Association between weight gain following smoking cessation and development of hypertension in the future.

Although quitting smoking lowers the risk of developing chronic conditions, it usually leads to weight gain. Literature on the association between weight gain after quitting smoking and the future development of hypertension is scarce. Among 234 596 individuals who visited our health center, 856 who had quit smoking for whom data were available at least 6 years after smoking cessation were included. We evaluated changes in blood pressure and antihypertensive drug prescription rate at 1 and 6 years after smoking cessation. We also compared weight and blood pressure between the smoking cessation and continued smoking groups after 6 years. Multiple regression analyses were performed to identify predictors of changes in systolic and diastolic blood pressures using covariates affecting blood pressure. Since a median weight gain of 1.8 kg was observed at 1 year after smoking cessation, we divided the participants into high and low-weight gain groups. No significant intergroup difference in the antihypertensive drug prescription rate was observed after 6 years. The high weight gain group showed significant increases in systolic and diastolic blood pressures after 6 years. Multiple regression analyses revealed that systolic blood pressure was affected by age and high weight gain, while diastolic blood pressure was affected by high weight gain. Our findings suggest that weight gain following smoking cessation leads to blood pressure elevation: the smoking cessation group gained more weight and had higher blood pressure than the continued smoking group. Therefore, weight loss guidance may be useful for individuals who want to quit smoking. Participants in the high weight gain group showed significant increases in systolic and diastolic blood pressures at 6 years after smoking cessation that were significantly different from those observed in participants in the low weight gain group and the continued smoking group.

Association between anthropometric indices and 5-year hypertension incidence in the general Japanese population.

No existing reports demonstrate the association between anthropometric indices (body mass index, waist circumference, body roundness index, a body shape index) and hypertension according to sex and age in the general Japanese population. This retrospective analysis involved individuals aged 30-69 years who underwent annual medical checkups at Kagoshima Koseiren Hospital in 2005-2019, and who did not meet hypertension criteria at baseline. The outcome was hypertension incidence after 5 years, and its association with baseline anthropometric indices was evaluated using multivariable logistic regression analysis by sex and age. In 41,902 participants (age 52.3 ± 10.2 years, 47.7% men), 7622 individuals (18.2%) developed hypertension after 5 years. Body mass index, waist circumference, and body roundness index were significantly associated with the development of hypertension in both men and women across all age categories from 30 s to 60 s. In the population with a body mass index <25 kg/m2, waist circumference and body roundness index were significantly associated with hypertension after 5 years. A body shape index was significantly associated with the development of hypertension in men in their 40 s and 50 s but not in women of any age group. The area under the curve values were lower for a body shape index than for body mass index, waist circumference, and body roundness index in both men and women of all age groups. A body shape index was not a stronger indicator for 5-year hypertension incidence than body mass index, waist circumference, or body roundness index in both men and women across age groups from their 30s-60 s. The results of this study will help to more efficiently identify populations at high risk of developing hypertension and provide preventive interventions. A total of 41,902 participants from health checkup programs were stratified by gender and age to investigate the association between baseline anthropometric indices and hypertension incidence over a 5-year period. BMI, WC, and BRI were almost equally effective and showed a better association with risk of developing hypertension in women and young adults compared to men and old adults. Conversely, ABSI showed no greater association than BMI or WC in any age group in both men and women. ABSI, a body shape index; AUC, area under the curve from receiver operating characteristic curve analysis; BMI, body mass index; BRI, body roundness index; WC, waist circumference.

Sex-specific associations between serum uric acid levels and risk of hypertension for different diagnostic reference values of high blood pressure.

