Introduction

Congenital heart disease (CHD) represents the most common form of congenital malformations, with an estimated incidence of 8–12 cases per 1000 live births, being the first cause of death within this group, explaining 6–10% of the overall mortality and up to 40% of deaths from congenital defects.1 Although the proposed etiology is multifactorial,2 the studies reported to date show variable results, noting ethnic, racial, demographic, socioeconomic, and exposure differences, among others. These variations can also be explained by the availability of diagnostic methods and the type of study used.3,4,5 Approximately 25% of CHDs have a known genetic cause, 10% have associated environmental factors, and the remaining 65% remain of unknown cause, possibly of a multifactorial and epigenetic nature.4,6

On the other hand, the World Health Organization (WHO) defines the Social Determinants of Health, DSS, as “the circumstances in which people are born, grow, work, live and age, including the broader set of forces and systems that influence the conditions of everyday life.”6 Through the different conferences and declarations made on this topic, a consensus has been reached in which the key to dealing with the profound inequities that exist today between various groups of the population, both globally and within each country, is to generate a growing collective awareness of the need to intervene in such determinants.6

It is of great importance for society to clarify how inequalities in the distribution of social goods such as income, wealth, stable employment, healthy eating, healthy lifestyles, access to health services, education, and recreation, among others, are manifested by generating differences unfair in the health status of social groups.7 Few studies have analyzed CHD from the perspective of the social determinants of health. Findings from these studies have found that low socioeconomic status, low income, and low parental education represent a higher risk for the development of heart disease.1,8,9 However, these associations are not enough to explain most CHDs, so this study aimed to analyze the social determinants in a group of families with children affected by CHD, performing an analysis based on the severity of the disease and their association with such determinants.

Methods

Design

This is an analytical cross-sectional study.

Population and sample

The study population comprises 140 families of children with CHD treated in a high complexity institution, specializing in cardiovascular diseases, in the city of Bucaramanga.

Study variables

The main dependent variables were the presence of CHD classified according to Mortality risk defined by the RACHS-1 Score (Risk Adjustment in Congenital Heart Surgery) and Complexity defined by the STS Score (Society of Thoracic Surgeons score). The independent variables considered were: sex, age (months), birth weight (g), socioeconomic level, parents’ education, parents’ occupation and age, family income, displacement status, place of residence, prenatal maternal nutritional status. birth control, nutritional status of the child, maternal prenatal exposures (smoking, insecticides, herbicides, alcohol, psychoactive substances), maternal and paternal diseases, access to health services, participation in programs and public policies, number of children, time of onset of symptoms and attendance at medical centers, and history of congenital malformations in relatives up to the second degree (history of CHD in relatives).

Data collection

This process was carried out for 12 months, in which a survey was conducted on the mother, father, or main caregiver who was able to answer it. The data collection activity was carried out by two professional nurses who are part of the pediatric heart surgery service, previously trained by the study researchers. All parents or caregivers of the participants who agreed to participate in the study signed an informed consent form. Families were selected from hospital and outpatient services.

Data quality

Data quality was checked to ensure data completeness. The survey was conducted digitally using tablets to capture the information. The questionnaire was created on the Commcare mobile platform and the data were recorded in a database in the Excel program.

Statistical analysis

A descriptive analysis was performed in which the categorical variables were expressed as proportions and the continuous variables as arithmetic means and their corresponding standard deviation (SD) if they had a normal distribution. Otherwise, these variables were described as medians and their interquartile range (IR). Chi2 test was used to determine whether there were statistically significant differences between the categorical variables and the Student’s t test or the Mann–Whitney U-test for the continuous variables, according to their distribution. The analyses were performed in Stata version 15.

Results

Characteristics of the participants

The sample consisted of 140 families, most of them (82.8%) belonging to low socio-economic levels (taking into account the socioeconomic stratum defined by the National Administrative Department of Statistics, DANE, and the Beneficiary Selection System for Programs Social -SISBEN-). Family income (in terms of current legal monthly minimum wages) was also taken into account.10 There was no sex predominance. In all, 22% of children were diagnosed with heart disease during pregnancy. The median age of the child population included was 8.7 months (IR: 30 months). Most families lived in urban areas (73.5%), with a predominant percentage from the Colombian Andean area (53.7%), 28.2% from the Caribbean area, 7.5% from the Orinoquía, and 2.0% were international patients (Aruba, Venezuela, and Ecuador). No significant differences were found in the evaluation of social determinants regarding the severity of heart disease (based on the analysis of the RACHS-1 (from the English: Risk Adjustment in Congenital Heart Surgery) and the STS (from the English, Society of Thoracic Surgeons score).11,12 No statistically significant differences were found either for the severity and mortality from CHD according to the age of the parents, the number of children, origin, religion, belonging to minority population groups, schooling, and occupation of the parents, and their family income. Table 1 summarizes the main variables included.

