Introduction
Hypertension is the most important risk factor of cardiovascular disease (CVD).[1] [2] [3] [4] [5–7] [5] [7]
Methods
Ethical approval
The study was approved by the ethics committee of Beijing An Zhen Hospital, Capital Medical University. All participants signed to indicate their informed consent.
Study population
This cohort study initially enrolled 4151 participants in Beijing from the Chinese Multi-provincial Cohort Study (CMCS), a nationwide, multicenter, prospective cohort study on CVD which has been reported previously.[8,9] Figure 1 ].
Figure 1: Flowchart of participant selection from the Chinese Multi-provincial Cohort Study (CMCS), a nationwide, multicenter, prospective cohort study on CVD. CVD: Cardiovascular disease.
Risk factor measurement
Demographic information, smoking status, and personal medical history were collected from each participant using standardized questionnaires in all surveys. Height, weight, waist circumference, and BP levels were measured during physical examinations. The mean value of two consecutive BP readings was used. Body mass index (BMI) was calculated as weight in kilograms divided by square of the height in meters. Waist circumference was measured at a level midway between the lower rib margin and the iliac crest while participants were semi-clothed. Smoking was defined as at least one cigarette per day. Diabetes was defined as fasting blood glucose (FBG) at least 7.0 mmol/L or a condition of previously diagnosed diabetes. Fasting blood samples were collected for laboratory measurements. Total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), triglycerides (TG), and FBG were measured on the day of survey.
Cumulative BP
Cumulative BP was calculated by summing the product of the mean BP for each pair of consecutive examinations and the time interval between these two consecutive examinations in years; the formula can be expressed as: Cumulative BP = [(BP1 +BP2 )/2 × time1–2 +(BP2 +BP3 )/2×time2–3 ], where BP1 , BP2 , and BP3 were BP measurements at years 0, 10, and 15; time1–2 and time2–3 were the time intervals from year 0 to 10, and from year 10 to 15, respectively. For participants who did not return for year 10, cumulative BP was calculated as (BP1 +BP3 )/2×time1–3 .
Case ascertainment
CVD events comprised of fatal and nonfatal acute coronary and stroke events. Acute coronary heart disease events included acute myocardial infarction, sudden death, and other coronary deaths. Acute stroke events included subarachnoid hemorrhage, intracerebral hemorrhage, and cerebral infarction. Diagnostic criteria were ascertained according to the World Health Organization's Monitoring of Trends and Determinants in Cardiovascular Disease protocol. A total of 207 incidents of CVD events occurred during the follow-up period from 2007 to 2018, with a mean follow-up of 10.2 years (SD 1.9 years).
Statistical analysis
Characteristics for participants were demonstrated as means ± SD if normally distributed or expressed as median (interquartile ranges) if skewed distributed. Categorical variables were expressed as frequencies and percentages (%). Levels and proportions of BP in 1992, 2002, and 2007 were compared by quartiles of cumulative BP. Cutoff points were 1818.2, 1970.8 and 2152.8 mmHg·year for the quartiles of cumulative SBP, and 1156.8, 1239.9 and 1334.9 mmHg·year for the quartiles of cumulative diastolic blood pressure (DBP). The cumulative incidence of CVD by quartiles of cumulative BP was calculated using the Kaplan–Meier method and compared with a log-rank test. The multivariate Cox proportional hazards regression was used to obtain hazard ratios (HRs) of CVD incidence associated with quartiles of 15-year cumulative SBP and cumulative DBP. In a first step, we adjusted for the classical risk factors, including age, sex, smoking status, diabetes, levels of HDL-C and LDL-C, and the use of antihypertensive and lipid-lowering drugs in 2007. Subsequently, the models were further adjusted for SBP or DBP levels in 2007. The restricted cubic spline was used to further display the relationship between risk (HRs) for CVD incidence and cumulative BP. Meanwhile, the risk of CVD associated with BP in 2007 and 15-year cumulative BP levels were evaluated separately after adjusting for the classical risk factors mentioned above. The discrimination values of cumulative BP and BP in 2007 were assessed using C-statistic. To explore the effect of cumulative BP independent of BP measurements in 2007, we performed 2 × 2 combined group analyses. First, 15-year cumulative BP levels from 1992 to 2007 and BP levels in 2007 were categorized by median levels, with 1970.8 mmHg·year for cumulative SBP, 1239.9 mmHg·year for cumulative DBP, 134.7 mmHg for 2007 SBP, and 81.7 mmHg for 2007 DBP. Subsequently, four combined groups were generated between cumulative BP levels and 2007 BP levels (ie, low cumulative SBP and low SBP, low cumulative SBP and high SBP, high cumulative SBP and low SBP, and high cumulative SBP and high SBP). Combinations of cumulative DBP levels with 2007 DBP levels were generated similarly. HRs for the long-term risk of CVD and 95% confidence intervals (CIs) were calculated for combinations of cumulative SBP with 2007 SBP in SBP model and for cumulative DBP with 2007 DBP in DBP model. The groups with low levels of both cumulative BP and baseline BP were used as the reference. Age, sex, smoking status, diabetes, levels of HDL-C and LDL-C, antihypertensive medications, and lipid-lowering drug use were adjusted in both the SBP model and DBP model.