The association between uric acid (UA) and hyperuricemia with 5-year hypertension incidence using different blood pressure (BP) diagnostic references in men and women without cardiometabolic diseases is unknown. We used the checkup data from Kagoshima Kouseiren Hospital. All participants with hypertension or on BP medication, diabetes, dyslipidemia, obesity, estimated glomerular filtration rate<60 ml/min/1.73m2, metabolic syndrome, history of gout, and UA-lowering medication were excluded. UA was categorized into sex-specific quartiles and hyperuricemia was defined as UA > 7 mg/dl in men and UA > 6 mg/dl in women. We performed multivariate logistic regression to assess the effects of UA on hypertension development. The 5-year hypertension incidence was defined as subsets of BP ≥ 140/90 mmHg in cohort 1 and BP ≥ 130/80 mmHg in cohort 2. The study enrolled 21,443 participants (39.8%, men) in cohort 1 and 15,245 participants (36.5%, men) in cohort 2. The incidence of hypertension in cohorts 1 and 2 over 5 years was 16.3% and 29.7% in men and 10.9% and 21.4% in women, respectively. When comparing the fourth to the first UA quartile, there was an association with hypertension in men in cohort 1, with odds ratio (OR): 1.36 (95% confidence interval [CI], 1.13-1.63, p < 0.01) and cohort 2, OR: 1.31 (95%CI, 1.09-1.57, p < 0.01), respectively, but not in women. Additionally, an association between hyperuricemia and hypertension was observed in men only in cohort 1, with OR: 1.23 (95%CI, 1.07-1.42, p = 0.02), and in women in cohort 2, OR: 1.57 (95%CI, 1.14-2.16, p < 0.01). The effect of UA on the development of hypertension is influenced by sex and incidence differs with the BP reference used. Uric acid effect on the development of hypertension is affected by sex and incidence differs with the BP reference used.

J-shaped Association between Serum Uric Acid Levels and the Prevalence of a Reduced Kidney Function: A Cross-Sectional Study Using Japanese Health Examination Data.

Objective While an association between a reduced kidney function and hyperuricemia has been reported, its association with hypouricemia is not well understood. The present study therefore investigated this association. Methods Using a large Japanese health examination dataset, we performed a multivariable logistic regression analysis to assess the association between serum uric acid (SUA) levels and a reduced kidney function. The covariates included the age, body mass index, alcohol intake, and the presence of hypertension, dyslipidemia, or diabetes. Patients This study included 227,672 patients (104,854 men; 46.1%), and the analyses were performed separately for men and women. The patients were classified into 5 groups: hypouricemia (SUA ≤2.0 mg/dL) (1st) and four other (2nd-5th) groups with SUA levels of ≤2.0, 2.1-5.1, 5.2-5.9, 6.0-6.8, ≥6.9 mg/dL in men and ≤2.0, 2.1-3.7, 3.8-4.4, 4.5-5.1, ≥5.2 mg/dL in women, respectively. Results The characteristics of the study population were as follows: men, age 55.9±14.9 years old, SUA 5.9±1.3 mg/dL, estimated glomerular filtration rate (eGFR) 80.0±17.2 mL/min/1.73 m2, and a reduced kidney function (eGFR<60.0 mL/min/1.73 m2) 9.4%; women, age 57.3±15.0 years old, SUA 4.5±1.1 mg/dL, eGFR 81.2±18.0 mL/min/1.73 m2, and a reduced kidney function 9.4%. Compared with the 2nd group, the other 4 groups groups had a significantly higher prevalence of a reduced kidney function [odds ratio (OR), 2.58; 95% confidence interval (CI), 1.64-4.06 in men; OR, 1.66; 95% CI, 1.16-2.39 in women]. Conclusion The prevalence of a reduced kidney function was high in both men and women in the hypouricemia and high-SUA groups. SUA levels and the prevalence of a reduced kidney function showed a J-shaped association.

Development of predictive equation and score for 5-year metabolic syndrome incidence in Japanese adults.

BACKGROUND: Predicting metabolic syndrome (MetS) is important for identifying high-risk cardiovascular disease individuals and providing preventive interventions. We aimed to develop and validate an equation and a simple MetS score according to the Japanese MetS criteria. METHODS: In total, 54,198 participants (age, 54.5±10.1 years; men, 46.0%), with baseline and 5-year follow-up data were randomly assigned to 'Derivation' and 'Validation' cohorts (ratio: 2:1). Multivariate logistic regression analysis was performed in derivation cohort and scores were assigned to factors corresponding to ß-coefficients. We evaluated predictive ability of the scores using area under the curve (AUC), then applied them to validation cohort to assess reproducibility. RESULTS: The primary model ranged 0-27 points had an AUC of 0.81 (sensitivity: 0.81, specificity: 0.81, cut-off score: 14), and consisted of age, sex, blood pressure (BP), body mass index (BMI), serum lipids, glucose measurements, tobacco smoking, and alcohol consumption. The simplified model (excluding blood tests) ranged 0-17 points with an AUC of 0.78 (sensitivity: 0.83, specificity: 0.77, cut-off score: 15) and included: age, sex, systolic BP, diastolic BP, BMI, tobacco smoking, and alcohol consumption. We classified individuals with a score <15 and ≥15 points as low- and high-risk MetS, respectively. Furthermore, the equation model generated an AUC of 0.85 (sensitivity: 0.86, specificity: 0.55). Analysis of the validation and derivation cohorts yielded similar results. CONCLUSION: We developed a primary score, an equation model, and a simple score. The simple score is convenient, well-validated with acceptable discrimination, and could be used for early detection of MetS in high-risk individuals.

