Nocturnal hypertension predicts left ventricular hypertrophy in children with primary hypertension
Original Article

Nocturnal hypertension predicts left ventricular hypertrophy in children with primary hypertension

Jiayu Wang1,2# ORCID logo, Jialing Zhang1,2#, Chen Chu3, Jie Wang3, Fang Liu3, Feng Wang3, Yonghao Gui1,2,3

1National Health Commission Key Laboratory of Neonatal Diseases (Fudan University), Shanghai, China; 2Institute of Pediatrics, Children’s Hospital of Fudan University, Shanghai, China; 3Heart Center, Children’s Hospital of Fudan University, Shanghai, China

Contributions: (I) Conception and design: F Wang, Y Gui; (II) Administrative support: Y Gui; (III) Provision of study materials or patients: C Chu, Jie Wang, F Liu, F Wang; (IV) Collection and assembly of data: Jiayu Wang, J Zhang; (V) Data analysis and interpretation: Jiayu Wang, J Zhang; (VI) Manuscript writing: All authors; (VII) Final approval of manuscript: All authors.

#These authors contributed equally to this work as co-first authors.

Correspondence to: Feng Wang, MD. Heart Center, Children’s Hospital of Fudan University, No. 399 Wanyuan Road, Minhang District, Shanghai 201102, China. Email: fmwong@126.com; Yonghao Gui, MD. National Health Commission Key Laboratory of Neonatal Diseases (Fudan University), Shanghai 201102, China; Institute of Pediatrics, Children’s Hospital of Fudan University, Shanghai 201102, China; Heart Center, Children’s Hospital of Fudan University, No. 399 Wanyuan Road, Minhang District, Shanghai 201102, China. Email: yh_gui@163.com.

Background: Childhood hypertension is a significant global health concern, with left ventricular hypertrophy (LVH) being its most common target organ damage. Evidence from Chinese pediatric populations remains scarce. Therefore, this study aimed to investigate the risk factors of LVH in children with primary hypertension and to develop a prediction model.

Methods: In this cross-sectional study, 121 children diagnosed with primary hypertension (aged 3–17 years) admitted to Children’s Hospital of Fudan University (January 1, 2019–December 31, 2024) were included. Clinical data (age, sex, height, weight, birth history, and family history of hypertension), laboratory parameters, 24-hour ambulatory blood pressure monitoring (ABPM), and echocardiography were collected. Participants were stratified into the LVH group and the non-LVH group based on left ventricular mass index (LVMI). Partial correlation analysis evaluated associations of variables with left ventricular mass and LVMI. Stepwise multivariable logistic regression was used to identify independent risk factors. Based on significant factors, a risk prediction model was constructed, with model performance assessed via receiver operating characteristic (ROC) curves [area under the curve (AUC)] and goodness-of-fit tests (Hosmer-Lemeshow χ2).

Results: LVH was observed in 17.4% (21/121) of participants, predominantly concentric hypertrophy. Partial correlation analysis adjusted for age and sex revealed positive correlations of alanine aminotransferase (ALT), aspartate aminotransferase (AST), 24-hour mean systolic blood pressure (SBP), daytime mean SBP, and morning mean SBP (the average of ambulatory SBP readings taken within 2 hours of waking up) with LVMI (r=0.26, 0.37, 0.25, 0.25, and 0.23, all P<0.05), respectively. Nocturnal hypertension was identified as an independent risk factor of LVH [odds ratio (OR) =4.07; 95% confidence interval (CI): 1.47–13.24; P=0.01]. The combined prediction model incorporating age, sex, body mass index (BMI), and nocturnal hypertension demonstrated a moderate discrimination (AUC =0.710; 95% CI: 0.593–0.827) and good calibration (Hosmer-Lemeshow χ2=5.70; P=0.68).

Conclusions: This study identified nocturnal hypertension as a critical independent risk factor for LVH in pediatric primary hypertension. The prediction model may provide valuable insights for early identification of LVH.

Keywords: Child; primary hypertension; left ventricular hypertrophy (LVH); risk factor; nocturnal hypertension

Submitted Aug 26, 2025. Accepted for publication Oct 22, 2025. Published online Nov 26, 2025.

doi: 10.21037/tp-2025-567

Highlight box

Key findings

• Nocturnal hypertension was demonstrated as an independent risk factor of left ventricular hypertrophy (LVH) (odds ratio =4.07).

