Abstract
Blood pressure (BP) is expected to have increased over time in children in most countries due to the increasing prevalence of childhood obesity worldwide. The authors conducted a systematic review of studies assessing secular trends in BP in children and adolescents. Of 1739 citations screened, the authors identified 18 studies including 2 042 470 participants examined between 1963 and 2012. Thirteen studies were conducted in high‐income countries, five in middle‐income countries, and none in low‐income countries. The prevalence of overweight or obesity increased in 17 studies and decreased in one study. BP decreased over time in 13 studies, increased in four, and did not change in one. These findings suggest that secular trends in BP do not mirror secular trends in overweight. This implies that other factors mitigate the effect of overweight on BP in children and adolescents.
Keywords: adolescents, children, hypertension, secular trends
1. Background
Elevated blood pressure (BP) is a major cause of death and morbidity worldwide. It is a leading risk factor for cardiovascular disease in adults.1 Children with elevated BP have an increased risk of having hypertension as adults2, 3 and can develop target organ damage such as left ventricular hypertrophy or atherosclerosis early in life.3 In adults, mean BP has decreased in many high‐income and middle‐income countries since a few decades, while an upward trend has been found in several low‐income countries.4 This decrease in middle‐ and high‐income countries may be partly explained by some favorable broad population‐based changes in dietary and other factors influencing BP and by improved detection and treatment of hypertension over time.5
In children, secular trends in BP are less well described.6, 7, 8, 9 Previous studies have suggested that BP may have decreased in the United States and in several European countries between 1948 and 1998 among children.6, 10 More recently, different trends were observed in different countries. While BP increased in children in China11, 12, 13 and in Greece,14 it did not increase or decreased in several countries, eg, Seychelles,15 Japan,16, 17 and Korea.18 In the United States, some studies documented upward trends in BP10, 19 while others, surprisingly, did not.20, 21, 22, 23 One study also showed different secular trends in boys and in girls in the United States.24 The reasons for this heterogeneity are unknown. Therefore, to describe and better understand worldwide secular trends in BP in children and adolescents, we conducted a systematic review of studies assessing such trends.
2. Methods
We conducted a systematic review following a detailed protocol and analysis plan, consistent with the meta‐analysis of observational studies in epidemiology (MOOSE) guidelines for meta‐analyses and systematic reviews of observational studies25 and using methods outlined in the Cochrane Handbook for Systematic Reviews of Interventions.26 The research consisted of the following steps: (1) systematic literature searches; (2) selection of study included; (3) data extraction; and (4) statistical analyses.
2.1. Systematic literature searches
We conducted a systematic search of the electronic databases MEDLINE via PubMed (1950–September 2015), CINAHL (1937–September 2015), Embase (1947–September 2015), and Web of Sciences (1975–September 2015) for studies assessing trends in BP in children. In addition, we conducted a search in Google Scholar and a hand search of bibliographies in all key retrieved articles. We considered publications in English, French, or German. A librarian helped to define search terms and to conduct the electronic literature search.
We used PubMed search syntax as the basis for all search strategies, using Medical Subject Headings (MeSH) and text terms with Boolean operators. MeSH terms included children‐related terms (“children,” “child,” “adolescent,” “teenagers,” “teens”); BP‐related terms (“high, elevated, increase, rising,” “blood pressure,” “BP,” “hypertension”); and trend‐related terms (“trends,” “trend study,” “trend studies,” “over time,” “year,” “period”). The studies with the MeSH terms “clinical trials” and “animals” were excluded from the search. The detailed search strategy is available upon request.
2.2. Study selection
Two reviewers (CR and AC) independently screened titles, abstracts, and full articles from the literature search to determine eligibility (Figure 1). Studies were included if: (1) they reported the mean level of BP on at least two different points in time; (2) they were conducted in children and adolescents (0–19 years); (3) they targeted a defined geographic region (ie, a state, a region, a province, a country) using a (repeated) cross‐sectional design and a population‐ or school‐based sampling; and (4) they were written in English, French, or German.
Figure 1.
Flow diagram of studies assessed and included. BP indicates blood pressure
Studies were excluded if their samples came from hospitals or specific tertiary referral clinical centers. If some studies used data from the same source (eg, from a national survey), these data were used only once. Disagreements about study selection was solved through discussion between the two reviewers.
2.3. Data extraction
Two reviewers (CR and AC) independently extracted data from the selected studies using a standardized extraction form. The following characteristics were abstracted from each study: (1) study authors and country and year of publication; (2) study characteristics (study period and design, sampling); (3) characteristics of the participants (number, age, sex); and (4) methods of BP measurement (use of oscillometric vs auscultatory devices, clinical validation of the device, training or certification of the assessor, use of standardized protocol, cuff size, number of visits and readings at each visits).
We built a quality score for the BP measurement method based on the following items: (1) description of the device used (clinically validated oscillometric or auscultatory); (2) training of the BP assessors; (3) use of a standardized measurement protocol; and (4) use of an appropriate cuff size in relation to arm circumference. If three or four items were correctly reported, the quality of BP measurement method was considered as high. If two or fewer items were correctly reported, the quality was considered as low.
2.4. Statistical analysis
We reported the prevalence of overweight and obesity or the mean body mass index (BMI) at the initial and the final study periods and the change between these two study periods in percent per year or kg/m2 per year. For BP values, we reported the prevalence of elevated BP or mean BP at the initial and the final study periods and the change between these two study periods in percent per year or mm Hg per year. Data were not pooled as study methods and periods differed largely across studies.
