OBJECTIVE

Water intake alters vasopressin secretion. Recent findings reveal an independent association between plasma copeptin, a surrogate for vasopressin, and risk of diabetes.

RESEARCH DESIGN AND METHODS

Participants were 3,615 middle-aged men and women, with normal baseline fasting glycemia (FG), who were recruited in a 9-year follow-up study. Odds ratios (ORs) and 95% CIs for the incidence of hyperglycemia (FG ≥6.1 mmol/L or treatment for diabetes) were calculated according to daily water intake classes based on a self-administered questionnaire.

RESULTS

During follow-up, there were 565 incident cases of hyperglycemia. After adjustment for confounding factors, ORs (95% CIs) for hyperglycemia associated with classes of water intake (<0.5 L, n = 677; 0.5 to <1.0 L, n = 1,754; and >1.0 L, n = 1,184) were 1.00, 0.68 (0.52–0.89), and 0.79 (0.59–1.05), respectively (P= 0.016).

CONCLUSIONS

Self-reported water intake was inversely and independently associated with the risk of developing hyperglycemia.

Copeptin, a stable glycopeptide comprising the COOH-terminal portion of the preprovasopressin, released in equimolar amounts as vasopressin, recently has been shown to represent an independent risk factor for diabetes (1). A causal link between vasopressin and glucose homeostasis is plausible because vasopressin induces gluconeogenesis in the rat liver and transiently increases glycemia in healthy humans and because vasopressin receptors are expressed in hepatocytes and pancreatic islets (29).

Vasopressin and copeptin secretion is known to depend on the level of hydration (10). Thus, we tested in initially normoglycemic participants of a large French cohort, whether water intake (W-Intake) was associated with the subsequent development of hyperglycemia or diabetes over a 9-year follow-up.

Study population

We included 3,615 French men and women, aged 30–65 years, with baseline fasting glycemia (FG) <6.1 mmol/L, who participated in the 9-year follow-up D.E.S.I.R. study (Data from Epidemiological Study on Insulin Resistance Syndrome). Volunteers were recruited and offered extensive health examinations every 3 years in western France. Participants provided written informed consent, and the protocol was approved by the ethics committee of Bicêtre Hospital, Kremlin-Bicêtre, France.

Incident hyperglycemia was identified by an FG ≥6.1 mmol/L or treatment for diabetes, and incident diabetes was identified by an FG ≥7.0 mmol/L or treatment of diabetes during at least one of the three follow-up examinations (years 3, 6, and 9).

Clinical and biochemical measures

Detailed methods have been reported previously (1113). Smoking, dietary habits, degree of physical activity, and alcohol consumption were assessed using a self-administered questionnaire. Mean daily intake of water, wine, beer or cider, and sweet beverages was categorized in the questionnaire into six mutually exclusive levels: none, <0.5, 0.5 to 1, 1 to 1.5, 1.5 to 2.0, and >2 L. In the present analyses, the levels were grouped into three classes: <0.5, 0.5 to 1, and >1 L. Other clinical and biological measurements are presented in the Supplementary Methods.

Statistical analyses

Skewed variables were log transformed. Results are presented as means (SD) or median (25th–75th percentiles) for quantitative variables and as percentages for qualitative variables. Baseline means and percentages were compared between the three W-Intake classes using ANOVA or χ2 tests. Logistic regression models were used to determine odds ratios (ORs) and 95% CIs corresponding to the comparison of incident hyperglycemia in middle and high classes of W-Intake in comparison with the lowest class. Adjustment variables were either known risk factors for type 2 diabetes or factors associated (P < 0.10) with hyperglycemia and W-Intake in our population.

Baseline characteristics of the 3,615 normoglycemic participants are presented according to their class of W-Intake (Table 1). Among them, during follow-up, 565 subjects became hyperglycemic and 202 developed diabetes. The daily W-Intake was negatively associated with the risk of new-onset hyperglycemia, even after adjustment for multiple metabolic risk factors. Compared with daily W-Intake of <0.5 L, ORs were 0.64 (95% CI 0.49–0.83) and 0.73 (0.55–0.97) for classes of 0.5–1.0 L and >1.0 L, respectively (P = 0.003). After further adjustments for intake of other beverages, the ORs were slightly attenuated: 0.68 (0.52–0.89) and 0.79 (0.59–1.05) for classes of 0.5–1.0 L and >1.0 L, respectively (P = 0.016) (Table 1). The relation was not linear (data not shown). With the two upper classes combined, the OR was 0.72 (0.56–0.92) (Supplementary Fig. 1). There was no interaction with several important characteristics, including those related to self-reported alcohol or tobacco consumption (Supplementary Table 1).

