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Journal of Peking University (Health Sciences) ›› 2022, Vol. 54 ›› Issue (5): 1047-1055. doi: 10.19723/j.issn.1671-167X.2022.05.035

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Effect of modification of antihypertensive medications on the association of nitrogen dioxide long-term exposure and chronic kidney disease

Lin MA1,Jing-yi WU2,Shuang-cheng LI3,Peng-fei LI2,4,*(),Lu-xia ZHANG2,4,5,*()   

  1. 1. Office of Development Planning and Academic Development, Peking University, Beijing 100191, China
    2. Advanced Institute of Information Technology, Peking University, Hangzhou 311215, China
    3. Laboratory for Earth Surface Processes of the Ministry of Education, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
    4. National Institute of Health Data Science, Peking University, Beijing 100191, China
    5. Renal Division, Department of Medicine, Peking University First Hospital, Peking University Institute of Nephrology, Beijing 100034, China
  • Received:2022-05-09 Online:2022-10-18 Published:2022-10-14
  • Contact: Peng-fei LI,Lu-xia ZHANG E-mail:pfli@aiit.org.cn;zhanglx@bjmu.edu.cn
  • Supported by:
    the National Natural Science Foundation of China(72125009);the PKU-Baidu Fund(2020BD004);the PKU-Baidu Fund(2020BD005)

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Abstract:

Objective: To investigate the potential effect of modification of antihypertensive medications on the association of nitrogen dioxide (NO2) long-term exposure and chronic kidney disease (CKD). Methods: Data of the national representative sample of adult population from the China National Survey of Chronic Kidney Disease (2007-2010) were included in the analyses, and exposure data of NO2 were collected and matched. Generalized mixed-effects models were used to analyze the associations between NO2 and CKD, stratified by the presence of hypertension and taking antihypertensive medications. The stratified exposure-response curves of NO2 and CKD were fitted using the natural spine smoothing function. The modifying effects of antihypertensive medications on the association and the exposure-response curve of NO2 and CKD were analyzed. Results: Data of 45 136 participants were included, with an average age of (49.5±15.3) years. The annual average exposure concentration of NO2 was (7.2±6.4) μg/m3. Altogether 6 517 (14.4%) participants were taking antihypertensive medications, and 4 833 (10.7%) participants were identified as having CKD. After adjustment for potential confounders, in the hypertension population not using antihypertensive medications, long-term exposure to NO2 was associated with a significant increase risk of CKD (OR: 1.38, 95%CI: 1.24-1.54, P < 0.001); while in the hypertension population using antihypertensive medications, no significant association between long-term exposure to NO2 and CKD (OR: 0.96, 95%CI: 0.86-1.07, P=0.431) was observed. The exposure-response curve of NO2 and CKD suggested that there was a non-linear trend in the association between NO2 and CKD. The antihypertension medications showed significant modifying effects both on the association and the exposure-response curve of NO2 and CKD (interaction P < 0.001). Conclusion: The association between long-term exposure to NO2 and CKD was modified by antihypertensive medications. Taking antihypertensive medications may mitigate the effect of long-term exposure to NO2 on CKD.

Key words: Antihypertensive agents, Nitrogen dioxide, Chronic kidney disease, Effect modification

CLC Number: 

  • R692

Table 1

Basic characteristics of study population"

