唐山市居民空腹血糖受损患病现状及影响因素

王存; 陈志新; 任虹云; 王自超; 郭媛媛; 蔡相颖; 申佩璇; 侯丽颖; 刘海峰; 李云

doi:10.16462/j.cnki.zhjbkz.2021.01.018

唐山市居民空腹血糖受损患病现状及影响因素

doi: 10.16462/j.cnki.zhjbkz.2021.01.018

1.
063210 唐山，华北理工大学公共卫生学院预防医学系
2.
063700 滦州，滦州市疾病预防控制中心慢病科
3.
064200 遵化，遵化市疾病预防控制中心慢病科
4.
063210 唐山，曹妃甸区疾病预防控制中心慢病科
5.
063000 唐山，唐山市疾病预防控制中心慢病科

基金项目:

唐山市科技创新团队培养计划 20130206D

详细信息

通讯作者:
李云，E-mail: liyun8022@163.com

中图分类号: R587.1;R195.4
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- 被引次数: 0
出版历程
- 收稿日期: 2020-06-28
- 修回日期: 2020-10-15
- 刊出日期: 2021-01-10

Analysis of prevalence and influencing factors of impaired fasting glucose in residents of Tangshan

1.
Department of Preventive Medicine, School of Public Health, North China University of Science and Technology, Tangshan 063210, China
2.
Department of Chronic Diseases, Luanzhou Center for Disease Control and Prevention, Luanzhou 063700, China
3.
Department of Chronic Diseases, Zunhua Center for Disease Control and Prevention, Zunhua 064200, China
4.
Department of Chronic Diseases, Caofeidian District Center for Disease Control and Prevention, Tangshan 063210, China
5.
Department of Chronic Diseases, Tangshan Center for Disease Control and Prevention, Tangshan 063000, China

Funds:

The Science and Technology Innovation Team Project of Tangshan 20130206D

More Information

Corresponding author: LI Yun, E-mail:liyun8022@163.com

摘要

摘要: 目的了解唐山市地区居民空腹血糖受损(impaired fasting glucose, IFG)患病现状及影响因素，为本地区糖尿病预防及心血管危险因素控制提供理论依据。方法依托于唐山市慢性病及其危险因素监测专项调查，于2018年1月1日-2018年12月31日期间，采用分层随机抽样方法，对11 475例唐山市常住成年居民进行问卷调查和体格检查，检测空腹血糖水平，采用Logistic回归分析模型分析IFG的可能影响因素。结果共收回有效问卷10 510份，应答率为91.6%。所有调查对象中，IFG者829例，总患病率为7.89%，其中男性8.59%，女性7.04%，差异有统计学意义(χ² =15.458, P < 0.001)。市区人群IFG患病率为10.95%，县区人群IFG患病率为6.36%(其中山区为9.56%，平原为6.55%，沿海为3.59%)，差异有统计学意义(χ² =43.340, P < 0.001)。多因素非条件Logistic回归分析模型分析显示，年龄、BMI、高血压、高脂血症、糖尿病家族史、城乡与IFG患病风险有关。结论唐山地区成人居民IFG患病率较高，年龄、超重、高血压、高脂血症、糖尿病家族史、城乡是IFG患病的影响因素。
- 空腹血糖受损 /
- 患病率 /
- 影响因素
Abstract: Objective To investigate the prevalence and influencing factors of impaired fasting glucose(IFG) in residents of Tangshan, and to provide evidence for the prevention and control of diabetes and cardiovascular risk factors in the region. Methods Based on the survey of chronic diseases and their risk factors in Tangshan city, 11 475 adult residents in urban and rural districts of Tangshan were randomly enrolled in this study from January 1, 2018 to December 31, 2018. All data were collected by questionnaire and physical examination. The prevalence of IFG was calculated. The Logistic regression analysis model was used to analyze the risk factors of IFG. Results A total of 10 510 valid questionnaires (91.6%) were retrieved. Among all the subjects, there were 829 cases of IFG, with a total prevalence of 7.89%. The prevalence was 8.59% for males and 7.04% for females, and the difference was statistically significant (χ² =15.458, P < 0.001). The prevalence was 10.95% for urban residents and 6.36% for rural residents, (9.56% for residents in mountainous areas, 6.55% for residents in plain areas and 3.59% for residents in coastal areas). Multivariate unconditional Logistic regression analysis showed that age, body mass index, hypertension, hyperlipidemia, family history of diabetes, urban or rural areas were associated with the risk of IFG. Conclusions The prevalence of IFG is relatively high for adult residents in Tangshan area. Age, overweight, hypertension, hyperlipidemia, family history of diabetes and urban area are the influencing factors of IFG.
- Impaired fasting glucose /
- Prevalence /
- Influencing factors