Table 1

Baseline characteristics of the study population and risk for new-onset hyperglycemia during follow-up, by classes of mean daily W-Intake


Daily W-Intake (L)
<0.5
 
0.5 to 1.0
 
>1.0
 
P for difference
 
General     
 n 677 1,754 1,184  
 Men (%) 48.6 47.9 45.4 0.31 
 Age (years) 46.4 (9.9) 47.3 (10.0) 46.3 (9.9) 0.001 
 BMI( kg/m224.1 (3.5) 24.4 (3.5) 24.7 (3.8) 0.001 
 Waist circumference (cm) 81.6 (10.7) 82.3 (11.0) 82.7 (11.6) 0.026 
 Physical activity (%)    0.0001 
  Low 28.7 25.7 19.4  
  Medium 56.1 54.6 52.6  
  High 15.2 19.8 28.0  
 Tobacco smoking (%)    0.0001 
  Never smokers 47.7 55.9 57.8  
  Ex-smokers 26.3 26.6 24.1  
  Current smokers 26.0 17.5 18.2  
Alcohol consumption (g/day) (%)    0.0001 
  Nonconsumers 22.0 23.0 30.7  
  1–10 24.7 27.2 31.2  
  10–20 8.1 8.4 6.7  
  >20 45.2 41.3 31.4  
 Creatininemia (μmol/L) 81.2 (13.0) 81.6 (13.0) 81.0 (12.9) 0.39 
 C-reactive protein* 1.00 (0.85–2.64) 0.87 (0.85–2.00) 0.85 (0.85–2.00) 0.49 
Blood pressure     
 Systolic (mmHg) 129 (15) 131 (15) 130 (15) 0.32 
 Diastolic (mmHg) 79 (10) 80 (9) 79 (9) 0.21 
 Hypertension (%) 32.5 34.3 32.4 0.50 
 Treated THZD/Furo (%) 3.7 2.2 3.2 0.07 
Metabolic data     
 Family history diabetes (%) 20.6 19.0 19.3 0.67 
 Fasting plasma glucose (mmol/L) 5.21 (0.45) 5.22 (0.44) 5.17 (0.44) 0.72 
 Fasting insulinemia (pmol/L) 42.7 (23.3) 45.0 (24.7) 44.1 (27.6) 0.08 
 HOMA-IR 1.40 (0.80) 1.48 (0.87) 1.43 (0.96) 0.10 
 HOMA-B 63 (46–89) 66 (46–92) 65 (47–91) 0.15 
 Total cholesterol (mmol/L) 5.76 (0.97) 5.72 (0.97) 5.66 (0.98) 0.007 
 Triglycerides (mmol/L) 1.14 (0.85) 1.09 (0.66) 1.09 (0.65) 0.15 
 HDL cholesterol (mmol/L)** 1.64 (0.41) 1.66 (0.43) 1.64 (0.44) 0.44 
 LDL cholesterol (mmol/L)** 3.39 (0.83) 3.35 (0.89) 3.32 (0.90) 0.032 
Other drinks     
Mean volume of sweet drinks (L) (%)    0.0001 
  <0.5 92.0 95.5 97.0  
  0.5 to 1.0 6.9 4.3 1.9  
  >1.0 1.0 0.2 1.1  
Mean volume of wine/day (L) (%)    0.0001 
  <0.5 89.1 93.9 96.4  
  0.5 to 1.0 9.9 6.1 3.6  
  >1.0 1.0 0.0 0.1  
Mean volume of beer or cider (L) (%)    0.056 
  <0.5 96.9 98.1 98.7  
  0.5 to 1.0 2.7 1.8 1.1  
Urine     
 Urine density (× 1,000) 1,019.6 (8.0) 1,019.3 (9.1) 1,017.9 (9.6) 0.0001 
ORs for new-onset hyperglycemia     
 Model 1 1.00 (reference) 0.64 (0.49–0.83) 0.73 (0.55–0.97) 0.003 
 Model 2 1.00 (reference) 0.68 (0.52–0.89) 0.79 (0.59–1.05) 0.016 