3. Results
Figure 1 shows the selection process of studies included in this review. Some 1739 records were identified, including 482 duplicates. After a first screening of titles and abstracts, 43 potentially relevant full‐text articles were reviewed for eligibility. Of these 43 studies, 15 were included. Three additional studies were found by manual searches. Finally, 18 studies were included.
Table 1 shows the main characteristics of the 18 included studies. They were conducted between 1963 and 2012. Some 13 studies were conducted in high‐income countries (Austria, Canada, Germany, two in Greece, Ireland, Japan, Russia, South Korea, Taiwan, and three in the United States),3, 10, 14, 17, 18, 20, 23, 28 five in middle‐income countries (Turkey, Seychelles, and three in China),12, 13, 15, 30 and none in low‐income countries.27 Some 13 studies were school‐based3, 10, 12, 14, 15, 17, 28, 30 and five were population‐based.13, 18, 20, 23, 36 The total number of participants was 2 042 470, with a median number per study of 8401 (range: 780–1 010 153). The participants were aged 4 to 19 years. The participation rate was reported in only six of 18 studies. When reported, the participation was relatively high.
Table 1.
Characteristics of the included studies
| First Author, Year of Publication | Country, Continent | Study Period | Sampling | Participation Rate | Participants, No. | Age, y |
|---|---|---|---|---|---|---|
| Agirbasli, 200830 | Turkey, Europe, and Asia | 1989–2005 | School‐based, unclear sampling strategy | No data | 1313 | 15–17 |
| Chiolero, 200915 | Seychelles, Africa (M) | 1998–2006 | School‐based, whole population | 79% | 25 586 | 4–18 |
| Din‐Dzietham, 200710 | United States, America (H) | 1963–2002 | School‐based, random selection | No data | 26 405 | 8–17 |
| Dong, 201529 | China, Asia (M) | 1985‐2010 | School‐based, whole population | No data | 1 010 153 | 8–17 |
| Freedman, 201220 | United States, America (H) | 1974–1993 | Population‐based, unclear sampling strategy | No data | 11 478 | 5–17 |
| Haas, 201233 | Germany, Europe (H) | 1994–2003 | School‐based, unclear sampling strategy | No data | 2228 | 1st grade (around 6 y) |
| Khang, 201118 | South Korea, Asia (H) | 1998–2008 | Population‐based, random selection | 1998: 86.5% 2001: 77.3%2005: 70.2%2007: 65.8%2008: 74.3% | 5909 | 10–19 |
| Kollias, 200914 | Greece, Europe (H) | 2004–2007 | School‐based, unclear sampling strategy | 2004: 75%,2007: 94% | 1004 | 12–17 |
| Lin, 201228 | Taiwan, Asia (H) | 1996–2006 | School‐based, random selection | 1996: 90.3%2006: 80.2% | 2557 | 12–14 |
| McCrindle, 20103 | Niagara, Ontario, Canada (H) | 2002–2008 | School‐based, whole population | No data | 20 719 | 14–15 |
| Rogacheva, 200734 | Russia, Europe, and Asia | 1995–2004 | School‐based, whole population | 1995: 95%2004: 85% | 780 | 15 |
| Shirasawa, 201217 | Ina, Japan, Asia (H) | 1994–2010 (4th grade) and 1997–2010 (7th grade) | School‐based, whole population | 99.3% | 10 894 | 9–10 and 12–13 |
| Smpokos, 201135 | Greece, Europe (H) | 1992–2007 | School‐based, random selection | No data | 967 | 5–8 |
| Wallner, 201036 | Austria, Europe (H) | 1986–2005 | Population‐based, whole population | No data | 879 660 | 18 |
| Watkins, 200432 | Ireland, Europe (H) | 1989–2001 | School‐based, random selection | No data | 3007 | 12 or 15 |
| Xi, 201313 | China, Asia (M) | 1993–2009 | Population‐based, random selection | No data | 2992 | 6–17 |
| Xi, 201623 | United States, America (H) | 1999–2012 | Population‐based, random selection | No data | 14 270 | 8–17 |
| Zhang, 201231 | China, Asia (M) | 2000–2010 | School‐based, random selection | No data | 22 548 | 7–17 |
Abbreviations: M, middle‐income countries; H, high‐income countries (World Bank classification).
Table 2 shows the methods of BP measurement. The auscultatory method was used in 17 studies3, 10, 12, 13, 14, 17, 18, 20 and the oscillometric method in one study.15 In 11 studies, trained clinical staff measured BP using a standardized protocol.10, 12, 13, 15, 18, 20, 23, 30 In 11 studies, the cuff size was based on arm circumference.3, 10, 12, 14, 15, 18, 20, 23 In the remaining seven studies,13, 17, 28, 32, 34, 35, 36 other criteria were used to choose cuff size or only one cuff was available. All BP measurements were taken during a single visit. At this visit, between one and six BP readings were recorded. Most of the studies averaged the different readings to determine BP values. In some studies, one or several items regarding BP measurement methods were not reported. The quality of BP measurement was considered as high in 11 studies (score of 3 or 4)10, 12, 13, 15, 17, 18, 20, 23 and low in seven studies (score of 1 or 2).3, 14, 28, 30, 33, 35, 36 No study had a quality score of 0.
Table 2.
