Spatial Point Pattern Analysis of Congenital Heart Defects in Lanzhou, China

Abstract

Background/Aim: Analysis of spatial point processes has been used to investigate spatial variation of disease risks, and their relationships with environmental factors; however, few studies have been conducted in China, where emissions from industries and heavy traffic pose serious public health concerns. The objective of this work is to investigate the impacts of major point sources and road networks on congenital heart defects (CHD) risks in Lanzhou, China, where maternal exposure to ambient air pollution was linked to increased risks of CHD. Methods: From a Lanzhou birth cohort during 2010-2012, 8,227 singleton live births with home addresses in the city urban area were included in this study. K, L, and Kcross functions were used to detect clustering tendency of the CHD (n=65) and healthy infants (n=8162). Kernel density ratio was used to identify potential clusters of CHD cases adjusting for the distribution of healthy infants. Poisson point process model was used to model intensity of CHD cases as a function of emission-weighted distance to major point sources (power plants and cement factories), road length density within 100m buffers, intensity of healthy infants, maternal income and education. Results: Similar significant clustering patterns were identified for CHD cases and healthy infants. Adjusting for the distribution of healthy infants, maternal income and education, CHD risks were significantly associated with increased road length density within 100 m buffer (RR: 1.07) and decreased emission-weighted distance from major point sources (RR: 0.07). Chi-square test with quadrat counts and Kolmogorov-Smirnov test validated the model and showed no spatial clustering in residuals. Conclusions: Results indicate proximity to major point sources and road network have adverse impacts on newborn’s health in Lanzhou, China. The identified clusters of CHD cases might allow policy makers or future mothers to make informed decisions regarding exposure control and risk management.