- Email: [email protected]
The relationship of body mass index and blood pressure in primary care pediatric patients
THE RELATIONSHIP OF BODY MASS INDEX AND BLOOD PRESSURE IN PRIMARY CARE PEDIATRIC PATIENTS BONITA FALKNER, MD, SAMUEL S. GIDDING, MD, GABRIELA RAMIREZ-GARNICA, PHD, MPH, STACEY ARMATTI WILTROUT, MA, MS, DAVID WEST, MD, AND ELIZABETH B. RAPPAPORT, MD
Objective To determine whether an association of overweight, or risk of overweight, and blood pressure can be detected in children in the pediatric primary care practice setting.
Study design We examined electronic medical record (EMR) data from primary care practices on 18,618 children age 2 to 19 years. Each child was classified on the basis of age- and sex-specific body mass index (BMI) percentile as normal weight (BMI < 85th percentile), at risk for overweight (BMI > 85th and < 95th percentile), or overweight (BMI > 95th percentile). BMI Z-score and height Z-score were computed. Systolic and diastolic blood pressures were compared among age-sex-BMI groups. Results Among children in primary care pediatric practices, 16.7% were at risk of overweight and 20.2% were overweight. With increasing BMI status there was a significant increase in both systolic blood pressure (P < .001) and diastolic blood pressure (P < .001). The association of higher blood pressure with increasing BMI status was present in all age groups. Conclusions Clinical data from pediatric primary care practices verify the high prevalence of childhood overweight. The effect of overweight on blood pressure is present in childhood and can be detected even in children as young as 2 to 5 years. (J Pediatr 2006;148:195-200)
levated blood pressure is a major risk factor for cardiovascular disease and is linked to cardiovascular morbidity.1 Among US adults, the prevalence of hypertension has increased from 25.0% in 1988 to 28.7% in 2000, an increase related to the parallel increase in obesity.2 Higher blood pressure in childhood is predictive of sustained hypertension in young adulthood.3 New evidence indicates that high blood pressure at a young age is not benign. Recent findings demonstrate that higher blood pressure during adolescence is associated with an increase in left ventricular mass 4 and significant thickening of carotid arterial walls in healthy young adults.5 Recently, Muntner et al 6 examined trends in systolic and diastolic blood pressure in children and adolescents using the National Health and Nutrition Examination Survey (NHANES) data from 2 serially conducted cross-sectional studies. They reported that, following age, race/ethnicity, and sex standardization, systolic blood pressure was 1.4 mm Hg higher and diastolic blood pressure was 3.3 mmHg higher in 1999-2000 than in 1988-1994. This population increase in blood pressure among children and adolescents was statistically significant and was largely (but not entirely) due to the increased prevalence of overweight in children. The marked increase in adiposity among children and adolescents over the past few decades is well established. Health statistics show that the prevalence of overweight in US children age 6 to 11 years rose from 4% to 15.3% between 1963 and 2000. During the most recent decade, the prevalence of overweight also increased among very young children (age 2 to 5 years), from 7.2% to 10.4%.7,8 The purpose of this study was to determine whether an association between overweight, or risk of overweight, and blood pressure could be detected in children in the From the Departments of Medicine and pediatric primary care practice setting. It was of particular interest to determine whether Pediatrics, Thomas Jefferson University, this association could be detected in children under age 6 years. Growth and blood Philadelphia, Pennsylvania; the Alfred I. dupressure measurements obtained during scheduled health assessment visits to pediatric Pont Hospital for Children, Wilmington, Delaware; and the Nemours Foundation, primary care practices were examined. This information was systematically recorded in an Orlando, Florida. electronic medical record (EMR). Sex and insurance status were also examined as Submitted for publication Apr 14, 2005; last correlates of blood pressure in children. revision received Sep 2, 2005; accepted
E
BMI EMR NHANES
Body mass index Electronic medical record National Health and Nutrition Examination Survey
SES
Socioeconomic status
Oct 11, 2005. Reprint requests: Bonita Falkner, MD, 833 Chestnut St., Suite 700, Philadelphia, PA 19107. E-mail: [email protected]. 0022-3476/$ - see front matter Copyright © 2006 Elsevier Inc. All rights reserved. 10.1016/j.jpeds.2005.10.030
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METHODS Study Population The Nemours Foundation operates a network of pediatric practices throughout Delaware and southeastern Pennsylvania. These practices provide primary health care to approximately 15% of Delaware children from birth to age 19 years. The clinics are distributed throughout the state to provide easy access to Delaware children. The clinics are centrally administered, thereby somewhat reducing the practice variability that might be present in 10 independent private practices. Clinical and demographic data, including height, weight, and blood pressure, are routinely collected in an EMR and stored in a data warehouse, allowing analyses of the patient population. Institutional Review Board approval was obtained to perform a record review and an analysis of deidentified EMR data. For this study, we selected all children age 2 to 19 years who were examined during well-child visits in 2002 and for whom height, weight, blood pressure measurements, and information on insurance type were available. Data from acute care visits were not used. Because data on race and ethnicity were assigned by the registering clerk rather than by selfassignment, these data were deemed unsuitable for this study. If patients were seen on more than 1 occasion during 2002, we analyzed data from the most recent visit on record. A total of 19,121 children had height, weight, and blood pressure measured at the same visit. Of this group, 448 patients were excluded from analysis because values were considered to be implausible due to data entry error, and 55 were excluded for lack of insurance information. Data from a total of 18,618 patients were analyzed. Procedure Data on height, weight, and blood pressure were obtained during scheduled health assessment visits. Measurements were obtained by a nurse or medical assistant trained in pediatric height, weight, and blood pressure measurement and were entered into the EMR. Height was measured without shoes, and weight was measured without heavy clothing using either a digital or balance-beam scale. In 7 of the 10 practice sites, height was measured on a wall-mounted stadiometer. At the other 3 sites, height was obtained using the measuring device attached to the scale. Blood pressure was measured with the child in the seated position according to pediatric measurement guidelines3 by auscultation with an appropriate-size cuff and an aneroid sphygmomanometer. The fifth Korotkoff sound was used to determine diastolic blood pressure. At 1 site, approximately half of the children (⬍ 10% of the total cohort) had blood pressure measured using an electronic device (Dynamap). Data Analysis Children were stratified into the following age categories: 2 to 5 years, 6 to 10 years, 11 to 15 years, and 16 to 19 196
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years. They were classified on the basis of age- and sexspecific BMI percentile into 3 groups: BMI ⬍ 85th percentile, BMI ⬎ 85th and ⬍ 95th percentile, and BMI ⬎ 95th percentile.9 Data on insurance status were obtained from the Nemours administrative database (Health Care Software, Inc.). Insurance type was used as a surrogate for socioeconomic status (SES) and was classified as commercial/private or government/public. Blood pressure and BMI distributions in the cohort were compared with national reference standards.9,10 The mean blood pressure for each age–sex–BMI group was calculated. The effect of BMI category on mean systolic blood pressure and mean diastolic blood pressure in each age–sex group was analyzed by analysis of variance. The analytical strategy involved performing univariate analyses to assess confounding, examining scatterplots to visually evaluate the relationship between systolic and diastolic blood pressure and each predictor variable, and fitting models with the PROC REG and PROC GLM procedures in SAS (SAS Institute, Cary, NC). Height and BMI were converted to age- and sex-specific Z-scores. Interactions between BMI and age and between BMI and insurance status were evaluated. A polynomial regression model was fit for the dependent variables of systolic and diastolic blood pressure, including BMI Z-score, age, insurance status, sex, and height Z-score. Because BMI alone is not sufficient to explain the variance in blood pressure, height was added to the model, as suggested by Michels et al.11 In addition, due to the nonlinear relationship between blood pressure and height, height was fit using a fourth-degree polynomial term with lesser polynomial terms included in the model. The final model for the dependent variables of systolic and diastolic blood pressure also included age, sex, height Z-score, BMI Z-score, and insurance status. Data were analyzed using SPSS version 12 (SPSS Inc., Chicago, IL) and SAS version 9.01. Finally, the blood pressure tables from the Fourth Report on the Diagnosis, Evaluation, and Treatment of High Blood Pressure in Children and Adolescents 10 were used to identify patients with systolic and/or diastolic blood pressure at or above the 95th percentile.