Analyses were performed using STATA version 14.2 (Stata Corp LP, College Station, TX, USA). A two-sided P value of <0.05 was considered as statistical significance. For variables with missing data, we imputed the missing values using the sequential regression multiple imputation method implemented by IVEware software version 0.2 (Survey Research Center, University of Michigan, Ann Arbor, MI, USA). The rate of missing variables ranged from 0.05% to 3.56%. Sensitivity analyses were conducted after excluding data with missing values.
Results
Characteristics of study participants
The mean age was 46.4 ± 8.0 years in 1992 and 62.1 ± 7.9 years in 2007 among the 2429 participants included in the analyses, of whom 42.9% were men. The levels of TC, LDL-C, TG, SBP and DBP, the prevalence of diabetes, and the use of antihypertensive and lipid-lowering drugs increased, and the level of HDL-C maintained stability during the 15 years from 1992 to 2007. The levels of BMI and waist circumference increased, but the proportion of smoking decreased from 1992 to 2002 and maintained stability through 2002 to 2007 [Table 1 ]. Participants with higher levels of cumulative SBP were older and more likely to be male [Supplementary Table 1, https://links.lww.com/CM9/A463 https://links.lww.com/CM9/A463 https://links.lww.com/CM9/A463
Table 1 -
Characteristics of study participants in 1992, 2002, and 2007.
1992
2002
2007
Parameters
(n = 2429)
(n = 2043)
(n = 2429)
Age (year)
46.4 ± 8.0
57.1 ± 7.9
62.1 ± 7.9
Male
1042 (42.9)
843 (41.3)
1042 (42.9)
BMI (kg/m2 )
23.9 ± 3.2
25.4 ± 3.3
25.1 ± 3.4
Waist circumference (cm)
79.4 ± 9.2
84.4 ± 8.9
84.8 ± 9.7
FBG (mmol/L)
5.3 ± 0.9
5.0 ± 1.3
5.9 ± 1.4
TC (mmol/L)
4.7 ± 0.9
5.4 ± 1.0
5.4 ± 1.0
LDL-C (mmol/L)∗
2.7 ± 0.8
3.3 ± 0.9
3.4 ± 0.9
HDL-C (mmol/L)
1.4 ± 0.4
1.4 ± 0.3
1.3 ± 0.3
TG (mmol/L)
1.0 (0.7–1.4)
1.3 (0.9–1.9)
1.5 (1.1–2.1)
SBP (mmHg)
120.6 ± 17.3
130.8 ± 19.0
136.1 ± 18.0
DBP (mmHg)
77.4 ± 10.8
81.9 ± 10.3
82.4 ± 9.9
Smoking
404 (16.6)
241 (11.8)
283 (11.7)
Diabetes
101 (4.2)
218 (10.7)
424 (17.5)
Antihypertensive drug use
127 (5.2)
457 (22.4)
829 (34.1)
Lipid-lowering drug use
46 (1.9)
138 (6.8)
216 (8.9)
Data are presented as n (%) or mean ± standard deviation or median (interquantile range).
∗ LDL-C in 1992 was calculated using the Friedewald formula calculation method from 2394 participants with TG < 4.5 mmol/L.Values are presented as the mean ± SD, median (interquartile range), or n (%). DBP: Diastolic blood pressure; FBG: Fasting blood glucose; HDL-C: High-density lipoprotein cholesterol; LDL-C: Low-density lipoprotein cholesterol; SBP: Systolic blood pressure; TC: Total cholesterol; TG: Triglycerides.
