Prevalence and risk factors for congenital heart defects among children in the Multi-Ethnic Yunnan Region of China
Original Article

Prevalence and risk factors for congenital heart defects among children in the Multi-Ethnic Yunnan Region of China

Yu Cao1,2#, Rongzhong Huang1,2#, Ruize Kong1,2, Hongrong Li1,2, Hong Zhang3,4, Yaxiong Li5,6, Liwen Liang3,4, Da Xiong1,2, Shen Han5,6, Liang Zhou3,4, Junyin Guo3,4, Guolin Dai1,2, Mingyao Meng7, Hongbo Lou3,4, Zongliu Hou7, Lihong Jiang1,2

1Department of Cardiovascular Surgery, the First Peoples’ Hospital of Yunnan Province, Kunming, China; 2Department of Cardiovascular Surgery, The Affiliated Hospital of Kunming University of Science and Technology, Kunming, China; 3Department of Cardiology, the First Peoples’ Hospital of Yunnan Province, Kunming, China; 4Department of Cardiology, The Affiliated Hospital of Kunming University of Science and Technology, Kunming, China; 5Department of Cardiovascular Surgery, Yan’an Affiliated Hospital of Kunming Medical University, Kunming, China; 6Key Laboratory of Cardiovascular Disease of Yunnan Province, Kunming, China; 7Department of Central Laboratory, Yan’an Affiliated Hospital of Kunming Medical University, Kunming, China

#There authors contributed equally to this work.

Correspondence to: Prof. Zongliu Hou. Department of Central Laboratory, Yan’an Affiliated Hospital of Kunming Medical University, No. 245 The People of East Road, Panlong District, Kunming 650034, China. Email: hzl579@163.com; Prof. Lihong Jiang. Department of Cardiovascular Surgery, The Affiliated Hospital of Kunming University of Science and Technology, No. 157 Jinbi Road, Xishan District, Kunming 650034, China. Email: jlh15198763375@163.com.

Background: To determine the congenital heart defect (CHD) prevalence and identify the associated risk factors in children within the multi-ethnic Yunnan Region of China.

Methods: This is a prospective matched case-control screening study. Screening for CHD in children residing within 28 county districts of Yunnan Province during the period of January 2001 to December 2016 was conducted. A total of 2,421 and CHD cohort and 24,210 control cohort were derived from a total population of 400,855 children (under 18 years of age).

Results: A total of 2,421 children were diagnosed with CHD, yielding a CHD prevalence of 6.04 cases per 1,000 children. The prevalence of CHD by sex was 6.54 per 1,000 females versus 5.59 per 1,000 males. The ethnic groups displaying the highest CHD prevalence were the Lisu (15.51 per 1,000), Achang (13.18 per 1,000), Jingpo (12.32 per 1,000), Naxi (9.68 per 1,000), and Tibetan (8.57 per 1,000), respectively. The most common CHD was atrial septal defect, amounting to 1.94 instances per 1,000 children. We identified a number of child-associated parameters that significantly correlated with greater CHD risk, such as lower mass at birth, shorter duration of gestation, and younger age at the time of screening. We also identified a number of maternal and familial risk factors.

Conclusions: This ultrasonic color Doppler imaging study revealed a relatively commonplace prevalence of CHD. Moreover, the prevalence of CHD in Yunnan Region significantly varied with sex and ethnic status. Certain child-associated, maternal, and familial risk factors may contribute to CHD risk.

Keywords: Epidemiology; risk factor; congenital heart defect; congenital heart defect (CHD); Doppler imaging; China


Submitted Aug 07, 2021. Accepted for publication Mar 17, 2022.

doi: 10.21037/tp-21-371


Introduction

Congenital heart defects (CHD) are among the most frequent birth defects, occurring in as many as 9.3 per 1,000 live births with significant geographical variation (1). Defects can range from asymptomatic to life-threatening, and many cases require surgical or pharmacological intervention at an early stage to prevent adverse outcomes (2). Timely screening is therefore necessary to help identify patients with CHD, diagnose cases early on, and lower mortality rates.

Several citywide and nationwide studies have been performed over the years to estimate the frequency of CHD among live births. An early study in the United Kingdom conducted from 1985 to 1994 screened 377,310 live neonatal births and diagnosed 1,942 instances of CHD, amounting to a prevalence of 0.52% (3). Another early study in the United States, conducted from 1968 to 1997 as part of the Metropolitan Atlanta Congenital Defects Program (MACDP), revealed a CHD prevalence of 0.62%, which was remarkably similar to the UK study (4). CHD screenings in urban China, within the cities of Shanghai in 1987 and Beijing in 2005, identified 6.9 CHD cases and 4.6 CHD cases per 1,000 live neonatal births, respectively (5,6). A more recent meta-analysis revealed a slightly higher CHD rate in Asian populations than in those of Europe or North America (1). Due to this variance, targeting and screening discrete geographic regions may be necessary to obtain accurate information on the CHD rate for a particular population.

Our objective was to determine the CHD prevalence and identify the associated risk factors in children within the multi-ethnic Yunnan Region of China. In this targeted screening study, we estimated the CHD rate for children under 18 years of age residing with Yunnan region and identified the risk factors associated with higher-than-average CHD prevalence in this population. We conducted our whole-population screen using ultrasonic color Doppler imaging, a non-invasive technique that superimposes colored velocity information obtained by Doppler ultrasound over anatomical images in grey-scale obtained by conventional pulse-echo ultrasound (7).

We present the following article in accordance with the STROBE reporting checklist (available at https://tp.amegroups.com/article/view/10.21037/tp-21-371/rc).


