Hypertension in a Cohort of Swedish Middle-Aged Caucasian Men in the Automotive Industry: A 25-year Follow-Up Study on Cardiovascular Risk at Varying Blood Pressure Thresholds

Hypertension in a Cohort of Swedish Middle-Aged Caucasian Men in the Automotive Industry: A 25-year Follow-Up Study on Cardiovascular Risk at Varying Blood Pressure Thresholds | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Hypertension in a Cohort of Swedish Middle-Aged Caucasian Men in the Automotive Industry: A 25-year Follow-Up Study on Cardiovascular Risk at Varying Blood Pressure Thresholds Lennart Dimberg, Lala Joulha Ian This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6948995/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 3 You are reading this latest preprint version Abstract Background Hypertension is a well-recognized risk factor for cardiovascular disease, with various diagnostic guidelines established based on age and comorbidities. The European Society of Hypertension defines uncomplicated hypertension with a diagnostic threshold of 140/90 mmHg, whereas the American Heart Association recommends a lower threshold of 130/80 mmHg. Methods This study aims to investigate the relationship between these two thresholds (130/80 and 140/90 mmHg) and to evaluate the prognostic values of systolic blood pressure (SBP) and diastolic blood pressure (DBP). Data were collected in 1993 and 1998 from a cohort of 1,000 randomly selected male industrial workers from Swedish automotive companies, who underwent comprehensive nurse-led health examinations, work-related surveys and laboratory tests. Over a span of 25 years, we tracked incidents of first-time myocardial infarctions, strokes, and deaths were tracked using national registries. Statistical analyses included Kaplan-Meier curves and Cox proportional hazards ratios for composite cardiovascular outcomes of first-time myocardial infarction, stroke, and cardiovascular death. The analyses included multivariate analysis to account for potential confounders. The covariates included age, body mass index, marital status, clerical versus manual work, physical activity level, smoking habits, non-high density lipoprotein cholesterol, diabetes status, SBP and DBP. Results In 1998, 914 participants (91%) completed both assessments. The adjusted Cox proportional hazards ratios indicated a statistically significant hazard ratio for hypertension defined as ≥140/90 mmHg in the 1998 analyses, while the cutoff at 130/80 mmHg did not achieve statistical significance. Both SBP and DBP were significantly associated with the composite outcome after adjustment for covariates in separate models; however, the model with both SBP and DBP as linear predictors did not yield a significant p-value for DBP. Conclusions : Our findings do not support the adoption of a lower blood pressure threshold of 130/80 mmHg for this population of middle-aged working men. Both SBP and DBP strongly correlated with Spearman’s rho of 0.88 and demonstrated comparable prognostic value but only SBP reached significance when analyzed together. Redefining hypertension and lowering treatment targets could significantly reshape the epidemiological landscape by reclassifying people eligible for treatment. Nevertheless, the overall reduction in cardiovascular risk may be minimal. Hypertension cohort study middle-aged men mortality cardiovascular risk factors Figures Figure 1 Figure 2 Figure 3 Figure 4 Background Hypertension is one of the most significant modifiable risk factors for cardiovascular disease (CVD), largely due to its strong causal link and high prevalence ( 1 ). The concept of a “risk factor” was first introduced by Kannel et al. in 1957 during the Framingham study, which examined the impacts of cigarette smoking, cholesterol levels, and blood pressure on cardiovascular outcomes ( 2 ). Often referred to as the "silent killer," hypertension typically presents without symptoms, yet uncontrolled cases can lead to serious health complications or death. It is a major contributor to various cardiovascular conditions, including coronary artery disease, left ventricular hypertrophy, valvular heart disease, arrhythmias, stroke, and renal failure ( 3 ). Hypertension is a core component of modern cardiovascular risk assessment tools, such as the Framingham Risk Score and the European SCORE2 system ( 4 , 5 ). Over time, clinical thresholds for systolic (SBP) and diastolic blood pressure (DBP) have evolved. Due to the stronger correlation between SBP and cardiovascular risk, many predictive models prioritize SBP. A 2008 Swedish review reported that 27% of the adult population met the definition of hypertension—SBP ≥ 140 mmHg and/or DBP ≥ 90 mmHg ( 6 ) More recently, studies—sometimes supported by pharmaceutical funding—have advocated for lowering these thresholds to ≥ 130/80 mmHg, even for individuals without major comorbidities. This redefinition could classify approximately 50% of the Swedish adult population as hypertensive ( 7 ) Current guidelines reflect this divergence. The 2023 European Society of Hypertension (ESH) maintains a diagnostic threshold of ≥ 140/90 mmHg, while the 2017 American College of Cardiology/American Heart Association (ACC/AHA) guidelines recommend ≥ 130/80 mmHg, with treatment goals adjusted by age ( 8 , 9 ). The 2019 guidelines from the European Society of Cardiology (ESC) provide detailed recommendations for blood pressure management in patients with diabetes mellitus. They advocate a general target of < 140/90 mmHg, with additional age-specific goals designed to optimize outcomes based on individual risk profiles. For younger patients with diabetes, maintaining SBP between 120 and 130 mmHg is recommended to reduce the risk of cardiovascular events. In contrast, for individuals aged 65 and older, a slightly higher SBP target of 130 to 140 mmHg is considered more appropriate, reflecting the need to avoid potential adverse effects of overly aggressive treatment in this age group. Across all age groups, DBP should remain below 90 mmHg. These individualized targets aim to strike a balance between the benefits of blood pressure reduction and the potential harms associated with excessive lowering, particularly in older adults. Cardiovascular risk varies across different populations, with manual industrial workers facing increased risk due to exposure to shift work, noise, and chemicals ( 10 , 11 ). In 1992, a longitudinal study was initiated to compare cardiovascular risk factors among 1,000 randomly selected middle-aged Caucasian male workers from French and Swedish automotive companies. A baseline investigation was conducted in 1993, followed by a follow-up in 1998 ( 12 , 13 ). This report focuses on the Swedish cohort, which has been followed for cardiovascular events—myocardial infarction, stroke, and mortality—through national registries until 2023 as a composite endpoint. This study investigates the long-term relationship between office-measured systolic and diastolic blood pressure and the incidence of cardiovascular outcomes. Specifically, we aim to answer the following research questions: What is the strength of the association between systolic blood pressure and the composite clinical endpoint? What is the strength of the association between diastolic blood pressure and clinical endpoints? For this population, what is the strength of the diagnostic limit 140/90 respectively 130/80 and the composite clinical endpoint? Methods Study population In 1993, a cohort of 1,144 middle-aged men (aged 45–50 years) employed by the Volvo Corporation was randomly selected by occupational physicians using date-of-birth records ( 12 ). Of these, 144 individuals declined participation due to a lack of interest or long-term illness. A follow-up examination with similar procedures was conducted in 1998. Participants underwent a nurse-led health examination conducted by three nurses and one physiotherapist. They also completed a self-administered questionnaire that collected information on medical history, marital status, smoking habits, alcohol consumption, lifestyle, mental health, working conditions, stress levels, and frequency of exercise. Examinations were performed at two workplace locations: Gothenburg and Trollhättan, approximately 76 km apart. Variables Blood pressure and heart rate were measured in the supine position, as the average of three readings taken from the right arm after a 10-minute rest period. Measurements were obtained using a semi-automatic cuff (LIC Hygien) and D2 International (Hestia Pharm). Hypertension was defined as a SBP ≥ 140 mmHg and/or DBP ≥ 90 mmHg, current use of antihypertensive medication, or a combination of these criteria. Venous blood samples were collected after an overnight fast. Blood glucose was measured, and values ≥ 7.0 mmol/L or self-reported diabetes mellitus were classified as diabetes ( 14 ). Serum cholesterol, triglycerides, and high-density lipoprotein (HDL) were measured, while low-density lipoprotein (LDL) cholesterol was calculated. Non-HDL cholesterol was defined as total cholesterol minus HDL cholesterol; levels ≥ 6.0 mmol/L were considered high-risk according to SCORE2 guidelines ( 15 ). Body mass index (BMI) was calculated as weight in kilograms divided by the square of height in meters (kg/m²). Snoring and use of oral snuff were recorded as binary variables (yes/no). Smoking status was defined based on current smoking. Alcohol consumption was reported via questionnaire, and physical activity was categorized based on recommendations from the Public Health Agency of Sweden ( 16 ). Covariates The following covariates were included in the analysis: age (years), BMI (kg/m²), marital status, work type (mainly clerical vs. mainly manual), physical activity level (≥ 3 hours/week vs. <3 hours/week), SBP and DBP (mmHg), total cholesterol (mmol/L), non-HDL cholesterol (mmol/L), smoking, diabetes status, and fasting blood glucose (mmol/L). Endpoints Diagnoses of myocardial infarction (MI), stroke, and cause of death were classified using register data of codes from the International Classification of Diseases (ICD) ( 17 ). MI was diagnosed using ICD-9 codes 410 and ICD-10 codes I21-I32 from National Myocardial Infarction Registry, Swedeheart, while stroke was defined using ICD-10 codes I60-64 from the National Stroke Registry ( 18 , 19 ). Mortality data were sourced from the Swedish cause of death registry with ICD codes related to cardiovascular mortality, ICD codes I01-I99 ( 20 ). For detailed ICD codes related to cardiovascular mortality, see Table 1 . Table 1 Cardiovascular causes of death Cardiovascular causes of death (ICD-10 & ICD-9) Frequency I139- Hypertensive heart and chronic kidney disease 1 I219- Acute myocardial infarction 13 I251- Atherosclerotic heart disease 5 I269- Pulmonary embolism 1 I259- Chronic ischemic heart disease, unspecified 1 I350- Aortic (valve) stenosis 2 I509- Heart failure, unspecified 1 I619- Intracerebral hemorrhage, unspecified 1 I629- Intracranial hemorrhage (nontraumatic), unspecified 1 I710- Aortic dissection 2 I713- Ruptured aortic aneurysm 1 Total 29 Abbreviation: ICD, International Classification of Diseases. A visual design of the project is presented in Figure 1. Statistical methods The primary outcome was defined as the time to the first occurrence of stroke, myocardial infarction, or cardiovascular death. Participants were censored at the time of death from non-cardiovascular causes or at the end of the follow-up period (December 31, 2023), whichever came first. Time-to-event analyses were performed using the Kaplan–Meier estimator, with differences between groups assessed using the log-rank test. Cox proportional hazards models were used for both univariate and multivariable analyses to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). The proportional hazards assumption was evaluated using a global test (21). Covariates were modeled as either binary or continuous linear variables, depending on their distribution and measurement scale. Statistical significance was defined as a two-tailed p-value < 0.05. All analyses were conducted in R (version 4.4.1), using the survival package for Cox models (21). Correlations between systolic and diastolic blood pressure were assessed using Spearman’s rho, a non-parametric measure of rank correlation. The relationship between SBP and DBP was further examined using Deming regression to account for measurement error in both variables. Results A total of 914 individuals (91%) from the cohort had complete blood pressure data from both 1993 and 1998. Table 2 presents the distribution of participants based on hypertension thresholds of ≥140/90 mmHg and ≥130/80 mmHg in 1998, along with corresponding baseline data from 1993. A detailed summary of missing data is provided in Table S1 (Supplement). Participants classified as hypertensive using either threshold exhibited significantly higher rates of diabetes and elevated non-HDL cholesterol (total cholesterol minus HDL ≥6.0 mmol/L), among other risk factors. Between 1993 and 1998, the increase in systolic and diastolic blood pressure was approximately 50% greater in the ≥140/90 mmHg group compared to the ≥130/80 mmHg group. Cardiovascular (CV) mortality was approximately twice as high among individuals meeting the ≥130/80 mmHg threshold, and three times higher among those at or above the ≥140/90 mmHg cutoff, compared to participants below these thresholds. The incidence of composite