社会经济地位、健康生活方式与高血压发病的前瞻性队列研究

林深荣; 苏旭; 吴延莉; 李雪娇; 王艺颖; 周婕; 刘涛

doi:10.16462/j.cnki.zhjbkz.2023.04.002

社会经济地位、健康生活方式与高血压发病的前瞻性队列研究

doi: 10.16462/j.cnki.zhjbkz.2023.04.002

林深荣¹,
苏旭²,
吴延莉²,
李雪娇³,
王艺颖²,
周婕²,
刘涛^{1, 2, ,}

1.
550025 贵阳，贵州大学医学院
2.
550004 贵阳，贵州省疾病预防控制中心慢性病防治研究所
3.
550025 贵阳，贵州医科大学公共卫生与健康学院，环境污染与疾病监控教育部重点实验室

基金项目:

贵州省科技计划项目 supported by qiankehe[2018]2819

详细信息

通讯作者:
刘涛，E-mail: 543820987@qq.com

中图分类号: R544.1
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出版历程
- 收稿日期: 2022-04-22
- 修回日期: 2022-08-04
- 网络出版日期: 2023-04-28
- 刊出日期: 2023-04-10

A prospective cohort study of socioeconomic status, healthy lifestyle and the incidence of hypertension

LIN Shenrong¹,
SU Xu²,
WU Yanli²,
LI Xuejiao³,
WANG Yiying²,
ZHOU Jie²,
LIU Tao^{1, 2
, ,}

1.
Medical College, Guizhou University, Guiyang 550025, China
2.
Institute of Chronic Disease Prevention and Control, Guizhou Center for Disease Control and Prevention, Guiyang 550004, China
3.
School of Public Health, the Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang 550025, China

Funds:

Guizhou Provincial Science and Technology Plan Project supported by qiankehe[2018]2819

More Information

Corresponding author: LIU Tao, E-mail: 543820987@qq.com

摘要

摘要: 目的探讨社会经济地位(socioeconomic status, SES)、健康生活方式与高血压发病的关系，为高血压的防控提供参考依据。方法采用分层整群随机抽样于2010年对抽取的贵州省12个县(市、区)≥18岁常住居民共9 280人进行基线调查，于2016—2020年对该队列所有人群进行随访；采用t检验、χ²检验进行单因素分析，使用Cox比例风险回归模型分析SES、健康生活方式对高血压发病的影响。结果研究有效样本量为3 401人，高血压发病765人，人群高血压发病密度为32.53/1 000人年。多因素Cox回归结果显示：与低SES(＜9分)人群相比，高SES(≥9分)人群高血压发病风险下降29.9%(HR=0.701, 95% CI: 0.584~0.842)；与≤2种健康生活方式的人群相比，4种、≥5种健康生活方式人群发病风险分别降低25.7%(HR=0.743, 95% CI: 0.581~0.950)、39.2%(HR=0.608, 95% CI: 0.455~0.812)。与SES低且健康生活方式≤2种的人群相比，SES低且具有3种、4种、≥5种健康生活方式人群高血压发病风险的差异均无统计学意义(均有P＞0.05)；SES高且具有3种、4种、≥5种健康生活方式的人群高血压发病风险分别降低36.3%(HR=0.637, 95% CI: 0.446~0.909)、44.0%(HR=0.560, 95% CI: 0.391~0.802)、55.8%(HR=0.442, 95% CI: 0.295~0.662)。结论 SES较低人群是贵州省高血压防控的重点人群，应采取措施提高其SES，并有针对性地开展健康教育与健康促进工作。
- 社会经济地位 /
- 健康生活方式 /
- 高血压 /
- 队列研究
Abstract: Objective To explore the relationship between socioeconomic status (SES), healthy lifestyle, and the incidence of hypertension, and to provide reference basis for the prevention and control of hypertension. Methods A total of 9 280 permanent residents aged 18 and over in 12 counties (cities and districts) of Guizhou Province were investigated by stratified cluster random sampling in 2010. All populations in this cohort were followed up from 2016 to 2020. T-test and χ² test were used for univariate analysis. And Cox proportional hazards regression was used in analyzing the impact of socioeconomic status and healthy lifestyle on the incidence of hypertension. Results The adequate sample size of the final cohort study was 3 401. Among them, 765 had hypertension, and the incidence density was 32.53/1 000 person-years. The results of multivariate Cox regression showed that compared with the population with low SES (< 9 points), the risk of hypertension in the people with high SES (≥9 points) decreased by 29.9% (HR=0.701, 95% CI: 0.584-0.842). Compared to the population with ≤2 healthy lifestyles, the incidence risk of people with 4, 5, and more healthy lifestyles decreased by 25.7% (HR=0.743, 95% CI: 0.581-0.950) and 39.2% (HR=0.608, 95% CI: 0.455-0.812), respectively. However, the difference in hypertension risk in the population with low SES and those with 3, 4, 5, or more healthy lifestyles was not statistically significant (all P>0.05) compared to those with low SES and ≤2 healthy lifestyles. The risk of hypertension in the population with high SES and have 3, 4, 5 or more healthy lifestyles was reduced by 36.3% (HR=0.637, 95% CI: 0.446-0.909), 44.0% (HR=0.560, 95% CI: 0.391-0.802) and 55.8% (HR=0.442, 95% CI: 0.295 -0.662), respectively. Conclusions The population with low SES is critical in preventing and controlling hypertension in Guizhou Province. Various measures should be taken to improve their socioeconomic status and simultaneously carry out health education and health promotion.
- Socioeconomic status /
- Healthy lifestyle /
- Hypertension /
- Cohort study