RESULTS A total of 18,618 pediatric primary care patients were included in this analysis of EMR-derived data. The sample contained a similar number of males (n ⫽ 9897) and females (n ⫽ 8721). The sample number was balanced across the age strata, with the exception of 16- to 19-year age group, which had somewhat fewer subjects. The percentage of cases receiving commercial insurance (51.8%) was similar to the percentage of cases receiving Medicaid or other government support for health care (48.2%). Table I provides the mean and standard deviation for systolic blood pressure, diastolic blood pressure, height, and weight for males and females according to age group. The table shows the expected increases in both mean systolic blood pressure and mean diastolic blood pressure with age. Mean systolic blood pressure was slightly lower in females compared with males, whereas mean diastolic blood pressure was similar The Journal of Pediatrics • February 2006
Table I. Height, weight, and blood pressure by age group and Sex Age group (years) 2 to 5 6 to 10 11 to 15 16 to 19
Sex (n)
Height (cm)
Weight (kg)
Systolic blood pressure (mm Hg)
Diastolic blood pressure (mm Hg)
Male (3321) Female (3010) Male (3391) Female (3008) Male (2685) Female (2238) Male (500) Female (465)
104.4 ⫾ 8.4 104.1 ⫾ 8.6 130.8 ⫾ 10.6 130.6 ⫾ 11.3 157.8 ⫾ 12.2 156.0 ⫾ 8.8 173.4 ⫾ 9.3 161.6 ⫾ 7.4
18.5 ⫾ 4.3 18.2 ⫾ 4.6 32.3 ⫾ 11.3 32.8 ⫾ 12.1 56.0 ⫾ 20.2 57.6 ⫾ 18.8 73.5 ⫾ 19.8 66.6 ⫾ 20.2
90.0 ⫾ 11.2 88.6 ⫾ 10.8 98.9 ⫾ 11.4 97.6 ⫾ 11.7 109.6 ⫾ 13.2 107.9 ⫾ 12.5 120.1 ⫾ 13.1 112.8 ⫾ 12.8
53.1 ⫾ 8.8 52.6 ⫾ 8.2 58.5 ⫾ 8.4 58.0 ⫾ 8.4 63.5 ⫾ 8.7 63.2 ⫾ 8.4 66.0 ⫾ 8.8 65.4 ⫾ 8.9
Values are mean ⫾ standard deviation. ⴱ(n) ⫽ number of cases.
in males and females in each age group. The mean systolic and diastolic blood pressure values in this sample were similar to the blood pressure levels at the 50th percentile described in the national database on blood pressure in children and adolescents.10 The distribution of normal-weight children (BMI ⬍ 85th percentile), children at risk for overweight (BMI 85th to 94th percentile), and overweight (BMI ⱖ 95th percentile) for each age group is provided in Table II. Overall, 63.1% had BMI ⬍ 85th percentile, 16.7% were at risk for overweight, and 20.2% were overweight with BMI ⱖ 95th percentile. The proportion of children at risk for overweight was similar across the age groups. The percentage of children in the overweight group increased significantly with increasing age (P ⫽ .001). The prevalence of risk for overweight and overweight children in this sample was somewhat higher than the rates for risk of overweight and overweight reported from the 1999-2000 NHANES data.7 The mean systolic blood pressure and diastolic blood pressure values for each BMI and age group are provided in Table III. There was a statistically significant increase in both systolic blood pressure (P ⬎ .001) and diastolic blood pressure (P ⬎ .001) that corresponded with increasing BMI category. The mean systolic and diastolic blood pressure values were significantly higher in the overweight group compared with the normal-weight group, with intermediate values in the at risk for overweight group. The association between higher blood pressure and increasing BMI was present in all age groups and could be detected as early as age 2 to 5 years. Multivariable analyses were performed to assess the relative importance of age, BMI, height, sex, and insurance status (as a measure of SES) on systolic and diastolic blood pressure (Table IV). All of these variables but height Z-score 4 accounted for a significant portion of blood pressure variance (for systolic: r ⫽ 0.661, r2 ⫽ 0.437; for diastolic: r ⫽ 0.518, r2 ⫽ 0.269). Analysis of standardized and nonstandardized beta coefficients showed that the most important predictors, in descending order of significance, were age, BMI Z-score, height Z-score, insurance type, and sex. Female sex and, interestingly, lack of commercial insurance were protective against higher blood pressure.
The definition of hypertension in children and adolescents requires a systolic and/or diastolic blood pressure value ⱖ 95th percentile on at least 3 separate visits.10 Although the EMR data in this study included only a single blood pressure measurement, the data were examined to determine the prevalence of blood pressure elevation based on a single measurement. Overall, 7.2% of the entire sample of 18,618 children and adolescents had systolic and/or diastolic blood pressure values ⱖ 95th percentile. Systolic blood pressure was recorded in the elevated range in 6% of this pediatric primary care cohort, and diastolic blood pressure was recorded in the elevated range in 2%. Table V gives the percentage of males and females with a single systolic and/or diastolic blood pressure value ⱖ 95th percentile for each age and BMI group. The overall prevalence of high blood pressure increased with age in both males and females and also increased with increasing BMI.