cardiovascular events was slightly higher in the ≥130/80 group but nearly doubled in those meeting the ≥140/90 mmHg criteria. Table 2: Descriptive data of participants at baseline (1993) and blood-pressures (BP) in 1998 above (yes) and below (no) categorized by the 130/90 resp 140/90 cutoff. Characteristics include changes in systolic blood pressure (SBP) and diastolic blood pressure (DBP) between 1993 and 1998, along with associated covariates. BP ≥130/80 in 1998 BP ≥140/90 in 1998 Overall Characteristics Yes N = 656 No N = 258 Yes N = 322 No N=592 N=914 Systolic BP (mm Hg) in 1998 Median (Q1, Q3) 137 (127, 148) 116 (110, 121) 149 (142, 157) 123 (116,129) 129 (120,143) Diastolic BP (mm Hg) in1998 Median (Q1, Q3) 88 (84, 95) 75 (72, 77) 95 (91, 100) 81 (75, 84) 84 (79, 91) Change in Systolic BP (mm Hg) between 1998-1993 17 (10, 25) 9 (3, 15) 22 (14, 32) 12 (5,18 14 (7, 22) Change in Diastolic BP mm Hg) between 1998-1993 Median (Q1, Q3) 15 (6, 25) -1 (-8, 7) 21 (12, 32) 5 (-4, 14) 10 (0, 21) age 50 n, (%) 41 (6.3) 20 (7.8) 16 (5.0) 45 (7.6) 61 (6.7) 51 n, (%) 126 (19) 57 (22) 54 (17) 129 (22) 183 (20) 52 n, (%) 112 (17) 49 (19) 60 (19) 101 (17) 161 (18) 53 n, (%) 154 (23) 45 (17) 78 (24) 121 (20) 199 (22) 54 n, (%) 149 (23) 51 (20) 72 (22) 128 (22) 200 (22) 55 n, (%) 74 (11) 36 (14) 42 (13) 68 (11) 110 (12) BMI (kg/m2) Median (Q1, Q3) 25.9 (23.7, 28.1) 24.2 (22.3, 26.2) 26.5 (24.1, 28.7) 24.9 (22.9, 26.9) 25.4 (23.3, 27.7) BMI >= 30* n, (%) 88 (13) 6 (2.3) 57 (18) 37 (6.3) 94 (10) Snorers n, (%) 136 (21) 49 (19) 71 (22) 114 (19) 185 (20) Diabetes* n, (%) 32 (4.9) 1 (0.4) 19 (5.9) 14 (2.4) 33 (3.6) TotminusHDLC* (mmol/l) Median (Q1, Q3) 4.40 (3.78, 4.99) 4.01 (3.54, 4.57) 4.44 (3.78, 5.02) 4.22 (3.68, 4.83) 4.29 (3.72, 4.90) TotminusHDLC * >=6 n, (%) 27 (4.2) 6 (2.3) 16 (5.0) 17 (2.9) 33 (3.6) LDL-cholesterol (mmol/l) Median (Q1, Q3) 3.70 (3.15, 4.29) 3.51 (3.10, 3.96) 3.65 (3.16, 4.29) 3.60 (3.12, 4.15) 3.63 (3.13, 4.21) Married or cohabitant n, (%) 505 (77) 199 (77%) 254 (79) 450 (76) 704 (77) University education n, (%) 163 (26) 50 (20) 79 (25) 134 (23) 213 (24) Manual workers n, (%) 245 (38%) 99 (39) 344 (38%) 214 (37) 344 (38) Smokers* n, (%) 169 (26) 82 (32) 78 (24) 173 (29) 251 (27) Snuff users* n, (%) 74 (11) 27 (10) 43 (13) 58 (9.8) 101 (11) Alcohol (g/week) * Median (Q1, Q3) 39 (12, 72) 39 (0, 76) 39 (12, 71) 39 (6, 74) 39 (6, 73) Exercise (>3 hours/week), (%) 137 (21) 44 (18) 71 (23) 110 (19) 181 (20) first event cardiovascular death* n, (%) 24 (3.7) 5 (1.9) 19 (5.9) 10 (1.7) 29 (3.2) myocardial infarction n, (%) 67 (10) 28 (11) 44 (14) 51 (8.6) 95 (10) Stroke n, (%) 37 (5.6) 10 (3.9) 21 (6.5) 26 (4.4) 47 (5.1) censored (death) n, (%) 98 (15) 35 (14) 52 (16) 81 (14) 133 (15) Censored (study end) n, (%) 430 (66) 180 (70) 186 (58) 424 (72) 610 (67) Event (composed) n, (%) 128 (20) 43 (17) 84 (26) 87 (15) 171 (19) Abbreviation: n=number; Q1=first quartile; Q3 =third quartile; BP=blood pressure; LDL=low density lipoproteins; BMI: Body mass index; TotminusHDLC= Total cholesterol minus high density lipoprotein cholesterol *Definitions, see Methods Unadjusted Cox Proportional Hazards Analysis Unadjusted Cox proportional hazards (CoxPH) analysis revealed a statistically significant association between hypertension defined as ≥140/90 mmHg and the risk of cardiovascular events (Table 3) Table 3 Univariate Cox proportional hazards analysis comparing participants characteristics and risk of first myocardial infarction, stroke, or cardiovascular death over 25 years, whatever comes first. Blood pressure is measured in 1993 and 1998. Complete information was available for 864 out of 914 (95%) participants. N indicates the number of valid participants from which the variable is derived. Full sample Complete cases N=864 Characteristic N HR 95% CI p-value HR 95% CI p-value SBP>140|DBP>90 (mmHg) (1998) 914 1.96 1.45, 2.65 <0.001 1.93 1.42, 2.64 130|DBP>80 (mm Hg)(1998) 914 1.18 0.84, 1.67 0.3 1.19 0.83, 1.70 0.3 Systolic BP 1998 (10 mm Hg) 914 1.19 1.10, 1.28 <0.001 1.18 1.09, 1,27 <0.001 Diastolic BP 1998 (10 mm Hg) 914 1.23 1.08, 1.42 0.002 1.23 1.07, 1.42 0.003 Age (years) 914 1.15 1.03, 1.27 0.01 1.17 1.05, 1.31 0.004 Body mass index (kg/m2) 914 1.09 1.05, 1.14 <0.001 1.09 1.04, 1.14 = 30 914 1.65 1.09, 2.49 0.018 1.68 1.10, 2.56 0.016 Married or cohabitant 913 0.75 0.54, 1.06 0.11 0.73 0.52, 1.04 0.084 University education 890 0.97 0.68, 1.40 0.9 0.93 0.64, 1.35 0.7 Manual workers 899 1.61 1.19, 2.19 0.002 1.61 1.18, 2.19 0.003 Snorers* 911 1.30 0.92, 1.85 0.14 1.20 0.83, 1.74 0.3 Smokers* 914 2.05 1.51, 2.78 <0.001 2.06 1.50, 2.84 3 hours/week) 889 1.15 0.80, 1.64 0.5 1.16 0.81, 1.68 0.4 TotminusHDLC* (mmol/l) (Median, interquartile range 908 1.22 1.03, 1.44 0.021 1.23 1.04, 1.47 0.017 TotminusHDLC* (mmol/l) >=6 908 0.84 0.34, 2.05 0.7 0.87 0.36, 2.12 0.8 LDL-cholesterol (mmol/l) 912 1.19 0.99, 1.44 0.062 1.21 1.00, 1.47 0.05 Abbreviation: HR = Hazard Ratio; CI = Confidence Interval; p-value=probability value; mm Hg= millimeter mercury; n=number; LDL=low density lipoproteins; TotminusHDLC= Total cholesterol minus high density lipoprotein cholesterol *Definitions, see Methods Adjusted Cox Proportional Hazard Analysis In the adjusted CoxPH model, hypertension at ≥140/90 mmHg was associated with a statistically significant 83% increased hazard ratio (HR) for cardiovascular events (Table 4). In contrast, hypertension defined as ≥130/90 mmHg did not show a statistically significant HR. Significant covariates included body mass index (BMI), manual labor, smoking status, diabetes, and non-HDL cholesterol (total cholesterol minus HDL-C). Table 4 Cox proportional hazards analysis comparing participants with systolic and diastolic blood pressures measured in 1998, and risk of first myocardial infarction, stroke, or cardiovascular death over 25 years. Hypertension criteria ≥ 130/80 measured in 1998 Hypertension criteria ≥ 140/90 measured in 1998 Model N HR 95% CI P-value HR 95% CI p-value Univariate Cox PH full sample 914 1.18 0.84,1.67 0.3 1.96 1.42, 2.65 <0,001 Univariate Cox PH Complete cases 864 1.19 0.83, 1.70 0.3 1.93 1.42, 2.64 0,001 Mutually adjusted Cox PH Complete cases 864 0.97 0.66, 1.43 0.9 1.83 1.33, 2.54 <0,001 Abbreviation: HR = Hazard Ratio; CI = Confidence Interval; Cox PH=Cox proportional hazards; p-values=probability value; BMI=body mass index; SBP=systolic blood pressure; DBP=diastolic blood pressure; mgHg=milligram mercury, mmol/l=millimoles per liter; TotminusHDLC= Total cholesterol minus high density lipoprotein cholesterol *Definitions, see Methods Systolic versus diastolic blood pressure Table 5 demonstrates that, when adjusted for the covariates listed above, modeling SBP in 1998 as a continuous predictor was significantly associated with combined cardiovascular endpoints, with an adjusted hazard ratio (HR) of 1.22 per 10 mmHg increase. Similarly, DBP was associated with an HR of 1.20. However, in a model including both SBP and DBP, only the HR for SBP remained statistically significant (p = 0.039), whereas the association with DBP was not (p = 0.5). Table 5 Cox proportional hazards analysis comparing participants’ systolic and diastolic blood pressure (in 1998) and risk of first myocardial infarction, stroke, or cardiovascular death over 25 years, adjusted for covariates Systolic BP 1998 (per 10 mmHg) Diastolic BP (per 10 mmHg) Model N HR 95% CI p-value HR 95% CI p-value Univariate Cox PH full sample 914 1.19 1.10,1.28 <0.001 1.23 1.08, 1.42 <0.002 Univariate Cox PH Complete cases 864 1.18 1.09, 1.27 <0.001 1.23 1.07, 1.42 0.003 Mutually adjusted Cox PH Complete cases 864 1.22 1.01, 1.45 0.039 1.2 1.03, 1.39 0.025 Abbreviation: HR = Hazard Ratio; CI = Confidence Interval; Cox PH=Cox proportional hazards; p-value=probability value; BP=blood pressure; mm Hg= millimeter mercury; n=number. Adjustment for covariates age, BMI, married/cohabitant, snorers, smokers, snuff users, alcohol consumption, diabetes, exercise and total cholesterol minus high density lipoproteins A strong correlation between systolic and diastolic blood pressure measured in 1998 is demonstrated in Figure 2. Kaplan–Meier survival curves for the ≥130/80 mmHg group (Figure 3) did not show a statistically significant difference in cardiovascular events compared to those below this threshold. In contrast, individuals with blood pressure ≥140/90 mmHg exhibited a significantly higher incidence of cardiovascular events, with approximately a 10% absolute increase in event rate over the 25-year follow-up period (Figure 4). The cut-off 140/90 is highly significant over 23 years of observation, with about a 20% increase in cardiovascular events (Figure 4). This comprehensive analysis underscores the significant association between hypertension, particularly at the ≥140/90 mmHg threshold in 1998, and increased cardiovascular event risk. Additionally, it highlights the differential impact of key covariates on these outcomes. When systolic and diastolic blood pressure were analyzed concurrently, both systolic and diastolic pressure emerged as independent predictors of combined cardiovascular events. Discussion Our study shows that SBP is a better predictor of the composite cardiovascular outcome. Conditional on using SBP, as a predictor, DBP does not appear to provide additional information. As SBP and DBP are highly correlated, from a statistical standpoint there is little or no gain by including two variables. Extensive research, such as the Framingham Heart Study, has also underscored the stronger association between elevated systolic blood pressure and increased risks of stroke and heart disease. Notably, we found that the hypertension threshold of 130/80 mmHg did not significantly predict adverse cardiovascular outcomes. This challenges the prediction which is the basis for the 2017 guidelines from the American College of Cardiology and the American Heart Association, which lowered the diagnostic threshold for hypertension to ≥130 mmHg systolic and ≥80 mmHg diastolic (9). The substantial changes in the American hypertension guidelines were largely driven by the 2015 Systolic Blood Pressure Intervention Trial (SPRINT). This landmark trial demonstrated that intensive blood pressure control—targeting a systolic BP of less than 120 mmHg significantly reduced the incidence of major cardiovascular events and all-cause mortality in high-risk individuals without diabetes, compared to a standard target of less than 140 mmHg (22). A recent 2024 meta-analysis by Whelton and colleagues indicated that targeting a ´SBP of less than 130 mmHg is associated with a significant reduction in the risk of major cardiovascular events and all-cause mortality. Although adverse events were more common among participants in the intensive SBP target groups, the absolute risk of these events remained low, suggesting that the benefits of intensive blood pressure lowering outweigh the risks for most patients (23). In contrast, another large meta-analysis involving 47,991 individuals showed no significant cardiovascular benefit from intensive BP lowering among those with normal (<130/80) or high-normal (<140/90) blood pressure and low to moderate risk. However, among high-to-very high-risk individuals (n = 21,863), intensive treatment was associated with a striking 60% reduction in stroke risk (24). In line with our findings, the study by Flint et al. (2017), which analyzed 1.3 million adults, revealed that SBP was stronger associated with cardiovascular outcomes, although in contrast to our findings, both systolic and diastolic blood pressures were independently associated with cardiovascular risk (25). Furthermore, a 2019 study suggests that adopting the American hypertension guidelines could potentially double the number of individuals diagnosed with hypertension in Canada. This increase would primarily affect younger adults at low to moderate cardiovascular risk, leading to a rise in healthcare utilization and costs without clear evidence of clinical benefit. While intensive blood pressure control has shown clear advantages for high-risk patients, particularly those with comorbidities, the appropriateness of a universal threshold of 130/80 mmHg remains controversial. Reflecting this uncertainty, Canadian guidelines have deliberately opted not to adopt the lower threshold, citing a lack of sufficient supporting evidence (26). Strengths and weaknesses The original cohort was randomly selected from a well-defined population of male workers in the Swedish engineering industry and followed over 25 years. Participation rates were high, with minimal attrition. The nurses and health professionals involved were specifically trained, and standardized, validated procedures were employed throughout the study. Baseline data collection methods were carefully developed in accordance with prevailing guidelines, and outcome data were obtained from high-quality national registers, enhancing the validity of endpoint classification. As a result, the study’s internal validity is robust. The application of multiply adjusted Cox proportional hazards modeling further strengthens the credibility of the findings. The minimal difference in estimated HR between the unadjusted and adjusted results is indicative of minimal changes if other variables had been observed and included in the analysis. This assumes that the variables included are the most important confounders and that those that were omitted (unavailable) are less important. Participant compliance