Components of the Complete Blood Count as a Risk Predictor for Incident Hypertension in a Large Taiwanese Population Follow-up Study

Abstract

Background: Previous studies investigating the relationship between hypertension (HT) and hematological parameters report inconsistent results, and most them included a small number of participants or only conducted a cross-sectional analysis of 1 or 2 hematological factors. Moreover, no large cohort follow-up studies have investigated this topic. The aim of this longitudinal study was to explore associations between components of the complete blood count (CBC) and incident HT using data from a large Taiwanese biobank

Methods and Results: Hematological parameters including white blood cell (WBC) count, red blood cell (RBC) count, hemoglobin, hematocrit (HCT), and platelet count were evaluated. We included 21,293 participants who did not have HT at baseline and followed them for a mean period of 3.9 years. During follow-up, 3,002 participants with new-onset HT (defined as incident HT) were identified. Univariable analysis revealed that high WBC count, high RBC count, high hemoglobin, high HCT, and low platelet count were associated with incident HT. Multivariable analysis after adjusting potential confounding factors found high WBC count (odds ratio [OR], 1.057; 95% confidence interval [CI], 1.028 to 1.087; P<0.001) and high HCT (OR, 1.023; 95% CI, 1.010 to 1.036; P<0.001) were still significantly associated with incident HT.

Conclusions: High WBC count and high HCT were associated with incident HT.

Hypertension (HT) is one of the most common diseases and an important cause of cardiovascular disease (CVD) and death in developed countries.^1,2 It causes cardiac hypertrophy, which leads to cardiomyopathy and heart failure, as well as serious blood vessel-related complications, such as stroke, coronary artery disease, aortic aneurysm, aortic vascular dissection, and renal vascular disease, all of which can result in permanent damage and death.³ The prevalence of HT among adults aged ≥18 years in Taiwan is approximately 25%, and the rate continues to increase.⁴

HT is a multifactorial disease, and inflammation is known to play an important role in the development of both atherosclerosis and HT.⁵ An elevated circulating white blood cell (WBC) count, a well-known independent marker of systemic inflammation, has been associated with CVD and death.^6,7 However, nearly all elements of the complete blood count (CBC), including WBCs, red blood cells (RBCs), and platelets, are also involved in the underlying pathogenesis of atherosclerosis.^8–10 The relationship between arterial calcification and RBCs is bidirectional: calcification promotes hemorrhage, and hemoglobin (Hb) release promotes calcification of elastic vascular tissues.⁹ Local RBC hemolysis has also been associated with both early and advanced stages of atherosclerosis.⁹ In addition to their known functions in thrombosis and hemostasis, platelets provide a link among inflammation, thrombosis, and atherosclerosis.¹⁰ In atherosclerosis, platelets promote the recruitment of inflammatory cells to the lesion site and release large amounts of inflammatory mediators by interacting with endothelial cells and circulating leukocytes.¹⁰ Various elements of the CBC have been associated with CVD and metabolic syndrome.^11–13 For example, Lassale et al reported that total and differential WBC counts, mean corpuscular volume, RBC distribution width, and platelet count likely to play a role in the incidence of CVD.¹¹ In addition, Anderson et al demonstrated a simple CBC-derived risk score comprising hematocrit (HCT) and WBC and platelet counts, and showed that the score had high predictive ability for the risk of incident death, and that better predictions were obtained when expanding the score to encompass more hematological parameters.¹⁴ Moreover, Hsu et al found that hemogram-based decision tree analysis, including Hb and WBC and platelet counts, could assist in the early identification of older patients at a high risk of future HT, type 2 diabetes, and CVD.¹² The CBC is routinely measured during blood examinations, and can provide an overview of a person’s general health status. Importantly, it is simple to perform and cost-effective. The most commonly used blood components in medical practice are WBC count, RBC count, Hb, HCT, and platelet count.