BP measurement methods
| First Author, Year of Publication | Auscultatory or Oscillometric Method | Training of Clinical Officer | Standardized Protocol | Cuff Size | Quality Score for BP Measurement Method | Number of Visits (V) and Readings (R) at Each Visit | Comments |
|---|---|---|---|---|---|---|---|
| Agirbasli, 200830 | Auscultatory | No information | Yes | Medium‐sized cuff (arm circumference: 22–32 cm) | 2 | V: 1; R: 3 | BP: average of 2 readings |
| Chiolero, 200915 | Oscillometric (Omron M5; clinically validated) | Yes | Yes | Based on arm circumference | 4 | V: 1; R: 2 | Children could be examined more than once (1 visit every 3 or 4 y); BP: average of 2 readings at 1‐min interval |
| Din‐Dzietham, 200710 | Auscultatory | Yes | Yes | Cuff of appropriate size based on arm circumference only since NHANES III (1988–1994) | 4 | V: 1; R: 3–6 | BP measurements methods varied over time and between surveys; BP: average of all readings; SBP: K1; DBP: K4 or K5 |
| Dong, 201529 | Auscultatory | Yes | Yes | Cuff of appropriate size based on arm circumference | 4 | V: 1; R: 3 | BP: average of 3 readings; SBP: K1; DBP: K5 |
| Freedman, 201220 | Auscultatory | Yes | Yes | Cuff of appropriate size based on arm circumference | 4 | V: 1; R: 6 (2×3 R by 2 trained observers) | BP: average of the 6 readings; DBP: K4 |
| Haas, 201233 | Not reported | Yes | No information | Cuff of appropriate size based on arm circumference | 2 | V: 1; R: not reported | |
| Khang, 201118 | Auscultatory | Yes | Yes | Based on arm circumference | 4 | V: 1; R: 2‐3 | BP: average of the 2 first readings; SBP: K1; DBP: K5 |
| Kollias, 200914 | Auscultatory | No information | No information | Cuff of appropriate size based on arm circumference | 2 | V: 1; R:3 | BP: average of 3 readings |
| Lin, 201228 | Auscultatory | No information | No information | Cuff of appropriate size | 2 | V: 1; R: 2 | BP: average of 2 readings; SBP: K1; DBP: K5 |
| McCrindle, 20103 | Not reported | No information | Yes | Cuff of appropriate size based on arm circumference | 2 | V: 1; R: 1–3 | BP: 1st reading; if BP ≥135/85 mm Hg, BP was measured twice and the mean of the 3 readings was recorded |
| Rogacheva, 200734 | Auscultatory | Yes | Yes | One cuff (12×35 cm) | 3 | V: 1; R: 2 | BP: average of 2 readings; SBP: K1; DBP: K5 |
| Shirasawa, 201217 | Auscultatory | Yes | No information | Cuff of two sizes (9 cm and 12 cm) | 3 | V: 1; R: 1–3 | BP: 1st reading; if SBP/DBP >120/70 mm Hg, BP was measured 3 times and 3rd reading used |
| Smpokos, 201135 | Auscultatory | No information | No information | No information | 1 | V: 1; R: 3 | BP: average of 2 readings |
| Wallner, 201036 | Auscultatory | No information | No information | No information | 1 | V: 1; R: No information | – |
| Watkins, 200432 | Auscultatory | Yes | Yes | Same standard adult cuff used in each survey | 3 | V: 1; R: 2 (Survey of 1990) or 1 (Survey of 2000) | Survey of 1990: average of 2 readings |
| Xi, 201313 | Auscultatory | Yes | Yes | No information | 3 | V: 1; R: 3 | BP: average of the last 2 readings |
| Xi, 201623 | Auscultatory | Yes | Yes | Based on arm circumference | 4 | V. 1; R: 1–3 (84.6% had 3 R) | BP: average of the last 2 readings; DBP: K1; DBP: K4 or K5 |
| Zhang, 201231 | Auscultatory | Yes | Yes | Cuff of appropriate size based on arm circumference | 4 | V: 1; R: 2 | BP: average of the 2 readings; DBP: K5 |
Abbreviations: BP, blood pressure; DBP, diastolic blood pressure; K, Korotkoff phases; NHANES, National Health and Nutrition Examination Survey; SBP, systolic blood pressure.
Table 3 shows the prevalence of overweight and obesity or mean BMI at the initial and final study periods and the change between these two study periods. In 17 studies (94% of all studies), there was an increase in the prevalence of overweight/obesity or in BMI3, 10, 12, 13, 14, 15, 18, 20 (Figure 2). In two of these studies, there was an increase in all sex and age categories except for one category in which the prevalence of obesity decreased. A decrease in the prevalence of overweight/obesity was observed in one study (in Japan).17 The change in prevalence of overweight/obesity per year ranged from no change (0.0% per year)12 to an increase of +0.7% per year.15, 30, 35 The change in mean BMI per year ranged from –0.0517 to +0.13 kg/m2 per year.20
Table 3.
