renal disease (ESRD), diagnosed Cushing’s syndrome/disease, stroke with cognitive deficiency, psychotic disorder, bipolar disorder, severe personality disorder, mental retardation, severe substance abuse); or inadequate knowledge of Swedish. BP and waist circumference (WC) measurements, saliva and blood samples were collected, supplemented by data from electronic medical records. Data were analysed for all, and separately for users and non-users of AHD. Depression was assessed by a self-report instrument. The study was approved by the Regional Ethical Review Board of Linköping University, Linköping (Registration no. M120-07, T89-08). All patients provided written informed consent.

Figure 1
Figure 1

Flow chart showing excluded and included patients with T1D.

Citation: Endocrine Connections 8, 11; 10.1530/EC-19-0407

Midnight salivary cortisol

Each patient collected one MSC sample between 23.30 and 00.30 h, using the Salivette® sampling method (Sarstedt, Nümbrecht, Germany) (22, 30, 31).

Patients had a restriction period of 30 min prior to sampling when they were told not to eat, drink, smoke, use snuff, or perform physical exercise, and a period of 60 min prior to sampling when they should avoid brushing their teeth. MSC samples delivered within 1 week from BP measurements were included. The samples were centrifuged and frozen at −25°C until assayed within a year. The Roche Cobas Cortisolassay®, a competitive electrochemiluminescence immunoassay (ECLIA) was used on an Elecsys 2010 immunoanalyser system (Roche Diagnostics) (32). The intra-coefficient of variation was <3%.

High MSC was defined as ≥9.3 nmol/L (22, 30, 33), which corresponds to the 83rd percentile in these participants.

Out of 292 patients who provided informed consent to participate, nine subjects were excluded due to the use of systemic corticosteroids, two subjects using topical steroids had very high MSC values (82 and 72 nmol/L) and were therefore excluded as contamination was suspected, and 85 subjects chose not to deliver or failed to deliver proper MSC samples (Fig. 1) (22). Finally, there were proper MSC samples for 196 participants.

Blood pressure and waist circumference

A nurse measured BP once on the patient’s right arm, with the patient in the sitting position. High systolic BP was defined as >130 mmHg, and high diastolic BP as >80 mmHg. The treatment targets for AHD, recommended in the Swedish National Guidelines for Diabetes in 2009, were systolic BP ≤130 and diastolic BP ≤80 mmHg (34).

Waist circumference was measured according to standard procedures by a nurse. Abdominal obesity was defined as waist circumference (meters) ≥0.88 for women and as ≥1.02 for men (9, 22, 35, 36, 37).

Episodes of hypoglycaemia

A severe episode of hypoglycaemia was defined as needing help from another person. Episodes during the last 6 months prior to recruitment were registered.

HbA1c and p-creatinine

HbA1c (presented as mmol/mol and %) was analysed with an Olympus AU clinical chemistry. The intra-coefficient of variation was <3%.

P-creatinine (µmol/L) was assayed by an AU2700® instrument (Beckman Coulter). The intra-coefficient of variation was <3%.

Smoking and physical inactivity

Smokers were defined as having smoked any amount of tobacco during the last year (22). Levels of physical activity performed at work and during leisure time were assessed by interviews performed by skilled nurses and physicians at the regular follow-up visits. Physical inactivity was defined as moderate activities, such as 30 min of walking, less than once a week (22, 37).

Self-reported depression

Depression was assessed by the Hospital Anxiety and Depression Scale – the depression subscale (HADS-D) which consists of seven statements rated from 0 to 3. Depression was defined as HADS-D ≥8 points as recommended by the constructors of the test (38), and as in our previous research (22, 30, 36, 39, 40). A major characteristic of HADS-D is that potential symptoms of somatic disease are not included (38).

Medication

AHD were Ca antagonists (ATC codes C08CA01-02); angiotensin-converting enzyme (ACE) inhibitors (ATC codes C09AA-BA); angiotensin II antagonists (ATC codes C09CA-DA); diuretics (ATC codes C03AA03 and C03CA01); selective beta-adrenoreceptor antagonists (ATC code C07AB). The use of AHD was dichotomised into users and non-users of AHD.

Antidepressants were SSRIs (ATC codes N06AB04 and N06AB10); SNRIs (ATC code N06AX16); combined serotonin and norepinephrine reuptake inhibitors (ATC code N06AX21); tricyclic antidepressants (ATC code N06AA04); and/or tetracyclic antidepressants (ATC code N06AX11). The use of antidepressants was dichotomised into users and non-users of antidepressants.

Statistical analysis

Analyses of data distribution using histograms revealed that MSC, systolic and diastolic BP, were not normally distributed. Data were presented as median values (quartile (q)1, q3; range), and analyses were performed with Mann–Whitney U test. Fisher’s exact test were used to analyze categorical data. Crude odds ratios (CORs) were calculated. Variables with P ≤ 0.10 for the CORs, and sex and age (independent of P values), were entered in multiple logistic regression analyses (Backward: Wald) with systolic BP >130 mmHg and diastolic BP >80 mmHg as dependent variables for all, users of AHD and non-users of AHD. In non-users of AHD, multiple logistic regression analyses (Backward: Wald) were performed with high MSC as a dependent variable. The Hosmer and Lemeshow test for goodness-of-fit and Nagelkerke R2 were used to evaluate each of these multiple logistic regression analyses models. Confidence intervals (CIs) of 95% were used. P < 0.05 was considered statistically significant. SPSS® version 23 (IBM) was used for the statistical analyses.

Results

One hundred and ninety-six patients with T1D participated in this study (54% men, 18–59 years, diabetes duration 1–55 years). Sixty patients (31%) were users of AHD and 136 (69%) were non-users of AHD. The patients used either multiple daily insulin injections (MDII) (90%) or continuous s.c. insulin infusion (CSII) (10%). Seven patients (4%) had cardiovascular complications.