Items All
(n=45 136)		 Without HBP
(n=29 725)		 HBP+without anti-HBP
(n=8 894)		 HBP+anti-HBP
(n=6 517)		 Missing P
CKD 4 833(10.7) 2 056(6.9) 1 377(15.5) 1 400(21.5) 0 < 0.001
NO2/(μg/m3) 7.2±6.4 6.7±6.2 7.5±6.4 8.9±7.0 0 < 0.001
Age 49.5±15.3 45.5±14.3 54.4±14.5 61.4±11.7 0 < 0.001
Female 25 706(57.0) 17 488(58.8) 4 354(49.0) 3 864(59.3) 0 < 0.001
Rural 21 748(48.2) 14 539(48.9) 4 600(51.7) 2 609(40.0) 0 < 0.001
Region 0 < 0.001
  South 10 241(22.7) 7 596(25.6) 1 573(17.7) 1 072(16.4)
  North 15 124(33.5) 9 504(32.0) 3 141(35.3) 2 479(38.0)
  East 10 089(22.4) 5 522(18.6) 2 567(28.9) 2 000(30.7)
  Middle 2 661(5.9) 2 011(6.8) 386(4.3) 264(4.1)
  Northwest 4 026(8.9) 2 676(9.0) 819(9.2) 531(8.1)
  Southwest 2 995(6.6) 2 416(8.1) 408(4.6) 171(2.6)
Education 119 < 0.001
  None 4 630(10.3) 2 217(7.5) 1 321(14.9) 1 092(16.8)
  Primary school 8 395(18.6) 4 826(16.2) 2 071(23.3) 1 498(23.0)
  Middle school 12 517(27.7) 8 362(28.1) 2 486(28.0) 1 669(25.6)
  High school 11 332(25.1) 7 916(26.6) 1 977(22.2) 1 439(22.1)
  College and above 8 143(18.0) 6 325(21.3) 1 016(11.4) 802(12.3)
Smoking 39 < 0.001
  Never 34 452(76.3) 22 876(77.0) 6 356(71.5) 5 220(80.1)
  Sometimes 1 071(2.4) 702(2.4) 236(2.7) 133(2.0)
  Almost once a day 9 574(21.2) 6 119(20.6) 2 294(25.8) 1 161(17.8)
Alcohol consumption 96 < 0.001
  < 1 time/week 38 031(84.3) 25 430(85.6) 6 999(78.7) 5 602(86.0)
  1-2 times/week 2 485(5.5) 1 656(5.6) 532(6.0) 297(4.6)
  >3 times/week 4 524(10.0) 2 569(8.6) 1 350(15.2) 605(9.3)
Exercise 9 277 < 0.001
  Never 21 413(47.4) 14 146(47.6) 4 634(52.1) 2 633(40.4)
  0-3 h/week 4 807(10.7) 3 227(10.9) 840(9.4) 740(11.4)
  >3 h/week 9 639(21.4) 5 803(19.5) 1 831(20.6) 2 005(30.8)
BMI/(kg/m2) 23.9±3.7 23.0±3.4 25.2±3.7 25.7±3.8 332 < 0.001
Total cholesterol 4.9±1.3 4.7±1.3 5.0±1.3 5.2±1.6 17 < 0.001
Diabetes 10 568(23.4) 5 090(17.1) 2 841(31.9) 2 637(40.5) 43 < 0.001
CVD 1 152(2.6) 294(1.0) 201(2.3) 657(10.1) 0 < 0.001
Nephrotoxic medications used 1 468(3.3) 808(2.7) 314(3.5) 346(5.3) 0 < 0.001
eGFR/(mL/min·1.73 m2) 101.1±27.6 103.6±27.6 99.6±27.3 92.1±25.6 0 < 0.001
uACR/(mg/g) 6.7(3.0, 14.4) 6.0(2.8, 11.9) 8.1(3.4, 18.3) 10.1(4.3, 24.2) 0 < 0.001
Albuminuria 6 030(13.4) 3 162(10.6) 1 488(16.7) 1 380(21.2) 0 < 0.001

Table 2

The modifying effect of antihypertensive medications on the association of NO2 with CKD"

Per 10 μg/m3
increase of NO2		 Univariate analysis Model 1 Model 2 Model 3
OR P Pinteraction OR P Pinteraction OR P Pinteraction OR P Pinteraction
All 1.36
(1.30, 1.41)		 < 0.001 < 0.001 1.40
(1.33, 1.46)		 < 0.001 < 0.001 1.45
(1.39, 1.52)		 < 0.001 < 0.001 1.45
(1.37, 1.52)		 < 0.001 < 0.001
Without HBP 1.57
(1.48, 1.67)		 < 0.001 1.70
(1.60, 1.82)		 < 0.001 1.74
(1.62, 1.86)		 < 0.001 1.70
(1.59, 1.83)		 < 0.001
HBP+without anti-HBP 1.12
(1.02, 1.22)		 0.013 1.25
(1.14, 1.38)		 < 0.001 1.41
(1.27, 1.55)		 < 0.001 1.38
(1.24, 1.54)		 < 0.001
HBP+anti-HBP 0.92
(0.85, 1.00)		 0.065 0.91
(0.83, 1.00)		 0.048 0.91
(0.83, 1.01)		 0.064 0.96
(0.86, 1.07)		 0.431

Table 3

The modifying effect of antihypertensive medications on the association of NO2 with eGFR"