DISCUSSION An examination of clinical data for more than 18,000 children and adolescents from EMR records in pediatric primary care practices identified high rates of both overweight and risk of overweight. Approximately 1/3 of children and adolescents, including very young children, have BMI ⬎ 85th percentile. Moreover, these data demonstrate a significant association between BMI and blood pressure detectable in all age groups, including very young children. Although this relationship has been well studied in older children and adolescents, information on toddlers and younger children has been limited. Compared with children with BMI ⬎ 85th percentile, both systolic blood pressure and diastolic blood pressure were higher in children with BMI ⬎ 85th and ⬍ 95th percentile and were highest in children with BMI ⱖ 95th percentile. These data demonstrate, for cardiovascular risk factor identification, the clinical usefulness of the new BMI growth charts introduced into clinical practice in this decade. This study is based on clinical practice data entered in EMRs, which is a novel source of data for clinical investigation. The application and use of EMRs is increasing due to improved technology and user acceptance. EMRs provide
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Table II. Sample size (n) and distribution (%) of overweight and at risk for overweight children by age group BMI < 85th percentile Age (years) 2 to 5 6 to 10 11 to 15 16 to 19 Total
85th to 94th percentile
> 95th percentile
1054 (16.7) 1054 (16.5) 852 (17.3) 161 (16.7) 3,121 (16.7)
1056 (16.7) 1356 (21.2) 1156 (23.5) 188 (19.5) 3,756 (20.2)
4221 (66.6) 3989 (62.3) 2915 (59.2) 616 (63.8) 11,741 (63.1)
Total 6331 (100) 6399 (100) 4923 (100) 965 (100) 18,618 (100)
Table III. Mean Blood Pressure in BMI, age, and sex Groups BMI %
Systolic blood pressure (mm Hg) Males 2 to 5 years 6 to 10 years 11 to 15 years 16 to 19 years* Females 2 to 5 years 6 to 10 years 11 to 15 years 16 to 19 years Diastolic blood pressure (mmHg) Males 2 to 5 years‡ 6 to 10 years 11 to 15 years 16 to 19 years* Females 2 to 5 years 6 to 10 years 11 to 15 years 16 to 19 years†
< 85th percentile
85th to 94th percentile
> 95th percentile
P value
89.1 ⫾ 11.1 (2197) 96.6 ⫾ 10.6 (2117) 107.0 ⫾ 12.1 (1660) 118.7 ⫾ 13.2 (333)
90.3 ⫾ 11.2 (549) 100.3 ⫾ 11.4 (563) 109.7 ⫾ 12.7 (430) 119.4 ⫾ 12.8 (75)
93.1 ⫾ 11.4 (575) 104.5 ⫾ 11.9 (711) 116.7 ⫾ 13.7 (595) 125.5 ⫾ 11.7 (92)
⬍.001 ⬍.001 ⬍.001 ⬍.001
87.5 ⫾ 10.3 (2024) 95.2 ⫾ 11.0 (1872) 104.6 ⫾ 11.4 (1255) 109.6 ⫾ 11.8 (283)
89.3 ⫾ 10.7 (505) 100.0 ⫾ 11.2 (491) 108.8 ⫾ 11.5 (422) 116.6 ⫾ 12.4 (86)
92.7 ⫾ 11.9 (481) 102.9 ⫾ 12.0 (645) 114.7 ⫾ 12.7 (561) 118.9 ⫾ 12.8 (96)
⬍.001 ⬍.001 ⬍.001 ⬍.001
52.3 ⫾ 8.6 (2197) 57.2 ⫾ 8.1 (2117) 62.1 ⫾ 8.3 (1660) 65.3 ⫾ 8.6 (333)
53.5 ⫾ 8.7 (549) 59.1 ⫾ 8.3 (563) 63.8 ⫾ 8.7 (430) 65.6 ⫾ 8.6 (75)
55.6 ⫾ 8.9 (575) 61.8 ⫾ 8.5 (711) 67.2 ⫾ 8.5 (595) 69.1 ⫾ 9.2 (92)
⬍.001 ⬍.001 ⬍.001 ⬍.001
51.8 ⫾ 8.0 (2024) 56.6 ⫾ 8.1 (1872) 61.2 ⫾ 7.9 (1255) 63.7 ⫾ 8.4 (283)
53.1 ⫾ 8.5 (505) 59.2 ⫾ 8.0 (491) 63.7 ⫾ 7.2 (422) 66.3 ⫾ 8.5 (86)
55.2 ⫾ 8.3 (481) 61.0 ⫾ 8.5 (645) 67.2 ⫾ 9.0 (561) 69.4 ⫾ 9.3 (96)
⬍.001 ⬍.001 ⬍.001 ⬍.001
Sample numbers are in parentheses. *⬍ 85th versus 85th to 94th; P ⫽ not significant. †⬍ 85th versus 85th–94th; P ⬍ .05.