Baseline data, comparisons between users and non-users of AHD, and comparisons between patients with high and low MSC are presented in Table 1. The 60 users of AHD compared to the 136 non-users were older (P < 0.001), had longer diabetes duration (P < 0.001), and higher prevalence of high systolic BP (32 vs 10%, P = 0.001). The 34 patients with high MSC compared to the 162 with low MSC were older (P = 0.002), and had higher prevalence of high systolic BP (P = 0.001), smoking (P = 0.002), and depression (P = 0.002).

Table 1

Baseline characteristics, comparisons between users and non-users of AHD, and between patients with high and low MSC.

All patientsUsers of antihypertensive drugsHigh midnight salivary cortisol (≥9.3 nmol/L)
YesNoPaYesNoPa
n1966013634162
Sex
 Men106 (54)38 (63)68 (50)0.09017 (50)89 (55)0.71
 Women90 (46)22 (37)68 (50)17 (50)73 (45)
Age (years)43 (32, 51; 18–59)49 (40, 55)40 (29, 49)<0.001b48 (42, 53)42 (29, 50)0.002
Diabetes duration (years)20 (11, 29; 1–55)29 (20, 35)16 (9, 26)<0.001b22 (15, 33)19 (10, 29)0.28
MSC (nmol/L)5.0 (3.1, 7.5; 1.9–47.0)5.4 (3.0, 8.4)4.9 (3.2, 7.0)0.36b12.0 (10.8, 14.2)4.5 (2.9, 6.1)<0.001
High MSC (≥9.3 nmol/L)34 (17)12 (20)22 (16)0.54
Systolic BP (mmHg)120 (110, 130; 90–160)130 (121, 139)120 (110, 125)<0.001b125 (120, 135)120 (110, 130)0.030
High systolic BP (>130 mmHg)33 (17)19 (32)14 (10)0.00113 (38)20 (12)0.001
Diastolic BP (mmHg)70 (70, 75; 55–100)70 (70, 78)70 (65, 75)0.058b70 (70, 78)70 (69, 75)0.34
High diastolic BP (>80 mmHg)9 (5)5 (8)4 (3)0.141 (3)8 (5)>0.99
Abdominal obesityc29 (15)11 (19)18 (14)0.395 (15)24 (15)>0.99
Hypoglycaemia (severe episodes)9 (5)1 (2)8 (6)0.281 (3)8 (5)>0.99
HbA1c
 mmol/mol63 (54, 71; 25–110)64 (53, 74)61 (54, 69)0.1862 (54, 71)63 (53, 71)0.88
 %7.9 (7.1, 8.6; 4.4–12.2)8.0 (7.0, 8.9)7.8 (7.1, 8.4)7.8 (7.1, 8.6)7.9 (7.0, 8.6)
P-creatinined (µmol/L)70 (62, 77; 28–182)70 (62, 80)68 (61, 76)0.16b66 (58, 71)70 (62, 78)0.027
Smokinge16 (9)6 (10)10 (8)0.598 (24)8 (5)0.002
Physical inactivityf19 (10)5 (8)14 (11)0.807 (21)12 (8)0.054
Depression20 (10)8 (13)12 (9)0.449 (26)11 (7)0.002
AHD60 (31)12 (35)48 (30)0.54
Antidepressants13 (7)6 (10)7 (5)0.224 (12)9 (6)0.25
Continuous s.c. insulin infusion20 (10)5 (8)15 (11)0.803 (9)17 (10)>0.99

Results are presented as median (q1, q3; min-max) or n (%).

aFisher’s exact test unless otherwise indicated. bMann–Whitney U test. Missing values for all/users of AHD/non-users of AHD: cAbdominal obesity n = 6/1/5; dcreatinine n = 7/1/6; esmoking n = 10/1/9; fphysical inactivity n = 12/1/11.

In Table 2 comparisons are presented between patients with high and low systolic BP. In the users of AHD, the patients with high systolic BP had higher prevalence of high MSC (P = 0.039). In the non-users of AHD, patients with high systolic BP had higher prevalence of physical inactivity (P = 0.009), high MSC (P = 0.012), depression (P = 0.022), and abdominal obesity (P = 0.025).

Table 2

Comparisons between patients with high and low systolic BP for all, users and non-users of antihypertensive drugs.

High systolic BP (>130 mmHg)
All patientsUsers of antihypertensive drugsNon-users of antihypertensive drugs
YesNoPaYesNoPaYesNoPa
n33163194114122
Sex
 Men22 (67)84 (52)0.1313 (68)25 (61)0.779 (64)59 (48)0.40
 Women11 (33)79 (48)6 (34)16 (39)5 (36)63 (52)
Age (years)51 (44, 56)42 (29, 50)<0.001b54 (51, 58)45 (34, 52)0.003b45 (40, 49)38 (28, 49)0.12b
Diabetes duration (years)25 (14, 35)19 (10, 29)0.082b29 (18, 44)28 (21, 35)0.99b22 (8, 29)16 (9, 26)0.39b
High MSC (≥9.3 nmol/L)13 (39)21 (13)0.0017 (37)5 (12)0.0396 (43)16 (13)0.012
Systolic BP (mmHg)140 (135, 140)120 (110, 125)<0.001b140 (140, 145)125 (120, 130)<0.001b135 (135, 140)120 (110, 125)<0.001b
High diastolic BP (>80 mmHg)5 (15)4 (2)0.0083 (16)2 (5)0.312 (14)2 (2)0.053
Abdominal obesity9 (27)20 (13)0.0584 (21)7 (18)0.735 (36)13 (11)0.025
Hypoglycaemia (severe episodes)2 (6)7 (4)0.651 (5)00.321 (7)7 (6)0.59
HbA1c
 mmol/mol60 (55, 71)63 (53, 70)0.54b64 (53, 74)65 (54, 73)0.94b60 (55, 71)61 (53, 69)0.69b
 %7.7 (7.2, 8.7)7.9 (7.0, 8.5)8.0 (7.0, 8.9)8.1 (7.1, 8.8)7.7 (7.2, 8.6)7.8 (7.0, 8.4)
P-creatinine (µmol/L)70 (57, 86)69 (62, 76)0.62b71 (60, 88)70 (63, 78)0.86b70 (50, 83)68 (61, 76)0.67b
Smoking5 (15)11 (7)0.174 (10)2 (10)>0.993 (21)7 (6)0.081
Physical inactivity7 (21)12 (8)0.0512 (10)3 (8)0.655 (36)9 (8)0.009
Depression8 (24)12 (7)0.0084 (21)4 (9)0.254 (29)8 (7)0.022
AHD19 (58)41 (25)0.001
Antidepressants2 (6)11 (7)>0.9906 (15)0.162 (14)5 (4)0.15

Results are presented as median (q1, q3) or n (%).

aFisher’s exact test unless otherwise indicated. bMann–Whitney U test. For missing values, see Table 1.

