Congenital Heart Defects (CHD)

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Introdution

Congenital heart defects (CHDs) are the most common group of congenital malformations affecting nearly 1% of live births throughout the world [1]. CHDs account for approximately one-third of all congenital anomalies, and are the leading noninfectious cause of death in the first year of life [2]. Even though massive breakthroughs have been achieved in cardiovascular diagnostics and cardiothoracic surgery over the past century, leading to an increased survival of newborns with CHDs, but the etiology of most congenital heart defects is still unknown. Several chromosomal anomalies, certain maternal illnesses, and prenatal exposures to specific therapeutic drugs are recognized risk factors. It is difficult to establish the role of a single factor, because in many cases, the cause of a defect is believed to be multifactorial, including environmental teratogens with genetic and chromosomal conditions [3]. CHDs include several distinct subtypes (e.g., conotruncal defects, left ventricular outflow track defects, septal defects), there is a potential for etiologic heterogeneity.

A variety of approaches to the conceptualization and measurement of socioeconomic status (SES) (social class, social status, etc) have been taken, reflecting different theoretical orientations on the one hand and the exigencies of conducting research on the other. The debate on the conceptualization of SES has a long history as part of sociological theory, and it can be divided to the Weberian approach () and the Marxist approach ().Although the Weberian and Marxist approaches have had some impacts on studies of the association between maternal SES and CHD, most studies are in general best characterized by their theoretical eclecticism. In our study, we used the most commonly measures, indexes, and ecological measures of SES, which is typically characterized byincome level, occupation category, and education attainment. According to International Standard Classification of Occupations (ISCO-08), skill level is used to arrange occupations into groups. Skill level is defined as a function of the complexity and range of tasks and duties to be performed in an occupation, which include four groups from low level to high level. Lower SES is often associated with health-damaging lifestyle resulting in the development of poor dietary habits as well as influencing behaviours related to smoking and physical activity. Previous studies have reported that Low SES increases the risk of developing chronic health conditions such as cardiovascular disease and diabetes mellitus (Strike PC,2004; Tamayo T,2010). Recently, there has been a steep increase in the number of maternal SES studies with CHDs as the primary health outcome; however, the evidence has been mixed, with some studies showing positive associations and others providing null results. There are also different conclusions for CHDs subtypes, for example, low SES has been reported to be associated with increased risk of certain anomalies including d-transposition of the great arteries, but reduced risk of tetralogy of Fallot (Carmichael 2003).

To date, mounting studies have focused on the association between the maternal SES and CHDs; however, results have been ambiguous, possibly because of inadequate sample sizes. Therefore, we conducted a meta-analysis to quantitatively assess the effect of maternal SES on CHDs.

Materials and Methods

Literature search

A computerized literature search was conducted in MEDLINE and EMBASE from their inception to January 1, 2014, by two independent investigators (Yu and Feng). We searched relevant studies using the following strategy: (“Socioeconomic Status” OR “Social Class” OR “Middle Class Population” OR “Caste” OR “education” OR “occupation” OR “income”) AND (“abnormalities” OR “birth defects” OR “congenital anomaly” OR “malformations” OR “congenital malformations” OR “congenital heart defect” OR “Heart Abnormality” OR “Malformation of heart” or “CHD”) AND (“maternal” OR “mother” OR “periconceptional” OR “pregnant” OR “gestation”). In addition, we carried out a broader search on environmental teratogens and CHDs and check the reference lists of retrieved articles and relevant review articles so as to identify additional relevant studies.

Eligibility Criteria

We selected articles that (1) were original epidemiologic studies (i.e., case–control, cohort, or cross-sectional studies), (2) were published in the English language, (3) examined the association between maternal SES and CHDs overall or any one of the CHD subtypes in infants, (4) reported RRs (i.e., risk ratios or odds ratios) and associated 95 % confidence intervals (CIs) or had raw data available, (5)defined CHDs or one of the CHD subtypes as an outcome, and (6) provided exposure information. Articles that reported results from more than one population were considered as separate studies. Non-peer-reviewed articles, ecologic assessments, correlation studies, experimental animal studies and mechanistic studies were excluded.

Data extraction

Data extraction was carried out separately by two reviewers (Yu and Feng) working independently. Where differences of opinion arose, these were resolved by discussion between the two. The studies meeting the inclusion criteria were reviewed to retrieve information of interest including study characteristics (i.e., authors, year of publication, geographic region, periods of data collection, study design, case classification, control definition, sample size, source of exposure data, and maternal socioeconomic status (income level, occupation category, and education attainment) and to record reported effect estimates and associated 95 % CIs as well as raw data if effect estimates were not available. If the original study reported risk estimates in association with more than one measure of SES, each estimate was extracted and then analyzed as its own association with the specific SES.

