(2024) 22:332
Gómez‑Martínez et al. BMC Medicine
https://doi.org/10.1186/s12916-024-03540-7

BMC Medicine

RESEARCH ARTICLE

Open Access

Trait impulsivity is associatedwith an increased risk of type 2 diabetes
incidence in adults over 8 years of follow‑up:
results from the NutriNet‑Santé cohort
Carlos Gómez‑Martínez1,2,3, Pauline Paolassini‑Guesnier4, Léopold Fezeu4, Bernard Srour4, Serge Hercberg4,
Mathilde Touvier4, Nancy Babio1,2,3, Jordi Salas‑Salvadó1,2,3† and Sandrine Péneau4*†   Abstract
Background Type 2 diabetes is one of the most prevalent and preventable diseases worldwide and impulsivity,
a psychological trait characterized by making quick decisions without forethought, has been suggested as a key fea‑
ture for health-related conditions. However, there have been no studies examining the relationships between impul‑
sivity and the incidence of type 2 diabetes and our aim was to assess the prospective association between trait
impulsivity and the risk of developing type 2 diabetes.
Methods A prospective observational study design was conducted between May 2014 and February 2023
within the NutriNet-Santé cohort. A web-based platform was used to collect data from the French adult population,with voluntary enrollment and participation. Of the 157,591 adults (≥ 18 years old) participating in the NutriNetSanté study when impulsivity was assessed, 109,214 participants were excluded due to prevalent type 1 or 2 diabe‑tes or missing data for impulsivity or follow-up data for type 2 diabetes. Trait impulsivity, and the attention, motor,
and non-planning subfactors, were assessed at baseline using the Barratt Impulsiveness Scale 11. Incident type 2
diabetes was ascertained through follow-up. Medical information was reviewed by NutriNet-Santé physician experts
to ascertain incident diabetes cases based on the ICD-10. Cox regression models, using hazard ratios and 95% confi‑
dence intervals (HR [95% CI]), were performed to evaluate associations between impulsivity per 1 standard deviation
increment and type 2 diabetes risk, adjusting by recognized confounders.
Results Of the 48,377 individuals studied (women 77.6%; age at baseline = 50.6 year ± 14.5 years), 556 individuals
developed type 2 diabetes over a median follow-up of 7.78 (IQR: 3.97–8.49) years. Baseline impulsivity was associatedwith an increased risk of type 2 diabetes incidence (HR = 1.10 [1.02, 1.20]). The motor impulsivity subfactor was posi‑
tively associated with type 2 diabetes risk (HR = 1.14 [1.04, 1.24]), whereas no associations were found for attention
and non-planning impulsivity subfactors.

†

Jordi Salas-Salvadó and Sandrine Péneau contributed equally to this work.

*Correspondence:
Sandrine Péneau
s.peneau@eren.smbh.univ-paris13.fr
Full list of author information is available at the end of the article© The Author(s) 2024. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which
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Gómez‑Martínez et al. BMC Medicine(2024) 22:332

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Conclusions Trait impulsivity was associated with an increased type 2 diabetes risk, mainly driven by the motor
impulsivity subfactor. If these results are replicated in other populations and settings, trait impulsivity may become
an important psychological risk factor to be considered in the prevention of type 2 diabetes.
Cohort registration Name of registry: The NutriNet-Santé Study. A Web-based Prospective Cohort Study of the Rela‑
tionship Between Nutrition and Health and of Dietary Patterns and Nutritional Status Predictors.
Cohort registration number: NCT03335644.
Date of registration: October 11, 2017.
URL: https://​clini​caltr​ials.​gov/​ct2/​show/​NCT03​335644
Keywords Impulsivity, Prospective cohort study, Motor, Attention, Planning, Personality, Psychological traits, Type 2
diabetes

Background
Type 2 diabetes is a chronic metabolic disease characterized by insulin resistance and elevated levels ofblood glucose, with a worldwide prevalence of 422 million people and around 1.6 million deaths attributable
to this medical condition yearly [1].
Genetic predisposition and different lifestyle behaviors have been recognized as risk factors for diabetes [2]. Personality traits predispose individuals to act
within a range of behaviors [3] and have also been suggested as risk factors for different health outcomes,
including diabetes [4]. Personality traits are relatively
stable characteristics across the lifespan but can also be
modified through psychological-based interventions [5,6].
Trait impulsivity, in particular, is a personality trait
characterized by difficulties with sustained attention,
rapid motor reactions, and lack of planning [7], andhas been linked to impaired inhibitory processes andhigher reward sensitivity [8]. Some studies have foundassociations between trait impulsivity, poor diet quality [9], higher body mass index (BMI) [10], and cardiometabolic risk [11]. Therefore, impulsivity could be
expected to increase the risk of type 2 diabetes incidence. However, to the best of our knowledge, there has
not been any prospective exploration of associations
between impulsivity and the risk of developing type 2
diabetes. A few cross-sectional studies have been performed and produced promising results [12, 13]. In one
study, higher glucose levels were associated with lower
inhibitory control (i.e., higher behavioral impulsivity),
especially in participants with prediabetes [12]. Participants with prediabetes also exhibited a greater impulsive reward sensitivity compared to healthy control
individuals [13]. Similar associations were observed inindividuals with type 2 diabetes, where higher HOMAinsulin resistance and glycated hemoglobin levels wereassociated with poorer performance on behavioral cognitive control and decision-making, respectively [14,15]. Finally, both higher trait and behavioral impulsivity
were found to be associated with poor diabetes management [16, 17].
As impulsivity has been suggested to play a role in diabetes status and control, we hypothesize that those individuals with high trait impulsivity will have an increased
risk of developing type 2 diabetes. Therefore, the main
aim of this work was to assess the associations between
baseline trait impulsivity and the risk of type 2 diabetes
incidence over 8 years of follow-up in the NutriNet-Santécohort.

