Regional differences and influencing factors of the health level of women and children in China

doi:10.3969/j.issn.1004-9479.2023.02.2021382

Abstract

Abstract:

Taking maternal mortality and perinatal mortality as the main indicators, and using coefficient variation, spatial autocorrelation, and panel regression analyze the spatial pattern and its influencing factors about women and children health from 2005 to 2015 in China. The results show that: ①The overall health level of women and children is on an upward trend, and the growth rate in the western region is the highest in China, but the overall trend is gradient 'East-Central-West' decreasing. ② The relative difference of the health level of women and children is remarkable. The difference in maternal mortality rate fluctuates, and the difference in perinatal mortality rate tends to increase during the ten years, in which, the difference in the western region is the largest, followed by the eastern region, and the central region smallest. ③The horizontal Moran's index of women and children health shows a "W"-shaped change trend, and the degree of spatial agglomeration decreases gradually. The stable hot spots arise in the central and eastern regions, and the stable cold spots in the western regions. ④ Prenatal examination rate, urbanization level and per capita public health expenditure promote the development of women and children health, while the proportion of environment temperature, high-risk maternal women, and female illiteracy rate restrain its improvement.

Key words: women and children health, maternal mortality, perinatal mortality, regional differences, influencing factors, China

摘要：

以孕产妇死亡率、围产儿死亡率作为中国妇幼健康水平的主要表征指标，运用变异系数、空间自相关、面板回归等方法对2005—2015年间中国妇幼健康水平进行空间格局变化和影响因素分析。结果表明：①2005—2015年以来中国妇幼健康水平整体呈上升趋势，西部增长幅度高于中东部地区，但整体保持“东-中-西”梯度递减的态势；②2005—2015年中国妇幼健康水平的相对差异显著，孕产妇死亡率的差异随时间呈波动变化、围产儿死亡率的差异随时间趋于上升；其中，西部地区的地带内差异最大、东部次之、中部最小；③妇幼健康水平的莫兰指数表现为“W”形的变化趋势，空间集聚程度逐渐减小，中东部地区形成稳定热点区、西部地区形成稳定冷点区；④产前检查率、城镇化水平和人均公共卫生支出的发展对妇幼健康的发展有促进作用，环境温度、高危孕产妇比例、女性文盲率的增加对妇幼健康的发展起抑制作用。

关键词: 妇幼健康, 孕产妇死亡率, 围产儿死亡率, 区域差异, 影响因素, 中国

Xiao XIE, Bin YING, Fangjuan DU, Xiaoyu SONG, Hanyan WU. Regional differences and influencing factors of the health level of women and children in China[J]. World Regional Studies, 2023, 32(2): 82-92.

谢潇, 盈斌, 杜芳娟, 宋潇玉, 吴函彦. 中国妇幼健康水平的区域差异和影响因素[J]. 世界地理研究, 2023, 32(2): 82-92.

