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Fertility intention and its affecting factors in China: A national cross-sectional survey
INTRODUCTION: Low fertility rate has become an inevitable problem globally. Although current policies have a certain effect on promoting fertility and raising the birth rate, the overall effect is not obvious to meet the need. Therefore, the exploration of fertility intention and its affecting facto...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9939585/ https://www.ncbi.nlm.nih.gov/pubmed/36814608 http://dx.doi.org/10.1016/j.heliyon.2023.e13445 |
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author | Xiang, Ze Zhang, Xinyue Li, Yiqi Li, Jiarui Wang, Yinlin Wang, Yujia Ming, Wai-Kit Sun, Xinying Jiang, Bin Zhai, Guanghua Wu, Yibo Wu, Jian |
author_facet | Xiang, Ze Zhang, Xinyue Li, Yiqi Li, Jiarui Wang, Yinlin Wang, Yujia Ming, Wai-Kit Sun, Xinying Jiang, Bin Zhai, Guanghua Wu, Yibo Wu, Jian |
author_sort | Xiang, Ze |
collection | PubMed |
description | INTRODUCTION: Low fertility rate has become an inevitable problem globally. Although current policies have a certain effect on promoting fertility and raising the birth rate, the overall effect is not obvious to meet the need. Therefore, the exploration of fertility intention and its affecting factors is extremely significant. METHODS: This study collected demographic data and the intention of respondents to have a second children, which focused on the factors that could affect fertility issues. 11,031 respondents were divided into non-fertile group (n = 5062) and fertile group (n = 5969) according to whether they had children or not, and the fertility group (n = 5969) were divided into group with 1–2 children (n = 5293) and group with ≥3 children (n = 676) according to the number of children. Non-fertility respondents aged 26–40 (n = 1369) were divided to explore the factors affecting the second-children intention. Binary logistic regression analysis was used to determine the affecting factors. RESULTS: It was revealed that gender [Male: OR: 0.60, 95% CI: 0.54–0.68], age [26–40: OR: 16.0, 95% CI: 13.4–19.1; 41–60: OR: 233.8, 95% CI: 186.7–292.6; >60: OR: 105.6, 95% CI: 77.1–144.6], political status [Partisans: OR: 0.48, 95% CI: 0.42–0.54], highest educational level [Middle school: OR: 0.21, 95% CI: 0.17–0.26; College degree or above: OR: 0.09, 95% CI: 0.08–0.11], whether having chronic disease [Yes: OR: 1.95, 95% CI: 1.60–2.38] and depression [Mild depression: OR: 0.63, 95% CI: 0.56–0.72; Moderate depression: OR: 0.43, 95% CI: 0.36–0.53; Moderate to severe depression: OR: 0.45, 95% CI: 0.35–0.57; Severe depression: OR: 0.50, 95% CI: 0.33–0.74] were important factors affecting fertility intention. We found that age [26–40: OR: 0.11, 95% CI: 0.08–0.15; 41–60: OR: 0.15, 95% CI: 0.12–0.18; >60: 0.81, 95% CI: 0.66–0.99], region [Central China: OR: 1.49, 95% CI: 1.20–1.86; Western China: OR: 1.75, 95% CI: 1.41–2.18], resident place [Urban: OR: 0.59, 95% CI: 0.49–0.72], per capita monthly household income [6001–12000: OR: 0.63, 95% CI:0.46–0.83; ≥12,000: OR: 1.83, 95% CI: 1.20–2.80], political status [Non-partisans: OR: 0.24, 95% CI: 0.09–0.69], highest educational level [Middle school: OR: 0.36, 95%CI: 0.27–0.46; College degree or above: OR: 0.22, 95% CI: 0.17–0.30] and anxiety [Moderate anxiety: OR: 1.39, 95% CI: 1.04–1.88; Severe anxiety: OR: 2.19, 95% CI: 1.26–3.80] were the main affecting factors for choosing the number of children. Furthermore, the second-children intention investigation in respondents aged 26–40 showed that gender [Male: OR: 2.06, 95% CI: 1.67–2.53], resident place [Urban: OR: 0.59, 95% CI: 0.49–0.72], per capita monthly household income [≥12,000: OR: 1.86, 95% CI: 1.23–2.82] and pressure [Severe pressure: OR: 0.54, 95% CI: 0.34–0.85] were the important factors. CONCLUSION: Region, educational level, psychological factors, income, political status and medical insurance were the important factors affecting the intention of fertility and the number of children. The government should take these factors into account when optimizing the existing policy. |
format | Online Article Text |
