Abstract
Background
Chronic pain and hypertension have an enormous influence on both society and individuals. No previous research has examined the association between pain in multiple sites and the risk of hypertension.
Methods
A total of 402,230 individuals in the United Kingdom (UK) Biobank were included. The number of pain sites was categorized into 0 (no pain), 1, 2, 3, ≥ 4 sites of pain, and “pain all over the body”. Cox proportional hazards model was respectively used to estimate the associations of the number of pain sites and specific pain with incident hypertension. Hazard ratio (HR) and 95% confidence interval (CI) was also calculated.
Results
There were 105,617 (26.3%) hypertension cases occurred during a median follow-up of 13.35 years. The incidence of hypertension in 0, 1, 2, 3, ≥ 4 pain sites, and “pain all over the body” were 23.2%, 27.5%, 31.3%, 34.6%, 38.0%, and 42.0%, respectively. Participants with 3, ≥ 4 pain sites, and “pain all over the body” respectively had 36% (95% CI: 33%-40%), 50% (95% CI: 46%-55%), and 62% (95% CI: 55%-69%) higher risk of hypertension compared with those without pain. All types of pain including headache, facial pain, neck/shoulder pain, back pain, stomach/abdominal pain, hip pain, and knee pain, were positively associated with the incidence of hypertension.
Conclusion
We provided evidence that the number of pain sites was associated with an increased risk of hypertension. Certain specific types of pain, such as headache, neck/shoulder pain, and back pain, were also associated with hypertension risk.
Supplementary Information
The online version contains supplementary material available at 10.1186/s41043-025-01089-6.
Keywords: Chronic pain, Hypertension, UK biobank, Cohort study, Back pain
Introduction
Chronic pain is a prevalent, complicated, and frustrating issue, which has an enormous influence on both society and individuals [1]. Chronic pain is not only a symptom accompanying other diseases, but it is also an independent condition in itself [2]. According to an estimation from the Global burden of disease (GBD) study 2019, a significant increase was observed in global prevalence of chronic pain between 1990 and 2019 [3]. Globally, low-back pain, headache, and neck pain were listed as the top 25 leading causes of global years lived with disability (YLDs) across all ages in 2021 [4]. Despite a decline in the age-standardized prevalence rate of low back pain from 1990 to 2021, the number of affected individuals increased from 386.7 million to 628.8 million [5]. In 2019, the estimated global prevalence of headache disorders reached 2.60 billion cases, with projections indicating a continued rise in headache burden over the next 15 years [3]. Chronic pain often occurs simultaneously at more than one anatomical site [6], and pain at multiple sites has been linked to worse health outcomes than pain at a single site [7].
Hypertension remains one of the leading risk factors for stroke, ischemic heart disease, and chronic kidney disease. It was estimated that 8.5 million deaths were attributable to systolic blood pressure (SBP) > 115 mmHg in 2015 around the world [8]. Although the age standardized prevalence of hypertension worldwide is stabilizing, the number of people aged 30–79 years with hypertension doubled from 1990 to 2019 [9]. Therefore, hypertension continues to be a serious public health concern, particularly for low- and middle-income countries as well as aging societies.
It is well recognized that the regions of the brain involved in antinociception and cardiovascular system control are substantially overlaped. The nucleus tractus solitarius (NTS), which is the location of the first synapse in the baroreceptor reflex pathway and acts as the interface between the autonomic and sensory systems, is of particular relevance [10]. Chronic pain frequently triggers heightened sympathetic nervous system activity, which in turn can elevate blood pressure [11]. Beyond the sympathetic nervous system and vascular elements already noted, neuroendocrine pathways, particularly the renin-angiotensin-aldosterone system (RAAS)—a key player in blood pressure control—have been found to interact with pain perception pathways [12]. Based on these interactions, it is reasonable to assume that there may be some connection between chronic pain and hypertension.