• A model comprising age, sex, body mass index, and nocturnal hypertension showed good discriminative ability (area under the curve =0.710).

What is known and what is new?

• LVH is a common organ damage in pediatric primary hypertension.

• This study identified nocturnal hypertension as an independent risk factor and developed a prediction model for LVH in this population.

What is the implication, and what should change now?

• The model may help early LVH detection in children with primary hypertension.

• Nocturnal blood pressure monitoring should be integrated into pediatric hypertension management.

Introduction

Hypertension in children is considered an important global health problem, with a pooled prevalence of 3.89% according to a recent meta-analysis (1). The most common target organ damage in hypertension is believed to be left ventricular hypertrophy (LVH). The pathologic mechanisms of LVH involved hemodynamic, neurohumoral, and genetic factors (2). Critically, LVH was revealed in approximately 30.5% of children with primary hypertension at the initial diagnosis, as confirmed by a recent meta-analysis of 5,622 untreated pediatric cases (3). Increased left ventricular mass index (LVMI) reflects the severity of LVH and is an independent risk factor for all-cause and cardiovascular-specific mortality (4). Notably, children with hypertension have nearly a four-fold higher risk of LVH compared to healthy children (5).

Many risk factors of pediatric LVH have been elucidated previously, among which body mass index (BMI) and 24-hour systolic blood pressure (SBP) were reported as independent predictors. For example, obesity is associated with a nearly nine-fold increased risk of LVH (6). However, evidence based on the Chinese pediatric population is scarce. Also, perinatal variables (including birth weight and gestational age, which may modulate cardiovascular developmental trajectories) have not been comprehensively studied.

To address these critical gaps, this cross-sectional study was conducted to evaluate the underlying risk factors of LVH and construct a risk prediction model for targeted intervention. We present this article in accordance with the STROBE reporting checklist (available at https://tp.amegroups.com/article/view/10.21037/tp-2025-567/rc).

Methods

Ethical statement

The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study protocol was approved by the ethics committee of the Children’s Hospital of Fudan University (No. 2024-376). Informed consent was waived by the ethics committee because of the retrospective nature of this study.

Study population

In this cross-sectional study, a total of 121 children (aged 3–17 years) with primary hypertension were admitted to the Children’s Hospital of Fudan University between January 1, 2019, and December 31, 2024. Children with secondary hypertension due to renal, vascular, endocrine, or central nervous system disorders were excluded (Figure 1). According to the Chinese Guidelines for the Prevention and Treatment of Hypertension (2024 revised edition) (7), the study population was stratified into three groups involving high-normal blood pressure (BP), stage 1 hypertension, and stage 2 hypertension. High normal BP was defined as SBP or diastolic BP (DBP) ≥ the age-, sex-, and height-specific 90th percentile (P90) and <95th percentile (P95) according to the Chinese pediatric BP references, or ≥120/80 mmHg (8). Hypertension was considered when: SBP and/or DBP ≥ P95 in children aged 3–15 years, or SBP/DBP ≥140/90 mmHg in those aged 16–17 years. Hypertension was further classified as stage 1 hypertension (SBP and/or DBP from P95 to P99+5 mmHg), and stage 2 hypertension (SBP and/or DBP ≥ P99+5 mmHg) (9,10).

Figure 1 Flowchart of study population.

Measurements and assessments

Physical examinations

Weight and height were measured with children in light clothes and no shoes using a standardized scale. BMI was calculated as weight (kg)/height2 (m2). Overweight was defined as BMI between P85 and < P95 for age and sex; obesity as BMI ≥ P95 as previously described (11,12). After the child rested for at least 10 minutes, BP was measured by trained staff using a validated electronic sphygmomanometer (Omron HBP-1320) and an appropriate-sized cuff on the right arm. Three measurements were taken at 1–2 minutes intervals, and the average of the last two readings was used for analysis.

Laboratory tests

Laboratory data were collected, including total cholesterol, triglyceride, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, alanine aminotransferase (ALT), aspartate aminotransferase (AST), creatinine, homocysteine, cystatin C, uric acid, glucose, C-peptide, insulin, angiotensin II, renin, aldosterone, and urine protein/creatinine ratio. Results and reference standards were obtained from medical records.