Methods

Patient and public involvement

The development of the research question and outcome measures were partly determined based on the unique ethnic constituencies of Yunnan Province and the varying altitude levels at which the residents of Yunnan Province live. Feedback received from the local target populations via the Yunnan Education Bureau and the Health and Family Planning Commission of Yunnan Province was critical to the design of this study. Adult community members were involved in encouraging the recruitment of minors into this study. Following publication, the key results of this study will be disseminated to the local target populations in their local languages by the Yunnan Education Bureau.

The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). This study obtained approval from the Ethics Review Committees at The First People’s Hospital of Yunnan Province, Kunming, China (No. KHLL2020-KY019) and Yan’an Affiliated Hospital of Kunming Medical University, Kunming, China (No. YYHKM04584). Written informed consent was obtained from all participants’ parents or legal guardians prior to their enrollment.

Enrollment for the screening program

Yunnan Province is situated in southern China and, in2010, was home to an estimated 46 million people, making it the 12th largest province in China in terms of population. The Province is sub-divided into a total of 129 county-level districts and has 1,565 cities. Among the country’s 56 recognized ethnic groups, 25 are found in Yunnan. Approximately 38% of the province’s population are members of ethnic minorities (8). The Congenital Malformation Registry Database of Yunnan Province (CMRD), compiled between January 2001 and December 2016, consists of 400,855 individuals residing within 28 of the province’s county-level districts. Prior to conducting this prospective matched case-control screening study, the Yunnan Education Bureau and the Health and Family Planning Commission of Yunnan Province jointly determined the distribution of children (aged 0–18 years) residing within the 28 county districts. After identifying target localities within the 28 districts, the Yunnan Branch of the Red Cross Society of China cooperated in a public relations effort to issue questionnaires within the townships and villages. Local schoolteachers affiliated with the local Education Bureaus (under the administration of the Yunnan Education Bureau) were responsible for educating community members about the screening program and helping participating parents to enroll their children in the study and complete the screening questionnaire. Every person under 18 years of age, whether exhibiting CHD symptoms or not, was encouraged to enroll in the CMRD through their parents. However, there were several reasons for non-enrollment: (I) the child’s parents did not provide their informed consent, (II) the child succumbed to a fatal condition prior to the screen, or (III) the child’s records were incomplete.

Collection of relevant health information via questionnaire

After enrollment, parents were provided with a questionnaire that requested the child’s details, as follows: (I) date of birth (DOB), (II) weight at delivery, (III) height at delivery, (IV) duration of gestation based on the birth certificate, (V) feeding method (breast milk, formulation, etc.), (VI) health history (i.e., any prior infections or congenital conditions, etc.), and (VII) present health condition. The questionnaire also contained questions related to the parents’ details: (VIII) health history and present health condition (e.g., history or presence of CHD hypertension, diabetes, etc.), (IX) lifestyle habits (e.g., alcohol consumption or smoking habits, etc.), and (X) socioeconomic status (e.g., education, occupation, net income, etc.). Finally, the questionnaire asked for details specific to the mother, as follows: (XI) weight-gain from pregnancy, (XII) complications during pregnancy (e.g., gestational diabetes, hypertension, or anemia, infections during pregnancy, medications received during pregnancy, etc.), (XIII) exposure to harmful chemicals (e.g., mercury, lead, benzene, formaldehyde, pesticide, etc.), and (XIV) activities during pregnancy (e.g., home renovation, etc.).

CHD screening procedures

First, a conventional cardiac physical examination by a licensed cardiologist was performed to screen for clinical suspicion of CHD. The cardiologist palpated upper and lower extremity pulses bilaterally and measured blood pressure via sphygmomanometry on the right arm. Jugular venous distension and precordial motion were checked. Cardiac valve areas were auscultated with the patient in a seated position. Typical abnormal signs from physical examination included cyanosis of the lips and nail beds, loud pulmonary valve (P2), murmurs, and splitting of the second heart sound. Quality control (QC) was performed by QC physicians during the screening program. The QC physicians randomly selected 10% of the participants from the physical exam screening and evaluated inter-rater reliability, observing an inter-rater agreement of over 95%.

Second, color Doppler echocardiography was used to confirm the presence of CHD in patients that were clinically suspected of CHD from the physical exam. Philips Sonos 5500 (Philips, Cambridge, MA, USA) color Doppler echocardiograph devices were employed to screen for CHD. An established protocol for CHD detection was employed by a team of trained and certified sonographers, who coordinated the CHD screening effort across Yunnan region.

Patients who were identified as having a CHD by the screening were then referred to a cardiologist, who performed diagnostic testing by heart catheterization to confirm CHD prior to heart surgery. The diagnosed anomalies were as follows: (I) ventricular septal defect (VSD), defined as an opening present in the interventricular septum, (II) atrial septal defect (ASD), defined as an opening present in the interatrial septum (other than a patent foramen ovale (PFO), defined in turn as an opening at the oval fossa measuring less than 5 mm in diameter); (III) patent ductus arteriosus (PDA), defined as a joining between the descending thoracic aorta and the left pulmonary artery, (IV) single ventricle, defined as a larger ventricle dominating a smaller ventricle or as a single ventricle with two atrioventricular valves, (V) pulmonary stenosis, defined as a narrowing or blockage from the right ventricle to the pulmonary artery resulting in elevated blood velocity (>2.0 mm/s), (VI) Ebstein’s anomaly, defined as a deviation in the septal and posterior leaflets from the right atrioventricular valve towards the apex of the right cardiac ventricular chamber (with the extent of deviation measured as the distance between the tricuspid valve and mitral valve and deemed significant when longer than 20 mm). For purposes of analysis, in cases where multiple CHD defects were observed, the case was identified by the most severe anomaly. In addition, CHD patients were assessed for the presence of congenital anomalies (e.g., congenital airway anomalies (CAAs), cleft lip/palate, congenital neurologic anomaly, etc.) and genetic syndromes using the diagnostic criteria stated in the International Pediatric and Congenital Cardiac Code (IPCCC) (9).