Few studies have explored the association between chronic pain and risk of hypertension at the population level, and existing results are inconsistent. A cross-sectional case comparison study revealed that 39% of the pain group was diagnosed with hypertension, compared with 21% of the nonpain group (p < 0.001) [13]. A recent cross-sectional study found a significant association between hypertension and chronic pain among 1031 employees and university students in Saudi Arabia [14]. In contrast, a cross-sectional study involving 349 workers suggested that there was no difference in musculoskeletal pain prevalence and sensitivity between hypertensive and normotensive workers [15]. All of these studies had small sample sizes and were retrospective in nature. More importantly, no research has examined the association between pain in multiple sites and the risk of hypertension. Therefore, this study aims to investigate the association of the number of pain site and specific pain with the risk of hypertension by using data from the UK Biobank cohort.
Methods
Study population
UK Biobank is a community-based cohort study conducted in England, Wales, and Scotland. The study enrolled more than 500,000 individuals aged 40 to 70 years between 2006 and 2010. A detailed description of the study design and population enrollment has been reported elsewhere [16]. Briefly, a total of 502,316 men and women was included at baseline. We excluded 2198 participants without pain data, 39,334 participants diagnosed with hypertension before/at baseline, and 58,413 participants had missing data on covariates. In addition, we further removed 141 participants who decided to withdraw from the UK Biobank. As a result, 402,230 individuals were included in the final analysis. All participants were followed for a median of 13.35 years via hospital record linkage for incident hypertension. A flowchart of the study population selection is shown in Fig. 1. The UK Biobank was approved by North West Multi-Centre Research Ethics Committee (Reference: 21/NW/0157).
Fig. 1.
A flowchart of the study population selection
Pain assessment
A touchscreen pain questionnaire was provided for participants to select whether they had experienced pain at the sites of the head, face, neck/shoulder, back, stomach/abdomen, hip, and knee in the last month. Participants could select more than one site and they could also select “pain all over the body”. If participants have chosen “pain all over the body” then they could not select any specific pain sites. Participants were then asked whether the stated pain had persisted for at least three months if they felt pain “all over the body” or in at least one site. The number of pain sites that persisted for at least three months was also calculated. The number of pain sites was categorized into six groups: 0 (no pain), 1, 2, 3, ≥ 4 sites of pain, and “pain all over the body”. These groups were used in the analysis and the group 0 (no pain) was used as reference group.
Definition of outcome
Disease outcomes were linked to hospital records from the UK. Hypertension was identified via the International Classification of Diseases Tenth Revision (ICD-10), codes I10, I11, I12, I13, and I15. The end of follow-up was set at December 19, 2022, as hospital records were available up to that date for our analysis. The follow-up time was calculated by taking the time interval between the baseline date and the date of the hypertension diagnosis, death, loss to follow-up, or end of follow-up, whichever occurred first.
Covariates measurement
Demographic and lifestyle data were collected using a touch-screen questionnaire by trained staff. Age was calculated based on the date of birth and the date of the baseline survey. Gender was classified into male and female according to biological sex. Ethnicity was classified into white, black, and others. Index of Multiple Deprivation (IMD), a composite indicator of deprivation, was calculated based on income, employment, health, education, access to services, community safety and physical environment [17]. Lifestyle variables include smoking, alcohol drinking, and sedentary activity. Smoking status was divided into three categories: never, past, and current. The frequency of alcohol consumption was divided into six categories: never, occasions only, 1–3 times/month, 1–2 times/week, 3–4 times/week, and almost daily. Sedentary time was calculated by adding the hours spent each day driving, using a computer, and watching television.
Body weight was measured by the Tanita BC-418 MA body composition analyzer (Tanita Corporation of America, IL). Standing height was measured by the Seca 202 gadget (SECA, Hamburg, Germany). Body mass index (BMI) was calculated by dividing weight in kilograms by the square of height in meters.
Serum c-reactive protein (CRP) and creatinine were measured using a Beckman Coulter AU5800 clinical chemistry analyzer. Urine sodium and potassium were quantified by the use of the ion selective electrode method on a AU5400 analyzer. Serum uric acid (SUA) was measured by uricase PAP analysis on Beckman Coulter AU5800 (Beckman Coulter).