Echocardiography

All examinations were performed during the children’s hospitalization. Standard echocardiographic measurements included left ventricular end-diastolic diameter (LVIDd), interventricular septal thickness (IVST), and left ventricular posterior wall thickness (LVPWT). Left ventricular mass (LVM) was calculated using the Devereux formula (13): LVM = 0.8 × 1.04 × [(LVIDd + IVST + LVPWT)3 − LVIDd3] + 0.6 (g). LVMI was derived as LVM divided by height2.7 (g/m2.7). Relative wall thickness (RWT) was calculated as (IVST + LVPWT)/LVIDd. Age-standardized RWT (RWTa) was determined as RWT − 0.005 × (age − 10) (cm) (14). LVH was diagnosed as LVMI ≥ the age- and sex-specific P95, referring to previous studies (no unified standard for childhood LVH currently exists) (15). High RWT was defined as RWTa ≥ P95 (0.375) (14). Based on LVMI and RWTa, children were then classified into four types: normal (normal LVMI and RWTa), concentric remodeling (normal LVMI and high RWTa), concentric hypertrophy (high LVMI and RWTa), and eccentric hypertrophy (high LVMI and normal RWTa).

Ambulatory BP monitoring (ABPM)

ABPM provided 24-hour mean BP, daytime BP, nighttime BP, and morning BP [i.e., the average of ambulatory BP readings taken within 2 hours of waking up (16)]. A dipper pattern was defined by an average nighttime BP 10% to 20% lower than the average daytime BP (17,18). We referred to the normative values for ambulatory SBP and DBP from a study in healthy children and adolescents by Soergel et al. (19).

Statistical analysis

Data were analyzed using R software. Continuous variables with normal distribution are presented as mean (standard deviation) and compared using independent samples t-test. Categorical variables were presented as percentages and compared using χ2 test or Fisher’s exact test. Partial correlation analysis (adjusted for age and sex) was used to assess relationships between variables and LVM as well as LVMI. Missing values were imputed using multiple imputation by chained equations. Variables with P<0.10 in univariate analysis were included in multivariate stepwise logistic regression (α-in =0.10, α-out =0.10). Receiver operating characteristic (ROC) curves were used to evaluate discriminative ability. DeLong’s test was applied to compare areas under the curves (AUCs) between models. Hosmer-Lemeshow tests were used to assess calibration. A two-tailed P<0.05 was considered statistically significant.

Results

Characteristics of participants

Among 121 participants, 98 (80.99%) were male, with a mean age of 11.79 (3.04) years. Obesity was considered in 63 (52.07%) children. Stage 1 and stage 2 hypertension accounted for 17.36% (21/121) and 80.17% (97/121), respectively (Table 1). In terms of ventricular geometry classification, 76 (62.81%) had normal geometry, 24 (19.83%) concentric remodeling, 15 (12.40%) concentric hypertrophy, and 6 (4.96%) eccentric hypertrophy.