Selection of matching healthy control cohort

Participants with CHD validated by color Doppler echocardiography were compared to a demographically-matched healthy control cohort derived from the same county-level district to analyze the risk factors for CHD. The conditions for demographic matching were as follows: (I) participants from the same country-level district and township or village, (II) participants of the same age in years, (III) participants of the same ethnic group, and (IV) participants of the same sex. The healthy control participants did not possess any non-hereditary or congenital diseases. Demographic matching was performed at a 1:10 ratio (i.e., one patient with a CHD was paired with ten healthy control participants). If the participants with a CHD was attending school, 10 healthy control children who were the same age in years, the same ethnicity, and the same sex were selected from the same school grade level as the participant with CHD. If the participant with a CHD was not attending school (e.g., those aged 0–3 years or those unable to attend school), 10 healthy control children who were the same age in years, the same ethnicity, and the same sex were selected from the same township or village as the participant with CHD.

Follow-up on enrollees with CHD

Clinical follow-up was performed on all participants with validated CHD for a period of 1 year. This follow-up included a pre-operative clinical examination (including ultrasound cardiography (UCG), electrocardiography (ECG), chest radiography, liver function, kidney function, and immunological function) as well as post-operative follow-up at 1 week, 3 months, 6 months, and 1 year. Those participants with untreated CHD were also followed-up for a period of 1 year.

Statistical analysis

All statistical tests were conducted with the Predictive Analytics Software suite (PASW, version 20.0, SPSS Statistics 20, IBM, Armonk, NY). Statistically significant results were taken for two-tailed P values of less than 0.05. Significance between the children with CHD and healthy children was computed by two variable tests for nominal data. Significant associations between CHD status and covariate parameters were calculated by logistic regression. The covariate parameters for each child were as follows: age, sex, mass, gestational age, etc. Covariate parameters from the mother were: age at child’s birth, body mass index (BMI) before pregnancy, weight, height, pregnancy issues (e.g., gestational diabetes, hypertension, infection, medication, exposure to harmful chemicals during pregnancy, etc.). The covariate parameters for both parents were as follows: health history and present health condition (e.g., CHD, hypertension, diabetes, etc.), lifestyle habits (e.g., alcohol consumption, smoking, etc.), and socioeconomic status (e.g., education, occupation, net income, altitude, etc.). The multiple imputation method was applied for deal with missing data values.


Results

From January 2001 to December 2016, 2,421 out of 400,855 children screened were conclusively diagnosed with CHD by color Doppler echocardiography (Table 1). This amounted to a prevalence of 6.04 CHD cases per 1,000 children in Yunnan region. We analyzed the presence of CAAs in this 2,421-member CHD cohort. Bronchomalacia and tracheomalacia were the most commonly found CAAs (Table S1). We also analyzed the presence of genetic syndromes in the CHD cohort, with Trisomy 21 and Turner’s syndrome being the most commonly found genetic syndromes (Table S2).

Table 1

Clinicopathological characteristics of the CHD and healthy control cohorts

Variable CHD cohort (n=2,421) Control cohort (n=24,210) P value
Sex, n (%)
   Female 1,253 (51.76) 12,530 (51.76) 1.00
   Male 1,168 (48.24) 11,680 (48.24) 1.00
Age at screening, (years), n (%)
   0–3 551 (22.76) 5,510 (22.76) 1.00
   4–6 488 (20.16) 4,880 (20.16) 1.00
   7–18 1,382 (57.08) 13,820 (57.08) 1.00
Comorbidity, n (%)
   Prematurity (<37 weeks) 347 (14.33) 1,892 (7.81) <0.001
   Cleft lip/palate 21 (0.87) 28 (0.12) <0.001
   CAA (Table S1) 97 (4.01) 11 (0.05) <0.001
   Genetic syndrome (Table S2) 238 (9.83) 28 (0.12) <0.001
   Congenital neurological anomaly 3 (0.12) 8 (0.03) 0.04
   Congenital gastrointestinal anomaly 2 (0.08) 9 (0.04) 0.29
   Congenital genitourinal anomaly 1 (0.04) 14 (0.06) 0.74

CHD, congenital heart defect; CAA, congenital airway anomaly.

The most frequent CHD condition was ASD, accounting for 1.94 cases per 1,000 children (Table 2). VSD was also relatively prevalent, with 1.37 instances per 1,000 children, followed by PFO with 1.29 instances per 1,000 children (Table 2). Out of the 2,421 CHD patient cohort, 187 patients (7.72%) possessed multiple CHD defects, with 172 children (7.10%) possessing two CHD defects, 13 children (0.54%) possessing three CHD conditions, 1 child (0.04%) possessing four CHD conditions, and 1 child (0.04%) possessing five CHD conditions.

Table 2

Prevalence of various CHD defects

CHD defect n Prevalence per 1,000
Atrial septal defect 779 1.94
Ventricular septal defect 548 1.37
Patent foramen ovale 516 1.29
Patent ductus arteriosus 278 0.69
Pulmonary stenosis 47 0.12
Tetralogy of Fallot 41 0.10
Atrioventricular septal defect 29 0.07
Aortic stenosis 13 0.03
Single ventricle 4 0.01
Ebstein’s anomaly 4 0.01
Compound type 65 0.16
Other lesions 97 0.24

CHD, congenital heart defect.

