Abstract
BACKGROUND:
There is little evidence to show that the blood pressure-to-height ratio (BPHR) accurately detects elevated blood pressure (EBP) in children. The present study evaluated the accuracy of BPHR in detecting EBP in children aged 8–11 years.
MATERIALS AND METHODS:
This cross-sectional study involved 1087 children (531 boys and 556 girls), aged 8–11 years. Weight, height, and blood pressure (BP) were measured using the standard procedure. EBP was defined as systolic or diastolic pressure at the 90th percentile or above at a specific gender, age, and height. Mann–Whitney U test and Spearman’s correlation were applied. The diagnostic accuracy was set at an area-under-the-curve of ≥0.90. Sex-specific cutoff points for systolic BPHR (SBPHR) and diastolic BPHR (DBPHR) were determined. The sensitivity and specificity of SBPHR and DBPHR were also determined.
RESULTS:
Most variables between sexes were comparable (P > 0.05), except weight, height, and body mass index (BMI) in the 8–9 years’ age group. Almost all variables for children with EBP were significantly higher than normotensive (P < 0.05). SBPHR correlated with all variables except BMI in girls. DBPHR correlated with almost all variables except age (sexes) and height (girls). The accuracy of SBPHR and DBPHR in diagnosing EBP in both sexes was above 95%. The optimal threshold of SBPHR and DBPHR for diagnosing EBP was 0.804/0.519 in boys and 0.831/0.530 in girls. The sensitivity and specificity were 90.8%–96.5% and 86.0%–93.2%, respectively.
CONCLUSION:
SBPHR and DBPHR have high accuracy, sensitivity, and specificity in detecting EBP in Indonesian children aged 8–11 years.
Keywords: Blood pressure-to-height ratio, children, diagnostic accuracy, elevated blood pressure
Introduction
The prevalence of elevated blood pressure (EBP) in children and adolescents worldwide has reached an alarming level.[1] Previous studies have shown that the incidence of hypertension (HT) in children ranges from 2% to 4%.[2,3] Because blood pressure (BP) in childhood is positively associated with adult BP, HT in a person’s younger years often predicts HT during adulthood.[4] Therefore, assessing BP to detect and prevent HT in children should be a global priority.[5] Like adults, children with HT can also experience severe complications such as stroke, end-stage renal diseases, or even premature death.[6] The early detection and treatment of childhood HT is of crucial importance to the lives and future of the children.[7,8]
Unfortunately, diagnosing HT in children and adolescents is not as simple as diagnosing it in adults. Unlike adults, normal BP ranges in children are based on sex, age, and height.[9,10] BP obtained from a physical examination cannot be used directly to confirm a diagnosis of HT in children. BP readings of children and adolescents must be plotted first on a standardized table of BP percentile based on sex, age, and height. Prehypertension can be confirmed when BP is between the 90th and 95th percentiles; HT is when BP is at the 95th percentile or greater based on a child’s age, sex, and height percentile.[9,10]
A more straightforward screening method has been developed to improve early diagnosis of HT in children and adolescents. This screening method, apart from being used for diagnoses, can also be used to increase the awareness of HT. This method applies the ratio of body size to BP. For example, several prior studies applied the BP-to-height ratio (BPHR).[11,12,13,14] The BPHR consists of a systolic BPHR (SBPHR) and a diastolic BPHR (DBPHR). Using the area-under-the-curve (AUC) technique to assess accuracy, it has been reported that the sensitivity and specificity of the BPHR are high (the results, however, vary with sex).[11,12,13,14] Studies conducted in Indonesia have also reported that the BPHR has a high sensitivity and specificity for diagnosing HT in adolescents.[15,16] The optimum cutoff of the SBPHR typically ranges from 0.75 to 0.88 for boys and from 0.77 to 0.90 for girls; the optimum cutoff of the DBPHR often ranges from 0.48 to 0.60 for boys and 0.50 to 0.63 for girls.[11,12,13,14,15,16] However, more information on the accuracy of the BPHR for diagnosing HT in children aged 8–11 years is necessary. The accuracy of BPHR in children younger than 12 years is not yet proven. Moreover, one study reported that the accuracy of the BPHR was lower in children younger than 12 compared with adolescents.[17]
Earlier studies have reported that the prevalence and incidence of HT vary by race and ethnicity. Studies conducted in the United States have shown that non-Hispanic Black individuals have the highest prevalence of HT.[18,19] Another study found that childhood HT was highest in Hispanics (3.1%) and lowest in Asians (1.7%).[3] A large school-based study conducted in China found that the prevalence of HT was 3%. A study in Indonesia involving 313 adolescents aged 12–18 years found the prevalence of HT to be 9.6%.[20]
The BPHR demonstrated high sensitivity and specificity in diagnosing adolescents’ EBP. However, since race and ethnicity can affect the diagnostic accuracy of BPHR, particularly in children under 12 years of age, this study aimed to evaluate its accuracy in diagnosing EBP in Indonesian children aged 8–11 years. Early HT screening in children has the potential to reduce the prevalence of HT in adults and its associated complications, including mortality.