Methods
Study design and population

A prospective study design was performed in the context
of the NutriNet-Santé study cohort, a web-based observational study with the objective to study relationships
between nutrition and health, as well as the determinantsof eating behavior and health status. The NutriNet-Santérecruitment started in May 2009 and currently has anopen ongoing enrolment. Volunteers are recruited via
multimedia campaigns from the general French population and are included if they are ≥ 18 years old, speak
French fluently, and have internet access. They are followed using a personal account on the study website(https://​etude-​nutri​net-​sante.​fr/), through which they
provide detailed information by answering multiple
questionnaires.
At inclusion, participants complete several self-report
web-based questionnaires to assess their diet, physicalactivity, anthropometric measures, lifestyle characteristics, socioeconomic conditions, and health status. Participants then complete this same set of questionnaires
every year after inclusion. Another set of optional questionnaires related to determinants of eating behaviors,
nutritional status, and specific health-related aspects issent to every participant each month. More informationon the study protocol can be found on the following website: https://​info.​etude-​nutri​net-​sante.​fr/​sitei​nfo/, whereGómez‑Martínez et al. BMC Medicine(2024) 22:332

the detailed study rationale, design, and methods are provided [18]. The study protocol was registered at https://​www.​clini​caltr​ials.​gov/ (NCT03335644).
All participants report an electronic informed consent.
Procedures were approved by the Institutional Research
Board of the French Institute for Health and Medical
Research (IRB INSERM no: 0000388FWA00005831) andthe Commission Nationale de l’Informatique et des Libertés (CNIL no: 908450 and 909,216). The study accomplishes the Declaration of Helsinki standards.
Impulsivity

Trait impulsivity was assessed using the validated French
version of the Barratt Impulsiveness Scale (BIS-11) [19],derived from the BIS-10 [20]. The BIS-11 is the most used
questionnaire to assess trait impulsivity in both researchand clinical practice [7]. This questionnaire was administered between May and November 2014. The BIS-11 isa 30-item self-reported questionnaire with a 4-point Likert scale scoring, ranging from “rarely/never” (1 point)
to “almost always/always” (4 points). The total BIS-11
score, as well as their impulsivity subfactors (attentional,
motor, and non-planning), were obtained by adding theirrespective items. The range of impulsivity scores was asfollows: BIS-11 total score (range 30–120), attentional
subfactor (range 8–32), motor subfactor (range 11–44),
and non-planning subfactor (range 11–44). Higher values
in the scores reflect higher impulsivity. The α Cronbach
value for the total score was 0.77, indicating an acceptable internal consistency.
Type 2 diabetes

Type 2 diabetes status was assessed using a multisource
approach (Additional file 1: Supplementary Method1). Incident cases of type 2 diabetes and medication
for this disease were recorded through yearly healthquestionnaires, a specific health check-up questionnaire every 6 months, or at any time spontaneously
through the NutriNet-Santé platform. Medical information was reviewed by NutriNet-Santé physician experts
to ascertain incident diabetes cases. Furthermore, thismedical record data was linked to the Système National
d’Information Inter-Régimes de l’Assurance Maladie(SNIIRAM) from the Caisse Nationale de l’Assurance
Maladie of the French national insurance system whereparticipants medication and medical consultation history was available. The SNIIRAM uses the International
Chronic Diseases Classification Clinical Modification
10th Revision (ICD-10) [21] to ascertain type 2 diabetes
incident cases. The first incident type 2 diabetes case wasconsidered between the impulsivity assessment and 8th
February 2023.