Per 10 μg/m3
increase of NO2		 Univariate analysis Model 1 Model 2 Model 3
RR P Pinteraction RR P Pinteraction RR P Pinteraction RR P Pinteraction
All 1.03
(1.03, 1.03)		 < 0.001 < 0.001 1.06
(1.06, 1.06)		 < 0.001 < 0.001 1.06
(1.06, 1.07)		 < 0.001 < 0.001 1.06
(1.06, 1.07)		 < 0.001 0.002
Without HBP 1.04
(1.03, 1.04)		 < 0.001 1.06
(1.06, 1.07)		 < 0.001 1.06
(1.06, 1.07)		 < 0.001 1.06
(1.06, 1.07)		 < 0.001
HBP+without anti-HBP 1.07
(1.07, 1.07)		 < 0.001 1.06
(1.06, 1.07)		 < 0.001 1.07
(1.07, 1.08)		 < 0.001 1.07
(1.07, 1.08)		 < 0.001
HBP+anti-HBP 1.02
(1.02, 1.03)		 < 0.001 1.04
(1.04, 1.05)		 < 0.001 1.06
(1.05, 1.06)		 < 0.001 1.06
(1.05, 1.06)		 < 0.001

Table 4

The modifying effect of antihypertensive medications on the association of NO2 with CKD by adjustment for different environmental covariates"

Per 10 μg/m3 increase of NO2 Adjusted for PM2.5 Adjusted for temperature Adjusted for relative humidity
OR P Pinteraction OR P Pinteraction OR P Pinteraction
All 1.80
(1.70, 1.90)		 < 0.001 < 0.001 1.55
(1.46, 1.64)		 < 0.001 < 0.001 1.45
(1.37, 1.53)		 < 0.001 < 0.001
Without HBP 2.12
(1.96, 2.28)		 < 0.001 1.90
(1.75, 2.06)		 < 0.001 1.77
(1.64, 1.92)		 < 0.001
HBP+without anti-HBP 1.65
(1.46, 1.86)		 < 0.001 1.38
(1.22, 1.56)		 < 0.001 1.28
(1.14, 1.44)		 < 0.001
HBP+anti-HBP 1.19
(1.06, 1.34)		 0.004 0.94
(0.83, 1.07)		 0.343 0.89
(0.79, 1.00)		 0.052

Figure 1

The modifying effect of antihypertensive medications on the exposure-response curve of NO2-CKD HBP, hypertension; anti-HBP, antihypertensive medications; CKD, chronic kidney disease; OR, odds ratio; NO2, nitrogen dioxide."