In Table 3 associations with high systolic BP are presented for all patients. Physical inactivity (adjusted odds ratio (AOR) 6.5), high MSC (AOR 3.9), abdominal obesity (AOR 3.7), AHD (AOR 2.9), age (per year) (AOR 1.07), and p-creatinine (per µmol/L) (AOR 1.03) were associated with high systolic BP.

Table 3

Associations with high systolic BP in all patients.

High systolic BP (>130 mmHg)
COR (95% CI)PAOR (95% CI)Pa
Sex (men)1.9 (0.9–4.1)0.121.5 (0.5–4.2)0.42
Age (per year)1.08 (1.04–1.12)0.0011.07 (1.02–1.13)0.012
Diabetes duration (per year)1.03 (1.00–1.06)0.0520.99 (0.95–1.03)0.57
High MSC (≥9.3 nmol/L)4.4 (1.9–10.1)0.0013.9 (1.4–10.6)0.007
Abdominal obesity2.6 (1.0–6.3)0.0403.7 (1.2–11.8)0.026
Hypoglycaemia (severe episodes)1.4 (0.3–7.2)0.67
HbA1c (mmol/mol)1.02 (0.99–1.05)0.201.02 (0.99–1.05)0.20
P-creatinine (per µmol/L)1.02 (1.00–1.04)0.0391.03 (1.00–1.05)0.043
Smoking2.3 (0.7–7.2)0.15
Physical inactivity3.1 (1.1–8.7)0.0296.5 (1.5–28.6)0.013
Depression4.0 (1.5–10.8)0.0061.9 (0.6–6.6)0.29
AHD4.0 (1.9–8.8)<0.0012.9 (1.1–7.3)0.027
Antidepressants0.9 (0.2–4.2)0.88

aMultiple logistic regression analyses (Backward: Wald): Variables with P values ≤0.10 for the CORs, sex and age are included in the analyses; n = a180; Nagelkerke R2: a0.341; Hosmer and Lemeshow Test: a0.142.

In Table 4 associations with high systolic BP are presented separately for users and non-users of AHD. In the users of AHD, high MSC (AOR 4.1) and age (per year) (AOR 1.11) were associated with high systolic BP. In the non-users of AHD, abdominal obesity (AOR 27.4), physical inactivity (AOR 14.7), male sex (AOR 9.0), smoking (AOR 7.9), and age (per year) (AOR 1.08), were associated with high systolic BP.

Table 4

Associations with high systolic BP for users and non-users of AHD.

High systolic BP (>130 mmHg)
Users of antihypertensive drugsNon-users of antihypertensive drugs
COR (95% CI)PAOR (95% CI)PaCOR (95% CI)PAOR (95 CI)Pb
Sex (men)1.4 (0.4–4.4)0.580.8 (0.2–3.2)0.781.9 (0.6–6.1)0.269.0 (1.3–63.3)0.028
Age (per year)1.10 (1.02–1.19)0.0101.01 (1.02–1.21)0.0141.04 (0.99–1.10)0.111.08 (1.01–1.16)0.027
Diabetes duration (per year)1.00 (0.96–1.05)0.971.02 (097–1.07)0.38
High MSC (≥9.3 nmol/L)4.2 (1.1–15.7)0.0334.1 (1.0–16.6)0.0485.0 (1.5–16.2)0.0082.7 (0.6–12.9)0.21
Abdominal obesity1.3 (0.3–5.0)0.744.4 (1.3–15.3)0.01827.4 (3.3–226)0.002
Hypoglycaemia (severe episodes)>0.991.3 (0.1–11.0)0.84
HbA1c (mmol/mol)1.01 (0.96–1.05)0.811.02 (0.98–1.07)0.27
P-creatinine (per µmol/L)1.01 (0.99–1.04)0.191.00 (0.95–1.05)0.96
Smoking1.1 (0.2–6.4)0.954.1 (0.9–18.3)0.0627.9 (1.2–53.2)0.033
Physical inactivity1.5 (0.2–9.5)0.709.3 (1.7–22.8)0.00514.7 (2.7–81.7)0.002
Depression2.5 (0.5–11.2)0.245.7 (1.5–22.3)0.0123.2 (0.5–20.1)0.21
Antidepressants>0.993.9 (0.7c22.3)0.13

a,bMultiple logistic regression analyses (Backward: Wald): Variables with P values ≤0.10 for the CORs, sex and age are included in the analyses; n = a60/b123; Nagelkerke R2: a0.277/b0.381; Hosmer and Lemeshow Test: a0.154/b0.136.

There were no associations between high MSC and high diastolic BP, neither for all patients (P = 0.63), users of AHD (P > 0.99), nor non-users of AHD (P = 0.63).

Discussion

The principal finding in this study of 196 adult patients with T1D was that patients with high systolic BP (>130 mmHg) compared to patients with low systolic BP, had higher prevalence of high MSC (≥9.3 nmol/L). This was the case for both users and non-users of AHD. In all patients, physical inactivity, high MSC, abdominal obesity, AHD, p-creatinine, and age, were independently associated with high systolic BP. In the users of AHD, high MSC and age were associated with high systolic BP. In the non-users of AHD, abdominal obesity, physical inactivity, male sex, smoking, and age, were associated with high systolic BP. In the non-users of AHD, high MSC was not independently associated with systolic BP. No association between high diastolic BP (≥80 mmHg) and high MSC was found in any group.