Materials and Methods
We conducted a cross-sectional analytic study from August 2022 to November 2023. The study involved students from Tarakanita Catholic Elementary School and Penjaringan Public Elementary School 3 in Jakarta, Indonesia. Ethical approval was obtained from the Institutional Review Board via Letter No. 15/11/KEP-FKUAJ/2019 dated 10/11/2019, and written informed consent was taken from the parents or legal guardians of all participants in the study after permission was obtained from the principals of both schools.
The inclusion criteria for this study were students aged 8–11 years, but not students aged 12 since they were preparing for examinations. Students who had signs of acute or chronic illnesses or were taking BP medication, had infections, or fevers were excluded. We obtained students’ medical histories from their parents and teachers.
The primary outcomes of this study were the SBPHR and DBPHR, aligned with the study’s objectives. The main purpose of this study was to evaluate the ability of SBPHR and DBPHR to diagnose HT. Therefore, other variables were considered secondary outcomes. Secondary outcomes included factors that could influence the primary outcomes, such as systolic BP, diastolic BP, weight, height, and BMI.
The anthropometric measurements were taken by assistants of the same gender to avoid ethical issues. Height and weight measurements were taken using standard procedures. Standing height was measured using a stature meter in Frankfort’s position. Participants stood with bare feet together and their backs straight against a wall. The results were recorded to the nearest 0.5 cm. Weight measurements were taken in a standing position with bare feet and minimal clothing using a digital scale (Seca Robusta 813, Germany). The results were recorded to the nearest 0.1 kg. The highest values of height and weight were recorded from three measurements. The body mass index (BMI) was calculated using the standard formula and expressed in units of kg/m2. A child’s BMI was classified as normal if it fell between the 5th and 90th percentiles and elevated at or above the 90th percentile, based on age and sex.[21]
BP was measured using an automated digital BP monitor (Omron T8 with IntelliSense, Japan) on each participant’s right arm. Students were instructed to sit quietly for 5 minutes resting in a comfortable examination room maintained at a temperature of 25°C. The appropriate cuff size was selected based on the participant’s arm length and circumference. The investigator measured BP three times, at intervals of 30–45 s, and the highest of the three readings was recorded. Normal BP was defined as systolic or diastolic pressure below the 90th percentile, prehypertension between the 90th and 95th percentiles, and HT above the 95th percentile, based on age, sex, and height.[4,10] For analysis, prehypertension and HT were combined into a single category labeled as “elevated” to identify increased BP before it progressed to HT. The SBPHR and DBPHR were calculated by dividing the systolic BP (mmHg) or diastolic BP (mmHg) by standing height (cm).
Standardized instruments and measurement procedures were used to minimize bias. The research assistants were given a brief training and interexaminer bias was minimized by evaluating interexaminer reliability. Examiners performed outcome measurements (weight and height) on ten participants, and the results of two examiners’ measurements indicated a high correlation (P < 0.001, r = 0.91).