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Covariates

Potential confounders of the relation between trait
impulsivity and type 2 diabetes were collected. We
used the data closest to the date of completion of the
BIS-11. Selected confounders were sociodemographics: sex (male, female), age (years), and educational level(less than high school degree, < 2 years after high school
degree, ≥ 2 years after high school degree); lifestyle:smoking status (never, former, current), physical activity (low, medium, high) using the International Physical Activity Questionnaire (IPAQ) [22], energy intake
without alcohol (kcal/day), alcohol intake (g/day) using
24 h-dietary records, and diet quality using the simplified Programme National Nutrition Santé—Guidelines
Score 2 (sPNNS-GS2) [23]; personal history of disease:prevalence or medication use for hypertension (no,yes), hypercholesterolemia (no, yes), and hypertriglyceridemia (no, yes); family history of diabetes disease (no,yes); depressive symptomatology (no, yes) using the selfreported Center for Epidemiologic Studies Depression
Scale questionnaire (CES-D) [24]; and anthropometrics:
BMI (kg/m2).
Statistical analysis

For this study, we included participants from the NutriNet-Santé cohort who completed the BIS-11 and did nothave prevalent type 1 or 2 diabetes diagnosed at baseline.
Covariates with missing values were handled using Multiple Imputation by Chained Equations (MICE) by fully
condition specification (Additional file 1: Supplementary
Method 2).
Differences in trait impulsivity scores between the
excluded participants with prevalent type 2 diabetes
and those included in the final population were assessedusing a t-test. A comparison of baseline population characteristics between included and excluded participants
was performed, using t-test or chi-square, as appropriate. Baseline participant characteristics are presented as
numbers and percentages for qualitative variables andas mean ± standard deviation (SD) for quantitative variables. Comparisons across trait impulsivity categories(low, medium, and high) were based on chi-square forcategorical variables and one-way ANOVA for quantitative variables.
Cox regression models, using hazard ratios and 95%
confidence interval (HR 95% CI), were performed to evaluate the linear associations between 1 SD increment oftrait impulsivity (and attention, motor, and non-planningsubfactors) and the incidence of type 2 diabetes, over
8 years of follow-up. Participants contributed persontime from their impulsivity assessment until the date oftype 2 diabetes event, date of last follow-up, date of death,Gómez‑Martínez et al. BMC Medicine(2024) 22:332

or 8th February 2023, whichever occurred first, and incidence rates were estimated. A parsimonious model was
run and adjusted at baseline for age (as timescale) andsex. The main model was further adjusted at baseline foreducational level (with a logarithmic time interaction),smoking status, physical activity, energy intake without
alcohol, alcohol intake, and diet quality. The rationale
for covariates selection is described in Additional file 2:
Table S1 [9, 23, 25–40] and Additional file 2: Table S2 [10,24, 41–46].
Linearity assumptions between total impulsivity,and its subfactors, with type 2 diabetes incidence wereverified using restricted cubic spline functions. If theassociations were non-linear (motor subfactor only),a correction was applied using a logarithmic base 10
transformation. Impulsivity categories were used to estimate cumulative hazard risks (Additional file 3: Fig. S1).
Impulsivity categories were determined by using specified cut-offs [7]: low (< 52), medium (≥ 52 and ≤ 71),
and high (> 71). An exploratory analysis was conductedstudying the associations between trait impulsivity categories and the incidence of type 2 diabetes, using Cox
regression models. Pearson correlation coefficients wereassessed to confirm the absence of collinearity between
the continuous variables included in the main model(Additional file 2: Table S3). Schoenfeld residuals werecomputed to confirm the risk of proportionality hazard
assumptions. Covariates with non-proportional hazard
risk were corrected in the main analyses by establishingan interaction by logarithmic time (education level only).
Furthermore, Schoenfeld residuals were tested again correcting for non-proportional hazard covariates.
Sensitivity analyses were performed to verify therobustness of the findings. Associations between impulsivity and type 2 diabetes risk were analyzed using stratified estimates for non-proportional hazard covariates andwithout a correction for these non-proportional covariates. A total of six additional models were evaluated withthe aim of studying various confounding factors. The
exclusion of incident cases of type 2 diabetes during thefirst 2 years of follow-up was also assessed. Interactions
were tested using the likelihood ratio test for sex, age(< 60 years, ≥ 60 years), overweight (BMI: < 25, ≥ 25 kg/m2), and diet quality (sPNNS-GS2: median to determine
low and high diet quality, by sex). A post hoc mediation
analysis was conducted to assess the role of baseline BMI
in the association between a 1 SD increase in total trait
impulsivity and the risk of developing type 2 diabetes.
Linear regressions were used to determine the association between impulsivity (exposure) and BMI (mediator),and Cox regressions were used to determine the association of impulsivity and BMI with incident type 2 diabetes (outcome). BMI was fixed as its mean. The model wasPage 4 of 11

adjusted for the same covariates as the main model, andconfounders were fixed either at the mode (sex, education, smoking status, and physical activity) or at the mean(energy intake, alcohol intake, and diet quality). Analyses
were performed using the bootstrapping decomposition
method (seed: 4500; replicates: 1000).
Analyses were performed with STATA 14. The STATA
med4way package [47] was used for mediation analyses.
Statistically significant results were considered when P
value was < 0.05.