The first strength of this study was that the population of patients with T1D was well defined. Patients with severe somatic or psychiatric comorbidities and/or substance abuse were excluded. Of particular importance is that no patients with diagnosed Cushing’s syndrome/disease (4, 5, 7), ESRD (4, 6) or severe substance abuse were included (25, 26). All patients using systemic corticosteroids, and two patients using topical steroids with extreme MSC values were excluded as contamination was suspected (22). We have previously controlled that the MSC levels did not differ between users and non-users of inhaled steroids, and we have performed non-response analyses (22). The non-response analyses showed no differences regarding age, diabetes duration, sex, metabolic variables, smoking, physical inactivity, or depression, between those who delivered and those who did not deliver MSC samples (22). Second, salivary cortisol measurement has advantages compared to blood measurements as it is non-invasive. Blood sampling can be stressful leading to increased cortisol secretion. Beneficial is also that participants can collect samples in their normal environment (31). Third, the cut-off level we chose to indicate high MSC has clinical implications. In previous research this cut-off level for high MSC was highly predictive of Cushing’s disease in patients with clinical features of hypercortisolism (33). Fourth, we presented our results for all patients, and separately for users and non-users of AHD. Fifth, we have adjusted for relevant variables such as age, sex, glycaemic control, abdominal obesity, severe hypoglycaemia episodes, depression, smoking, physical inactivity, and kidney function, which all have been associated with either hypertension or increased cortisol secretion, or both (4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 21, 22, 23, 24, 27, 28).

The main limitation was that only one MSC sample was collected from each patient. Due to the inconvenience of midnight sampling, we anticipated a lower participation rate if we had demanded repeated samplings. A second limitation was that we did not perform any dexamethasone suppression tests for the participants with high MSC values. A third limitation was that we did not have any matched controls without T1D.

There is clear evidence from previous research that increased cortisol secretion contributes to the development of hypertension (4, 5, 6, 7), which in turn has impact on the development of atherosclerosis, CV disease and mortality (3, 7, 15, 16, 17). We found a clear independent association between high MSC and high systolic BP in all patients which supports previous research (4, 5, 6, 7). In the users of AHD, the association between high MSC and high systolic BP was direct without any mediators. However, the number of patients using AHD was low, and the CIs for the CORs for the potential mediators (smoking, physical inactivity and depression) were wide, which indicate a profound statistical uncertainty of these estimates.

Despite the even higher prevalence of high MSC secretion in the non-users of AHD with high systolic BP, the association between MSC and high systolic BP was not sustained after adjustments for age, depression, physical inactivity and smoking. We have previously shown that these four variables were associated with high MSC in these patients (22). In the non-users of AHD, we found three targets for intervention in order to reduce high systolic BP – abdominal obesity, physical inactivity and smoking – which is in accordance with previous research (8, 10, 11). We did not find any association between depression and hypertension, which differs from previous research (12). As the CI for the AORs between depression and high systolic blood pressure was very wide, indicating a statistical uncertainty, we suggest exploration in a larger population sample. The association between male sex and high systolic BP in the sub group of non-AHD users, is in accordance with previous research (13).

In this study we clearly showed that patients with T1D with high systolic BP had a high prevalence of high MSC, both in users and non-users of AHD. Increased cortisol secretion is one important cause of treatment-resistant hypertension according to previous research (14). In clinical practice we suggest that MSC should be measured in T1D patients with high systolic BP. We also suggest in case of high MSC, that a dexamethasone test should be performed to explore whether the patients have impaired glucocorticoid-negative feedback (14, 18, 21). The cut-off value we chose (MSC ≥9.3 nmol/L) showed previously a high predictive value to distinguish Cushing’s disease from pseudo-Cushing’s syndrome (33). Several types of disturbances of the HPA axis functioning in T1D have been demonstrated (18, 19, 20, 21), but other factors might contribute to increased MSC secretion, which should be explored. We have previously shown that depression, physical inactivity and smoking were associated with high MSC in these patients with T1D (22). We suggest further research on causes and consequences of HPA axis dysfunction in patients with T1D. We are planning to explore the prevalence of high MSC in a normative Swedish population sample for comparison in further research.

In conclusion, physical inactivity, high MSC, abdominal obesity, AHD, p-creatinine, and age, were independently associated with high systolic BP in adult patients with T1D. Our hypothesis that high MSC secretion might contribute to hypertension and to treatment failure of AHD was supported.

Declaration of interest

The authors declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported.

Funding

This research was supported by the Research and Development Fund of Region Kronoberg, Växjö, Sweden, and by the Research Council of South Eastern Sweden (FORSS), Linköping, Sweden. The funding sources were not involved in the collection, analysis and interpretation of data, in the writing of the report, or in the decision to submit the article for publication.

Acknowledgments

The authors are grateful to Anna Lindgren, PhD, Lund University, Centre of Mathematics, Lund, Sweden, for her statistical skills. They are also grateful to the specialist diabetes nurses and doctors who recruited the patients included in this study.

References

  • 1

    KatsarouAGudbjörnsdottirSRawshaniADabeleaDBonifacioEAndersonBJJacobsenLMSchatzDALernmarkÅ. Type 1 diabetes mellitus. Nature Reviews: Disease Primers 2017 17016. (https://doi.org/10.1038/nrdp.2017.16)

    • Search Google Scholar
    • Export Citation
  • 2

    LarssonSCWallinAHåkanssonNStackelbergOBäckMWolkA. Type 1 and type 2 diabetes mellitus and incidence of seven cardiovascular diseases. International Journal of Cardiology 2018 6670. (https://doi.org/10.1016/j.ijcard.2018.03.099)

    • Search Google Scholar
    • Export Citation
  • 3

    American Diabetes Association. Cardiovascular disease and risk management: standards of medical care in diabetes – 2018. Diabetes Care 2018 S86S104. (https://doi.org/10.2337/dc18-S009)

    • Search Google Scholar
    • Export Citation
  • 4

    WhitworthJABrownMAKellyJJWilliamsonPM. Mechanism of cortisol-induced hypertension in humans. Steroids 1995 7680. (https://doi.org/10.1016/0039-128X(94)00033-9)

    • Search Google Scholar
    • Export Citation
  • 5

    FeeldersRAPulgarSJKempelAPereiraAM. The burden of Cushing’s disease: clinical and health-related quality of life aspects. European Journal of Endocrinology 2012 311326. (https://doi.org/10.1530/EJE-11-1095)

