The burden of hypertension is increasing rapidly worldwide due to the global aging, and the prevalence of hypertension in adults is predicted to increase by 60% to a total of 1.56 billion (1.54 billion-1.58 billion) in 2025 according to the diagnostic criteria (systolic blood pressure [SBP] ≥ 140 mmHg, or diastolic blood pressure [DBP] ≥ 90 mmHg),1,2 which is used in most countries. However, the American College of Cardiology (ACC) and American Heart Association (AHA) changed the blood pressure threshold value and recommended new goals of SBP/DBP < 130/80 mmHg in 2017 hypertension guideline.3 More adults will be diagnosed as hypertensive patients by the newest American guideline, especially in the elderly population.4 Studies have pointed out that blood pressure varied in the elderly with the increasing age, performed as SBP continuing to rise, DBP declining, and PP being widen finally.5
Pulse pressure (PP) is another index of blood pressure which is defined as the difference between SBP and DBP, representing the maximal and minimal pressures fluctuation during a cardiac cycle.6 The normal PP is about 40 mmHg, and more than 60 mmHg is clinically considered as wide PP. Wide PP is related to some chronic diseases such as chronic kidney disease,7 diabetes8 and stroke,9,10 as well as some neurological diseases like cognitive decline and dementia.11 Moreover, wide PP is an independent predictor of extensive cardiovascular disease.12–14 Taking an individual's SBP and DBP into consideration, wide PP patients can divide into three types of low SBP and low DBP (LSLD), high SBP and low DBP (HSLD), and high SBP and high DBP (HSHD).15 The antihypertensive treatment has focused on SBP only for a long time. However, PP can better reflect cardiovascular status in the elderly population due to the blood pressure characteristics of changing with increasing age.
Hypertension is always related to some unhealthy state or behaviors, such as overweight and obesity, a high-salt diet, smoking, excessive alcohol consumption, inadequate physical activity, sleep disorders.16–21 These factors cause physiological and psychological changes in the human body and lead to hypertension finally. But evidence that how these risk factors influence the individual's SBP or DBP was not consistent. And studies about the influencing factors about different types of wide PP were limited.
Therefore, we aimed to describe the distribution of blood pressure in the elderly Chinese population and found influencing factors of wide PP in this study.
METHODS Study design and participantsThe study participants were derived from the baseline population of Yiwu Elderly Cohort Study from 2019 to 2021. This cohort were conducted in Yiwu, Zhejiang province of China. The participants were chosen as following inclusion criteria: (1) age was and above 65 years and (2) living in the study area at least 5 years. Individuals were excluded if they were bed-ridden, had hearing disorders, serious physiological or psychological illnesses. From baseline population, a total of 5090 elderly residents responded to the questionnaire and among them, 5033 residents participated in the physical examination. For this cross-sectional study, 5033 individuals who both completed the physical examination and the questionnaire were included. Three persons who lacked information on blood pressure were excluded. Finally, 5030 eligible objects were included in further analysis in the study.
Measurement of wide PPFor the participants, left and right brachial artery of SBP and DBP were measured after sitting quietly for 5 min by a professional medical staff. The final SBP and DBP were calculated as mean of left and right arms. PP was calculated as SBP minus DBP. Taking the approximate median value PP = 65 mmHg as cut-off value, all the elderly were divided into the normal PP (PP < 65 mmHg) group and the wide PP group (PP ≥ 65 mmHg). And in the wide PP group, according to the approximate median cut-off values SBP = 140 mmHg and DBP = 75 mmHg, participants were divided into three wide PP groups: LSLD (SBP < 140 and DBP < 75 mmHg), HSLD (SBP ≥ 140 and DBP < 75 mmHg), and HSHD (SBP ≥ 140 and DBP ≥ 75 mmHg).
Measurement of potential influencing factorsFace-to-face interviewer-administered questionnaires were used to assess demographic factors (age, gender, body height, marital status, and educational level), health-related factors (number of chronic diseases and body mass index [BMI]), and lifestyle factors (smoking, alcohol drinking, tea drinking, and sleep quality).
