Smoking,alcohol consumption,and new-onset impaired glucose metabolism in male patients with type 1 autoimmune pancreatitis: a retrospective cohort study

Abstract

Background:

Type 1 autoimmune pancreatitis (AIP) is more prevalent among males, a significant proportion of whom are known to smoke and consume alcohol, both of which can cause damage to the pancreas. AIP is associated with the new-onset impaired glucose metabolism (NO-IGM). However, it remains unclear whether smoking and alcohol consumption exacerbate this risk.

Objectives:

The present study aims to clarify the potential impact of smoking and alcohol consumption on the risk of NO-IGM in male patients with type 1 AIP.

Design:

A retrospective cohort study.

Methods:

This retrospective cohort study included 305 male patients with type 1 AIP. The participants were categorized into four groups based on smoking and drinking status: neither, smoking-only, drinking-only, and both group. The impact of smoking and heavy drinking on AIP-related IGM was analyzed using multivariate modified Poisson regression.

Results:

The prevalence of NO-IGM was 40.66% in the study. In the multivariate modified Poisson regression analysis, smoking-only group (relative risk (RR), 2.44; 95% CI, 1.70–3.51) and both smoking and drinking (RR, 2.84; 95% CI, 1.93–4.19) were associated with an increased risk of type 1 AIP-related NO-IGM. Drinking only (estimated RR >1) also appeared to elevate this risk.

Conclusion:

In male patients with type 1 AIP, smoking and heavy drinking may increase the risk of AIP-related NO-IGM.

Keywords

AIP blood glucose heavy alcohol consumption smoking

Introduction

Autoimmune pancreatitis (AIP) is a rare chronic inflammatory disorder of the pancreas. According to a nationwide survey conducted in Japan, the overall prevalence of AIP was 10.1 per 100,000 persons.¹ AIP is classified into two subtypes: type 1 and type 2. Type 1 AIP is characterized by lymphoplasmacytic infiltration and fibrosis, and it is more prevalent than type 2. Type 1 AIP is often associated with elevated serum immunoglobulin G4 (IgG4) levels and is considered a manifestation of systemic IgG4-related disease.² Notably, type 1 AIP predominantly affects middle-aged to elderly males,³ making it a significant clinical concern in this demographic.

A considerable proportion of males engage in smoking and alcohol consumption,^4,5 both of which are well-established risk factors for pancreatic damage. Smoking and drinking have both been linked to an increased risk of pancreatitis and pancreatic cancer.^6,7 The pancreas, particularly the islets of Langerhans, plays a critical role in glucose homeostasis through the secretion of insulin and glucagon. Consequently, any damage to the pancreatic parenchyma, including that caused by inflammatory processes such as AIP, can impair glucose metabolism.

Emerging evidence indicates that diabetes mellitus is a frequent complication of AIP, with a prevalence ranging from 43% to 83%.^8–11 While the relationship between AIP and diabetes mellitus (DM) has been explored, the potential role of lifestyle factors, such as smoking and alcohol consumption, in influencing the risk of glucose dysregulation in AIP patients has not been thoroughly investigated.

Given the high prevalence of smoking and alcohol use among males, coupled with the established detrimental effects of these habits on pancreatic health, it is plausible that they may further increase the risk of new-onset glucose dysregulation in patients with AIP. However, to date, there is a paucity of data addressing this hypothesis. The current study aims to evaluate whether smoking and alcohol consumption are associated with an increased risk of new-onset impaired glucose metabolism (NO-IGM) in male patients with type 1 AIP. By elucidating the potential role of these modifiable lifestyle factors, our findings may improve the clinical management of this patient population.

Materials and methods

Patients and study design

The cohort in this retrospective cohort study comprised patients diagnosed with type 1 AIP at Peking Union Medical College Hospital (a tertiary referral center in China) between January 2017 and December 2024. The diagnosis of AIP was established in accordance with the 2011 International Consensus Diagnostic Criteria (ICDC).¹² Exclusion criteria included: (1) female patients, (2) individuals aged <18 years, (3) those diagnosed with type 2 AIP, (4) patients with incomplete data, particularly those lacking information on smoking, alcohol consumption, and glucose metabolism, and (5) individuals with concurrent conditions affecting glucose metabolism, such as Cushing’s syndrome or thyroid dysfunction. Ultimately, 305 male patients with definitive type 1 AIP were included in the analysis. Detailed exclusion criteria are illustrated in the flowchart presented in Figure 1. The present study was conducted in accordance with the STROBE reporting guidelines (Supplemental Material).¹³

Figure 1.