    • Search Google Scholar
    • Export Citation
  • 6

    KellyJJMangosGWilliamsonPMWhitworthJA. Cortisol and hypertension. Clinical and Experimental Pharmacology and Physiology: Supplement 1998 S51S56. (https://doi.org/10.1111/j.1440-1681.1998.tb02301.x)

    • Search Google Scholar
    • Export Citation
  • 7

    IsidoriAMGraziadioCParagliolaRMCozzolinoAAmbrogioAGColaoACorselloSMPivonelloR & ABC Study Group. The hypertension of Cushing’s syndrome: controversies in the pathophysiology and focus on cardiovascular complications. Journal of Hypertension 2015 4460. (https://doi.org/10.1097/HJH.0000000000000415)

    • Search Google Scholar
    • Export Citation
  • 8

    RedonJ. Hypertension in obesity. Nutrition Metabolism and Cardiovascular Diseases 2001 344353.

  • 9

    MelinEOThulesiusHOHillmanMLandin-OlssonMThunanderM. Abdominal obesity in type 1 diabetes associated with gender, cardiovascular risk factors and complications, and difficulties achieving treatment targets: a cross sectional study at a secondary care diabetes clinic. BMC Obesity 2018 15. (https://doi.org/10.1186/s40608-018-0193-5)

    • Search Google Scholar
    • Export Citation
  • 10

    KokkinosPSheriffHKheirbekR. Physical inactivity and mortality risk. Cardiology Research and Practice 2011 924945. (https://doi.org/10.4061/2011/924945)

    • Search Google Scholar
    • Export Citation
  • 11

    VirdisAGiannarelliCFritsch NevesMFTaddeiSGhiadoniL. Cigarette smoking and hypertension. Current Pharmaceutical Design 2010 25182525. (https://doi.org/10.2174/138161210792062920)

    • Search Google Scholar
    • Export Citation
  • 12

    JonasBSFranksPIngramDD. Are symptoms of anxiety and depression risk factors for hypertension? Longitudinal evidence from the National Health and Nutrition Examination Survey I Epidemiologic Follow-up Study. Archives of Family Medicine 1997 4349. (https://doi.org/10.1001/archfami.6.1.43)

    • Search Google Scholar
    • Export Citation
  • 13

    CollierAGhoshSHairMWaughN. Gender differences and patterns of cardiovascular risk factors in Type 1 and Type 2 diabetes: a population-based analysis from a Scottish region. Diabetic Medicine 2015 4246. (https://doi.org/10.1111/dme.12569)

    • Search Google Scholar
    • Export Citation
  • 14

    SloandJABalakrishnanSLFongMWBisognanoJD. Evaluation and treatment of resistant hypertension. Cardiology Journal 2007 329339.

  • 15

    DekkerMJKoperJWvan AkenMOPolsHAPHofmanAde JongFHKirschbaumCWittemanJCMLambertsSWJTiemeierH. Salivary cortisol is related to atherosclerosis of carotid arteries. Journal of Clinical Endocrinology and Metabolism 2008 37413747. (https://doi.org/10.1210/jc.2008-0496)

    • Search Google Scholar
    • Export Citation
  • 16

    ReynoldsRMLabadJStrachanMWBraunAFowkesFGLeeAJFrierBMSecklJRWalkerBRPriceJF Elevated fasting plasma cortisol is associated with ischemic heart disease and its risk factors in people with type 2 diabetes: the Edinburgh Type 2 diabetes study. Journal of Clinical Endocrinology and Metabolism 2010 16021608. (https://doi.org/10.1210/jc.2009-2112)

    • Search Google Scholar
    • Export Citation
  • 17

    KumariMShipleyMStaffordMKivimakiM. Association of diurnal patterns in salivary cortisol with all-cause and cardiovascular mortality: findings from the Whitehall II study. Journal of Clinical Endocrinology and Metabolism 2011 14781485. (https://doi.org/10.1210/jc.2010-2137)

    • Search Google Scholar
    • Export Citation
  • 18

    KorczakDJPereiraSKoulajianKMatejcekAGiaccaA. Type 1 diabetes mellitus and major depressive disorder: evidence for a biological link. Diabetologia 2011 24832493. (https://doi.org/10.1007/s00125-011-2240-3)

    • Search Google Scholar
    • Export Citation
  • 19

    LebingerTGSaengerPFukushimaDKKreamJWuRFinkelsteinJW. Twenty-four-hour cortisol profiles demonstrate exaggerated nocturnal rise in diabetic children. Diabetes Care 1983 506509. (https://doi.org/10.2337/diacare.6.5.506)

    • Search Google Scholar
    • Export Citation
  • 20

    RoyMSRoyAGallucciWTCollierBYoungKKamilarisTCChrousosGP. The ovine corticotropin-releasing hormone-stimulation test in type I diabetic patients and controls: suggestion of mild chronic hypercortisolism. Metabolism 1993 696700. (https://doi.org/10.1016/0026-0495(93)90235-G)

    • Search Google Scholar
    • Export Citation
  • 21

    ChanOInouyeKRiddellMCVranicMMatthewsSG. Diabetes and the hypothalamo-pituitary-adrenal (HPA) axis. Minerva Endocrinologica 2003 87102.

    • Search Google Scholar
    • Export Citation
  • 22

    MelinEOThunanderMLandin-OlssonMHillmanMThulesiusHO. Depression, smoking, physical inactivity and season independently associated with midnight salivary cortisol in type 1 diabetes. BMC Endocrine Disorders 2014 75. (https://doi.org/10.1186/1472-6823-14-75)

    • Search Google Scholar
    • Export Citation
  • 23

    BadrickEKirschbaumCKumariM. The relationship between smoking status and cortisol secretion. Journal of Clinical Endocrinology and Metabolism 2007 819824. (https://doi.org/10.1210/jc.2006-2155)

    • Search Google Scholar
    • Export Citation
  • 24

    GoldPWChrousosGP. Organization of the stress system and its dysregulation in melancholic and atypical depression: high vs low CRH/NE states. Molecular Psychiatry 2002 254275. (https://doi.org/10.1038/sj.mp.4001032)

    • Search Google Scholar
    • Export Citation
  • 25

    LovalloWR. Cortisol secretion patterns in addiction and addiction risk. International Journal of Psychophysiology 2006 195202. (https://doi.org/10.1016/j.ijpsycho.2005.10.007)

    • Search Google Scholar
    • Export Citation
  • 26

    SarnyaiZShahamYHeinrichsSC. The role of corticotropin-releasing factor in drug addiction. Pharmacological Reviews 2001 209244.