Numerical variables were presented as means with standard deviations, while categorical data were reported as frequencies with percentages. The normality of numerical data distribution was assessed using the Kolmogorov–Smirnov test, which revealed that all numerical data were nonnormally distributed. The Kruskal–Wallis test was used to analyze differences in variables among the normal, prehypertension, and HT groups. When the Kruskal–Wallis test yielded a significant result (P < 0.05), the Mann–Whitney test was applied to identify which groups differed. Associations between categorical variables were analyzed using the Chi-square test, with odds ratios and 95% confidence intervals included. Spearman’s correlation coefficient was used to assess the strength of the association between SBPHR and DBPHR with age, height, weight, BMI, and percentiles of SBP and DBP.
We used a receiver operating characteristic (ROC) curve to separately assess the diagnostic accuracy of SBPHR and DBPHR for predicting EBP; age-, sex-, and height-specific reference standards were used. The ROC curves were plotted using sensitivity measures for the various cutoff points. Specificity was obtained by calculating values in Excel (Microsoft, USA). The diagnostic power of the SBPHR and DBPHR was measured by determining the AUC. We considered SBPHR’s and DBPHR’s diagnostic ability satisfactory if a value yielded an AUC value greater than or equal to 0.90.[22] The optimal cutoffs for both SBPHR and DBPHR were determined using the specificity and sensitivity values. Those values, in turn, yielded the maximum ROC curves through the Youden index. The highest value of the Youden index indicated the best cutoff point and the most optimal sensitivity and specificity. We used the Statistical Software Package SPSS version 21.0 for Windows (SPSS Inc., Chicago, IL, USA).
Results
A comparison of the data from the two schools showed no difference between the numeric variables of the two schools (P > 0.05). Therefore, we decided to pool the data from two schools and analyze them as a single unit. The characteristics of the subjects and comparisons based on gender are presented in Table 1. Boys and girls significantly differ in BMI across all age groups (all P < 0.05). Weight differs between genders only in the 8- and 9-year age group (P < 0.001 and 0.009), height differs between genders only in the 8-year age group (P < 0.001), and SBPHR differs only in the 11-year age group (P = 0.001). There were no significant differences in SBP, DBP, or DBPHR between genders across all age groups.
Table 1.
Characteristics of study subjects according to age and sex
| Age (years) | Overall (n=1087) | Boys (n=531) | Girls (n=556) | P-value |
|---|---|---|---|---|
| Weight (kg) | ||||
| 8 (n=247) | 28.7±7.7 | 31.5±8.4 | 27.0±6.6 | <0.001 |
| 9 years (n=297) | 32.7±9.7 | 34.5±11.2 | 30.8±7.5 | 0.009 |
| 10 years (n=268) | 35.9±10.4 | 37.5±11.8 | 34.6±8.8 | 0.087 |
| 11 years (n=275) | 43.3±11.9 | 44.1±12.4 | 42.2±11.1 | 0.166 |
| Height (cm) | ||||
| 8 years (n=247) | 127.1±6.3 | 129.1±6.1 | 125.9±6.1 | <0.001 |
| 9 years (n=297) | 132.6±6.8 | 133.2±6.9 | 132.0±6.6 | 0.071 |
| 10 years (n=268) | 138.0±7.0 | 137.9±7.3 | 138.0±6.7 | 0.742 |
| 11 years (n=275) | 146.3±8.1 | 145.5±8.3 | 147.3±7.7 | 0.067 |
| BMI (kg/m2) | ||||
| 8 years (n=247) | 17.6±3.6 | 18.7±4.0 | 16.8±3.0 | <0.001 |