Increasing research has shown that changes in hemogram parameters are also associated with HT, including WBC count,^15–17 RBC count,¹⁸ Hb,^18–21 HCT,^18,22–25 platelet count,^26,27 mean platelet volume (MPV),^26,28,29 and platelet distribution width (PDW).^26,30 Although some research has been carried out on the relationship between hematological factors and HT, most of these studies have only investigated 1 or 2 factors, only included a small number of participants, or only conducted a cross-sectional analysis.^{19–22,28,31–33} Therefore, the ability of these hematological parameters to predict incident HT is unclear. In addition, some studies of the predictive ability of hematological factors for the risk of HT have reported a significant predictive effect,^15,28,34 but others have suggested a weak association.^19,22,35,36 These published data are controversial, derive from small sample sizes, and there were differences in study population and design. Therefore, the aim of the present study was to explore the association of hematological parameters with the risk of incident HT in a large Taiwanese population follow-up study.

Methods

Taiwan Biobank (TWB)

The TWB was established to collect the genomic and lifestyle data of Taiwanese residents, and it is now Taiwan’s largest government-sponsored biobank with 104,451 participants enrolled from 2012 to 2018.^37,38 Ethical approval for use of the TWB data was granted by the Institutional Review Board (IRB) on Biomedical Science Research, Academia Sinica, Taiwan, and the Ethics and Governance Council of the TWB. Community-based volunteers aged 30–70 years without a cancer history were enrolled in the TWB, and they all underwent physical examinations and had blood drawn for laboratory analysis. During in-person interviews, the participants were asked to fill out questionnaires with the assistance of a TWB researcher, during which personal information and medical histories were collected. Data collection in the TWB was based on long-term follow-up, and participants were followed up every 2–4 years according to their specific disease. All participants in the TWB provided written informed consent before enrollment.

Demographic, Medical, and Laboratory Data

We recorded the following variables: sex, age, presence of diabetes mellitus (DM) and HT, body mass index (BMI), smoking and alcohol histories, resting heart rate, systolic blood pressure (SBP), and diastolic blood pressure (DBP). We also documented whether the participants performed regular exercise, defined as physical activity for ≥30 min at least 3 times per week. In addition to hematological data (total WBC count, RBC count, Hb, HCT, and platelet count), we also recorded fasting blood chemical data, including serum creatinine, triglycerides, cholesterol, and glucose.

Blood pressure (BP) readings were taken digitally by a trained member of staff. Before the initial BP measurement, participants were asked to avoid nicotine, exercise, and caffeine for at least 30 min. BP (SBP and DBP) was measured 3 times at intervals of 1–2 min, and the average was used in the analysis.

A total of 27,209 participants (mean follow-up duration 3.9 years) with complete baseline and follow-up data were included in this study. Participants with baseline HT (n=5,916) were excluded, and the remaining 21,293 were included (Figure).

Figure.

Flowchart of study population.

Definition of Incident HT

Participants with no history of HT (self-reported), and SBP/DBP <140/90 mmHg were defined as not having HT. Those who developed HT (self-reported) or whose SBP/DBP ≥140/90 mmHg during follow-up were defined as having incident HT.

Ethics Statement

The IRB of Kaohsiung Medical University Hospital approved this study (KMUHIRB-E(I)-20210058), which was conducted in accordance with the Declaration of Helsinki.

Statistical Analysis

Categorical variables are presented as number (percentage), and continuous variables are presented as mean (standard deviation). The enrolled participants were divided into 2 groups based on incident HT. The independent samples t-test was used to compare continuous variables between groups, and the chi-square test was used for categorical variables. Univariable binary logistic regression analysis was used to find the factors associated with incident HT. In the multivariable binary logistic regression analysis, we adjusted age, sex, DM, SBP, BMI, smoking and alcohol history, regular exercise, fasting glucose, total cholesterol, and triglycerides. P<0.05 was considered to be significant. Statistical analyses were performed using SPSS version 26.0 for Windows (SPSS Inc., Chicago, USA).

Results

The total number of participants in this study was 21,293 (14,522 women, 6771 men; mean age 49.6±10.3 years), of whom 3,002 had incident HT and 18,291 did not.

Comparison of Baseline Characteristics

Participants in the incident HT group were older, followed for a longer period, and had a higher percentage of male participants than the group without incident HT. They had a higher prevalence of DM and regular exercise. They also had higher levels of SBP, heart rate, BMI, smoking and alcohol history, fasting glucose, total cholesterol, and triglycerides (Table 1). Regarding the components of the CBC, the incident HT group had higher WBC and RBC counts, Hb, and HCT and lower platelet count.