  • 27

    LiXXiangXHuJGoswamiRYangSZhangAWangYLiQBiX. Association between serum cortisol and chronic kidney disease in patients with essential hypertension. Kidney and Blood Pressure Research 2016 384391. (https://doi.org/10.1159/000443435)

    • Search Google Scholar
    • Export Citation
  • 28

    TraustadottirTBoschPRMattKS. The HPA axis response to stress in women: effects of aging and fitness. Psychoneuroendocrinology 2005 392402. (https://doi.org/10.1016/j.psyneuen.2004.11.002)

    • Search Google Scholar
    • Export Citation
  • 29

    MelinEODerekeJThunanderMHillmanM. Soluble CD163 was linked to galectin-3, diabetic retinopathy and antidepressants in type 1 diabetes. Endocrine Connections 2018 7 13431353. (https://doi.org/10.1530/EC-18-0336)

    • Search Google Scholar
    • Export Citation
  • 30

    MelinEOThunanderMLandin-OlssonMHillmanMThulesiusHO. Depression differed by midnight cortisol secretion, alexithymia and anxiety between diabetes types: a cross sectional comparison. BMC Psychiatry 2017 335. (https://doi.org/10.1186/s12888-017-1495-8)

    • Search Google Scholar
    • Export Citation
  • 31

    GarianiKMarques-VidalPWaeberGVollenweiderPJornayvazFR. Salivary cortisol is not associated with incident insulin resistance or type 2 diabetes mellitus. Endocrine Connections 2019 8 870877. (https://doi.org/10.1530/EC-19-0251)

    • Search Google Scholar
    • Export Citation
  • 32

    BelayaZEIljinAVMelnichenkoGARozhinskayaLYDragunovaNVDzeranovaLKButrovaSATroshinaEADedovII. Diagnostic performance of late-night salivary cortisol measured by automated electrochemiluminescence immunoassay in obese and overweight patients referred to exclude Cushing’s syndrome. Endocrine 2012 494500. (https://doi.org/10.1007/s12020-012-9658-3)

    • Search Google Scholar
    • Export Citation
  • 33

    AlwaniRASchmit JongbloedLWde JongFHvan der LelyAJde HerderWWFeeldersRA. Differentiating between Cushing’s disease and pseudo-Cushing’s syndrome: comparison of four tests. European Journal of Endocrinology 2014 477486. (https://doi.org/10.1530/EJE-13-0702)

    • Search Google Scholar
    • Export Citation
  • 34

    The National Board of Health and Welfare. Swedish National Guidelines for Diabetes. Stockholm, Sweden: Socialstyrelsen2009. (available at: https://www.socialstyrelsen.se/)

    • Search Google Scholar
    • Export Citation
  • 35

    KleinSAllisonDBHeymsfieldSBKelleyDELeibelRLNonasCKahnR. Waist circumference and cardiometabolic risk: a consensus statement from shaping America’s health: Association for Weight Management and Obesity Prevention; NAASO, the Obesity Society; the American Society for Nutrition; and the American Diabetes Association. Obesity 2007 10611067. (https://doi.org/10.1038/oby.2007.632)

    • Search Google Scholar
    • Export Citation
  • 36

    MelinEOThunanderMSvenssonRLandin-OlssonMThulesiusHO. Depression, obesity and smoking were independently associated with inadequate glycemic control in patients with Type 1 diabetes. European Journal of Endocrinology 2013 861869. (https://doi.org/10.1530/EJE-13-0137)

    • Search Google Scholar
    • Export Citation
  • 37

    MelinEOSvenssonRThunanderMHillmanMThulesiusHOLandin-OlssonM. Gender, alexithymia and physical inactivity associated with abdominal obesity in type 1 diabetes mellitus: a cross sectional study at a secondary care hospital diabetes clinic. BMC Obesity 2017 21. (https://doi.org/10.1186/s40608-017-0157-1)

    • Search Google Scholar
    • Export Citation
  • 38

    ZigmondASSnaithRP. The hospital anxiety and depression scale. Acta Psychiatrica Scandinavica 1983 361370. (https://doi.org/10.1111/j.1600-0447.1983.tb09716.x)

    • Search Google Scholar
    • Export Citation
  • 39

    MelinEODerekeJThunanderMHillmanM. Depression in type 1 diabetes was associated with high levels of circulating galectin-3. Endocrine Connections 2018 819828. (https://doi.org/10.1530/EC-18-0108)

    • Search Google Scholar
    • Export Citation
  • 40

    MelinEOThulesiusHOHillmanMSvenssonRLandin-OlssonMThunanderM. Lower HDL-cholesterol, a known marker of cardiovascular risk, was associated with depression in type 1 diabetes: a cross sectional study. Lipids in Health and Disease 2019 65. (https://doi.org/10.1186/s12944-019-1009-4)

    • Search Google Scholar
    • Export Citation

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  • 1

    KatsarouAGudbjörnsdottirSRawshaniADabeleaDBonifacioEAndersonBJJacobsenLMSchatzDALernmarkÅ. Type 1 diabetes mellitus. Nature Reviews: Disease Primers 2017 17016. (https://doi.org/10.1038/nrdp.2017.16)

    • Search Google Scholar
    • Export Citation
  • 2

    LarssonSCWallinAHåkanssonNStackelbergOBäckMWolkA. Type 1 and type 2 diabetes mellitus and incidence of seven cardiovascular diseases. International Journal of Cardiology 2018 6670. (https://doi.org/10.1016/j.ijcard.2018.03.099)