was notably high, facilitated by the convenience of conducting interviews and examinations at occupational clinics during working hours. Nonetheless, some limitations should be acknowledged. The impact of treatment of hypertension has not been monitored over the period. This is likely to reduce the hazard ratio of the group above 140/90 given that the Swedish guidelines have suggested this cutoff for treatment. No participant was exposed to a 130/80 treatment guideline. The national stroke registry (Riksstroke) only began in 1994 and did not achieve full national coverage until 1998, which may have led to underreporting of stroke events in the early years. Additionally, silent strokes and non-hospitalized myocardial infarctions may have gone undetected. The external validity of the study is limited, as the cohort consisted exclusively of middle-aged men employed in a specific industry in Sweden, which may restrict generalizability to other populations. Confounding factors and biases Several confounding factors may have influenced the findings of this study, particularly due to changes in participant behavior over the 25-year follow-up period. For example, some participants may have started or quit smoking, experienced fluctuations in blood pressure, initiated treatment for hypertension or hypercholesterolemia, modified their alcohol consumption, or undergone weight changes. Such variations could undermine the reliability of baseline data as predictors over time. Supporting this, a longitudinal Swedish study of 50-year-old men followed for 50 years documented secular trends in cardiovascular risk factors—including reduced smoking rates and cholesterol levels alongside increased BMI and more sedentary lifestyles—which likely apply to our cohort (27). Additionally, the widespread introduction of medications during the study period may have affected outcomes and prognosis. Potential biases also warrant consideration, especially concerning self-reported data, where underreporting of smoking and alcohol use is common. Although laboratory analyses were conducted in certified hospital facilities with quality control measures, calibration errors cannot be entirely excluded. Finally, despite efforts to minimize errors, data entry mistakes may have occurred, even with double-checking procedures by nursing staff. Conclusion DBP and SBP are significant when including them one at a time but adjusting for other covariates. Only SBP is significant when DBP and SBP and the covariates are all in one model. Our study found no evidence to support lowering the hypertension threshold from 140/90 mmHg to 130/80 mmHg in this cohort of relatively healthy, middle-aged men working in the engineering sector. Systolic and diastolic blood pressure and showed a similar significant association with cardiovascular outcomes. Redefining hypertension and lowering treatment targets could substantially alter the epidemiological landscape by reclassifying many low-risk individuals as hypertensive. While this would increase the number of people eligible for treatment, the overall reduction in cardiovascular risk might be minimal. Additionally, adopting these stricter guidelines could lead to increased healthcare resource utilization and costs, with unclear benefits. Abbreviations ACC/AHA American College of Cardiology/American Heart Association BMI Body mass index BP Blood pressure CI Confidence interval CoxPH Cox proportional hazards CV Cardiovascular CVD cardiovascular disease DBP diastolic blood pressure ESC European Society of Cardiology ESH European Society of Hypertension HRs Hazard ratios HDL-C High-density lipoprotein cholesterol ICD International classification of disease LDL Low-density lipoprotein MI Myocardial infarction P-Value Probability value SBP systolic blood pressure Declarations Ethical approval and informed consent This study was conducted under the principles outlined in the Declaration of Helsinki, obtaining written consent from the participants. The Research Ethics Committee of Gothenburg University approved the original study protocol on February 11, 1993 (Dnr. 23-93), with amendments approved on February 19, 2019. Additionally, applications to access data from the Swedeheart (myocardial infarctions), the national stroke, and death registries were also approved. This work was supported by the Volvo Research Fund and the Mary von Sydow Foundation. The authors declare no conflicts of interest. Consent for publication N/A All data is anonymized and cannot be attributed to a single person. The participants are informed about our findings through a website of the Coeur project. https://www.researchweb.org/is/vgr/project/278712 (accessed June 18, 2025). References Fuchs FD, Whelton PK. High blood pressure and cardiovascular disease. Hypertension . 2020;75(2):285-292. https://doi.org/10.1161/HYPERTENSIONAHA.119.14240 Kannel WB, Dawber TR, Kagan A, Revotskie N, Stokes J 3rd. Factors of risk in the development of coronary heart disease—six-year follow-up experience. The Framingham Study. Ann Intern Med . 1961;55:33-50. https://doi.org/10.7326/0003-4819-55-1-33 World Health Organization. Hypertension.https://www.who.int/news-room/fact-sheets/detail/hypertension. Accessed June 2, 2025. Anderson KM, Wilson PW, Odell PM, Kannel WB. An updated coronary risk profile. Circulation . 1991;83(1):356-362. SCORE2-OP Working Group and ESC Cardiovascular Risk Collaboration. SCORE2-OP risk prediction algorithms: estimating incident cardiovascular event risk in older persons in four geographical risk regions. Eur Heart J . 2021;42(25):2455-2467. https://doi.org/10.1093/eurheartj/ehab312 Swedish Council on Health Technology Assessment. Moderately Elevated Blood Pressure: A Systematic Review . Swedish Council on Health Technology Assessment; 2008. Report No. 170/1U.. https://www.sbu.se/en/publications/sbu-assesses/moderately-elevated-blood-pressure. Accessed February 5, 2025 Unger T, Borghi C, Charchar F, et al. 2020 International Society of Hypertension global hypertension practice guidelines. J Hypertens . 2020;38(6):982-1004. https://doi.org/10.1097/HJH.0000000000002453 Kreutz R, Brunström M, Burnier M, et al. 2024 European Society of Hypertension clinical practice guidelines for the management of arterial hypertension. Eur J Intern Med . 2024;126:1-15. https://doi.org/10.1016/j.ejim.2024.05.033 Whelton PK, Carey RM, Aronow WS, et al. 2017 ACC/AHA guideline for the prevention, detection, evaluation, and management of high blood pressure in adults. J Am Coll Cardiol . 2018;71:e127-e248. Tunstall-Pedoe H, Kuulasmaa K, Mahonen M, Tolonen H, Ruokokoski E, Amouyel P. Contribution of trends in survival and coronary-event rates to changes in coronary heart disease mortality: 10-year results from 37 WHO MONICA project populations. Lancet . 1999;353(9164):1547-1557. Hwang WJ, Hong O. Work-related cardiovascular disease risk factors using a socioecological approach: implications for practice and research. Eur J Cardiovasc Nurs . 2012;11(1):114-126. https://doi.org/10.1177/1474515111430890 Simon A, Dimberg L, Björntorp P, et al. Comparison of cardiovascular risk profile between male employees of two automotive companies in France and Sweden. The Coeur Project Group. Eur J Epidemiol . 1997;13(8):885-891. Dimberg L, Eriksson B, Hashem M. Myocardial infarction and death: findings from a 22-year follow-up of a cohort of 980 employed Swedish men. Public Health . 2019;175:148-155. https://doi.org/10.1016/j.puhe.2019.07.006 Cosentino F, Grant PJ, Aboyans V, et al. 2019 ESC guidelines on diabetes, pre-diabetes, and cardiovascular diseases developed in collaboration with the EASD. Eur Heart J . 2020;41(2):255-323. https://doi.org/10.1093/eurheartj/ehz486 SCORE2 Working Group and ESC Cardiovascular Risk Collaboration. SCORE2 risk prediction algorithms: new models to estimate 10-year risk of cardiovascular disease in Europe. Eur Heart J . 2021;42(25):2439-2454. https://doi.org/10.1093/eurheartj/ehab309 Folkhälsomyndigheten. Folkhälsomyndigheten. Recommendations for physical activity and sedentary behavior in 2023 (in Swedish).https://www.folkhalsomyndigheten.se/livsvillkor-levnadsvanor/mat-fysisk-aktivitet-overvikt-och-fetma/fysisk-aktivitet-och-stillasittande/riktlinjer-och-rekommendationer-for-fysisk-aktivitet-och-stillasittande/. Accessed June 2, 2025. World Health Organization. International classification of diseases.https://www.who.int/standards/classifications/classification-of-diseases. Accessed February 5, 2025. Jernberg T, Attebring MF, Hambraeus K, et al. The Swedish Web-system for enhancement and development of evidence-based care in heart disease evaluated according to recommended therapies (SWEDEHEART). Heart . 2010;96(20):1617-1621. Riksstroke. Annual report 2018.http://www.riksstroke.org/wp-content/uploads/2019/09/Riksstroke_Årsrapport-8_slutversion.pdf. Accessed September 7, 2020. Brooke HL, Talbäck M, Hornblad J, et al. The Swedish cause of death register. Eur J Epidemiol . 2017;32(9):765-773. Grambsch PM, Therneau TM. Proportional hazards tests and diagnostics based on weighted residuals. Biometrika . 1994;81(3):515-526. Wright JT, Williamson JD, Whelton PK, et al. A randomized trial of intensive versus standard blood-pressure control. N Engl J Med . 2015;373(22):2103-2116. https://doi.org/10.1056/NEJMoa1511939 Whelton PK, O’Connell S, Mills KT, He J. Optimal antihypertensive systolic blood pressure: a systematic review and meta-analysis. Hypertension . 2024;81(11):2329-2339. https://doi.org/10.1161/HYPERTENSIONAHA.124.23597 Thomopoulos C, Parati G, Zanchetti A. Effects of blood pressure-lowering treatment in individuals with high-normal and normal blood pressure: meta-analyses of randomized trials. J Hypertens . 2017;35(11):2150-2160. Flint AC, Conell C, Ren X, et al. Effect of systolic and diastolic blood pressure on cardiovascular outcomes. N Engl J Med . 2019;381(3):243-251. Garies S, Hao S, McBrien K, et al. Prevalence of hypertension, treatment, and blood pressure targets in Canada associated with the 2017 ACC/AHA guidelines. JAMA Netw Open . 2019;2(3):e190406. https://doi.org/10.1001/jamanetworkopen.2019.0406 Zhong Y, Rosengren A, Fu M, Welin L, Welin C, Caidahl K, Mandalenakis Z, Dellborg M, Svärdsudd K, Hansson PO. Secular changes in cardiovascular risk factors in Swedish 50-year-old men over a 50-year period: The study of men born in 1913, 1923, 1933, 1943, 1953 and 1963. Eur J Prev Cardiol. 2017 Apr;24(6):612-620. doi: 10.1177/2047487316676905. Epub 2016 Oct 28. PMID: 27794107. Additional Declarations No competing interests reported. Supplementary Files NISupplementhypertensionstudy20250616.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviewers invited by journal 08 Jul, 2025 Submission checks completed at journal 08 Jul, 2025 First submitted to journal 05 Jul, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6948995","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":482656824,"identity":"140c9bb7-f90c-44fc-9bd8-49145c1efe25","order_by":0,"name":"Lennart Dimberg","email":"data:image/png;base64,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","orcid":"","institution":"University of Gothenburg","correspondingAuthor":true,"prefix":"","firstName":"Lennart","middleName":"","lastName":"Dimberg","suffix":""},{"id":482656825,"identity":"20f6fdd6-f510-406c-8de0-74cd1e3d98de","order_by":1,"name":"Lala Joulha Ian","email":"","orcid":"","institution":"University of Gothenburg","correspondingAuthor":false,"prefix":"","firstName":"Lala","middleName":"Joulha","lastName":"Ian","suffix":""}],"badges":[],"createdAt":"2025-06-22 10:38:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6948995/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6948995/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":86503033,"identity":"b74d42c4-bfa5-450c-ac84-7f2b07a7cf7b","added_by":"auto","created_at":"2025-07-11 11:28:47","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":39790,"visible":true,"origin":"","legend":"\u003cp\u003eA visual design of the project.\u003c/p\u003e","description":"","filename":"image1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6948995/v1/c12462a11f4063f95c142425.jpg"},{"id":86503034,"identity":"3332c4ba-defd-4756-aff4-cf90b3b1e471","added_by":"auto","created_at":"2025-07-11 11:28:47","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":328136,"visible":true,"origin":"","legend":"\u003cp\u003eDepicts the correlation between systolic and diastolic blood pressures measured in 1998 and how they related to the specified cutoffs, showing a strong correlation.\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-6948995/v1/daecc5161949386c9c5da9b1.png"},{"id":86503035,"identity":"878b7311-e635-4bda-bf7b-6157abe5c0f1","added_by":"auto","created_at":"2025-07-11 11:28:47","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":205582,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan Meier curves of elevated blood pressure (BP) at 130/80 versus normal BP (measured in 1998) and association with cardiovascular events, see methods\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-6948995/v1/832887fd6bcdff187bbccd52.png"},{"id":86503630,"identity":"8959ba4b-b362-4f18-a82e-722e2da28c67","added_by":"auto","created_at":"2025-07-11 11:36:47","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":211444,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan Meier curves of elevated BP at 140/90 (measured in 1998) and association with cardiovascular events, see methods\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-6948995/v1/cc0145a25a01e52a0b17b802.png"},{"id":86504686,"identity":"9779bc7f-13b1-42b5-8686-92c2a174b1eb","added_by":"auto","created_at":"2025-07-11 11:44:49","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2329688,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6948995/v1/375e40e9-ec67-44ba-9187-92239ec11953.pdf"},{"id":86503629,"identity":"bb461186-783f-446c-8d99-400d376f85e3","added_by":"auto","created_at":"2025-07-11 11:36:47","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":32129,"visible":true,"origin":"","legend":"","description":"","filename":"NISupplementhypertensionstudy20250616.docx","url":"https://assets-eu.researchsquare.com/files/rs-6948995/v1/bc64f419bc884dedea1c3e22.