Table 1. Baseline Characteristics of Participants With and Without Incident HT

Characteristics	Participants with incident HT (n=3,002)	Participants without incident HT (n=18,291)	P value	All participants (n=21,293)
Age (years)	54.7±9.3	48.8±10.2	<0.001	49.6±10.3
Male (%)	42.9	30.0	<0.001	31.8
DM (%)	6.6	3.0	<0.001	3.5
SBP (mmHg)	123.5±10.1	110.0±12.2	<0.001	111.6±12.8
Heart rate (beats/min)	69.9±9.1	69.4±8.7	0.001	69.4±8.8
BMI (kg/m2)	24.9±3.4	23.4±3.3	<0.001	23.6±3.4
Smoking history (%)	28.0	21.5	<0.001	22.4
Alcohol history (%)	11.2	6.6	<0.001	7.2
Regular exercise (%)	50.2	42.4	<0.001	43.5
Fasting glucose (g/dL)	99.4±24.8	93.6±17.1	<0.001	94.4±18.5
Total cholesterol (mg/dL)	199.5±35.5	194.2±35.3	<0.001	195.0±35.3
Triglycerides (mg/dL)	129.2±98.0	104.0±75.5	<0.001	107.5±79.5
Components of complete blood count
WBC count (1,000/μL)	6.16±1.63	5.86±1.60	<0.001	5.90±1.61
RBC count (106/μL)	4.79±0.50	4.69±0.50	<0.001	4.71±0.50
Hemoglobin (g/dL)	14.0±1.5	13.6±1.5	<0.001	13.6±1.5
HCT (%)	43.8±4.4	42.7±4.4	<0.001	42.9±4.4
Platelets (1,000/μL)	239.1±58.6	242.8±57.7	0.001	242.3±57.9
Follow-up (years)	4.00±1.38	3.85±1.26	<0.001	3.87±1.28

BMI, body mass index; DM, diabetes mellitus; HCT, hematocrit; HT, hypertension; RBC, red blood cell; SBP, systolic blood pressure; WBC, white blood cell.

Factors Associated With Incident HT

Univariable analysis revealed that male sex, older age, DM, and high SBP, heart rate, BMI, smoking and alcohol history, regular exercise, fasting glucose, total cholesterol, and triglycerides were associated with incident HT (Table 2). With regards to the components of the CBC, high WBC count (odds ratio [OR], 1.115; 95% confidence interval [CI], 1.089 to 1.141; P<0.001), high RBC count (OR, 1.462; 95% CI, 1.358 to 1.573; P<0.001), high Hb (OR, 1.222; 95% CI, 1.190 to 1.255; P<0.001), high HCT (OR, 1.062; 95% CI, 1.052 to 1.071; P<0.001), and low platelet count (OR, 0.999; 95% CI, 0.998 to 1.000; P<0.001) were associated with incident HT in the univariable analysis.

Table 2. Determinants of Incident HT Using Univariable Binary Logistic Analysis of All Study Participants (n=21,293)

Parameter	Univariable
	OR (95% CI)	P value
Age (per 1 year)	1.064 (1.060–1.069)	<0.001
Male (vs. female)	1.750 (1.617–1.894)	<0.001
DM	2.304 (1.948–2.724)	<0.001
SBP (per 1 mmHg)	1.109 (1.104–1.113)	<0.001
Heart rate (per 1 beat/min)	1.007 (1.003–1.012)	<0.001
BMI (per 1 kg/m2)	1.139 (1.126–1.151)	<0.001
Smoking history	1.420 (1.301–1.549)	<0.001
Alcohol history	1.813 (1.595–2.060)	<0.001
Regular exercise	1.369 (1.267–1.479)	<0.001
Fasting glucose (per 1 g/dL)	1.012 (1.010–1.014)	<0.001
Total cholesterol (per 1 mg/dL)	1.004 (1.003–1.005)	<0.001
Triglyceride (per 1 mg/dL)	1.003 (1.003–1.004)	<0.001
Component of complete blood count
WBC count (1,000/μL)	1.115 (1.089–1.141)	<0.001
RBC count (106/μL)	1.462 (1.358–1.573)	<0.001
Hemoglobin (per 1 g/dL)	1.222 (1.190–1.255)	<0.001
HCT (%)	1.062 (1.052–1.071)	<0.001
Platelets (1,000/μL)	0.999 (0.998–1.000)	<0.001

Values expressed as odds ratio (OR) and 95% confidence interval (CI). Abbreviations as in Table 1.