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表 1 2018年唐山市研究对象的年龄与性别构成

Table 1. The age and gender composition of research subjects in Tangshan in 2018

年龄(岁)	男		女		合计
年龄(岁)	人数	构成比(%)	人数	构成比(%)	人数	构成比(%)
18~	1 331	23.19	1 383	28.99	2 714	25.82
35~	954	16.62	954	20.00	1 908	18.15
45~	1 191	20.75	1 061	22.24	2 252	21.43
55~	1 395	24.30	922	19.33	2 317	22.05
65~	652	11.36	342	7.17	994	9.46
≥75	217	3.78	108	2.26	325	3.09
合计	5 740	100.00	4 770	100.00	10 510	100.00

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表 2 2018年唐山市研究对象中不同因素与IFG患病率的关系

Table 2. The relationship between different factors and the prevalence of IFG in Tangshan in 2018

变量	调查人数	患病人数	患病率(%)	χ²值	P值
性别				15.458	< 0.001
男	5 740	493	8.59
女	4 770	336	7.04
年龄(岁)				773.450	< 0.001
18~	2 714	61	2.25
35~	1 908	98	5.14
45~	2 252	206	9.15
55~	2 317	278	12.00
65~	994	151	15.19
≥75	325	35	10.77
城乡				43.340	< 0.001
市区	3 499	383	10.95
县区	7 011	446	6.36
地理环境				83.220	< 0.001
山区	2 008	192	9.56
平原	6 020	548	9.10
沿海	2 482	89	3.59
BMI(kg/m²)				211.323	< 0.001
< 18.5	615	48	7.80
18.5~	4 035	223	5.53
24.0~	4 083	357	8.74
≥28.0	1 777	201	11.31
高血压				400.264	< 0.001
高血压	2 634	336	12.76
非高血压	7 876	493	6.26
高脂血症				269.172	< 0.001
高血脂	2 077	263	12.66
非高血脂	8 433	566	6.71
糖尿病家族史				12.606	0.002
有	716	64	8.94
无	9 794	765	7.81
吸烟				50.118	< 0.001
是	3 414	296	8.67
否	7 077	532	7.52
饮酒				24.733	< 0.001
是	3 436	314	9.14
否	7 027	512	7.29
服用降压药				278.210	< 0.001
是	1 127	156	13.84
否	9 258	655	7.07
服用降脂药				125.533	< 0.001
是	173	29	16.76
否	9 915	741	7.47
服用降糖药				1528.768	< 0.001
是	299	34	11.37
否	10 182	794	7.80

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表 3 2018年唐山市研究对象IFG影响因素的非条件Logistic回归分析模型结果

Table 3. Unconditional Logistic regression analysis model results of factors affecting IFG in Tangshan in 2018

自变量	β值	s_x	Wald χ²值	P值	OR (95% CI)值
年龄(岁)			157.016	< 0.001
18~					1.000
35~	0.727	0.168	18.677	< 0.001	2.070(1.488~2.879)
45~	1.299	0.155	70.564	< 0.001	3.664(2.706~4.961)
55~	1.600	0.155	106.439	< 0.001	4.953(3.655~6.713)
65~	1.900	0.173	120.846	< 0.001	6.685(4.764~9.380)
≥75	1.479	0.249	35.395	< 0.001	4.387(2.695~7.140)
BMI(kg/m²)			37.586	< 0.001
< 18.5					1.000
18.5~	-0.269	0.188	2.051	0.152	0.764(0.529~1.104)
24.0~	0.105	0.183	0.327	0.567	1.111(0.775~1.590)
≥28.0	0.421	0.193	4.737	0.030	1.524(1.043~2.226)
糖尿病家族史
有	0.408	0.182	5.041	0.025	1.490(1.111~1.999)
无					1.000
高血压
是	0.366	0.103	12.522	< 0.001	1.352(1.134~1.612)
否					1.000
高脂血症
是	0.400	0.104	14.827	< 0.001	1.490(1.234~1.800)
否					1.000
吸烟
是	-0.196	0.119	2.722	0.099	0.822(0.651~1.038)
否					1.000
饮酒
是	0.093	0.115	0.661	0.416	1.098(0.876~1.376)
否					1.000
性别
女	-0.135	0.119	1.279	0.258	0.874(0.691~1.104)
男					1.000
城乡
市区	0.151	0.092	2.676	0.102	1.163(0.971~1.393)
县区					1.000
服用降压药
是	0.138	0.116	1.428	0.232	1.148(0.915~1.441)
否					1.000
服用降脂药
是	0.591	0.231	6.551	0.010	1.806(1.148~2.839)
否					1.000