BMI was calculated as weight (kilograms)/height 2(meters) and classified as underweight, normal weight, overweight and obesity according to the index <18.5, ≥18.5 and <24.0, ≥ 24.0 and <28.0, and ≥28.0. The number of chronic diseases was counted by self-reported history of chronic diseases, including hypertension, diabetes, stroke, coronary heart disease, osteoarthritis, chronic obstructive pulmonary disease and Parkinson's disease arthritis. It was categorized into three groups including no chronic disease, one kind of disease, and two or more kinds of diseases.
The smoking, alcohol drinking and tea drinking were categorized as current, former and never status. More than one cigarette per day for at least 3 months was defined as current smoker; Once smoked but gave up for 6 months was defined as former smoker. More than 100 g alcohol per week for at least 3 months was defined as current alcohol drinker; Once alcohol drank but gave up for 6 months was defined as former alcohol drinker. At least 2 times per week for more than 2 months was defined as current tea drinker; Once tea drank but gave up for 6 months was defined as former tea drinker. Pittsburgh Sleep Quality Index (PSQI) was used to evaluate the sleep status in last 1 month. The scale was divided into 7 components as sleep quality, time to fall asleep, time to sleep, sleep efficiency, sleep disorders, sleep drug use and daytime dysfunction, with each component being 0–3 points. The total score of the scale was 21. The sleep quality was classified as very good, fairly good, fairly bad and very bad according to PSQI in 0 to 5, 6–10, 11–15 and 16–21.22
Statistical analysisCharacteristics of participants were described using means ± standard deviation (SD) for continuous variables with normal distribution, median (interquartile range, IQR) for non-normally distributed variables, and frequency (proportion) for categorical variables. Differences between participants in the normal group and the wide PP group were tested using t-test and non-parametric Wilcoxon test for continuous variables and Chi-square tests for categorical variables. Differences between participants in the normal group and LSLD, HSLD, and HSHD groups were tested using analysis of variance (ANOVA) and Kruskal-Wallis H test for continuous variables, and Chi-square tests for categorical variables, and Dunnett's test and partitions of Chi-square method were used for post hoc tests. Taking the normal group as reference, multivariate logistic regression models were used to analyze the odds ratios (ORs) and 95% confidence intervals (95% CIs) of demographic factors, health-related factors and lifestyle factors in total, and different types of wide PP groups respectively. Considering the great difference about the four lifestyles of smoking, alcohol drinking, tea drinking, and sleep quality between males and females, subgroup analyses were performed to assess the associations of lifestyles with wide PP by gender. A value of p < .05 was considered statistically significant. All statistical analyses were performed in R software (version4.1.1).
RESULTSA total of 5030 participants ≥65 years old were included in this cross-sectional study finally, including 2460 males (48.9%). The IQR of age was from 67 to 76 years old, with the median value of 71 years. The average body height was 160 cm. According to BMI category, 56.5% participants were normal while 37.0% were overweight and obesity, and the median value (IQR) of BMI was 22.96 (21.03,25.02) kg/m2. 79.5% of the participants were married and 70.2% had a primary school education or below. The proportions of current smokers, current drinkers and current tea drinkers were not high, accounting for 13.7%, 27.5%, and 11.7%, respectively. 66.1% of the elderly had very good sleep while 4.4% had fairly bad sleep. 25.6% of participants reported they have not been diagnosed chronic diseases, 38.9% had one and 35.4% had more than two diseases. The basic characteristics of the participants were shown in Table 1.