Daily W-Intake (L)
<0.5
 
0.5 to 1.0
 
>1.0
 
P for difference
 
General     
 n 677 1,754 1,184  
 Men (%) 48.6 47.9 45.4 0.31 
 Age (years) 46.4 (9.9) 47.3 (10.0) 46.3 (9.9) 0.001 
 BMI( kg/m224.1 (3.5) 24.4 (3.5) 24.7 (3.8) 0.001 
 Waist circumference (cm) 81.6 (10.7) 82.3 (11.0) 82.7 (11.6) 0.026 
 Physical activity (%)    0.0001 
  Low 28.7 25.7 19.4  
  Medium 56.1 54.6 52.6  
  High 15.2 19.8 28.0  
 Tobacco smoking (%)    0.0001 
  Never smokers 47.7 55.9 57.8  
  Ex-smokers 26.3 26.6 24.1  
  Current smokers 26.0 17.5 18.2  
Alcohol consumption (g/day) (%)    0.0001 
  Nonconsumers 22.0 23.0 30.7  
  1–10 24.7 27.2 31.2  
  10–20 8.1 8.4 6.7  
  >20 45.2 41.3 31.4  
 Creatininemia (μmol/L) 81.2 (13.0) 81.6 (13.0) 81.0 (12.9) 0.39 
 C-reactive protein* 1.00 (0.85–2.64) 0.87 (0.85–2.00) 0.85 (0.85–2.00) 0.49 
Blood pressure     
 Systolic (mmHg) 129 (15) 131 (15) 130 (15) 0.32 
 Diastolic (mmHg) 79 (10) 80 (9) 79 (9) 0.21 
 Hypertension (%) 32.5 34.3 32.4 0.50 
 Treated THZD/Furo (%) 3.7 2.2 3.2 0.07 
Metabolic data     
 Family history diabetes (%) 20.6 19.0 19.3 0.67 
 Fasting plasma glucose (mmol/L) 5.21 (0.45) 5.22 (0.44) 5.17 (0.44) 0.72 
 Fasting insulinemia (pmol/L) 42.7 (23.3) 45.0 (24.7) 44.1 (27.6) 0.08 
 HOMA-IR 1.40 (0.80) 1.48 (0.87) 1.43 (0.96) 0.10 
 HOMA-B 63 (46–89) 66 (46–92) 65 (47–91) 0.15 
 Total cholesterol (mmol/L) 5.76 (0.97) 5.72 (0.97) 5.66 (0.98) 0.007 
 Triglycerides (mmol/L) 1.14 (0.85) 1.09 (0.66) 1.09 (0.65) 0.15 
 HDL cholesterol (mmol/L)** 1.64 (0.41) 1.66 (0.43) 1.64 (0.44) 0.44 
 LDL cholesterol (mmol/L)** 3.39 (0.83) 3.35 (0.89) 3.32 (0.90) 0.032 
Other drinks     
Mean volume of sweet drinks (L) (%)    0.0001 
  <0.5 92.0 95.5 97.0  
  0.5 to 1.0 6.9 4.3 1.9  
  >1.0 1.0 0.2 1.1  
Mean volume of wine/day (L) (%)    0.0001 
  <0.5 89.1 93.9 96.4  
  0.5 to 1.0 9.9 6.1 3.6  
  >1.0 1.0 0.0 0.1  
Mean volume of beer or cider (L) (%)    0.056 
  <0.5 96.9 98.1 98.7  
  0.5 to 1.0 2.7 1.8 1.1  
Urine     
 Urine density (× 1,000) 1,019.6 (8.0) 1,019.3 (9.1) 1,017.9 (9.6) 0.0001 
ORs for new-onset hyperglycemia     
 Model 1 1.00 (reference) 0.64 (0.49–0.83) 0.73 (0.55–0.97) 0.003 
 Model 2 1.00 (reference) 0.68 (0.52–0.89) 0.79 (0.59–1.05) 0.016 

Data are means (SD) or medians (25th–75th percentiles) for continuous variables and percentages of patients for categorical variables. THZD, thiazidic diuretics; Furo, furosemide; HOMA-IR, homeostatic model assessment index of insulin resistance; HOMA-B, homeostatic model assessment index of insulin secretion. Hypertension was defined as systolic or diastolic blood pressure >140 or 90, respectively, or treated with antihypertensive drugs. ORs (95% CIs) for the association between daily W-Intake at baseline and the risk of incident hyperglycemia (fasting plasma glucose ≥6.1 mmol/L or treatment for diabetes) are presented according to two statistical models; variables for adjustment were either known risk factors for type 2 diabetes or factors associated (P < 0.10) with hyperglycemia and W-Intake in our population. Model 1: Adjusted for age, sex, BMI, baseline FG, physical activity, smoking status, triglycerides, HOMA-IR, and total cholesterol. Model 2: Further adjusted on self-reported intake of other fluids (i.e., volumes of beer or cider, sweet drinks, and wine consumed per day). Significant P values (<0.05) are in boldface.