greater capacity for retention and storage of large volumes of information and increased efficiency of information retrieval. Due to the large volume of clinical data that can be stored in EMRs and the ability to interact with clinicians in real time, there is also the potential to use EMRs to alert physicians to obesity-related morbidity and to examine the usefulness of EMRs in health care improvement. This study analyzed EMR data from pediatric primary care practices for children drawn from urban, suburban, and rural communities; thus the data are representative of the health profile of children under the supervision of primary care clinicians. Since the 1987 publication of the report of the Second 198
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Task Force on High Blood Pressure in Children and Adolescents, it has been recommended that blood pressure measurement be part of routine health assessment in children. This recommendation was reiterated in subsequent reports in 19963 and in 2004.10 The EMR data from the pediatric practices in our study reflect this standard of care in that blood pressure measurements were obtained and entered on most patients in each practice. The methods for blood pressure measurement described by each practice are also consistent with the recommendations. In these ambulatory clinics, most blood pressure measurements were obtained by auscultation and using a blood pressure cuff sized appropriately for the The Journal of Pediatrics • February 2006
Table IV. Multivariate Analysis on Determinants of Blood Pressure Unstandardized coefficients Model Systolic blood pressure (Constant) HtZ HtZ2 HtZ3 HtZ4 Age Sex ins-typ BMIZ Diastolic blood pressure (Constant) HtZ HtZ2 HtZ3 HtZ4 age sex ins-typ BMIZ
Standardized coefficients
B
Standard error
77.584 1.015 .407 ⫺.042 .001 2.116 ⫺1.813 3.293 2.283
.227 .110 .077 .019 .007 .020 .161 .162 .072
342.074 .078 9.240 .056 5.267 ⫺.019 ⫺2.257 .002 .179 .598 107.949 ⫺.062 ⫺11.237 .112 20.330 .183 31.856
.000 .000 .000 .024 .858 .000 .000 .000 .000
47.333 .787 .250 ⫺.031 ⫺.003 1.101 ⫺.530 .505 1.255
.169 .082 .058 .014 .005 .015 .121 .121 .054
.093 .052 ⫺.022 ⫺.008 .475 ⫺.028 .026 .153
279.277 9.591 4.329 ⫺2.213 ⫺.669 75.203 ⫺4.400 4.169 23.448
.000 .000 .000 .027 .504 .000 .000 .000 .000
Beta
t
P value
Variables are height Z-scores (HtZ), HtZ2, HtZ3, HtZ4; age in years (age); sex; insurance type (ins-type); and BMI Z-score (BMIZ)
Table V. Prevalence of systolic and/or diastolic blood pressure > 95th percentile BMI % group
Males 2 to 5 years 6 to 10 years 11 to 15 years 16 to 19 years Females 2 to 5 years 6 to 10 years 11 to 15 years 16 to 19 years
< 85th percentile
85th to 95th percentile
>95th percentile
Total
5.7% 4.6% 6.6% 9.6%
6.6% 6.6% 8.8% 13.3%
7.8% 10.8% 20.0% 18.5%
6.2% 6.3% 9.9% 11.8%
3.4% 4.3% 5.5% 4.6%
4.4% 9.0% 7.8% 16.3%
7.9% 11.2% 19.8% 20.8%
4.3% 6.5% 9.5% 10.1%
child’s upper arm. In this study, only a single blood pressure measurement, along with a single measurement of height and weight at the same visit, from each patient were used in the data analysis. Although the blood pressure measurements were obtained in a clinical setting and from several different practice sites, these data can be compared with national data.
The mean value for both systolic and diastolic blood pressure in each age stratum in our sample is within 1 to 2 mm Hg of the 50th percentile in the recent Working Group report.10 We also compared the standard deviation for systolic and diastolic blood pressure in each age stratum of our sample with the standard deviation for systolic and diastolic blood pressure in the national childhood blood pressure dataset provided in the Working Group report.10 These national childhood blood pressure data, based on more than 60,000 children, report standard deviations for systolic blood pressure of 10.7 mm Hg for males and 10.5 mm Hg for females and standard deviations of diastolic blood pressure of 11.6 mm Hg for males and 11.0 for females. The standard deviations in blood pressure values from our sample (Table III) are nearly identical. For normal-weight males and females (BMI ⬍ 85th percentile), the prevalence of systolic and/or diastolic blood pressure values ⱖ 95th percentile was close to the 5% for each age group except 16- to 19-year-old males (Table V). Therefore, the blood pressure data in this study, although derived from multiple primary care practices, appear to be comparable to the national data. The prevalence of overweight, detected from primary care practice records, in this large sample of children is higher than the prevalence of childhood overweight derived from the 1999-2000 NHANES. The NHANES is designed to be a representative sample of the US population. The distribution of subjects in the NHANES reflects the national demographics according to age, sex, race/ethnicity, and area of residence (urban/rural, region). Data from the most recent NHANES described a prevalence of overweight (BMI ⬎ 95th percentile) of just over 15% in both children and adolescents, with higher rates in minority groups than in non-Hispanic whites.7 The overall prevalence of overweight in our study was 20%. Although we do not have accurate information on race, it is possible that our sample included a larger portion of AfricanAmerican and Hispanic children compared with the NHANES, which could explain the somewhat higher prevalence of overweight in our study. Alternatively, the somewhat higher prevalence of overweight in our study may, to some extent, reflect the rapid upward trend in the rates of childhood obesity. A large proportion of the population variance in blood pressure can be explained by the small number of variables examined in our study. As expected, age and height are important correlates of blood pressure level. In younger children, because of accelerated maturation caused by obesity, changes in height may actually mask the impact of obesity on blood pressure. However, BMI Z-score was the second-most important component of the model, following age. These data are consistent with a secular trend toward increasing blood pressure in children, attributable to the rise in overweight.8,12 An unexpected finding was the association of noncommercial insurance with lower blood pressure. Absence of commercial insurance is one of many markers typically associated with lower SES, a condition often associated with higher blood pressure.
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The effect of increasing BMI on blood pressure in childhood demonstrated in the EMR data obtained from pediatric primary care practices reflects the reality confronted by primary care physicians caring for children. These primary care data show that overweight begins at a very young age and that the blood pressure gradient associated both with at risk for overweight and overweight is expressed throughout childhood. These findings are consistent with the concept that a reversal in the secular trend of increasing overweight would have an impact on the subsequent prevalence of hypertension.13 Developing and applying effective strategies for preventing childhood obesity beginning at very young ages is critical. But even if prevention of childhood obesity were immediately achievable, there are currently substantial numbers of children and adolescents with established obesity, many of whom have cardiovascular risk factors requiring more direct medical management. Based on a single blood pressure measurement in this population, ⬎ 7.5% of the 2- to 5-yearold children and 10% to 20% of the older children and adolescents had elevated blood pressure levels and required follow-up measurements.