TABLE 1 Basic characteristics of the participants
| Wide PP groupb | |||||||
| Overall (N = 5030) | Normal groupa (N = 2303) | Total (N = 2727) | LSLDc (N = 482) | HSLDd (N = 877) | HSHDe (N = 1368) | p-Valuef | |
| Median (IQR) | |||||||
|
Age (years) |
71.0 (67.0,76.0) |
69.0 (66.5,73.0) |
72.0 (68.0,78.0) |
72.0 (69.0,77.0) |
74.0 (69.0,80.0) |
72.0 (68.0,77.0) |
<.001 |
| Body height (cm) |
160.0 (154.0,166.0) |
161.0 (155.0,167.5) |
158.5 (153.0,165.0) |
158.0 (153.0,164.5) |
157.0 (152.0,163.0) |
159.0 (153.0,165.6) |
<.001 |
|
BMI (kg/m2) |
22.96 (21.03,25.02) |
22.94 (21.05,25.10) |
22.96 (20.98,24.94) |
22.49 (20.46,24.29) |
22.81 (20.66,24.80) |
23.34 (21.30,25.31) |
<.001 |
| Frequency (n, %) | |||||||
| Male | 2460 (48.9%) | 1276 (55.4%) | 1184 (43.4%) | 211 (43.8%) | 346 (39.5%) | 627 (45.8%) | <.001 |
| Married | 3998 (79.5%) | 1955 (84.9%) | 2043 (74.9%) | 372 (77.2%) | 637 (72.6%) | 1034 (75.6%) | <.001 |
| Education level | <.001 | ||||||
| Illiterate | 1406 (28.0%) | 501 (21.8%) | 905 (33.2%) | 142 (29.5%) | 327 (37.3%) | 436 (31.9%) | |
| Primary school | 2121 (42.2%) | 1033 (44.9%) | 1088 (39.9%) | 215 (44.6%) | 340 (38.8%) | 533 (39.0%) | |
| Middle school | 1228 (24.4%) | 622 (27.0%) | 606 (22.2%) | 93 (19.3%) | 168 (19.2%) | 345 (25.2%) | |
| High school or above | 248 (4.9%) | 137 (5.9%) | 111 (4.1%) | 30 (6.2%) | 32 (3.6%) | 49 (3.6%) | |
| Number of chronic diseases | <.001 | ||||||
| None | 1290 (25.6%) | 651 (28.3%) | 639 (23.4%) | 129 (26.8%) | 184 (21.0%) | 326 (23.8%) | |
| Single | 1956 (38.9%) | 851 (37.0%) | 1105 (40.5%) | 186 (38.6%) | 349 (39.8%) | 570 (41.7%) | |
| multiple | 1780 (35.4%) | 799 (34.7%) | 981 (36.0%) | 167 (34.6%) | 344 (39.2%) | 470 (34.4%) | |
| Smoking | <.001 | ||||||
| Current smoker | 687 (13.7%) | 403 (17.5%) | 284 (10.4%) | 56 (11.6%) | 90 (10.3%) | 138 (10.1%) | |
| Former smoker | 524 (10.4%) | 265 (11.5%) | 259 (9.5%) | 48 (10.0%) | 75 (8.6%) | 136 (9.9%) | |
| Never smoker | 3811 (75.8%) | 1633 (70.9%) | 2178 (79.9%) | 378 (78.4%) | 707 (80.6%) | 1093 (79.9%) | |
| Alcohol drinking | <.001 | ||||||
| Current alcohol drinker | 1385 (27.5%) | 644 (28.0%) | 741 (27.2%) | 124 (25.7%) | 192 (21.9%) | 425 (31.1%) | |
| Former alcohol drinker | 244 (4.9%) | 127 (5.5%) | 117 (4.3%) | 21 (4.4%) | 40 (4.6%) | 56 (4.1%) | |
| Never alcohol drinker | 3386 (67.3%) | 1525 (66.2%) | 1861 (68.2%) | 335 (69.5%) | 640 (73.0%) | 886 (64.8%) | |
| Tea drinking | .008 | ||||||
| Current tea drinker | 590 (11.7%) | 308 (13.4%) | 282 (10.3%) | 62 (12.9%) | 73 (8.3%) | 147 (10.7%) | |
| Former tea drinker | 119 (2.4%) | 52 (2.3%) | 67 (2.5%) | 11 (2.3%) | 21 (2.4%) | 35 (2.6%) | |
| Never tea drinker | 4278 (85.0%) | 1928 (83.7%) | 2350 (86.2%) | 405 (84.0%) | 772 (88.0%) | 1173 (85.7%) | |
| Sleep quality | .009 | ||||||
| Very good | 3326 (66.1%) | 1532 (66.5%) | 1794 (65.8%) | 322 (66.8%) | 564 (64.3%) | 908 (66.4%) | |
| Fairly good | 1006 (20.0%) | 458 (19.9%) | 548 (20.1%) | 98 (20.3%) | 203 (23.1%) | 247 (18.1%) | |
| Fairly bad | 219 (4.4%) | 77 (3.3%) | 142 (5.2%) | 22 (4.6%) | 47 (5.4%) | 73 (5.3%) | |
Normal group: PP < 65 mmHg.