Cumulative BP and changes in BP levels
Individuals with higher levels of cumulative BP also had higher levels of SBP and DBP in each examination during the 15 years from 1992 to 2007. Mean levels of SBP increased steadily with time in the first to third quartiles of cumulative SBP, whereas mean SBP level peaked at a 5-year early in the fourth quartile. Changes in DBP levels exhibited a pattern similar to SBP over time, except that the increase in DBP levels in the first to third quartiles was flatter compared with the slope of SBP [Figure 2 ]. Consistent with changes in mean BP level, the proportion of SBP ≥140 mmHg or DBP ≥90 mmHg also increased over the 15 years from 1992 to 2007 in the first to third quartiles of cumulative BP, while the proportion peaked in 2002 and then decreased in 2007 in the fourth quartile [Supplementary Figure 1, https://links.lww.com/CM9/A463
Figure 2: Blood pressure levels in 1992, 2002, and 2007 by quartiles of cumulative blood pressure during 1992–2007. (A) SBP; (B) DBP. DBP: Diastolic blood pressure; SBP: Systolic blood pressure.
Cumulative BP and future CVD risk
During the follow-up period, CVD incidence rates were 357.4, 505.0, 1054.4, and 1819.6 per 100,000 person-years for participants with the first to fourth quartiles of cumulative SBP, respectively, and the counterpart rates were 354.7, 693.4, 1102.3 and 1556.7 per 100,000 person-years for the first to fourth quartiles of cumulative DBP, respectively. The Kaplan-Meier curves showed that the participants with higher levels of cumulative SBP or cumulative DBP exhibited significantly higher incidence risk of CVD during follow-up (log-rank P < 0.001) [Figure 3 ].
Figure 3: The Kaplan-Meier curves for CVD incidence in participants with quartiles of cumulative blood pressure during 1992–2007. (A) SBP; (B) DBP. CVD: Cardiovascular disease; DBP: Diastolic blood pressure; SBP: Systolic blood pressure.
After adjusting for classical risk factors with the Cox proportional hazards regression models, the HRs (95% CI) of the second to fourth quartiles of cumulative BP for predicting CVD were 1.17 (0.67–2.04), 2.10 (1.27–3.48), and 3.27 (1.97–5.43) for cumulative SBP, and 1.61 (0.96–2.71), 2.36 (1.43–3.87), and 2.78 (1.69–4.60) for cumulative DBP, compared with the first quartile [Table 2 ]. After further adjusting for SBP or DBP levels in 2007, the associations were attenuated but were still of statistical significance or borderline statistical significance in the third and fourth quartiles of cumulative SBP and cumulative DBP. The results were similar in sensitivity analysis in participants with complete data (n = 2326) [Supplementary Table 3, https://links.lww.com/CM9/A463 https://links.lww.com/CM9/A463
Table 2 -
Hazard ratios and 95% confidence intervals for incident CVD by quartiles of 15-year cumulative blood pressure.
Cumulative SBP
Cumulative DBP
Classical risk factors∗
Classical risk factorsSBP
Classical risk factors∗
Classical risk factors∗ + DBP
Items
Hazard ratios (95% CI)
P
Hazard ratios (95% CI)
P
Hazard ratios (95% CI)
P
Hazard ratios (95% CI)
P
Quartile 1
Reference
Reference
Reference
Reference
Quartile 2
1.17 (0.67–2.04)
0.577
1.03 (0.59–1.81)
0.916
1.61 (0.96–2.71)
0.073
1.46 (0.86–2.48)
0.159
Quartile 3
2.10 (1.27–3.48)
0.004
1.69 (0.99–2.87)
0.054
2.36 (1.43–3.87)
0.001
1.99 (1.18–3.35)
0.010
Quartile 4
3.27 (1.97–5.43)
<0.001
2.20 (1.21–3.98)
0.009
2.78 (1.69–4.60)
<0.001
2.08 (1.17–3.71)
0.013
∗ Classical risk factors include age, sex, smoking status, diabetes, levels of HDL-C and LDL-C, and the use of antihypertensive and lipid-lowering drugs.CVD: Cardiovascular disease; DBP: Diastolic blood pressure; HDL-C: High-density lipoprotein cholesterol; LDL-C: Low-density lipoprotein cholesterol; SBP: Systolic blood pressure.
After adjusting for the traditional risk factors, the HRs for CVD incidence associated with per SD increase and the third to fourth quartiles of cumulative SBP and DBP were higher than those associated with 2007 BP levels, respectively, although the 95% CIs were overlapping [Supplementary Table 4, https://links.lww.com/CM9/A463 P = 0.129). The results for DBP were similar, with a C-statistic of 0.72 (0.68–0.75) for 2007 DBP vs. 0.73 (0.69–0.76) for cumulative DBP, P = 0.312.
