title: Predictors for neonatal death in the rural areas of Shaanxi Province of Northwestern China: a cross-sectional study.
abstract: BACKGROUND
  Almost all (99%) neonatal deaths arise in low-income and middle-income countries. Approximately 450 new-born children die every hour, which is mainly from preventable causes. There has been increased recognition of the need for these countries to implement public health interventions that specifically target neonatal deaths. The purpose of this paper is to identify the predictors of neonatal death in Type 4 rural (poorest) counties in Shaanxi Province of northwestern China.
  
  
  METHODS
  A cross-sectional study was conducted in Shaanxi Province, China. A single-stage survey design was identified to estimate standard errors. Because of concern about the complex sample design, the data were analysed using multivariate logistic regression analysis. Socioeconomic and maternal health service utilization factors were added into the model.
  
  
  RESULTS
  During the study period, a total of 4750 women who delivered in the past three years were randomly selected for interview in the five counties. There were 4880 live births and 54 neonatal deaths identified. In the multiple logistic regression, the odds of neonatal death was significantly higher for multiparous women (OR = 2.77; 95% CI: 1.34, 5.70) and women who did not receive antennal health care in the first trimester of pregnancy (OR = 2.49; 95% CI: 1.41, 4.40). Women who gave birth in a county-level hospital (OR = 0.18; 95% CI: 0.04, 0.86) and had junior high school or higher education level (OR = 0.20; 95% CI: 0.05, 0.84) were significantly protected from neonatal death.
  
  
  CONCLUSIONS
  Public health interventions directed at reducing neonatal death should address the socioeconomic factors and maternal health service utilization, which significantly influence neonatal mortality in rural China. Multipara, low educational level of the women, availability of prenatal visits in the first trimester of pregnancy and hospital delivery should be considered when planning the interventions to reduce the neonatal mortality in rural areas.
authors.affiliation: Department of Epidemiology and Health Statistics, Xi'an Jiaotong University Health Science Center, Xi'an, PR China. lichao.xjtu1985@stu.xjtu.edu.cn.
authors.forename: Chao
authors.initials: C
authors.lastname: Li
authors.affiliation: Department of Epidemiology and Health Statistics, Xi'an Jiaotong University Health Science Center, Xi'an, PR China. xjtu_yh.paper@aliyun.com.
authors.forename: Hong
authors.initials: H
authors.lastname: Yan
authors.affiliation: Department of Epidemiology and Health Statistics, Xi'an Jiaotong University Health Science Center, Xi'an, PR China. tjzlx@mail.xjtu.edu.cn.
authors.forename: Lingxia
authors.initials: L
authors.lastname: Zeng
authors.affiliation: School of Public Health, University of Sydney, Room 307A, Edward Ford Building (A27), University of Sydney, Sydney, NSW, 2006, Australia. michael.dibley@sydney.edu.au.
authors.forename: Michael J
authors.initials: MJ
authors.lastname: Dibley
authors.affiliation: Department of Clinical Sciences, Liverpool School of Tropical Medicine, Pembroke Place, Liverpool, L3 5QA, UK. duolao.wang@lshtm.ac.uk.
authors.forename: Duolao
authors.initials: D
authors.lastname: Wang
mesh_terms: D000328:Adult; D002681:China / Q000453:epidemiology; D003430:Cross-Sectional Studies; D005260:Female; D006801:Humans; D007223:Infant; D007226:Infant Mortality / Q000639:trends*; D007231:Infant, Newborn; D007407:Interviews as Topic; D016015:Logistic Models; D008427:Maternal Health Services / Q000706:statistics & numerical data; D010298:Parity; D066087:Perinatal Death / Q000209:etiology*; D011204:Poverty Areas; D011247:Pregnancy; D011295:Prenatal Care; D012424:Rural Population / Q000706:statistics & numerical data; D055815:Young Adult