Results
Description of the study population

Among the 157,591 individuals included in the NutriNetSanté study at the time of impulsivity assessment, a totalof 48,377 participants were included in the present analyses and of these, 556 developed type 2 diabetes (Fig. 1).
Comparison of baseline population characteristics
between included and excluded participants can be foundin Additional file 2: Table S4. Baseline characteristics ofthe studied population were shown in Table 1. Mean age
was 50.4 (SD: 14.6) years, and around three-quarters of
the population were women. Compared with individuals
presenting lower impulsivity, those with higher impulsivity were more likely to be younger, female, and former
or current smokers; to have a lower level of education,
physical activity, and diet quality; and to have a higher
alcohol consumption, BMI, and prevalence or medication
use of hypertension, hypertriglyceridemia, and depressive symptomatology. The median follow-up was approximately 8 (median: 7.78; interquartile range: 3.97–8.49)
years (person-years: 297,027), and the incidence rate
(95% CI) was 1.87 (1.72, 2.03) for 1000 person-years.
Participants excluded due to prevalent type 2 diabetes at baseline exhibited higher trait impulsivity scores(mean: 59.83; SD: 8.48) compared to the final population (mean: 58.70; SD: 7.98) analyzed (P < 0.001). No statistically significant difference was observed in the total
impulsivity score between participants with prevalent(mean: 59.83; SD: 8.48) and incident (mean: 59.35; SD:8.06) type 2 diabetes (P = 0.15).
Associations between trait impulsivity and type 2 diabetes

Restricted cubic splines suggested a linear relationshipbetween total impulsivity and type 2 incident diabetes(P = 0.51) (Additional file 3: Fig. S2).
In both the parsimonious and main model, a positive
linear significant association was found between a 1 SD
increment of impulsivity and incidence of type 2 diabetes(main model; HR [95% CI] = 1.10 [1.02, 1.20]; P = 0.019)(Fig. 2). The associations between trait impulsivity categories and the incidence of type 2 diabetes were not significant (Additional file 2: Table S5).

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Fig. 1 Flowchart of the studied population

In the parsimonious model, all impulsivity subfactors (attention, motor, and non-planning) were associated with an increased risk of type 2 diabetes incidence,
although only motor impulsivity remained significantly
related in the main model (HR [95% CI] = 1.14 [1.04,
1.24]; P = 0.003) (Fig. 3).
Given the non-proportional hazard estimates observedfor educational level (Additional file 2: Table S6; Additional file 2: Table S7), sensitivity analyses were performed with a stratification on educational level andwithout correction for this covariate. In both analyses,
the directionality and significance of the associations
between total impulsivity, its subfactors, and type 2 diabetes were maintained (Additional file 2: Table S8; Additional file 2: Table S9). The associations between total
trait impulsivity and type 2 diabetes were also maintained
after the adjustment of sociodemographic and lifestyleconfounders (Additional file 2: Table S10). However, theadditional adjustment for personal and familiar historyof disease, as well as for depressive symptomatology,
attenuated the relationships showing borderline nonsignificant results (all P ≤ 0.075). More specifically, after

the inclusion of BMI in the models, the association waslargely attenuated becoming non-significant (P = 0.53).
When excluding participants with early incident type 2
diabetes (first 2 years of follow-up), the associations werealso attenuated (P = 0.11) (Additional file 2: Table S11).
Assessed interactions for sex, age, overweight, and dietquality showed no significant results (all P > 0.20). The
results of the mediation analysis by BMI in the association between trait impulsivity and the risk of developing
type 2 diabetes showed a significant total effect (HR [95%CI] = 1.10 [1.00, 1.19]; P = 0.048), a borderline significant
controlled direct effect when BMI was fixed at its mean
(HR = 1.09 [0.99, 1.18]; P = 0.070), and a significant pureindirect effect (HR [95% CI] = 1.02 [1.01, 1.03]; P < 0.001)
indicating a strong mediation effect of BMI (Additional
file 3: Fig. S3).

Discussion
To the best of our knowledge, this is the first study investigating long-term relationships between impulsivity
and type 2 diabetes incidence. In the present study, conducted in the context of a large population, baseline trait

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Table 1 Baseline characteristics of the study population by trait impulsivity categories, NutriNet-Santé cohort, France, 2014–2023(n = 48,377)
Characteristics

All participantsP ­value*

Trait impulsivity
Low (n = 8659)

Medium (n = 36,743)

High (n = 2975)

Age (years)

50.63 ± 14.56†

51.11 ± 14.06

50.59 ± 14.60

49.78 ± 15.37< 0.001

Sex (female)

37,568 (77.66)‡

6244 (72.11)

28,863 (78.55)

2461 (82.72)< 0.001

1032 (2.14)

120 (1.39)

779 (2.13)

133 (4.48)

Educational level (n = 48,278)
Less than high school degree< 0.001  < 2 years after high school degree

14,108 (31.39)

2167 (25.09)

10,753 (29.36)

1188 (40.01)  ≥ 2 years after high school degree

33,091 (68.61)

6351 (73.52)

25,092 (68.51)

1648 (55.51)

22,333 (46.17)4625 (53.41)

16,687 (45.42)

1021 (34.32)

Smoking status (n = 48,376)
Never< 0.001

Former

20,899 (43.20)

3423 (39.53)