Development of a risk prediction score and equation for chronic kidney disease: a retrospective cohort study.

Chronic kidney disease (CKD) is a risk factor for end-stage renal disease and contributes to increased risk of cardiovascular disease morbidity and mortality. We aimed to develop a risk prediction score and equation for future CKD using health checkup data. This study included 58,423 Japanese participants aged 30-69 years, who were randomly assigned to derivation and validation cohorts at a ratio of 2:1. The predictors were anthropometric indices, life style, and blood sampling data. In derivation cohort, we performed multivariable logistic regression analysis and obtained the standardized beta coefficient of each factor that was significantly associated with new-onset CKD and assigned scores to each factor. We created a score and an equation to predict CKD after 5 years and applied them to validation cohort to assess their reproducibility. The risk score ranged 0-16, consisting of age, sex, hypertension, dyslipidemia, diabetes, hyperuricemia, and estimated glomerular filtration rate (eGFR), with area under the curve (AUC) of 0.78 for the derivation cohort and 0.79 for the validation cohort. The CKD incidence gradually and constantly increased as the score increased from ≤ 6 to ≥ 14. The equation consisted of the seven indices described above, with AUC of 0.88 for the derivation cohort and 0.89 for the validation cohort. We developed a risk score and equation to predict CKD incidence after 5 years in Japanese population under 70 years of age. These models had reasonably high predictivity, and their reproducibility was confirmed through internal validation.

Clinical significance of atherosclerotic risk factors differs in early and advanced stages of plaque formation: A longitudinal study in the general population.

BACKGROUND: Carotid plaque is a well-known prognostic factor for cardiovascular diseases. It is unclear which risk factors are associated with the transformation of carotid plaque over time. In this longitudinal study, we examined the risk factors related to carotid plaque progression. METHODS: We enrolled 738 men without medication (mean age: 55 ± 10 years) who underwent the first and second health examinations. We measured carotid plaque thickness (PT) at three points of the right and left carotid artery. Plaque score (PS) was calculated by summing all the PTs. We divided the PS into three groups: None-group (PS <1.1), Early-group (1.1 ≤ PS <5.1), and Advanced-group (PS ≥5.1). We analyzed the relationship between PS progression and parameters such as age, body mass index, systolic blood pressure (SBP), fasting blood sugar, low-density lipoprotein cholesterol (LDL-C), and smoking and exercise habits. RESULTS: In multivariable logistic regression analysis, age and SBP were independent factors for PS progression from none to early stages (age, OR 1.07, p = 0.002; SBP, 10 mmHg, OR 1.27, p = 0.041). Age, follow-up period and LDL-C were independently associated factors for PS progression from early to advanced stages (age, OR 1.08,p < 0.001; follow-up period OR1.19, p = 0.041; LDL-C, 10 mg/dL, OR 1.10, p = 0.049). CONCLUSIONS: SBP was independently associated with the progress of early atherosclerosis, while LDL-C was independently associated with the progression of advanced atherosclerosis in the general population. Further studies are needed to assess whether early control of SBP and LDL-C levels can reduce the occurrence of future cardiovascular events.

Cutoff Values of Brachial-Ankle Pulse Wave Velocity for Atherosclerotic Risks by Age and Sex in the Japanese General Population.