Moreover, combined group analyses were performed to analyze whether the effect of 15-year cumulative exposure of BP was independent of BP measurements at one examination [Table 3 ]. Results from both the SBP model and the DBP model showed that after adjustment of other covariates, high cumulative BP levels at the median or above were significantly associated with increased risk of CVD, irrespective of whether the level of BP measurement in 2007 was high or not. If BP levels in 2007 were high but cumulative BP levels from 1992 to 2007 were low, the association with CVD risk was only significant for high DBP, but not high SBP.
Table 3 -
Hazard ratios and 95% confidence intervals for the risk of CVD incidence associated with combined groups of cumulative BP levels during 1992–2007 and BP levels in 2007.
Variables
Hazard Ratios (95%CI)
P
∗ SBP model
Low cumulative SBP and low SBP
Reference
Low cumulative SBP and high SBP
1.21 (0.66–2.22)
0.535
High cumulative SBP and low SBP
2.01 (1.21–3.36)
0.007
High cumulative SBP and high SBP
2.63 (1.77–3.90)
<0.001
∗ DBP model
Low cumulative DBP and low DBP
Reference
Low cumulative DBP and high DBP
1.78 (1.06–2.98)
0.028
High cumulative DBP and low DBP
2.02 (1.27–3.21)
0.003
High cumulative DBP and high DBP
2.38 (1.62–3.48)
<0.001
∗ Combined groups of cumulative SBP levels during 1992–2007 and SBP levels in 2007.BP: Blood pressure; CVD: Cardiovascular disease; DBP: Diastolic blood pressure; HDL-C: High-density lipoprotein cholesterol; LDL-C: Low-density lipoprotein cholesterol; SBP: Systolic blood pressure. The 15-year cumulative BP levels and BP levels in 2007 were categorized by median. All the models were adjusted for age, sex, smoking status, diabetes, levels of HDL-C and LDL-C, antihypertensive medications, and lipid-lowering drugs.
Discussion
In this long-term cohort study, we demonstrated that elevated cumulative BP level was significantly associated with increased risk of CVD, and that this association was independent of BP measurements at one examination. If the 15-year cumulative BP level was higher than the median, that is, 1970.8/1239.9 mmHg·year for cumulative SBP/DBP, which was equivalent to maintaining a level of SBP/DBP higher than 131/83 mmHg in 15 years, the CVD risk would significantly increase in the future.
The effect of BP load over a long time on CVD risk has been the subject of intensive interest globally. In the original and the offspring Framingham Heart Study, antecedent BP, defined as the average of BP measurements preceding the baseline, was an important determinant of future risk of CVD events above and beyond the baseline BP.[10–12] [13–16] [5,7]
Although several previous studies have reported a better predictive value of cumulative BP compared to a single BP measurement,[5–7] [9] [17] [18]
Our study has several implications for CVD prevention. First, our findings suggest that it is ideal to maintain the levels of SBP and DBP below 130 mmHg and 80 mmHg, respectively, as long as possible to maintain lifelong cardiovascular health. Although it has been demonstrated by randomized clinical trials that antihypertensive treatment significantly lower risk of CVD,[19,20] [21] [22] [23] [24,25] [24,25] [26,27]
The strengths of this study include its long-term follow-up, the standardized procedures used for data collection, and adjudication of suspected CVD using detailed evaluation criteria. Since participants have their BP measured at multiple time points over 15 years, we can analyze the risk of incident CVD associated with both the BP levels and the duration. However, some limitations should also be mentioned. First, for the estimates of cumulative BP, we relied on three measurements over 15 years. The estimation may not have captured more frequent fluctuations in BP levels. Moreover, although we have adjusted for all classical CVD risk factors in the multivariate analysis, we cannot exclude the impact of some unaccounted-for and residual confounding factors.
In conclusion, our study demonstrated that elevated cumulative SBP or DBP was independently associated with increased risk of CVD in the Chinese population. Among participants with 15-year cumulative BP levels higher than the median, that is, 1970.8/1239.9 mmHg·year for cumulative SBP/DBP, which was equivalent to maintaining SBP/DBP level higher than 131/83 mmHg in 15 years, the CVD risk would increase significantly irrespective of whether or not the BP measurements at one examination was high. Our findings emphasize the importance of cumulative BP level in identifying individuals with high risk of CVD in the future.