Table 1

Characteristics of participants with and without LVH

Variables Total (n=121) LVH (n=21) Non-LVH (n=100) Missing (%) t/z/χ2 P
Age (years) 11.79 (3.04) 11.10 (3.27) 11.93 (2.99) 0 1.14 0.26
Age group (%) 0 1.15 0.28
   3–6 years 6.61 14.29 5.00
   7–17 years 93.39 85.71 95.00
Boys (%) 80.99 85.71 80.00 0 0.09 0.76
Disease duration group (%) 0 0.84 0.84
   <2 months 61.16 66.67 60.00
   2 months–<6 months 14.88 9.52 16.00
   6 months–<1 year 7.44 9.52 7.00
   ≥1 year 16.53 14.29 17.00
History of prematurity (%) 11.61 5.56 12.77 7.4 0.22 0.64
Cesarean delivery (%) 44.64 55.56 42.55 7.4 1.03 0.31
Birth weight (%) 14.0 – 0.85
   Low birth weight (<2,500 g) 7.44 4.76 8.00
   Normal birth weight (2,500–4,000 g) 74.38 80.95 73.00
   Macrosomia (>4,000 g) 4.13 0.00 5.00
Feeding type (%) 7.4 0.78 0.68
   Breastfeeding 49.11 42.11 50.54
   Artificial feeding 12.50 10.53 12.90
   Mixed feeding 38.39 47.37 36.56
First-degree family history of hypertension (%) 39.67 52.38 37.00 0 1.72 0.19
BMI (kg/m2) 24.29 (5.98) 24.21 (6.58) 24.31 (5.89) 0 0.07 0.95
Body type (%) 0 0.76 0.69
   Normal 26.45 23.81 27.00
   Overweight 21.49 28.57 20.00
   Obesity 52.07 47.62 53.00
Abnormal total cholesterol (%) 15.00 14.29 15.15 0.8 <0.001 >0.99
Abnormal triglyceride (%) 25.00 38.10 22.22 0.8 2.33 0.13
Abnormal high-density lipoprotein cholesterol (%) 32.50 42.86 30.30 0.8 1.24 0.26
Abnormal low-density lipoprotein cholesterol (%) 12.50 4.76 14.14 0.8 0.67 0.41
Abnormal ALT (%) 15.00 28.57 12.12 0.8 2.50 0.11
Abnormal AST (%) 15.00 33.33 11.11 0.8 5.08 0.02
Abnormal serum creatinine (%) 23.33 23.81 23.23 0.8 <0.001 >0.99
Abnormal homocysteine (%) 15.18 15.00 15.22 7.4 <0.001 >0.99
Abnormal cystatin C (%) 2.86 11.76 1.14 13.2 – 0.07
Uric acid (μmol/L) 415.91 (114.60) 368.14 (122.77) 426.04 (110.81) 0.8 2.13 0.03
Glucose (mmol/L) 5.03 (1.09) 5.14 (1.44) 5.01 (1.01) 2.5 0.50 0.62
C-peptide (ng/mL) 4.50 (3.61) 4.15 (3.46) 4.58 (3.66) 6.6 0.49 0.63
Insulin (pmol/L) 216.16 (273.91) 191.89 (242.93) 221.44 (281.14) 7.4 0.44 0.66
Serum creatinine (μmol/L) 57.03 (16.89) 55.59 (26.30) 57.33 (14.30) 0.8 0.43 0.67
Angiotensin II (pg/mL) 130.77 (82.86) 103.36 (31.12) 136.02 (88.57) 7.4 1.54 0.13
Renin (pg/mL) 88.14 (119.90) 85.03 (101.78) 88.69 (123.27) 5.8 0.12 0.91
Aldosterone (pg/mL) 188.80 (205.68) 186.21 (203.67) 189.25 (207.06) 5.0 0.06 0.96
Urinary protein/urinary creatinine 0.11 (0.10) 0.12 (0.10) 0.10 (0.11) 9.9 0.78 0.44
Comorbidities (%)
   Fatty liver 17.36 23.81 16.00 0 0.29 0.59
   Hyperuricemia 8.26 14.29 7.00 0 0.44 0.51
   Abnormal glucose metabolism† 4.13 14.29 2.00 0 – 0.04
   Hyperlipidemia 2.48 4.76 2.00 0 – 0.44
Hypertension (%) 0 3.19 0.21
   High-normal BP 2.48 4.76 2.00
   Stage 1 hypertension 17.36 4.76 20.00
   Stage 2 hypertension 80.17 90.48 78.00
24-hour ambulatory hypertension (%) 50.89 73.68 46.24 7.4 4.76 0.03
Daytime hypertension (%) 56.25 78.95 51.61 7.4 4.79 0.03
Nocturnal hypertension (%) 51.35 77.78 46.24 8.3 6.01 0.01
Morning hypertension (%) 47.27 68.42 42.86 9.1 4.12 0.04
Dipper pattern (%) 72.07 66.67 73.12 8.3 0.31 0.58

Continuous variables are presented as mean (standard deviation) and categorical variables are presented as percentages. †, abnormal glucose metabolism included prediabetes and type 2 diabetes. The diagnostic criteria for type 2 diabetes are to meet one of the following laboratory values: (I) FPG ≥7.0 mmol/L; (II) 2-h OGTT ≥11.1 mmol/L; (III) random plasma glucose ≥11.1 mmol/L; and (IV) HbA1c ≥6.5%. Prediabetes was indicated by both clinically (FPG 5.6–6.9 mmol/L) and by not meeting the other criteria for type 2 diabetes. ALT, alanine aminotransferase; AST, aspartate aminotransferase; BMI, body mass index; BP, blood pressure; FPG, fasting plasma glucose; HbA1c, glycated hemoglobin; LVH, left ventricular hypertrophy; OGTT, oral glucose tolerance test.