| 9 years (n=297) | 18.3±4.1 | 19.1±4.7 | 17.5±3.2 | 0.015 |
| 10 years (n=268) | 18.6±4.2 | 19.4±4.6 | 18.0±3.7 | 0.029 |
| 11 years (n=275) | 20.1±4.3 | 20.7±4.6 | 19.2±3.8 | 0.008 |
| SBP (mmHg) | ||||
| 8 years (n=247) | 101.8±14.4 | 101.3±13.1 | 102.0±15.1 | 0.972 |
| 9 years (n=297) | 103.1±13.7 | 103.3±12.1 | 103.0±15.3 | 0.452 |
| 10 years (n=268) | 104.5±12.6 | 103.8±12.8 | 105.2±12.5 | 0.729 |
| 11 years (n=275) | 107.4±11.9 | 108.9±12.2 | 105.4±11.1 | 0.057 |
| DBP (mmHg) | ||||
| 8 years (n=247) | 61.6±13.1 | 60.9±11.3 | 62.0±14.1 | 0.810 |
| 9 years (n=297) | 64.7±12.4 | 63.3±10.0 | 66.2±14.3 | 0.336 |
| 10 years (n=268) | 66.4±12.6 | 64.8±11.1 | 67.8±13.6 | 0.262 |
| 11 years (n=275) | 70.8±11.7 | 70.1±11.3 | 71.7±12.2 | 0.301 |
| SBPHR | ||||
| 8 years (n=247) | 0.80±0.11 | 0.79±0.10 | 0.81±0.11 | 0.184 |
| 9 years (n=297) | 0.78±0.10 | 0.78±0.08 | 0.78±0.12 | 0.962 |
| 10 years (n=268) | 0.76±0.09 | 0.75±0.08 | 0.76±0.09 | 0.826 |
| 11 years (n=275) | 0.74±0.08 | 0.75±0.07 | 0.72±0.08 | 0.001 |
| DBPHR | ||||
| 8 years (n=247) | 0.48±0.10 | 0.47±0.08 | 0.49±0.11 | 0.304 |
| 9 years (n=297) | 0.49±0.09 | 0.47±0.07 | 0.50±0.11 | 0.133 |
| 10 years (n=268) | 0.48±0.09 | 0.47±0.08 | 0.49±0.10 | 0.414 |
| 11 years (n=275) | 0.48±0.08 | 0.48±0.08 | 0.49±0.08 | 0.758 |
BMI=Body mass index, SBP=Systolic blood pressure, DBP=Diastolic blood pressure, SBPHR=SBP to height ratio, DBPHR=DBP to height ratio
Table 2 compares variables among boys with normal BP, prehypertension, and HT. Except for age (P = 0.14), most variables – including weight, height, BMI, SBP, DBP, SBPHR, and DBPHR – were significantly higher in the prehypertension and HT groups than the normal group (all P < 0.001). Chi-square analysis revealed a significant association between elevated BMI and EBP (P < 0.001).
Table 2.
Comparison of variables by blood pressure status in boys
| SBP/DBP | P-value | Mean rank | |||
|---|---|---|---|---|---|
|
| |||||
| Normal (n=394) | Pre-HT (n=54) | HT (n=83) | |||
| Age (years) | 9.6±1.1 | 9.7±1.2 | 9.6±1.1 | 0.14 | 244.4–245.2 |
| Weight (kg) | 34.5±10.6 | 42.0±8.6* | 48.5±14.5* | <0.001 | 230.2–356.9 |
| Height (cm) | 136.0±9.2 | 139.3±7.8 | 140.8±11.5* | <0.001 | 238.5–291.7 |
| BMI (kg/m2), n (%) | 18.4±4.1 | 21.5±2.9* | 24.0±4.6* | <0.001 | 228.4–371.5 |
| Normoweight | 248 (92.2) | 9 (3.3) | 12 (4.5) | <0.001 | - |
| Overweight | 49 (55.7) | 15 (17) | 24 (27.3) | ||
| Obesity | 97 (55.8) | 30 (17.2) | 47 (27) | ||
| SBP (mmHg) | 99.8±9.9 | 117.5±3.2* | 126.5±6.3* | <0.001 | 217.2–459.8 |
| DBP (mmHg) | 61.1±8.7 | 74.8±10.5* | 76.6±11.3* | <0.001 | 226.6–385.4 |
| SBPHR | 0.76±0.07 | 0.85±0.03* | 0.90±0.06* | <0.001 | 218.0–453.4 |
| DBPHR | 0.45±0.06 | 0.54±0.07* | 0.54±0.10* | <0.001 | 227.8–376.4 |
*Significantly different from the normal group. SBP=Systolic blood pressure, DBP=Diastolic blood pressure, BMI=Body mass index, SBPHR=SBP to height ratio, DBPHR=DBP to height ratio, HT=Hypertension
Table 3 compares variables among girls with normal BP, prehypertension, and HT. Most variables – including weight, BMI, SBP, DBP, SBPHR, and DBPHR – were significantly higher in the prehypertension and HT groups compared to the normal group (all P < 0.001), except for age and height (P = 0.860 and P = 0.230, respectively). The Chi-square test revealed a significant association between elevated BMI and BP in girls (P < 0.001).