Of the 2,421 CHD patients, 441 cases (18.22%) displayed elevated moderate-severe pulmonary arterial pressure via color Doppler echocardiography. A total of 337 patients of the 2,421 CHD patient cohort underwent corrective surgery, yielding a treatment rate of 13.92%. Out of the 2,421 CHD patients, a total of 231 children perished during their 1-year follow-up period, yielding a 1-year mortality rate of 9.54% (Table S3). Of these 231 CHD children who died during follow-up, 14/231 (6.06%) underwent corrective surgery, making the one-year mortality rate of operative cases to be 14/337 (4.15%).

Subgroup analysis (Table 3) demonstrated a greater prevalence of CHD in female children compared to male children (6.54 per 1,000 females versus 5.59 per 1,000 males). Certain factors related to the children, mothers, and families were also statistically associated with CHD prevalence. The child-related factors that affected the prevalence of CHD were age at screening, birthweight, and duration of gestation. The highest CHD rates were observed in children who were school-aged at screening, weighed less than 2.5 kg at birth, and had a gestational period of less than 37 weeks. Maternal factors that influenced the prevalence of CHD were age, elevated BMI before pregnancy, gestational diabetes, hypertension, anemia, infection, medication, and exposure to harmful chemicals during pregnancy. The greatest frequency of CHD was also observed in babies whose mothers had BMIs greater than 28 kg/m2 before pregnancy and who were older than 40 years old and younger than 20 years old. Family factors that affected the prevalence of CHD were familial history of CHD, education, family income, dwelling altitude, and ethnicity. CHD prevalence was positively associated with parental history of CHD and dwelling altitude but negatively associated with parental education and income. Notably, the Lisu, Jingpo, Achang, Naxi and Tibetan ethnicities displayed the highest CHD prevalence rates compared to the other Chinese ethnic groups included in the study.

Table 3

Prevalence of CHD by various subgroups

Variable Prevalence per 1,000 P value
Child characteristics <0.001
   Sex
    Male 5.59
    Female 6.54
   Age at screening, (years) <0.001
    0–3 4.09
    4–6 6.31
    7–18 7.32
   Birthweight (g) <0.001
    <2,500 11.69
    2,500–<3,000 7.70
    3,000–<3,500 5.86
    3,500–<4,000 5.04
    ≥4,000 5.13
   Gestational age (weeks) <0.001
    <37 10.09
    37 8.09
    38 5.59
    39–40 5.68
    ≥41 5.53
Maternal characteristics
   Maternal age at birth (years) 0.001
    <20 7.40
    20–24 6.73
    25–29 5.62
    30–34 5.89
    35–39 7.01
    ≥40 9.39
   Maternal pre-pregnancy BMI (kg/m2) 0.036
    <18.5 5.71
    18.5–23.9 5.86
    24.0–27.9 6.28
    ≥28 7.28
   Prenatal infection <0.001
    No 5.38
    Yes 58.29
   Prenatal contact with toxic substances 0.003
    No 6.04
    Yes 18.69
   Prenatal medication use <0.001
    No 5.89
    Yes 13.20
   Gestational hypertension <0.001
    No 5.98
    Yes 9.97
   Gestational diabetes <0.001
    No 5.98
    Yes 10.18
   Prenatal anemia 0.001
    No 5.92
    Yes 7.85
Family characteristics
   History of mother with CHD <0.001
    No 6.01
    Yes 38.57
   History of father with CHD <0.001
    No 6.04
    Yes 30.20
   Education of mother (years) <0.001
    ≥16 5.22
    15–16 5.83
    13–14 5.83
    <13 7.61
   Education of father (years) <0.001
    ≥16 5.29
    15–16 6.01
    13–14 6.01
    <13 7.25
   Smoking 0.115
    None 5.74
    Both mother and father 5.07
    Father 6.37
    Mother 2.72
   Family income (yuan/month) <0.001
    <1,000 10.95
    1,000–2,000 8.30
    2,000–3,000 6.07
    >3,000 3.23
   Altitude (m) <0.001
    <1,000 2.45
    1,000–2,000 5.90
    2,000–3,000 7.25
    >3,000 9.45
   Ethnicity <0.001
    Han 5.19
    Tibetan 8.57
    Bai 6.30
    Dai 5.90
    Hani 8.42
    Yi 7.95
    Zhuang 3.59
    Naxi 9.68
    Lisu 15.51
    Wa 8.43
    Jingpo 12.32
    Keno 5.71
    Miao 7.87
    Hui 5.73
    Achang 13.18
    Yao 0.00
    Pumi 0.00
    Others 6.64

CHD, congenital heart defect; BMI, body mass index.

We constructed two models to determine the comparative CHD risk in children (Table 4). Model 1 did not adjust for any covariates, while Model 2 adjusted for all covariates. Covariate parameters considered for the child included: sex, age at screening, mass at birth, and duration of gestational period. Covariate parameters considered for the mother included: age at child’s birth, BMI before pregnancy, gestational diabetes, hypertension, anemia, infection, medication, and exposure to harmful chemicals during pregnancy. Covariate parameters considered for the family included: history of CHD, smoking status, education, family income, altitude, and ethnicity.

