Nicotine Dependence as a Prognostic Factor for Glycaemic Control in Non-Diabetic Smokers: A Nationwide Korean Survey

By Ji Hyeon Park¹, Yoo Jeong Lee², In Cheol Hwang³, Hong Yup Ahn⁴

Affiliations

1. Department of General Surgery, Gil Medical Centre, Gachon University College of Medicine, Incheon, Republic of Korea
2. Palliative Care Centre and Department of Family Medicine, Korea University Guro Hospital, Seoul, Republic of Korea
3. Department of Family Medicine, Gil Medical Centre, Gachon University College of Medicine, Incheon, Republic of Korea
4. Department of Statistics, Dongguk University, Seoul, Republic of Korea

doi: 10.29271/jcpsp.2026.05.680

ABSTRACT
This study examined the independent relationship between nicotine dependence and glycaemic indices among non-diabetic smokers. Data from 672 non-diabetic smokers who participated in a nationwide Korean survey were analysed. The glycaemic indices examined were serum fasting glucose and glycated haemoglobin. Nicotine dependence was assessed using the time to first cigarette after arising. Covariates included demographics, health-related habits, comorbidities, and daily smoking amount. Stepwise multivariate regression analysis showed that nicotine dependence was significantly related to both glycaemic indices, independently of confounders, including the amount smoked daily. In conclusion, this study shows that nicotine dependence is independently associated with glycaemic control among non-diabetic smokers.

Key Words: Glycated haemoglobin, Glycaemic control, Nicotine dependence, Smoking.

Evidence linking smoking and the development of diabetes is incontrovertible. A meta-analysis of 88 prospective studies showed that current smoking significantly increases the risk of diabetes development (relative risk = 1.37).¹ Although the mechanisms remain to be elucidated, they would appear to involve reduced insulin secretion and enhanced insulin resistance indu-ced directly or indirectly by nicotine.² However, few studies have investigated the relationship between smoking and glycaemic control among non-diabetic individuals.³ In addition, nicotine dependence has not often been differentiated from cigarette smoking in several studies.² Therefore, the relationship between nicotine dependence and glycaemic control among non- diabetics was investigated, in consideration of current smoking amount.

Data were extracted from the 2022 Korea National Health and Nutrition Examination Survey, which is a nationwide survey using stratified, multi-stage, and clustered sampling methods. Information  on  the  survey  has  been  described  in  detail.⁴

Initially, 783 current smokers were identified, and after exclud-ing 111 patients with type II diabetes, 672 were included in the analysis.

Nicotine dependence was assessed based on the time to first cigarette after arising, which is often regarded as the best single indicator.⁵ Response options were ≤5 minutes, 6-30 minutes, 30-60 minutes, and >60 minutes. Subjects who smoked within 30 minutes of arising were considered to be nicotine dependent. Fasting glucose levels were assessed using an enzymatic assay, and glycated haemoglobin (HbA1c) levels were measured by high-performance liquid chroma- tography.

Covariates included demographics (age, gender, attained education level, household income level, and current job), comorbidities (hypertension and obesity), health-related habits (exercise and drinking), and daily smoking amount. Educational level was grouped as middle school or below and high school or above. Family size-adjusted monthly income was used as an index of economic status. Drinking more than twice per week was defined as frequent drinking. Aerobic exercise was determined by ≥2.5 hours/week of mode-rate-intensity activities, ≥1.25 hours/week of high-intensity activities, or a combination of activities. Obesity was defined as a body mass  index  of  ≥25  kg/m².

 

 

Table I: Characteristics of participants according to nicotine dependence.

Parameters	Without nicotine dependence	With nicotine dependence	p-values
Number of participants	330	342
Demographics
Age, years	46 (34–62)	51 (39–61)	0.045
Male gender	285 (86.4)	268 (78.4)	0.007
Middle school graduate or below	48 (14.9)	87 (26.1)	<0.001
Less than average household income	135 (40.9)	156 (45.8)	0.206
Currently no job	72 (23.7)	81 (26.1)	0.484
Health-related habits
Frequent drinking (≥2 times/week)	147 (45.6)	161 (48.4)	0.489
Aerobic exercisea	145 (47.7)	147 (47.6)	0.975
Comorbidities
Obesity (body mass index ≥25kg/m2)	132 (40.4)	134 (39.4)	0.801
Hypertension	64 (19.4)	74 (21.6)	0.472
Daily smoking amount, cigarette	10 (5–15)	15 (10–20)	<0.001
Glycaemic index
Serum fasting glucose, mg/dL	95 (90–103)	98 (91–105)	0.018
HbA1c, %	5.4 (5.2–5.6)	5.5 (5.2–5.8)	<0.001
HbA1c: Glycated haemoglobin. Data are presented as medians (interquartile ranges) or numbers (percentages), and p-values were determined using the Wilcoxon rank-sum test or the chi-square test. a≥2.5 hours/week of moderate-intensity activities, ≥1.25 hours/week of high-intensity activities, or a combination of activities.

Table II: Factors associated with glycaemic control, including nicotine dependence.