Flowchart of patient inclusion and exclusion.

Variables

The exposures in this study were smoking or heavy drinking. Smoking was defined as a smoking index (calculated as the number of cigarettes smoked per day multiplied by the number of years smoked) exceeding 200 pack-years.¹⁴ Heavy drinking was defined as a daily pure alcohol intake exceeding 40 g.¹⁵ Information on smoking and alcohol consumption was collected by physicians during medical history interviews. The outcome of interest was NO-IGM, defined as fasting blood glucose (FBG) ⩾ 6.1 mmol/L, 2-h postprandial blood glucose ⩾7.8 mmol/L following a 75 g oral glucose tolerance test, or glycated hemoglobin (HbA1c) ⩾5.7%.^16,17 Blood glucose measurements were obtained prior to the initiation of steroid therapy. NO-IGM were identified as those occurring concurrently with AIP diagnosis or within 1 year.^18,19 Specifically, this included two scenarios: (1) individuals with no prior history of IGM who newly developed dysregulation of blood glucose, and (2) individuals with a history of IGM who experienced significant fluctuations or poor glycemic control. Other variables included age, symptoms (absence of symptoms, abdominal pain, jaundice, and weight loss), the number of extra-pancreatic other organ involvement (OOI including extra-pancreatic bile duct,²⁰ lung, salivary glands, lymph nodes and kidney), obesity (defined as a body mass index >28 kg/m² prior to AIP onset), allergic diseases (bronchial asthma and allergic rhinitis), preexisting diabetes mellitus (pDM), Eosinophil (EOS), alanine aminotransferase, total bilirubin (TBIL), gamma-glutamyl transferase (GGT), FBG, IgG4, pancreatic morphology (diffuse pancreatic enlargement or not), and pancreatic cyst formation. All laboratory tests were conducted prior to the initiation of steroid therapy. Imaging findings were determined by abdominal computed tomography, pancreatic magnetic resonance imaging, or endoscopic ultrasound.

Statistical analyses

Continuous variables were expressed as medians (Q1, Q3), and comparisons between groups were performed using the Mann–Whitney U test. Categorical variables were presented as counts (percentages), and intergroup comparisons were conducted using the chi-square test or Fisher’s exact probability test. We first described the characteristics of the entire cohort, followed by analyses of differences between groups based on smoking and alcohol consumption status (neither smoking nor drinking, smoking only, drinking only, and both smoking and drinking). Univariate and multivariate regression analyses were performed using modified Poisson regression²¹ (comparing neither smoking nor drinking vs smoking only and neither smoking nor drinking vs both smoking and drinking). The relative risks (RRs) along with their corresponding 95% confidence intervals (CIs) were reported. In the multivariate regression analysis, we adjusted for age, obesity, IgG4, EOS, and pDM, based on existing literature,^22–25 clinical experience, and the result of the univariate analysis. To mitigate the risk of type I error due to multiple comparisons, the Bonferroni correction was applied. A p value less than the corrected significance level (0.05/2 = 0.025) was considered statistically significant. Statistical analyses were performed using R version 4.2.0 (https://www.r-project.org/).

Results

Characteristics of the cohort

A total of 305 male patients with type 1 AIP were included, with the median age being 59 years (53.00, 65.00). Of the total cohort, 151 patients (49.51%) had jaundice, 47 (15.41%) were classified as obese, and 67 (21.97%) had a history of allergic diseases. Regarding lifestyle factors, 154 (50.49%) were smokers, and 60 (19.67%) were identified as heavy drinkers. In terms of smoking and drinking status, 143 (46.89%) neither smoked nor drank, 102 (33.44%) smoked only, 8 (2.62%) drank only, and 52 (17.05%) engaged in both smoking and heavy drinking. Forty-six (15.08%) had a history of pDM, while 124 (40.66%) experienced NO-IGM. FBG levels were 5.90 mmol/L (5.30, 7.30), while IgG4 was 7530.00 mg/L (4090.00, 15,000.00). Additional features are summarized in Table 1.