More details of methods used for covariates measurement in the UK Biobank are presented in previous publications [18, 19].
Statistical analysis
We used mean ± standard deviation (SD) and n (percentage) to present continuous variables and categorical variables respectively. The between group differences in characteristics were compared by using one-way Analysis of Variance (ANOVA) for continuous variables and chi-square tests for categorical variables. Kaplan-Meier curves and log-rank test were used to assess the unadjusted incidence rate of hypertension. Cox proportional hazards models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs). The proportional hazards assumption was evaluated using Schoenfeld residuals. Fine and Gray competing risk models were performed for validation. We also performed restricted cubic splines (RCS) to evaluate the potential dose-response relationship between number of pain sites and the risk of hypertension. Subgroup analyses were conducted age (≤ 50 vs. >50 years), sex (male vs. female), and follow-up durations (≤ 5 vs. >5 years). Sensitivity analyses were performed by excluding participants who were diagnosed with cancer. A two-tailed p-value < 0.05 was considered statistical significance. R 4.4.3 (R Foundation for Statistical Computing, Vienna, Austria) was used for all statistical analyses.
Results
A total of 402,230 participants in the UK Biobank were included in this study. The mean age was 56.2 ± 8.1 years for the whole population. The baseline characteristics of the study population according to the categories of pain sites are shown in Table 1. Participants with more number of pain sites were more likely to be older, to be women, to be physically inactive, to be current smoker, to have higher BMI, and to have higher level of CRP.
Table 1.
Characteristics of the study population in UK biobank (n = 402230)
| Characteristics | Total | Number of pain sites | P value | |||||
|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 2 | 3 | ≥ 4 | All over the body | |||
| Sample size | 402,230 | 231,593 | 92,376 | 43,654 | 19,245 | 10,646 | 4716 | |
| Age, year | 56.2 ± 8.1 | 56.0 ± 8.1 | 56.2 ± 8.1 | 56.4 ± 8.0 | 56.6 ± 7.9 | 56.2 ± 7.8 | 56.6 ± 7.6 | < 0.0001 |
| Men, n (%) | 181,837 (45.2) | 110,097 (47.5) | 41,732 (45.2) | 17,717 (40.6) | 7204 (37.4) | 3459 (32.5) | 1628 (34.5) | < 0.0001 |
| Race, n (%) | < 0.0001 | |||||||
| White | 382,559 (95.1) | 220,936 (95.4) | 87,922 (95.2) | 41,406 (94.9) | 18,138 (94.3) | 9952 (93.5) | 4205 (89.2) | |
| Black | 5701 (1.4) | 3111 (1.3) | 1321 (1.4) | 625 (1.4) | 314 (1.6) | 191 (1.8) | 139 (2.9) | |
| Others | 13,970 (3.5) | 7546 (3.3) | 3133 (3.4) | 1623 (3.7) | 793 (4.1) | 503 (4.7) | 372 (7.9) | |
| Index of Multiple Deprivation | 16.9 ± 13.8 | 15.9 ± 13.1 | 16.9 ± 13.7 | 18.2 ± 14.7 | 19.7 ± 15.3 | 22.2 ± 16.4 | 24.0 ± 16.9 | < 0.0001 |
| Sedentary time, h/d | 4.8 ± 2.4 | 4.6 ± 2.3 | 4.8 ± 2.4 | 5.0 ± 2.5 | 5.1 ± 2.6 | 5.3 ± 2.9 | 5.3 ± 3.1 | < 0.0001 |
| Smoking status, n (%) | < 0.0001 | |||||||
| Never | 223,592 (55.6) | 134,164 (57.9) | 50,088 (54.2) | 22,624 (51.8) | 9413 (48.9) | 5038 (47.3) | 2265 (48.0) | |
| Former | 136,756 (34.0) | 76,036 (32.8) | 32,444 (35.1) | 15,686 (35.9) | 7224 (37.5) | 3810 (35.8) | 1556 (33.0) | |