Wide PP group: PP ≥ 65 mmHg.
LSLD: PP ≥ 65 & SBP ≤ 140 & DBP ≤ 75 mmHg.
HSLD: PP ≥ 65 & SBP ≥ 140 & DBP ≤ 75 mmHg.
HSHD: PP ≥ 65 & SBP ≥ 140 & DBP ≥ 75 mmHg.
p-Value* showed the statistical difference between normal group and LSLD, HSLD, HSHD groups.
Descriptive results showed that the median value (IQR) of SBP, DBP, PP in the elderly of Yiwu were 141(130, 154) mmHg, 75(68, 82) mmHg and 66(57, 77) mmHg. According to the grouping of the approximate median cut-off value of PP, 2303(45.8%) persons were in the normal group and 2727(54.2%) persons were in the wide PP group. Then according to the approximate median cut-off value of SBP = 140 mmHg and DBP = 75 mmHg, participants in the wide PP group were categorized as three types, including 482(17.7%) in LSLD, 877(32.1%) in HSLD, and 1368(50.2%) in HSHD. Compared to the normal group, the ages of participants in all three different types of wide PP were older, the body heights were smaller, and the proportions of the males, the married, and the non-chronic disease were lower. BMI were relatively smaller in LSLD and larger in HSHD. The results were presented in Table 1.
Figure 1 showed the samples, proportions, ORs (95% CIs) for demographic factors (age, gender, body height, marital status, educational level), health-related factors (number of chronic diseases, BMI) and lifestyle factors (smoking, alcohol drinking, tea drinking, sleep quality) between the normal group and the wide PP group. Taking the normal group as reference, the results showed that older age (OR = 2.48, 95% CI: 2.14-2.88), female (OR = 1.31, 95% CI: 1.07-1.60), the not married (OR = 1.26, 95% CI: 1.07-1.49), having single (OR = 1.36, 95% CI: 1.17-1.59) or multiple (OR = 1.28, 95% CI: 1.09-1.50) chronic diseases and current alcohol drinker (OR = 1.29, 95% CI: 1.11-1.50) were positively associated with wide PP, whereas lager body height (OR = .78, 95% CI: .62-.99), higher education level (OR = .60, 95% CI: .43-.82), current smoker (OR = .79, 95% CI: .64-.97) were negatively associated with wide PP in elderly. BMI, tea drinking and sleep quality were not statistically associated with wide PP.
Enlarge this image.FIGURE 1. Samples, proportions and ORs (95% CIs) for demographic factors, health-related factors and lifestyle factors between the normal group and the total wide PP group.
