Modeling geographic risk of complex congenital heart defects in Eastern Wisconsin

Geospatial Distribution of Prenatally and Postnatally Diagnosed Congenital Heart Disease: Implications for Equitable Care from a Fetal Heart Society Research Collaborative Study

OBJECTIVE

To characterize patterns in the geospatial distribution of pre- and postnatally diagnosed congenital heart disease (CHD) across 6 surgical centers.

STUDY DESIGN

A retrospective, multicenter case series from the Fetal Heart Society identified patients at 6 centers from 2012 through 2016 with prenatally (PrND) or postnatally (PoND) diagnosed hypoplastic left heart syndrome (HLHS) or d-transposition of the great arteries (TGA). Geospatial analysis for clustering was done by the average nearest neighbor (ANN) tool or optimized hot spot tool, depending on spatial unit and data type. Both point location and county case rate per 10 000 live births were assessed for geographic clustering or dispersion.

RESULTS

Of the 453 CHD cases, 26% were PoND (n = 117), and 74% were PrND (n = 336). PrND cases, in all but one center, displayed significant geographic clustering by the ANN. Conversely, PoND cases tended toward geographic dispersion. Dispersion of PoND HLHS occurred in 2 centers (ANN = 1.59, P < .001; and 1.47, P = .016), and PoND TGA occurred in 2 centers (ANN = 1.22, P < .05; and ANN = 1.73, P < .001). Hot spot analysis of all CHD cases (TGA and HLHS combined) revealed clustering near areas of high population density and the tertiary surgical center. Hot spot analysis of county-level case rate, accounting for population density, found variable clustering patterns.

CONCLUSION

Geographic dispersion among postnatally detected CHD highlights the need for a wider reach of prenatal cardiac diagnosis tailored to the specific needs of a community. Geospatial analysis can support centers in improving the equitable delivery of prenatal care.

Neighborhood location and nutritional resources as a risk factor for congenital heart disease in the fetus

BACKGROUND

Congenital heart disease (CHD) is the most common birth defect, influenced by maternal health, environmental conditions, and genetics. Maternal health and nutrition, particularly maternal diabetes, is a modifiable risk factor for development of CHD in the fetus. However, the importance of food access during pregnancy on the development of CHD remains unknown. The objective of this study was to investigate the association between maternal neighborhood characteristics, particularly food access, and occurrence of prenatally diagnosed CHD.

METHODS

A retrospective case series studied maternal-fetal dyads with prenatally diagnosed CHD between 2019 and 2021 in Washington, DC. Moran's I of maternal addresses evaluated geographic clustering of disease. Negative binomial regression assessed association between census tract demographics and population-adjusted CHD rate.

RESULTS

A total of 307 dyads were analyzed. Global Moran's I showed significant CHD clustering (p-value = .004). However, degree of clustering was not clinically meaningful. After adjusting for neighborhood socioeconomic status, residing in food deserts was not a predictor for CHD. However, neighborhoods with a higher percentage of households receiving Supplemental Nutrition Assistance Program (SNAP) benefits were associated with higher rates of conotruncal heart defects (Incident Rate Ratio [IRR] = 1.04, CI = 1.01-1.08) and aggregate CHD (IRR = 1.03, CI = 1.01-1.05).

CONCLUSIONS

Neighborhood location and food access were not associated with CHD. However, increased enrollment in SNAP was associated with higher rates of CHD. The association between CHD and SNAP benefits warrants further exploration. Understanding food access and maternal nutrition may illuminate disparities in the burden of CHD.

Geographic Distribution of Congenital Heart Disease: A Single Surgical Center Experience

OBJECTIVE

To determine presence of spatial clustering or dispersion of pre and postnatally detected hypoplastic left heart syndrome (HLHS) and d-transposition of the great arteries (TGA) cases.

STUDY DESIGN

This retrospective study examined all patients with a prenatal or postnatal diagnosis of HLHS or TGA who had an initial visit or hospitalization at our tertiary care center over a 5-year period from 2012 to 2016 (n = 105). Using geographic information systems software, the nearest neighbor ratio (NNR) tool was used to determine whether statistically significant clustering or dispersion occurred.

RESULTS

Geographic clustering was observed among prenatally diagnosed pooled cases of HLHS and TGA and all total cases (NNR = 0.73 and 0.66, respectively), but not postnatally detected cases (NNR = 1.08). Notably, there was significant dispersion of postnatally detected TGA cases (NNR = 1.22) There was no pattern for prenatally detected TGA or HLHS when analyzed individually.

CONCLUSIONS

The spatial distribution of HLHS and TGA is not random; these conditions occur in geographic clusters. Clustering of all patients in the study population and dispersion of postnatal diagnosis of TGA represent opportunities for improved delivery of fetal cardiac care.