*The C-reactive protein was available for only 181, 466, and 333 subjects in the three classes of W-Intake, respectively.

**HDL cholesterol and LDL cholesterol were not available for 28 and 26 subjects, respectively.

The same trend, although nonsignificant, was observed for the association with new-onset diabetes: compared with participants with a daily W-Intake <0.5 L, ORs for those drinking 0.5–1.0 L and >1.0 L water per day were 0.68 (95% CI 0.41–1.15) and 0.75 (0.43–1.32), respectively, P = 0.36.

Risk for hyperglycemia was negatively and independently related with self-reported W-Intake in normoglycemic middle-aged individuals from the French general population. This observational study does not establish causality. However, the association was moderately attenuated when important metabolic risk factors and potential confounders were introduced as covariables in the analysis, including intake of other classes of beverages with known adverse long-term effects (sweet and alcohol-containing drinks). Our data support the novel idea that vasopressin, besides its role in urine concentration, is also an important actor in glucose homeostasis (1).

The negative association of W-Intake and risk for hyperglycemia was relevant among many subsets of participants, and those reporting a low W-Intake (<0.5 L) had a higher risk for hyperglycemia (for example, participants in the high physical activity group) (Supplementary Table 1). This indicates that identification of individuals with a W-Intake of <0.5 L may be widely relevant to target preventive interventions regarding the metabolic risk.

Our study has several limitations. Diabetes incidence was low and statistical power was thus limited; 24-h urine volume was not measured, but the urinary density was inversely associated with self-reported W-Intake, arguing for the validity of the questionnaire (Table 1). In addition, we cannot exclude residual confounding: healthier behaviors correlating with higher water drinking could account for the observed association. Finally, only volunteers were included and the results may not be extrapolated to the general population.

Knowing the rise of vasopressin in diabetes, its effect on glycemia, gluconeogenesis, and glucagon release, it is surprising that no attention had been given to vasopressin as a possible risk factor for hyperglycemia and diabetes until a recent report of an association between copeptin and the incidence of diabetes (1,4,5,14). Our study extends this observation, drawing attention to a low W-Intake as a possible new risk factor for impaired glycemia. It suggests that an increase in W-Intake, an easy and costless intervention, could prevent or delay the onset of hyperglycemia and subsequent diabetes. Hopefully, our study will serve as a benchmark to design appropriate clinical trials testing the efficacy of this intervention in people who report drinking <0.5 L of water per day, as did almost 20% of the participants in this cohort.

APPENDIX

Members of the D.E.S.I.R. Study Group: INSERM CESP U1018: B. Balkau, P. Ducimetière, and E. Eschwège; INSERM U367: F. Alhenc-Gelas; CHU D’Angers: Y. Gallois and A. Girault; Bichat Hospital: F. Fumeron, M. Marre, and R. Roussel; CHU de Rennes: F. Bonnet; CNRS UMR8090, LILLE: P. Froguel; Centres d’Examens de Santé: Alençon, Angers, Blois, Caen, Chartres, Chateauroux, Cholet, Le Mans, Orléans, and Tours; Institut de Recherche Médecine Générale: J. Cogneau; General practitioners of the region; and Institute inter-Regional pour la Santé: C. Born, E. Caces, M. Cailleau, J.G. Moreau, O. Lantieri, F. Rakotozafy, J. Tichet, and S. Vol.

The D.E.S.I.R. study has been financed by INSERM contracts with Caisse nationale de l'assurance maladie des travailleurs salariés (CNAMTS), Lilly, Novartis Pharma, and sanofi-aventis; INSERM (Réseaux en Santé Publique, Interactions entre les déterminants de la santé, Cohortes Santé TGIR 2008); the Association Diabète Risque Vasculaire; the Fédération Française de Cardiologie; La Fondation de France; Association de Langue Française pour l'Etude du Diabète et des Maladies Métaboliques (ALFEDIAM)/Société Francophone de Diabétologie; L'Office national interprofessionnel des vins (ONIVINS); Ardix Medical; Bayer Diagnostics; Becton Dickinson; Cardionics; Merck Santé; Novo Nordisk; Pierre Fabre; Roche; and Topcon. These organizations had no role in the design and conduct of the study; collection, management, analysis, and interpretation of data; or preparation, review, and approval of the manuscript. No other potential conflicts of interest relevant to this article were reported.