| Current | 41,882 (10.4) | 21,393 (9.2) | 9844 (10.7) | 5344 (12.2) | 2608 (13.6) | 1798 (16.9) | 895 (19.0) | |
| Drinking status, n (%) | < 0.0001 | |||||||
| Never | 29,654 (7.4) | 14,412 (6.2) | 6701 (7.3) | 3827 (8.8) | 2137 (11.1) | 1613 (15.2) | 964 (20.4) | |
| Occasions only | 44,394 (11.0) | 22,407 (9.7) | 10,092 (10.9) | 5792 (13.3) | 3072 (16.0) | 2038 (19.1) | 993 (21.1) | |
| 1–3 times/month | 44,985 (11.2) | 24,778 (10.7) | 10,348 (11.2) | 5334 (12.2) | 2469 (12.8) | 1477 (13.9) | 579 (12.3) | |
| 1–2 times/week | 105,194 (26.2) | 61,468 (26.5) | 24,481 (26.5) | 11,168 (25.6) | 4616 (24.0) | 2427 (22.8) | 1034 (21.9) | |
| 3–4 times/week | 95,256 (23.7) | 58,420 (25.2) | 21,699 (23.5) | 9192 (21.1) | 3665 (19.0) | 1660 (15.6) | 620 (13.2) | |
| Almost daily | 82,747 (20.6) | 50,108 (21.6) | 19,055 (20.6) | 8341 (19.1) | 3286 (17.1) | 1431 (13.4) | 526 (11.2) | |
| BMI, kg/m2 | 27.2 ± 4.6 | 26.7 ± 4.3 | 27.4 ± 4.7 | 27.8 ± 4.9 | 28.4 ± 5.2 | 29.0 ± 5.6 | 29.4 ± 5.8 | < 0.0001 |
| Uric acid, µmol/L | 306.1 ± 78.9 | 306.4 ± 78.6 | 306.9 ± 79.2 | 305.1 ± 79.5 | 304.3 ± 79.4 | 300.4 ± 77.9 | 304.8 ± 80.8 | < 0.0001 |
| Creatinine, µmol/L | 71.8 ± 15.5 | 72.2 ± 15.2 | 71.8 ± 15.6 | 71.1 ± 16.7 | 70.4 ± 14.9 | 69.5 ± 14.9 | 70.0 ± 22.5 | < 0.0001 |
| C-reactive protein, mg/L | 2.5 ± 4.2 | 2.3 ± 3.9 | 2.5 ± 4.2 | 2.8 ± 4.5 | 3.2 ± 5.1 | 3.6 ± 5.1 | 4.6 ± 6.6 | < 0.0001 |
| Urinary sodium, mmol/L | 77.3 ± 44.4 | 76.7 ± 44.1 | 77.9 ± 44.6 | 78.2 ± 44.8 | 78.6 ± 45.5 | 78.0 ± 46.2 | 78.6 ± 46.5 | < 0.0001 |
| Urinary potassium, mmol/L | 63.2 ± 33.9 | 63.2 ± 33.9 | 63.6 ± 33.9 | 63.1 ± 34.1 | 63.0 ± 33.9 | 61.4 ± 33.6 | 61.3 ± 33.8 | < 0.0001 |
Note: continuous variables are presented as mean ± standard deviation (SD) and categorical variables are presented as n (%). BMI, body mass index; UK, United Kingdom
There were 105,617 (26.3%) hypertension cases occurred during a median follow-up of 13.35 years. The incidence of hypertension in 0, 1, 2, 3, ≥ 4 pain sites, and “pain all over the body” were 23.2%, 27.5%, 31.3%, 34.6%, 38.0%, and 42.0%, respectively. The Kaplan-Meier curves (see Supplemental Fig. 1) showed that individuals with more sites of pain had significantly higher incident hypertension (p for log-rank < 0.0001). After adjusted for multiple covariates, participants in the group of 1, 2, 3, ≥ 4 pain sites, and “pain all over the body” respectively had 14% (HR: 1.14, 95% CI: 1.12–1.16), 29% (HR: 1.29, 95% CI: 1.27–1.32), 36% (HR: 1.36, 95% CI: 1.33–1.40), 50% (HR: 1.50, 95% CI: 1.46–1.55), and 62% (HR: 1.62, 95% CI: 1.55–1.69) higher risk of hypertension compared with those without pain (see Table 2). Upon validation with competing risks models, the findings remain essentially unchanged. The results consistently demonstrated a positive association between number of pain sites and hypertension incidence across all subgroups (see Supplemental Table 1). We additionally found that there is a non-linear dose-response relationship between number of pain sites and hypertension risk (see Fig. 2). Sensitivity analyses revealed that there are no essential changes in the association between the number of pain sites and the risk of hypertension after excluding 36,642 participants who were diagnosed with cancer at baseline (see Supplemental Table 2).