Table 4

Odd ratios (and 95% CI) of CHD by various factors

Variable Model 1 Model 2**
Odd ratio 95% CI Odd ratio 95% CI
Child characteristics
   Sex
    Male 1.00 1.00
    Female 1.44 1.31–1.59 1.48 1.34–1.62
    P for difference <0.001 <0.001
   Age at screening, (years)
    0–3 4.23 3.13–5.72 3.71 2.71–5.07
    4–6 1.16 1.00–1.36 1.18 1.01–1.38
    7–18 1.19 1.01–1.39 1.24 1.05–1.44
    P for trend <0.001 <0.001
   Birthweight (g)
    <2,500 2.03 1.70–2.44 1.63 1.29–2.06
    2,500–<3,000 1.25 1.10–1.42 1.18 1.03–1.36
    3,000–<3,500 1.00 1.00
    3,500–<4,000 0.84 0.75–0.95 0.86 0.76–0.97
    ≥4,000 0.96 0.81–1.15 0.97 0.82–1.17
    P for trend <0.001 <0.001
   Gestational age (weeks)
    <37 1.79 1.51–2.11 1.18 0.95–1.47
    37 1.51 1.27–1.79 1.26 1.06–1.52
    38 0.98 0.86–1.12 0.90 0.78–1.03
    39–40 1.00 1.00
    ≥41 0.92 0.80–1.08 0.97 0.83–1.13
    P for trend <0.001 0.032
Maternal characteristics
   Maternal age at birth (years)
    <20 1.26 0.83–1.94 0.95 0.61–1.48
    20–24 1.25 1.10–1.41 1.06 0.93–1.22
    25–29 1.00 1.00
    30–34 1.08 0.96–1.22 1.09 0.97–1.24
    35–39 1.22 1.02–1.46 1.11 0.93–1.34
    ≥40 1.78 1.25–2.50 1.55 1.09–2.20
    P for trend 0.001 0.239
   Maternal pre-pregnancy BMI (kg/m2)
    <18.5 1.01 0.82–1.24 0.97 0.78–1.20
    18.5–23.9 1.00 1.00
    24.0–27.9 1.03 0.90–1.20 1.00 0.85–1.16
    ≥28 1.23 1.00–1.51 1.15 0.93–1.42
    P for trend 0.159 0.454
   Prenatal infection
    No 1.00 1.00
    Yes 14.08 12.10–16.48 14.60 12.20–17.31
    P for difference <0.001 <0.001
   Prenatal contact with toxic substances
    No 1.00 1.00
    Yes 3.44 1.50–7.89 1.15 0.47–2.81
    P for difference 0.005 0.848
   Prenatal medication use
    No 1.00 1.00
    Yes 2.39 1.90–2.98 0.91 0.70–1.18
    P for difference <0.001 0.319
   Gestational hypertension
    No 1.00 1.00
    Yes 1.64 1.24–2.18 1.40 1.04–1.89
    P for difference <0.001 0.016
   Gestational diabetes
    No 1.00 1.00
    Yes 1.75 1.29–2.36 1.82 1.32–2.48
    P for difference <0.001 <0.001
   Prenatal anemia
    No 1.00 1.00
    Yes 1.36 1.14–1.62 1.22 1.01–1.45
    P for difference 0.002 0.074
Family characteristics
   History of mother with CHD
    No 1.00 1.00
    Yes 6.84 3.72–12.60 6.45 3.13–13.26
    P for difference <0.001 <0.001
   History of father with CHD
    No 1.00 1.00
    Yes 5.54 2.19–14.01 4.35 1.53–12.29
    P for difference <0.001 <0.001
   Education of mother (years)
    ≥16 1.00 1.00
    15–16 1.10 0.98–1.26 1.10 0.95–1.28
    13–14 1.15 1.00–1.31 1.11 0.92–1.33
    <13 1.45 1.29–1.65 1.33 1.08–1.65
    P for trend <0.001 0.016
   Education of father (years)
    ≥16 1.00 1.00
    15–16 1.14 1.00–1.30 1.06 0.91–1.24
    13–14 1.13 0.99–1.29 0.98 0.83–1.17
    <13 1.38 1.21–1.56 0.97 0.79–1.20
    P for trend <0.001 0.819
   Smoking
    None 1.00 1.00
    Both mother and father 0.86 0.54–1.39 0.74 0.45–1.22
    Father 1.07 0.97–1.18 1.02 0.92–1.14
    Mother 0.45 0.07–3.24 0.36 0.05–2.65
    P for trend 0.099 0.315
   Family income (yuan/month)
    <1,000 1.37 1.15–1.61 1.16 0.97–1.39
    1,000–1,999 1.19 1.05–1.33 1.00 0.87–1.15
    2,000–2,999 0.99 0.88–1.12 0.92 0.81–1.05
    ≥3,000 1.00 1.00
    P for trend <0.001 0.173
   Altitude (m)
    <1,000 1.00 1.00
    1,000–2,000 0.99 0.88–1.11 0.92 0.82–1.05
    2,000–3,000 1.18 1.05–1.32 1.00 0.88–1.14
    >3,000 1.36 1.15–1.59 1.16 0.97–1.37
    P for trend <0.001 0.179

**, Model 1 did not adjust for any covariates, while Model 2 adjusted for all covariates listed in the above table. CHD, congenital heart defect; BMI, body mass index; CI, confidence interval.

