Data source and study setting
We used the nationwide database provided by National Health Insurance Service (NHIS), covering 97% of the population in Korea. The NHIS recommends that all individuals aged ≥ 40 years and employers of all age among the insured, undergo a general health screening at least every two years14, which includes a standard questionnaire of past medical history, current medications, and lifestyle behaviors (smoking, drinking, and physical activity), anthropometric measurements (height, weight, body mass index, and blood pressure), and laboratory tests. In addition, medical treatment database (based on medical bills claimed by medical service providers for their medical expense claims) can be linked with the health examination database. Therefore, the NHIS retains an extensive health information dataset of the entire Korean population.
Study population
Among participants who underwent the health screening examination between 2009 and 2012 we identified 2,746,079 individuals with DM as follows: (1) fasting plasma glucose ≥ 126 mg/dL at the health screening or (2) a previous history of DM which was defined as International Classification of Disease (ICD)-10 code (E11–14) diagnosis with at least one claim per year for the prescription of antidiabetic agents before the health screening. This definition was based on the consensus of relevant findings widely used in previous studies15,16 4,5. We excluded participants aged under 20 (n = 390), and then selected current smokers (n = 758,049) according to the definition of current smokers given by the World Health Organization17. Among them, 485,547 participants underwent the follow-up health examination within two years. We excluded those who had previously been diagnosed with any cancer (n = 54,192) or pneumonia (n = 56,067) before the second health screening and those with missing variables used in the study (n = 33,891). To reduce the effect of reverse causality, we applied a one-year lag time by excluding participants who were diagnosed with pneumonia (n = 7,293) and who died (n = 1,306) within one year after the second health examination period. Finally, we included a total of 332,798 participants (Fig. 1).
Definition of change in amount of cigarette smoking
Information on smoking status and smoking behavior change was obtained from a self-administered questionnaire of the national health examination in the NHIS. The participants who answered that they were current smokers were asked about the average number of cigarettes per day and duration of smoking in years. At the first examination, participants were queried on the number of cigarettes smoked per day, and were grouped as (1) light smoker (< 10 cigarettes per day), (2) moderate smoker (10–19 cigarettes per day), and (3) heavy smoker (≥ 20 cigarettes per day). Then, s7tudy participants in each of the three groups were categorized into four subgroups by comparing the number of cigarettes per day between the first examination and the follow-up examination18: (1) quitters were those who quit smoking, (2) reducers were those who reduced the number of cigarettes by 20% or more, (3) sustainers were those who reduced the number of cigarettes by less than 20% or increased by less than 20%, and (4) increasers were those who increased the number of cigarettes by 20% or more.
Study outcomes and follow-up
The primary endpoint of this study was pneumonia hospitalization, which was identified on the basis of the ICD-10 codes of J10.0, J11.0, and J12 to J18 administered for hospital admission. The cohort was followed from one year after the date of the second health examination to the date of pneumonia hospitalization, death, or until the end of the study period (December 31, 2018), whichever came first.
Covariates
Household income was categorized into quartiles based on insurance premium levels (in Korea, insurance premiums are determined by income level), with those covered by Medical Aid (the poorest 3%) being merged into the lowest income quartile. Area of residence was dichotomized by rural and urban.
Alcohol drinking status classified participants into the following four groups according to the amount of alcohol consumed per day: (1) none, (2) mild (< 15 g of alcohol/day), (3) moderate (15–30 g of alcohol/day), and (4) heavy (≥ 30 g/day). Regular physical activity was defined as moderate physical activity for more than 30 min and more than 5 days per week during the past week. Body mass index was calculated using weight (kg) divided by height (m) in meters squared.
Comorbid medical conditions were assessed using comprehensive information regarding past medical history and clinical and pharmacy ICD-10 codes. Comorbidities including arterial hypertension (I10-I13 or I15), dyslipidemia (E78), chronic kidney disease (CKD; N18 or N19), interstitial lung disease [ILD, J84.0, J84.1, J84.8], asthma (J45 or J46), and chronic obstructive pulmonary disease [COPD, J43 or J44]) were included in our analysis.
For stratified analyses, DM patients were categorized considering DM severity by the duration of DM (newly-onset DM, DM of duration < 5 years, and DM of duration ≥ 5 years), the number of oral antidiabetic agents used (0, 1–2, and ≥ 3), and use of insulin.
Statistical analysis
The baseline characteristics are presented as the mean ± standard deviation and number with percentage for categorical variables. The rates of pneumonia hospitalization were presented per 1,000 person-years. Cox proportional hazards regression analysis was conducted to evaluate the association between smoking behavior change and pneumonia hospitalization among individuals with DM. Model 2 was adjusted for age, sex, body mass index, household income, area of residence, duration of smoking, previous pack-years of smoking, alcohol consumption, regular physical activity, comorbidities (hypertension, dyslipidemia, CKD, and pulmonary diseases (defined as any of ILD, asthma, or COPD). Waist circumference, blood pressure, and laboratory findings was not included for adjustment to evade duplication with other covariates (body mass index, hypertension, dyslipidemia). At final model 3, as our study focused on DM population, DM-related variables including fasting glucose level, duration of DM, and insulin use were additionally adjusted compared to model 2.
Stratification analyses by age (< 65 years and ≥ 65 years), sex, smoking level at the first examination (light, moderate, or heavy smoker), pulmonary disease, duration of DM, the number of oral antidiabetic agents, and the use of insulin were performed to see the potentially different association of smoking behavior change with pneumonia hospitalization. The statistical analyses were performed using SAS version 9.4 (SAS Institute Inc., Cary, NC, USA). P values < 0.05 were considered statistically significant.
Ethics statement
This study was approved by the Institutional Review Board of Samsung Medical Center (SMC 2022-07-072). Anonymized and de-identified information was used for analyses; therefore, informed consent was not required. The database is open to all researchers whose study protocols are approved by the official review committee.