Funding
This work was supported by the National Key Research and Development Program of China (No. 2016YFC0900902); the Capital's Funds for Health Improvement and Research (No. 020-1-1051; and the Beijing Nova Programme Interdisciplinary Cooperation Project (No. Z191100001119017)).
Conflicts of interest
None.
References
1. GBD 2017 Risk Factor Collaborators. Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990-2017: A systematic analysis for the Global Burden of Disease Study 2017.
Lancet 2018; 392:1923–1994. doi: 10.1016/S0140-6736(18)32225-6.
2. Zhou M, Wang H, Zeng X, Yin P, Zhu J, Chen W, et al. Mortality, morbidity, and risk factors in China and its provinces, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017.
Lancet 2019; 394:1145–1158. doi: 10.1016/S0140-6736(19)30427-1.
3. Lewington S, Clarke R, Qizilbash N, Peto R, Collins R. Prospective Studies Collaboration. Age-specific relevance of usual blood pressure to vascular mortality: A meta-analysis of individual data for one million adults in 61 prospective studies.
Lancet 2002; 360:1903–1913. doi: 10.1016/s0140-6736(02)11911-8.
4. Ueda P, Gulayin P, Danaei G. Long-term moderately elevated LDL-cholesterol and blood pressure and risk of coronary heart disease.
PLoS One 2018; 13:e0200017doi: 10.1371/journal.pone.0200017.
5. Wang YX, Song L, Xing AJ, Gao M, Zhao HY, Li CH, et al. Predictive value of cumulative blood pressure for all-cause mortality and cardiovascular events.
Sci Rep 2017; 7:41969doi: 10.1038/srep41969.
6. Pool LR, Ning H, Wilkins J, Lloyd-Jones DM, Allen NB. Use of long-term cumulative blood pressure in cardiovascular risk prediction models.
JAMA Cardiol 2018; 3:1096–1100. doi: 10.1001/jamacardio.2018.2763.
7. Nwabuo CC, Appiah D, Moreira HT, Vasconcellos HD, Yano Y, Reis JP, et al. Long-term cumulative blood pressure in young adults and incident heart failure, coronary heart disease, stroke, and cardiovascular disease: The CARDIA study.
Eur J Prev Cardiol 2020; 2047487320915342 [ahead of print]. doi: 10.1177/2047487320915342.
8. Liu J, Hong Y, D’Agostino RB Sr, Wu Z, Wang W, Sun J, et al. Predictive value for the Chinese population of the Framingham CHD risk assessment tool compared with the Chinese multi-provincial cohort study.
JAMA 2004; 291:2591–2599. doi: 10.1001/jama.291.21.2591.
9. Qi Y, Han X, Zhao D, Wang W, Wang M, Sun J, et al. Long-term cardiovascular risk associated with stage 1 hypertension defined by the 2017 ACC/AHA hypertension guideline.
J Am Coll Cardiol 2018; 72:1201–1210. doi: 10.1016/j.jacc.2018.06.056.
10. Vasan RS, Massaro JM, Wilson PW, Seshadri S, Wolf PA, Levy D, et al. Antecedent blood pressure and risk of cardiovascular disease: The Framingham Heart Study.
Circulation 2002; 105:48–53. doi: 10.1161/hc0102.101774.
11. Lee DS, Massaro JM, Wang TJ, Kannel WB, Benjamin EJ, Kenchaiah S, et al. Antecedent blood pressure, body mass index, and the risk of incident heart failure in later life.
Hypertension 2007; 50:869–876. doi: 10.1161/HYPERTENSIONAHA.107.095380.
12. Bonifonte A, Ayer T, Veledar E, Clark A, Wilson PW. Antecedent blood pressure as a predictor of cardiovascular disease.
J Am Soc Hypertens 2015; 9:690-696 e691doi: 10.1016/j.jash.2015.06.013.
13. Li W, Jin C, Vaidya A, Wu Y, Rexrode K, Zheng X, et al. Blood pressure trajectories and the risk of intracerebral hemorrhage and cerebral infarction: a prospective study.
Hypertension 2017; 70:508–514. doi: 10.1161/HYPERTENSIONAHA.117.09479.
14. Smitson CC, Scherzer R, Shlipak MG, Psaty BM, Newman AB, Sarnak MJ, et al. Association of blood pressure trajectory with mortality, incident cardiovascular disease, and heart failure in the cardiovascular health study.
Am J Hypertens 2017; 30:587–593. doi: 10.1093/ajh/hpx028.