16,051 (43.69)

1425 (47.90)

Current

5144 (10.63)

611 (7.06)

4004 (10.90)

529 (17.78)

11,025 (22.83)

8408 (22.92)

84,088 (22.92)

751 (25.37)

Physical activity (IPAQ) (n = 48,314)
Low< 0.001

Medium20,248 (41.94)

3561 (41.20)

15,501 (42.26)

1186 (40.07)

High17,009 (35.23)

3217 (37.22)

12,769 (34.81)

1023 (34.56)

Energy intake without alcohol (kcal/day) (n = 45,080)

1787.29 ± 474.28

1789.09 ± 474.73

1786.23 ± 471.91

1795.35 ± 502.41

0.59

Alcohol intake (g/day) (n = 45,080)

7.92 ± 12.01

7.21 ± 11.12

8.05 ± 12.10

8.66 ± 13.22< 0.001

Diet quality (sPNNS-GS2; range: − 17 to 13.5) (n = 44,318)

1.28 ± 3.56

1.41 ± 3.55

1.27 ± 3.54

0.95 ± 3.80

< 0.001

Body mass index (kg/m2) (n = 48,212)

23.86 ± 4.34

23.65 ± 4.16

23.87 ± 4.36

24.41 ± 5.00

< 0.001

Hypertension prevalence and/or medication

6400 (13.23)

1131 (13.06)

4818 (13.11)

451 (15.16)

0.006

Hypercholesterolemia prevalence and/or medication

8719 (18.02)

1545 (17.84)

6618 (18.01)

556 (18.69)

0.58

Hypertriglyceridemia prevalence and/or medication

1657 (3.43)

285 (3.29)

1243 (3.38)

129 (4.34)

0.017

Family history of diabetes (n = 47,996)

9689 (20.19)

1717 (19.97)

7370 (20.21)

602 (20.53)

0.78

Depressive symptomatology (n = 19,464)

2359 (12.12)263 (7.71)

14,887 (12.14)

288 (24.68)< 0.001

Abbreviations: IPAQ, International Physical Activity Questionnaire; sPNNS-GS2, simplified Programme National Nutrition Santé—Guidelines Score 2
Trait impulsivity categories were determined using the following cut-offs: low (< 52), medium (≥ 52 and ≤ 71), and high (> 71), based on the Barratt Impulsiveness
Scale 11 questionnaire*

P value showing comparisons between categories of trait impulsivity (low, medium, high) based on chi-square for categorical variables and ANOVA for quantitative
variables†

Mean ± SD (all such values)‡n (%) (all such values)

impulsivity was significantly associated with an increased
risk of type 2 diabetes, independently of several recognized confounding factors.
Psychological aspects have been highlighted as major
characteristics for the establishment of diseases [4]. Psychological traits predispose human behavior based on
established patterns of emotions and cognitive processes
that interact with genetic, biological, cultural, and social
spheres [3]. Therefore, it seems reasonable that psychological traits, such as an impulsive proneness which has
been associated with unhealthy behaviors and glycemic
dysregulations [11, 16, 17], may play a role in the development of glucose-related diseases such as type 2 diabetes.
Unfortunately, there is a lack of studies analyzing theassociations between personality traits and the incidence of type 2 diabetes, and none of the studies has
examined these associations evaluating trait impulsivity.

Remarkably, the present work shows an association
between trait impulsivity and the risk of developing type2 diabetes. Our data support previous cross-sectional
studies in populations with or at risk of developing type2 diabetes where an inverse relationship between behavioral impulsivity levels and glycemic status [12–15], andpoor diabetes control [16, 17] have been reported.
The present results are also in line with those of apooled project including 5 prospective cohorts and34,914 adults from the USA and the UK where higher
trait conscientiousness was linearly associated withlower type 2 diabetes incidence and its caused-related
mortality [48]. Trait impulsivity has been proposed as
an antagonist of conscientiousness, which is describedas the propensity to be self-controlled, responsible, andwell-organized [49]. The associations shown in the present work between impulsivity and type 2 diabetes couldGómez‑Martínez et al. BMC Medicine(2024) 22:332

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Fig. 2 Associations between trait impulsivity and type 2 diabetes risk, NutriNet-Santé cohort, France, 2014–2023 (n = 48,377). Abbreviations:
HR per 1 SD (95% CI), hazard ratio per 1 standard deviation increment and 95% confidence interval. Cox regression analyses were performed
using hazard ratios and 95% CI to assess associations between 1 SD increment of total trait impulsivity and the risk of type 2 diabetes incidence
over a median follow-up of 8 years in the NutriNet-Santé cohort. Total population (n = 48,377) and type 2 diabetes incident cases (n = 556).
Person-years = 297,027 and incidence rate = 1.87 (95% CI: 1.72, 2.03) per 1000 person-years. Parsimonious model: adjusted for baseline sex and age(time scale). Main model: parsimonious model + baseline education level (less than high school degree, < 2 years after high school degree, ≥ 2 years
after high school degree), smoking status (never, former, current smoker), physical activity (International Physical Activity Questionnaire: high,moderate, low), energy intake without alcohol (kcal/day), alcohol intake (g/day), and diet quality (simplified Programme National Nutrition Santé—
Guidelines Score 2). Non-proportional hazard risk covariates were corrected by adding a logarithmic time interaction (educational level only)