Comparison between LVH and non-LVH groups

No significant differences were observed in age, sex, disease duration, prematurity, cesarean section, birth weight, feeding mode, family history of hypertension, BMI, body size, blood lipids, creatinine, or homocysteine between groups. In univariable analysis, the LVH group had higher proportions of abnormal AST values, abnormal glucose metabolism, 24-hour hypertension, daytime hypertension, nocturnal hypertension, and morning hypertension (all P<0.05). Partial correlation analysis (adjusted for age and sex) showed positive correlations of BMI, ALT, AST, uric acid, C-peptide, and insulin with LVM (all P<0.05); and positive correlations of ALT, AST, 24-hour mean SBP, daytime mean SBP, and morning mean SBP with LVMI (all P<0.05) (Table 2).

Table 2

Partial correlation of variables with LVM as well as LVMI

Variables LVM LVMI
BMI 0.52* 0.22
Total cholesterol 0.11 0.14
Triglyceride 0.19 0.08
High-density lipoprotein cholesterol −0.22 −0.04
Low-density lipoprotein cholesterol 0.20 0.19
Serum free fatty acids −0.02 0.01
ALT 0.38* 0.26*
AST 0.37* 0.37*
Uric acid 0.36* 0.07
Glucose 0.14 0.08
C-peptide 0.31* 0.09
Insulin 0.25* 0.10
Serum creatinine 0.19 −0.01
Homocysteine −0.10 −0.12
Cystatin C 0.08 0.11
Angiotensin II −0.03 −0.14
Renin 0.10 0.11
Aldosterone 0.21 0.02
Urinary protein/urinary creatinine −0.03 0.10
Clinic SBP 0.21 0.19
Clinic DBP 0.02 0.21
24-hour mean SBP 0.17 0.25*
24-hour mean DBP −0.08 0.16
Daytime mean SBP 0.18 0.25*
Daytime mean DBP −0.08 0.16
Nocturnal mean SBP 0.11 0.18
Nocturnal mean DBP −0.09 0.16
Morning SBP 0.21 0.23*
Morning DBP <0.001 0.20

*, P<0.05. ALT, alanine aminotransferase; AST, aspartate aminotransferase; BMI, body mass index; DBP, diastolic blood pressure; LVM, left ventricular mass; LVMI, left ventricular mass index; SBP, systolic blood pressure.

Risk factors of LVH

Multivariable stepwise logistic regression identified nocturnal hypertension as an independent risk factor for LVH [odds ratio (OR) =4.07; 95% confidence interval (CI): 1.47–13.24; P=0.01]. Sensitivity analysis using data without missing value imputation (n=97) confirmed nocturnal hypertension as an independent risk factor (OR =4.68; 95% CI: 1.28–23.10; P=0.03). ROC curves showed AUCs of 0.601 (95% CI: 0.463–0.740) for the model including age, sex, and BMI (Model 1) and 0.710 (95% CI: 0.593–0.827) for the model including nocturnal hypertension (Model 2), with good discriminative ability (Figure 2). The Hosmer-Lemeshow test indicated good calibration for Model 2 (χ2=5.70, P=0.68).

Figure 2 Comparisons of discrimination ability for LVH in children with primary hypertension. Model 1 adjusted for age, sex, and BMI. Model 2 additionally adjusted for nocturnal hypertension. AUC, area under the curve; BMI, body mass index; LVH, left ventricular hypertrophy.

Discussion

LVH was confirmed in 17.36% of the 121 children with primary hypertension in the present cross-sectional analysis, with concentric hypertrophy (12.40%) as the main subtype. Nocturnal hypertension was identified as an independent risk factor for LVH. This observation highlights the important role of ABPM in risk stratification. It implies that children with primary hypertension, particularly those with elevated nocturnal BP, warrant closer monitoring and management. The combined model (age, sex, BMI, nocturnal hypertension) had an AUC of 0.710, providing a reference for early identification of high-risk children.