Table 1 Sociodemographic and clinical characteristics of the study population according to the risk of mortality measured by Score Rachs and Complexity measured by Score STS.
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The families were made up of both parents and between one and three children (93%). Three couples (2.1%) were consanguinity. Most of the mothers were housewives (67.1%) with a median age of 24 years, while for the fathers it was 30 years. Thirty-eight (27.1%) of them had a formal employment relationship in different professions, the main profession being agriculture (18.6%), followed by jobs related to construction (12.4%). Eleven couples (7.6%) belonged to some indigenous ethnic group. The mothers had completed 11 academic years on average and the men 10 years. Regarding the personal pathological history, 10.3% of the mothers and 8.9% of the fathers had a history of diseases, such as asthma, diabetes, and hypertension, among others. Only one of the mothers had a history of CHD (tetralogy of Fallot). In all, 75.6% of the mothers had a normal preconception nutritional status.

Of the total, 26.9% of the women had started prenatal control after the fourth month of gestation and 28.3% managed to perform four or fewer prenatal controls. About 5% of the women stated that they had used psychoactive drugs during pregnancy, 12.4% alcoholic beverages, 11.7% smoked cigarettes, 36% of the mothers reported frequently sharing spaces with cigarette smokers, 48.5% reported contact with substances for agricultural use, and 34.2% daily exposure to wood smoke.

Seventeen women (12.1%) were diagnosed with micronutrient deficiency during pregnancy, 13 of them due to anemia. Twenty-three (15.9%) received some type of antibiotic (especially beta-lactams) at some point during pregnancy. Only 32 (22.0%) had in utero heart disease suspected by prenatal ultrasound.

The frequencies of CHD in children were divided into general pathophysiological groups for analytical purposes, as shown in Table 2. Eleven of the children had Down syndrome, two of them heterotaxy and one Noonan syndrome.

Table 2 Frequency of congenital heart disease by pathophysiological groups.
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Social determinants associated with severity of heart disease

Bivariate and multivariate analyses were performed to evaluate the social determinants and their relationship with the severity of CHD. Thus, 16 children (11.5%) were found to have a RACHS-1 greater than 3 and 37 (26.8%) and an STS score greater than 3. No statistical differences were found between heart disease and its severity based on these scales. In aspects such as sex, genetic syndrome, age of the parents, history of exposure or consumption of tobacco or psychostimulant substances during pregnancy, number of children, religion, belonging to minority population groups, education, and occupation of the parents, as well as the area of origin, no statistically significant differences were found either.

After grouping the heart diseases according to their physiology into cyanotic, non-cyanotic, and single ventricle, an analysis based on severity was performed for both the RACHS-1 and STS scores, in which statistically significant differences were found in the three groups in relationship with low socioeconomic status, exposure to cigarette smoke and wood smoke during pregnancy, as shown in Tables 3 and 4. There was a greater strength of association between the variables of interest in the group of single ventricles in these aspects when compared to the other pathophysiological groups. For some other variables, significant associations were found, but not consistently in the two models based on the evaluated score.

Table 3 Association between social determinants and congenital heart disease adjusted by the RACHS-1.
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Table 4 Association between social determinants and congenital heart disease adjusted for Complexity (Score STS).
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Discussion

Establishing the etiology of CHD continues to be a challenge. Several studies have warned of the possible association between social determinants and the presence of heart disease.1,2,6,7 These factors could play an important role in epigenetic events, which would explain the geographical differences in the incidence and type of heart disease.2 The present study found a relationship between certain social determinants, potentially modifiable, with the type of heart disease and its complexity, an aspect not described so far in the reported series.

Different studies have studied the relationship between low socioeconomic status and its impact on children with CHD. The study by Pace et al. demonstrated, for example, how low economic status and sociodemographic factors related to it affected the survival of children with CHD regardless of the pathology group studied, with some differences when taking into account the type of heart defect.13 Nembhard et al., for their part, also found differences in the mortality of children with this condition when the maternal ethnic group was analyzed in a study based on the Texas Birth Defect Registry, of children born with CHD from 1996 to 2003.14 The relationship of factors associated with low socioeconomic status would cause a gap to exist in the social determinants, still unclear, when they are compared with the most favored families. On the other hand, but from an etiological point of view, Aghan et al. found that low socioeconomic status favored the presence of severe and non-severe heart defects, with the low educational level being the only significant factor in severe cases, thus proposing that this factor could influence this difference, allowing, for example, greater access to therapeutic abortion in the group with a better educational level.1