REFERENCES 1. Vasan RS, Larson MG, Leip EP, Evans JC, O’Donnell CJ, Kannel WB, et al. Impact of high-normal blood pressure on the risk of cardiovascular disease. N Engl J Med 2001;345:1291-7. 2. Flegal KM, Carroll MD, Ogden C, Johnson CL. Prevalence and trends in obesity among US adults, 1999-2000. JAMA 2002;288:1723-7. 3. Update on the 1987 Task Force Report on High Blood Pressure in Children and Adolescents: a working group report from the National High
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Blood Pressure Education Program. National High Blood Pressure Education Program Working Group on Hypertension Control in Children and Adolescents. Pediatrics 1996;98:649-58. 4. Sorof JM, Alexandrov AV, Cardwell G, Portman RJ. Carotid artery intimal-medial thickness and left ventricular hypertrophy in children with elevated blood pressure. Pediatrics 2003;111:61-6. 5. Vos LE, Oren A, Uiterwaal C, Gorissen WH, Grobbee DE, Bots ML. Adolescent blood pressure and blood pressure tracking into young adulthood are related to subclinical atherosclerosis: the Atherosclerosis Risk in Young Adults (ARYA) study. Am J Hypertens 2003;16:549-55. 6. Muntner P, He J, Cutler JA, Wildman RP, Whelton PK. Trends in blood pressure among children and adolescents. JAMA 2004;291:2107-13. 7. Ogden CL, Flegal KM, Carroll MD, Johnson CL. Prevalence and trends in overweight among US children and adolescents, 1999-2000. JAMA 2002;288:1728-32. 8. Nesbitt SD, Ashaye MO, Stettler N, Sorof JM, Goran MI, Parekh R, et al. Overweight as a risk factor in children: a focus on ethnicity. Ethn Dis 2004;14:94-110. 9. Kuczmarski RJ, Ogden CL, Guo SS, Grummer-Strawn LM, Flegal KM, Mei Z, et al. 2000 CDC growth charts for the United States: methods and development. Vital Health Stat 2002;11:1-190. 10. National High Blood Pressure Education Program Working Group on High Blood Pressure in Children and Adolescents. The fourth report on the diagnosis, evaluation and treatment of high blood pressure in children and adolescents. Pediatrics 2004;114:555-76. 11. Michels KB, Greenland S, Rosner BA. Does body mass index adequately capture the relation of body composition and body size to health outcomes? Am J Epidemiol 1998;147:167-72. 12. Gidding SS, Bao W, Srinivasan SR, Berenson GS. Effects of secular trends in obesity on coronary risk factors in children: the Bogalusa Heart Study. J Pediatr 1995;127:868-74. 13. Duncan GE, Li SM, Zhou X-H. Prevalence and trends of a metabolic syndrome phenotype among U.S. adolescents, 1999-2000. Diabetes Care 2004;27:2438-43.
The Journal of Pediatrics • February 2006
Objective To determine whether an association of overweight, or risk of overweight, and blood pressure can be detected in children in the pediatric primary care practice setting.
Study design We examined electronic medical record (EMR) data from primary care practices on 18,618 children age 2 to 19 years. Each child was classified on the basis of age- and sex-specific body mass index (BMI) percentile as normal weight (BMI < 85th percentile), at risk for overweight (BMI > 85th and < 95th percentile), or overweight (BMI > 95th percentile). BMI Z-score and height Z-score were computed. Systolic and diastolic blood pressures were compared among age-sex-BMI groups. Results Among children in primary care pediatric practices, 16.7% were at risk of overweight and 20.2% were overweight. With increasing BMI status there was a significant increase in both systolic blood pressure (P < .001) and diastolic blood pressure (P < .001). The association of higher blood pressure with increasing BMI status was present in all age groups. Conclusions Clinical data from pediatric primary care practices verify the high prevalence of childhood overweight. The effect of overweight on blood pressure is present in childhood and can be detected even in children as young as 2 to 5 years. (J Pediatr 2006;148:195-200)
levated blood pressure is a major risk factor for cardiovascular disease and is linked to cardiovascular morbidity.1 Among US adults, the prevalence of hypertension has increased from 25.0% in 1988 to 28.7% in 2000, an increase related to the parallel increase in obesity.2 Higher blood pressure in childhood is predictive of sustained hypertension in young adulthood.3 New evidence indicates that high blood pressure at a young age is not benign. Recent findings demonstrate that higher blood pressure during adolescence is associated with an increase in left ventricular mass 4 and significant thickening of carotid arterial walls in healthy young adults.5 Recently, Muntner et al 6 examined trends in systolic and diastolic blood pressure in children and adolescents using the National Health and Nutrition Examination Survey (NHANES) data from 2 serially conducted cross-sectional studies. They reported that, following age, race/ethnicity, and sex standardization, systolic blood pressure was 1.4 mm Hg higher and diastolic blood pressure was 3.3 mmHg higher in 1999-2000 than in 1988-1994. This population increase in blood pressure among children and adolescents was statistically significant and was largely (but not entirely) due to the increased prevalence of overweight in children. The marked increase in adiposity among children and adolescents over the past few decades is well established. Health statistics show that the prevalence of overweight in US children age 6 to 11 years rose from 4% to 15.3% between 1963 and 2000. During the most recent decade, the prevalence of overweight also increased among very young children (age 2 to 5 years), from 7.2% to 10.4%.7,8 The purpose of this study was to determine whether an association between overweight, or risk of overweight, and blood pressure could be detected in children in the From the Departments of Medicine and pediatric primary care practice setting. It was of particular interest to determine whether Pediatrics, Thomas Jefferson University, this association could be detected in children under age 6 years. Growth and blood Philadelphia, Pennsylvania; the Alfred I. dupressure measurements obtained during scheduled health assessment visits to pediatric Pont Hospital for Children, Wilmington, Delaware; and the Nemours Foundation, primary care practices were examined. This information was systematically recorded in an Orlando, Florida. electronic medical record (EMR). Sex and insurance status were also examined as Submitted for publication Apr 14, 2005; last correlates of blood pressure in children. revision received Sep 2, 2005; accepted
E
BMI EMR NHANES
Body mass index Electronic medical record National Health and Nutrition Examination Survey
SES
Socioeconomic status
Oct 11, 2005. Reprint requests: Bonita Falkner, MD, 833 Chestnut St., Suite 700, Philadelphia, PA 19107. E-mail: [email protected]. 0022-3476/$ - see front matter Copyright © 2006 Elsevier Inc. All rights reserved. 10.1016/j.jpeds.2005.10.030
195