A previous meta-analysis of 47 studies reported a 30.5% prevalence of LVH in children with primary hypertension, but heterogeneity was high due to the varying diagnostic criteria (3). In our study, using LVMI ≥ age- and sex-specific P95 (Khoury’s criteria) (15), the prevalence of LVH was 17.36%; using fixed sex-specific thresholds (males ≥37.08 g/m2.7, females ≥34.02 g/m2.7), the prevalence increased up to 29.8% (36/121), consistent with previous studies (9).

Partial correlation analysis showed a significant positive correlation between BMI and LVM (r=0.52, P<0.001), but not with LVMI (r=0.22, P=0.07), possibly due to limited sample size (n=121). Multiple studies confirmed that obese children had higher LVM and LVMI than normal-weight children (20-22). For example, Liu et al. found BMI was an independent risk factor for LVH in 430 children with primary hypertension (OR =1.17) (9). A multi-center cohort study in over 10,000 participants (median follow-up 24 years) showed that childhood obesity was an independent risk factor for cardiovascular events in adulthood [risk ratio (RR) =1.41], emphasizing the importance of early weight intervention (23).

In our study, children with abnormal glucose metabolism (including diabetes or prediabetes) had a higher LVH proportion than those with normal glucose (14.29% vs. 2.00%, P=0.04), consistent with epidemiological evidence (24). A large prospective cohort study of nearly 15,000 adults (aged 35–74 years) found that prediabetes and type 2 diabetes increased LVH risk by 24% (RR =1.24) and 78% (RR =1.78) over 5 years, respectively (25). The potential mechanisms include advanced glycation end-product formation, transforming growth factor-β (TGF-β)-mediated fibrosis, lipid deposition, and elevated insulin-like growth factor levels (25).

Consistent with findings from previous studies (26), SBP showed a stronger correlation with LVH than DBP in our study. A cohort study comprising 1.3 million adults reported SBP as a stronger predictor of adverse cardiovascular outcomes [hazard ratio (HR) =1.18 vs. HR =1.06 for DBP] (27). A Mendelian randomization analysis of 5,596 participants in the UK Biobank confirmed a causal relationship between elevated SBP and increased LVM (28). Notably, nocturnal hypertension was proved to be an independent risk factor for LVH in children, consistent with adult studies linking nocturnal hypertension to increased risks of pulse wave velocity, carotid intima-media thickness, and myocardial hypertrophy (29). A cohort study of 59,124 adults (median follow-up 9.7 years) found that each 10 mmHg increase in nighttime SBP was associated with 45% higher all-cause mortality and 51% higher cardiovascular-specific mortality (30), which might be attributable to increased blood volume resulting from high salt sensitivity, supine posture, and overactivation of the renin-angiotensin-aldosterone and sympathetic nervous systems (17).

After adjusting for age and sex, ALT and AST were positively correlated with LVMI, consistent with findings from the Huantai Childhood Cardiovascular Health Cohort (n=1,340), where each unit increase in ALT was associated with increased LVM and LVMI (β=0.23 and 0.18, respectively) (31).

Strengths and limitations

Our study integrated echocardiographic results with ABPM and key metabolic biomarkers. However, there are several limitations in our study, including lacking external validity due to the single-center design, potential selection bias (e.g., the predominance of male participants), lack of information on other potential predictors (e.g., lifestyles, urinary albumin/creatinine ratio), a relatively small sample size, a short follow-up period that may have led to the underdiagnosis of LVH, and residual bias caused by missing data. Future research should incorporate multi-center data to validate our conclusions.