Trends in mean BMI or in the prevalence of overweight/obesity
| First Author, Year of Publication | Body Weight Category or Mean BMI | Sex | Initial Study Period | Final Study Period | Change in the prevalence of overweight or obesity, per year, or change in mean BMI, kg/m2 per year |
|---|---|---|---|---|---|
| Agirbasli, 200830 | Overweight (%) | 1989–1990 | 2004–2005 | ||
| Boys, aged 15 | 1.4 | 15.7 | +0.9% | ||
| Boys, aged 16 | 2.2 | 22.5 | +1.3% | ||
| Boys, aged 17 | 9.2 | 21 | +0.7% | ||
| Girls, aged 15 | 3.4 | 19 | +1.0% | ||
| Girls, aged 16 | 7.0 | 6.0 | −0.1% | ||
| Girls, aged 17 | 2.7 | 4.1 | +0.1% | ||
| Chiolero, 200915 | Overweight (% [SEM]) | 1998–2000 | 2004–2006 | ||
| Boys | 10.7 (0.4) | 16.0 (0.4) | +0.7% | ||
| Girls | 15.1 (0.5) | 19.5 (0.4) | +0.6% | ||
| Boys and girls | 12.9 (0.3) | 17.7 (0.3) | +0.6% | ||
| Din‐Dzietham, 200710 | Obesity (% [SEM]) | 1963–70 | 1999–2002 | ||
| Boys and girls; non‐Hispanic blacks | 5.4 (1.0) | 22.4 (1.2) | +0.4% | ||
| Boys and girls; non‐Hispanic whites | 5.6 (0.4) | 14.1 (1.7) | +0.2% | ||
| Dong, 201529 | Obesity (%) | 1985 | 2010 | ||
| Boys | 0.0 | 3.4 | +0.1% | ||
| Girls | 0.0 | 0.9 | 0.0% | ||
| Freedman, 201220 | BMI (kg/m2 [SD]) | 1974 | 1993 | ||
| Boys | 17.5 (3) | 20.0 (5) | +0.13 | ||
| Girls | 17.8 (4) | 20.2 (5) | +0.13 | ||
| Haas, 201233 | BMI (kg/m2 [SD]) | 1994 | 2003 | ||
| Boys | 15.8 (2.4) | 15.9 (2.4) | +0.01 | ||
| Girls | 15.6 (2.4) | 15.9 (1.9) | +0.03 | ||
| Khang, 201118 | BMI (kg/m2 [SEM]) | 1998 | 2007/8 | ||
| Boys and girls | 19.9 (0.1) | 21.0 (0.1) | +0.11 | ||
| Kollias, 200914 | Obesity (%) | 2004 | 2007 | ||
| Boys and girls | 9.2 | 10.9 | +0.6% | ||
| Lin, 201228 | BMI (kg/m2 [SEM]) | 1996 | 2006 | ||
| Boys | 21.1 (0.1) | 21.6 (0.2) | +0.05 | ||
| Girls | 20.7 (0.1) | 20.5 (0.2) | −0.02 | ||
| McCrindle, 20103 | Obesity (%) | 2002‐2003 | 2007‐2008 | ||
| Boys and girls | 12 | 13 | +0.2% | ||
| Rogacheva, 200734 | BMI (kg/m2 [SD]) | 1995 | 2004 | ||
| Boys | 19.6 (2.2) | 19.7 (2.1) | +0.01 | ||
| Girls | 19.7 (2.6) | 20.1 (2.6) | +0.04 | ||
| Shirasawa, 201217 | Change in mean BMI per year (kg/m2 per y [95% CI]) | 1994 | 2010 | ||
| Boys, 4th grade | NR | NR | −0.04 | ||
| Girls, 4th grade | NR | NR | −0.03 | ||
| 1997 | 2010 | ||||
| Boys, 7th grade | NR | NR | −0.05 | ||
| Girls, 7th grade | NR | NR | −0.04 | ||
| Smpokos, 201135 | Overweight | 1992–1993 | 2006–2007 | ||
| Boys | 19.4 | 33.7 | +1.0% | ||
| Girls | 24.5 | 34.6 | +0.7% | ||
| Wallner, 201036 | Obesity (%) | 1986–1990 | 2001–2005 | ||
| Boys | 2.6 | 5.4 | +0.1% | ||
| Watkins, 200432 | BMI (kg/m2 [SD]) | 1990 | 2000 | ||
| Boys, aged 12 | 18.9 (3.3) | 19.4 (3.4) | +0.05 | ||
| Girls, aged 12 | 19.2 (2.9) | 20.3 (3.6) | +0.11 | ||
| Boys, aged 15 | 20.4 (2.5) | 20.6 (3.3) | +0.02 | ||
| Girls, aged 15 | 21.9 (3.1) | 22.0 (3.4) | +0.01 | ||
| Xi, 201313 | Obesity (% [SEM]) | 1993 | 2009 | ||
| Boys and girl | 6.1 (0.6) | 13.1 (1.1) | +0.4% | ||
| Xi, 201632 | Obesity (% [SEM]) | 1999–2002 | 2009–2012 | ||
| Boys and girls | 17.1 (1.0) | 20.3 (0.7) | +0.2% | ||
| Zhang, 201231 | Overweight (% [95% CI]) | 2000 | 2010 | ||
| Boys | 12.8 (11.7–13.8) | 17.5 (16.2–18.7) | +0.5% | ||
| Girls | 7.7 (6.9–8.6) | 11.8 (10.8–12.9) | +0.4% | ||
| Boys and girls | 10.3 (9.6–10.9) | 14.7 (13.8–15.5) | +0.4% |
Abbreviations: BMI, body mass index; CI, confidence interval; NR, not reported; SD, standard deviation; SEM, standard error of the mean. Italicized values indicate change in mean BMI.