Table 2.
Association between the number of pain sites and risk of hypertension
| Number of pain sites | P for trend | ||||||
|---|---|---|---|---|---|---|---|
| 0 | 1 | 2 | 3 | ≥ 4 | All over the body | ||
| Incidence of hypertension, n (%) | 53,831 (23.2) | 25,427 (27.5) | 13,674 (31.3) | 6660 (34.6) | 4043 (38.0) | 1982 (42.0) | < 0.0001 |
| HR (95% CI) estimated from Cox regression models | |||||||
| Model 1a | 1 (Reference) | 1.23 (1.21–1.25) | 1.46 (1.44–1.49) | 1.66 (1.62–1.70) | 1.99 (1.92–2.05) | 2.27 (2.17–2.37) | < 0.0001 |
| Model 2b | 1 (Reference) | 1.19 (1.18–1.21) | 1.38 (1.36–1.41) | 1.51 (1.47–1.54) | 1.73 (1.67–1.79) | 1.92 (1.84–2.01) | < 0.0001 |
| Model 3c | 1 (Reference) | 1.14 (1.12–1.16) | 1.29 (1.27–1.32) | 1.36 (1.33–1.40) | 1.50 (1.46–1.55) | 1.62 (1.55–1.69) | < 0.0001 |
| HR (95% CI) estimated from Fine and Gray models | |||||||
| Model 1a | 1 (Reference) | 1.23 (1.21–1.24) | 1.46 (1.43–1.48) | 1.64 (1.60–1.68) | 1.97 (1.91–2.04) | 2.19 (2.09–2.30) | < 0.0001 |
| Model 2b | 1 (Reference) | 1.19 (1.18–1.21) | 1.38 (1.35–1.40) | 1.50 (1.46–1.54) | 1.73 (1.67–1.79) | 1.87 (1.78–1.96) | < 0.0001 |
| Model 3c | 1 (Reference) | 1.14 (1.12–1.16) | 1.29 (1.26–1.31) | 1.35 (1.32–1.39) | 1.51 (1.46–1.56) | 1.59 (1.51–1.67) | < 0.0001 |
aadjusted for age and sex; badjusted for age, sex, race, index of multiple deprivation (IMD), smoking, drinking, and sedentary time; cadjusted for age, sex, race, IMD, smoking, drinking, sedentary time, body mass index, serum uric acid, creatinine, c-reactive protein, urinary sodium, and urinary potassium. HR, hazard ratio; CI, confidence interval. Values in the table are presented as n (%) for incidence of hypertension. HR (95% CI) is presented for Cox regression with their confidence interval
Fig. 2.