The odds ratios (ORs) and 95% confidence intervals (95% CIs) for CHD risk were calculated for both models (Table 4). Younger age (0–3 years) at screening (OR =3.71, 95% CI: 2.71–5.07), lower birth mass (<2,500 g) (OR =1.63, 95% CI: 1.29–2.06), and shorter duration (<37 weeks) of gestation (OR =1.18, 95% CI: 0.95–1.47) remained significant factors for CHD compared to the healthy control cohort. There was a greater likelihood of CHD for children whose mothers were 40 years of age or older (OR =1.55, 95% CI: 1.09–2.20), suffered from an infection during pregnancy (OR =14.60, 95% CI: 12.20–17.31), and experienced gestational diabetes (OR =1.82, 95% CI: 1.32–2.48) or hypertension (OR =1.40, 95% CI: 1.04–1.89). There was an increased risk of CHD in children whose parents had CHD (mother, OR =6.45, 95% CI: 3.13–13.26; father, OR =4.35, 95% CI: 1.53–12.29) or for children with mothers having less than 13 years of education (OR =1.33, 95% CI: 1.08–1.65).


Discussion

Out of a cohort of 400,855 children in Yunnan region, 2,421 children were diagnosed with CHD, amounting to a prevalence of 6.04 cases per 1,000 children. There was a statistically significant dependence on sex, with 6.54 CHD cases per 1,000 females within a cohort of 1,253 girls versus 5.59 CHD cases per 1,000 males within a cohort of 1,168 boys. After adjusting for covariates, we found that several infant factors (i.e., age at screening, mass at birth, and duration of gestational period), maternal factors (i.e., BMI before pregnancy, age of mother at child’s birth, gestational diabetes, hypertension, and anemia, infection, medication, and exposure to harmful chemicals during pregnancy), and familial factors (i.e., history of CHD, education, and income) significantly influenced the risk of CHD in the children included in the study.

Previous studies have identified similar rates of CHD prevalence in Asian children ranging from 0 to 18 years of age (10,11). That being said, our calculated prevalence of CHD in Yunnan Province children may vary slightly from earlier studies on other populations. Most previous CHD screening programs in China have only enrolled children suspected of possessing a CHD based on signs and symptoms (5,6). In these previous studies, children were initially observed by heart auscultation, and only those individuals exhibiting suspicious signs and symptoms were then examined by non-invasive echocardiography or more invasive cardiac catheterization. However, in our CMRD screening program, all children under 18 years of age—whether exhibiting CHD symptoms or not—were encouraged to enroll through their parents. Therefore, because several instances of CHD have been identified in asymptomatic children, our reported frequency of CHD may be slightly different than those of previous screening programs. Earlier data in nine CHD registries derived from those of specialized cardiology clinics in UK, US, and Sweden from the 1940s to the 1960s, summarized by Hoffman et al. found incidence rates of 3.20–6.00 cases of CHD per 1,000 live births (12). Hoffman et al. speculates that these early figures were inaccurately low compared to more recent median estimates of 7.00–8.00 CHD cases per 1,000 live births due to knowledge deficiencies in CHD diagnosis among pediatricians, only severe CHD cases being diagnosed and referred to cardiology clinics, and a general reluctance to establish CHD diagnoses by invasive cardiac catheterization due to the unavailability of effective diagnostic echocardiography (13). The CHD prevalence rates reported here fall slightly lower than the current median estimates of 7.00–8.00 CHD cases per 1,000 live births (13). This phenomenon may also be due to a combination of factors alluded to by Hoffman et al. or to underlying ethnodemographic differences in the risk of CHD in Western and Chinese populations.

In our study, we found that the CHD prevalence was higher in girls than in boys, which is consistent with reports from other Chinese provinces (14-16). Moreover, CHD prevalence was affected by ethnic status, with the Lisu (15.51 per 1,000), Achang (13.18 per 1,000), Jingpo (12.32 per 1,000), Naxi (9.68 per 1,000), and Tibetan (8.57 per 1,000) ethnicities displaying the highest CHD prevalence relative to Han Chinese (5.19 per 1,000). Yunnan Province possesses the greatest number of ethnic groups among the provinces and autonomous regions in China (17). Minority ethnicities such as the Lisu, Achang, Jingpo, Naxi, and Tibetan typically do not fully assimilate with the Han Chinese majority population and are less likely to intermarry with other Chinese ethnicities (18); therefore, the odds of consanguineous marriages [a genetic factor contributing to CHD risk (19)] is higher in these minority ethnicities. Moreover, critical socioeconomic factors should also be taken into account; for instance, some minority groups, such as Lisu, Achang, and Jingpo, have significantly lower average incomes than Han Chinese (20). The etiologies of ethnically-based differences in CHD prevalence remain largely unstudied, so further studies should be conducted to illustrate the roles (if any) that genetic susceptibility and socioeconomic factors may play in the risk of CHD.

The most frequent CHD defect in our study was ASD, which occurred at a rate of 1.94 cases per 1,000 children. This rate was lower than in previous CHD screening programs. For example, 10.6 cases per 1,000 Chinese live births was found in 2015 (15), 3.77 cases per 1,000 Brazilian live births was found in 2003 (21), and 3.89 cases per 1,000 Canadian infants was found in 2000 (22). Our rates of ASD may be lower than these studies due to the differentiation of ASD from PFO in our analysis; if we were to merge our ASD and PFO prevalence rates together, then the resulting figure of 3.23 cases per 1,000 children more closely approximates that of previous studies.

