BMI水平及动态变化与高血压、糖尿病、血脂异常共病发生风险的前瞻性队列研究

周婕; 吴延莉; 王艺颖; 余丽莎; 张骥; 余杨文; 李雪娇; 龙梦雅; 刘涛

doi:10.16462/j.cnki.zhjbkz.2023.12.010

BMI水平及动态变化与高血压、糖尿病、血脂异常共病发生风险的前瞻性队列研究

doi: 10.16462/j.cnki.zhjbkz.2023.12.010

1.
贵州省疾病预防控制中心，贵阳 550004
2.
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，贵阳 550025

基金项目:

贵州省科技计划 Guizhou Science Support [2018]2819

详细信息

通讯作者:
刘涛，E-mail：543820987@qq.com

中图分类号: R181.2+3
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出版历程
- 收稿日期: 2022-12-02
- 修回日期: 2023-04-28
- 刊出日期: 2023-12-10

Prospective cohort study on the association of body mass index level and its dynamic changes on risks of incident comorbidity among hypertension, diabetes and dyslipidemia

1.
Guizhou Center for Disease Control and Prevention, Guiyang 550004, China
2.
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 Science and Technology Plan Project Guizhou Science Support [2018]2819

More Information

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

摘要

摘要: 目的探讨体质指数(body mass index, BMI)水平及动态变化与高血压、糖尿病、血脂异常共病发生的风险, 为慢性非传染性疾病(慢性病)共病防控提供参考依据。方法数据来自2010年建立的贵州省自然人群队列, 采用分层随机整群抽样的方法, 对12个县(市、区)的48个乡镇共9 280人进行调查。2016-2020年, 完成了随访调查。排除基线高血压、糖尿病、血脂异常共病和随访时数据缺失的调查对象, 最终4 688例进入分析。采用Cox比例风险回归模型分析BMI值、不同BMI变化值及BMI变化情况(保持正常BMI、持续超重肥胖、正常BMI变为超重肥胖、超重肥胖变为正常BMI)与高血压、糖尿病、血脂异常共病之间的关系, 计算HR值和95% CI。结果不同地区、性别、年龄、民族、教育水平、吸烟、饮酒、膳食得分人群高血压、糖尿病、血脂异常共病差异均有统计学意义(均P < 0.05)。共病发生风险随着BMI值的升高而增加(HR=1.046, 95% CI: 1.031~1.061), 且超重(HR=1.293, 95% CI: 1.124~1.487)、肥胖(HR=2.130, 95% CI: 1.706~2.658)人群发生风险高于BMI正常人群。BMI减少1.0 kg/m²以下时共病发生风险降低21.3%, BMI增加5.0 kg/m²及以上时, 共病发生风险增加42.9%(HR=1.429, 95% CI: 1.108~1.845)。持续超重肥胖(HR=2.301, 95% CI: 1.962~2.697)、正常BMI变为超重肥胖(HR=1.698, 95% CI: 1.451~1.987)人群共病发生风险较保持正常BMI的人群分别增加2.301倍、1.698倍。结论 BMI水平及动态变化与高血压、糖尿病、血脂异常共病密切相关, 控制和降低BMI至正常水平是预防3种疾病共病必要和有效的方法。
- 体质指数 /
- 共病 /
- 发生风险 /
- 前瞻性研究
Abstract: Objective To investigate body mass index (BMI) level and its dynamic changes and the risk of comorbidity of hypertension, diabetes and dyslipidemia, and provide the reference for prevention and control of chronic disease comorbidity. Methods The data used in the study were from the natural cohort of Guizhou province established in 2010.In order to obtain the cohort, stratified random cluster sampling method was employed to investigate a total of 9 280 people from 48 towns in 12 counties (cities, districts).A follow-up survey was completed from 2016 to 2020.The subjects with baseline hypertension, diabetes, dyslipidemia comorbidities and with incomplete data during follow-up were excluded.A total of 4 688 patients were ultimately included into this study.Cox proportional hazard regression model was used to analyze the relationship between BMI values, different change values of BMI and changes in BMI (maintaining normal BMI, continuing overweight and obesity, changing from the normal BMI to the overweight and obesity, changing from the overweight and obesity to the normal BMI) and hypertension, diabetes, dyslipidemia comorbidity.Risk ratio (HR) and 95%CI were calculated. Results Among the groups distinguished by region, gender, age, ethnic group, education level, smoking, drinking and dietary score, differences in comorbidity of hypertension, diabetes and dyslipidemia were significant statistically (all P < 0.05).The risk of comorbidity increased with the increase of BMI value (HR=1.046, 95% CI: 1.031-1.061).Moreover, the risk of comorbidity among the groups of overweight (HR=1.293, 95% CI: 1.124-1.487) and obesity (HR=2.130, 95% CI: 1.706-2.658) was higher than that among the groups having normal BMIs.The risk for the group with BMIs lowered by 1.0 kg/m² or less to undergo comorbidity was decreased by 21.3%, whereas the risk for the group with BMI increased by 5.0 kg/m² or more to undergo comorbidity was increased by 42.9%(HR=1.429, 95% CI: 1.108-1.845).For the patients who kept overweight (HR=2.301, 95% CI: 1.962-2.697) and the patients who had normal BMI but became overweight (HR=1.698, 95% CI: 1.451-1.987), the risks of comorbidity were increased 2.301 times and 1.698 times, respectively, compared with those with normal BMI. Conclusions BMI level and its dynamic changes are closely related with comorbidity of hypertension, diabetes and dyslipidemia.Controlling and reducing BMI to normal level is a necessary and effective method to prevent comorbidity of the three diseases.
- Body mass index /
- Comorbidity /
- Occurrence risk /
- Prospective study

