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Blood pressure variability in relation to 24-hour urinary sodium excretion in high salt intake polish population
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Abstracts / Journal of the American Society of Hypertension 9(4S) (2015) e63–e72
adolescents Also, the logistic regression analysis was used to estimate the most important risk factors for WCH. The WCH prevalence was 5.2% (n¼26) in all adolescents, 8.0% in males and 2.7% in females (p<0.007). Adolescents with WCH showed significant higher values than normotensives in all anthropometric parameters studied, these values were: 7318 vs. 478 kg for weight (p<0.0001), 1659 vs. 15810 cm fir height (p<0.007), 8513 vs. 665 mm for waist circumference (p<0.0001), 9912 vs. 846 mm for hip circumference, 26.65 vs. 18.52 kg/mt2 for BMI (p<0.0001), 0.850.1 vs. 0.780.1 for WHR (p<0.0001) and 0.510.1 vs. 0.410.1 for WHtR (p<0.0001). Spearman Correlation shows a statistically significant correlation among WCH with weight (r¼0.297), waist circumference (r¼0.297), BMI (r¼0.290), WHtR (r¼0.290), hip circumference (r¼0.288), and WHR (r¼0.211). The BMI was the most important risk factor for WCH (OR¼ 2.411; 95% Cls¼1.803-3.225). In conclusion, there is a high WCH prevalence in Hispanic adolescent population. In this age group, all anthropometric parameters are associated with the presence of WCH, but only the BMI should be the most important factor to predict WCH in adolescents. These conditions, WCH and higher BMI, are extremely important because from the early age the subjects could be in cardiovascular risk. Keywords: White coat hypertension; Adolescents; Anthropometric parameters P-118 Blood pressure variability in relation to 24-hour urinary sodium excretion in high salt intake polish population Katarzyna Stolarz-Skrzypek, Adam Bednarski, Grzegorz Kiełbasa, Malgorzata Kloch-Badelek, Danuta Czarnecka. Jagiellonian University Medical College, Krakow, Poland Blood pressure variability (BPV) is a novel and promising marker of cardiovascular risk. Some studies suggested increased salt intake as the explanation for non-dipping phenomenon or increased short-term BPV. The aim of the study was to investigate the relation between salt intake and blood pressure variability in high salt intake population. The study group included 292 subjects recruited from the general population of Southern Poland. Ambulatory blood pressure (ABP) monitors (SpaceLabs 90207) were programmed to obtain measurements each 15 min. during the day (6.00-22.00) and each 30 min. nighttime. Based on the ABP data, we calculated for systolic and diastolic BP: 24 h, daytime and nighttime standard deviation (SD), and ‘sleep-through’ and ‘pre-awakening’ morning surge, as the indexes of short-term BPV, as well as daynight BP difference as the index of long-term BPV. Sodium intake was assessed based on 24h urinary sodium excretion. Database management and statistical analysis were performed with SAS software (SAS Institute, Cary, NC), version 9.3. The study group included 132 men and 160 women, 159 participants were hypertensive (54.5%), mean age ¼ 4714.8 yrs, mean sodium excretion ¼ 170 74 mmol/24 h. While adjusting for age, sex, antihypertensive treatment, body mass index, and life style, we did not observe any linear relation between sodium intake and calculated indexes of BPV. In sub-group analysis, in women, we observed negative correlation between sodium intake and ‘sleep-through’ SBP surge ([beta SE]: -0.032 0.014, p ¼ 0.026). Conversely, in men, there was a positive association between sodium intake and SD of daytime DBP ([beta SE]: 0.0048 0.0023, p ¼ 0.042). Furthermore, in women, we confirmed positive correlation between dietary salt intake and 24 h ([beta SE]: 0.041 0.014, p ¼ 0.004), daytime ([beta SE]: 0.04 0.015, p ¼ 0.007) and nighttime ([beta SE]: 0.042 0.015, p ¼ 0.006) mean SBP. In our study group, we confirmed the association of sodium intake with systolic blood pressure values over 24 hours, during daytime and nighttime, but only in women. Moreover, in women, we observed negative correlation between the index of short-term BPV and sodium intake with similar non-significant trends regarding other indices of BPV. Keywords: blood pressure variability; sodium; salt