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Hypertension in a Cohort of Swedish Middle-Aged Caucasian Men in the Automotive Industry: A 25-year Follow-Up Study on Cardiovascular Risk at Varying Blood Pressure Thresholds","fulltext":[{"header":"Background","content":"\u003cp\u003eHypertension is one of the most significant modifiable risk factors for cardiovascular disease (CVD), largely due to its strong causal link and high prevalence (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). The concept of a \u0026ldquo;risk factor\u0026rdquo; was first introduced by Kannel et al. in 1957 during the Framingham study, which examined the impacts of cigarette smoking, cholesterol levels, and blood pressure on cardiovascular outcomes (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eOften referred to as the \"silent killer,\" hypertension typically presents without symptoms, yet uncontrolled cases can lead to serious health complications or death. It is a major contributor to various cardiovascular conditions, including coronary artery disease, left ventricular hypertrophy, valvular heart disease, arrhythmias, stroke, and renal failure (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Hypertension is a core component of modern cardiovascular risk assessment tools, such as the Framingham Risk Score and the European SCORE2 system (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eOver time, clinical thresholds for systolic (SBP) and diastolic blood pressure (DBP) have evolved. Due to the stronger correlation between SBP and cardiovascular risk, many predictive models prioritize SBP. A 2008 Swedish review reported that 27% of the adult population met the definition of hypertension\u0026mdash;SBP\u0026thinsp;\u0026ge;\u0026thinsp;140 mmHg and/or DBP\u0026thinsp;\u0026ge;\u0026thinsp;90 mmHg (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e)\u003c/p\u003e\u003cp\u003eMore recently, studies\u0026mdash;sometimes supported by pharmaceutical funding\u0026mdash;have advocated for lowering these thresholds to \u0026ge;\u0026thinsp;130/80 mmHg, even for individuals without major comorbidities. This redefinition could classify approximately 50% of the Swedish adult population as hypertensive (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e)\u003c/p\u003e\u003cp\u003e Current guidelines reflect this divergence. The 2023 European Society of Hypertension (ESH) maintains a diagnostic threshold of \u0026ge;\u0026thinsp;140/90 mmHg, while the 2017 American College of Cardiology/American Heart Association (ACC/AHA) guidelines recommend\u0026thinsp;\u0026ge;\u0026thinsp;130/80 mmHg, with treatment goals adjusted by age (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e The 2019 guidelines from the European Society of Cardiology (ESC) provide detailed recommendations for blood pressure management in patients with diabetes mellitus. They advocate a general target of \u0026lt;\u0026thinsp;140/90 mmHg, with additional age-specific goals designed to optimize outcomes based on individual risk profiles. For younger patients with diabetes, maintaining SBP between 120 and 130 mmHg is recommended to reduce the risk of cardiovascular events. In contrast, for individuals aged 65 and older, a slightly higher SBP target of 130 to 140 mmHg is considered more appropriate, reflecting the need to avoid potential adverse effects of overly aggressive treatment in this age group. Across all age groups, DBP should remain below 90 mmHg. These individualized targets aim to strike a balance between the benefits of blood pressure reduction and the potential harms associated with excessive lowering, particularly in older adults.\u003c/p\u003e\u003cp\u003eCardiovascular risk varies across different populations, with manual industrial workers facing increased risk due to exposure to shift work, noise, and chemicals (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn 1992, a longitudinal study was initiated to compare cardiovascular risk factors among 1,000 randomly selected middle-aged Caucasian male workers from French and Swedish automotive companies. A baseline investigation was conducted in 1993, followed by a follow-up in 1998 (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). This report focuses on the Swedish cohort, which has been followed for cardiovascular events\u0026mdash;myocardial infarction, stroke, and mortality\u0026mdash;through national registries until 2023 as a composite endpoint.\u003c/p\u003e\u003cp\u003eThis study investigates the long-term relationship between office-measured systolic and diastolic blood pressure and the incidence of cardiovascular outcomes. Specifically, we aim to answer the following research questions:\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eWhat is the strength of the association between systolic blood pressure and the composite clinical endpoint?\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eWhat is the strength of the association between diastolic blood pressure and clinical endpoints?\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eFor this population, what is the strength of the diagnostic limit 140/90 respectively 130/80 and the composite clinical endpoint?\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cb\u003eStudy population\u003c/b\u003e\u003c/p\u003e\u003cp\u003eIn 1993, a cohort of 1,144 middle-aged men (aged 45\u0026ndash;50 years) employed by the Volvo Corporation was randomly selected by occupational physicians using date-of-birth records (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Of these, 144 individuals declined participation due to a lack of interest or long-term illness. A follow-up examination with similar procedures was conducted in 1998. Participants underwent a nurse-led health examination conducted by three nurses and one physiotherapist. They also completed a self-administered questionnaire that collected information on medical history, marital status, smoking habits, alcohol consumption, lifestyle, mental health, working conditions, stress levels, and frequency of exercise. Examinations were performed at two workplace locations: Gothenburg and Trollh\u0026auml;ttan, approximately 76 km apart.\u003c/p\u003e\u003cp\u003e\u003cb\u003eVariables\u003c/b\u003e\u003c/p\u003e\u003cp\u003eBlood pressure and heart rate were measured in the supine position, as the average of three readings taken from the right arm after a 10-minute rest period. Measurements were obtained using a semi-automatic cuff (LIC Hygien) and D2 International (Hestia Pharm). Hypertension was defined as a SBP\u0026thinsp;\u0026ge;\u0026thinsp;140 mmHg and/or DBP\u0026thinsp;\u0026ge;\u0026thinsp;90 mmHg, current use of antihypertensive medication, or a combination of these criteria.\u003c/p\u003e\u003cp\u003eVenous blood samples were collected after an overnight fast. Blood glucose was measured, and values\u0026thinsp;\u0026ge;\u0026thinsp;7.0 mmol/L or self-reported diabetes mellitus were classified as diabetes (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Serum cholesterol, triglycerides, and high-density lipoprotein (HDL) were measured, while low-density lipoprotein (LDL) cholesterol was calculated. Non-HDL cholesterol was defined as total cholesterol minus HDL cholesterol; levels\u0026thinsp;\u0026ge;\u0026thinsp;6.0 mmol/L were considered high-risk according to SCORE2 guidelines (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eBody mass index (BMI) was calculated as weight in kilograms divided by the square of height in meters (kg/m\u0026sup2;). Snoring and use of oral snuff were recorded as binary variables (yes/no). Smoking status was defined based on current smoking. Alcohol consumption was reported via questionnaire, and physical activity was categorized based on recommendations from the Public Health Agency of Sweden (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cb\u003eCovariates\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe following covariates were included in the analysis: age (years), BMI (kg/m\u0026sup2;), marital status, work type (mainly clerical vs. mainly manual), physical activity level (\u0026ge;\u0026thinsp;3 hours/week vs. \u0026lt;3 hours/week), SBP and DBP (mmHg), total cholesterol (mmol/L), non-HDL cholesterol (mmol/L), smoking, diabetes status, and fasting blood glucose (mmol/L).\u003c/p\u003e\u003cp\u003e\u003cb\u003eEndpoints\u003c/b\u003e\u003c/p\u003e\u003cp\u003eDiagnoses of myocardial infarction (MI), stroke, and cause of death were classified using register data of codes from the International Classification of Diseases (ICD) (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eMI was diagnosed using ICD-9 codes 410 and ICD-10 codes I21-I32 from National Myocardial Infarction Registry, Swedeheart, while stroke was defined using ICD-10 codes I60-64 from the National Stroke Registry (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eMortality data were sourced from the Swedish cause of death registry with ICD codes related to cardiovascular mortality, ICD codes I01-I99 (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). For detailed ICD codes related to cardiovascular mortality, see Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCardiovascular causes of death\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCardiovascular causes of death (ICD-10 \u0026amp; ICD-9)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFrequency\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eI139- Hypertensive heart and chronic kidney disease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eI219- Acute myocardial infarction\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eI251- Atherosclerotic heart disease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eI269- Pulmonary embolism\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eI259- Chronic ischemic heart disease, unspecified\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eI350- Aortic (valve) stenosis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eI509- Heart failure, unspecified\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eI619- Intracerebral hemorrhage, unspecified\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eI629- Intracranial hemorrhage (nontraumatic), unspecified\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eI710- Aortic dissection\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eI713- Ruptured aortic aneurysm\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e29\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\n\u003cp\u003eAbbreviation: ICD, International Classification of Diseases.\u003c/p\u003e\n\u003cp\u003eA visual design of the project is presented in Figure 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical methods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe primary outcome was defined as the time to the first occurrence of stroke, myocardial infarction, or cardiovascular death. Participants were censored at the time of death from non-cardiovascular causes or at the end of the follow-up period (December 31, 2023), whichever came first.\u003c/p\u003e\n\u003cp\u003eTime-to-event analyses were performed using the Kaplan\u0026ndash;Meier estimator, with differences between groups assessed using the log-rank test. Cox proportional hazards models were used for both univariate and multivariable analyses to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). The proportional hazards assumption was evaluated using a global test (21).\u003c/p\u003e\n\u003cp\u003eCovariates were modeled as either binary or continuous linear variables, depending on their distribution and measurement scale. Statistical significance was defined as a two-tailed p-value \u0026lt; 0.05.\u003c/p\u003e\n\u003cp\u003eAll analyses were conducted in R (version 4.4.1), using the \u003cstrong\u003esurvival\u003c/strong\u003e package for Cox models (21). Correlations between systolic and diastolic blood pressure were assessed using Spearman\u0026rsquo;s rho, a non-parametric measure of rank correlation. The relationship between SBP and DBP was further examined using Deming regression to account for measurement error in both variables.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 914 individuals (91%) from the cohort had complete blood pressure data from both 1993 and 1998. Table 2 presents the distribution of participants based on hypertension thresholds of \u0026ge;140/90 mmHg and \u0026ge;130/80 mmHg in 1998, along with corresponding baseline data from 1993. A detailed summary of missing data is provided in Table S1 (Supplement).