We next performed multivariable analysis to explore which of the CBC components were associated with incident HT (Table 3). After adjustment of age, sex, DM, SBP, BMI, smoking and alcohol history, regular exercise, fasting glucose, total cholesterol, and triglycerides, the results showed that high WBC (OR, 1.057; 95% CI, 1.028 to 1.087; P<0.001) and high HCT (OR, 1.023; 95% CI, 1.010 to 1.036; P<0.001) were significantly associated with incident HT. However, RBC count and Hb were not significantly associated with incident HT in the multivariable analysis.

Table 3. Multivariable Binary Logistic Analysis of Hemogram Parameters for Incident HT

Parameters	Multivariable
	OR (95% CI)	P value
WBC count (1,000/μL)	1.057 (1.028–1.087)	<0.001
RBC count (106/μL)	1.064 (0.964–1.174)	0.22
Hemoglobin (per 1 g/dL)	1.037 (0.999–1.077)	0.058
HCT (%)	1.023 (1.010–1.036)	<0.001
Platelets (1,000/μL)	1.001 (1.000–1.002)	0.052

Covariates in the multivariable model included age, sex, DM, SBP, BMI, smoking and alcohol history, regular exercise, fasting glucose, total cholesterol, and triglycerides. Values expressed as OR and 95% CI. Abbreviations as in Tables 1,2.

The results of multivariable logistic regression analysis to identify the association of hemogram parameters for incident HT by sex are shown in Table 4. In the male participants (n=6,771), after adjusting for age, DM, SBP, BMI, smoking and alcohol history, regular exercise, fasting glucose, total cholesterol, and triglycerides, high WBC (OR, 1.057; 95% CI, 1.014 to 1.102; P=0.009), high HCT (OR, 1.021; 95% CI, 1.002 to 1.041; P=0.032), and high platelet count (OR, 1.002; 95% CI, 1.001 to 1.003; P=0.003) were significant associated with incident HT. In the female participants (n=14,522), after adjusting for age, DM, SBP, BMI, smoking and alcohol history, regular exercise, fasting glucose, total cholesterol, and triglycerides, high WBC (OR, 1.059; 95% CI, 1.019 to 1.100; P=0.003) and high HCT (OR, 1.022; 95% CI, 1.005 to 1.039; P=0.010) were significant associated with incident HT.

Table 4. Multivariable Binary Logistic Analysis of Hemogram Parameters for Incident HT in Different Sexes

Parameters	Male (n=6,771)		Female (n=14,522)
	Multivariable		Multivariable
	OR (95% CI)	P value	OR (95% CI)	P value
WBC count (1,000/μL)	1.057 (1.014–1.102)	0.009	1.059 (1.019–1.100)	0.003
RBC count (106/μL)	1.022 (0.884–1.181)	0.771	1.084 (0.947–1.242)	0.242
Hemoglobin (per 1 g/dL)	1.051 (0.989–1.116)	0.107	1.022 (0.973–1.074)	0.379
HCT (%)	1.021 (1.002–1.041)	0.032	1.022 (1.005–1.039)	0.010
Platelets (1,000/μL)	1.002 (1.001–1.003)	0.003	1.000 (0.999–1.001)	0.662

Covariates in the multivariable model included age, DM, SBP, BMI, smoking and alcohol history, regular exercise, fasting glucose, total cholesterol, and triglyceride. Values expressed as OR and 95% CI. Abbreviations as in Tables 1,2.

Discussion

In this study, we found that high WBC and RBC counts, Hb, and HCT, as well as a low platelet count were associated with the development of HT in the univariable analysis. After adjusting for the effect of confounding factors, including age, sex, DM, SBP, BMI, smoking and alcohol history, regular exercise, fasting glucose, total cholesterol, and triglycerides, high WBC count and high HCT were still significantly associated with incident HT in the multivariable analysis. Furthermore, the interaction between platelet count and sex was also statistically significant, but high platelet count was strongly associated with incident HT only in men.