id | pubmed-9939585 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-99395852023-02-21 Fertility intention and its affecting factors in China: A national cross-sectional survey Xiang, Ze Zhang, Xinyue Li, Yiqi Li, Jiarui Wang, Yinlin Wang, Yujia Ming, Wai-Kit Sun, Xinying Jiang, Bin Zhai, Guanghua Wu, Yibo Wu, Jian Heliyon Research Article INTRODUCTION: Low fertility rate has become an inevitable problem globally. Although current policies have a certain effect on promoting fertility and raising the birth rate, the overall effect is not obvious to meet the need. Therefore, the exploration of fertility intention and its affecting factors is extremely significant. METHODS: This study collected demographic data and the intention of respondents to have a second children, which focused on the factors that could affect fertility issues. 11,031 respondents were divided into non-fertile group (n = 5062) and fertile group (n = 5969) according to whether they had children or not, and the fertility group (n = 5969) were divided into group with 1–2 children (n = 5293) and group with ≥3 children (n = 676) according to the number of children. Non-fertility respondents aged 26–40 (n = 1369) were divided to explore the factors affecting the second-children intention. Binary logistic regression analysis was used to determine the affecting factors. RESULTS: It was revealed that gender [Male: OR: 0.60, 95% CI: 0.54–0.68], age [26–40: OR: 16.0, 95% CI: 13.4–19.1; 41–60: OR: 233.8, 95% CI: 186.7–292.6; >60: OR: 105.6, 95% CI: 77.1–144.6], political status [Partisans: OR: 0.48, 95% CI: 0.42–0.54], highest educational level [Middle school: OR: 0.21, 95% CI: 0.17–0.26; College degree or above: OR: 0.09, 95% CI: 0.08–0.11], whether having chronic disease [Yes: OR: 1.95, 95% CI: 1.60–2.38] and depression [Mild depression: OR: 0.63, 95% CI: 0.56–0.72; Moderate depression: OR: 0.43, 95% CI: 0.36–0.53; Moderate to severe depression: OR: 0.45, 95% CI: 0.35–0.57; Severe depression: OR: 0.50, 95% CI: 0.33–0.74] were important factors affecting fertility intention. We found that age [26–40: OR: 0.11, 95% CI: 0.08–0.15; 41–60: OR: 0.15, 95% CI: 0.12–0.18; >60: 0.81, 95% CI: 0.66–0.99], region [Central China: OR: 1.49, 95% CI: 1.20–1.86; Western China: OR: 1.75, 95% CI: 1.41–2.18], resident place [Urban: OR: 0.59, 95% CI: 0.49–0.72], per capita monthly household income [6001–12000: OR: 0.63, 95% CI:0.46–0.83; ≥12,000: OR: 1.83, 95% CI: 1.20–2.80], political status [Non-partisans: OR: 0.24, 95% CI: 0.09–0.69], highest educational level [Middle school: OR: 0.36, 95%CI: 0.27–0.46; College degree or above: OR: 0.22, 95% CI: 0.17–0.30] and anxiety [Moderate anxiety: OR: 1.39, 95% CI: 1.04–1.88; Severe anxiety: OR: 2.19, 95% CI: 1.26–3.80] were the main affecting factors for choosing the number of children. Furthermore, the second-children intention investigation in respondents aged 26–40 showed that gender [Male: OR: 2.06, 95% CI: 1.67–2.53], resident place [Urban: OR: 0.59, 95% CI: 0.49–0.72], per capita monthly household income [≥12,000: OR: 1.86, 95% CI: 1.23–2.82] and pressure [Severe pressure: OR: 0.54, 95% CI: 0.34–0.85] were the important factors. CONCLUSION: Region, educational level, psychological factors, income, political status and medical insurance were the important factors affecting the intention of fertility and the number of children. The government should take these factors into account when optimizing the existing policy. Elsevier 2023-02-03 /pmc/articles/PMC9939585/ /pubmed/36814608 http://dx.doi.org/10.1016/j.heliyon.2023.e13445 Text en © 2023 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Research Article Xiang, Ze Zhang, Xinyue Li, Yiqi Li, Jiarui Wang, Yinlin Wang, Yujia Ming, Wai-Kit Sun, Xinying Jiang, Bin Zhai, Guanghua Wu, Yibo Wu, Jian Fertility intention and its affecting factors in China: A national cross-sectional survey |
title | Fertility intention and its affecting factors in China: A national cross-sectional survey |
title_full | Fertility intention and its affecting factors in China: A national cross-sectional survey |
title_fullStr | Fertility intention and its affecting factors in China: A national cross-sectional survey |
title_full_unstemmed | Fertility intention and its affecting factors in China: A national cross-sectional survey |
title_short | Fertility intention and its affecting factors in China: A national cross-sectional survey |
title_sort | fertility intention and its affecting factors in china: a national cross-sectional survey |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9939585/ https://www.ncbi.nlm.nih.gov/pubmed/36814608 http://dx.doi.org/10.1016/j.heliyon.2023.e13445 |
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