Figure 2.
Number of studies reporting an increase, a decrease, or no change in the prevalence of overweight/obesity or in mean body mass index (BMI) and in the prevalence of elevated blood pressure (BP) or in mean BP
Table 4 shows the prevalence of elevated BP or mean BP at the initial and final study periods and the change between these two study periods. The 13 studies (72% of all studies) showed a decrease in BP across time,10, 12, 15, 17, 18, 20, 23, 30 four (22%) an increase,13, 14, 28, 31 and one (6%) no change3 (Figure 2). Change in the prevalence of elevated BP per year ranged from −1.2% per year18 to +2.3% per year.14 The change in mean systolic BP per year ranged from −1.0932 to −0.13 mm Hg per year.36 The change in mean diastolic BP per year ranged from −1.0532 to 0.00 mm Hg per year.36
Table 4.
Trends in mean BP and prevalence of EBP
| First Author, Year of Publication | EBP Definition | Sex | Initial Study Period | Final Study Period | Change in the prevalence of EBP, per year, or change in mean BP, mm Hg per year | Adjustments |
|---|---|---|---|---|---|---|
| Agirbasli, 200830 | Change in mean BP/y (mm Hg/y [95% CI]) | 1989–1990 | 2004–2005 | Height and body mass index | ||
| Boys | NR | NR | −0.45/−0.36 | |||
| Girls | NR | NR | −0.35/−0.39 | |||
| Chiolero, 200915 | SBP/DBP ≥95th percentile (CDC definition; % [SEM]) | 1998–2000 | 2004–2006 | Based on sex‐, age‐, and height‐specific percentiles; further adjustment for age and height | ||
| Boys | 8.4 (0.4) | 6.9 (0.3) | −0.2% | |||
| Girls | 9.8 (0.4) | 7.8 (0.3) | −0.3% | |||
| Boys and girls | 9.1 (0.3) | 7.4 (0.2) | −0.2% | |||
| Din‐Dzietham, 200710 | EBP: SBP/DBP ≥95th percentile (CDC definition; % [SEM]) | 1963–1970 | 1999–2002 | Age | ||
| Boys and girls | 37.2 (0.7) | 3.7 (0.4) | −0.9% | |||
| Dong, 201529 | ESBP: systolic BP ≥95th percentile (% [SEM]) | 1985 | 2010 | Age, province, and urban/rural area | ||
| Boys | 5.1 (0.1) | 4.9 (0.1) | 0.0% | |||
| Girls | 5.5 (0.1) | 3.5 (0.1) | −0.1% | |||
| Freedman, 201220 | EBP: SBP/DBP ≥90th percentile (%) | 1974 | 1993 | Based on sex‐, age‐, and height‐specific percentiles; no further adjustment | ||
| Boys | 5.8 | 4.1 | −0.1% | |||
| Girls | 8.1 | 5.8 | −0.1% | |||
| Haas, 201233 | SBP/DBP (mean [SD]) | 1994 | 2003 | No adjustment | ||
| Boys | 105.1 (10.0)/70.7 (8.4) | 101.1 (7.7)/63.5 (5.7) | −0.44/−0.80 | |||
| Girls | 105.2 (10.0)/71.0 (8.5) | 100.9 (7.6)/64.1 (7.0) | −0.47/−0.76 | |||
| Khang, 201118 | EBP: SBP/DBP ≥95th percentile (CDC definition; % [95% CI]) | 1998 | 2007/8 | Based on sex‐, age‐, and height‐specific percentiles; further adjustment for age | ||
| Boys | 12.5 (10.2–14.8) | 4.4 (3.0–5.7) | −0.8% | |||
| Girls | 13.6 (11.1–16.0) | 1.9 (0.9–2.8) | −1.2% | |||
| Kollias, 200914 | EBP: SBP/DBP ≥95th percentile (CDC definition; %) | 2004 | 2007 | No adjustment | ||
| Boys and girls | 16.1 | 22.9 | 2.3% | |||
| Lin, 201228 | EBP: SBP/DBP ≥95th percentile (internal reference; %) | 1996 | 2006 | Sex, age, and height | ||
| Boys | 22.8 | 29.7 | 0.7% | |||
| Girls | 12.5 | 20.7 | 0.8% | |||
| McCrindle, 20103 | EBP: SBP/DBP ≥95th percentile (%) | 2002–2003 | 2007–2008 | Based on sex‐, age‐, and height‐specific percentile; no further adjustment | ||
| Boys and girls | 9 | 9 | 0.0% | |||
| Rogacheva, 200734 | SBP/DBP (mean [SD]) | 1995 | 2004 | No adjustment | ||
| Boys | 119 (12)/62 (10) | 116 (11)/59 (8) | −0.33/−0.33 | |||
| Girls | 115 (11)/64 (8) | 113 (9)/59 (8) | −0.22/−0.55 | |||
| Shirasawa, 201217 | Change in mean BP/y (mm Hg/y [95% CI]) | 1994 | 2010 | No adjustment | ||
| Boys (4th grade) | NR | NR | −0.35/−0.45 | |||
| Girls (4th grade) | NR | NR | −0.43/−0.43 | |||
| 1997 | 2010 | |||||
| Boys (7th grade) | NR | NR | −0.51/−0.42 | |||
| Girls (7th grade) | NR | NR | −0.47/−0.36 | |||
| Smpokos, 201135 | SBP/DBP (mean [SD]) | 1992–1993 | 2006–2007 | Age and weight | ||
| Boys | 104.3 (0.6)/60.4 (0.5) | 91.3 (0.8)/57.0 (0.6) | −0.86/−0.22 | |||
| Girls | 102.0 (0.7)/59.8 (0.5) | 88.9 (0.7)/55.3 (0.6) | −0.86/−0.30 | |||
| Wallner, 201036 | SBP/DBP (mean [SD]) | No adjustment | ||||
| 1986–1990 | 2001–2005 | |||||
| Boys | 128.2/71.5 | 126.30/71.5 | −0.13/0.00 | |||