be explained by the idiosyncratic neurological impulsivity
network, which may lead to impulsive behaviors guided
by the trait impulsivity proneness. The characteristic
impulsive neural pathway involves the prefrontal cortex (high-order cognitive system), ventral striatum andnucleus accumbens (reward-dopaminergic system), andamygdala (emotional-limbic system) regions [50]. Theinteraction between this network and impulsivity traits
drives individuals to have a great urgency to respond totheir positive and negative emotional states and a highsensitivity to immediate rewards, combined with a lack ofprefrontal cortex capacity to restrain the need for immediate gratification or to avoid negative emotions [51, 52].
Consequently, this interplay between trait and neurological impulsivity predisposes individuals to externalize impulsive behaviors characterized by acting without
considering the consequences of their behavior [51, 52].
These mechanisms may also explain the positive associations found between impulsivity measures and major risk
factors for type 2 diabetes such as diet quality [9], BMI[10], insulin resistance [14], and hyperglycemia [12].
Some lifestyle behaviors, such as poor diet quality,
have been shown to increase cytokines production in
adipose tissue and liver, promoting insulin resistance[53]. Results from the Nurses’ Health Studies, which followed more than 200,000 participants, indicated that theconsumption of unhealthy food was associated with anincreased incidence of type 2 diabetes [54]. Trait impulsivity has also been shown to be inversely associatedwith the adherence to healthy dietary patterns [9]. In our
analyses, the adjustment for different food-related variables did not change the directionality and significanceof the associations between impulsivity and type 2 diabetes incidence, but we cannot completely discard someresidual confounding effects. When BMI was included
as a covariate in the models, the association was largely
attenuated and became non-significant. Mediation analyses confirmed a substantial mediating effect of BMI on
the association between trait impulsivity and type 2 diabetes incidence. While the indirect effect through BMI
was significant, the direct effect did not reach statisticalsignificance, shedding light on the observed attenuation.
Impulsivity has previously been associated with higher
odds of obesity in the NutriNet-Santé study and withincreasing BMI levels as shown by a meta-analysis [10,55]. Adiposity has a recognized central role in the development of type 2 diabetes as higher BMI has been shownto induce low-grade inflammation and decrease insulin
sensitivity, increasing the risk of hyperglycemia [56]. In
addition, longitudinal studies show that negative psychological factors generally precede and predict faster rateof weight gain rather than the opposite [57], suggesting aunidirectional association between impulsivity and BMI
on the risk of type 2 diabetes incidence.

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Fig. 3 Associations between trait impulsivity subfactors and type 2 diabetes risk, NutriNet-Santé cohort, France, 2014–2023 (n = 48,377).
Abbreviations: HR per 1 SD (95% CI), hazard ratio per 1 standard deviation increment and 95% confidence interval. Cox regression analyses were
performed using hazard ratios and 95% CI to assess associations between 1 SD increment of attention, motor, and non-planning trait impulsivity
subfactors and the risk of type 2 diabetes incidence over a median follow-up of 8 years in the NutriNet-Santé cohort. The attention impulsivity
subfactor was log10 transformed due to potential non-linear association (P = 0.03). Total population (n = 48,377) and type 2 diabetes incident cases(n = 556). Person-years = 297,027 and incidence rate = 1.87 (95% CI: 1.72, 2.03) per 1000 person-years. Parsimonious model: adjusted for baseline
sex and age (time scale). Main model: parsimonious model + baseline education level (less than high school degree, < 2 years after high school
degree, ≥ 2 years after high school degree), smoking status (never, former, current smoker), physical activity (International Physical Activity
Questionnaire: high, moderate, low), energy intake without alcohol (kcal/day), alcohol intake (g/day), and diet quality (simplified Programme
National Nutrition Santé—Guidelines Score 2). Non-proportional hazard risk covariates were corrected by adding a logarithmic time interaction(educational level only)

When considering subtraits of impulsivity, we observedthat motor personality was the only subfactor consistently associated with type 2 diabetes incidence in themain models, whereas attention and non-planning
impulsivity subfactors did not show significant associations. Impulsivity subtraits are attributable to different cognitive control subsystems [58]. In particular, themotor impulsivity subfactor, which involves acting without thinking [7], has been found to be more strongly
associated with the activation of neural networks related
to cognitive control compared with the attention andnon-planning subfactors [58]. These neural networks
have been proposed to be key neural bases for behavioral
impulsivity [8]. Therefore, and in consideration of the factthat personality traits are precursors of behaviors [3], theresults of the present study, which demonstrated a consistent association between motor trait impulsivity andthe incidence of type 2 diabetes, could suggest that thissubfactor may be the precursor of the deleterious relationships found between behavioral impulsivity and glucose-related measurements [12–15]. When participants