Table 1.

Characteristics of the patients.

Variables	Median (Q1, Q3) or n (%)
Male, n (%)	305 (100)
Age, years	59.00 (53.00, 65.00)
Symptoms, n (%)
Absence of symptoms	50 (16.39)
Abdominal pain	156 (51.15)
Jaundice	151 (49.51)
Weight loss	123 (40.33)
Obesity, n (%)	47 (15.41)
Allergic diseases, n (%)	67 (21.97)
Smoking, n (%)	154 (50.49)
Heavy drinking, n (%)	60 (19.67)
Smoking and drinking status, n (%)
Neither	143 (46.89)
Smoking only	102 (33.44)
Drinking only	8 (2.62)
Both	52 (17.05)
pDM	46 (15.08)
NO-IGM	124 (40.66)
OOI, n (%)
Extra-pancreatic bile duct	125 (40.98)
Lung	159 (52.13)
Salivary glands	98 (32.13)
Lymph nodes	168 (55.08)
Kidney	47 (15.41)
Number of OOI	2.00 (2.00, 3.00)
Diffuse pancreatic enlargement, n (%)	171 (56.07)
Cyst formation, n (%)	44 (14.43)
EOS, ×10⁹/L	0.20 (0.11, 0.36)
ALT, U/L	59.00 (21.00, 199.00)
TBIL, μmol/L	25.40 (12.10, 79.30)
GGT, U/L	228.00 (27.00, 637.00)
FBG, mmol/L	5.90 (5.30, 7.30)
IgG4, mg/L	7530.00 (4090.00, 15,000.00)

ALT, alanine aminotransferase; EOS, eosinophils; FBG, fasting blood glucose; GGT, gamma-glutamyl transferase; IgG4, immunoglobulin G4; NO-IGM, new-onset impaired glucose metabolism; OOI, other organ involvement; pDM, preexisting diabetes mellitus; TBIL, total bilirubin.

Characteristics of patients based on different smoking and drinking statuses

The study compared patients’ characteristics among four groups: Neither, Smoking-only, Drinking-only, and Both group. The results are summarized in Table 2. Significant differences were observed in several variables when comparing neither group with the smoking-only group and with both group. Given that the drinking group consists of only eight patients, the statistical power of any inferential tests would be very low. Therefore, we will limit our analysis to descriptive statistics for this group.

Table 2.

Characteristics of the patients grouped by smoking and drinking status.

Variables	Neither	Smoking only	Drinking only^a	Both	p ^b	p ^c
Number	143	102	8	52
Age, years	59.00 (53.00, 65.00)	60.00 (53.25, 66.00)	54.50 (51.25, 66.75)	58.50 (53.75, 67.00)	0.808	0.635
Obesity, n (%)	19 (13.29)	19 (18.63)	1 (12.50)	8 (15.38)	0.255	0.708
Allergic diseases, n (%)	42 (29.37)	19 (18.63)	1 (12.50)	5 (9.62)	0.055	0.004
pDM, n (%)	26 (18.18)	15 (14.71)	0 (0.00)	5 (9.62)	0.472	0.148
NO-IGM, n (%)	31 (21.68)	54 (52.94)	4 (50.00)	35 (67.31)	<0.001	<0.001
OOI, n (%)
Extra-pancreatic bile duct	50 (34.97)	49 (48.04)	2 (25.00)	24 (46.15)	0.040	0.154
Lung	66 (46.15)	65 (63.73)	4 (50.00)	24 (46.15)	0.007	1.000
Salivary glands	52 (36.36)	29 (28.43)	5 (62.50)	12 (23.08)	0.193	0.081
Lymph nodes	67 (46.85)	63 (61.76)	7 (87.50)	31 (59.62)	0.021	0.115
Kidney	22 (15.38)	12 (11.76)	3 (37.50)	10 (19.23)	0.419	0.521
Number of OOI	2.00 (1.00, 3.00)	2.00 (2.00, 3.00)	3.00 (2.75, 3.25)	2.00 (2.00, 3.00)	0.013	0.297
Diffuse pancreatic enlargement, n (%)	80 (55.94)	54 (52.94)	6 (75.00)	31 (59.62)	0.642	0.647
Cyst formation, n (%)	15 (10.49)	17 (16.67)	2 (25.00)	10 (19.23)	0.157	0.106
EOS, ×10⁹/L	0.18 (0.08, 0.28)	0.23 (0.12, 0.40)	0.18 (0.12, 0.32)	0.22 (0.13, 0.39)	0.005	0.005
ALT, U/L	44.00 (21.00, 197.50)	63.00 (23.25, 188.75)	93.50 (21.75, 374.75)	111.50 (21.00, 232.50)	0.464	0.302
TBIL, μmol/L	20.00 (11.70, 53.80)	27.35 (12.03, 86.78)	64.95 (32.92, 149.40)	59.10 (13.47, 137.38)	0.225	0.008
GGT, U/L	122.00 (23.00, 656.00)	236.50 (41.00, 563.50)	259.50 (124.75, 448.00)	411.50 (37.25, 781.75)	0.274	0.034
FBG, mmol/L	5.60 (5.20, 6.80)	6.40 (5.50, 7.70)	6.00 (5.05, 6.92)	6.80 (5.68, 8.12)	0.003	0.002
IgG4, mg/L	7446.00 (4220.00, 15,450.00)	9885.00 (4427.50, 14,875.00)	10,450.00 (5815.00, 12,601.50)	5624.50 (3430.00, 13,150.00)	0.641	0.070

