南京市老年体检人群空腹血糖轨迹与新发心血管病的关联

陈荃; 杜金玲; 洪忻

doi:10.16462/j.cnki.zhjbkz.2024.03.005

南京市老年体检人群空腹血糖轨迹与新发心血管病的关联

doi: 10.16462/j.cnki.zhjbkz.2024.03.005

陈荃^{1, 2},
杜金玲²,
洪忻^{1, 2, ,}

1.
南京医科大学附属南京市疾病预防控制中心，南京 210003
2.
南京医科大学公共卫生学院，南京 211166

基金项目:

江苏省卫生健康委2022年度医学科研项目 M2022028

详细信息

通讯作者:
洪忻，E-mail: nj_hongxin@126.com

中图分类号: R181.1
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- 被引次数: 0
出版历程
- 收稿日期: 2023-07-04
- 修回日期: 2023-09-29
- 网络出版日期: 2024-04-08
- 刊出日期: 2024-03-10

Association between fasting blood glucose trajectories and new-onset cardiovascular diseases in the elderly health check-up population in Nanjing

CHEN Quan^{1, 2},
DU Jinling²,
HONG Xin^{1, 2
, ,}

1.
Nanjing Center for Disease Control and Prevention, Nanjing Medical University, Nanjing 210003, China
2.
School of Public Health, Nanjing Medical University, Nanjing 211166, China

Funds:

Jiangsu Provincial Health and Health Commission 2022 Medical Research Projects M2022028

More Information

Corresponding author: HONG Xin, E-mail: nj_hongxin@126.com

摘要

摘要: 目的探讨南京市老年人群(≥65岁)空腹血糖(fasting plasma glucose，FPG)轨迹和新发心血管病(cardiovascular disease，CVD)结局事件的关联。方法从南京市老年健康体检人群中选取符合纳入标准者作为研究对象，共计7 079人纳入研究队列，采用群组化轨迹模型(group-based trajectory modeling，GBTM)构建2018―2020年FPG指标(FPG取其对数使其服从正态分布)随年份变化的轨迹并分组，随访该人群2021年CVD的发病情况，应用Cox回归模型分析不同轨迹组和新发CVD的关联。结果该人群的FPG轨迹最终分为低水平组(5 635，79.6%)、中水平组(1 201，17.0%)和高水平组(243，3.4%)。随访期间共有CVD结局事件70例，其中低水平组、中水平组和高水平组新发病例数分别占该组人数的0.83%、1.42%、2.47%，发病率随着FPG轨迹水平升高而增加(趋势χ² =8.750, P=0.003)，差异有统计学意义(χ² =9.050, P=0.011)。Cox回归模型分析结果显示，高水平组的CVD发病风险是低水平组的2.96倍(95% CI：1.27~6.92)。结论老年人群较高水平的FPG轨迹和较高的CVD发病风险相关，FPG值偏高会增加CVD的发病风险，应及时干预，以实现早期预防CVD的目的。
- 老年人群 /
- 空腹血糖 /
- 轨迹 /
- 心血管病 /
- 队列研究
Abstract: Objective To investigate the association between fasting blood glucose trajectory and the incidence of cardiovascular disease among the elderly population aged 65 years and above in Nanjing. Methods A total of 7 079 participants were included from the Nanjing elderly health checkup cohort who met the inclusion criteria. The trajectory of fasting plasma glucose(FPG) index (FPG was taken as its logarithm to make it obey normal distribution) was constructed by group-based trajectory model (GBTM) over the years from 2018 to 2020. And we followed up the incidence of cardiovascular disease in 2021. A Cox regression model was used to analyze the association between distinct trajectory groups and the incidence of cardiovascular disease. Results The FPG trajectory was finally divided into low-level group (5 635, 79.6%), medium-level group (1 201, 17.0%) and high-level group (243, 3.4%). A total of 70 cases of cardiovascular disease were newly reported during the follow-up period, with the low, medium, and high level groups accounting for 0.83%, 1.42%, and 2.47% of the new cases in the group, respectively. The incidence of cardiovascular disease increased with increasing FPG levels (trend χ² =8.750, P=0.003), and the difference was statistically significant (χ² =9.050, P=0.011). The Cox regression model showed that the risk of cardiovascular disease in the high-level group was 2.96 times higher than that in the low-level group (95% CI: 1.27-6.92). Conclusions Long-term high levels of FPG increase the risk of cardiovascular disease in the elderly, so timely intervention and early prevention are warranted.
- Elderly population /
- Fasting plasma glucose /
- Trajectory /
- Cardiovascular disease /
- Cohort study