with incident cases of type 2 diabetes within the first
2 years of follow-up were removed, only the motor subfactor remained associated with type 2 diabetes in themain model, suggesting a strong association for this personality subfactor. It is important to consider that thissensitivity analysis excluded around 7000 participants
and almost 50% of incident cases, which considerably
reduced the statistical power. Given that half of the cases
occurred during the first 2 years of follow-up, it is possible that reverse causation may have occurred between
impulsivity and type 2 diabetes. However, the impulsivity trait is theoretically established early in life [52] which
reduces the likelihood of such reverse causation.
The main strengths of the present analyses were thenovelty of the assessed relationships, the large population
studied, and the long period of follow-up, but some limitations deserve to be mentioned. First, the observational
design did not allow to establish causal relationships.
Second, some additional residual confounding bias could
exist, although models were adjusted by several and recognized confounders and multiple sensitivity analyses

Gómez‑Martínez et al. BMC Medicine(2024) 22:332

were performed to check the robustness of the findings.
Third, trait impulsivity was a self-reported measure, but
the questionnaire employed was the most widely usedassessment of trait impulsivity and was validated for the
French population. Addressing impulsive eating more
specifically could be of great interest given that disinhibited eating behavior has been positively associated withinsulin resistance [59]. Fourth, the type 2 diabetes incidence rate per 1000 person-years observed in our study(1.87) was low compared to the incidence rate (between
7.74 and 8.97 for the period 2012–2020) found in a recent
study involving more than 20 million French individuals [60]. The rate observed in our study may be partly
explained by the voluntary enrollment of the participantsin the NutriNet-Santé study where more women andmore participants with higher education, higher income,and professional status are found than in the general
French population [61]. These participants may be more
likely to have high health awareness and a stronger interest in nutrition which in turn is associated with a lower
risk of developing metabolic diseases. The selection bias
indicates that caution should be exercised when extrapolating the results to the general population. For example,
higher impulsivity values are usually reported in men andour population was predominantly women. However, asex interaction was tested and not found.
The clinical relevance of this study should be noted.
Higher levels of impulsivity have been associated withan increase in the risk of highly prevalent disorders with
substantial public health burden such as overeating andobesity [10], eating disorders [62], substance-related disorders [50], and psychiatric conditions [51]. The present
work further extends these findings by highlighting theincreased risk of developing type 2 diabetes associatedwith higher impulsivity. Emphasizing positive psychological characteristics could be potential strategies for the
primary and secondary prevention of type 2 diabetes. In
particular, mindfulness which has showed an inverse association with impulsivity could be beneficial [6, 63]. Additionally, the need for cognition (NFC) has been identified
as a protective psychological factor for diabetes self-management and glycemic control [64]. Reducing the intensity of negative emotions in patients with type 2 diabetes
is another potential factor of interest given its mediating
effect on the relationship between trait impulsivity andexecutive function [65]. It is also important to acknowledge that impulsive behaviors can sometimes be strategic
responses based on individual needs or motivations andtherefore may serve adaptive purposes in certain contexts[66]. Therefore, further research is needed to explore thecomplex associations between impulsivity and chronic
diseases, considering both potential benefits and risks.

Page 9 of 11

Conclusions
To conclude, trait impulsivity was associated with anincreased risk of type 2 diabetes incidence over 8 years offollow-up in a large French cohort. Specifically, the personality subfactor of motor impulsivity was found to be
an important feature to consider for the onset of type 2
diabetes. If these results are confirmed in other populations and settings, trait impulsivity could be a promising
psychological risk factor to consider for the prevention oftype 2 diabetes.
Abbreviations
BIS-11	Barratt Impulsiveness Scale
BMI	Body mass index
CES-D	Center for Epidemiologic Studies Depression Scalequestionnaire
ICD-10	International Chronic Diseases Classification Clinical Modifica‑tion 10th Revision
IPAQ	International Physical Activity Questionnaire
MICE	Multiple Imputation by Chained Equations
NFC	Need for cognition
SD	Standard deviation
SNIIRAM	Système National d’Information Inter-Régimes de l’Assurance
MaladiesPNNS-GS2	
Simplified Programme National Nutrition Santé—Guidelines
Score 2