METHODS Study Population The Nemours Foundation operates a network of pediatric practices throughout Delaware and southeastern Pennsylvania. These practices provide primary health care to approximately 15% of Delaware children from birth to age 19 years. The clinics are distributed throughout the state to provide easy access to Delaware children. The clinics are centrally administered, thereby somewhat reducing the practice variability that might be present in 10 independent private practices. Clinical and demographic data, including height, weight, and blood pressure, are routinely collected in an EMR and stored in a data warehouse, allowing analyses of the patient population. Institutional Review Board approval was obtained to perform a record review and an analysis of deidentified EMR data. For this study, we selected all children age 2 to 19 years who were examined during well-child visits in 2002 and for whom height, weight, blood pressure measurements, and information on insurance type were available. Data from acute care visits were not used. Because data on race and ethnicity were assigned by the registering clerk rather than by selfassignment, these data were deemed unsuitable for this study. If patients were seen on more than 1 occasion during 2002, we analyzed data from the most recent visit on record. A total of 19,121 children had height, weight, and blood pressure measured at the same visit. Of this group, 448 patients were excluded from analysis because values were considered to be implausible due to data entry error, and 55 were excluded for lack of insurance information. Data from a total of 18,618 patients were analyzed. Procedure Data on height, weight, and blood pressure were obtained during scheduled health assessment visits. Measurements were obtained by a nurse or medical assistant trained in pediatric height, weight, and blood pressure measurement and were entered into the EMR. Height was measured without shoes, and weight was measured without heavy clothing using either a digital or balance-beam scale. In 7 of the 10 practice sites, height was measured on a wall-mounted stadiometer. At the other 3 sites, height was obtained using the measuring device attached to the scale. Blood pressure was measured with the child in the seated position according to pediatric measurement guidelines3 by auscultation with an appropriate-size cuff and an aneroid sphygmomanometer. The fifth Korotkoff sound was used to determine diastolic blood pressure. At 1 site, approximately half of the children (⬍ 10% of the total cohort) had blood pressure measured using an electronic device (Dynamap). Data Analysis Children were stratified into the following age categories: 2 to 5 years, 6 to 10 years, 11 to 15 years, and 16 to 19 196
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years. They were classified on the basis of age- and sexspecific BMI percentile into 3 groups: BMI ⬍ 85th percentile, BMI ⬎ 85th and ⬍ 95th percentile, and BMI ⬎ 95th percentile.9 Data on insurance status were obtained from the Nemours administrative database (Health Care Software, Inc.). Insurance type was used as a surrogate for socioeconomic status (SES) and was classified as commercial/private or government/public. Blood pressure and BMI distributions in the cohort were compared with national reference standards.9,10 The mean blood pressure for each age–sex–BMI group was calculated. The effect of BMI category on mean systolic blood pressure and mean diastolic blood pressure in each age–sex group was analyzed by analysis of variance. The analytical strategy involved performing univariate analyses to assess confounding, examining scatterplots to visually evaluate the relationship between systolic and diastolic blood pressure and each predictor variable, and fitting models with the PROC REG and PROC GLM procedures in SAS (SAS Institute, Cary, NC). Height and BMI were converted to age- and sex-specific Z-scores. Interactions between BMI and age and between BMI and insurance status were evaluated. A polynomial regression model was fit for the dependent variables of systolic and diastolic blood pressure, including BMI Z-score, age, insurance status, sex, and height Z-score. Because BMI alone is not sufficient to explain the variance in blood pressure, height was added to the model, as suggested by Michels et al.11 In addition, due to the nonlinear relationship between blood pressure and height, height was fit using a fourth-degree polynomial term with lesser polynomial terms included in the model. The final model for the dependent variables of systolic and diastolic blood pressure also included age, sex, height Z-score, BMI Z-score, and insurance status. Data were analyzed using SPSS version 12 (SPSS Inc., Chicago, IL) and SAS version 9.01. Finally, the blood pressure tables from the Fourth Report on the Diagnosis, Evaluation, and Treatment of High Blood Pressure in Children and Adolescents 10 were used to identify patients with systolic and/or diastolic blood pressure at or above the 95th percentile.
RESULTS A total of 18,618 pediatric primary care patients were included in this analysis of EMR-derived data. The sample contained a similar number of males (n ⫽ 9897) and females (n ⫽ 8721). The sample number was balanced across the age strata, with the exception of 16- to 19-year age group, which had somewhat fewer subjects. The percentage of cases receiving commercial insurance (51.8%) was similar to the percentage of cases receiving Medicaid or other government support for health care (48.2%). Table I provides the mean and standard deviation for systolic blood pressure, diastolic blood pressure, height, and weight for males and females according to age group. The table shows the expected increases in both mean systolic blood pressure and mean diastolic blood pressure with age. Mean systolic blood pressure was slightly lower in females compared with males, whereas mean diastolic blood pressure was similar The Journal of Pediatrics • February 2006
Table I. Height, weight, and blood pressure by age group and Sex Age group (years) 2 to 5 6 to 10 11 to 15 16 to 19
Sex (n)
Height (cm)
Weight (kg)
Systolic blood pressure (mm Hg)
Diastolic blood pressure (mm Hg)
Male (3321) Female (3010) Male (3391) Female (3008) Male (2685) Female (2238) Male (500) Female (465)
104.4 ⫾ 8.4 104.1 ⫾ 8.6 130.8 ⫾ 10.6 130.6 ⫾ 11.3 157.8 ⫾ 12.2 156.0 ⫾ 8.8 173.4 ⫾ 9.3 161.6 ⫾ 7.4
18.5 ⫾ 4.3 18.2 ⫾ 4.6 32.3 ⫾ 11.3 32.8 ⫾ 12.1 56.0 ⫾ 20.2 57.6 ⫾ 18.8 73.5 ⫾ 19.8 66.6 ⫾ 20.2
90.0 ⫾ 11.2 88.6 ⫾ 10.8 98.9 ⫾ 11.4 97.6 ⫾ 11.7 109.6 ⫾ 13.2 107.9 ⫾ 12.5 120.1 ⫾ 13.1 112.8 ⫾ 12.8
53.1 ⫾ 8.8 52.6 ⫾ 8.2 58.5 ⫾ 8.4 58.0 ⫾ 8.4 63.5 ⫾ 8.7 63.2 ⫾ 8.4 66.0 ⫾ 8.8 65.4 ⫾ 8.9
Values are mean ⫾ standard deviation. ⴱ(n) ⫽ number of cases.
in males and females in each age group. The mean systolic and diastolic blood pressure values in this sample were similar to the blood pressure levels at the 50th percentile described in the national database on blood pressure in children and adolescents.10 The distribution of normal-weight children (BMI ⬍ 85th percentile), children at risk for overweight (BMI 85th to 94th percentile), and overweight (BMI ⱖ 95th percentile) for each age group is provided in Table II. Overall, 63.1% had BMI ⬍ 85th percentile, 16.7% were at risk for overweight, and 20.2% were overweight with BMI ⱖ 95th percentile. The proportion of children at risk for overweight was similar across the age groups. The percentage of children in the overweight group increased significantly with increasing age (P ⫽ .001). The prevalence of risk for overweight and overweight children in this sample was somewhat higher than the rates for risk of overweight and overweight reported from the 1999-2000 NHANES data.7 The mean systolic blood pressure and diastolic blood pressure values for each BMI and age group are provided in Table III. There was a statistically significant increase in both systolic blood pressure (P ⬎ .001) and diastolic blood pressure (P ⬎ .001) that corresponded with increasing BMI category. The mean systolic and diastolic blood pressure values were significantly higher in the overweight group compared with the normal-weight group, with intermediate values in the at risk for overweight group. The association between higher blood pressure and increasing BMI was present in all age groups and could be detected as early as age 2 to 5 years. Multivariable analyses were performed to assess the relative importance of age, BMI, height, sex, and insurance status (as a measure of SES) on systolic and diastolic blood pressure (Table IV). All of these variables but height Z-score 4 accounted for a significant portion of blood pressure variance (for systolic: r ⫽ 0.661, r2 ⫽ 0.437; for diastolic: r ⫽ 0.518, r2 ⫽ 0.269). Analysis of standardized and nonstandardized beta coefficients showed that the most important predictors, in descending order of significance, were age, BMI Z-score, height Z-score, insurance type, and sex. Female sex and, interestingly, lack of commercial insurance were protective against higher blood pressure.