ORs (95%CIs) for these factors in LSLD, HSLD, HSHD groups were presented in Figure 2. Positive associations were found between age and all three groups, and the OR value was biggest in HSLD group. Positive associations were also found between female and LSLD, HSLD groups, widowed and others and HSHD group. Larger body height was negatively associated with HSLD group, and higher education level was negatively associated with HSLD, HSHD two groups. Compared to the normal BMI, the ORs (95%CIs) of overweight were .74(.57, .95) in LSLD group, .91(.74, 1.11) in HSLD group, and 1.27(1.08, 1.50) in HSHD group. In HSLD group, having single (OR = 1.46, 95% CI: 1.16-1.84) or multiple (OR = 1.54, 95% CI: 1.22-1.95) chronic diseases both showed positive associations. In HSHD group, only having single chronic disease (OR = 1.36, 95% CI: 1.13-1.64) showed positive association. Current smoker (OR = .66, 95% CI: .51-.85) was negatively associated while current alcohol drinker (OR = 1.48, 95% CI: 1.24-1.76) was negatively associated with HSHD group. Tea drinking and sleep quality were no statistical significance between all the groups.
Enlarge this image.FIGURE 2. ORs (95% CIs) for demographic factors, health-related factors and lifestyle factors between the normal group and LSLD, HSLD, HSHD groups (LSLD: PP ≥ 65 & SBP ≤ 140 & DBP ≤ 75 mmHg; HSLD: PP ≥ 65 & SBP ≥ 140 & DBP ≤ 75 mmHg; HSHD: PP ≥ 65 & SBP ≥ 140 & DBP ≥ 75 mmHg).
Subgroup analyses conducted by gender for lifestyle factors and all types of wide PP were presented in Table 2. Among male, current smoker still had a negative association while current alcohol drinker was positive in the wide PP group. Tea drinking and sleep quality had no statistical significance in wide PP group. Among female, smoking, alcohol drinking and tea drinking were not statistically significant with wide PP. Compared to having very good sleep, fairly bad sleep quality had a critical positive association with wide PP.
TABLE 2 Results of subgroup analyses for lifestyles and wide PP
| Male (n = 2460) | Female (n = 2570) | |||
| Lifestyle factors | Normal groupa(n = 1276) | Wide PP groupb(n = 1184) | Normal groupa(n = 1027) | Wide PP groupb(n = 1543) |
| OR (95%CI) | OR (95%CI) | OR (95%CI) | OR (95%CI) | |
| Smoking | ||||
| Never smoker | 1.00(ref.) | 1.00(ref.) | 1.00(ref.) | 1.00(ref.) |
| Former smoker | 1.00(ref.) | .92(.73,1.17) | 1.00(ref.) | .46(.02,12.53) |
| Current smoker | 1.00(ref.) | .77(.62,.95) | 1.00(ref.) | 1.30(.26,9.68) |
| Alcohol drinking | ||||
| Never drinker | 1.00(ref.) | 1.00(ref.) | 1.00(ref.) | 1.00(ref.) |
| Former drinker | 1.00(ref.) | 1.00(.70,1.42) | 1.00(ref.) | .67(.34,1.34) |
| Current drinker | 1.00(ref.) | 1.58(1.31,1.91) | 1.00(ref.) | .89(.70,1.14) |
| Tea drinking | ||||
| Never tea drinker | 1.00(ref.) | 1.00(ref.) | 1.00(ref.) | 1.00(ref.) |
| Former tea drinker | 1.00(ref.) | 1.30(.82,2.07) | 1.00(ref.) | .81(.28,2.40) |
| Current tea drinker | 1.00(ref.) | .88(.70,1.10) | 1.00(ref.) | 1.19(.76,1.91) |
| Sleep quality | ||||
| Very good | 1.00(ref.) | 1.00(ref.) | 1.00(ref.) | 1.00(ref.) |
| Fairly good | 1.00(ref.) | .83(.66,1.05) | 1.00(ref.) | .98(.80,1.20) |
| Fairly bad | 1.00(ref.) | 1.15(.65,2.04) | 1.00(ref.) | 1.40(.99,2.02) |
Normal group: PP < 65 mmHg.
Wide PP group: PP ≥ 65 mmHg.