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表 4 2018年唐山市市区研究对象IFG影响因素的非条件Logistic回归分析模型结果

Table 4. Unconditional Logistic regression analysis model results of factors affecting IFG of urban residents in Tangshan in 2018

自变量	β值	s_x	Wald χ²值	P值	OR (95% CI)值
年龄(岁)			63.698	< 0.001
18~					1.000
35~	1.160	0.549	4.474	0.034	3.191(1.089~9.352)
45~	1.636	0.525	9.701	0.002	5.134(1.834~14.374)
55~	2.186	0.519	17.753	< 0.001	8.900(3.219~24.603)
65~	2.685	0.528	25.849	< 0.001	14.654(5.206~41.250)
≥75	2.488	0.571	18.984	< 0.001	12.034(3.930~36.848)
BMI(kg/m²)			10.099	0.018
< 18.5					1.000
18.5~	-0.095	0.256	0.139	0.709	0.909(0.550~1.501)
24.0~	0.294	0.248	1.405	0.236	1.342(0.825~2.181)
≥28.0	0.431	0.278	2.406	0.121	1.538(0.893~2.651)
糖尿病家族史
有	0.292	0.222	1.732	< 0.188	1.339(0.867~2.068)
无					1.000
高血压
是	0.398	0.117	11.489	< 0.001	1.489(1.183~1.875)
否					1.000
高脂血症
是	0.322	0.121	7.051	0.008	1.380(1.088~1.751)
否					1.000
吸烟
是	-0.236	0.144	2.686	0.101	0.790(0.596~1.047)
否					1.000
饮酒
是	0.073	0.142	0.264	0.607	1.075(0.815~1.420)
否					1.000
性别
女	-0.249	0.169	2.172	0.141	0.780(0.560~1.086)
男					1.000
服用降压药
是	0.142	0.169	0.698	0.403	1.152(0.827~1.606)
否					1.000
服用降脂药
是	-0.471	0.551	0.731	0.392	0.624(0.212~1.837)
否					1.000

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表 5 2018年唐山市县区研究对象IFG影响因素的非条件Logistic回归分析模型结果

Table 5. Unconditional Logistic regression analysis model results of factors affecting IFG of rural residents in Tangshan in 2018

自变量	β值	s_x	Wald χ²值	P值	OR (95% CI)值
年龄(岁)			108.386	< 0.001
18~					1.000
35~	0.732	0.182	16.164	< 0.001	2.079(1.455~2.970)
45~	1.415	0.167	71.982	< 0.001	4.116(2.968~5.707)
55~	1.585	0.174	82.675	< 0.001	4.880(3.468~6.868)
65~	1.587	0.216	54.168	< 0.001	4.889(3.204~7.459)
≥75	0.799	0.398	4.027	0.045	2.223(1.019~4.853)
BMI(kg/m²)			30.363	< 0.001
< 18.5					1.000
18.5~	-0.589	0.276	4.534	0.033	0.555(0.323~0.954)
24.0~	-0.238	0.272	0.765	0.382	0.789(0.463~1.343)
≥28.0	0.173	0.279	0.386	0.534	1.189(0.689~2.053)
糖尿病家族史
有	0.471	0.188	6.282	0.012	1.602(1.108~2.316)
无					1.000
高血压
是	0.172	0.122	1.977	0.160	1.188(0.934~1.510)
否					1.000
高脂血症
是	0.617	0.122	25.618	< 0.001	1.854(1.460~2.355)
否					1.000
吸烟
是	-0.015	0.151	0.010	0.919	0.985(0.732~1.324)
否					1.000
饮酒
是	-0.013	0.151	0.007	0.933	0.987(0.735~1.326)
否					1.000
性别
女	0.058	0.124	0.220	0.639	1.060(0.832~1.350)
男					1.000
沿海
是	-0.762	0.124	37.674	< 0.001	0.467(0.366~0.595)
否					1.000
服用降压药
是	0.130	0.160	0.654	0.419	1.139(0.831~1.559)
否					1.000
服用降脂药
是	0.862	0.272	10.018	0.002	2.369(1.389~4.040)
否					1.000

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