The definition of hypertension in children and adolescents requires a systolic and/or diastolic blood pressure value ⱖ 95th percentile on at least 3 separate visits.10 Although the EMR data in this study included only a single blood pressure measurement, the data were examined to determine the prevalence of blood pressure elevation based on a single measurement. Overall, 7.2% of the entire sample of 18,618 children and adolescents had systolic and/or diastolic blood pressure values ⱖ 95th percentile. Systolic blood pressure was recorded in the elevated range in 6% of this pediatric primary care cohort, and diastolic blood pressure was recorded in the elevated range in 2%. Table V gives the percentage of males and females with a single systolic and/or diastolic blood pressure value ⱖ 95th percentile for each age and BMI group. The overall prevalence of high blood pressure increased with age in both males and females and also increased with increasing BMI.
DISCUSSION An examination of clinical data for more than 18,000 children and adolescents from EMR records in pediatric primary care practices identified high rates of both overweight and risk of overweight. Approximately 1/3 of children and adolescents, including very young children, have BMI ⬎ 85th percentile. Moreover, these data demonstrate a significant association between BMI and blood pressure detectable in all age groups, including very young children. Although this relationship has been well studied in older children and adolescents, information on toddlers and younger children has been limited. Compared with children with BMI ⬎ 85th percentile, both systolic blood pressure and diastolic blood pressure were higher in children with BMI ⬎ 85th and ⬍ 95th percentile and were highest in children with BMI ⱖ 95th percentile. These data demonstrate, for cardiovascular risk factor identification, the clinical usefulness of the new BMI growth charts introduced into clinical practice in this decade. This study is based on clinical practice data entered in EMRs, which is a novel source of data for clinical investigation. The application and use of EMRs is increasing due to improved technology and user acceptance. EMRs provide
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Table II. Sample size (n) and distribution (%) of overweight and at risk for overweight children by age group BMI < 85th percentile Age (years) 2 to 5 6 to 10 11 to 15 16 to 19 Total
85th to 94th percentile
> 95th percentile
1054 (16.7) 1054 (16.5) 852 (17.3) 161 (16.7) 3,121 (16.7)
1056 (16.7) 1356 (21.2) 1156 (23.5) 188 (19.5) 3,756 (20.2)
4221 (66.6) 3989 (62.3) 2915 (59.2) 616 (63.8) 11,741 (63.1)
Total 6331 (100) 6399 (100) 4923 (100) 965 (100) 18,618 (100)
Table III. Mean Blood Pressure in BMI, age, and sex Groups BMI %
Systolic blood pressure (mm Hg) Males 2 to 5 years 6 to 10 years 11 to 15 years 16 to 19 years* Females 2 to 5 years 6 to 10 years 11 to 15 years 16 to 19 years Diastolic blood pressure (mmHg) Males 2 to 5 years‡ 6 to 10 years 11 to 15 years 16 to 19 years* Females 2 to 5 years 6 to 10 years 11 to 15 years 16 to 19 years†
< 85th percentile
85th to 94th percentile
> 95th percentile
P value
89.1 ⫾ 11.1 (2197) 96.6 ⫾ 10.6 (2117) 107.0 ⫾ 12.1 (1660) 118.7 ⫾ 13.2 (333)
90.3 ⫾ 11.2 (549) 100.3 ⫾ 11.4 (563) 109.7 ⫾ 12.7 (430) 119.4 ⫾ 12.8 (75)
93.1 ⫾ 11.4 (575) 104.5 ⫾ 11.9 (711) 116.7 ⫾ 13.7 (595) 125.5 ⫾ 11.7 (92)
⬍.001 ⬍.001 ⬍.001 ⬍.001
87.5 ⫾ 10.3 (2024) 95.2 ⫾ 11.0 (1872) 104.6 ⫾ 11.4 (1255) 109.6 ⫾ 11.8 (283)
89.3 ⫾ 10.7 (505) 100.0 ⫾ 11.2 (491) 108.8 ⫾ 11.5 (422) 116.6 ⫾ 12.4 (86)
92.7 ⫾ 11.9 (481) 102.9 ⫾ 12.0 (645) 114.7 ⫾ 12.7 (561) 118.9 ⫾ 12.8 (96)
⬍.001 ⬍.001 ⬍.001 ⬍.001
52.3 ⫾ 8.6 (2197) 57.2 ⫾ 8.1 (2117) 62.1 ⫾ 8.3 (1660) 65.3 ⫾ 8.6 (333)
53.5 ⫾ 8.7 (549) 59.1 ⫾ 8.3 (563) 63.8 ⫾ 8.7 (430) 65.6 ⫾ 8.6 (75)
55.6 ⫾ 8.9 (575) 61.8 ⫾ 8.5 (711) 67.2 ⫾ 8.5 (595) 69.1 ⫾ 9.2 (92)
⬍.001 ⬍.001 ⬍.001 ⬍.001
51.8 ⫾ 8.0 (2024) 56.6 ⫾ 8.1 (1872) 61.2 ⫾ 7.9 (1255) 63.7 ⫾ 8.4 (283)
53.1 ⫾ 8.5 (505) 59.2 ⫾ 8.0 (491) 63.7 ⫾ 7.2 (422) 66.3 ⫾ 8.5 (86)
55.2 ⫾ 8.3 (481) 61.0 ⫾ 8.5 (645) 67.2 ⫾ 9.0 (561) 69.4 ⫾ 9.3 (96)
⬍.001 ⬍.001 ⬍.001 ⬍.001
Sample numbers are in parentheses. *⬍ 85th versus 85th to 94th; P ⫽ not significant. †⬍ 85th versus 85th–94th; P ⬍ .05.