The formation of the heart is a complicated developmental process that can be disrupted by a variety of factors, possibly leading to a structural defect (23). A particularly critical developmental period occurs from the second to eighth week of pregnancy (24). For example, contracting a viral infection or receiving medications during the first trimester increases the risk of CHD occurrence (25,26). In addition, the genetic makeup of the fetus is a known risk element for CHD, with the genetic predisposition controlled by a complex gene inheritance pattern (27). Consistent with this theory, we observed a greater predisposition to CHD in children whose mothers and fathers also possessed CHD at birth. Our study also revealed a number of maternal features that correlated positively with CHD prevalence, including advanced age, higher BMI before pregnancy, gestational diabetes, hypertension, and anemia, infection, medication, and exposure to harmful chemicals during pregnancy. These findings largely match those of a previous CHD screening study conducted in Tianjin, China (15). In particular, the relationship between diabetes and CHD risk is a complex one. The prevalence of CHD in the offspring of mothers with diabetes ranges from 3% to 5%, a significantly higher figure than in mothers without diabetes (28). Moreover, CHD survivors possess an increased risk of developing type 2 diabetes after age 30, with cyanotic CHD survivors being at particular risk (29). On a molecular level, we know that gestational diabetes induces Smad2 activation and alters endothelial growth factor expression in areas of the heart most susceptible to CHD (30). With respect to advanced age, older mothers are more likely to harbor de novo mutations in transcription factors regulating cardiac formation, while younger mothers have been linked to other kinds of birth anomalies (31). Unfortunately, the precise molecular pathway(s) associated with these maternal risk factor-related CHD defects remain largely unknown and require further investigation.

One interesting finding from our screening program was that the mother’s degree of education influenced the prevalence of CHD. It is possible that the lower levels of socioeconomic resources typically available to children with poorly-educated mothers could lead to poorer outcomes due to inferior access to healthcare services and adequate nutrition. Likewise, lower levels of maternal education may lead to inferior lifestyle choices, such as prenatal smoking or alcohol consumption, which contribute to increased CHD risk in her offspring. That being said, improving population-based screening can help alleviate negative outcomes by improving CHD diagnosis rates in at-risk children with these characteristics.

Every child our screening identified as having CHD was referred to a cardiologist in Yunnan region for follow-up care. Out of the original 2,421 children to have been diagnosed with CHD, a total of 231 children (9.54%) perished during their 1-year follow-up period. This relatively high 1-year mortality rate may be attributable to two factors: (I) some children with CHD defects did not receive a timely diagnosis at an earlier point in their life and had progressed to a near-fatal condition at the time of screening; and (II) some families of the patients with CHD had disadvantaged socioeconomic conditions and did not have the ability to medically manage their child’s condition.

This study possesses several strengths, including the large cohort size, the use of non-invasive, accurate ultrasonic color Doppler imaging that can detect even small CHD defects, and our application of rigorous statistical analyses. This study also suffers from some limitations. First, risk factors were evaluated by a transverse study rather than a longitudinal one; therefore, it is not possible to establish causality between risk factors and CHD. Although we attempted to screen the entire population of the CMRD, a portion of children died before performance of the screen; some of these succumbed to acute severe CHD, which means that the morbidity of CHD could be underestimated. As health records become more widely digitized, we may be able to account for these cases in future analyses.

We employed non-invasive ultrasonic color Doppler imaging in a targeted screening study for CHDs among children aged 18 years and under in China’s Yunnan region. Our study revealed a CHD prevalence of 6.04 per 1,000 children in Yunnan Province. We also identified several child-associated and maternal risk factors that predisposed children to a higher risk of CHDs in this population, which may help identify at-risk patients in future screening efforts.


Acknowledgments

We would like to thank the patient participants, patient advisers, and CMRD personnel that made this study possible.

Funding: This work was supported by the National Natural Science Foundation of China (Nos. 81760059, 81960068) and the Yunnan Health Training Project of High-Level Talents (Nos. YNWR-QNBJ-2020-263, H2017018) and Special Joint Program of Yunnan Province (No. 2018FE001-181).


Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://tp.amegroups.com/article/view/10.21037/tp-21-371/rc

Data Sharing Statement: Available at https://tp.amegroups.com/article/view/10.21037/tp-21-371/dss

Peer Review File: Available at https://tp.amegroups.com/article/view/10.21037/tp-21-371/prf

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tp.amegroups.com/article/view/10.21037/tp-21-371/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 (as revised in 2013). This study obtained approval from the Ethics Review Committees at The First People’s Hospital of Yunnan Province, Kunming, China (No. KHLL2020-KY019) and Yan’an Affiliated Hospital of Kunming Medical University, Kunming, China (No. YYHKM04584). Written informed consent was obtained from all participants’ parents or legal guardians prior to their enrollment.

