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. 2019 Dec 20;9(1):19511.
doi: 10.1038/s41598-019-56113-7.

Smoking and risk of incident end-stage kidney disease in general population: A Nationwide Population-based Cohort Study from Korea

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Smoking and risk of incident end-stage kidney disease in general population: A Nationwide Population-based Cohort Study from Korea

Hong Sang Choi et al. Sci Rep. .

Abstract

We analyzed data from the Korean National Health Insurance Service (NHIS) to investigate whether smoking increases the risk of end-stage kidney disease (ESKD). This retrospective nationwide population-based cohort study included the data of 23,232,091 participants who underwent at least one health examination between 2009 and 2012. Smoking status was recorded at baseline. The incidence of ESKD was identified via ICD-10 codes and special medical aid codes from the Korean National Health Insurance Service database till December 2016. A Cox proportional-hazards model with multivariable adjustment was used to evaluate the association between smoking and ESKD incidence. Overall, 24.6% of participants were current smokers; 13.5% and 61.9%, were ex- and non-smokers, respectively. Overall, 45,143 cases of ESKD developed during the follow-up period. Current smokers (hazard ratio [HR], 1.39; 95% confidence interval [CI], 1.35-1.43) and ex-smokers (HR, 1.09; 95% CI, 1.06-1.12) demonstrated a significant increase in the adjusted risk of ESKD compared to non-smokers. The risk of ESKD was directly proportional to the smoking duration, number of cigarettes smoked daily, and pack-years. In conclusion, smoking is associated with a greater risk of ESKD in the general Korean population; the risk increases with an increase in the smoking duration, number of cigarettes smoked daily, and pack-years.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
Relevance of smoking status to risk of incident ESKD. (A) Amount of cigarette per day. (B) Duration of smoking (years) and (C) pack-years. Hazard ratio of incident ESKD according to smoking status. Error bars represent 95% confidence intervals for lower and upper limits. Adjusted for age, sex, body mass index, alcohol consumption, regular exercise, income, diabetes mellitus, hypertension, chronic kidney disease, dyslipidemia, hemoglobin level and proteinuria.
Figure 2
Figure 2
Flow diagram of study population selection.

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