WBC count is a routinely measured marker of systemic inflammation, and has been demonstrated to be an independent predictor of CVD and death in several studies.^6,39,40 In the Framingham study, Kannel et al reported that an elevated WBC count was a marker of an increased risk of CVD, even within the normal range.⁶ In a population-based cohort study designed to investigate the etiology of atherosclerosis, Lee et al found that elevated WBC count was a risk factor for coronary artery disease, ischemic stroke, and cardiovascular death in African-American and white men and women.⁴⁰ Chronic inflammation can cause vascular damage, endothelial dysfunction, and the development of atherosclerotic disease, in which macrophages and other phagocytes derived from WBCs play an important role.^41,42 Friedman et al were the first to discover that WBCs may be a predictor of HT, and in a study of 1,031 people who were followed for an average of 6 years, they found a progressive increase in the risk of developing HT as the WBC quartile increased from lowest to highest.³² However, previous studies suggested that the relationship between WBC count and HT was affected by ethnicity and sex.^15,17,34,43 The NHANES I Epidemiologic Follow-up Study reported an association between a higher WBC count and an increased incidence of HT in white men, and possibly older white and black women, but no positive association was found in black men.⁴³ A predominantly white cohort study conducted in Wisconsin reported that an elevated WBC count was associated with incident HT among women and men independent of smoking and most traditional cardiovascular risk factors.³⁴ In Asia, a cross-sectional study showed a significant association between WBC count and the risk of HT in a large sample of Chinese adults, independent of adiposity and other metabolic changes related to fasting glucose and lipid levels.¹⁷ In addition, an observational study of a general Japanese population showed a close association between WBC count and further development of HT.¹⁵ Regarding the subtypes of WBCs, high levels of neutrophils⁴⁴ and monocytes,⁴⁵ and low lymphocytes⁴⁶ have been proposed as potential predictors of CVD. The neutrophil count was demonstrated to be the strongest component of the WBC associated with SBP and DBP in an observational analysis of the UK Biobank, but there was no evidence of a causal effect in Mendelian randomization analysis.¹⁶ On the other hand, cross-sectional and Mendelian randomization analyses of the UK Biobank found that a high blood lymphocyte count might play a causal role in the development of HT.¹⁶ Our study supported the findings from previous studies, and we found a link between high WBC count and incident HT in this large Taiwanese population follow-up study. Moreover, the effect of WBCs on HT remained significant after adjustment of potential confounders.

Erythrocyte parameters, including RBC count, Hb, and HCT, are the most essential factors when determining the viscosity of whole blood.⁴⁷ Increased Hb and HCT leads to increased viscosity, which in turn causes cardiovascular events.⁴⁸ However, the relationship between blood viscosity and BP is inconclusive. Previous studies have suggested that increased blood viscosity may play a role in the hemodynamics of systemic HT,^49,50 but that BP and blood viscosity are not correlated in normal healthy subjects.^51,52 However, only a few studies have examined the relationship between erythrocyte parameters and BP. Bernd et al reported that a higher average arterial pressure was associated with erythrocyte count, HCT, and Hb concentration, but they did not adjust the other risk factors.¹⁸ Other studies have reported a positive association between Hb level and both SBP and DBP, but most of these studies were cross-sectional.^19–21,24 In addition, some studies reported inconsistent conclusions and findings.^35,36 Shimizu et al reported that the positive association between Hb level and the risk of HT was limited to Japanese men and women with a BMI <25 kg/m.^2,36 In a Korean study, Kim et al found that the relationship between Hb level and BP existed only in their cross-sectional analysis but not in the longitudinal analysis, suggesting that Hb did not cause HT.³⁵ Many cross-sectional studies have shown a positive association between HCT and HT,^18,22,24,53 but prospective studies are few.^25,54 A significant association between HCT and the risk of pre-HT was also reported in a large cross-sectional study involving 23,691 patients in China.²³ However, most of the previous studies only examined 1 or 2 erythrocyte parameters in relation to HT, and most of them were cross-sectional in design. Our large population prospective study might fill this gap in the knowledge, as we showed that all 3 erythrocyte parameters, namely RBC count, Hb, and HCT, were all associated with incident HT in the univariate analysis. However, only HCT remained significantly associated with incident HT after adjustment of confounding factors, which suggests HCT as a useful predictor of future HT development. More research is needed to elucidate the different mechanisms in predicting incident HT by these 3 erythrocyte parameters.