Seasonality of Hypoplastic Left Heart Syndrome and Single Ventricle Heart in Poland in the Context of Air Pollution

Hypoplastic left heart syndrome (HLHS) and single ventricle (SV) remain a significant cause of cardiac deaths occurring in the first week of life. Their pathogenesis and seasonal frequency are still unknown. Therefore, we attempt to look at the genesis of the HLHS and SV in the context of territorial distribution as well as seasonality. A total of 193 fetuses diagnosed with HLHS and 92 with SV were selected. The frequency was analyzed depending on the year, calendar month, quarter and season (fall-winter vs. spring-summer). The spatial distribution of HLHS and SV in Poland was analyzed. We observed a statistically significant overrepresentation of HLHS formation frequency in March: 27 (14.00%) in comparison to a monthly median of 15 (IQR: 13.75-16.25; p = 0.039), as well as a significantly higher frequency of HLHS in 2007-2009: 65 cases (33.68%) in comparison to the annual mean of 13.79 ± 6.36 (p < 0.001). We noted a higher frequency of SV among parous with the last menstrual period reported in the fall/winter season of 58 vs. 34 in the spring/summer season (p = 0.014). The performed analysis also revealed significant SV overrepresentation in 2008: 11 cases (12.00%) in comparison to the annual mean of 6.57 ± 2.71 (p = 0.016). Every single case of HLHS was observed when the concentration of benzo(a)pyrene and/or PM10 exceeded the acceptable/target level. Our research indicates that both the season and the level of pollution are significant factors affecting the health of parous women and their offspring. The reason why HLHS and SV develop more frequently at certain times of the year remains unclear, therefore research on this topic should be continued, as well as on the effects of PM10 and benzo(a)pyrene exposure.

Distribution of congenital anomalies by race/ethnicity and geospatial location in Oklahoma, 1997-2009

INTRODUCTION

Congenital anomalies were the leading cause of infant mortality, responsible for 23 and 21% of deaths in Oklahoma and the USA, respectively, in 2016. We aimed to determine the prevalence by race/ethnicity and spatial distribution of congenital anomalies to identify geographic and racial/ethnic disparities, particularly among American Indian/Alaska Natives (AI/AN).

METHODS

We evaluated the prevalence of anomalies by type and race/ethnicity among 648,074 live births in Oklahoma from 1997 to 2009. Prevalence proportion ratios (PPRs) and 95% confidence intervals (CIs) were calculated using Poisson regression. We used Moran's I and Getis-Ord Gi* to evaluate spatial clustering for neural tube defects, critical congenital heart defects (CCHDs), and oral clefts among births whose residence geocoded to the ZIP code or finer level.

RESULTS

Overall prevalence of anomalies among live births was 3.9%. Non-Hispanic (NH) African American (PPR: 0.87, 95% CI: 0.83, 0.91), Asian/Pacific Islander (PPR: 0.70, 95% CI: 0.63, 0.78), and Hispanic (PPR: 0.87, 95% CI: 0.83, 0.91) children had a lower prevalence of anomalies compared to NH whites. The prevalence in NH AI/AN children was similar to NH whites (PPR: 1.01, 95% CI: 0.97, 1.05). However, differences in specific types of anomalies were observed by race/ethnicity. We observed no spatial autocorrelation for CCHD and oral clefts. Neural tube defects demonstrated spatial autocorrelation (p < .0001). Local hot spots varied by anomaly.

DISCUSSION

The prevalence of anomalies by race/ethnicity and geography differed by race/ethnicity and region, though this varied by anomaly. Additional research is needed to identify behavioral or environmental factors to target for prevention.

Spatial pattern and variations in the prevalence of congenital heart disease in children aged 4-18 years in the Qinghai-Tibetan Plateau

PURPOSE

This study aimed to investigate the spatial distribution pattern of the prevalence of congenital heart disease (CHD) in children in Qinghai-Tibetan Plateau (QTP), a high-altitude region in China.

METHODS

Epidemiological data from a survey on the prevalence of CHD in Qinghai Province including 288,066 children (4-18 years) were used in this study. The prevalence and distribution pattern of CHD was determined by sex, CHD subtype, and nationality and altitude. Spatial pattern analysis using Getis-Ord Gi^⁎ was used to identify the spatial distribution of CHD. Bayesian spatial binomial regression was performed to examine the relationship between the prevalence of CHD and environmental risk factors in the QTP.

RESULTS

The prevalence of CHD showed a significant spatial clustering pattern. The Tibetan autonomous prefecture of Yushu (average altitude > 4000 m) and the Mongolian autonomous county of Henan (average altitude > 3600 m) in Huangnan had the highest prevalence of CHD. Univariate analysis showed that with ascending altitude, the total prevalence of CHD, that in girls and boys with CHD, and that of the subtypes PDA and ASD increasing accordingly. Thus, environmental factors greatly contributed to the prevalence of CHD.

CONCLUSIONS

The prevalence of CHD shows significant spatial clustering pattern in the QTP. The CHD subtype prevalence clustering pattern has statistical regularity which would provide convenient clues of environmental risk factors. Our results may provide support to make strategies of CHD prevention, to reduce the incidence of CHD in high altitude regions of China.

