Chlamydia trachomatis infection among patients attending sexual and reproductive health clinics: A cross-sectional study in Bao'an District, Shenzhen, China.

This study aimed to estimate the prevalence of chlamydial trachomatis (CT) infection and explore its risk factors among patients attending sexual and reproductive health clinics in Shenzhen, China. We collected demographic and clinical information from attendees (aged 18-49). CT and Neisseria gonorrhoeae (NG) infection was determined by nucleic acid amplification test (NAAT) on self-collected urine specimens. Of 1,938 participants recruited, 10.3% (95% confidence interval [CI]: 9.6%-11.0%) tested positive for CT. Prevalence was similar between men (10.6% [85/804]; 95% CI, 9.5%-11.7%) and women (10.1% [115/1134]; 95% CI: 9.2%-11.0%). Being 18-25 years old (adjusted odds ratio [aOR] = 2.52; 95%CI:1.35-4.71), never tested for CT before (aOR = 2.42; 95%CI: 1.05-5.61) and infected with NG(aOR = 3.87; 95%CI: 2.10-7.10) were independently associated with CT infection. We found that CT infection is prevalent among patients attending sexual and reproductive health clinics in Shenzhen, China. A comprehensive program including CT screening, surveillance and treatment is urgently needed.

Chi-squared Automatic Interaction Detection Decision Tree Analysis of Risk Factors for Infant Anemia in Beijing, China.

BACKGROUND: In the past decades, studies on infant anemia have mainly focused on rural areas of China. With the increasing heterogeneity of population in recent years, available information on infant anemia is inconclusive in large cities of China, especially with comparison between native residents and floating population. This population-based cross-sectional study was implemented to determine the anemic status of infants as well as the risk factors in a representative downtown area of Beijing. METHODS: As useful methods to build a predictive model, Chi-squared automatic interaction detection (CHAID) decision tree analysis and logistic regression analysis were introduced to explore risk factors of infant anemia. A total of 1091 infants aged 6-12 months together with their parents/caregivers living at Heping Avenue Subdistrict of Beijing were surveyed from January 1, 2013 to December 31, 2014. RESULTS: The prevalence of anemia was 12.60% with a range of 3.47%-40.00% in different subgroup characteristics. The CHAID decision tree model has demonstrated multilevel interaction among risk factors through stepwise pathways to detect anemia. Besides the three predictors identified by logistic regression model including maternal anemia during pregnancy, exclusive breastfeeding in the first 6 months, and floating population, CHAID decision tree analysis also identified the fourth risk factor, the maternal educational level, with higher overall classification accuracy and larger area below the receiver operating characteristic curve. CONCLUSIONS: The infant anemic status in metropolis is complex and should be carefully considered by the basic health care practitioners. CHAID decision tree analysis has demonstrated a better performance in hierarchical analysis of population with great heterogeneity. Risk factors identified by this study might be meaningful in the early detection and prompt treatment of infant anemia in large cities.