Figures/Tables 6

References 31

1	中华人民共和国国家卫生健康委员会.中国妇幼健康事业发展报告(2019)..
	National Health Commission of the People's Republic of China.Report on the development of women and child health undertakings in China (2019). .
2	国家卫生和计划生育委员会.中国卫生和计划生育统计年鉴(2019).北京:中国协和医科大学出版社,2019.
	National Health and Family Planning Commission. China Statistical Yearbook of Health and Family Planning (2019). Beijing: China Union Medical University Press,2019.
3	BANG A, BANG R, BAITULE S, et al. Effect of home-based neonatal care and management of sepsis on neonatal mortality: Field trial in rural India. The Lancet, 1999, 354(9194):1955-1961.
4	MOLONA G, WEISER T, LIPSITZ S, et al. Relationship between cesarean delivery rate and maternal and neonatal mortality. Journal of the American Medical Association, 2015, 314(21):2263-2270.
5	FELISBINO-MENDES M, MOREIRA A, VELASQUEZ-MELENDEZ G. Association between maternal nutritional extremes and offspring mortality: A population-based cross-sectional study, Brazil, demographic health survey 2006. Midwifery, 2015, 31(9):897-903.
6	姚瑶,刘斌,刘国恩.妇幼保健院规模与妇幼保健水平的关系:基于全国省级面板数据的研究.人口与发展,2014,20(4):65-75.
	YAO Y, LIU B, LIU G. The relationship between maternal and child health care institution scale and maternal-child health care level: An empirical analysis based on province-level panel data. Population and Development, 2014,20(4):65-75.
7	MISHRA P, PAUTANTHANG N, MARBANIANG S, et al. Geographical divide led inequality in accessing maternal healthcare services between hills and valley regions of manipur state, India. Clinical Epidemiology and Global Health, 2021(11): 100744.
8	陈小红,黄亚捷,盘诗芮.环境污染对孕产妇死亡率影响分析——基于2005—2015年省级面板数据实证研究.中国人口·资源与环境,2018,28(S2):67-70.
	CHEN X, HUANG Y, PAN S. Analysis of the effect of environmental pollution on maternal mortality: Empirical research based on provincial panel data during 2005-2015. China Population, Resources and Environment, 2018,28(S2):67-70.
9	修璟威,刘晓迪,李望晨,等.2012—2017年中国孕产妇死亡率空间分布特征.中国妇幼保健,2019,34(13):2905-2907.
	XIU J, LIU X, LI W, et al. Characteristics of the spatial distribution of maternal mortality in China from 2012 to 2017. Maternal and Child Health Care of China, 2019,34(13):2905-2907.
10	LI Z, FU J, JIANG D, et al. Spatiotemporal distribution of U5MR and their relationship with geographic and socioeconomic factors in China. International Journal of Environmental Research and Public Health,2017,14(11):1428.
11	RODRIGUES N, MONTEIRO D, ALMEIDA A, et al. Temporal and spatial evolution of maternal and neonatal mortality rates in Brazil, 1997-2012. Jornal de Pediatria, 2016, 92(6):567-573.
12	毕蕾,鞠磊,张寒,等.基于空间模型的我国孕产妇死亡率影响因素分析.中国妇幼保健,2018,33(7):1441-1444.
	BI L, JU L, ZHANG H, et al. Analysis on the influencing factors of maternal mortality rate in China based on spatial model. Maternal and Child Health Care of China,2018,33(7):1441-1444.
13	向堃,宋德勇.我国省域孕产妇死亡率的空间实证研究.中国卫生经济,2015,34(4):61-63.
	XIANG K, SONG D. Spatial analysis of China province-level maternal mortality. Chinese Health Economics,2015,34(4):61-63.
14	毛文琳,卫龙宝.政府卫生支出规模对居民健康的影响研究.浙江社会科学,2020(3):11-20.
	MAO W, WEI L. The relationship between specific mortality and public health expenditure. Zhejiang Social Sciences, 2020(3):11-20.
15	梁峥嵘,陈祥华,于贞杰,等.基于集中指数和泰尔指数评价山东省妇幼保健资源分布及儿童健康公平性.中国卫生统计,2015,32(2):231-234.
	LIANG Z, CHEN X, YU Z, et al. Analysis on the equity of distribution of maternal and child health care resource and children's health equity in Shandong Province based on concentration index and theil index. Chinese Journal of Health Statistics, 2015,32(2):231-234.
