Kidney Res Clin Pract > Volume 40(2); 2021 > Article |
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Funding
This work was supported by the Industrial Strategic Technology Development Program - Development of bio-core technology (10077474, Development of early diagnosis technology for acute/chronic renal failure) funded by the Ministry of Trade, Industry and Energy (Republic of Korea).
Authors’ contributions
Conceptualization: SP, HL, KK, KWJ, DKK
Data curation: SL, YK, YL, MWK, YCK, SSH, HL, JPL, KWJ, CSL, YSK, DKK
Formal analysis: SP, KK, SL, YK
Funding acquisition: SL, YK, DKK
Investigation: SP, DKK
Methodology: HL, JPL, KWJ, CSL, YSK, DKK
Writing–original draft: All authors
Writing–review & editing: All authors
All authors read and approved the final manuscript.
Characteristic |
Alcohol intake (drink/wk) |
|||
---|---|---|---|---|
0 or 1 | >1 and ≤7 | >7 and ≤14 | >14 | |
No. of participants | 3,694 | 83,392 | 67,522 | 57,525 |
Alcohol use (time/wk) | 1 (1‒1) | 5 (3‒6) | 10 (9‒12) | 21 (17‒28) |
Age (yr) | 59 (51‒64) | 58 (50‒63) | 58 (50‒63) | 58 (51‒63) |
Sex | ||||
Female | 2,406 (65.1) | 49,677 (59.6) | 30,560 (45.3) | 16,129 (28.0) |
Male | 1,288 (34.9) | 33,715 (40.4) | 36,962 (54.7) | 41,396 (72.0) |
Body mass index (kg/m2) | 25.9 (23.4‒29.2) | 26.0 (23.6‒28.9) | 26.4 (24.0‒29.2) | 27.2 (24.8‒29.9) |
Obesitya | 760 (20.6) | 15,827 (19.0) | 13,400 (19.8) | 14,157 (24.6) |
Waist circumference (cm) | 86 (77‒96) | 87 (78‒96) | 90 (81‒98) | 94 (86‒102) |
Central obesityb | 1,119 (30.3) | 23,373 (28.0) | 19,173 (28.4) | 19,377 (33.7) |
Previous history of stroke, angina, or heart attack | 178 (4.8) | 3,461 (4.2) | 3,255 (4.8) | 3,272 (5.7) |
Hypertension | 641 (17.4) | 13,982 (16.8) | 12,298 (18.2) | 13,335 (23.2) |
Systolic BP (mmHg) | 134.0 (122.5‒147.5) | 134.0 (122.5‒147.0) | 136.0 (125.0‒148.5) | 140.5 (129.0‒153.0) |
Diastolic BP (mmHg) | 80.5 (73.5‒87.0) | 81.0 (74.5‒87.5) | 82.0 (75.5‒89.0) | 84.5 (78.0‒91.5) |
Diabetes mellitus | 154 (4.2) | 3,025 (3.6) | 2,346 (3.5) | 2,512 (4.4) |
Hemoglobin A1c (mmol/mol) | 35.3 (32.9‒37.9) | 35.0 (32.6‒37.4) | 34.7 (32.3‒37.2) | 34.8 (32.3‒37.3) |
Dyslipidemia | 566 (15.3) | 11,534 (13.8) | 10,613 (15.7) | 13,335 (23.2) |
Total cholesterol (mmol/L) | 5.6 (4.9‒6.4) | 5.7 (4.9‒6.4) | 5.7 (5.0‒6.4) | 5.7 (5.0‒6.5) |
LDL cholesterol (mmol/L) | 3.5 (3.0‒4.1) | 3.5 (3.0‒4.1) | 3.5 (3.0‒4.1) | 3.5 (3.0‒4.1) |
HDL cholesterol (mmol/L) | 1.4 (1.2‒1.7) | 1.4 (1.2‒1.7) | 1.4 (1.2‒1.7) | 1.5 (1.2‒1.7) |
History of smoking | ||||
None | 2,506 (67.8) | 52,079 (62.5) | 34,176 (50.6) | 20,845 (36.2) |
Ex-smoker | 990 (26.8) | 25,977 (31.2) | 27,155 (40.2) | 27,159 (47.2) |
Current smoker | 198 (5.4) | 5,336 (6.4) | 6,191 (9.2) | 9,521 (16.6) |
Moderate physical activity (day/wk) | 3 (2‒5) | 3 (2‒5) | 3 (2‒5) | 3 (2‒5) |
No. of illnesses | 1 (0‒3) | 1 (0‒2) | 1 (0‒2) | 1 (0‒3) |
No. of treatments received | 2 (0‒3) | 1 (0‒3) | 1 (0‒3) | 2 (0‒3) |
Income grade (GBP) | ||||
<18,000 | 941 (25.5) | 15,218 (18.2) | 10,555 (15.6) | 9,232 (16.0) |