1 World Health Organization. Ambient (outdoor) air pollution [EB/OL]. (2021-09-22) [2022-03-07]. https://www.who.int/news-room/fact-sheets/detail/ambient-(outdoor)-air-quality-and-health.
2 Li X , Jin L , Kan H . Air pollution: A global problem needs local fixes[J]. Nature, 2019, 570 (7762): 437- 439.
doi: 10.1038/d41586-019-01960-7
3 Orellano P , Reynoso J , Quaranta N , et al. Short-term exposure to particulate matter (PM10 and PM2.5), nitrogen dioxide (NO2), and ozone (O3) and all-cause and cause-specific mortality: Systematic review and meta-analysis[J]. Environ Int, 2020, 142, 105876.
doi: 10.1016/j.envint.2020.105876
4 Lu JP , Lu Y , Wang XC , et al. Prevalence, awareness, treatment, and control of hypertension in China: data from 1.7 million adults in a population-based screening study (China PEACE Million Persons Project)[J]. Lancet, 2017, 390 (10112): 2549- 2558.
doi: 10.1016/S0140-6736(17)32478-9
5 Zhang L , Wang F , Wang L , et al. Prevalence of chronic kidney disease in China: A cross-sectional survey[J]. Lancet, 2012, 379 (9818): 815- 822.
doi: 10.1016/S0140-6736(12)60033-6
6 Wu MY , Lo WC , Chao CT , et al. Association between air pollutants and development of chronic kidney disease: A systematic review and meta-analysis[J]. Sci Total Environ, 2020, 706, 135522.
doi: 10.1016/j.scitotenv.2019.135522
7 Bowe B , Xie Y , Li T , et al. Associations of ambient coarse particulate matter, nitrogen dioxide, and carbon monoxide with the risk of kidney disease: A cohort study[J]. Lancet Planet Health, 2017, 1 (7): e267- e276.
doi: 10.1016/S2542-5196(17)30117-1
8 梁琛瑜, 王万州, 马麟, 等. 大气NO2长期暴露与中国成人慢性肾脏病的关联: 基于中国慢性肾脏病流行病学调查[J]. 环境与职业医学, 2021, 38 (6): 566- 572.
9 Cockwell P , Fisher LA . The global burden of chronic kidney disease[J]. Lancet, 2020, 395 (10225): 662- 664.
doi: 10.1016/S0140-6736(19)32977-0
10 Murad MH , Larrea-Mantilla L , Haddad A , et al. Antihyperten-sive agents in older adults: A systematic review and meta-analysis of randomized clinical trials[J]. J Clin Endocrinol Metab, 2019, 104 (5): 1575- 1584.
doi: 10.1210/jc.2019-00197
11 Liu B , Wang Q , Wang Y , et al. Utilization of antihypertensive drugs among chronic kidney disease patients: Results from the Chinese cohort study of chronic kidney disease (C-STRIDE)[J]. J Clin Hypertens (Greenwich), 2020, 22 (1): 57- 64.
doi: 10.1111/jch.13761
12 Ptinopoulou AG , Pikilidou MI , Lasaridis AN . The effect of antihypertensive drugs on chronic kidney disease: A comprehensive review[J]. Hypertens Res, 2013, 36 (2): 91- 101.
doi: 10.1038/hr.2012.157
13 Sarnak MJ , Levey AS , Schoolwerth AC , et al. Kidney disease as a risk factor for development of cardiovascular disease: A statement from the American Heart Association Councils on Kidney in Cardiovascular Disease, High Blood Pressure Research, Clinical Cardiology, and Epidemiology and Prevention[J]. Circulation, 2003, 108 (17): 2154- 2169.
doi: 10.1161/01.CIR.0000095676.90936.80
14 Brook RD , Franklin B , Cascio W , et al. Air pollution and cardiovascular disease: A statement for healthcare professionals from the Expert Panel on Population and Prevention Science of the American Heart Association[J]. Circulation, 2004, 109 (21): 2655- 2671.
doi: 10.1161/01.CIR.0000128587.30041.C8
15 Li G , Huang J , Wang J , et al. Long-term exposure to ambient PM(2.5) and increased risk of CKD prevalence in China[J]. J Am Soc Nephrol, 2021, 32 (2): 448- 458.
doi: 10.1681/ASN.2020040517
16 Geddes JA , Martin RV , Boys BL , et al. Long-term trends worldwide in ambient NO2 concentrations inferred from satellite observations[J]. Environ Health Perspect, 2016, 124 (3): 281- 289.
doi: 10.1289/ehp.1409567
17 Geddes JA , Martin RV , Boys BL , et al. Global 3-year running mean ground-level nitrogen dioxide (NO2) grids from GOME, SCIAMACHY and GOME-2[M]. Palisades, New York: NASA Socioeconomic Data and Applications Center (SEDAC), 2017.
18 Guo J , Xia F , Zhang Y , et al. Impact of diurnal variability and meteorological factors on the PM2.5-AOD relationship: Implications for PM2.5 remote sensing[J]. Environ Pollut, 2017, 221, 94- 104.
doi: 10.1016/j.envpol.2016.11.043
19 Lv B , Hu Y , Chang HH , et al. Daily estimation of ground-level PM2.5 concentrations at 4km resolution over Beijing-Tianjin-Hebei by fusing MODIS AOD and ground observations[J]. Sci Total Environ, 2017, 580, 235- 244.