Between-group comparison was not performed for the “drinking only” group owing to its limited sample size, as this could adversely affect the robustness of statistical analyses.

Neither versus Smoking-only group, the significance threshold set at 0.025 (0.05/2) following Bonferroni correction.

Neither versus Both group, the significance threshold set at 0.025 (0.05/2) following Bonferroni correction.

The prevalence of NO-IGM was significantly higher in the smoking-only group (52.94%) and the both group (67.31%) compared to the neither group (21.68%) (both p < 0.001). The FBG in the smoking-only group (median, 6.40 mmol/L) and the both group (median, 6.80 mmol/L) were significantly higher than those in the neither group (median, 5.60 mmol/L, p = 0.003 and 0.002, respectively). The differences in the distribution of the number of OOI and EOS between the neither group and the smoking-only group were statistically significant (both p < 0.025). The differences in the distribution of allergic diseases, EOS, and TBIL between the neither group and the both group were also statistically significant (all p < 0.025).

The relationship between different smoking and drinking statuses and type 1 AIP-related NO-IGM

Modified Poisson regression was employed to investigate the relationship between different smoking and drinking statuses and AIP-related NO-IGM, as shown in Table 3. After adjusting for covariates (age, EOS, obesity, pDM, and IgG4), the risk of NO-IGM in the smoking-only group was 2.44 times that of the neither group (RR, 2.44; 95% CI, 1.70–3.51, p < 0.001). The risk in the both group was 2.84 times that of the neither group (RR, 2.84; 95% CI, 1.93–4.19, p < 0.001). By comparing these two RR values (2.84 and 2.44, respectively), it can be inferred that heavy drinking also contributes to an increased risk of NO-IGM.

Table 3.

The relationship between different smoking and drinking statuses and AIP-related NO-IGM using modified Poisson regression.

Exposure status	Crude model, RR (95% CI) p	Adjusted model,^a RR (95% CI) p
Smoking only vs neither	2.44 (1.70, 3.50) p < 0.001	2.44 (1.70, 3.51) p < 0.001
Both vs neither	3.10 (2.16, 4.47) p < 0.001	2.84 (1.93, 4.19) p < 0.001
Effects of heavy drinking	Estimated RR > 1	Estimated RR > 1

The model was adjusted for EOS, obesity, pDM, age, and IgG4.

AIP, autoimmune pancreatitis; EOS, eosinophil; IgG4, immunoglobulin G4; pDM, preexisting diabetes mellitus; RR, relative risk.

Discussion

To the best of our knowledge, the present study is the first study to specifically investigate the association between smoking, heavy drinking, and NO-IGM in male patients with type 1 AIP. In this retrospective cohort study of 305 patients, we observed that smoking and heavy drinking may increase the risk of type 1 AIP-related NO-IGM.