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图 1 研究对象纳入排除的流程图

Figure 1. Flowchart for inclusion and exclusion of participants

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图 2 3组FPG轨迹的拟合结果

Figure 2. Three groups of FPG trajectory fitting results

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表 1 研究对象的基线资料特征

Table 1. Characteristics of baseline information on the participants

变量Variable	总人群^① Total population^① (n=7 079)	变量Variable	总人群^① Total population^① (n=7 079)
年龄/岁Age/years	71.07±4.88	吸烟Smoking	1 795(25.36)
年龄组/岁Age group/years		饮酒Drinking	1 833(25.89)
65-79	6 571(92.82)	体育锻炼Physical activity	794(11.22)
≥80	508(7.18)	BMI/(kg·m^-2)	24.71±3.44
性别Gender		WC/cm	82.89±8.78
男Male	3 314(46.81)	SBP/mmHg	144.40±20.03
女Female	3 765(53.19)	DBP/mmHg	80.99±10.65
婚姻状况Marital status		FPG/(mmol·L^-1)	5.84±1.39
已婚Married	5 635(79.60)	TC/(mmol·L^-1)	5.06±0.97
未婚，离异或丧偶Divorced, widowed, or not married	1 444(20.40)	TG/(mmol·L^-1)	1.43±0.99
文化程度Education		LDL-C/(mmol·L^-1)	1.54±0.44
高中以下High school below	7 008(99.00)	HDL-C/(mmol·L^-1)	2.80±0.75
高中及以上High school and above	71(1.00)
注：WC，腰围；SBP，收缩压；DBP，舒张压；TC，总胆固醇；TG，三酰甘油；LDL-C，低密度脂蛋白胆固醇；HDL-C，高密度脂蛋白胆固醇。 ①以人数(占比/%)或x±s表示。 Note: WC, waist circumference; SBP, systolic blood pressure; DBP, diastolic blood pressure; TC, total cholesterol; TG, triglycerides; LDL-C, low-density lipoprotein cholesterol; HDL-C, high-density lipoprotein cholesterol. ①Number of people (proportion/%) or x±s.

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表 2 空腹血糖指标对数值轨迹模型分组依据

Table 2. Basis for grouping of fasting blood glucose indicators into numerical trajectory models

分组数量Number of subgroups	BIC	2△(BICij)	分组数量Number of subgroups	BIC	2△(BICij)
1	21 456.37	(基线)(Baseline)	4	26 975.65	828.82
2	25 659.30	8 405.86	5	27 285.32	619.34
3	26 561.24	1 803.88	6	27 597.30	623.96
注：BIC，贝叶斯信息标准；2△(BICij)，2个比较模型BIC差值的2倍，近似等于贝叶斯因子对数值。 Note: BIC, Bayesian information criterion; 2△(BICij), the value is approximately equal to 2 times of the difference of BIC between the 2 compared models, approximately equal to the value of Bayesian factor logarithm.

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表 3 不同轨迹组的相关参数

Table 3. Relevant parameters for different trajectory groups

分组 Groups	参数 Parameters	估计值 Estimate	s_x	t值value	P值value
低水平组Low-level group	截距Intercept	0.741	0.003	214.445	< 0.001
	线性项Linear	-0.017	0.004	-4.268	< 0.001
	二次项Quadratic	0.004	0.001	3.974	< 0.001
中水平组Middle-level group	截距Intercept	0.871	0.008	103.662	< 0.001
	线性项Linear	-0.037	0.009	-4.079	< 0.001
	二次项Quadratic	0.012	0.002	5.167	< 0.001
高水平组High-level group	截距Intercept	0.892	0.020	44.525	< 0.001
	线性项Linear	0.120	0.025	4.752	< 0.001
	二次项Quadratic	-0.029	0.006	-4.584	< 0.001

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表 4 不同空腹血糖轨迹组研究对象的基线资料

Table 4. Baseline information of participants among different fasting blood glucose trajectory groups