Platelet activity is an important contributor to atherothrombosis, which is the primary risk factor of most CVD.^10,55 Increased platelet activation and aggregation contribute to the pathogenesis of HT, and are also linked to hypertensive risk factors.^56–58 Platelet indices include platelet count, mean MPV, and PDW. Previous studies have found that HT is related to the platelet indices, but most of those focused more on MPV.^{28,29,58–60} Platelet count has also been associated with death and future CVD.⁶¹ However, few studies have investigated the relationship between HT and platelet count.^26,27 A population-based study in China explored the association between platelet indices and BP using the quadratic inference function method, and showed that platelet count was associated with DBP only in the male participants.²⁶ A bidirectional Mendelian randomization study using cross-sectional data from the TWB found a significant causal effect of high platelet count on an increased risk of HT.²⁷ In our longitudinal study, we found a negative association between platelet count and incident HT in the univariable analysis, and the relationship became insignificant after multivariable analysis. In the univariate analysis, low platelets were associated with incident HT, probably because platelet counts were lower in males than in females and the platelet count decreases with age; both male sex and age are significant risk factors of incident HT. Such results were also found in a previous study using the same TWB database.²⁷ In addition, a high platelet count is associated with incident HT exclusively in men, indicating that the role of platelets in the development of incident HT differs by sex. This implied that platelet count might be associated with the risk of HT, but the association was weak and easily confounded by other factors. Unfortunately, only platelet count was available in our study, so we were unable to analyze the relationship between the other platelet indices and incident HT.

Study Limitations

The main strengths of this study were that we included a large cohort of participants and 5 hematological parameters were analyzed. Despite these strengths, there were also several limitations. First, inflammation plays an important role in the development of HT. We had no data for C-reactive protein levels, although we found a significant association between WBC count and incident HT in the multivariable analysis, which suggested the association between WBC and incident HT could be mediated by inflammation. Second, we had no medication information, so we could not adjust for that in the multivariable analysis. Hence, the effect of medication on the present findings could be excluded completely. Third, the median follow-up duration was relatively short (3.9 years). Even though WBC count and HCT were significantly associated with incident HT in this relatively short period, a longer follow-up period might provide more reliable results. Fourth, participants may have a bias in their recall of HT history, even though we used average BP measurements to reduce diagnostic errors. Fifth, we did not have dietary information, which may influence the development of HT, so we were unable to determine the effect of diet on incident HT. Finally, although we analyzed the relationships of WBC count, RBC count, Hb, HCT, and platelet count with HT, data for other hematologic parameters were not available in the TWB dataset, and therefore we were unable to analyze their relationships with incident HT.

In conclusion, our results showed that high WBC count and high HCT were associated with incident HT in a large cohort of participants in Taiwan. Further studies are warranted to investigate the mechanisms underlying these associations.

Conflicts of Interest

The authors declare that they have no known competing financial interests or personal relationships that could appear to influence the work reported here.

Author Contributions

Y.-H.L. reviewed the articles and wrote the manuscript. S.-C.C., and W.-H.L. analyzed and interpreted the data. Y.-C.C., J.-C.H., and P.-Y.W. provided consultation and validation. C.-H.H. and C.-H.K. supervised the work. H.-M.S. revised the manuscript draft and the final version of the submitted manuscript. All authors read and approved the final manuscript.

Data Availability Statement

The data that support the findings of this study are available from Taiwan Biobank, but restrictions apply to the availability of the data, which were used under license for the current study, and so are not publicly available. Data are, however, available from the authors upon reasonable request and with permission of Taiwan Biobank.

Acknowledgment

Our study was supported by a grant from Kaohsiung Municipal Siaogang Hospital (kmhk-109-008, K-110-02, and S-109-11), Kaohsiung Medical University, Kaohsiung, Taiwan.

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