16	丁宁欣,夏曼曼,邱英鹏,等."新生儿安全项目地区"经济发展及卫生投入对妇幼健康的影响.中国卫生经济,2017,36(10):66-68.
	DING N, XIA M, QIU Y, et al. The impact of economic development and health investment on maternal and child health in "Newborn Health Project Area". Chinese Health Economics, 2017,36(10):66-68.
17	刘旭栋,杨兰,邱伟涛,等.甘肃省妇幼保健资源分布及妇女儿童健康公平性研究.中国妇幼保健,2020,35(11):1956-1960.
	LIU X, YANG L, QIU W,et al.Research on the distribution of maternal and child health care resources and the equity of women and children's health in Gansu Province. Maternal and Child Health Care of China,2020,35(11):1956-1960.
18	杜两省,刘斌,范丹.大气污染对围产儿死亡率的影响研究.环境经济研究,2018,3(4):71-85.
	DU L, LIU B, FAN D. The effect of air pollution on perinatal mortality. Journal of Environmental Economics, 2018,3(4):71-85.
19	SON J, LEE J, BELL M. Is ambient temperature associated with risk of infant mortality? A multi-city study in Korea. Environmental Research, 2017(158):748-752.
20	BAILEY B, EUSER A, BOL K, et al. High-altitude residence alters blood-pressure course and increases hypertensive disorders of pregnancy. The Journal of Maternal-Fetal & Neonatal Medicine, 2022,35(7): 1264-1271.
21	张雪,齐庆青,刘凤洁,等.年龄对经产孕妇孕产期健康及妊娠结局的影响.中国妇幼保健,2018,33(23):5406-5409.
	ZHANG X, QI Q, LIU F, et al. Effect of age on health and pregnancy outcome of parturient women. Maternal and Child Health Care of China,2018,33(23):5406-5409.
22	GREPIN K, BHARADWAJ P. Maternal education and child mortality in Zimbabwe. Journal of Health Economics, 2015(44):97-117.
23	张天成,陈露,谭利明,等.中国孕产妇死亡率时空变化及预测探究.中国卫生统计,2018,35(5):745-747.
	ZHANG T, CHEN L, TAN L, et al. Temporal and spatial variation and prediction of maternal mortality in China. Chinese Journal of Health Statistics, 2018,35(5):745-747.
24	陈云,吴雨.长江经济带人口健康水平的空间格局及影响因素.经济地理,2020,40(9):152-159.
	CHEN Y, WU Y. Spatial pattern and influencing factors of population health level in the Yangtze River Economic Belt. Economic Geography, 2020,40(9):152-159.
25	杨振,丁启燕,王念,等.中国人口健康脆弱性地区差异与影响因素分析.地理科学,2018,38(1):135-142.
	YANG Z, DING Q, WANG N, et al. Distribution characteristics of health vulnerability and its influence factors in China. Scientia Geographica Sinica,2018,38(1):135-142.
26	童磊,郑珂,苏飞,等.浙江省人口健康脆弱性评估及影响因素分析.地理科学,2020,40(8):1293-1299.
	TONG L, ZHENG K, SU F, et al. Analysis of population health vulnerability assessment and influencing factors in Zhejiang Province. Scientia Geographica Sinica,2020,40(8):1293-1299.
27	穆学青,郭向阳,明庆忠.多维贫困视角下县域旅游扶贫效率时空演化及影响机理——以云南25个边境县(市)为例.经济地理,2020,40(12):199-210.
	MU X, GUO X, MING Q. The spatio-temporal evolution and impact mechanism of county tourism poverty alleviation efficiency from the perspective of multidimensional poverty: A case study of 25 border counties(cities)in Yunnan Province. Economic Geography, 2020,40(12):199-210.
28	ANSELIN L. Local indicators of spatial association: LISA. Geographical Analysis, 1995, 27(2): 93-115.
29	马丽梅,张晓.区域大气污染空间效应及产业结构影响.中国人口·资源与环境,2014,24(7):157-164.
	MA L, ZHANG X. Spatial effects of regional air pollution and the impact of industrial structure. China Population, Resources and Environment, 2014,24(7):157-164.
30	周榕,庄汝龙,黄晨熹.中国人口老龄化格局演变与形成机制.地理学报,2019,74(10):2163-2177.
	ZHOU R, ZHUANG R, HUANG C. Pattern evolution and formative mechanism of aging in China. Acta Geographica Sinica, 2019,74(10):2163-2177.
31	赵雪雁,王伟军,万文玉.中国居民健康水平的区域差异:2003—2013.地理学报,2017,72(4):685-698.
	ZHAO X, WANG W, WAN W. Regional inequalities of residents' health level in China: 2003-2013. Acta Geographica Sinica, 2017,72(4):685-698.