Conclusions

In conclusion, nocturnal hypertension is an independent risk factor for LVH in children with primary hypertension. The combined model (age, sex, BMI, nocturnal hypertension) with an AUC of 0.710 may aid early screening and individualized intervention to delay LVH progression and reduce the long-term cardiovascular risk.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://tp.amegroups.com/article/view/10.21037/tp-2025-567/rc

Data Sharing Statement: Available at https://tp.amegroups.com/article/view/10.21037/tp-2025-567/dss

Peer Review File: Available at https://tp.amegroups.com/article/view/10.21037/tp-2025-567/prf

Funding: This study was supported by the Children’s Hospital of Fudan University-Green Seed Program (No. EKQM202422), the Discipline Leader Training Program of Children’s Hospital of Fudan University (No. EKXDPY202308), the Outstanding Clinical Scientist Training Program of Fudan University (No. DGF828030-3/047), the Shanghai High-Level Local University Construction Project-First-class Clinical Medicine Discipline Development Project-Child Development and Health (No. DGF501062), and the Fudan University’s Key Project for Double First-Class Construction of Disciplines, Early Childhood Healthy Development and Maintenance (No. IDF156014).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tp.amegroups.com/article/view/10.21037/tp-2025-567/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study protocol was approved by the ethics committee of the Children’s Hospital of Fudan University (No. 2024-376). Informed consent was waived by the ethics committee because of the retrospective nature of this study.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