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表 1 社会经济地位衡量指标的赋分标准

Table 1. Scoring criteria of socioeconomic status measurement indicators

家庭人均年收入(元)	个人受教育程度	职业	分值(分)
≥13 500	大专及以上	国家机关、党群组织、企事业单位负责人	6
8 000~＜13 500	高中/中专/技校	专业技术人员、办事人员和有关人员	5
5 400~＜8 000	初中毕业	商业、服务业人员	4
3 600~＜5 400	小学毕业	生产运输设备操作人员及有关人员、农林牧渔水利业生产人员	3
2 000~＜3 600	小学未毕业	其他劳动者	2
＜2 000	未受过正规教育	无业	1

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表 2 基线人群基本特征[n(%)]

Table 2. Basic characteristics of the baseline population[n(%)]

变量	高血压组 (n=765)	非高血压组 (n=2 636)	t/χ²值	P值	变量	高血压组 (n=765)	非高血压组 (n=2 636)	t/χ²值	P值
年龄(岁)			92.148	＜0.001	不吸烟			2.707	0.100
18~＜45	367(17.63)	1 715(82.37)			否	254(24.26)	793(75.74)
45~＜60	265(27.18)	710(72.82)			是	511(21.71)	1 843(78.29)
≥60	133(38.66)	211(61.34)			不饮酒			0.287	0.592
性别			4.032	0.045	否	280(23.01)	937(76.99)
男	373(24.06)	1 177(75.94)			是	485(22.21)	1 699(77.79)
女	392(21.18)	1 459(78.82)			蔬菜摄入≥300 g/d			0.591	0.442
民族			0.263	0.608	否	258(23.29)	850(76.71)
汉族	480(22.78)	1 627(77.22)			是	507(22.11)	1 786(77.89)
少数民族	285(22.02)	1 009(78.98)			水果摄入≥200 g/d			5.807	0.016
婚姻状况			16.589	＜0.001	否	728(22.96)	2 443(77.04)
未婚	44(13.66)	278(86.34)			是	37(16.09)	193(83.91)
已婚/同居	647(23.21)	2 140(76.79)			烹调油摄入≤25 g/d			3.011	0.083
离婚/丧偶/分居	74(25.34)	218(74.66)			否	611(23.16)	2 027(76.84)
城乡居住地			6.652	0.010	是	154(20.18)	609(79.82)
城市	215(19.80)	871(80.20)			食盐摄入≤6 g/d			3.933	0.047
农村	550(23.76)	1 765(76.24)			否	566(23.40)	1 853(76.60)
家庭人均年收入^a(元)			16.650	0.005	是	199(20.26)	783(79.74)
＜2 000	123(26.80)	336(73.20)			睡眠时间≥7 h/d			4.167	0.041
2 000~＜3 600	152(23.21)	503(76.79)			否	113(26.34)	316(73.66)
3 600~＜5 400	124(22.02)	439(78.98)			是	652(21.90)	2 320(78.10)
5 400~＜8 000	115(22.82)	389(77.18)			代谢当量值 (x±s，mL/kg·min)	111.9±116.4	118.3±126.9	1.256	0.209
8 000~＜13 500	148(23.49)	482(76.51)			糖尿病^a			1.498	0.221
≥13 500	96(16.70)	479(83.30)			否	706(22.21)	2 473(77.79)
个人受教育程度			46.219	＜0.001	是	55(25.82)	158(74.18)
未受过正规教育	164(32.35)	343(67.65)			血脂异常			1.389	0.239
小学未毕业	123(25.73)	355(74.27)			否	300(23.58)	972(76.42)
小学毕业	163(22.48)	562(77.52)			是	465(21.84)	1 664(78.16)
初中毕业	214(19.18)	902(80.82)			高血压家族史^a			1.166	0.280
高中/中专/技校	68(17.30)	325(82.70)			否	483(22.07)	1 705(77.93)
大专及以上	33(18.13)	149(81.87)			是	84(19.72)	342(80.28)
职业			13.605	0.018	SES分组(分) ^a			18.979	＜0.001
无业	110(22.49)	379(77.51)			＜9	335(26.42)	933(73.58)
其他劳动者	62(19.68)	253(80.32)			≥9	423(19.97)	1 695(80.03)
生产运输设备操作人员及有关人员、农林牧渔水利业生产人员	506(24.20)	1 585(75.80)			健康生活方式数量(种)			9.114	0.028
商业、服务业人员	30(17.05)	146(83.95)			≤2	200(25.94)	571(74.06)
专业技术人员、办事人员和有关人员	46(16.55)	232(83.45)			3	205(22.88)	691(77.12)
国家机关、党群组织、企事业单位负责人	11(21.15)	41(78.85)			4	226(21.48)	826(78.52)
BMI分级(kg/m²) ^a			9.704	0.021	≥5	134(19.65)	548(80.35)
正常	486(21.88)	1 735(78.12)
轻体重	36(17.39)	171(82.61)
超重	195(24.22)	610(75.78)
肥胖	47(29.75)	111(70.25)
注：^a表示该变量有缺失值。