Table 3.
Comparison of variables by blood pressure status in girls
| SBP/DBP | P-value | Mean rank | |||
|---|---|---|---|---|---|
|
| |||||
| Normal (n=366) | Pre-HT (n=88) | HT (n=102) | |||
| Age (years) | 9.4±1.1 | 9.0±1.1 | 9.4±0.9 | 0.860 | 273.9–212.7 |
| Weight (kg) | 31.8±9.0 | 32.9±11.3 | 34.2±10.9* | <0.001 | 259.5–275.7 |
| Height (cm) | 134.7±9.9 | 133.0±11.4 | 133.3±9.1 | 0.230 | 268.8–235.2 |
| BMI (kg/m2), n (%) | 17.2±3.1 | 18.1±3.2 | 18.9±4.2* | <0.001 | 253.3–302.6 |
| Normoweight | 282 (72.3) | 45 (11.5) | 63 (16.2) | <0.001 | - |
| Overweight | 55 (55) | 26 (26) | 19 (19) | ||
| Obesity | 29 (43.9) | 17 (25.8) | 20 (30.3) | ||
| SBP (mmHg) | 97.1±10.2 | 114.3±3.3* | 123.6±7.8* | <0.001 | 215.1–468.5 |
| DBP (mmHg) | 59.7±8.6 | 73.9±13.9* | 81.1±14.7* | <0.001 | 229.0–408.0 |
| SBPHR | 0.72±0.07 | 0.86±0.05* | 0.93±0.08* | <0.001 | 215.6–466.5 |
| DBPHR | 0.44±0.06 | 0.56±0.09* | 0.61±0.11* | <0.001 | 226.4–419.5 |
*Significantly different from the normal group. BMI=Body mass index, SBP=Systolic blood pressure, DBP=Diastolic blood pressure, SBPHR=SBP to height ratio; DBPHR=DBP to height ratio, HT=Hypertension
Table 4 shows the correlation between SBPHR and DBPHR and various variables (age, weight, height, BMI, SBP percentile, and DBP percentile) in boys and girls. In boys, the SBPHR correlates negatively with age (r = −0.164, P < 0.001) and height (r = −0.093, P = 0.031) but positively with weight (r = 0.185, P < 0.001), BMI (r = 0.307, P < 0.001), SBP percentile (r = 0.631, P < 0.001), and DBP percentile (r = 0.351, P < 0.001). In girls, SBPHR shows a negative correlation with age (r = −0.281, P < 0.001), weight (r = −0.125, P < 0.001), and height (r = −0.291, P < 0.001) but a positive correlation with SBP percentile (r = 0.691, P < 0.001) and DBP percentile (r = 0.433, P < 0.001). The DBPHR in boys correlates positively with weight (r = 0.376, P < 0.001), height (r = 0.121, P = 0.005), BMI (r = 0.452, P < 0.001), SBP percentile (r = 0.405, P < 0.001), and DBP percentile (r = 0.611, P < 0.001). Similarly, in girls, DBPHR correlates positively with weight (r = 0.106, P = 0.012), BMI (r = 0.174, P < 0.001), SBP percentile (r = 0.519, P < 0.001), and DBP percentile (r = 0.725, P < 0.001).
Table 4.