变量Variable	空腹血糖轨迹分组 ^① Fasting blood glucose trajectory groups ^①			χ²/F值value	P值 value
变量Variable	低水平组 Low-level group	中水平组 Medium-level group	高水平组 High-level group	χ²/F值value	P值 value
人数Number of population	5 635(79.60)	1 201(16.97)	243(3.43)
年龄/岁Age/years	71.11±4.94	70.86±4.65	71.23±4.58	1.408	0.245
性别Gender				53.798	< 0.001
女性Female	2 762(49.02)	461(38.38)	91(37.45)
男性Male	2 873(50.98)	740(61.62)	152(62.55)
婚姻状况Marital status				9.277	0.010
已婚Married	4 527(80.34)	920(76.60)	188(77.37)
未婚，离异或丧偶Divorced, widowed, or not married	1 108(19.66)	281(23.40)	55(22.63)
文化程度Education				4.329	0.363
高中以下High school below	5 582(99.06)	1 186(98.75)	240(98.77)
高中及以上High school and above	53(0.94)	15(1.25)	3(1.23)
吸烟Smoking	1 533(27.21)	219(18.23)	43(17.70)	51.680	< 0.001
饮酒Drinking	1 530(27.15)	260(21.65)	47(19.34)	22.058	< 0.001
体育锻炼Physical activity	593(10.52)	171(14.24)	30(12.35)	14.040	0.001
BMI/(kg·m^-2)	24.41±3.40	25.87±3.31	25.92±3.62	108.152	< 0.001
WC/cm	82.07±8.68	86.06±8.99	86.47±9.29	123.369	< 0.001
SBP/mmHg	143.49±20.11	148.05±19.32	146.63±22.20	27.199	< 0.001
DBP/mmHg	80.71±10.93	81.86±9.98	82.72±10.74	8.969	< 0.001
FPG/(mmol·L^-1)	5.49±8.45	7.18±1.30	9.99±2.99	60.948	< 0.001
TC/(mmol·L^-1)	5.35±10.97	5.65±19.30	5.27±1.07	0.290	0.748
TG/(mmol·L^-1)	1.37±1.24	1.73±1.31	1.98±2.41	58.231	< 0.001
LDL-C/(mmol·L^-1)	2.87±4.99	2.86±0.75	2.94±0.80	0.030	0.970
HDL-C/(mmol·L^-1)	1.66±4.11	1.44±0.42	1.45±0.37	1.997	0.136
新发CVD病例New cases of CVD	47(0.83)	17(1.42)	6(2.47)	9.050	0.011
注：WC，腰围；SBP，收缩压；DBP，舒张压；TC，总胆固醇；TG，三酰甘油；LDL-C，低密度脂蛋白胆固醇；HDL-C，高密度脂蛋白胆固醇; CVD, 心血管病。 ①以人数(占比/%)或x±s表示。 Note: WC, waist circumference; SBP, systolic blood pressure; DBP, diastolic blood pressure; TC, total cholesterol; TG, triglycerides; LDL-C, low-density lipoprotein cholesterol; HDL-C, high-density lipoprotein cholesterol; CVD, cardiovascular disease. ①Number of people (proportion/%) or x±s.

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表 5 不同空腹血糖轨迹组发生心血管病的Cox回归分析

Table 5. Cox regression analysis of the occurrence of cardiovascular disease among different fasting blood glucose trajectory groups

模型Model	类别Category	β值 value	s_x	Wald χ² 值value	HR值value (95% CI)	P值 value
模型1 Model 1	低水平组Low-level group				1.000
	中水平组Medium-level group	0.529	0.283	3.492	1.697(0.975~2.955)	0.062
	高水平组High-level group	1.085	0.434	6.267	2.960(1.266~6.924)	0.012
模型2 Model 2	低水平组Low-level group				1.000
	中水平组Medium-level group	0.488	0.284	2.944	1.629(0.933~2.845)	0.086
	高水平组High-level group	1.020	0.434	5.516	2.774(1.184~6.501)	0.019
模型3 Model 3	低水平组Low-level group				1.000
	中水平组Medium-level group	0.430	0.291	2.178	1.537(0.868~2.722)	0.140
	高水平组High-level group	0.914	0.443	4.262	2.495(1.047~5.945)	0.039
注：模型1未经调整；模型2在模型1的基础上调整了年龄和性别；模型3在模型2的基础上调整了基线BMI、腰围、收缩压、舒张压、总胆固醇、三酰甘油、低密度脂蛋白胆固醇和高密度脂蛋白胆固醇指标平均值。 Note: Model 1 unadjusted; model 2 adjusting for age and gender based on model 1; Model 3 adjusting for baseline mean BMI, waist circumference, systolic blood pressure, diastolic blood pressure, total cholesterol, triglycerides, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol.

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