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表 3 SES、健康生活方式分别对高血压发病的Cox回归分析

Table 3. Cox regression analysis of SES and healthy lifestyle on hypertension

变量	新发病数(人)	发病密度/1 000人年	HR(95% CI)
变量	新发病数(人)	发病密度/1 000人年	模型1	P值	模型2	P值	模型3	P值
SES分组(分)
＜9	335	39.58	1.000		1.000		1.000
≥9	423	28.29	0.607(0.525~0.701)	＜0.001	0.689(0.592~0.802)	＜0.001	0.701(0.584~0.842)	＜0.001
健康生活方式分组(种)
≤2	200	38.51	1.000		1.000		1.000
3	205	33.44	0.836(0.688~1.016)	0.071	0.860(0.703~1.052)	0.142	0.848(0.671~1.072)	0.169
4	226	30.82	0.720(0.595~0.871)	0.001	0.801(0.650~0.987)	0.038	0.743(0.581~0.950)	0.018
≥5	134	27.57	0.594(0.477~0.740)	＜0.001	0.690(0.541~0.879)	0.003	0.608(0.455~0.812)	0.001
注：模型1：不调整；模型2：调整年龄、性别、婚姻、城乡；模型3：在模型2基础上调整MET、健康生活方式/SES分组(在研究SES对高血压发病的影响时，调整健康生活方式；在研究健康生活方式对高血压发病的影响时，调整SES分组)、BMI、糖尿病、血脂异常及高血压家族史。

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表 4 SES、健康生活方式联合作用对高血压发病的Cox回归分析

Table 4. Cox regression analysis of combination of SES and healthy lifestyle on the incidence of hypertension

SES分组(分)	健康生活方式分组(种)	新发病数(人)	发病密度/1 000人年	HR(95% CI)
SES分组(分)	健康生活方式分组(种)	新发病数(人)	发病密度/1 000人年	模型1	P值	模型2	P值	模型3	P值
＜9	≤2	77	45.76	1.000		1.000		1.000
	3	94	43.10	0.880(0.651~1.190)	0.406	0.916(0.676~1.240)	0.569	0.933(0.639~1.360)	0.718
	4	105	36.12	0.707(0.527~0.949)	0.021	0.819(0.602~1.114)	0.203	0.812(0.555~1.187)	0.282
	≥5	59	34.85	0.614(0.437~0.862)	0.005	0.717(0.504~1.020)	0.064	0.702(0.452~1.089)	0.114
≥9	≤2	122	34.81	0.637(0.479~0.848)	0.002	0.736(0.550~0.986)	0.040	0.793(0.558~1.128)	0.198
	3	108	27.59	0.487(0.363~0.653)	＜0.001	0.592(0.439~0.799)	0.001	0.637(0.446~0.909)	0.013
	4	120	27.23	0.437(0.328~0.583)	＜0.001	0.570(0.422~0.769)	＜0.001	0.560(0.391~0.802)	0.002
	≥5	73	23.33	0.353(0.256~0.487)	＜0.001	0.486(0.347~0.682)	＜0.001	0.442(0.295~0.662)	＜0.001
注：模型1：不调整；模型2：调整年龄、性别、婚姻、城乡；模型3：在模型2基础上调整MET、BMI、糖尿病、血脂异常及高血压家族史。

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