RR was used as the measure for the summary statistic of associations between maternal SES and CHD risk. To simplify the procedure, RR represented all reported study-specific results derived from cohort studies and OR from case-control studies. RR estimates and 95 % CIs were extracted from each study for CHDs overall and CHD subtypes. To augment comparability between the studies using different SEP categories, we compared the lowest with the highest SEP category. If the original study reported the risk estimates not in this order, we back-calculated the point estimate and 95% CI. For the articles that did not report estimates in the form of RR or OR, the risk estimates and 95% CI were recalculated from the presented raw data by using standard equations.

Statistical analysis

The strength of the association between maternal SES and CHD risk was evaluated by RR with 95% confidence intervals. We calculated pooled RR and accompanying 95% confidence interval (95% CI) for the lowest versus the highest categories of both income and education. Occupation include four groups from low level to high level, and pooled RR and accompanying 95% CI were calculated for the first versus the fourth , the second versus the fourth, the third versus the fourth categories.

We tested for heterogeneity across studies using Cochran Q and I2 statistics [9]. If there was an evidence of heterogeneity (P<0.05 or I2≧50%), we used a random-effects model, which provided a more appropriate summary effect estimate between heterogeneous study-specific estimates. If the Cochran Q and I2 statistics showed no evidence of heterogeneity, we used a fixed-effects analysis, applying inverse variance weighting to calculate summary RR estimates [10].

Publication bias was evaluated by generating funnel plots for a visual examination, conducting correlation and regression tests for significance, and using Egger’s linear regression [11] and Begg’s rank correlation [12] methods. A P value of <0.05 for the two aforementioned tests was considered representative of significant statistical publication bias. All statistical analyses were performed by using STATA (version 11.0; StataCorp, College Station, Texas, USA).

Results

Study characteristics

The search strategy generated 3343 citations, of which 30 were identified in the final analysis for 52375 incident cases (Figure 1). All of the studies were published form 1989–2013. There were 28 case–control studies [], 2 cohort studies [].The main study characteristics of included studies are shown in Table 1. As shown, 17 studies [] were conducted in the United States/Canada, 10 in Europe [], and 2 in other regions (1 in China and 1 in Egypt) [].Meanwhile, 26 studies were conducted in high-income countries, and 4 in middle or low-income countries. Among these studies, 27 investigated the association of educational attainment with CHD risk, and 5 examined the association of income level with CHD risk; 5 examined the association of occupational categories with CHD risk.

Overall result

The overall results of this meta-analysis provided evidence of a significant increase in the risk of CHD among the lowest socioeconomic categories for all three socioeconomic indicators (figure 2-4). Heterogeneity was observed for education and occupation (p<0.01) (Table 2).

Association of SES categories with CHD risk

27 studies evaluated the association between maternal educational attainment and CHDs as a group (Table 2). We found that maternal educational attainment was associated with an 11% increased risk of CHDs (RR =1.11, 95% CI: 1.02, 1.21) (Figure 2). Statistically significant heterogeneity was detected (Q= 86.03, P<0.001, I2 = 64.0%), with no publication bias (Begg’s test: P=0.06, Egger’s test: P =0.16) (Figure 5). When stratified by country’s income group, 8% increment was found among high-income countries (RR = 1.08, 95% CI: 0.99, 1.18), meanwhile, a significant increment (44%) was found among middle or low income countries in education (RR = 1.44, 95% CI: 1.07, 1.17). Corresponding with this, in subgroup analysis by geographic reign, null results were found among European (RR = 1.30, 95% CI: 0.96–1.77) and North American studies (RR = 1.05, 95% CI: 0.95, 1.15). The results were fairly consistent with the overall summary measure when the analysis were restricted to cohort studies (RR = 1.26, 95% CI: 1.21, 1.31) and under 1000 sample size (RR = 1.28, 95% CI: 1.05, 1.57). However, no significant association was observed between case-control studies (RR = 1.09, 95% CI: 0.99, 1.20) and More than 1000 sample size (RR = 1.08, 95% CI: 0.98, 1.18).An increased incidence of CHD was observed when studies on income were pooled (RR=1.05, 95% CI: 1.01, 1.10) (Table 2) with no heterogeneity (Q= 3.54, P = 0.618, I2 =0.0%) and publication bias (Egger’s test: P =0.96)(Figure 3).For occupational categories, Figure 4 shows the relationship between SES, categorized by occupation in classes one to four, and CHD. In most of the studies reviewed, risk of CHD was higher in the lowest classes and affected the entire SES spectrum: the first versus the fourth (RR =1.51, 95% CI = 1.09–2.24), the second versus the fourth (RR =1.12, 95% CI: 1.00, 1.26), the third versus the fourth (RR =1.18, 95% CI: 1.00, 1.39). In high income countries, maternal occupation categories were associated with a 7% increased risk of CHDs (For the first level vs. the fourth level, RR =1.07, 95% CI: 0.92, 1.24), meanwhile, a significant increment (155%) was found among middle or low income countries in education (RR = 2.55, 95% CI: 1.76, 3.70).

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