年份	孕产妇死亡率				围产儿死亡率
年份	全国	东部	中部	西部	全国	东部	中部	西部
平均值	1.212	0.464	0.251	1.001	0.470	0.307	0.248	0.440
2005	1.067	0.496	0.273	0.786	0.376	0.311	0.190	0.251
2006	1.012	0.590	0.175	0.762	0.425	0.321	0.126	0.323
2007	1.154	0.427	0.201	0.905	0.426	0.308	0.169	0.361
2008	1.250	0.381	0.235	1.032	0.454	0.309	0.186	0.412
2009	1.372	0.440	0.235	1.151	0.449	0.304	0.216	0.424
2010	1.151	0.459	0.318	0.983	0.485	0.303	0.281	0.470
2011	1.403	0.451	0.216	1.158	0.490	0.338	0.335	0.479
2012	1.461	0.731	0.286	1.234	0.561	0.292	0.306	0.590
2013	1.331	0.414	0.188	1.175	0.500	0.301	0.340	0.506
2014	1.060	0.409	0.391	0.915	0.478	0.291	0.290	0.494
2015	1.074	0.304	0.241	0.915	0.525	0.303	0.290	0.533

年份	孕产妇死亡率				围产儿死亡率
年份	全国	东部	中部	西部	全国	东部	中部	西部
平均值	1.212	0.464	0.251	1.001	0.470	0.307	0.248	0.440
2005	1.067	0.496	0.273	0.786	0.376	0.311	0.190	0.251
2006	1.012	0.590	0.175	0.762	0.425	0.321	0.126	0.323
2007	1.154	0.427	0.201	0.905	0.426	0.308	0.169	0.361
2008	1.250	0.381	0.235	1.032	0.454	0.309	0.186	0.412
2009	1.372	0.440	0.235	1.151	0.449	0.304	0.216	0.424
2010	1.151	0.459	0.318	0.983	0.485	0.303	0.281	0.470
2011	1.403	0.451	0.216	1.158	0.490	0.338	0.335	0.479
2012	1.461	0.731	0.286	1.234	0.561	0.292	0.306	0.590
2013	1.331	0.414	0.188	1.175	0.500	0.301	0.340	0.506
2014	1.060	0.409	0.391	0.915	0.478	0.291	0.290	0.494
2015	1.074	0.304	0.241	0.915	0.525	0.303	0.290	0.533

维度	变量	指标	孕产妇死亡率		围产儿死亡率
维度	变量	指标	FE	RE	FE	RE
自然环境	X1	年平均气温	0.362^*(1.88)	-0.377^***(-3.30)	-0.044(-0.25)	-0.249^**(-2.11)
	X2	年平均降水量	0.068（1.28）	-0.026(-0.57)	0.005（0.17）	-0.020(-0.72)
	X3	人均SO₂排放量	-0.030(-0.36)	-0.058(-0.84)	0.087（1.36）	0.072（1.39）
人口结构	X4	高危孕产妇比例	0.261^**（2.24）	0.209^**（2.11）	0.231^**（2.36）	0.244^**（2.53）
	X5	产前检查率	-0.496(-1.61)	-0.675^*(-1.94)	-0.402^*(-2.03)	-0.442^**(-2.21)
	X6	15岁以上女性文盲率	0.241^**（2.62）	0.263^***（4.21）	0.044（1.27）	0.035（1.10）
社会经济	X7	城镇化率	-1.943^***(-4.38)	-1.861^***(-7.84)	-1.663^***(-8.86)	-1.427^***(-11.24)
	X8	千人卫生机构数	-0.003(-0.07)	-0.036(-0.88)	-0.026(-1.16)	-0.035(-1.58)
	X9	人均公共卫生支出	-0.215^***(-3.17)	-0.181^***(-4.94)	-0.105^***(-2.96)	-0.130^***(-3.97)
常数项			11.237^***（5.78）	14.012^**（7.26）	10.589^***（9.20）	10.604^***（10.96）
R²			0.744	0.735	0.861	0.858
F统计值			31.28^***		64.11^***
Hausman检验			77.272^***		43.615^***

维度	变量	指标	孕产妇死亡率		围产儿死亡率
维度	变量	指标	FE	RE	FE	RE
自然环境	X1	年平均气温	0.362^*(1.88)	-0.377^***(-3.30)	-0.044(-0.25)	-0.249^**(-2.11)
	X2	年平均降水量	0.068（1.28）	-0.026(-0.57)	0.005（0.17）	-0.020(-0.72)
	X3	人均SO₂排放量	-0.030(-0.36)	-0.058(-0.84)	0.087（1.36）	0.072（1.39）
人口结构	X4	高危孕产妇比例	0.261^**（2.24）	0.209^**（2.11）	0.231^**（2.36）	0.244^**（2.53）
	X5	产前检查率	-0.496(-1.61)	-0.675^*(-1.94)	-0.402^*(-2.03)	-0.442^**(-2.21)
	X6	15岁以上女性文盲率	0.241^**（2.62）	0.263^***（4.21）	0.044（1.27）	0.035（1.10）
社会经济	X7	城镇化率	-1.943^***(-4.38)	-1.861^***(-7.84)	-1.663^***(-8.86)	-1.427^***(-11.24)
	X8	千人卫生机构数	-0.003(-0.07)	-0.036(-0.88)	-0.026(-1.16)	-0.035(-1.58)
	X9	人均公共卫生支出	-0.215^***(-3.17)	-0.181^***(-4.94)	-0.105^***(-2.96)	-0.130^***(-3.97)
常数项			11.237^***（5.78）	14.012^**（7.26）	10.589^***（9.20）	10.604^***（10.96）
R²			0.744	0.735	0.861	0.858
F统计值			31.28^***		64.11^***
Hausman检验			77.272^***		43.615^***

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