| Watkins, 200432 | SBP/DBP (mean [SD]) | 1990 | 2000 | Estimates adjusted for age, height, BMI, physical activity, self‐reported smoking, and sampling stratification are similar to unadjusted estimates | ||
| Boys (aged 12) | 111.0 (11.6)/67.9 (9.5) | 102.9 (11.6)/59.1 (8.7) | −0.81/−0.88 | |||
| Girls (aged 12) | 111.5 (12.2)/70.9 (9.1) | 104.2 (12.1)/60.4 (8.6) | −0.73/−1.05 | |||
| Boys (aged 15) | 123.3 (12.4)/73.4 (9.4) | 113.2 (12.8)/62.5 (8.4) | −1.09/−0.98 | |||
| Girls (aged 15) | 118.3 (11.8)/74.3 (8.8) | 109.9 (11.1)/64.5 (8.7) | −0.84/−0.98 | |||
| Xi, 201313 | EBP: SBP or DBP ≥95th percentile (Chinese reference percentile; % [SEM]) | 1993 | 2009 | Sex, age, body mass index, and region | ||
| Boys | 8.2 (0.8) | 12.6 (1.5) | 0.3% | |||
| Girls | 7.0 (0.8) | 15.2 (1.8) | 0.5% | |||
| Xi, 201623 | EBP: SBP/DBP ≥95th percentile (CDC definition; % [SEM]) | 1999–2002 | 2009–2012 | Based on sex‐, age‐, and height‐specific percentile; no further adjustment | ||
| Boys | 3.2 (0.4) | 1.8 (0.5) | −0.1% | |||
| Girls | 2.6 (0.5) | 1.4 (0.2) | −0.1% | |||
| Boys and girls | 2.9 (0.3) | 1.6 (0.3) | −0.1% | |||
| Zhang, 201231 | EBP: SBP/DBP ≥95th percentile (CDC definition; % [95% CI]) | 2000 | 2010 | Based on sex‐, age‐, and height‐specific percentile; no further adjustment | ||
| Boys | 19.3 (18.1–20.5) | 26.1 (24.7–27.6) | 0.7% | |||
| Girls | 14.7 (13.6–15.8) | 19.8 (18.4–21.1) | 0.5% |
Abbreviations: BP, blood pressure; CDC, Centers for Disease Control and Prevention; CI, confidence interval; DBP, diastolic blood pressure; ESBP, elevated systolic blood pressure; EBP, elevated blood pressure; NR, not reported; SBP, systolic blood pressure; SD, standard deviation; SEM, standard error of the mean. Italicized values indicate change in mean BMI.
4. Discussion
We conducted a systematic review of studies assessing secular trends in BP in children and adolescents. We identified 18 studies including 2 042 470 participants examined between 1963 and 2012 in 13 different countries. While almost all of the studies showed an increase in overweight and obesity, a majority of studies showed a secular decrease in BP in children. Our findings suggest that BP secular trends in the pediatric population do not parallel trends in overweight. This implies that other factors mitigate the effect of excess body weight on BP in children and adolescents.
To our knowledge, this is the first systematic review assessing worldwide trends of BP in children and adolescents. We previously conducted a nonsystematic review suggesting that trends in BP in children were not directly correlated to trends in body weight in children.7 In a study that assessed BP trends in adults based on data collected since 1980 in numerous countries worldwide, Danaei and colleagues4 showed that the average level of BP has decreased in high‐ and middle‐income countries, while it has increased in low‐income countries. Our systematic review indicates that the pattern of BP trends in children was not clearly different according to a country's economic development. However, no data were available among children in low‐income countries. In adults, the wide use of antihypertensive treatment is likely to have contributed to the decrease in BP, especially in high‐income countries.5 Since very few children and adolescents are treated with medication for hypertension, observed secular trends cannot be explained, even partly, by medical treatment. This means that other preventive factors have to be involved in explaining the lack of upward BP trends in children.
It could have been possible to pool data across studies and perform a meta‐analysis; however, several issues prevented us from doing so. First, the periods covered were not identical across studies, and one can reasonably expect to have period‐specific trends (eg, as observed in the United States). Second, pooling would assume that trends are identical throughout countries, while it is clearly not the case. Third, the pooled estimates would reflect BP trends observed in the available studies, but it would not be possible to infer from this estimate the true average change in these countries or worldwide.