P-119 Glycemic status and incident hypertension Ahmet Temizhan,5 Sadi Gulec,2 Aytekin Oguz,3 Yuksel Altuntas,4 Kubilay Karsidag.1 1Istanbul University Faculty of Medicine, Istanbul, Turkey; 2Ankara University Faculty of Medicine, Ankara, Turkey; 3 Medeniyet University Faculty of Medicine, Istanbul, Turkey; 4Sisli Etfal Hospital, Istanbul, Turkey; 5Turkiye Yuksek Ihtisas Hospital, Ankara, Turkey Background: Prevalence of HT is increased in DM and even in the prediabetic state. However, there is little information available about glycemic status and development of HT in course of time. Objectives: The aim of the study was to determine the development of HT with respect to glycemic status in Turkish adults. Methods: This study was an analysis of the 3rd year follow up results of PURE Turkey study. It was being conducted in urban and rural areas of 8 provinces since 2008. A total of 2312 participants 35 years old (F:1412, M:900) were enrolled in the study. 985 normotensive individuals at baseline out of the whole cohort were investigated with respect to development of HT in the third year follow up. Subjects who are treated with hypoglycemic medications or with a fasting plasma glucose (FPG) level of 126 mg/dL or HbA1c level of 6.5% were considered to have DM. Prediabetes was defined as a FPG level of 100 to <126 mg/dL or HbA1c level of 5.7 to <6.5% and without history of DM. Persons with FPG level <100 mg/dL and HbA1c level <5.7% and without history of DM was defined as nondiabetic. Results: Table :The characteristics of subjects The incidence of HT in the 3rd year was significantly higher in prediabetics and diabetics when compared to controls. Multiple logistic regression analysis demonstrated that glycemic status, age and BMI level at baseline were independent predictors of incident HT (p¼0.0348, p<0.0001 and p<0.0001, respectively). This implies that being prediabetic increased the odds of developing HT within three years by 4.1% while being diabetic increased the odds of developing HT by 8.1% when compared to normal controls. On the other hand, a one unit increase in the BMI level would increase the odds of developing HT by 1.4% and a one unit increase in the age would increase the odds of developing HT by 0.7%. Conclusion: In this cohort of Turkish adults, pre-diabetics as well as diabetics seem to have increased incidence of hypertension. Our data suggest that abnormal glucose metabolism might be a sign that alerts us years before the onset of HT. Keywords: Dysglycemia; incident; hypertension
The characteristics of subjects
Female gender (%) Age, year (SD) BMI, kg/m2 (SD) Mean SBP, mmHg (SD) Baseline 3rd year Mean Difference of SBP at the 3rd year Mean DBP, mmHg (SD) Baseline 3rd year Mean Difference of DBP at 3rd year Incidence of HT at the 3rd year (%)
Nondiabetics (n:856)
Prediabetics (n:77)
Diabetics (n:52)
66 45(8) 28(5)
70 47(8) 31(6)y
63 48(8)* 30(6)*
107.047.84 116.4413.28 9.4013.26
110.22 7.49 124.1415.41z 13.9215.67z
107.507.82 122.5913.90z 15.09 15.83z
69.406.49 73.908.45 4.518.34
70.446.75 77.008.69z 6.569.23z
69.637.74 74.077.64 4.438.65
9.2
19.5z
21.2z
Abstracts / Journal of the American Society of Hypertension 9(4S) (2015) e63–e72
adolescents Also, the logistic regression analysis was used to estimate the most important risk factors for WCH. The WCH prevalence was 5.2% (n¼26) in all adolescents, 8.0% in males and 2.7% in females (p<0.007). Adolescents with WCH showed significant higher values than normotensives in all anthropometric parameters studied, these values were: 7318 vs. 478 kg for weight (p<0.0001), 1659 vs. 15810 cm fir height (p<0.007), 8513 vs. 665 mm for waist circumference (p<0.0001), 9912 vs. 846 mm for hip circumference, 26.65 vs. 18.52 kg/mt2 for BMI (p<0.0001), 0.850.1 vs. 0.780.1 for WHR (p<0.0001) and 0.510.1 vs. 0.410.1 for WHtR (p<0.0001). Spearman Correlation shows a statistically significant correlation among WCH with weight (r¼0.297), waist circumference (r¼0.297), BMI (r¼0.290), WHtR (r¼0.290), hip circumference (r¼0.288), and WHR (r¼0.211). The BMI was the most important risk factor for WCH (OR¼ 2.411; 95% Cls¼1.803-3.225). In conclusion, there is a high WCH prevalence in Hispanic adolescent population. In this age group, all anthropometric parameters are associated with the presence of WCH, but only the BMI should be the most important factor to predict WCH in adolescents. These conditions, WCH and higher BMI, are extremely important because from the early age the subjects could be in cardiovascular risk. Keywords: White coat hypertension; Adolescents; Anthropometric parameters P-118 Blood pressure variability in relation to 24-hour urinary sodium excretion in high salt intake polish population Katarzyna Stolarz-Skrzypek, Adam Bednarski, Grzegorz Kiełbasa, Malgorzata Kloch-Badelek, Danuta Czarnecka. Jagiellonian University Medical College, Krakow, Poland Blood pressure variability (BPV) is a novel and promising marker of cardiovascular risk. Some studies suggested increased salt intake as the explanation for non-dipping phenomenon or increased short-term BPV. The aim of the study was to investigate the relation between salt intake and blood pressure variability in high salt intake population. The study group included 292 subjects recruited from the general population of Southern Poland. Ambulatory blood pressure (ABP) monitors (SpaceLabs 90207) were programmed to obtain measurements each 15 min. during the day (6.00-22.00) and each 30 min. nighttime. Based on the ABP data, we calculated for systolic and diastolic BP: 24 h, daytime and nighttime standard deviation (SD), and ‘sleep-through’ and ‘pre-awakening’ morning surge, as the indexes of short-term BPV, as well as daynight BP difference as the index of long-term BPV. Sodium intake was assessed based on 24h urinary sodium excretion. Database management and statistical analysis were performed with SAS software (SAS Institute, Cary, NC), version 9.3. The study group included 132 men and 160 women, 159 participants were hypertensive (54.5%), mean age ¼ 4714.8 yrs, mean sodium excretion ¼ 170 74 mmol/24 h. While adjusting for age, sex, antihypertensive treatment, body mass index, and life style, we did not observe any linear relation between sodium intake and calculated indexes of BPV. In sub-group analysis, in women, we observed negative correlation between sodium intake and ‘sleep-through’ SBP surge ([beta SE]: -0.032 0.014, p ¼ 0.026). Conversely, in men, there was a positive association between sodium intake and SD of daytime DBP ([beta SE]: 0.0048 0.0023, p ¼ 0.042). Furthermore, in women, we confirmed positive correlation between dietary salt intake and 24 h ([beta SE]: 0.041 0.014, p ¼ 0.004), daytime ([beta SE]: 0.04 0.015, p ¼ 0.007) and nighttime ([beta SE]: 0.042 0.015, p ¼ 0.006) mean SBP. In our study group, we confirmed the association of sodium intake with systolic blood pressure values over 24 hours, during daytime and nighttime, but only in women. Moreover, in women, we observed negative correlation between the index of short-term BPV and sodium intake with similar non-significant trends regarding other indices of BPV. Keywords: blood pressure variability; sodium; salt
P-119 Glycemic status and incident hypertension Ahmet Temizhan,5 Sadi Gulec,2 Aytekin Oguz,3 Yuksel Altuntas,4 Kubilay Karsidag.1 1Istanbul University Faculty of Medicine, Istanbul, Turkey; 2Ankara University Faculty of Medicine, Ankara, Turkey; 3 Medeniyet University Faculty of Medicine, Istanbul, Turkey; 4Sisli Etfal Hospital, Istanbul, Turkey; 5Turkiye Yuksek Ihtisas Hospital, Ankara, Turkey Background: Prevalence of HT is increased in DM and even in the prediabetic state. However, there is little information available about glycemic status and development of HT in course of time. Objectives: The aim of the study was to determine the development of HT with respect to glycemic status in Turkish adults. Methods: This study was an analysis of the 3rd year follow up results of PURE Turkey study. It was being conducted in urban and rural areas of 8 provinces since 2008. A total of 2312 participants 35 years old (F:1412, M:900) were enrolled in the study. 985 normotensive individuals at baseline out of the whole cohort were investigated with respect to development of HT in the third year follow up. Subjects who are treated with hypoglycemic medications or with a fasting plasma glucose (FPG) level of 126 mg/dL or HbA1c level of 6.5% were considered to have DM. Prediabetes was defined as a FPG level of 100 to <126 mg/dL or HbA1c level of 5.7 to <6.5% and without history of DM. Persons with FPG level <100 mg/dL and HbA1c level <5.7% and without history of DM was defined as nondiabetic. Results: Table :The characteristics of subjects The incidence of HT in the 3rd year was significantly higher in prediabetics and diabetics when compared to controls. Multiple logistic regression analysis demonstrated that glycemic status, age and BMI level at baseline were independent predictors of incident HT (p¼0.0348, p<0.0001 and p<0.0001, respectively). This implies that being prediabetic increased the odds of developing HT within three years by 4.1% while being diabetic increased the odds of developing HT by 8.1% when compared to normal controls. On the other hand, a one unit increase in the BMI level would increase the odds of developing HT by 1.4% and a one unit increase in the age would increase the odds of developing HT by 0.7%. Conclusion: In this cohort of Turkish adults, pre-diabetics as well as diabetics seem to have increased incidence of hypertension. Our data suggest that abnormal glucose metabolism might be a sign that alerts us years before the onset of HT. Keywords: Dysglycemia; incident; hypertension
The characteristics of subjects
Female gender (%) Age, year (SD) BMI, kg/m2 (SD) Mean SBP, mmHg (SD) Baseline 3rd year Mean Difference of SBP at the 3rd year Mean DBP, mmHg (SD) Baseline 3rd year Mean Difference of DBP at 3rd year Incidence of HT at the 3rd year (%)
Nondiabetics (n:856)
Prediabetics (n:77)
Diabetics (n:52)
66 45(8) 28(5)
70 47(8) 31(6)y
63 48(8)* 30(6)*
107.047.84 116.4413.28 9.4013.26
110.22 7.49 124.1415.41z 13.9215.67z
107.507.82 122.5913.90z 15.09 15.83z
69.406.49 73.908.45 4.518.34
70.446.75 77.008.69z 6.569.23z
69.637.74 74.077.64 4.438.65
9.2
19.5z
21.2z