This article has Open Peer Review reports available.
Exploratory spatial data analysis for the identification of risk factors to birth defects
© Wu et al; licensee BioMed Central Ltd. 2004
Received: 09 October 2003
Accepted: 18 June 2004
Published: 18 June 2004
Birth defects, which are the major cause of infant mortality and a leading cause of disability, refer to "Any anomaly, functional or structural, that presents in infancy or later in life and is caused by events preceding birth, whether inherited, or acquired (ICBDMS)". However, the risk factors associated with heredity and/or environment are very difficult to filter out accurately. This study selected an area with the highest ratio of neural-tube birth defect (NTBD) occurrences worldwide to identify the scale of environmental risk factors for birth defects using exploratory spatial data analysis methods.
The fact that there were two typical hotspot clustering phenomena provides evidence that the risk for neural-tube birth defect exists on two different scales (a socioeconomic scale at 6.84 km and a soil type scale at 22.8 km) for the area studied. Although our study has limited spatial exploratory data for the analysis of the neural-tube birth defect occurrence ratio and for finding clues to risk factors, this result provides effective clues for further physical, chemical and even more molecular laboratory testing according to these two spatial scales.
Birth defects, formally defined by the March of Dimes Birth Defects Foundation, refer to "any anomaly, functional or structural, that presents in infancy or later in life and is caused by events preceding birth, whether inherited, or acquired". Varying from minor cosmetic irregularities to life threatening disorders, birth defects are the major cause of infant mortality and a leading cause of disability. However, they can be prevented and early intervention is important to ameliorate their consequences . But this requires an accurate understanding of the causes and risk factors in advance.
According to results of birth defects research, the probability of birth defects caused by genetic factors may be similar in various regions. However, environmental risk factors, such as chemicals, toxins, and environmental pollution account for different ratios of birth defect occurrences in different regions. Those environmental risk factors, including socioeconomic status and geographical elements, often have spatial associations as well as various patterns.
As long as diseases have been recognized, it has been apparent that many of them are manifested in clusters. Interest in those clusters resides not so much in the mere aggregation of cases but rather in populations that have a high rate of disease. Experience in epidemiology should remind us that clustering can also be observed for variables that are not causes but serve as markers for the causes. The scientific reason to study disease clusters is to learn about clustering of the causes  (Rothman, 1990). Exploratory spatial data analysis methods, which aim at testing hypotheses of spatially distributed object analysis, can serve as a tool in identifying risk factors for birth defects.
Spatial position and expression
Bayesian modeling of neural-tube birth defects data
As one of the areas with the highest ratio of neural-tube birth defects, inspection branches were well organized in this county. Records of birth defect cases for four years (1998~2001) were acquired based on hospital registers and investigation in villages. These cases were divided into neural-tube birth defects and other birth defects by organ system. Neural-tube birth defects include anencephaly, spina bifida, encephalocele, holoprosencephaly and hydrecephalus, among others. Different birth defects may be caused by different risk factors, and we limited our research to neural-tube birth defects.
However, there are seldom full records for normal births. For the total number of birth records, we used the number of births planned every year for each village. As the family planning policy has been strictly carried out, this number reflects the real births in maximum. Furthermore, because birth defects are low probability events, four years' neural-tube birth defects cases were added together and considered as one year's cases for the calculation of the occurrence ratio.
When the occurrence ratio was calculated, the number of births in each village was different because of population differences, which would cause a bias in the ratio acquired by simply dividing the number of birth defects by the number of all births. Generally, villages with smaller populations, which correspondingly have fewer births, will have larger variances for calculating the ratio of birth defects occurrence. Simply dividing the number of birth defects by the number of all births may cause an error in our spatial analysis. 
In order to remove the dependence of the sampling variance on population size and calculate the neural-tube birth defects ratio, Bayesian modeling methods were used through WinBUGS software. The observed number of cases in each village was treated as a binomial random variable with parameter P i in our analysis. P i is the probability of a live birth in village i having a birth defect. The standard rate (observed birth defects cases divided by all births) is the maximum likelihood estimate of P i . As the environmental and socioeconomic status are similar, the P i is assumed to be constant within the same village. And the parameter P i is modeled through a logit transformation log it(P i ), expressed as:
log it(P i ) = log[P i /(1.0 - P i )] = μ + ν i + ε i
Spatial statistics methods
Here, S is the standard variance of the birth defects occurrence ratio, When the distance from village j to i is within distance d, then w ij (d) = 1; otherwise w ij (d) = 0, and , . The higher the value of is, the greater the influence of village i is at a given distance d, indicating that village i is a hotspot of the region.