    • Search Google Scholar
    • Export Citation
  • 3

    American Diabetes Association. Cardiovascular disease and risk management: standards of medical care in diabetes – 2018. Diabetes Care 2018 S86S104. (https://doi.org/10.2337/dc18-S009)

    • Search Google Scholar
    • Export Citation
  • 4

    WhitworthJABrownMAKellyJJWilliamsonPM. Mechanism of cortisol-induced hypertension in humans. Steroids 1995 7680. (https://doi.org/10.1016/0039-128X(94)00033-9)

    • Search Google Scholar
    • Export Citation
  • 5

    FeeldersRAPulgarSJKempelAPereiraAM. The burden of Cushing’s disease: clinical and health-related quality of life aspects. European Journal of Endocrinology 2012 311326. (https://doi.org/10.1530/EJE-11-1095)

    • Search Google Scholar
    • Export Citation
  • 6

    KellyJJMangosGWilliamsonPMWhitworthJA. Cortisol and hypertension. Clinical and Experimental Pharmacology and Physiology: Supplement 1998 S51S56. (https://doi.org/10.1111/j.1440-1681.1998.tb02301.x)

    • Search Google Scholar
    • Export Citation
  • 7

    IsidoriAMGraziadioCParagliolaRMCozzolinoAAmbrogioAGColaoACorselloSMPivonelloR & ABC Study Group. The hypertension of Cushing’s syndrome: controversies in the pathophysiology and focus on cardiovascular complications. Journal of Hypertension 2015 4460. (https://doi.org/10.1097/HJH.0000000000000415)

    • Search Google Scholar
    • Export Citation
  • 8

    RedonJ. Hypertension in obesity. Nutrition Metabolism and Cardiovascular Diseases 2001 344353.

  • 9

    MelinEOThulesiusHOHillmanMLandin-OlssonMThunanderM. Abdominal obesity in type 1 diabetes associated with gender, cardiovascular risk factors and complications, and difficulties achieving treatment targets: a cross sectional study at a secondary care diabetes clinic. BMC Obesity 2018 15. (https://doi.org/10.1186/s40608-018-0193-5)

    • Search Google Scholar
    • Export Citation
  • 10

    KokkinosPSheriffHKheirbekR. Physical inactivity and mortality risk. Cardiology Research and Practice 2011 924945. (https://doi.org/10.4061/2011/924945)

    • Search Google Scholar
    • Export Citation
  • 11

    VirdisAGiannarelliCFritsch NevesMFTaddeiSGhiadoniL. Cigarette smoking and hypertension. Current Pharmaceutical Design 2010 25182525. (https://doi.org/10.2174/138161210792062920)

    • Search Google Scholar
    • Export Citation
  • 12

    JonasBSFranksPIngramDD. Are symptoms of anxiety and depression risk factors for hypertension? Longitudinal evidence from the National Health and Nutrition Examination Survey I Epidemiologic Follow-up Study. Archives of Family Medicine 1997 4349. (https://doi.org/10.1001/archfami.6.1.43)

    • Search Google Scholar
    • Export Citation
  • 13

    CollierAGhoshSHairMWaughN. Gender differences and patterns of cardiovascular risk factors in Type 1 and Type 2 diabetes: a population-based analysis from a Scottish region. Diabetic Medicine 2015 4246. (https://doi.org/10.1111/dme.12569)

    • Search Google Scholar
    • Export Citation
  • 14

    SloandJABalakrishnanSLFongMWBisognanoJD. Evaluation and treatment of resistant hypertension. Cardiology Journal 2007 329339.

  • 15

    DekkerMJKoperJWvan AkenMOPolsHAPHofmanAde JongFHKirschbaumCWittemanJCMLambertsSWJTiemeierH. Salivary cortisol is related to atherosclerosis of carotid arteries. Journal of Clinical Endocrinology and Metabolism 2008 37413747. (https://doi.org/10.1210/jc.2008-0496)

    • Search Google Scholar
    • Export Citation
  • 16

    ReynoldsRMLabadJStrachanMWBraunAFowkesFGLeeAJFrierBMSecklJRWalkerBRPriceJF Elevated fasting plasma cortisol is associated with ischemic heart disease and its risk factors in people with type 2 diabetes: the Edinburgh Type 2 diabetes study. Journal of Clinical Endocrinology and Metabolism 2010 16021608. (https://doi.org/10.1210/jc.2009-2112)

    • Search Google Scholar
    • Export Citation
  • 17

    KumariMShipleyMStaffordMKivimakiM. Association of diurnal patterns in salivary cortisol with all-cause and cardiovascular mortality: findings from the Whitehall II study. Journal of Clinical Endocrinology and Metabolism 2011 14781485. (https://doi.org/10.1210/jc.2010-2137)

    • Search Google Scholar
    • Export Citation
  • 18

    KorczakDJPereiraSKoulajianKMatejcekAGiaccaA. Type 1 diabetes mellitus and major depressive disorder: evidence for a biological link. Diabetologia 2011 24832493. (https://doi.org/10.1007/s00125-011-2240-3)

    • Search Google Scholar
    • Export Citation
  • 19

    LebingerTGSaengerPFukushimaDKKreamJWuRFinkelsteinJW. Twenty-four-hour cortisol profiles demonstrate exaggerated nocturnal rise in diabetic children. Diabetes Care 1983 506509. (https://doi.org/10.2337/diacare.6.5.506)

    • Search Google Scholar
    • Export Citation
  • 20

    RoyMSRoyAGallucciWTCollierBYoungKKamilarisTCChrousosGP. The ovine corticotropin-releasing hormone-stimulation test in type I diabetic patients and controls: suggestion of mild chronic hypercortisolism. Metabolism 1993 696700. (https://doi.org/10.1016/0026-0495(93)90235-G)

    • Search Google Scholar
    • Export Citation
  • 21

    ChanOInouyeKRiddellMCVranicMMatthewsSG. Diabetes and the hypothalamo-pituitary-adrenal (HPA) axis. Minerva Endocrinologica 2003 87102.