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图 1 不同BMI变化情况与高血压、糖尿病、血脂异常共病发生风险

Figure 1. Risk of comorbidities of hypertension, diabetes and dyslipidemia with different BMI changes

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表 1 不同人口学特征和生活方式人群分布及共病情况

Table 1. Distribution and comorbidity of population with different demographic characteristics and lifestyle

特征 Characteristics	人数^① Number of people ^①	任意2种疾病共病 ^① Comorbidities of any two diseases ^①	3种疾病共病 ^① Comorbidities of three diseases ^①	合计共病 ^① Total comorbidity ^①	χ²值 value	P值 value
合计Total	4 688 (100.0)	940 (20.1)	179 (3.8)	1 119 (23.9)
地区Region					11.898	0.001
城市City	1 556 (33.2)	266 (17.1)	58 (3.7)	324 (20.8)
农村Village	3 132 (66.8)	674 (21.5)	121 (3.9)	795 (25.4)
性别Gender					16.412	＜0.001
男Male	2 162 (46.1)	489 (22.6)	86 (4.0)	575 (26.6)
女Female	2 526 (53.9)	451 (17.9)	93 (3.7)	544 (21.5)
年龄段/岁Age group/year					106.028	＜0.001
18~＜45	2 668 (56.9)	415 (15.6)	79 (3.0)	494 (18.5)
45~＜60	1 370 (29.2)	345 (25.2)	53 (3.9)	398 (29.1)
≥60	650 (13.9)	180 (27.7)	47 (7.2)	227 (34.9)
民族Ethnicity					9.536	0.002
汉族Han	2 836 (60.5)	590 (20.8)	131 (4.6)	721 (25.4)
少数民族Minority	1 852 (39.5)	350 (18.9)	48 (2.6)	398 (21.5)
婚姻Married					2.278	0.131
在婚Married	3 816 (81.4)	783 (20.5)	145 (3.8)	928 (24.3)
非在婚Unmarried	872 (18.6)	157 (18.0)	34 (3.9)	191 (21.9)
教育水平/年Education level /year					26.300	＜0.001
< 9	2 600 (55.5)	568 (21.8)	127 (4.9)	695 (26.7)
≥9	2 088 (44.5)	372 (17.8)	52 (2.5)	424 (20.3)
吸烟Smoking					28.872	＜0.001
现在吸烟Current smoking	1 298 (27.7)	319 (24.6)	61 (4.7)	380 (29.3)
现在不吸烟Not current smoking	3 390 (72.3)	621 (18.3)	118 (3.5)	739 (21.8)
饮酒Drinking					16.302	＜0.001
从不饮酒Never drinking	3 180 (67.8)	596 (18.7)	108 (3.4)	704 (22.1)
饮酒Drinking	1 508 (32.2)	344 (22.8)	71 (4.7)	415 (27.5)
膳食得分/分Diet score/score					5.972	0.050
0~＜2	1 646 (35.9)	357 (21.7)	64 (3.9)	421 (25.6)
2~＜4	2 677 (58.3)	521 (19.5)	104 (3.9)	625 (23.3)
≥4	268 (5.8)	46 (17.2)	6 (2.2)	52 (19.4)
锻炼Exercise					1.306	0.253
经常锻炼Exercise regularly	267 (5.7)	40 (15.0)	16 (6.0)	56 (21.0)
不经常锻炼Not exercise regularly	4 421 (94.3)	900 (20.4)	163 (3.7)	1 063 (24.0)
睡眠时间/(h·d^-1) Sleep duration/(h·d^-1)					16.053	＜0.001
＜7	577 (12.3)	139 (24.1)	36 (6.2)	175 (30.3)
7~＜9	2 991 (63.8)	574 (19.2)	101 (3.4)	675 (22.6)
≥9	1 120 (23.9)	227 (20.3)	42 (3.8)	269 (24.0)
注：①以[人数(占比/%)]表示。 Note: ① [Number of people (proportion /%)].

