A multi-level analysis of risk factors for Schistosoma japonicum infection in China

Abstract

The aim of this study was to explore the risk factors of schistosomiasis japonica in China, using a hierarchical multi-level model with individuals nested within villages. Methods: A cross-sectional survey of schistosomiasis japonica was conducted in 16 villages in the Chinese province of Hunan. A multi-level modeling technique (HLM version 6.04) was used to assess risk factors of schistosomiasis. The results from this multi-level model were compared with those from a conventional single-level logistic regression model. Results: A total of 10 245 individuals were enrolled in this study, of whom about 4.1% were infected with Schistosoma japonicum. In the multi-level model analysis, individual level variables such as gender, age, and occupation, and village level variables such as type of S. japonicum endemic area, drinking water source, sewage treatment, June temperature, and April rainfall were associated with schistosomiasis japonica infection. Conventional single-level logistic regression analysis selected more independent variables, and had narrower confidence intervals around the corresponding regression coefficients. In particular, per capita income, precipitation in October, and density of infected snails were statistically significant in the conventional singlelevel logistic regression analysis but not in the multi-level model.

Correlation between clonorchiasis incidences and climatic factors in Guangzhou, China

“…This is consistent with the findings from Sichuan province of China, which suggested that mean rainfall should be considered as the critical natural predictor for the prevalence of clonorchiasis [13]. Similarly, some published literature also indicated that rainfall were associated with schistosomiasis japonica infection in China [20,21], of which Xu XJ and his research team [22] proved that prevalence of schistosomiasis showed a significant linear regression relationship with annual rainfall. In Guangzhou, it is very common for rural households having a pond where fish are bred as a source of food.…”

Analysis of Complex Patterns of Human Exposure and Immunity to Schistosomiasis mansoni: The Influence of Age, Sex, Ethnicity and IgE

“…Small-scale, micro-epidemiological studies investigating risk factors for Schistosoma infection are often limited by their lack of data on individual-level cercarial exposure (for example, [51]). Although some studies have attempted to overcome this limitation by using proxy markers for exposure such as distance to an infective water body [52], [53], care should be taken because exposure to S. mansoni infection is a highly complex, multi-factorial process [54] and unreliable exposure estimates may bias results [45].…”

Schistosomiasis in the People's Republic of China: the Era of the Three Gorges Dam

“…Although the risk factors (61,119,166,223) and means of becoming infected (i.e., occupation [fishing and farming], domestic duties [washing], and social activities [swimming]) are likely similar in the areas of endemicity around both Poyang and Dongting Lakes, there are subtle differences in the patterns of transmission. The areas of endemicity in the Poyang Lake region have two distinct transmission seasons.…”