DISCUSSIONThis study described the distribution of blood pressure, especially PP in the elderly population and examined the associations between demographic factors (age, gender, body height, marital status, educational level), health-related factors (BMI, number of chronic diseases), lifestyle factors (smoking, alcohol drinking, tea drinking, sleep quality) and wide PP, including different types of wide PP groups (LSLD, HSLD, HSHD). The findings revealed that the median value of SBP, DBP, PP in 5030 elderly participants were 141 mmHg, 75 and 66 mmHg. We also found that people in PP ⩾ 65 mmHg group accounted for more than half proportion in the elderly. Among the three different types of wide PP, the HSHD type accounted for the highest proportion of about 50%, and the LSLD type was the least, about 17.7%. Compared to the normal group, age, gender, marital status, education, BMI, number of chronic diseases, smoking, alcohol drinking, tea drinking and sleep quality had different effects on either all wide PP group or LSLD, HSLD, HSHD groups. And four lifestyle factors smoking, alcohol drinking, tea drinking and sleep quality also had different effects between male and female.
In this study, the median SBP of the elderly was 141 mmHg, which was higher than the diagnostic criteria for hypertension in China, while the DBP of 75 mmHg was in the normal range.23 And the median value PP = 66 mmHg was also higher than the critical value of normal individuals. This Isolated systolic hypertension was common in the elderly which mainly due to arterial aging.24 As age increasing, arterial continued to stiffen and ventricular ejection patterns changed, contributing to increasing blood pressure, mainly SBP and PP.25,26 However, according to the grouping of our study, we found that it was not HSLD group but HSHD group that accounted for about half of the elderly patients in wide PP participants. It indicated that the higher PP in the elderly was probably owing to the increasing of both SBP and DBP, which not only a physiological change, but also a pathological cause and had a relationship with hypertension.
When exploring the demographic factors of different types wide PP, the results showed that age had positive relationships with all types wide PP, and the OR value was the largest in HSLD group, which could be explained from the physiological mechanism of age-induced changes in cardiac ejection and arterial stiffness. The older the vessel is, the more severe the sclerosis, the more susceptible to HSLD type wide PP.27 Old women were more likely to have wide PP, which was consistent with evidence of previous studies. Studies noted that SBP continued to rise with age in both men and women, while DBP increased first and then declined at about 55 years old and it was at this age that men's and women's SBP began to differ, with women still increasing dramatically but men not,26,28 so women's PP usually would be wider than men. Body height might influence the transmission of reflected waves, thus affecting the PP finally, larger body height was less prone to have HSLD type wide PP. People not in marriage were more likely to develop HSHD type wide PP. We suspected that it might cause by lack of care and supervision from a spouse. These old people were more likely to have bad lifestyle habits, ignore some chronic diseases, be lack of treatment or do not take medication regularly for hypertension. Education played protective roles in the HSLD and HSHD groups, which was consistent with the conclusion of previous studies,29 because both two groups were hypertensive patients and a certain level of education helped them to know about this chronic disease, understand its harm, and seek social help for treatment more easily.
With regard to health-related factors, many studies had pointed out that overweight and obesity was a risk factor for hypertension patients.30–32 In this study, we used BMI to evaluate overweight or obesity of participants. Interestingly, we found that the OR value of BMI was less than 1.0 in the LSLD group, indicating that the elderly with low SBP and DBP but still wide PP was generally slim, and gaining weight might be a beneficial behavior for them to control PP. Having single or multiple chronic diseases had positive associations in HSLD and HSHD groups but no statistical relationship in LSLD group. However, hypertension was included in chronic diseases in the interview, and hypertension had a strong correlation with HSLD and HSHD groups, so the casual relationship between number of chronic diseases and different types of wide PP was uncertain.