Study Strengths and Limitations
Our systematic review has several strengths. First, it is the largest review ever published on BP secular trends in children. Data include more than 2 million children and adolescents from 13 different countries. Second, we used a systematic review protocol following a high methodology standard (MOOSE, Cochrane) and we screened all major databases. Important limitations should also be noted. First, the quality of BP measurement methods was low in several studies, raising some concerns regarding direct comparison of BP measurements over time. This is a difficulty in BP trend studies since in most cases differences in measurement methods are expected. Standardized protocols and training of staff who measure BP are keys to improve quality. Second, the selected studies do not cover the whole world. We were able to identify data from 13 countries, and no study was conducted in low‐income countries. The participation rate was often not reported. Another limitation is the fact that we did not have information on other covariates that could influence BP such as diet (eg, salt and fruit and vegetable intake), physical activity, or birth weight. Finally, we could not analyze data at the individual level.
5. Perspectives
This systematic review updates knowledge on global trends in BP in children and adolescents. Studies are needed to examine trends in BP in children and adolescents in low‐income countries. The issue of directionality of secular trends of BP in children, and the relation with trends in the prevalence of overweight, is important to guide public health interventions in pediatric populations. It is fundamental to investigate other determinants of BP such as salt intake and physical activity, as well as more distal (ie, social) potential determinants and analyze their impact on BP at a population level. In a life course epidemiology perspective, such studies will help guide the primordial prevention of hypertension and cardiovascular diseases.37, 38
Financial Disclosure
The authors report no specific funding in relation to this research and no conflicts of interest to disclose.
Authors' Contributions
CR and AC designed the study protocol, conducted the systematic review, analyzed data, and drafted the first version of the manuscript. All other authors revised the study protocol, contributed to the analyses and interpretation of data, and revised the manuscript.
Acknowledgments
Not applicable.
Roulet C, Bovet P, Brauchli T, et al. Secular trends in blood pressure in children: A systematic review. J Clin Hypertens. 2017;19:488-497. 10.1111/jch.12955
References
- 1. Danaei G, Singh GM, Paciorek CJ, et al. The global cardiovascular risk transition: Associations of four metabolic risk factors with national income, urbanization, and Western diet in 1980 and 2008. Circulation. 2013;127:1493–1502. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2. Chen X, Wang Y. Tracking of blood pressure from childhood to adulthood: A systematic review and meta‐regression analysis. Circulation. 2008;117:3171–3180. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3. McCrindle BW, Manlhiot C, Millar K, et al. Population trends toward increasing cardiovascular risk factors in Canadian adolescents. J Pediatr. 2010;157:837–843. [DOI] [PubMed] [Google Scholar]
- 4. Danaei G, Finucane MM, Lin JK, et al. National, regional, and global trends in systolic blood pressure since 1980: Systematic analysis of health examination surveys and epidemiological studies with 786 country‐years and 5·4 million participants. Lancet. 2011;377:568–577. [DOI] [PubMed] [Google Scholar]
- 5. Chiolero A, Paccaud F, Bovet P. Upward hypertension trends: Changes in blood pressure or in Antihypertensive treatment. Hypertension. 2009;53:e22. [DOI] [PubMed] [Google Scholar]
- 6. McCarron P, Smith GD, Okasha M. Secular changes in blood pressure in childhood, adolescence and young adulthood: Systematic review of trends from 1948 to 1998. J Hum Hypertens. 2002;16:677–689. [DOI] [PubMed] [Google Scholar]
- 7. Chiolero A, Bovet P, Paradis G, Paccaud F. Has blood pressure increased in children in response to the obesity epidemic? Pediatrics. 2007;119:544–553. [DOI] [PubMed] [Google Scholar]
- 8. Chiolero A. Blood pressure in children and adolescents: population secular trends and cohort analyses. PhD thesis. Montreal, Canada: Department of Epidemiology & Biostatistics, McGill University; 2011. [Google Scholar]
- 9. Feber J, Ahmed M. Hypertension in children: New trends and challenges. Clin Sci. 2010;119:151–161. [DOI] [PubMed] [Google Scholar]
- 10. Din‐Dzietham R, Liu Y, Bielo MV, Shamsa F. High blood pressure trends in children and adolescents in national surveys, 1963 to 2002. Circulation. 2007;116:1488–1496. [DOI] [PubMed] [Google Scholar]
- 11. Liang YJ, Xi B, Hu YH, et al. Trends in blood pressure and hypertension among Chinese children and adolescents: China Health and Nutrition Surveys 1991‐2004. Blood Press. 2011;20:45–53. [DOI] [PubMed] [Google Scholar]
- 12. Dong B, Wang HJ, Wang Z, Liu JS, Ma J. Trends in blood pressure and body mass index among Chinese children and adolescents from 2005 to 2010. Am J Hypertens. 2013;26:997–1004. [DOI] [PubMed] [Google Scholar]
- 13. Xi B, Liang Y, Mi J. Hypertension trends in Chinese children in the national surveys, 1993 to 2009. Int J Cardiol. 2013;165:577–579. [DOI] [PubMed] [Google Scholar]