15. Petruski-Ivleva N, Viera AJ, Shimbo D, Muntner P, Avery CL, Schneider AL, et al. Longitudinal patterns of change in systolic blood pressure and incidence of cardiovascular disease: the atherosclerosis risk in communities study.
Hypertension 2016; 67:1150–1156. doi: 10.1161/HYPERTENSIONAHA.115.06769.
16. Lee CL, Wang JS. Systolic blood pressure trajectory and cardiovascular outcomes: An analysis using data in the systolic blood pressure intervention trial.
Int J Clin Pract 2020; 74:e13450doi: 10.1111/ijcp.13450.
17. Zhang Y, Vittinghoff E, Pletcher MJ, Allen NB, Zeki Al Hazzouri A, Yaffe K, et al. Associations of blood pressure and cholesterol levels during young adulthood with later cardiovascular events.
J Am Coll Cardiol 2019; 74:330–341. doi: 10.1016/j.jacc.2019.03.529.
18. Han M, Chen Q, Liu L, Li Q, Ren Y, Zhao Y, et al. Stage 1 hypertension by the 2017 American College of Cardiology/American Heart Association hypertension guidelines and risk of cardiovascular disease events: Systematic review, meta-analysis, and estimation of population etiologic fraction of prospective cohort studies.
J Hypertens 2020; 38:573–578. doi: 10.1097/HJH.0000000000002321.
19. Liu L, Zhang Y, Liu G, Li W, Zhang X, Zanchetti A, et al. The Felodipine Event Reduction (FEVER) Study: a randomized long-term placebo-controlled trial in Chinese hypertensive patients.
J Hypertens 2005; 23:2157–2172. doi: 10.1097/01.hjh.0000194120.42722.ac.
20. Group SR, Wright JT Jr, Williamson JD, Whelton PK, Snyder JK, Sink KM, et al. A randomized trial of intensive versus standard blood-pressure control.
N Engl J Med 2015; 373:2103–2116. doi: 10.1056/NEJMoa1511939.
21. Liu K, Colangelo LA, Daviglus ML, Goff DC, Pletcher M, Schreiner PJ, et al. Can antihypertensive treatment restore the risk of cardiovascular disease to ideal levels? The Coronary Artery Risk Development in Young Adults (CARDIA) Study and the Multi-Ethnic Study of Atherosclerosis (MESA).
J Am Heart Assoc 2015; 4:e002275doi: 10.1161/JAHA.115.002275.
22. Whelton SP, McEvoy JW, Shaw L, Psaty BM, Lima JAC, Budoff M, et al. Association of normal systolic blood pressure level with cardiovascular disease in the absence of risk factors.
JAMA Cardiol 2020; 5:1011–1018. doi: 10.1001/jamacardio.2020.1731.
23. Wang Z, Chen Z, Zhang L, Wang X, Hao G, Zhang Z, et al. Status of hypertension in China: Results from the China hypertension survey, 2012-2015.
Circulation 2018; 137:2344–2356. doi: 10.1161/CIRCULATIONAHA.117.032380.
24. Whelton PK, Carey RM, Aronow WS, Casey DE Jr, Collins KJ, Dennison Himmelfarb C, et al. 2017 ACC/AHA/AAPA/ABC/ACPM/AGS/APhA/ASH/ASPC/NMA/PCNA guideline for the prevention, detection, evaluation, and management of high blood pressure in adults: Executive summary: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines.
Circulation 2018; 138:e426–e483. doi: 10.1161/CIR.0000000000000597.
25. Joint Committee for Guideline R. 2018 Chinese guidelines for prevention and treatment of hypertension–A report of the Revision Committee of Chinese Guidelines for Prevention and Treatment of Hypertension.
J Geriatr Cardiol 2019; 16:182–241. doi: 10.11909/j.issn.1671-5411.2019.03.014.
26. Gu D, Reynolds K, Wu X, Chen J, Duan X, Muntner P, et al. Prevalence, awareness, treatment, and control of hypertension in china.
Hypertension 2002; 40:920–927. doi: 10.1161/01.hyp.0000040263.94619.d5.
27. Sun N, Mu J, Li Y. Working Committee of Salt evaluation Blood Pressure Management, Chinese Medical Association Hypertension Professional Committee, Hypertension Group, Chinese Society of Cardiology. An expert recommendation on salt intake and blood pressure management in Chinese patients with hypertension: a statement of the Chinese Medical Association Hypertension Professional Committee.
J Clin Hypertens (Greenwich) 2019; 21:446–450. doi: 10.1111/jch.13501.