\u003c/p\u003e\n\u003cp\u003eParticipants classified as hypertensive using either threshold exhibited significantly higher rates of diabetes and elevated non-HDL cholesterol (total cholesterol minus HDL \u0026ge;6.0 mmol/L), among other risk factors. Between 1993 and 1998, the increase in systolic and diastolic blood pressure was approximately 50% greater in the \u0026ge;140/90 mmHg group compared to the \u0026ge;130/80 mmHg group.\u003c/p\u003e\n\u003cp\u003eCardiovascular (CV) mortality was approximately twice as high among individuals meeting the \u0026ge;130/80 mmHg threshold, and three times higher among those at or above the \u0026ge;140/90 mmHg cutoff, compared to participants below these thresholds. The incidence of composite cardiovascular events was slightly higher in the \u0026ge;130/80 group but nearly doubled in those meeting the \u0026ge;140/90 mmHg criteria.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2: Descriptive data of participants at baseline (1993) and blood-pressures (BP) in 1998 above (yes) and below (no) categorized by the 130/90 resp 140/90 cutoff.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCharacteristics include changes in systolic blood pressure (SBP) and diastolic blood pressure (DBP) between 1993 and 1998, along with associated covariates.\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"756\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBP\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e\u0026ge;130/80 in 1998\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBP\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e\u0026ge;140/90 in 1998\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOverall\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003eYes\u003cbr\u003e\u0026nbsp;N = 656\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003eNo\u003cbr\u003e\u0026nbsp;N = 258\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003eYes\u003cbr\u003e\u0026nbsp;N = 322\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003cp\u003eN=592\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003eN=914\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003eSystolic BP (mm Hg) in 1998\u003c/p\u003e\n \u003cp\u003eMedian (Q1, Q3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e137 (127, 148)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e116 (110, 121)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e149 (142, 157)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e123 (116,129)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e129\u003c/p\u003e\n \u003cp\u003e(120,143)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003e\u0026nbsp;Diastolic BP (mm Hg) in1998\u003c/p\u003e\n \u003cp\u003eMedian (Q1, Q3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e88 (84, 95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e75 (72, 77)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e95 (91, 100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e81 (75, 84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e84 (79, 91)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003eChange in Systolic BP (mm Hg) between 1998-1993\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e17 (10, 25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e9 (3, 15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e22 (14, 32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e12 (5,18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e14 (7, 22)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003eChange in Diastolic BP mm Hg) between 1998-1993 Median (Q1, Q3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e15 (6, 25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e-1 (-8, 7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e21 (12, 32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e5 (-4, 14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e10 (0, 21)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003eage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003e50 n, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e41 (6.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e20 (7.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e16 (5.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e45 (7.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e61 (6.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003e51 n, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e126 (19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e57 (22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e54 (17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e129 (22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e183 (20)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003e52 n, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e112 (17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e49 (19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e60 (19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e101 (17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e161 (18)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003e53 n, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e154 (23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e45 (17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e78 (24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e121 (20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e199 (22)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003e54 n, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e149 (23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e51 (20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e72 (22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e128 (22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e200 (22)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003e55 n, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e74 (11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e36 (14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e42 (13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e68 (11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e110 (12)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003eBMI (kg/m2) Median (Q1, Q3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e25.9 (23.7, 28.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e24.2 (22.3, 26.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e26.5 (24.1, 28.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e24.9 (22.9, 26.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e25.4 (23.3, 27.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003eBMI \u0026gt;= 30* n, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e88 (13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e6 (2.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e57 (18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e37 (6.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e94 (10)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003eSnorers n, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e136 (21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e49 (19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e71 (22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e114 (19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e185 (20)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003eDiabetes* n, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e32 (4.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e1 (0.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e19 (5.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e14 (2.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e33 (3.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003eTotminusHDLC*\u003c/p\u003e\n \u003cp\u003e(mmol/l) Median (Q1, Q3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e4.40 (3.78, 4.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e4.01 (3.54, 4.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e4.44 (3.78, 5.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e4.22 (3.68, 4.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e4.29 (3.72, 4.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003eTotminusHDLC * \u0026gt;=6 n, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e27 (4.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e6 (2.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e16 (5.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e17 (2.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e33 (3.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003eLDL-cholesterol (mmol/l) Median (Q1, Q3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e3.70 (3.15, 4.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e3.51 (3.10, 3.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e3.65 (3.16, 4.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e3.60 (3.12, 4.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e3.63 (3.13, 4.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003eMarried or cohabitant n, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e505 (77)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e199 (77%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e254 (79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e450 (76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e704 (77)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003eUniversity education n, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e163 (26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e50 (20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e79 (25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e134 (23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e213 (24)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003eManual workers n, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e245 (38%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e99 (39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e344 (38%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e214 (37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e344 (38)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003eSmokers* n, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e169 (26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e82 (32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e78 (24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e173 (29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e251 (27)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003eSnuff users* n, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e74 (11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e27 (10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e43 (13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e58 (9.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e101 (11)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003eAlcohol (g/week) * Median (Q1, Q3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e39 (12, 72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e39 (0, 76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e39 (12, 71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e39 (6, 74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e39 (6, 73)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003eExercise (\u0026gt;3 hours/week), (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e137 (21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e44 (18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e71 (23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e110 (19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e181 (20)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003efirst event\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003ecardiovascular death* n, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e24 (3.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e5 (1.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e19 (5.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e10 (1.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e29 (3.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003emyocardial infarction n, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e67 (10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e28 (11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e44 (14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e51 (8.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e95 (10)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003eStroke n, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e37 (5.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e10 (3.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e21 (6.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e26 (4.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e47 (5.