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| Analysis on the pregnancy age trend of primiparas with planning pregnancy in rural areas in Minle county of Gansu province from 2013 to 2019 |
| 1. Family Planning Service Centre of Minle County，Gansu Province, 734500；2. School of Public Health, Lanzhou University；3. National Research Institute for Family Planning |
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Abstract To analyze the pregnancy age trend of primiparas with planning pregnancy in rural areas, and to provide data support for reducing the risk of adverse pregnancy outcomes and for improving reproductive quality. Methods: 2606 rural Han Chinese women who participated in the National Free Pre-pregnancy Health Examination in Minle County of Gansu Province and got pregnant in 2013-2019 were included in this study. The distribution of pregnancy age in different years was described, and the simple linear regression and generalized regression models were used to test the annual change of pregnant age. The marginal effects model was used to analyze the pregnant age difference of primiparas between 2013-2015 or 2017-2019 and 2016, and the simple linear regression model was used to test annual change of pregnant age. Results: The pregnant age of participants has increased from 23.33 (95% CI: 23.14-23.52) years old in 2013 to 26.05 (95% CI: 25.68-26.42) years old in 2019, P trend <0.001. And the average pregnant age had increase 2.72 (95% CI: 2.30-3.14) years old in these 7 years, with an annual increasing of 0.26 (95% CI: 0.21-0.32) years old. The marginal effects also showed that comparing that in 2016, the difference of pregnant age had increased from-0.78 (95% CI: -1.17-0.39) years old in 2013 to 0.87 (95% CI: 0.43-1.32) years old in 2019, P trend <0.001. The absolute difference of average pregnant age was 1.65 years old, with an annual increasing of 0.26 (95% CI: 0.21-0.31) years old. Conclusion: The pregnant age of rural primipara in Minle county is increasing year by year, it is suggests that the pregnancy of advanced age women should be strengthened by maternal and child health workers for reducing the rate of adverse pregnancy events.
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