18,000–30,999 | 1,010 (27.3) | 21,262 (25.5) | 16,129 (23.9) | 13,238 (23.0) |
31,000–51,999 | 962 (26.0) | 23,223 (27.8) | 18,904 (28.0) | 15,809 (27.5) |
52,000–100,000 | 659 (17.8) | 18,980 (22.8) | 16,818 (24.9) | 14,487 (25.2) |
>100,000 | 122 (3.3) | 4,709 (5.6) | 5,116 (7.6) | 4,759 (8.3) |
No. of household member | 2 (2‒3) | 2 (2‒3) | 2 (2‒3) | 2 (2‒3) |
eGFR (mL/min/1.73 m2) | 91.9 (81.8‒99.1) | 92.3 (82.6‒99.5) | 92.6 (83.4‒99.6) | 93.4 (84.6‒100.2) |
< 60 mL/min/1.73 m2 | 103 (2.8) | 1,588 (1.9) | 1,115 (1.7) | 875 (1.5) |
For the prevalent CKD outcome, logistic regression analysis was performed (OR), and for the incident ESKD outcome, Cox regression analysis was performed (HR).
Multivariable model 1 was adjusted for age, sex, history of diabetes mellitus, and hypertension. When analyzing the incident ESKD outcome, the baseline eGFR was additionally adjusted.
Multivariable model 2 was adjusted for age, sex, body mass index, waist circumference, history of angina/heart attack/stroke, diabetes mellitus, hemoglobin A1c level, hypertension, systolic blood pressure (BP), diastolic BP, dyslipidemia, total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, smoking (nonsmoker, ex-smoker, current smoker), average days of moderate physical activity per week, number of illnesses, number of treatments received, income grade (<₤18,000, ₤18,000–₤30,999, ₤31,000–₤51,999, ₤52,000–₤100,000, and >₤100,000), and number of household members.
CI, confidence interval; CKD, chronic kidney disease; ESKD, end-stage kidney disease; HR, hazard ratio; OR, odds ratio.
Univariable model |
Multivariable model |
|||
---|---|---|---|---|
Exp(β) (95% CI) | p-value | Adjusted exp(β) (95% CI) | p-value | |
For numerical amounts of alcohol intake | 0.96 (0.92–0.99) | 0.04 | 0.95 (0.92–0.99) | 0.02 |
Reported exp(β) and confidence interval values were from a linear regression model with amounts of alcohol use as the outcome variable and polygenic risk score (PRS) for chronic kidney disease stage ≥ 3 as the exposure variable. The effect sizes of one standard deviation increment of the PRS are reported. The multivariable model was adjusted for age, sex, diabetes mellitus, and hypertension.
CI, confidence interval.
Sehoon Park
https://orcid.org/0000-0002-4221-2453
Soojin Lee
https://orcid.org/0000-0001-5633-3961
Yaerim Kim
https://orcid.org/0000-0003-1596-1528
Yeonhee Lee
https://orcid.org/0000-0002-9216-420X
Min Woo Kang
https://orcid.org/0000-0002-9411-3481
Kwangsoo Kim
https://orcid.org/0000-0002-4586-5062
Yong Chul Kim
https://orcid.org/0000-0003-3215-8681
Seung Seok Han
https://orcid.org/0000-0003-0137-5261
Hajeong Lee
https://orcid.org/0000-0002-1873-1587
Jung Pyo Lee
https://orcid.org/0000-0002-4714-1260
Kwon Wook Joo
https://orcid.org/0000-0001-9941-7858
Chun Soo Lim
https://orcid.org/0000-0001-9123-6542
Yon Su Kim
https://orcid.org/0000-0003-3091-2388
Dong Ki Kim
https://orcid.org/0000-0002-5195-7852
Impact of chronic kidney disease on mortality: A nationwide cohort study2019 September;38(3)