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003ecensored (death) n, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e98 (15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e35 (14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e52 (16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e81 (14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e133 (15)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003eCensored (study end) n, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e430 (66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e180 (70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e186 (58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e424 (72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e610 (67)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003eEvent (composed) n, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e128 (20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e43 (17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e84 (26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e87 (15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e171 (19)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviation: n=number; Q1=first quartile; Q3 =third quartile; BP=blood pressure; LDL=low density lipoproteins; BMI: Body mass index; TotminusHDLC= Total cholesterol minus high density lipoprotein cholesterol *Definitions, see Methods\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eUnadjusted Cox Proportional Hazards Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUnadjusted Cox proportional hazards (CoxPH) analysis revealed a statistically significant association between hypertension defined as \u0026ge;140/90 mmHg and the risk of cardiovascular events (Table 3)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eUnivariate Cox proportional hazards analysis comparing participants characteristics and risk of first myocardial infarction, stroke, or cardiovascular death over 25 years, whatever comes first. \u0026nbsp;Blood pressure is measured in 1993 and 1998. Complete information was available for 864 out of 914 (95%) participants. N indicates the number of valid participants from which the variable is derived.\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"654\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 260px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFull sample\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 209px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eComplete cases N=864\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eN\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003eSBP\u0026gt;140|DBP\u0026gt;90\u003c/p\u003e\n \u003cp\u003e(mmHg) (1998)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e914\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e1.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e1.45, 2.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e1.42, 2.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003eSBP\u0026gt;130|DBP\u0026gt;80 (mm Hg)(1998)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e914\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e1.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e0.84, 1.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.83, 1.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003eSystolic BP 1998 (10 mm Hg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e914\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e1.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e1.10, 1.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e1.09, 1,27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003eDiastolic BP 1998 (10 mm Hg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e914\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e1.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e1.08, 1.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e1.07, 1.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.003\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003eAge (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e914\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e1.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e1.03, 1.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.01\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e1.05, 1.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.004\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003eBody mass index (kg/m2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e914\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e1.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e1.05, 1.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e1.04, 1.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003eBody mass index (kg/m2) \u0026gt;= 30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e914\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e1.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e1.09, 2.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.018\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e1.10, 2.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.016\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003eMarried or cohabitant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e913\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e0.54, 1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.52, 1.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.084\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003eUniversity education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e890\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e0.68, 1.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.64, 1.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003eManual workers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e899\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e1.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e1.19, 2.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.61\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.18, 2.19\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.003\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003eSnorers*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e911\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e1.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e0.92, 1.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.83, 1.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003eSmokers*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e914\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e2.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e1.51, 2.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.06\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.50, 2.84\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003eSnuff users*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e914\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e0.50, 1.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.39, 1,23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003eAlcohol (per 10 g/week) *\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e889\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e0.98, 1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.98, 1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003eDiabetes*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e914\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e2.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e1.24, 4.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.008\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e2.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e1.12, 3.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.02\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003eExercise (\u0026gt;3 hours/week)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e889\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e1.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e0.80, 1.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.81, 1.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003eTotminusHDLC*\u003c/p\u003e\n \u003cp\u003e(mmol/l)\u003c/p\u003e\n \u003cp\u003e(Median, interquartile range\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e908\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e1.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e1.03, 1.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.021\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e1.04, 1.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.017\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003eTotminusHDLC*\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(mmol/l) \u0026gt;=6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e908\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e0.34, 2.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.36, 2.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003eLDL-cholesterol (mmol/l)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e912\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e1.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e0.99, 1.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.062\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e1.00, 1.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviation: HR = Hazard Ratio; CI = Confidence Interval; p-value=probability value; mm Hg= millimeter mercury; n=number; LDL=low density lipoproteins; TotminusHDLC= Total cholesterol minus high density lipoprotein cholesterol *Definitions, see Methods\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAdjusted Cox Proportional Hazard Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the adjusted CoxPH model, hypertension at \u0026ge;140/90 mmHg was associated with a statistically significant 83% increased hazard ratio (HR) for cardiovascular events (Table 4). In contrast, hypertension defined as \u0026ge;130/90 mmHg did not show a statistically significant HR. Significant covariates included body mass index (BMI), manual labor, smoking status, diabetes, and non-HDL cholesterol (total cholesterol minus HDL-C).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eCox proportional hazards analysis comparing participants with systolic and diastolic blood pressures measured in 1998, and risk of first myocardial infarction, stroke, or cardiovascular death over 25 years.\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"618\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 261px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHypertension criteria\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026ge;\u003cstrong\u003e130/80 measured in 1998\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 220px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHypertension criteria\u0026nbsp;\u003c/strong\u003e\u0026ge;\u003cstrong\u003e140/90 measured in 1998\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eN\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 80px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003col\u003e\n \u003cli\u003eUnivariate Cox PH full sample\u0026nbsp;\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e914\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.84,1.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e1.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e1.42, 2.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 80px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0,001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003col start=\"2\"\u003e\n \u003cli\u003eUnivariate Cox PH Complete cases\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e864\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.83, 1.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e1.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e1.42, 2.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 80px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003col start=\"3\"\u003e\n \u003cli\u003eMutually adjusted Cox PH Complete cases\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e864\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.66, 1.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e1.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e1.33, 2.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 80px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0,001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviation: HR = Hazard Ratio; CI = Confidence Interval;\u0026nbsp;Cox PH=Cox proportional hazards;\u0026nbsp;p-values=probability value;\u0026nbsp;BMI=body mass index; SBP=systolic blood pressure; DBP=diastolic blood pressure; mgHg=milligram mercury, mmol/l=millimoles per liter; TotminusHDLC= Total cholesterol minus high density lipoprotein cholesterol\u003c/p\u003e\n\u003cp\u003e*Definitions, see Methods\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSystolic versus diastolic blood pressure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 5 demonstrates that, when adjusted for the covariates listed above, modeling SBP in 1998 as a continuous predictor was significantly associated with combined cardiovascular endpoints, with an adjusted hazard ratio (HR) of 1.22 per 10 mmHg increase. Similarly, DBP was associated with an HR of 1.20.\u003c/p\u003e\n\u003cp\u003eHowever, in a model including both SBP and DBP, only the HR for SBP remained statistically significant (p = 0.039), whereas the association with DBP was not (p = 0.5).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eCox proportional hazards analysis comparing participants\u0026rsquo; systolic and diastolic\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eblood pressure (in 1998) and risk of first myocardial infarction, stroke, or cardiovascular death over 25 years, adjusted for covariates\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"614\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 261px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSystolic BP 1998 (per 10 mmHg)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiastolic BP (per 10 mmHg)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eN\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003col\u003e\n \u003cli\u003eUnivariate Cox PH full sample\u0026nbsp;\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e914\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e1.10,1.