Typical distance scales and their meanings
Nearest distance among remote villages
6.2 – 9.3 km
Socio-economic activities scopes
Differentiated distance of soil types
19.5 – 30 km
Geological variance distance
Birth defects are becoming a major cause of rising infant mortality. It has been found that birth defects account for a gradual increase in infant mortality from one fourth to one third of all births in the 1990's. In order to prevent birth defects or enable early intervention, risk factors have been assessed in laboratories using many analytical methods . However, as people live in different kinds of environments and have different socioeconomic statuses, no laboratory environment can fully simulate the conditions associated with risk factors. So the analytical results determined in laboratories can only explain a small fraction of the risk factors for birth defects.
Socioeconomic status is the most obvious potential obstacle in any spatial analysis of health outcomes. There has been little research on the strength of the relation between socioeconomic status and the risk of congenital anomaly (birth defects) (H. Dolk, 1998) . Our work suggests that there is a typical grouped distribution of hotspots when distance scopes based on residents' common socio-economic activities are taken as a critical distance value. We therefore think that socioeconomic status may affect the scope of risk factors. For example, the scope of intermarriage usually falls within the definition of social activities distance, and the male and female usually have similar socioeconomic status when they get married. This may indicate that they have been exposed to some common risk factors, which would accelerate the occurrence of birth defects.
Difference in chemical element contents of three main soil types in Heshun
leached cinnamon soil
Co Pb Cu Ni Cr Zn Mn
As F Hg
Pb Ni Cr Zn Mn Hg Cd
As Co F Cu
As F Hg Cd
Co Pb Ni Cr Zn Mn
Nutrient of the three soil types
leached cinnamon soil
For the data used in this study, birth defects may not have been fully reported in this area as some pregnant women chose home births rather than hospital births. So we used data from hospital records and investigations in villages. Some women may have relocated their place of residence during their pregnancy, so there could be a migration bias in risk factor identification. However, as chemicals accumulate in the body over time and there have been no large scale movements of people in this region, we think there is little migration bias for the selected study area.  As birth defects are low-probability events and the family planning policy was carried out strictly, we added four years of birth defects cases together to calculate the occurrence ratio. Though this may magnify the occurrence ratio, little bias would be introduced for long-existing environmental risk factors for birth defects in the spatial dimension.
This study was supported by grants 2001CB5103 from the National "973" Program, 30025042, JJ03000101 and 49871064 from the National Nature Science Foundation of China, 2002AA135230 from the National High Technology Research and Development Program and the Science Innovation Project of the Chinese Academy of Sciences and the "211" program of Peking University.
- International Birth Defects Information Systems: [http://ibis-birthdefects.org/]
- Rothman KJ: A sobering start for the cluster busters' conference. Am J Epidemiol. 1990, 132: S6-S13.PubMedGoogle Scholar
- MMWR of CDC, 1990/39(RR-11). 1-16. [http://www.cdc.gov/mmwr/preview/mmwrhtml/00001797.htm]
- Cressie N, Read TRC: Spatial Data Analysis of Regional Counts. Biom J. 1989, 31 (6): 699-719.View ArticleGoogle Scholar
- Haining R: Spatial Data Analysis, theory and practice. 2003, Cambridge University PressView ArticleGoogle Scholar
- Getis A, Ord JK: The Analysis of Spatial Association by Use of Distance Statistics. Geographical Analysis. 1992, 24: 189-206.View ArticleGoogle Scholar
- Aldstadt J, Getis A: Point Pattern Analysis in an ArcGIS Environment. [http://www.dpi.inpe.br/gilberto/csiss/papers/aldstadt.pdf]
- An XL, Fu SHL: Environmental Eugenics. 1995, Beijing Medical University and Chinese Union Medical University Union PressGoogle Scholar
- Dolk H, Vrijheid M, Armstrong B, Abramsky L, Bianchi F, Garne E, Nelen V, Robert E, Scott JES, Stone D, Tenconi R: Risk of congenital anomalies near hazardous-waste landfill sites in Europe: the EUROHAZCON study. Lancet. 1998, 352: 423-427. 10.1016/S0140-6736(98)01352-X.View ArticlePubMedGoogle Scholar
- Institute of Soil Research, CAS: Soil types distribution of China. 1978, Chinese Map PressGoogle Scholar
- Sh C, Zhao L, Guo X, Gao S, Yang J, Li J: The distribution of chemical elements base values and influenced factors in Shanxi province of China. Agro-Environmental Protection. 1996, 15 (1): 24-28.Google Scholar
- Meng L: To the comparisons of the loss for natural soil's nitrogen and phosphorus. Geography and Territorial Research. 2002, 18 (4): 98-103.Google Scholar
- Armstrong B: Study design for exposure assessment in epidemiological studies. the science of the total Environmental. 1995, 168: 187-194. 10.1016/0048-9697(95)98172-F.View ArticleGoogle Scholar
- The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2458/4/23/prepub
This article is published under license to BioMed Central Ltd. This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose, provided this notice is preserved along with the article's original URL.