Smoking and alcohol consumption are well-recognized factors that contribute to pancreatic damage. Nicotine, the primary component of tobacco, has been shown to exert toxic effects on pancreatic beta cells, leading to impaired insulin secretion and reduced insulin sensitivity.^26,27 A study conducted in mice models revealed that cigarette smoke exposure leads to β-cell dysfunction through the activation of oxidative stress and ceramide accumulation. Even after smoking cessation, β-cell function remained impaired, with reduced insulin secretion, β-cell proliferation, and increased islet ceramide levels. The ex vivo exposure of β-cells to cigarette smoke extract corroborated these findings, showing a direct link between ceramide accumulation and β-cell dysfunction.²⁸ Similarly, a population-based study, which assessed a non-diabetic Chinese cohort, found a dose-dependent relationship between cigarette smoking and impaired β-cell function, as indicated by decreased HOMA%B values. Heavy smokers exhibited elevated HbA1c levels and an increased risk of developing type 2 diabetes, reinforcing the negative impact of smoking on glucose regulation.²⁹ Alcohol consumption is a widely recognized risk factor for both acute and chronic pancreatitis. Research has shown that alcohol consumption contributes to pancreatitis by impairing the function of the cystic fibrosis transmembrane conductance regulator (CFTR) in the pancreas. Alcohol reduces CFTR expression and disrupts its localization, leading to impaired pancreatic fluid and bicarbonate secretion. Metabolites of alcohol and fatty acids inhibit CFTR activity by increasing intracellular calcium levels, depleting adenosine triphosphate, and depolarizing mitochondrial membranes, and these disruptions exacerbate pancreatic inflammation.³⁰ A systematic review and meta-analysis confirm a dose-response relationship between alcohol consumption and pancreatitis risk. Consuming more than 100 g of alcohol per day significantly increases the risk of chronic pancreatitis.³¹ A clinical study,³² which included 59 patients with definite type 1 AIP, is closely related to the present study. Multivariate regression analysis in that study indicated that smoking was a risk factor for DM at initial diagnosis of AIP (OR, 4.92; 95% CI, 1.22–19.9; p = 0.025). However, alcohol consumption was not included in the multivariate regression analysis in that study. Moreover, the combined effect of alcohol and cigarette smoke exacerbates pancreatic damage. In pancreatic acinar cells, co-exposure to alcohol and cigarette smoke extract induces significant endoplasmic reticulum stress, leading to increased cell death. Cigarette smoke suppresses the adaptive unfolded protein response triggered by alcohol while promoting oxidative stress and C/EBP homologous protein-mediated apoptosis pathways.³³

It is relatively common for AIP and DM to coexist. A meta-analysis including 6522 AIP patients showed that the overall prevalence of diabetes in AIP (including type 1 and 2) was estimated to be 37%.³⁴ 17% to 65% of patients with AIP are simultaneously diagnosed with diabetes.¹⁸ This type of diabetes is known as type 3c DM (T3cDM) and is characterized by impaired pancreatic endocrine function, often resulting from chronic inflammation and fibrosis that affect both the exocrine and endocrine compartments of the pancreas.³⁵ The pathogenesis of T3cDM in AIP is closely linked to the autoimmune-mediated destruction of pancreatic islets.³⁶ The development of diabetes in AIP is primarily driven by the infiltration of CD4+ and CD8+ T-cells into the pancreatic islets and exocrine tissues, leading to the destruction of insulin-producing β-cells and impaired glucose tolerance.³⁶ The presence of autoantibodies, such as those against amylase α-2A, which have been identified as a marker for both AIP and fulminant type 1 diabetes, contributes to the progression of this process.³⁷ The detection of these autoantibodies suggests a common autoimmune etiology underlying both conditions, highlighting the close immunological relationship between AIP and fulminant type 1 diabetes.³⁷ Steroid therapy in the treatment of AIP has been shown to significantly impact the clinical course of diabetes. Steroid therapy can lead to improvements in glycemic control, as evidenced by reductions in HbA1c levels and insulin requirements.^19,38 Previous research conducted at our center has indicated that steroid therapy had a beneficial effect on the progression of DM in nearly half of AIP patients complicated with DM at diagnosis, particularly in those with normal GGT levels at diagnosis and no pancreatic atrophy following steroid therapy.¹⁸ However, the long-term use of corticosteroids may also lead to adverse metabolic effects, including insulin resistance and worsening of glycemic control.^39,40 Therefore, careful monitoring and adjustment of steroid therapy are essential to balance the benefits and risks in patients with AIP-associated diabetes.