R.R., L.F., and L.B. researched data, contributed to discussion, and wrote, reviewed, and edited the manuscript. N.B. and F.A.-G. contributed to discussion and reviewed and edited the manuscript. B.B., O.L., and M.M. researched data, contributed to discussion, and reviewed and edited the manuscript.

Parts of this study were presented in abstract form at the 71st Scientific Sessions of the American Diabetes Association, San Diego, California, 24–28 June 2011.

1.
Enhörning
S
,
Wang
TJ
,
Nilsson
PM
, et al
.
Plasma copeptin and the risk of diabetes mellitus
.
Circulation
2010
;
121
:
2102
2108
[PubMed]
2.
Zerbe
RL
,
Vinicor
F
,
Robertson
GL
.
Plasma vasopressin in uncontrolled diabetes mellitus
.
Diabetes
1979
;
28
:
503
508
[PubMed]
3.
Bankir
L
,
Bardoux
P
,
Ahloulay
M
.
Vasopressin and diabetes mellitus
.
Nephron
2001
;
87
:
8
18
[PubMed]
4.
Whitton
PD
,
Rodrigues
LM
,
Hems
DA
.
Stimulation by vasopressin, angiotensin and oxytocin of gluconeogenesis in hepatocyte suspensions
.
Biochem J
1978
;
176
:
893
898
[PubMed]
5.
Spruce
BA
,
McCulloch
AJ
,
Burd
J
, et al
.
The effect of vasopressin infusion on glucose metabolism in man
.
Clin Endocrinol (Oxf)
1985
;
22
:
463
468
[PubMed]
6.
Phillips
PA
,
Abrahams
JM
,
Kelly
JM
,
Mooser
V
,
Trinder
D
,
Johnston
CI
.
Localization of vasopressin binding sites in rat tissues using specific V1 and V2 selective ligands
.
Endocrinology
1990
;
126
:
1478
1484
[PubMed]
7.
Serradeil-Le Gal
C
,
Raufaste
D
,
Marty
E
,
Garcia
C
,
Maffrand
JP
,
Le Fur
G
.
Binding of [3H] SR 49059, a potent nonpeptide vasopressin V1a antagonist, to rat and human liver membranes
.
Biochem Biophys Res Commun
1994
;
199
:
353
360
[PubMed]
8.
Folny
V
,
Raufaste
D
,
Lukovic
L
, et al
.
Pancreatic vasopressin V1b receptors: characterization in In-R1-G9 cells and localization in human pancreas
.
Am J Physiol Endocrinol Metab
2003
;
285
:
E566
E576
[PubMed]
9.
Oshikawa
S
,
Tanoue
A
,
Koshimizu
TA
,
Kitagawa
Y
,
Tsujimoto
G
.
Vasopressin stimulates insulin release from islet cells through V1b receptors: a combined pharmacological/knockout approach
.
Mol Pharmacol
2004
;
65
:
623
629
[PubMed]
10.
Meijer
E
,
Bakker
SJ
,
Halbesma
N
,
de Jong
PE
,
Struck
J
,
Gansevoort
RT
.
Copeptin, a surrogate marker of vasopressin, is associated with microalbuminuria in a large population cohort
.
Kidney Int
2010
;
77
:
29
36
[PubMed]
11.
Balkau
B
,
Lange
C
,
Fezeu
L
, et al
.
Predicting diabetes: clinical, biological, and genetic approaches: Data from the Epidemiological Study on the Insulin Resistance Syndrome (DESIR)
.
Diabetes Care
2008
;
31
:
2056
2061
[PubMed]
12.
Gautier
A
,
Balkau
B
,
Lange
C
,
Tichet
J
,
Bonnet
F
;
DESIR Study Group
.
Risk factors for incident type 2 diabetes in individuals with a BMI of <27 kg/m2: the role of gamma-glutamyltransferase. Data from an Epidemiological Study on the Insulin Resistance Syndrome (DESIR)
.
Diabetologia
2010
;
53
:
247
253
[PubMed]
13.
Konrat
C
,
Mennen
LI
,
Cacès
E
, et al
;
the D.E.S.I.R. Study Group. Alcohol intake and fasting insulin in French men and women. The D.E.S.I.R. Study
.
Diabetes Metab
2002
;
28
:
116
123
[PubMed]
14.
Yibchok-Anun
S
,
Cheng
H
,
Heine
PA
,
Hsu
WH
.
Characterization of receptors mediating AVP- and OT-induced glucagon release from the rat pancreas
.
Am J Physiol
1999
;
277
:
E56
E62
[PubMed]

Supplementary data