Regional differences in right versus left congenital heart disease diagnoses in neonates in the United States

BACKGROUND

Differences in the prevalence of left and right congenital heart defects (CHD) across the United States are unclear. This study evaluated the overall prevalence and the distribution of right versus left CHD across US regions and divisions in neonates.

METHODS

Newborns born from 2000 to 2014 diagnosed with CHD were identified using the National Inpatient Sample. Heart defects were stratified into right, left, and "neither" subtypes. The risk of right and left heart diagnoses between US Census regions and divisions was compared using multivariable binomial regression, adjusting for infant, and hospital characteristics.

RESULTS

Two hundred forty thousand four hundred fifty-five newborns were included and 38,185 (15.9%) were classifiable as having either right or left subtypes. Between 2000 and 2014, the prevalence of right defects increased from 1.65 to 2.88 cases/1,000 live born infants (p < .0001), left defects increased from 0.47 to 0.75 cases/1,000 live born infants (p < .0001), and "neither" defects increased from 10.82 to 20.09 cases/1,000 live born infants (p < .0001). Newborns in the Northeast (RD_adj .03, 95% CI .02, .03), Midwest (RD_adj .02, 95% CI .02, .03), and South (RD_adj .02, 95% CI .02, .02) were significantly more likely to have a right heart defect diagnosis compared to the West. When stratified by division, New England states had a significantly higher prevalence of right defects compared to the Pacific (RD_adj .09, 95% CI .06, 0.11). No differences in the prevalence of left defects were seen.

CONCLUSIONS

The prevalence of CHD diagnoses at birth in the US has increased, and regional differences in the prevalence of right defects appear to exist.

Spatial patterns of the congenital heart disease prevalence among 0- to 14-year-old children in Sichuan Basin, P. R China, from 2004 to 2009

Background

Congenital heart disease (CHD) is the most common type of major birth defects in Sichuan, the most populous province in China. The detailed etiology of CHD is unknown but some environmental factors are suspected as the cause of this disease. However, the geographical variations in CHD prevalence would be highly valuable in providing a clue on the role of the environment in CHD etiology. Here, we investigate the spatial patterns and geographic differences in CHD prevalence among 0- to 14-year-old children, discuss the possible environmental risk factors that might be associated with CHD prevalence in Sichuan Basin from 2004 to 2009.

Methods

The hierarchical Bayesian model was used to estimate CHD prevalence at the township level. Spatial autocorrelation statistics were performed, and a hot-spot analysis with different distance thresholds was used to identify the spatial pattern of CHD prevalence. Distribution and clustering maps were drawn using geographic information system tools.

Results

CHD prevalence was significantly clustered in Sichuan Basin in different spatial scale. Typical hot/cold clusters were identified, and possible CHD causes were discussed. The association between selected hypothetical environmental factors of maternal exposure and CHD prevalence was evaluated.

Conclusions

The largest hot-spot clustering phenomena and the CHD prevalence clustering trend among 0- to 14-year-old children in the study area showed a plausibly close similarity with those observed in the Tuojiang River Basin. The high ecological risk of heavy metal(Cd, As, and Pb)sediments in the middle and lower streams of the Tuojiang River watershed and ammonia–nitrogen pollution may have contribution to the high prevalence of CHD in this area.

Human gene copy number spectra analysis in congenital heart malformations

The clinical significance of copy number variants (CNVs) in congenital heart disease (CHD) continues to be a challenge. Although CNVs including genes can confer disease risk, relationships between gene dosage and phenotype are still being defined. Our goal was to perform a quantitative analysis of CNVs involving 100 well-defined CHD risk genes identified through previously published human association studies in subjects with anatomically defined cardiac malformations. A novel analytical approach permitting CNV gene frequency "spectra" to be computed over prespecified regions to determine phenotype-gene dosage relationships was employed. CNVs in subjects with CHD (n = 945), subphenotyped into 40 groups and verified in accordance with the European Paediatric Cardiac Code, were compared with two control groups, a disease-free cohort (n = 2,026) and a population with coronary artery disease (n = 880). Gains (≥200 kb) and losses (≥100 kb) were determined over 100 CHD risk genes and compared using a Barnard exact test. Six subphenotypes showed significant enrichment (P ≤ 0.05), including aortic stenosis (valvar), atrioventricular canal (partial), atrioventricular septal defect with tetralogy of Fallot, subaortic stenosis, tetralogy of Fallot, and truncus arteriosus. Furthermore, CNV gene frequency spectra were enriched (P ≤ 0.05) for losses at: FKBP6, ELN, GTF2IRD1, GATA4, CRKL, TBX1, ATRX, GPC3, BCOR, ZIC3, FLNA and MID1; and gains at: PRKAB2, FMO5, CHD1L, BCL9, ACP6, GJA5, HRAS, GATA6 and RUNX1. Of CHD subjects, 14% had causal chromosomal abnormalities, and 4.3% had likely causal (significantly enriched), large, rare CNVs. CNV frequency spectra combined with precision phenotyping may lead to increased molecular understanding of etiologic pathways.