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e1.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e1.08, 1.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003col start=\"2\"\u003e\n \u003cli\u003eUnivariate Cox PH Complete cases\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e864\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e1.09, 1.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e1.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e1.07, 1.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.003\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003col start=\"3\"\u003e\n \u003cli\u003eMutually adjusted Cox PH Complete cases\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e864\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e1.01, 1.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.039\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e1.03, 1.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.025\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviation: HR = Hazard Ratio; CI = Confidence Interval; Cox PH=Cox proportional hazards; p-value=probability value; BP=blood pressure; mm Hg= millimeter mercury; n=number.\u003c/p\u003e\n\u003cp\u003eAdjustment for covariates age, BMI, married/cohabitant, snorers, smokers, snuff users, alcohol consumption, diabetes, exercise and total cholesterol minus high density lipoproteins\u003c/p\u003e\n\u003cp\u003eA strong correlation between systolic and diastolic blood pressure measured in 1998 is demonstrated in Figure 2.\u003c/p\u003e\n\u003cp\u003eKaplan\u0026ndash;Meier survival curves for the \u0026ge;130/80 mmHg group (Figure 3) did not show a statistically significant difference in cardiovascular events compared to those below this threshold.\u003c/p\u003e\n\u003cp\u003eIn contrast, individuals with blood pressure \u0026ge;140/90 mmHg exhibited a significantly higher incidence of cardiovascular events, with approximately a 10% absolute increase in event rate over the 25-year follow-up period (Figure 4).\u003c/p\u003e\n\u003cp\u003eThe cut-off 140/90 is highly significant over 23 years of observation, with about a 20% increase in cardiovascular events (Figure 4).\u003c/p\u003e\n\u003cp\u003eThis comprehensive analysis underscores the significant association between hypertension, particularly at the \u0026ge;140/90 mmHg threshold in 1998, and increased cardiovascular event risk. Additionally, it highlights the differential impact of key covariates on these outcomes. When systolic and diastolic blood pressure were analyzed concurrently, both systolic and diastolic pressure emerged as independent predictors of combined cardiovascular events.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur study shows that SBP is a better predictor of the composite cardiovascular outcome. Conditional on using SBP, as a predictor, DBP does not appear to provide additional information. As SBP and DBP are highly correlated, from a statistical standpoint there is little or no gain by including two variables. Extensive research, such as the Framingham Heart Study, has also underscored the stronger association between elevated systolic blood pressure and increased risks of stroke and heart disease. Notably, we found that the hypertension threshold of 130/80 mmHg did not significantly predict adverse cardiovascular outcomes. This challenges the prediction which is the basis for the 2017 guidelines from the American College of Cardiology and the American Heart Association, which lowered the diagnostic threshold for hypertension to \u0026ge;130 mmHg systolic and \u0026ge;80 mmHg diastolic (9).\u003c/p\u003e\n\u003cp\u003eThe substantial changes in the American hypertension guidelines were largely driven by the 2015 Systolic Blood Pressure Intervention Trial (SPRINT). This landmark trial demonstrated that intensive blood pressure control\u0026mdash;targeting a systolic BP of less than 120 mmHg significantly reduced the incidence of major cardiovascular events and all-cause mortality in high-risk individuals without diabetes, compared to a standard target of less than 140 mmHg (22).\u003c/p\u003e\n\u003cp\u003eA recent 2024 meta-analysis by Whelton and colleagues indicated that targeting a \u0026acute;SBP of less than 130 mmHg is associated with a significant reduction in the risk of major cardiovascular events and all-cause mortality. Although adverse events were more common among participants in the intensive SBP target groups, the absolute risk of these events remained low, suggesting that the benefits of intensive blood pressure lowering outweigh the risks for most patients (23).\u003c/p\u003e\n\u003cp\u003eIn contrast, another large meta-analysis involving 47,991 individuals showed no significant cardiovascular benefit from intensive BP lowering among those with normal (\u0026lt;130/80) or high-normal (\u0026lt;140/90) blood pressure and low to moderate risk. However, among high-to-very high-risk individuals (n = 21,863), intensive treatment was associated with a striking 60% reduction in stroke risk (24).\u003c/p\u003e\n\u003cp\u003eIn line with our findings, the study by Flint et al. (2017), which analyzed 1.3 million adults, revealed that SBP was stronger associated with cardiovascular outcomes, although in contrast to our findings, both systolic and diastolic blood pressures were independently associated with cardiovascular risk (25).\u003c/p\u003e\n\u003cp\u003eFurthermore, a 2019 study suggests that adopting the American hypertension guidelines could potentially double the number of individuals diagnosed with hypertension in Canada. This increase would primarily affect younger adults at low to moderate cardiovascular risk, leading to a rise in healthcare utilization and costs without clear evidence of clinical benefit. While intensive blood pressure control has shown clear advantages for high-risk patients, particularly those with comorbidities, the appropriateness of a universal threshold of 130/80 mmHg remains controversial. Reflecting this uncertainty, Canadian guidelines have deliberately opted not to adopt the lower threshold, citing a lack of sufficient supporting evidence (26).\u003c/p\u003e\n\u003ch3\u003eStrengths and weaknesses\u003c/h3\u003e\n\u003cp\u003eThe original cohort was randomly selected from a well-defined population of male workers in the Swedish engineering industry and followed over 25 years. Participation rates were high, with minimal attrition. The nurses and health professionals involved were specifically trained, and standardized, validated procedures were employed throughout the study. Baseline data collection methods were carefully developed in accordance with prevailing guidelines, and outcome data were obtained from high-quality national registers, enhancing the validity of endpoint classification. As a result, the study\u0026rsquo;s internal validity is robust.\u003c/p\u003e\n\u003cp\u003eThe application of multiply adjusted Cox proportional hazards modeling further strengthens the credibility of the findings. The minimal difference in estimated HR between the unadjusted and adjusted results is indicative of minimal changes if other variables had been observed and included in the analysis. This assumes that the variables included are the most important confounders and that those that were omitted (unavailable) are less important. Participant compliance was notably high, facilitated by the convenience of conducting interviews and examinations at occupational clinics during working hours.\u003c/p\u003e\n\u003cp\u003eNonetheless, some limitations should be acknowledged. The impact of treatment of hypertension has not been monitored over the period. This is likely to reduce the hazard ratio of the group above 140/90 given that the Swedish guidelines have suggested this cutoff for treatment. No participant was exposed to a 130/80 treatment guideline.\u003c/p\u003e\n\u003cp\u003eThe national stroke registry (Riksstroke) only began in 1994 and did not achieve full national coverage until 1998, which may have led to underreporting of stroke events in the early years. Additionally, silent strokes and non-hospitalized myocardial infarctions may have gone undetected. The external validity of the study is limited, as the cohort consisted exclusively of middle-aged men employed in a specific industry in Sweden, which may restrict generalizability to other populations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConfounding factors and biases\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSeveral confounding factors may have influenced the findings of this study, particularly due to changes in participant behavior over the 25-year follow-up period. For example, some participants may have started or quit smoking, experienced fluctuations in blood pressure, initiated treatment for hypertension or hypercholesterolemia, modified their alcohol consumption, or undergone weight changes. Such variations could undermine the reliability of baseline data as predictors over time. Supporting this, a longitudinal Swedish study of 50-year-old men followed for 50 years documented secular trends in cardiovascular risk factors\u0026mdash;including reduced smoking rates and cholesterol levels alongside increased BMI and more sedentary lifestyles\u0026mdash;which likely apply to our cohort (27). Additionally, the widespread introduction of medications during the study period may have affected outcomes and prognosis.\u003c/p\u003e\n\u003cp\u003ePotential biases also warrant consideration, especially concerning self-reported data, where underreporting of smoking and alcohol use is common. Although laboratory analyses were conducted in certified hospital facilities with quality control measures, calibration errors cannot be entirely excluded. Finally, despite efforts to minimize errors, data entry mistakes may have occurred, even with double-checking procedures by nursing staff.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eDBP and SBP are significant when including them one at a time but adjusting for other covariates. Only SBP is significant when DBP and SBP and the covariates are all in one model. Our study found no evidence to support lowering the hypertension threshold from 140/90 mmHg to 130/80 mmHg in this cohort of relatively healthy, middle-aged men working in the engineering sector. Systolic and diastolic blood pressure and showed a similar significant association with cardiovascular outcomes. Redefining hypertension and lowering treatment targets could substantially alter the epidemiological landscape by reclassifying many low-risk individuals as hypertensive. While this would increase the number of people eligible for treatment, the overall reduction in cardiovascular risk might be minimal. Additionally, adopting these stricter guidelines could lead to increased healthcare resource utilization and costs, with unclear benefits.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eACC/AHA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAmerican College of Cardiology/American Heart Association\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eBMI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eBody mass index\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eBP\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eBlood pressure\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eConfidence interval\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCoxPH\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eCox proportional hazards\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCV\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eCardiovascular\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCVD\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ecardiovascular disease\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eDBP\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ediastolic blood pressure\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eESC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eEuropean Society of Cardiology\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eESH\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eEuropean Society of Hypertension\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eHRs\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eHazard ratios\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eHDL-C\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eHigh-density lipoprotein cholesterol\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eICD\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eInternational classification of disease\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eLDL\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eLow-density lipoprotein\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eMI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eMyocardial infarction\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eP-Value\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eProbability value\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eSBP\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003esystolic blood pressure\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical approval and informed consent\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted under the principles outlined in the Declaration of Helsinki, obtaining written consent from the participants. The Research Ethics Committee of Gothenburg University approved the original study protocol on February 11, 1993 (Dnr. 23-93), with amendments approved on February 19, 2019.