Supplementary Information
The online version contains supplementary material available at https://​doi.​
org/​10.​1186/​s12916-​024-​03540-7.
Additional file 1: Supplementary Method 1 Incident type 2 diabetes ascer‑
tainment in NutriNet-Santé and biological data assessment. Supplemen‑tary Method 2 Multiple Imputation by Chained Equations
Additional file 2: Table S1 Rationale for selected confounders in the mainmodel. Table S2 Rationale for selected confounders in sensitivity analyses.
Table S3 Pearson correlations between continuous variables included in
the main model. Table S4 Baseline characteristics of the study populationcomparing included and excluded participants. Table S5 Associations
between categories of trait impulsivity and the risk of developing type2 diabetes. Table S6 Assessment of proportional hazard risk assumptions
between total trait impulsivity and risk of developing type 2 diabetes,with and without correction for non-proportional hazard risks covariates.
Table S7 Assessment of proportional hazard risk assumptions between
impulsivity subfactors and risk of developing type 2 diabetes, with andwithout correction for proportional hazard risks covariates. Table S8
Associations between total and subfactors of trait impulsivity and risk ofdeveloping type 2 diabetes over 8 years using stratified estimates for nonproportional hazard risk covariates. Table S9 Associations between total
and subfactors of trait impulsivity and risk of developing type 2 diabetes
over 8 years without proportional hazard risk correction. Table S10 All
models of associations between total and subfactors of trait impulsivity
and risk of developing type 2 diabetes over 8 years. Table S11 Associations
between total and subfactors of trait impulsivity and risk of developing
type 2 diabetes over 8 years excluding incident cases in the first 2 years offollow-up
Additional file 3: Fig. S1 Cumulative hazards between categories of total
trait impulsivity and risk of developing type 2 diabetes. Fig. S2 Restrictedcubic splines between trait impulsivity and risk of developing type 2
diabetes. Fig. S3 Mediation analysis of body mass indexlevels in theassociations between total trait impulsivity and the risk of developing type2 diabetesGómez‑Martínez et al. BMC Medicine(2024) 22:332

Acknowledgements
The authors thank Cédric Agaesse (dietary data manager) and Alexandre
De-Sa (dietitian); Selim Aloui (IT manager), Thi Hong Van Duong, Régis Gatib‑elza, Jagatjit Mohinder, and Aladi Timera (computer scientists); Julien Allegre,
Nathalie Arnault, Laurent Bourhis, Nicolas Dechamp (biostatisticians), andFabien Szabo de Edelenyi, Ph.D. (biostatistics team manager); Maria Gomes
and Mirette Foham (NutriNet-Santé participant support); and Paola Yvroud,
M.D. (health event validator) (all affiliated with CRESS-EREN) for their technicalcontribution to the NutriNet-Santé study. The authors sincerely thank all thevolunteers of the NutriNet-Santé cohort.
Authors’ contributions
SH, LF, MT, and SP contributed to the NutriNet-Santé study conceptualizationand coordination. JS and SP coordinated the project. CG-M, BS, LF, and SP
contributed to the methodology and formal analysis. CG-M wrote the originaldraft and revised the manuscript based on comments from JS and SP. CG-M,
PP-G, LF, BS, SH, MT, NB, JS-S, and SP reviewed and approved the manuscript
for submission. CG-M, PP-G, LF, BS, SH, MT, NB, JS-S, and SP had the final
responsibility for the decision to submit for publication.
Funding
The NutriNet-Santé study was supported by the following public institu‑
tions: the Ministry of Health, Public Health France, the National Institute of
Health and Medical Research (INSERM), the National Institute of Agricultural,
Food and Environmental Research (INRAE), the National Conservatory ofArts and Crafts (CNAM), and Université Sorbonne Paris Nord. CG-M receives a
predoctoral (2020PMF-PIPF-37) from URV. Researchers were independent fromfunders. The funders had no role in considering the study design or in thecollection, analysis, interpretation of data, writing of the report, or decision tosubmit the article for publication.
Availability of data and materials
Researchers from public institutions can submit a collaboration request to Dr.
Mathilde Touvier via collaboration@etude-nutrinet-sante.fr, including informa‑tion on the institution and a brief description of the project. All requests will
be reviewed by the steering committee of the NutriNet-Santé study. If thecollaboration is accepted, a data access agreement will be necessary, andappropriate authorizations from competent administrative authorities may
be needed. In accordance with existing regulations, no personal data will beaccessible. The analysis code can be requested from the authors.

Declarations
Ethics approval and consent to participate
Electronic informed consent is provided by each person included in the Nutri‑
Net-Santé cohort. The study is registered at https://​clini​caltr​ials.​gov/​ct2/​show/​
NCT03​335644, conducted according to the Declaration of Helsinki guidelines
and approved by the Institutional Review Board of the French Institute for
Health and Medical Research (IRB-Inserm) and the Commission Nationale del’Informatique et des Libertés (CNIL No 908450/909216).
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Author details
1
Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia,
Alimentació, Nutrició, Desenvolupament i Salut Mental (ANUT-DSM), Reus,
Spain. 2 Institut d’Investigació Sanitària Pere Virgili (IISPV), Reus, Spain. 3 Centro
de Investigación Biomédica en Red de Fisiopatología de La Obesidad y Nutri‑ción (CIBEROBN), Instituto de Salud Carlos III (ISCIII), Madrid, Spain. 4 Centerof Research in Epidemiology and StatisticS (CRESS), Nutritional Epidemiology
Research Team (EREN), Université Sorbonne Paris Nord and Université Paris
Cité, INSERM, INRAE, CNAM, 93017 Bobigny, France.
Received: 9 January 2024 Accepted: 24 July 2024

Page 10 of 11

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