AIM: In this study, we aim to analyze the correlation between brachial-ankle pulse wave velocity (baPWV) and Suita score or Framingham risk score and obtain the cutoff value of baPWV by sex and age for cardiovascular risk, as assessed by these scores in the large Japanese annual health checkup data. METHODS: In total, 25,602 participants (14,539 men and 11,063 women), who had their annual health checkups, were included in this study. Cutoff values of baPWV for the moderate- and high-risk groups stratified by sex and age were obtained using a receiver operating characteristic (ROC) curve analysis. RESULTS: As per our findings, the Suita score demonstrated better correlations with baPWV than the Framingham risk score in both sexes (men, Suita score R2=0.41 and Framingham risk score R2=0.37; women, Suita score R2=0.54 and Framingham risk score R2=0.33). The ROC curve analysis demonstrated the cutoff values of baPWV for moderate- and high-risk groups estimated using the Suita score, and they are as follows: in men, the baPWV cutoff values were 1,350 cm/s in the 40s, 1,430 cm/s in the 50s, 1,520 cm/s in the 60s, and 1,880 cm/s in the 70s. In women, the baPWV cutoff values were 1,350 cm/s in the 40s, 1,430 cm/s in the 50s, 1,570 cm/s in the 60s, and 1,800 cm/s in the 70s. CONCLUSIONS: We demonstrated that baPWV significantly correlated with the Suita score or Framingham risk score in both men and women, with the former presenting a stronger correlation than the latter. We propose the cutoff values of baPWV for moderate- and high-risk groups estimated using the Suita score.

Insufficient blood pressure control is independently associated with increased arterial stiffness.

Hypertension is a risk factor for atherosclerosis. Achieving the therapeutic target value of blood pressure (BP) prevents the onset of cardiovascular events; however, it is not clear how antihypertensive drug use and BP control status relate to arterial stiffness. The purpose of this study is to investigate the relationship between BP control status with or without antihypertensive drugs and arterial stiffness. Nine hundred eighty individuals (mean age: 68 ± 11 years) who participated in a community-based cohort study were enrolled. Arterial stiffness was evaluated using the cardio-ankle vascular index (CAVI). Higher BP was defined as a systolic BP ≥ 140 mmHg or diastolic BP ≥ 90 mmHg. Participants were divided into four groups: normal, non higher BP without antihypertensive drugs (n = 421); untreated, higher BP without antihypertensive drugs (n = 174); good control, non higher BP with antihypertensive drugs (n = 209); and poor control, higher BP with antihypertensive drugs (n = 176). In multivariable logistic analysis adjusted for age, sex, dyslipidemia and diabetes mellitus medication use, obesity, smoking, alcohol drinking, and heart rate at the CAVI measurement for a high CAVI-using a borderline cutoff value of 8.0-the other three groups were significantly associated with a high CAVI when compared with the normal group. By contrast, multivariable logistic analysis of a high CAVI using an abnormal cutoff value of 9.0 demonstrated that the poor control and untreated groups were significantly associated with a high CAVI, whereas the good control group was not. In conclusion, even with antihypertensive drugs, poor BP control is independently associated with a high CAVI.

Assessment of Future Hypertension Risk by Sex Using Combined Body Mass Index and Waist-to-Height Ratio.

Background: Body mass index (BMI) and the waist-to-height ratio (WHtR) are widely used anthropometric indices of obesity to predict cardiovascular risks. However, the usefulness of combining WHtR and BMI values to predict hypertension risk by sex has not been well elucidated. Methods and Results: This cohort study enrolled 45,921 participants (mean [±SD] age 53.8±10.5 years; 47.0% men) without hypertension from among those undergoing annual health checkups. Participants were divided into 4 categories based on median BMI and WHtR values, and the 5-year incidence of hypertension was assessed for both sexes using logistic regression analysis. Mean (±SD) BMI and WHtR values were 23.5±3.1 kg/m2 and 0.50±0.05, respectively, in men and 22.4±3.3 kg/m2 and 0.53±0.06, respectively, in women. Among the women, those with high BMI and low WHtR had an increased risk of hypertension compared with those with low BMI and low WHtR (odds ratio [OR] 1.37, P<0.001); however, the same result was not found in men (OR 1.14, P=0.080). In both sexes, the incidence of hypertension was higher among participants with low BMI and high WHtR than among those with low BMI and low WHtR (men: OR 1.26, P<0.001; women: OR 1.15, P=0.048). Conclusions: Using WHtR and BMI together provides a better hypertension risk assessment. Among men, those with a high BMI had no increased hypertension risk when WHtR was low.