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAdditionally, applications to access data from the Swedeheart (myocardial infarctions), the national stroke, and death registries were also approved.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Volvo Research Fund and the Mary von Sydow Foundation. The authors declare no conflicts of interest.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eN/A\u003c/p\u003e\n\u003cp\u003eAll data is anonymized and cannot be attributed to a single person. The participants are informed about our findings through a website of the Coeur project. https://www.researchweb.org/is/vgr/project/278712 (accessed June 18, 2025).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eFuchs FD, Whelton PK. High blood pressure and cardiovascular disease.\u0026nbsp;\u003cem\u003eHypertension\u003c/em\u003e. 2020;75(2):285-292. https://doi.org/10.1161/HYPERTENSIONAHA.119.14240\u003c/li\u003e\n \u003cli\u003eKannel WB, Dawber TR, Kagan A, Revotskie N, Stokes J 3rd. Factors of risk in the development of coronary heart disease\u0026mdash;six-year follow-up experience. The Framingham Study.\u0026nbsp;\u003cem\u003eAnn Intern Med\u003c/em\u003e. 1961;55:33-50. https://doi.org/10.7326/0003-4819-55-1-33\u003c/li\u003e\n \u003cli\u003eWorld Health Organization. Hypertension.https://www.who.int/news-room/fact-sheets/detail/hypertension. Accessed June 2, 2025.\u003c/li\u003e\n \u003cli\u003eAnderson KM, Wilson PW, Odell PM, Kannel WB. An updated coronary risk profile.\u0026nbsp;\u003cem\u003eCirculation\u003c/em\u003e. 1991;83(1):356-362.\u003c/li\u003e\n \u003cli\u003eSCORE2-OP Working Group and ESC Cardiovascular Risk Collaboration. SCORE2-OP risk prediction algorithms: estimating incident cardiovascular event risk in older persons in four geographical risk regions.\u0026nbsp;\u003cem\u003eEur Heart J\u003c/em\u003e. 2021;42(25):2455-2467. https://doi.org/10.1093/eurheartj/ehab312\u003c/li\u003e\n \u003cli\u003eSwedish Council on Health Technology Assessment.\u0026nbsp;\u003cem\u003eModerately Elevated Blood Pressure: A Systematic Review\u003c/em\u003e. Swedish Council on Health Technology Assessment; 2008. Report No. 170/1U.. https://www.sbu.se/en/publications/sbu-assesses/moderately-elevated-blood-pressure. Accessed February 5, 2025\u003c/li\u003e\n \u003cli\u003eUnger T, Borghi C, Charchar F, et al. 2020 International Society of Hypertension global hypertension practice guidelines.\u0026nbsp;\u003cem\u003eJ Hypertens\u003c/em\u003e. 2020;38(6):982-1004. https://doi.org/10.1097/HJH.0000000000002453\u003c/li\u003e\n \u003cli\u003eKreutz R, Brunström M, Burnier M, et al. 2024 European Society of Hypertension clinical practice guidelines for the management of arterial hypertension.\u0026nbsp;\u003cem\u003eEur J Intern Med\u003c/em\u003e. 2024;126:1-15. https://doi.org/10.1016/j.ejim.2024.05.033\u003c/li\u003e\n \u003cli\u003eWhelton PK, Carey RM, Aronow WS, et al. 2017 ACC/AHA guideline for the prevention, detection, evaluation, and management of high blood pressure in adults.\u0026nbsp;\u003cem\u003eJ Am Coll Cardiol\u003c/em\u003e. 2018;71:e127-e248.\u003c/li\u003e\n \u003cli\u003eTunstall-Pedoe H, Kuulasmaa K, Mahonen M, Tolonen H, Ruokokoski E, Amouyel P. Contribution of trends in survival and coronary-event rates to changes in coronary heart disease mortality: 10-year results from 37 WHO MONICA project populations.\u0026nbsp;\u003cem\u003eLancet\u003c/em\u003e. 1999;353(9164):1547-1557.\u003c/li\u003e\n \u003cli\u003eHwang WJ, Hong O. Work-related cardiovascular disease risk factors using a socioecological approach: implications for practice and research.\u0026nbsp;\u003cem\u003eEur J Cardiovasc Nurs\u003c/em\u003e. 2012;11(1):114-126. https://doi.org/10.1177/1474515111430890\u003c/li\u003e\n \u003cli\u003eSimon A, Dimberg L, Björntorp P, et al. Comparison of cardiovascular risk profile between male employees of two automotive companies in France and Sweden. The Coeur Project Group.\u0026nbsp;\u003cem\u003eEur J Epidemiol\u003c/em\u003e. 1997;13(8):885-891.\u003c/li\u003e\n \u003cli\u003eDimberg L, Eriksson B, Hashem M. Myocardial infarction and death: findings from a 22-year follow-up of a cohort of 980 employed Swedish men.\u0026nbsp;\u003cem\u003ePublic Health\u003c/em\u003e. 2019;175:148-155. https://doi.org/10.1016/j.puhe.2019.07.006\u003c/li\u003e\n \u003cli\u003eCosentino F, Grant PJ, Aboyans V, et al. 2019 ESC guidelines on diabetes, pre-diabetes, and cardiovascular diseases developed in collaboration with the EASD.\u0026nbsp;\u003cem\u003eEur Heart J\u003c/em\u003e. 2020;41(2):255-323. https://doi.org/10.1093/eurheartj/ehz486\u003c/li\u003e\n \u003cli\u003eSCORE2 Working Group and ESC Cardiovascular Risk Collaboration. SCORE2 risk prediction algorithms: new models to estimate 10-year risk of cardiovascular disease in Europe.\u0026nbsp;\u003cem\u003eEur Heart J\u003c/em\u003e. 2021;42(25):2439-2454. https://doi.org/10.1093/eurheartj/ehab309\u003c/li\u003e\n \u003cli\u003eFolkh\u0026auml;lsomyndigheten. Folkh\u0026auml;lsomyndigheten. Recommendations for physical activity and sedentary behavior in 2023 (in Swedish).https://www.folkhalsomyndigheten.se/livsvillkor-levnadsvanor/mat-fysisk-aktivitet-overvikt-och-fetma/fysisk-aktivitet-och-stillasittande/riktlinjer-och-rekommendationer-for-fysisk-aktivitet-och-stillasittande/. Accessed June 2, 2025.\u003c/li\u003e\n \u003cli\u003eWorld Health Organization. International classification of diseases.https://www.who.int/standards/classifications/classification-of-diseases. Accessed February 5, 2025.\u003c/li\u003e\n \u003cli\u003eJernberg T, Attebring MF, Hambraeus K, et al. The Swedish Web-system for enhancement and development of evidence-based care in heart disease evaluated according to recommended therapies (SWEDEHEART).\u0026nbsp;\u003cem\u003eHeart\u003c/em\u003e. 2010;96(20):1617-1621.\u003c/li\u003e\n \u003cli\u003eRiksstroke. Annual report 2018.http://www.riksstroke.org/wp-content/uploads/2019/09/Riksstroke_Årsrapport-8_slutversion.pdf. Accessed September 7, 2020.\u003c/li\u003e\n \u003cli\u003eBrooke HL, Talbäck M, Hornblad J, et al. The Swedish cause of death register.\u0026nbsp;\u003cem\u003eEur J Epidemiol\u003c/em\u003e. 2017;32(9):765-773.\u003c/li\u003e\n \u003cli\u003eGrambsch PM, Therneau TM. Proportional hazards tests and diagnostics based on weighted residuals.\u0026nbsp;\u003cem\u003eBiometrika\u003c/em\u003e. 1994;81(3):515-526.\u003c/li\u003e\n \u003cli\u003eWright JT, Williamson JD, Whelton PK, et al. A randomized trial of intensive versus standard blood-pressure control.\u0026nbsp;\u003cem\u003eN Engl J Med\u003c/em\u003e. 2015;373(22):2103-2116. https://doi.org/10.1056/NEJMoa1511939\u003c/li\u003e\n \u003cli\u003eWhelton PK, O\u0026rsquo;Connell S, Mills KT, He J. Optimal antihypertensive systolic blood pressure: a systematic review and meta-analysis.\u0026nbsp;\u003cem\u003eHypertension\u003c/em\u003e. 2024;81(11):2329-2339. https://doi.org/10.1161/HYPERTENSIONAHA.124.23597\u003c/li\u003e\n \u003cli\u003eThomopoulos C, Parati G, Zanchetti A. Effects of blood pressure-lowering treatment in individuals with high-normal and normal blood pressure: meta-analyses of randomized trials.\u0026nbsp;\u003cem\u003eJ Hypertens\u003c/em\u003e. 2017;35(11):2150-2160.\u003c/li\u003e\n \u003cli\u003eFlint AC, Conell C, Ren X, et al. Effect of systolic and diastolic blood pressure on cardiovascular outcomes.\u0026nbsp;\u003cem\u003eN Engl J Med\u003c/em\u003e. 2019;381(3):243-251.\u003c/li\u003e\n \u003cli\u003eGaries S, Hao S, McBrien K, et al. Prevalence of hypertension, treatment, and blood pressure targets in Canada associated with the 2017 ACC/AHA guidelines.\u0026nbsp;\u003cem\u003eJAMA Netw Open\u003c/em\u003e. 2019;2(3):e190406. https://doi.org/10.1001/jamanetworkopen.2019.0406\u003c/li\u003e\n \u003cli\u003eZhong Y, Rosengren A, Fu M, Welin L, Welin C, Caidahl K, Mandalenakis Z, Dellborg M, Sv\u0026auml;rdsudd K, Hansson PO. Secular changes in cardiovascular risk factors in Swedish 50-year-old men over a 50-year period: The study of men born in 1913, 1923, 1933, 1943, 1953 and 1963. Eur J Prev Cardiol. 2017 Apr;24(6):612-620. doi: 10.1177/2047487316676905. Epub 2016 Oct 28. PMID: 27794107.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"the-egyptian-heart-journal","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"tehj","sideBox":"Learn more about [The Egyptian Heart Journal](https://tehj.springeropen.com)","snPcode":"43044","submissionUrl":"https://submission.springernature.com/new-submission/43044/3","title":"The Egyptian Heart Journal","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Open","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Hypertension, cohort study, middle-aged men, mortality, cardiovascular risk factors","lastPublishedDoi":"10.21203/rs.3.rs-6948995/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6948995/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHypertension is a well-recognized risk factor for cardiovascular disease, with various diagnostic guidelines established based on age and comorbidities. The European Society of Hypertension defines uncomplicated hypertension with a diagnostic threshold of 140/90 mmHg, whereas the American Heart Association recommends a lower threshold of 130/80 mmHg.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study aims to investigate the relationship between these two thresholds (130/80 and 140/90 mmHg) and to evaluate the prognostic values of systolic blood pressure (SBP) and diastolic blood pressure (DBP).\u003c/p\u003e\n\u003cp\u003eData were collected in 1993 and 1998 from a cohort of 1,000 randomly selected male industrial workers from Swedish automotive companies, who underwent comprehensive nurse-led health examinations, work-related surveys and laboratory tests. Over a span of 25 years, we tracked incidents of first-time myocardial infarctions, strokes, and deaths were tracked using national registries.\u003c/p\u003e\n\u003cp\u003eStatistical analyses included Kaplan-Meier curves and Cox proportional hazards ratios for composite cardiovascular outcomes of first-time myocardial infarction, stroke, and cardiovascular death. The analyses included multivariate analysis to account for potential confounders. The covariates included age, body mass index, marital status, clerical versus manual work, physical activity level, smoking habits, non-high density lipoprotein cholesterol, diabetes status, SBP and DBP.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn 1998, 914 participants (91%) completed both assessments. The adjusted Cox proportional hazards ratios indicated a statistically significant hazard ratio for hypertension defined as ≥140/90 mmHg in the 1998 analyses, while the cutoff at 130/80 mmHg did not achieve statistical significance. Both SBP and DBP were significantly associated with the composite outcome after adjustment for covariates in separate models; however, the model with both SBP and DBP as linear predictors did not yield a significant p-value for DBP.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e: Our findings do not support the adoption of a lower blood pressure threshold of 130/80 mmHg for this population of middle-aged working men. Both SBP and DBP strongly correlated with Spearman’s rho of 0.88 and demonstrated comparable prognostic value but only SBP reached significance when analyzed together. Redefining hypertension and lowering treatment targets could significantly reshape the epidemiological landscape by reclassifying people eligible for treatment. Nevertheless, the overall reduction in cardiovascular risk may be minimal.\u003c/p\u003e","manuscriptTitle":"Hypertension in a Cohort of Swedish Middle-Aged Caucasian Men in the Automotive Industry: A 25-year Follow-Up Study on Cardiovascular Risk at Varying Blood Pressure Thresholds","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-11 11:28:42","doi":"10.21203/rs.3.rs-6948995/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2025-07-09T02:22:02+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-09T00:22:52+00:00","index":"","fulltext":""},{"type":"submitted","content":"The Egyptian Heart Journal","date":"2025-07-05T07:18:27+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"the-egyptian-heart-journal","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"tehj","sideBox":"Learn more about [The Egyptian Heart Journal](https://tehj.springeropen.com)","snPcode":"43044","submissionUrl":"https://submission.springernature.com/new-submission/43044/3","title":"The Egyptian Heart Journal","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Open","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ab31eebb-67c4-43c9-b198-76f104b7ef4b","owner":[],"postedDate":"July 11th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-07-11T11:28:42+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-11 11:28:42","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6948995","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6948995","identity":"rs-6948995","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}