greater capacity for retention and storage of large volumes of information and increased efficiency of information retrieval. Due to the large volume of clinical data that can be stored in EMRs and the ability to interact with clinicians in real time, there is also the potential to use EMRs to alert physicians to obesity-related morbidity and to examine the usefulness of EMRs in health care improvement. This study analyzed EMR data from pediatric primary care practices for children drawn from urban, suburban, and rural communities; thus the data are representative of the health profile of children under the supervision of primary care clinicians. Since the 1987 publication of the report of the Second 198
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Task Force on High Blood Pressure in Children and Adolescents, it has been recommended that blood pressure measurement be part of routine health assessment in children. This recommendation was reiterated in subsequent reports in 19963 and in 2004.10 The EMR data from the pediatric practices in our study reflect this standard of care in that blood pressure measurements were obtained and entered on most patients in each practice. The methods for blood pressure measurement described by each practice are also consistent with the recommendations. In these ambulatory clinics, most blood pressure measurements were obtained by auscultation and using a blood pressure cuff sized appropriately for the The Journal of Pediatrics • February 2006
Table IV. Multivariate Analysis on Determinants of Blood Pressure Unstandardized coefficients Model Systolic blood pressure (Constant) HtZ HtZ2 HtZ3 HtZ4 Age Sex ins-typ BMIZ Diastolic blood pressure (Constant) HtZ HtZ2 HtZ3 HtZ4 age sex ins-typ BMIZ
Standardized coefficients
B
Standard error
77.584 1.015 .407 ⫺.042 .001 2.116 ⫺1.813 3.293 2.283
.227 .110 .077 .019 .007 .020 .161 .162 .072
342.074 .078 9.240 .056 5.267 ⫺.019 ⫺2.257 .002 .179 .598 107.949 ⫺.062 ⫺11.237 .112 20.330 .183 31.856
.000 .000 .000 .024 .858 .000 .000 .000 .000
47.333 .787 .250 ⫺.031 ⫺.003 1.101 ⫺.530 .505 1.255
.169 .082 .058 .014 .005 .015 .121 .121 .054
.093 .052 ⫺.022 ⫺.008 .475 ⫺.028 .026 .153
279.277 9.591 4.329 ⫺2.213 ⫺.669 75.203 ⫺4.400 4.169 23.448
.000 .000 .000 .027 .504 .000 .000 .000 .000
Beta
t
P value
Variables are height Z-scores (HtZ), HtZ2, HtZ3, HtZ4; age in years (age); sex; insurance type (ins-type); and BMI Z-score (BMIZ)
Table V. Prevalence of systolic and/or diastolic blood pressure > 95th percentile BMI % group
Males 2 to 5 years 6 to 10 years 11 to 15 years 16 to 19 years Females 2 to 5 years 6 to 10 years 11 to 15 years 16 to 19 years
< 85th percentile
85th to 95th percentile
>95th percentile
Total
5.7% 4.6% 6.6% 9.6%
6.6% 6.6% 8.8% 13.3%
7.8% 10.8% 20.0% 18.5%
6.2% 6.3% 9.9% 11.8%
3.4% 4.3% 5.5% 4.6%
4.4% 9.0% 7.8% 16.3%
7.9% 11.2% 19.8% 20.8%
4.3% 6.5% 9.5% 10.1%
child’s upper arm. In this study, only a single blood pressure measurement, along with a single measurement of height and weight at the same visit, from each patient were used in the data analysis. Although the blood pressure measurements were obtained in a clinical setting and from several different practice sites, these data can be compared with national data.
The mean value for both systolic and diastolic blood pressure in each age stratum in our sample is within 1 to 2 mm Hg of the 50th percentile in the recent Working Group report.10 We also compared the standard deviation for systolic and diastolic blood pressure in each age stratum of our sample with the standard deviation for systolic and diastolic blood pressure in the national childhood blood pressure dataset provided in the Working Group report.10 These national childhood blood pressure data, based on more than 60,000 children, report standard deviations for systolic blood pressure of 10.7 mm Hg for males and 10.5 mm Hg for females and standard deviations of diastolic blood pressure of 11.6 mm Hg for males and 11.0 for females. The standard deviations in blood pressure values from our sample (Table III) are nearly identical. For normal-weight males and females (BMI ⬍ 85th percentile), the prevalence of systolic and/or diastolic blood pressure values ⱖ 95th percentile was close to the 5% for each age group except 16- to 19-year-old males (Table V). Therefore, the blood pressure data in this study, although derived from multiple primary care practices, appear to be comparable to the national data. The prevalence of overweight, detected from primary care practice records, in this large sample of children is higher than the prevalence of childhood overweight derived from the 1999-2000 NHANES. The NHANES is designed to be a representative sample of the US population. The distribution of subjects in the NHANES reflects the national demographics according to age, sex, race/ethnicity, and area of residence (urban/rural, region). Data from the most recent NHANES described a prevalence of overweight (BMI ⬎ 95th percentile) of just over 15% in both children and adolescents, with higher rates in minority groups than in non-Hispanic whites.7 The overall prevalence of overweight in our study was 20%. Although we do not have accurate information on race, it is possible that our sample included a larger portion of AfricanAmerican and Hispanic children compared with the NHANES, which could explain the somewhat higher prevalence of overweight in our study. Alternatively, the somewhat higher prevalence of overweight in our study may, to some extent, reflect the rapid upward trend in the rates of childhood obesity. A large proportion of the population variance in blood pressure can be explained by the small number of variables examined in our study. As expected, age and height are important correlates of blood pressure level. In younger children, because of accelerated maturation caused by obesity, changes in height may actually mask the impact of obesity on blood pressure. However, BMI Z-score was the second-most important component of the model, following age. These data are consistent with a secular trend toward increasing blood pressure in children, attributable to the rise in overweight.8,12 An unexpected finding was the association of noncommercial insurance with lower blood pressure. Absence of commercial insurance is one of many markers typically associated with lower SES, a condition often associated with higher blood pressure.
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The effect of increasing BMI on blood pressure in childhood demonstrated in the EMR data obtained from pediatric primary care practices reflects the reality confronted by primary care physicians caring for children. These primary care data show that overweight begins at a very young age and that the blood pressure gradient associated both with at risk for overweight and overweight is expressed throughout childhood. These findings are consistent with the concept that a reversal in the secular trend of increasing overweight would have an impact on the subsequent prevalence of hypertension.13 Developing and applying effective strategies for preventing childhood obesity beginning at very young ages is critical. But even if prevention of childhood obesity were immediately achievable, there are currently substantial numbers of children and adolescents with established obesity, many of whom have cardiovascular risk factors requiring more direct medical management. Based on a single blood pressure measurement in this population, ⬎ 7.5% of the 2- to 5-yearold children and 10% to 20% of the older children and adolescents had elevated blood pressure levels and required follow-up measurements.
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