Regarding lifestyle factors, only current smoker was found to be negatively associated with the HSHD group, contrary to what we usually thought of smoking as a risk factor for hypertension. Nonetheless, a cross-sectional study of the association between smoking and blood pressure in men aged 20–80 years in Inner Mongolia also found that the adjusted blood pressure was lower in current smokers versus nonsmokers and former smokers, meanwhile the adjusted PP tend to be decreased steadily as the pack/years increased in current smokers.33 Some studies have conducted that smoking can cause acute blood pressure increase,34 but the effect on PP was unclear and the long-term effects on blood pressure were also inconclusive. In our study, current alcohol drinker was positively correlated with HSHD group. We all know that heavy alcohol intake was a risk factor of hypertension. However, some prospective studies conducted that moderate alcohol intake was beneficial.35,36 Meanwhile a meta-analysis had pointed out that reducing alcohol intake could decrease blood pressure in participants who drank six or more drinks per day if they reduced their intake by about 50%.37 Consequently, more evidence was needed to clarify the association of daily alcohol intake and wide PP. We had not found association between tea drinking and wide PP, but it had been reported that moderate drinking of green tea is a protective factor for hypertension patients. Some laboratory studies had shown that tea and its secondary metabolites played important roles in relaxing smooth muscle contraction, enhancing endothelial nitric oxide synthase activity, reducing vascular inflammation, inhibiting rennin activity, and anti-vascular oxidative stress.38 We have not found a relationship between sleep quality and wide PP either. Sleep quality was self-reported in our study, so recall bias and reporting bias might influence our results.
However, subgroup analyses between lifestyle factors and wide PP by gender found that only among male, current smoker was still negatively and current alcohol drinker was positively with wide PP, which indicated smoking and alcohol drinking would affect male's PP more.
Our study was based on the Yiwu Elderly Cohort, which collected relatively complete lifestyle information of the elderly population and its sample size is relatively adequate. In addition, this study divided wide PP population into three different types to explore their associations with a series of influencing factors, which can better clarify wide PP and see if PP is a better index to assess blood pressure in the elderly. While, this study still had some limitations. Firstly, the cut-off values of SBP, DBP and PP were determined from the approximate median values in this elderly population, so the grouping of wide PP may differ in other populations and might cause different results. Secondly, in addition to influencing factors included in this study, other confounding factors might need to be considered. For instance, different degrees of aortic valve insufficiency were common in elderly population, which was a very important factor influencing PP. However, in our study, echocardiography was not available. Finally, this was a cross-sectional design study, so the results did not support inferences regarding causality. Therefore, case control studies or cohort studies were needed to verify the causality of these influence factors and different types wide PP further.
CONCLUSIONSour study provided evidence that blood pressure in the elderly population was different from general population, and half of the elderly had wide PP, mostly HSHD type wide PP. In addition, we explored the influencing factors of different types of wide PP, we found age, gender, body height, marital status, education level, chronic diseases, BMI, smoking and alcohol drinking had different associations with different types wide PP. Future prospective studies were required to prove the mechanism between these factors and increased risk of wide PP (supplementary materials).
AUTHOR CONTRIBUTIONSMengling Tang and Honglei Dai designed the study. Dandan Yang and Jie Chen processed data, performed statistical analysis and drafted the manuscript. Tingting Zhang, Yaoyao Lin, Xuecheng Yao, Lin Meng, Fanjia Guo and Kun Chen carefully revised the intellectual content.
ACKNOWLEDGMENTSThis study was supported by the Fundamental Research Funds for the Central Universities (2021FZZX001-39, 2020QNA7018). This study conformed to the guidelines of the Declaration of Helsinki, and the study protocol was reviewed and approved by the Ethics Committee of the fourth affiliated hospital of Zhejiang University. Written informed consents were obtained from all participants before enrolling in the study.
CONFLICTS OF INTERESTThe authors declare that they have no potential conflicts of interest.
PATIENT CONSENT STATEMENTWritten informed consents were obtained from all participants before enrolling in the study.
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Details
; Dai, Honglei 2 ; Tang, Mengling 1
1 Department of Public Health, Fourth Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
2 Fourth Affiliated Hospital, Zhejiang University School of Medicine, Jinhua, China
3 Department of Public Health, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China