Given the aforementioned content, we cautiously propose a “two-hit” hypothesis to explain the development of endocrine dysfunction in patients with type 1 AIP. The first hit involves the detrimental effects of smoking or heavy drinking on pancreatic tissue. The second hit is the onset of AIP, which further exacerbates pancreatic injury through autoimmune-mediated inflammation and fibrosis. These sequential insults collectively impair pancreatic endocrine function. The concept of “two-hit” is illustrated in Figure 2.

Figure 2.

The illustration depicting the “two-hit” hypothesis.

In this study, we employed modified Poisson regression to assess the association between smoking, heavy drinking, and IGM, rather than the more commonly used logistic regression. This approach was chosen because modified Poisson regression directly estimates RRs, which are more interpretable and clinically relevant than odds ratios derived from logistic regression, especially when the outcome of interest is not rare (the prevalence of NO-IGM was 40.66% in the cohort). Logistic regression tends to overestimate the effect size when the outcome prevalence is high, leading to potentially misleading conclusions.⁴¹ In addition, the use of a robust sandwich variance estimator in modified Poisson regression accounts for potential model misspecification and ensures more reliable standard errors and CIs.²¹ This methodological choice enhances the validity and interpretability of our findings, providing a more accurate assessment.

This study has several limitations that should be acknowledged. First, the retrospective design inherently introduces the risk of recall and selection biases, particularly in the collection of smoking and alcohol consumption data, which were self-reported and subject to potential inaccuracies. Second, since the proportion of female patients who smoked or consumed alcohol was very low in this cohort, the study population was restricted to male patients with type 1 AIP, which may limit the generalizability of our findings to female patients. Third, while we adjusted for several potential confounders, residual confounding due to unmeasured factors, such as dietary habits, physical activity levels, cannot be ruled out. Fourth, smoking and heavy drinking may have an interaction effect, which could lead to inaccurate indirect inferences about the impact of heavy drinking on NO-IGM. Fifth, the current study is a retrospective cohort study without a priori sample size calculation. However, considering that AIP is a rare disease, our inclusion of 305 male patients with type 1 AIP represents one of the larger sample sizes in studies of this kind to date. Although we observed statistically significant associations between smoking, heavy drinking, and NO-IGM, future prospective studies should perform appropriate sample size calculations based on the effect size estimates from our study to ensure adequate statistical power. Sixth, this study is a clinical investigation and does not address the molecular mechanisms underlying the association of smoking, drinking, and AIP-related impaired glucose metabolism. Further molecular research is required to elucidate the specific cytokines and biological pathways underlying the observed association of smoking and drinking status with NO-IGM.

Conclusion

In conclusion, this retrospective cohort study of 305 male patients with type 1 AIP demonstrates that smoking and heavy drinking may significantly increase the risk of AIP-related NO-IGM. Our findings reveal that patients who both smoke and drink heavily have nearly three times (RR 2.84) the risk of developing NO-IGM compared to those with neither habit, while smoking alone doubles (RR 2.44) this risk. These results support our proposed “two-hit” hypothesis, wherein lifestyle factors create initial pancreatic damage that is then exacerbated by autoimmune inflammation. Future studies with larger, more diverse cohorts and more detailed exposure assessments are warranted to validate our findings.

Supplemental Material

sj-pdf-1-taj-10.1177_20406223251371512 – Supplemental material for Smoking, alcohol consumption, and new-onset impaired glucose metabolism in male patients with type 1 autoimmune pancreatitis: a retrospective cohort study

Supplemental material, sj-pdf-1-taj-10.1177_20406223251371512 for Smoking, alcohol consumption, and new-onset impaired glucose metabolism in male patients with type 1 autoimmune pancreatitis: a retrospective cohort study by Wenfeng Xi, Xiaoyin Bai, Tao Guo, Hanze Du, Yueyi Zhang, Xinyuan Cao, Qingwei Jiang, Yunlu Feng and Aiming Yang in Therapeutic Advances in Chronic Disease

Footnotes

Acknowledgements

None.

Declarations

ORCID iDs

Tao Guo

Aiming Yang

Supplemental material

Supplemental material for this article is available online.

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