Variables	Serum glucose level	p-values	HbA1c level	p-values
	ßa (95% CI)		ßa (95% CI)
Nicotine dependence	3.34 (1.04–5.64)	0.004	0.10 (0.02–0.18)	0.020
Age (per 1-year increase)	0.18 (0.11–0.26)	<0.001	0.01 (0.01–0.01)	<0.001
Frequent drinking (≥ 2 times/week)	3.79 (1.47–6.11)	0.001
Obesity	7.15 (4.79–9.51)	<0.001	0.23 (0.00–0.01)	<0.001
Smoking amount (per 1-cigarette increase)			0.01 (0.00–0.01)	0.009
ß: Regression coefficient; CI: Confidence interval; HbA1c: Glycated haemoglobin. aFrom stepwise multivariate regression models adjusted for demographics (age, gender, education level, economic level, current job), and comorbidities (hypertension and obesity), health-related habits (exercise and drinking), and daily smoking amount.

Characteristics were compared by nicotine dependence using the Wilcoxon rank-sum test for continuous variables (i.e., age, daily smoking amount, fasting glucose level, and HbA1c level; the variables were not normally distributed, as indicated by the skewness and kurtosis tests for normality) or χ² test for categorical variables.  Stepwise multivariate regression models were utilised to identify factors associated with glycaemic control indices. The statistical analysis was conducted using STATA MP 17.0 (Stata Corp., TX), and p-values <0.05 were deemed statistically significant.

Among a total of 672 participants, approximately half had nicotine dependence, and they were more likely to be older, female, have a low educational status, be smokers, and have poor glycaemic control (Table I).

Table II shows factors associated with high levels of fasting glucose or HbA1c using stepwise multivariate regression models. Nicotine dependence was significantly associated with both indices independently of confounders, including daily smoking amount.

Diabetes is the fastest-growing public health concern, and thus its prevention and/or early detection should be the focus of research attention.⁶ It has been well documented that smokers are at risk of developing overt diabetes. This preli-minary study indicates that this association exists prior to the emergence of diabetes status and that the risk of diabetes development may be influenced by nicotine dependence, independent of smo-king amount. The results suggest that nicotine dependence in smokers should be regularly asse-ssed, and if found to be high or to increase, glycaemic control should be monitored frequently.

To the best of the authors’ knowledge, only one previous study is comparable to this one. In that study, the smoking profiles of normoglycaemic and prediabetic adult Caucasians were examined.³ The authors concluded that smoking can accele-rate progression from normoglycaemia to pre-diabetes. How-ever, the effect of nicotine dependence was not considered with respect to smoking amount; rather, the effects of smoking amount and nicotine dependence were examined separately.

This study has some limitations. First, due to the cross-sectional design, causal inference was not possible. Second, a more comprehensive dataset that includes full Fagerstrom Test for Nicotine Dependence results, family histories of diabe-tes, and serum insulin levels is needed. In addition, longi-tudinal studies based on smoking cessation clinic data are required to examine temporal changes.

FUNDING:
This study was funded by Gachon University Gil Medical Centre (Grant No. FRD2023-10).

ETHICAL APPROVAL:
The Institutional Review Board (IRB) of Gachon University Gil Medical Centre (IRB No. GCIRB2024-295) approved the study protocol.

PATIENTS’ CONSENT:
All participants provided written informed consent.

COMPETING INTEREST:
The authors declared no conflict of interest.

AUTHORS’ CONTRIBUTION:
JHP, YJL: Interpretation and manuscript preparation.
ICH: Conceptualisation, methodology, manuscript review, and editing.
HYA: Formal analysis and interpretation.
All authors approved the final version of the manuscript to be published.

REFERENCES

1. Pan A, Wang Y, Talaei M, Hu FB, Wu T. Relation of active, passive, and quitting smoking with incident type 2 diabetes: A systematic review and meta-analysis. Lancet Diabetes Endocrinol 2015; 3(12):958-67. doi: 10.1016/S2213-8587 (15)00316-2.
2. Durlach V, Verges B, Al-Salameh A, Bahougne T, Benzerouk F, Berlin I, et al. Smoking and diabetes interplay: A comprehensive review and joint statement. Diabetes Metab 2022; 48(6):101370. doi: 10.1016/j.diabet.2022.101370.
3. Aeschbacher S, Schoen T, Clair C, Schillinger P, Schönenberger S, Risch M, et al. Association of smoking and nicotine dependence with pre-diabetes in young and healthy adults. Swiss Med Wkly 2014; 144:w14019. doi: 10.4414/ smw.2014.14019.
4. Kweon S, Kim Y, Jang MJ, Kim Y, Kim K, Choi S, et al. Data resource profile: The Korea National Health and Nutrition Examination Survey (KNHANES). Int J Epidemiol 2014; 43(1):69-77. doi: 10.1093/ije/dyt228.
5. Fagerstrom K. Time to first cigarette; the best single indi-cator of tobacco dependence? Monaldi Arch Chest Dis 2003; 59(1):91-4.
6. Hossain MJ, Al-Mamun M, Islam MR. Diabetes mellitus, the fastest growing global public health concern: Early detection should be focused. Health Sci Rep 2024; 7(3):e2004. doi: 10.1002/hsr2.2004.