  1. Ruan X, Zhu A, Wang T, et al. Global Prevalence of Hypertension in Children and Adolescents Younger Than 19 Years: A Systematic Review and Meta-Analysis. JAMA Pediatr 2025;179:987-99. [Crossref] [PubMed]
  2. Yildiz M, Oktay AA, Stewart MH, et al. Left ventricular hypertrophy and hypertension. Prog Cardiovasc Dis 2020;63:10-21. [Crossref] [PubMed]
  3. Sinha MD, Azukaitis K, Sladowska-Kozłowska J, et al. Prevalence of left ventricular hypertrophy in children and young people with primary hypertension: Meta-analysis and meta-regression. Front Cardiovasc Med 2022;9:993513. [Crossref] [PubMed]
  4. Bluemke DA, Kronmal RA, Lima JA, et al. The relationship of left ventricular mass and geometry to incident cardiovascular events: the MESA (Multi-Ethnic Study of Atherosclerosis) study. J Am Coll Cardiol 2008;52:2148-55. [Crossref] [PubMed]
  5. Chung J, Robinson CH, Yu A, et al. Risk of Target Organ Damage in Children With Primary Ambulatory Hypertension: A Systematic Review and Meta-Analysis. Hypertension 2023;80:1183-96. [Crossref] [PubMed]
  6. Gupta-Malhotra M, Hashmi SS, Poffenbarger T, et al. Left Ventricular Hypertrophy Phenotype in Childhood-Onset Essential Hypertension. J Clin Hypertens (Greenwich) 2016;18:449-55. [Crossref] [PubMed]
  7. Chinese Hypertension Guideline Revision Committee. Chinese Hypertension Prevention and Treatment Guidelines (2024 Revision). Chinese Journal of Hypertension 2024;32:603-700.
  8. Fan H, Yan YK, Mi J. Updating blood pressure references for Chinese children aged 3-17 years. Chinese Journal of Hypertension 2017;25:428-35.
  9. Liu Y, Shi L, Lin Y, et al. Clinical features and risk factors of left ventricular hypertrophy in children with primary hypertension. Chinese Journal of Pediatrics 2023;61:1031-7. [Crossref] [PubMed]
  10. The fourth report on the diagnosis, evaluation, and treatment of high blood pressure in children and adolescents. Pediatrics 2004;114:555-76.
  11. Li H, Xiang X, Yi Y, et al. Epidemiology of obesity and influential factors in China: a multicenter cross-sectional study of children and adolescents. BMC Pediatr 2024;24:498. [Crossref] [PubMed]
  12. Lo JC, Sinaiko A, Chandra M, et al. Prehypertension and hypertension in community-based pediatric practice. Pediatrics 2013;131:e415-24. [Crossref] [PubMed]
  13. Devereux RB, Alonso DR, Lutas EM, et al. Echocardiographic assessment of left ventricular hypertrophy: comparison to necropsy findings. Am J Cardiol 1986;57:450-8. [Crossref] [PubMed]
  14. de Simone G, Daniels SR, Kimball TR, et al. Evaluation of concentric left ventricular geometry in humans: evidence for age-related systematic underestimation. Hypertension 2005;45:64-8. [Crossref] [PubMed]
  15. Khoury PR, Mitsnefes M, Daniels SR, et al. Age-specific reference intervals for indexed left ventricular mass in children. J Am Soc Echocardiogr 2009;22:709-14. [Crossref] [PubMed]
  16. Wang JG, Kario K, Park JB, et al. Morning blood pressure monitoring in the management of hypertension. J Hypertens 2017;35:1554-63. [Crossref] [PubMed]
  17. Kario K. Nocturnal Hypertension: New Technology and Evidence. Hypertension 2018;71:997-1009. [Crossref] [PubMed]
  18. Parati G, Stergiou G, O'Brien E, et al. European Society of Hypertension practice guidelines for ambulatory blood pressure monitoring. J Hypertens 2014;32:1359-66. [Crossref] [PubMed]
  19. Soergel M, Kirschstein M, Busch C, et al. Oscillometric twenty-four-hour ambulatory blood pressure values in healthy children and adolescents: a multicenter trial including 1141 subjects. J Pediatr 1997;130:178-84. [Crossref] [PubMed]
  20. Dhuper S, Abdullah RA, Weichbrod L, et al. Association of obesity and hypertension with left ventricular geometry and function in children and adolescents. Obesity (Silver Spring) 2011;19:128-33. [Crossref] [PubMed]
  21. Bartkowiak J, Spitzer E, Kurmann R, et al. The impact of obesity on left ventricular hypertrophy and diastolic dysfunction in children and adolescents. Sci Rep 2021;11:13022. [Crossref] [PubMed]
  22. Zhang Y, Zhao M, Bovet P, et al. Association of abdominal obesity and high blood pressure with left ventricular hypertrophy and geometric remodeling in Chinese children. Nutr Metab Cardiovasc Dis 2021;31:306-13. [Crossref] [PubMed]
  23. Kartiosuo N, Raitakari OT, Juonala M, et al. Cardiovascular Risk Factors in Childhood and Adulthood and Cardiovascular Disease in Middle Age. JAMA Netw Open 2024;7:e2418148. [Crossref] [PubMed]
  24. Rutter MK, Parise H, Benjamin EJ, et al. Impact of glucose intolerance and insulin resistance on cardiac structure and function: sex-related differences in the Framingham Heart Study. Circulation 2003;107:448-54. [Crossref] [PubMed]
  25. Schmitt VH, Billaudelle AM, Schulz A, et al. Disturbed Glucose Metabolism and Left Ventricular Geometry in the General Population. J Clin Med 2021;10:3851. [Crossref] [PubMed]
  26. Wu H, Shi L, Lin Y, et al. The Correlation Between ABPM Parameters and Left Ventricular Hypertrophy in Pediatric Essential Hypertension. Front Pediatr 2022;10:896054. [Crossref] [PubMed]
  27. Flint AC, Conell C, Ren X, et al. Effect of Systolic and Diastolic Blood Pressure on Cardiovascular Outcomes. N Engl J Med 2019;381:243-51. [Crossref] [PubMed]
  28. Hendriks T, Said MA, Janssen LMA, et al. Effect of Systolic Blood Pressure on Left Ventricular Structure and Function: A Mendelian Randomization Study. Hypertension 2019;74:826-32. [Crossref] [PubMed]
  29. Salles GF, Reboldi G, Fagard RH, et al. Prognostic Effect of the Nocturnal Blood Pressure Fall in Hypertensive Patients: The Ambulatory Blood Pressure Collaboration in Patients With Hypertension (ABC-H) Meta-Analysis. Hypertension 2016;67:693-700. [Crossref] [PubMed]
  30. Staplin N, de la Sierra A, Ruilope LM, et al. Relationship between clinic and ambulatory blood pressure and mortality: an observational cohort study in 59 124 patients. Lancet 2023;401:2041-50. [Crossref] [PubMed]
  31. Song YX, Yang LL, Zhao M, et al. Association between alanine aminotransferase levels and cardiac structure in childhood. Chinese Journal of School Health 2024;45:1388-92, 1398.
Cite this article as: Wang J, Zhang J, Chu C, Wang J, Liu F, Wang F, Gui Y. Nocturnal hypertension predicts left ventricular hypertrophy in children with primary hypertension. Transl Pediatr 2025;14(11):3011-3019. doi: 10.21037/tp-2025-567

Article Options

Download Citation

Share