    • Search Google Scholar
    • Export Citation
  • 22

    MelinEOThunanderMLandin-OlssonMHillmanMThulesiusHO. Depression, smoking, physical inactivity and season independently associated with midnight salivary cortisol in type 1 diabetes. BMC Endocrine Disorders 2014 75. (https://doi.org/10.1186/1472-6823-14-75)

    • Search Google Scholar
    • Export Citation
  • 23

    BadrickEKirschbaumCKumariM. The relationship between smoking status and cortisol secretion. Journal of Clinical Endocrinology and Metabolism 2007 819824. (https://doi.org/10.1210/jc.2006-2155)

    • Search Google Scholar
    • Export Citation
  • 24

    GoldPWChrousosGP. Organization of the stress system and its dysregulation in melancholic and atypical depression: high vs low CRH/NE states. Molecular Psychiatry 2002 254275. (https://doi.org/10.1038/sj.mp.4001032)

    • Search Google Scholar
    • Export Citation
  • 25

    LovalloWR. Cortisol secretion patterns in addiction and addiction risk. International Journal of Psychophysiology 2006 195202. (https://doi.org/10.1016/j.ijpsycho.2005.10.007)

    • Search Google Scholar
    • Export Citation
  • 26

    SarnyaiZShahamYHeinrichsSC. The role of corticotropin-releasing factor in drug addiction. Pharmacological Reviews 2001 209244.

  • 27

    LiXXiangXHuJGoswamiRYangSZhangAWangYLiQBiX. Association between serum cortisol and chronic kidney disease in patients with essential hypertension. Kidney and Blood Pressure Research 2016 384391. (https://doi.org/10.1159/000443435)

    • Search Google Scholar
    • Export Citation
  • 28

    TraustadottirTBoschPRMattKS. The HPA axis response to stress in women: effects of aging and fitness. Psychoneuroendocrinology 2005 392402. (https://doi.org/10.1016/j.psyneuen.2004.11.002)

    • Search Google Scholar
    • Export Citation
  • 29

    MelinEODerekeJThunanderMHillmanM. Soluble CD163 was linked to galectin-3, diabetic retinopathy and antidepressants in type 1 diabetes. Endocrine Connections 2018 7 13431353. (https://doi.org/10.1530/EC-18-0336)

    • Search Google Scholar
    • Export Citation
  • 30

    MelinEOThunanderMLandin-OlssonMHillmanMThulesiusHO. Depression differed by midnight cortisol secretion, alexithymia and anxiety between diabetes types: a cross sectional comparison. BMC Psychiatry 2017 335. (https://doi.org/10.1186/s12888-017-1495-8)

    • Search Google Scholar
    • Export Citation
  • 31

    GarianiKMarques-VidalPWaeberGVollenweiderPJornayvazFR. Salivary cortisol is not associated with incident insulin resistance or type 2 diabetes mellitus. Endocrine Connections 2019 8 870877. (https://doi.org/10.1530/EC-19-0251)

    • Search Google Scholar
    • Export Citation
  • 32

    BelayaZEIljinAVMelnichenkoGARozhinskayaLYDragunovaNVDzeranovaLKButrovaSATroshinaEADedovII. Diagnostic performance of late-night salivary cortisol measured by automated electrochemiluminescence immunoassay in obese and overweight patients referred to exclude Cushing’s syndrome. Endocrine 2012 494500. (https://doi.org/10.1007/s12020-012-9658-3)

    • Search Google Scholar
    • Export Citation
  • 33

    AlwaniRASchmit JongbloedLWde JongFHvan der LelyAJde HerderWWFeeldersRA. Differentiating between Cushing’s disease and pseudo-Cushing’s syndrome: comparison of four tests. European Journal of Endocrinology 2014 477486. (https://doi.org/10.1530/EJE-13-0702)

    • Search Google Scholar
    • Export Citation
  • 34

    The National Board of Health and Welfare. Swedish National Guidelines for Diabetes. Stockholm, Sweden: Socialstyrelsen2009. (available at: https://www.socialstyrelsen.se/)

    • Search Google Scholar
    • Export Citation
  • 35

    KleinSAllisonDBHeymsfieldSBKelleyDELeibelRLNonasCKahnR. Waist circumference and cardiometabolic risk: a consensus statement from shaping America’s health: Association for Weight Management and Obesity Prevention; NAASO, the Obesity Society; the American Society for Nutrition; and the American Diabetes Association. Obesity 2007 10611067. (https://doi.org/10.1038/oby.2007.632)

    • Search Google Scholar
    • Export Citation
  • 36

    MelinEOThunanderMSvenssonRLandin-OlssonMThulesiusHO. Depression, obesity and smoking were independently associated with inadequate glycemic control in patients with Type 1 diabetes. European Journal of Endocrinology 2013 861869. (https://doi.org/10.1530/EJE-13-0137)

    • Search Google Scholar
    • Export Citation
  • 37

    MelinEOSvenssonRThunanderMHillmanMThulesiusHOLandin-OlssonM. Gender, alexithymia and physical inactivity associated with abdominal obesity in type 1 diabetes mellitus: a cross sectional study at a secondary care hospital diabetes clinic. BMC Obesity 2017 21. (https://doi.org/10.1186/s40608-017-0157-1)

    • Search Google Scholar
    • Export Citation
  • 38

    ZigmondASSnaithRP. The hospital anxiety and depression scale. Acta Psychiatrica Scandinavica 1983 361370. (https://doi.org/10.1111/j.1600-0447.1983.tb09716.x)

    • Search Google Scholar
    • Export Citation
  • 39

    MelinEODerekeJThunanderMHillmanM. Depression in type 1 diabetes was associated with high levels of circulating galectin-3. Endocrine Connections 2018 819828. (https://doi.org/10.1530/EC-18-0108)

    • Search Google Scholar
    • Export Citation
  • 40

    MelinEOThulesiusHOHillmanMSvenssonRLandin-OlssonMThunanderM. Lower HDL-cholesterol, a known marker of cardiovascular risk, was associated with depression in type 1 diabetes: a cross sectional study. Lipids in Health and Disease 2019 65. (https://doi.org/10.1186/s12944-019-1009-4)

    • Search Google Scholar
    • Export Citation