- 14. Kollias A, Antonodimitrakis P, Grammatikos E, Chatziantonakis N, Grammatikos EE, Stergiou GS. Trends in high blood pressure prevalence in Greek adolescents. J Hum Hypertens. 2009;23:385–390. [DOI] [PubMed] [Google Scholar]
- 15. Chiolero A, Paradis G, Madeleine G, Hanley JA, Paccaud F, Bovet P. Discordant secular trends in elevated blood pressure and obesity in children and adolescents in a rapidly developing country. Circulation. 2009;119:558–565. [DOI] [PubMed] [Google Scholar]
- 16. Kouda K, Nakamura H, Nishio N, Fujita Y, Takeuchi H, Iki M. Trends in body mass index, blood pressure, and serum lipids in Japanese children: Iwata population‐based annual screening (1993‐2008). J Epidemiol. 2010;20:212–218. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17. Shirasawa T, Ochiai H, Nishimura R, et al. Secular trends in blood pressure among Japanese schoolchildren: A population‐based annual survey from 1994 to 2010. J Epidemiol. 2012;22:448–453. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18. Khang YH, Lynch JW. Exploring determinants of secular decreases in childhood blood pressure and hypertension. Circulation. 2011;124:397–405. [DOI] [PubMed] [Google Scholar]
- 19. Rosner B, Cook NR, Daniels S, Falkner B. Childhood blood pressure trends and risk factors for high blood pressure: The NHANES experience 1988‐2008. Hypertension. 2013;62:247–254. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20. Freedman DS, Goodman A, Contreras OA, DasMahapatra P, Srinivasan SR, Berenson GS. Secular trends in BMI and blood pressure among children and adolescents: The Bogalusa Heart Study. Pediatrics. 2012;130:e159–e166. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21. Okosun IS, Seale JP, Boltri JM, Davis‐Smith M. Trends and clustering of cardiometabolic risk factors in American adolescents from 1999 to 2008. J Adolesc Health. 2012;50:132–139. [DOI] [PubMed] [Google Scholar]
- 22. Kit BK, Kuklina E, Carroll MD, Ostchega Y, Freedman DS, Ogden CL. Prevalence of and trends in dyslipidemia and blood pressure among US children and adolescents, 1999‐2012. JAMA Pediatr. 2015;169:272–279. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23. Xi B, Zhang T, Zhang M, et al. Trends in Elevated Blood Pressure Among US Children and Adolescents: 1999‐2012. Am J Hypertens. 2016;29:217–225. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24. Ostchega Y, Carroll M, Prineas RJ, McDowell MA, Louis T, Tilert T. Trends of elevated blood pressure among children and adolescents: Data from the National Health and Nutrition Examination Survey 1988–2006. Am J Hypertens. 2009;22:59–67. [DOI] [PubMed] [Google Scholar]
- 25. Stroup DF, Berlin JA, Morton SC, et al. Meta‐analysis of observational studies in epidemiology: A proposal for reporting. Meta‐analysis Of Observational Studies in Epidemiology (MOOSE) group. JAMA. 2000;283:2008–2012. [DOI] [PubMed] [Google Scholar]
- 26. Cochrane Handbook for Systematic Reviews of Interventions . www.cochrane.org/handbook. Accessed June 5, 2016.
- 27. World Bank Country and Lending Groups . https://datahelpdesk.worldbank.org/knowledgebase/articles/906519. Accessed June 5, 2016.
- 28. Lin FH, Chu NF, Hsieh AT. The trend of hypertension and its relationship to the weight status among Taiwanese young adolescents. J Hum Hypertens. 2012;26:48–55. [DOI] [PubMed] [Google Scholar]
- 29. Dong B, Wang Z, Song Y, Wang HJ, Ma J. Understanding trends in blood pressure and their associations with body mass index in Chinese children, from 1985 to 2010: a cross‐sectional observational study. BMJ Open. 2015;5:e009050. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30. Agirbasli M, Tanrikulu B, Arikan S, et al. Trends in body mass index, blood pressure and parental smoking habits in middle socio‐economic level Turkish adolescents. J Hum Hypertens. 2008;22:12–17. [DOI] [PubMed] [Google Scholar]
- 31. Zhang YX, Zhao JS, Sun GZ, Lin M, Chu ZH. Prevalent trends in relatively high blood pressure among children and adolescents in Shandong, China. Ann Hum Biol. 2012;39:259–263. [DOI] [PubMed] [Google Scholar]
- 32. Watkins D, McCarron P, Murray L, et al. Trends in blood pressure over 10 years in adolescents: Analyses of cross sectional surveys in the Northern Ireland Young Hearts project. BMJ. 2004;329:139. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33. Haas GM, Bertsch T, Schwandt P. Trends of components of the metabolic syndrome in German first graders throughout 10 years: The PEP family heart study. Cholesterol. 2012;2012:231962. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34. Rogacheva A, Laatikainen T, Tossavainen K, Vlasoff T, Panteleev V, Vartiainen E. Changes in cardiovascular risk factors among adolescents from 1995 to 2004 in the Republic of Karelia, Russia. Eur J Public Health. 2007;17:257–262. [DOI] [PubMed] [Google Scholar]
- 35. Smpokos EA, Linardakis M, Papadaki A, Kafatos A. Secular changes in anthropometric measurements and blood pressure in children of Crete, Greece, during 1992/93 and 2006/07. Prev Med. 2011;52:213–217. [DOI] [PubMed] [Google Scholar]
- 36. Wallner A, Hirz A, Schober E, Harbich H, Waldhoer T. Evolution of cardiovascular risk factors among 18‐year‐old males in Austria between 1986 and 2005. Wien Klin Wochenschr. 2010;122:152–158. [DOI] [PubMed] [Google Scholar]
- 37. Labarthe DR. Prevention of cardiovascular risk factors in the first place. Prev Med. 1999;29:S72–S78. [DOI] [PubMed] [Google Scholar]
- 38. Gillman MW. Primordial prevention of cardiovascular disease. Circulation. 2015;131:599–601. [DOI] [PMC free article] [PubMed] [Google Scholar]