However, one of the latent difficulties when evaluating the social determinants of a population and its impact on health status could be related to the way in which low socioeconomic status has been established in the different studies since this would include not only monthly monetary income, but also aspects related to the geographic area of residence, the sociopolitical structure of the country or jurisdiction evaluated, or even access to quality health and education services, among others, for which precise definitions are required to better define the real social level of a family. In the present study, families with a low economic level (determined by social stratum according to DANE criteria),10 exposure to cigarette smoke and wood smoke during pregnancy, turned out to be social determinants associated with the severity of heart diseases analyzed by physiological groups. Although these could be related, as previously mentioned, to epigenetic changes, which would partly explain the regional differences described, there are no studies that investigate such changes at the population level.

There is growing evidence of the association of cigarette exposure, either as a previous active or passive smoker and during pregnancy (even after stopping) with the development of several congenital malformations in the child.15,16,17,18,19 Several of the components of tobacco and tobacco smoke have been associated with teratogenic or embryogenic phenomena in animal models, with nicotine and carbon monoxide being the most studied given their ability to cross the placenta and therefore reach the fetal circulation.20 The mechanisms involved in the development of these conditions are not yet completely clear, nor can they be considered as an independent factor, although some studies have shown their association mainly with septal and left ventricular outflow tract defects, being more significant when exposure occurred before and after conception.17 Probably the phenomenon of fetal hypoxia related to tobacco, determined by the vasoconstrictor effect of nicotine on the uterine arteries and the increase in the concentration of carboxyhemoglobin in the fetus due to carbon monoxide, contributes to the development of embryopathy.20 The rest of the components of tobacco have not been analyzed in-depth and unfortunately, most of the studies have been carried out establishing exposure through surveys (qualitative evaluation), which could favor the presence of various biases, since the existence of a dose-effect relationship would be likely (after measurement of blood or urine concentrations of nicotine in the pregnant mother, to mention one example). The findings of this study could have an impact on public health to the extent that policies are implemented to reduce exposure to cigarettes, especially during pregnancy.

Similarly, more than 250 organic compounds generated from the combustion of wood have been identified, some volatilized with the ability to recondense into fine particles and other pyrolysis products secondary to the reactions of said process, noting in addition to particulate material, aromatic hydrocarbons, levoglucosan, carbon monoxide, and nitrogen dioxide. These will vary according to the type of wood studied.21 There are studies that associate indoor pollution due to products of biomass combustion (including wood) and different pathological conditions. In the pediatric population, most of them are related to respiratory disease, low birth weight, excess perinatal mortality, and sudden infant death syndrome.22 Although there are controversial studies in which the presence of various congenital malformations is associated with proximity or direct exposure to incinerators, as an example of the emission of biomass products,23,24,25,26 the association after exposure to wood smoke does not has been systematically reported. Oxidative stress with subsequent recruitment of inflammatory cells and generation of reactive oxygen species after entry into the respiratory system and even the bloodstream of particulate matter and high concentrations of toxic gases such as carbon monoxide have been implicated as reasonable mechanisms. in the generation of these pathologies,22,27 and that could also explain cardiac embryopathy. This study found significant statistical differences related between potentially modifiable factors and the pathophysiological group of heart disease, which could explain the geographical differences in the incidence of its different types according to the region studied. Unfortunately, given the selection of the sample, the number of participants, the varied type of heart disease included, and the risk of data loss affected by recall bias could influence the results obtained in the long run.

Finally, it is important to highlight that a total of 530,000 households in a situation of extreme poverty, where 2.1 million Colombians live, face the risk factor (use of fossil fuels in the home).28

In Colombia, there is a guideline from the National Council for Economic and Social Policy (CONPES), Document CONPES 3550 of 2008, which in the formulation of its action plan considered the control of the use of traditional fuels and previously, since 2007, a study commissioned by the World Bank had made indoor pollution visible as one of the environmental priorities for reducing poverty in the country.29

Perhaps, as has been mentioned, the development of CHD has a multifactorial origin, where, without a doubt, social determinants play an important role. There is of course the influence of confounding factors that would further complicate the establishment of these relationships. Perhaps the combination and potentiation between some of them favor the presentation and its severity. The detection of such determinants could support interventions from the field of public health that truly impact child health. Population-based studies that include quantitative exposure assessment are required to clearly define which are the most relevant and which could be modifiable.

The conclusions were that exposure to cigarette smoke, wood smoke during pregnancy, and low socioeconomic status were found to be social determinants associated with the severity of heart disease analyzed by physiological groups. The detection of such determinants could support interventions from the field of public health that have an impact on the incidence and severity of this type of congenital defect.