Correlation between systolic blood pressure to height ratio and diastolic blood pressure to height ratio with relevant variables
| Age | Weight | Height | BMI | Percentile SBP | Percentile DBP | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
|
|
|
|
|
|
|
|||||||
| P-value | r | P-value | r | P-value | r | P-value | r | P-value | r | P-value | r | |
| SBPHR | ||||||||||||
| Boys | <0.001 | −0.164 | <0.001 | 0.185 | 0.031 | −0.093 | <0.001 | 0.307 | <0.001 | 0.631 | <0.001 | 0.351 |
| Girls | <0.001 | −0.281 | 0.003 | −0.125 | <0.001 | −0.291 | 0.353 | 0.039 | <0.001 | 0.691 | <0.001 | 0.433 |
| DBPHR | ||||||||||||
| Boys | 0.428 | 0.034 | <0.001 | 0.376 | 0.005 | 0.121 | <0.001 | 0.452 | <0.001 | 0.405 | <0.001 | 0.611 |
| Girls | 0.939 | 0.003 | 0.012 | 0.106 | 0.714 | −0.016 | <0.001 | 0.174 | <0.001 | 0.519 | <0.001 | 0.725 |
BMI=Body mass index, SBP=Systolic blood pressure, DBP=Diastolic blood pressure, SBPHR=SBP to height ratio, DBPHR=DBP to height ratio
Table 5 presents the accuracy of the SBPHR in diagnosing EBP according to gender. A cutoff of 0.804 for the SBPHR in boys yielded an AUC of 0.959 (P < 0.001) and a sensitivity and specificity of 96% and 86%, respectively. In girls, the cutoff was 0.831, which resulted in an AUC of 0.969 (P < 0.001) with a high sensitivity (91%) and specificity (93%). For the DBPHR, a cutoff point of 0.519 in boys yielded an AUC of 0.979 (P < 0.001) with a sensitivity and specificity of 97% and 90%, respectively. A cutoff point of 0.530 in girls resulted in an AUC of 0.971 (P < 0.001), with a sensitivity and specificity of 94% and 91%, respectively.
Table 5.
Areas under the curves of systolic blood pressure to height ratio and systolic blood pressure to height ratio for diagnosing body mass index, systolic blood pressure, diastolic blood pressure, systolic blood pressure to height ratio, diastolic blood pressure to height ratio defined by age, gender, and height-specific references
| Cut-off points | AUC | 95% CI | P-value | Sensitivity (%) | Specificity (%) | PPV (%) | NPV (%) | |
|---|---|---|---|---|---|---|---|---|
| SBPHR | ||||||||
| Boys | 0.81 | 0.96 | 0.938−0.980 | <0.001 | 96.0 | 86.0 | 93.9 | 87.3 |
| Girls | 0.83 | 0.97 | 0.952−0.987 | <0.001 | 90.8 | 93.2 | 90.8 | 93 |
| DBPHR | ||||||||
| Boys | 0.52 | 0.98 | 0.968−0.989 | <0.001 | 96.5 | 89.7 | 95.3 | 89.7 |
| Girls | 0.53 | 0.97 | 0.955−0.987 | <0.001 | 93.8 | 91.2 | 93.8 | 91.2 |
AUC=Area under the curve, BMI=Body mass index, SBP=Systolic blood pressure, DBP=Diastolic blood pressure, SBPHR=SBP to height ratio, DBPHR=DBP to height ratio, PPV=Positive predictive value, NPV=Negative predictive value, CI=Confidence interval
Discussion
Diagnosing HT in children is achieved by reading BP percentile charts. However, reading such charts can be complicated and intimidating to parents and people not versed in medical terminology. The BPHR has been developed as a simple, easy, inexpensive, and acceptable tool to diagnose EBP in children.[11] This study investigated the accuracy of the BPHR in diagnosing elevated BP in Indonesian children aged 8–11. We found that both the SBPHR and DBPHR had high AUC (>0.96), which resulted in high sensitivity (>90%) and specificity (86–93%). Our cutoffs for the SBPHR, DBPHR, sensitivity, and specificity were comparable to those noted by several earlier studies that focused on adolescents.[11,14,15,16]
A correlation analysis of SBPHR and DBPHR with potential influencing variables revealed that both measures correlated with most variables. However, SBPHR showed the strongest correlation with the SBP percentile, while DBPHR was most strongly correlated with the DBP percentile. Age and height, typically used to classify BP in children, did not demonstrate a strong correlation with SBPHR or DBPHR. Therefore, using sex-specific cutoff values for SBPHR and DBPHR can improve the accuracy of diagnosing HT in adolescents.