doi: 10.1016/j.scitotenv.2016.12.049
20 Lee HJ , Liu Y , Coull BA , et al. A novel calibration approach of MODIS AOD data to predict PM2.5 concentrations[J]. Atmos Chem Phys, 2011, 11 (15): 7991- 8002.
doi: 10.5194/acp-11-7991-2011
21 Levin A , Stevens PE , Bilous RW , et al. Kidney Disease: Improving Global Outcomes (KDIGO) CKD Work Group. KDIGO 2012 clinical practice guideline for the evaluation and management of chronic kidney disease[J]. Kidney Int Suppl, 2013, 3 (1): 1- 105.
doi: 10.1038/kisup.2012.73
22 He D , Wu S , Zhao H , et al. Association between particulate matter 2.5 and diabetes mellitus: A meta-analysis of cohort studies[J]. J Diabetes Investig, 2017, 8 (5): 687- 696.
doi: 10.1111/jdi.12631
23 Yang BY , Qian Z , Li S , et al. Ambient air pollution in relation to diabetes and glucose-homoeostasis markers in China: A cross-sectional study with findings from the 33 Communities Chinese Health Study[J]. Lancet Planet Health, 2018, 2 (2): e64- e73.
doi: 10.1016/S2542-5196(18)30001-9
24 Yang BY , Qian Z , Howard SW , et al. Global association between ambient air pollution and blood pressure: A systematic review and meta-analysis[J]. Environ Pollut, 2018, 235, 576- 588.
doi: 10.1016/j.envpol.2018.01.001
25 Cai Y , Zhang B , Ke W , et al. Associations of short-term and long-term exposure to ambient air pollutants with hypertension: A systematic review and meta-analysis[J]. Hypertension, 2016, 68 (1): 62- 70.
doi: 10.1161/HYPERTENSIONAHA.116.07218
26 Dadvand P , Nieuwenhuijsen MJ , Agustí À , et al. Air pollution and biomarkers of systemic inflammation and tissue repair in COPD patients[J]. Eur Respir J, 2014, 44 (3): 603- 613.
doi: 10.1183/09031936.00168813
27 Kim HJ , Min JY , Min KB , et al. CDH13 gene-by-PM10 interaction effect on lung function decline in Korean men[J]. Chemosphere, 2017, 168, 583- 589.
doi: 10.1016/j.chemosphere.2016.11.022
28 Mills NL , Donaldson K , Hadoke PW , et al. Adverse cardiovascular effects of air pollution[J]. Nat Clin Pract Cardiovasc Med, 2009, 6 (1): 36- 44.
doi: 10.1038/ncpcardio1399
29 Pope CA 3rd , Bhatnagar A , Mccracken JP , et al. Exposure to fine particulate air pollution is associated with endothelial injury and systemic inflammation[J]. Circ Res, 2016, 119 (11): 1204- 1214.
doi: 10.1161/CIRCRESAHA.116.309279
30 Silverstein DM . Inflammation in chronic kidney disease: Role in the progression of renal and cardiovascular disease[J]. Pediatr Nephrol, 2009, 24 (8): 1445- 1452.
doi: 10.1007/s00467-008-1046-0
31 Gupta J , Mitra N , Kanetsky PA , et al. Association between albuminuria, kidney function, and inflammatory biomarker profile in CKD in CRIC[J]. Clin J Am Soc Nephrol, 2012, 7 (12): 1938- 1946.
doi: 10.2215/CJN.03500412
32 纪培颖, 许雁集, 沈凌. 不同降压药对慢性肾脏病患者肾脏的保护作用[J]. 当代医学, 2019, 25 (13): 143- 145.
doi: 10.3969/j.issn.1009-4393.2019.13.057
33 Abe M , Okada K , Maruyama T , et al. Comparison of the antiproteinuric effects of the calcium channel blockers benidipine and amlodipine administered in combination with angiotensin receptor blockers to hypertensive patients with stage 3-5 chronic kidney disease[J]. Hypertens Res, 2009, 32 (4): 270- 275.
doi: 10.1038/hr.2009.11
34 环境保护部, 国家质量监督检验检疫总局. GB 3095—2012环境空气质量标准[S]. 北京: 中国环境科学出版社, 2012.
35 World Health Organization . Air quality guidelines: global update 2005: Particulate matter, ozone, nitrogen dioxide, and sulfur dioxide[M]. Geneva: WHO, 2006.
36 Mehta AJ , Zanobetti A , Bind MA , et al. Long-term exposure to ambient fine particulate matter and renal function in older men: The veterans administration normative aging study[J]. Environ Health Perspect, 2016, 124 (9): 1353- 1360.
doi: 10.1289/ehp.1510269
37 Szyszkowicz M , Rowe BH , Brook RD . Even low levels of ambient air pollutants are associated with increased emergency department visits for hypertension[J]. Can J Cardiol, 2012, 28 (3): 360- 366.
doi: 10.1016/j.cjca.2011.06.011
38 Nam YS , Cho KH , Kang HC , et al. Greater continuity of care reduces hospital admissions in patients with hypertension: An analysis of nationwide health insurance data in Korea, 2011-2013[J]. Health Policy, 2016, 120 (6): 604- 611.
doi: 10.1016/j.healthpol.2016.04.012
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