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. van der Linde D, Konings EE, Slager MA, et al. Birth prevalence of congenital heart disease worldwide: a systematic review and meta-analysis. J Am Coll Cardiol 2011;58:2241-7. [Crossref] [PubMed]
  2. Sun R, Liu M, Lu L, et al. Congenital Heart Disease: Causes, Diagnosis, Symptoms, and Treatments. Cell Biochem Biophys 2015;72:857-60. [Crossref] [PubMed]
  3. Wren C, O'Sullivan JJ. Survival with congenital heart disease and need for follow up in adult life. Heart 2001;85:438-43. [Crossref] [PubMed]
  4. Botto LD, Correa A, Erickson JD. Racial and temporal variations in the prevalence of heart defects. Pediatrics 2001;107:E32. [Crossref] [PubMed]
  5. Liu WT, Ning SB, Hua BJ, et al. The incidence and its characteristics of congenital heart disease in Yangpu and Xuhui districts of Shanghai. Chinese Journal of Pediatrics 1995;33:347-9.
  6. Wang H, Yuan X, Xi Y, et al. Prevalence study of congenital heart disease in 19432 children aged 0-2. Chin J Child Health Care 2001;9:236-38.
  7. Evans DH, Jensen JA, Nielsen MB. Ultrasonic colour Doppler imaging. Interface Focus 2011;1:490-502. [Crossref] [PubMed]
  8. China NBoSo. Communiqué of the national bureau of statistics of People’s Republic of China on major figures of the 2010 population census. Beijing: National Bureau of Statistics of China Press, 2011.
  9. Franklin RCG, Béland MJ, Colan SD, et al. Nomenclature for congenital and paediatric cardiac disease: the International Paediatric and Congenital Cardiac Code (IPCCC) and the Eleventh Iteration of the International Classification of Diseases (ICD-11). Cardiol Young 2017;27:1872-938. [Crossref] [PubMed]
  10. Yan HQ, Chen YH, Ying CN. Prevalence study of congenital heart disease in 17933 children aged 0-2. Maternal and Child Health Care of China 2006;21:82-3.
  11. Kapoor R, Gupta S. Prevalence of congenital heart disease, Kanpur, India. Indian Pediatr 2008;45:309-11. [PubMed]
  12. Hoffman JI. Natural history of congenital heart disease. Problems in its assessment with special reference to ventricular septal defects. Circulation 1968;37:97-125. [Crossref] [PubMed]
  13. Hoffman JI, Kaplan S. The incidence of congenital heart disease. J Am Coll Cardiol 2002;39:1890-900. [Crossref] [PubMed]
  14. Liu F, Yang YN, Xie X, et al. Prevalence of Congenital Heart Disease in Xinjiang Multi-Ethnic Region of China. PLoS One 2015;10:e0133961. [Crossref] [PubMed]
  15. Liu X, Liu G, Wang P, et al. Prevalence of congenital heart disease and its related risk indicators among 90 796 Chinese infants aged less than 6 months in Tianjin. International Journal of Epidemiology 2015;44:884-93. [Crossref] [PubMed]
  16. Chun H, Yue Y, Wang Y, et al. High prevalence of congenital heart disease at high altitudes in Tibet. Eur J Prev Cardiol 2019;26:756-9. [Crossref] [PubMed]
  17. Postiglione GA. Schooling and inequality in China. In: Postiglione GA. Education and social change in China: Inequality in a Market Economy. New York: Routledge, 2015:17-38.
  18. Jian Z. The recent trend of ethnic intermarriage in China: an analysis based on the census data. The Journal of Chinese Sociology 2017;4:11. [Crossref]
  19. Shieh JT, Bittles AH, Hudgins L. Consanguinity and the risk of congenital heart disease. Am J Med Genet A 2012;158A:1236-41. [Crossref] [PubMed]
  20. Yunnan Bureau of Statistics.China Statistics Print Retrieved, 2013-10-24. Available online: http://stats.yn.gov.cn/tjsj/tjnj/201901/t20190121_834601.html
  21. Amorim LF, Pires CA, Lana AM, et al. Presentation of congenital heart disease diagnosed at birth: analysis of 29,770 newborn infants. J Pediatr (Rio J) 2008;84:83-90. [Crossref] [PubMed]
  22. Marelli AJ, Mackie AS, Ionescu-Ittu R, et al. Congenital heart disease in the general population: changing prevalence and age distribution. Circulation 2007;115:163-72. [Crossref] [PubMed]
  23. Simmons MA, Brueckner M. The genetics of congenital heart disease… understanding and improving long-term outcomes in congenital heart disease: a review for the general cardiologist and primary care physician. Curr Opin Pediatr 2017;29:520-8. [Crossref] [PubMed]
  24. Eleftheriades M, Tsapakis E, Sotiriadis A, et al. Detection of congenital heart defects throughout pregnancy; impact of first trimester ultrasound screening for cardiac abnormalities. J Matern Fetal Neonatal Med 2012;25:2546-50. [Crossref] [PubMed]
  25. Liu S, Liu J, Tang J, et al. Environmental risk factors for congenital heart disease in the Shandong Peninsula, China: a hospital-based case-control study. J Epidemiol 2009;19:122-30. [Crossref] [PubMed]
  26. Oster ME, Riehle-Colarusso T, Alverson CJ, et al. Associations between maternal fever and influenza and congenital heart defects. J Pediatr 2011;158:990-5. [Crossref] [PubMed]
  27. Bruneau BG. The developmental genetics of congenital heart disease. Nature 2008;451:943-8. [Crossref] [PubMed]
  28. Gao Y, Huang GY. Advance in the etiology and the epidemiology of congenital heart disease. Chinese Journal of Evidence-Based Pediatrics 2008;3:213-22.
  29. Madsen NL, Marino BS, Woo JG, et al. Congenital Heart Disease With and Without Cyanotic Potential and the Long-term Risk of Diabetes Mellitus: A Population-Based Follow-up Study. J Am Heart Assoc 2016;5:e003076. [Crossref] [PubMed]
  30. Roest PA, Molin DG, Schalkwijk CG, et al. Specific local cardiovascular changes of Nepsilon-(carboxymethyl)lysine, vascular endothelial growth factor, and Smad2 in the developing embryos coincide with maternal diabetes-induced congenital heart defects. Diabetes 2009;58:1222-8. [Crossref] [PubMed]
  31. Reefhuis J, Honein MA. Maternal age and non-chromosomal birth defects, Atlanta--1968-2000: teenager or thirty-something, who is at risk? Birth Defects Res A Clin Mol Teratol 2004;70:572-9. [Crossref] [PubMed]
Cite this article as: Cao Y, Huang R, Kong R, Li H, Zhang H, Li Y, Liang L, Xiong D, Han S, Zhou L, Guo J, Dai G, Meng M, Lou H, Hou Z, Jiang L. Prevalence and risk factors for congenital heart defects among children in the Multi-Ethnic Yunnan Region of China. Transl Pediatr 2022;11(6):813-824. doi: 10.21037/tp-21-371

Download Citation