Jian Zhao1, Yun Zhao2, Mengran Du3, Colin W Binns1, Andy H Lee1. 1. School of Public Health, Curtin University, Perth, Australia. 2. School of Public Health, Curtin University, Perth, Australia. Electronic address: y.zhao@curtin.edu.au. 3. West China School of Public Health, Sichuan University, Chengdu, China.
Abstract
OBJECTIVE: to examine the association between maternal education and breastfeeding prevalence in China. METHODS: a systematic review and meta-analysis was conducted based on the literature of observational studies retrieved from electronic databases of CNKI, Medline, Embase, CINHAL, ProQuest and Science Direct. Maternal education was recoded into two binary categorical variables using different cut-off points. Both fixed and random effect models were used to estimate the pooled association between maternal education and breastfeeding prevalence in China. Visual inspection of Galbraith plot for heterogeneity detection, sensitivity analysis and publication bias test were performed. FINDINGS: a total of 31 studies were included in the systematic review, and 15 and 26 studies were suitable for meta-analysis in terms of two different cutoff points of maternal education respectively. In the group using 6-year education cut-off (Group 1), the odds of breastfeeding was 10% (pooled OR=0.90, 95% CI: 0.83, 0.97) lower in mothers who had been educated for 'more than 6 years' compared to mothers with '6 years or less' education. In the group using 12-year education cut-off (Group 2), the odds of breastfeeding was 9% (pooled OR=0.91, 95% CI: 0.86, 0.96) lower in mothers who had 'more than 12 years' education compared to mothers who attained '12 years or less' education. There was substantial heterogeneity across the studies in both groups. Through meta-regression analysis, sample size of studies was detected contributing to the heterogeneity in Group 1; however none of study level factors were found to be a source of heterogeneity in Group 2. CONCLUSION: in the Chinese culture and employment environment, mothers who have attained a higher level of education are less likely to breastfeed their babies compared to mothers with lower education levels.
OBJECTIVE: to examine the association between maternal education and breastfeeding prevalence in China. METHODS: a systematic review and meta-analysis was conducted based on the literature of observational studies retrieved from electronic databases of CNKI, Medline, Embase, CINHAL, ProQuest and Science Direct. Maternal education was recoded into two binary categorical variables using different cut-off points. Both fixed and random effect models were used to estimate the pooled association between maternal education and breastfeeding prevalence in China. Visual inspection of Galbraith plot for heterogeneity detection, sensitivity analysis and publication bias test were performed. FINDINGS: a total of 31 studies were included in the systematic review, and 15 and 26 studies were suitable for meta-analysis in terms of two different cutoff points of maternal education respectively. In the group using 6-year education cut-off (Group 1), the odds of breastfeeding was 10% (pooled OR=0.90, 95% CI: 0.83, 0.97) lower in mothers who had been educated for 'more than 6 years' compared to mothers with '6 years or less' education. In the group using 12-year education cut-off (Group 2), the odds of breastfeeding was 9% (pooled OR=0.91, 95% CI: 0.86, 0.96) lower in mothers who had 'more than 12 years' education compared to mothers who attained '12 years or less' education. There was substantial heterogeneity across the studies in both groups. Through meta-regression analysis, sample size of studies was detected contributing to the heterogeneity in Group 1; however none of study level factors were found to be a source of heterogeneity in Group 2. CONCLUSION: in the Chinese culture and employment environment, mothers who have attained a higher level of education are less likely to breastfeed their babies compared to mothers with lower education levels.
Authors: Xialing Wu; Xiao Gao; Tingting Sha; Guangyu Zeng; Shiping Liu; Ling Li; Cheng Chen; Yan Yan Journal: Int J Environ Res Public Health Date: 2019-03-06 Impact factor: 3.390
Authors: Juana María Aguilar-Ortega; Juan Luis González-Pascual; César Cardenete-Reyes; Carmen Pérez-de-Algaba-Cuenca; Santiago Pérez-García; Laura Esteban-Gonzalo Journal: BMC Pregnancy Childbirth Date: 2019-01-28 Impact factor: 3.007