Dose-response relationship between number of pain site and the risk of hypertension. Note: HR (95% CI) was adjusted for age, sex, race, index of multiple deprivation (IMD), smoking, drinking, sedentary time, body mass index, serum uric acid, creatinine, c-reactive protein, urinary sodium, and urinary potassium. HR, hazard ratio; CI, confidence interval. The number 5 on the x-axis represents pain all over the body. The height of the purple density curve represents the proportion of population to the total study population
The results of association between specific pain site and the risk of hypertension are shown in Fig. 3. We found that all types of pain were positively associated with the incidence of hypertension. The adjusted HRs (95% CIs) were 1.17 (1.14–1.19) for headache, 1.25 (1.17–1.33) for facial pain, 1.17 (1.15–1.19) for neck/shoulder pain, 1.19 (1.18–1.21) for back pain, 1.28 (1.25–1.32) for stomach/abdominal pain, 1.25 (1.23–1.27) for hip pain, 1.19 (1.17–1.20) for knee pain, and 1.44 (1.38–1.51) for pain all over the body. Sensitivity analyses showed no essential changes in the results for the association between specific pain and the risk of hypertension (see Supplemental Table 3).
Fig. 3.
Association between specific pain site and the risk of hypertension. Note: HR (95% CI) was adjusted for age, sex, race, index of multiple deprivation (IMD), smoking, drinking, sedentary time, body mass index, serum uric acid, creatinine, c-reactive protein, urinary sodium, and urinary potassium. HR, hazard ratio; CI, confidence interval; UK, United Kingdom
Discussion
In this study, we provided a comprehensive estimate of the associations of the number of pain sites and specific pain with risk of hypertension among UK adults. We found that the number of pain sites was positively associated with risk of hypertension after adjustment for multiple covariates including demographic, socioeconomic, lifestyle, and pathophysiological factors. The effect was not modified by age, sex, and follow-up durations according to the subgroup analysis. We additionally found that specific pain such as headache, neck/shoulder pain, and back pain were all separately associated with incident hypertension.
A few previous studies have explored the relationship between some specific pain and hypertension, and results from these studies are controversial. A prospective study in Norway found that high blood pressure was associated with a reduced risk of headache. Those with a SBP of 150 mmHg or higher had 30% lower risk of having headache compared with those with SBP lower than 140 mmHg [20]. A recent cross-sectional study conducted in US adults found that individuals who had severe headaches were associated with 25% higher odds of hypertension (OR: 1.25, 95% CI: 1.03–1.53) compared with those without severe headaches [21]. Al-Ghamdi et al.. conducted a cross-sectional survey in Al-Kharj, Saudi Arabia. They suggested a statistically significant relationship between hypertension and chronic pain defined as self-reported pain that lasts for three months or more [14]. However, a two-Sample Mendelian randomization (MR) study found no potential association between chronic pain and essential hypertension [22]. It should be noted that both the exposure (chronic pain) and the primary outcome (essential hypertension) in that MR analysis came from the UK Biobank. It is a significant methodological flaw in that it violates the requirement in MR analysis that the source population of exposure and outcome should not overlap [23].
Based on the UK Biobank cohort, our analysis observed positive associations of specific pain such as headache, facial pain, neck/shoulder pain, back pain, stomach/abdominal pain, hip pain, knee pain, and pain all over the body, with the incidence of hypertension during a long-term follow-up. As far as we know, there was no previous study has explored the association between the number of pain sites and the risk of hypertension. For the first time, the present study provides new evidence for a positive association between the number of pain sites and incident hypertension. This association remains unchanged even after excluding those with a diagnosis of cancer in the sensitivity analysis. These findings suggest the potential of the number of pain sites as an independent risk factor for hypertension.
Human pain is a multifaceted phenomenon, encompassing biological, psychological, and social dimensions that interact dynamically to shape individual experiences. At least 150 genes are known to be linked to chronic pain in humans. They contain genes from pathways that involve inflammation, the immune system, and stress, such as OPRM and COMT [24]. Chronic inflammation is one of the major insults that drive increased blood pressure. It evokes endothelial damage and dysfunction, ultimately leading to narrowing and stiffness of blood vessels [25]. While our analysis adjusted for CRP levels to account for systemic inflammation, the persistent association between chronic pain and hypertension underscores the need for nuanced interpretation. Immune cells secrete cytokines such as interleukin, interferon, and tumor necrosis factor, which affect the inflammatory reaction, oxidative stress, and kidney sodium water retention to participate in blood pressure regulation [26]. Emerging evidence from the neuro-immune interface highlights that pain modulation involves bidirectional signaling between glial cells and nociceptive neurons, driven by proinflammatory cytokines and damage-associated molecular patterns [27]. Stress acts by increasing system adrenergic tone which determines a reduction in the production of nitric oxide and induces the secretion of proinflammatory cytokines. When the adrenergic system is activated due to chronic stress or depression, it can lead to blood pressure elevation [28, 29]. Nevertheless, the exact mechanism underlying the association between chronic pain and hypertension still requires further investigation to elucidate.