The AUC values that we found near the predetermined standard AUC value of 0.90 revealed that both the SBPHR and DBPHR had discriminatory power when diagnosing HT. The mean SBPHR in boys and girls was 0.75–0.79 (cutoff: 0.804) and 0.72–0.81 (0.831), respectively; the corresponding measurements for the DBPHR were 0.47–0.48 (0.519) and 0.49–0.50 (0.530). Compared to studies of adolescents in other countries, our findings revealed larger mean and cutoff SBPHR and DBPHR values.[11,14] As in previous studies, we found that optimum cutoff values tended to decrease in boys with increasing age and height. Our findings were consistent with an earlier study of Indonesian adolescents,[15,16] in which the mean and cutoff SBPHR and DBPHR values were similar.
Both the SBPHR and DBPHR are relatively accurate at diagnosing HT in children. We showed that the sensitivity and specificity of the optimum SBPHR cutoff values were 96.0% and 86.0% in boys and 90.8% and 93.2% in girls. The specificity of the optimum DBPHR cutoff values were 96.5% and 89.7% in boys and 93.8% and 91.2% in girls. These results are similar to those found by studies that examined the accuracy of the SBPHR and DBPHR in diagnosing HT in adolescents.[11,14,15,16]
Body size is believed to influence BP.[23,24] Since the girls in our study had smaller bodies than the boys across all age groups, we expected the girls to have lower BP than the boys. However, we found that girls’ SBP and DBP exceeded the boys. We have no explanation for this finding. This result might be related to the “White-Coat Hypertension” phenomenon.[25] The girls might have experienced more significant pressure in the physical examination process of their study than the boys. As a result, their mean SBP and DBP might have been pushed higher than the boys’ across all age groups.
This study has some limitations. First, the BP measurements were conducted only on one visit. The 2017 American Academy of Pediatrics Hypertension Clinical Guidelines recommend that BP measurements be performed over 3 days to reduce white-coat HT and overestimate the prevalence of HT.[10,26] Second, we measured BP using a digital oscillometric device. Such devices have been the subject of debate. Oscillometric devices are associated with ease of use and reduced observer/examiner bias, but they also have limitations. Digital oscillometric measurements are typically higher than the readings obtained by auscultation,[27,28] with variations reaching up to 10 mmHg.[29] Furthermore, normative BP data are obtained by auscultation using a mercury sphygmomanometer.[10] Therefore, the AAP recommends that if BP is elevated in a digital oscillometric reading, it should be confirmed using an auscultatory measurement.[10] Third, the possibility of white-coat HT cannot be ignored. This situation refers to a patient’s BP being elevated in a doctor’s office but normal in other settings.[25] However, we have tried to minimize white-coat HT by several endeavors, such as conducting three BP measurements in a comfortable room and inviting a teacher and school friends into the examination room to put students being examined at ease.
Conclusion
The BPHR is a simple, practical, easy-to-use diagnostic tool with high sensitivity and acceptable specificity for the detection of EBP in children aged 8–11. We determined BP in children using a BP value chart of age-, sex-, and height-specific percentiles. However, we should interpret the results of this study with caution because of the limitations of our investigation. Even so, we recommend the use of BPHR to screen for EBP in children aged 8–11 years. Follow-on studies will be necessary to address some of the issues of the limitations of this investigation and previous studies.
Conflicts of interest
There are no conflicts of interest.
Acknowledgment
The authors are sincerely grateful to the principals for granting them permission for the study and the students for agreeing to participate.
Funding Statement
This study was financially supported by Atma Jaya Catholic University of Indonesia.
References
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