Strengths and limitations
This study has several strengths. We investigated the association between chronic pain and risk of hypertension in a large population, which increased the generalizability of the results. In addition, a cohort study design with long-term follow-up increased the reliability of the results. Furthermore, we analyzed the relationship between the number of pain sites and hypertension, as well as the relationship between different specific types of pain and hypertension, which increased the versatility of the results. However, our study has limitations that should be addressed. First, ICD-10 codes were used to identify incident cases of hypertension from hospital inpatient records in the UK Biobank cohort, which may result in some mild cases that do not require hospitalization being missed, and this limitation is inherent to all hospital-based epidemiological studies of hypertension [30, 31]. Future work could integrate data of General Practitioner (GP) surgeries to quantify the extent of underascertainment and assess generalizability. Second, although we included multiple confounding factors, the possibility of residual confounding by unmeasured factors cannot be totally ruled out. Third, due to the observational nature of this study, we are unable to determine whether there is a causal relationship between pain and hypertension. As confirmed by Schoenfeld residual tests (age: p < 0.001; smoking status: p < 0.001; BMI: p < 0.001; uric acid: p < 0.001; creatinine: p < 0.001; CRP: p < 0.001), the effects of these covariates vary significantly over time. However, we conducted stratified Cox models by follow-up time (e.g., ≤ 5 years vs. >5 years) and observed consistent directional associations, which further confirms the reliability of the results.
In conclusion, the number of pain sites was associated with an increased risk of hypertension in UK adults. Certain specific types of pain, such as headache, neck/shoulder pain, and back pain, were also associated with an increased risk of hypertension. These findings indicate that chronic pain may act as an independent risk factor for incident hypertension, and it holds potential value for early detection of hypertension risk in the general population.
Supplementary Information
Below is the link to the electronic supplementary material.
Acknowledgements
We are thankful to the UK Biobank participants. This study was conducted with the UK Biobank Resource under project 129048.
Abbreviations
- BMI
Body mass index
- CI
Confidence interval
- CRP
C-reactive protein
- DBP
Diastolic blood pressure
- HR
Hazard ratio
- ICD-10
International classification of diseases tenth revision
- IMD
Index of multiple deprivation
- MR
Mendelian randomization
- NHANES
National health and nutrition examination survey
- OR
Odds ratio
- RAAS
Renin-angiotensin-aldosterone system
- RCS
Restricted cubic splines
- SBP
Systolic blood pressure
Author contributions
LZ and WT contributed to the study design. YC, FC, and LZ analyzed data and wrote the manuscript. WC, JL, JZ, and WT critically revised and edited the manuscript for important intellectual content. All authors approved the final version of the manuscript to be published. LZ had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
Funding
This study was supported by Sichuan Science and Technology Program (Grant Number: 2022YFS0604) and National Natural Science Foundation of China (Grant Number: 82300350).
Data availability
The data used in this study is available from application through approval and oversight by the UK Biobank Limited.
Declarations
Ethics approval and consent to participate
The North West Multi-centre Research Ethics Committee (MREC) approved the UK Biobank study (Reference: 21/NW/0157). The informed consent has been obtained from all participants.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Yu Chen and Fuli Chen contributed equally to this work.
Contributor Information
Wenjie Tian, Email: tianwenjie1976@hotmail.com.
Long Zhou, Email: zhoulong@med.uestc.edu.cn.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The data used in this study is available from application through approval and oversight by the UK Biobank Limited.