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表 2 BMI水平与高血压、糖尿病、血脂异常共病发生的HR值(95% CI)

Table 2. HR value of BMI level and comorbidities of hypertension, diabetes and dyslipidemia (95% CI)

BMI水平 BMI level	共病患者 Comorbidity	发病密度/千人年^-1 Incidence density/per thousand years^-1	HR值value (95% CI) ^①	P值 value	HR值value (95% CI) ^②	P值 value	HR值value (95% CI) ^③	P值 value
合计共病Total comorbidity
BMI值value	1 119	33.70	1.052 (1.037~1.067)	＜0.001	1.045 (1.030~1.061)	＜0.001	1.046 (1.031~1.061)	＜0.001
BMI分级/(kg·m^-2) BMI classification/(kg·m^-2)
消瘦Asarcia(＜18.5)	58	29.17	0.944 (0.722~1.234)	0.670	0.957 (0.732~1.251)	0.747	0.965 (0.734~1.270)	0.801
正常Normal(18.5~＜24.0)	675	30.44	1.000		1.000		1.000
超重Overweight(24.0~＜28.0)	295	39.93	1.295 (1.129~1.485)	＜0.001	1.289 (1.124~1.478)	＜0.001	1.293 (1.124~1.487)	＜0.001
肥胖Obesity(≥28.0)	91	55.18	2.093 (1.681~2.606)	＜0.001	2.069 (1.661~2.577)	＜0.001	2.130 (1.706~2.658)	＜0.001
任意2种疾病共病Comorbidities of any two diseases
BMI值value	940	28.31	1.048 (1.032~1.065)	＜0.001	1.042 (1.026~1.059)	＜0.001	1.043 (1.026~1.060)	＜0.001
BMI分级/(kg·m^-2) BMI classification/(kg·m^-2)
消瘦Asarcia(＜18.5)	49	24.65	0.943 (0.705~1.263)	0.696	0.959 (0.716~1.284)	0.779	0.983 (0.731~1.323)	0.912
正常Normal(18.5~＜24.0)	571	25.75	1.000		1.000		1.000
超重Overweight(24.0~＜28.0)	252	34.11	1.307 (1.127~1.516)	＜0.001	1.301 (1.121~1.508)	＜0.001	1.307 (1.124~1.521)	0.001
肥胖Obesity(≥28.0)	68	41.23	1.856 (1.443~2.387)	＜0.001	1.837 (1.428~2.364)	＜0.001	1.876 (1.455~2.419)	＜0.001
3种疾病共病Comorbidities of three diseases
BMI值value	179	5.39	1.065 (1.033~1.099)	＜0.001	1.060 (1.027~1.094)	＜0.001	1.058 (1.025~1.092)	0.001
BMI分级/(kg·m^-2) BMI classification/(kg·m^-2)
消瘦Asarcia(＜18.5)	9	4.53	0.947 (0.479~1.872)	0.876	0.943 (0.477~1.865)	0.866	0.870 (0.421~1.796)	0.707
正常Normal(18.5~＜24.0)	104	4.69	1.000		1.000		1.000
超重Overweight(24.0~＜28.0)	43	5.82	1.230 (0.862~1.755)	0.253	1.222 (0.856~1.743)	0.270	1.212 (0.842~1.744)	0.300
肥胖Obesity(≥28.0)	23	13.95	3.369 (2.143~5.297)	＜0.001	3.298 (2.096~5.191)	＜0.001	3.538 (2.232~5.609)	＜0.001
注：BMI: 体质指数。 ①为模型1：未调整任何因素; ②为模型2：调整性别和年龄(连续变量); ③为模型3：调整性别、年龄(连续变量)、地区、民族、现在吸烟、从不饮酒、经常锻炼、膳食得分和睡眠时间等因素。 Note: BMI, body mass index. ① Model 1: no factors are adjusted; ② Model 2: adjusting for gender and age (continuous variables); ③ Model 3: adjusting for gender, age (continuous variable), region, ethnicity, current smoking, never drinking, regular exercise, diet score, and sleep duration.

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表 3 BMI动态变化与高血压、糖尿病、血脂异常共病发生的HR值(95% CI)

Table 3. HR value of BMI dynamic change and comorbidities of hypertension, diabetes and dyslipidemia (95% CI)

BMI动态变化 BMI dynamic change	共病患者 Comorbidity	发病密度/千人年^-1 Incidence density /per thousand years^-1	HR值value (95% CI) ^①	P值 value	HR值value (95% CI) ^②	P值 value	HR值value (95% CI) ^③	P值 value
合计共病Total comorbidity
BMI变化值分组Group of BMI change value
1	308	30.22	0.800 (0.673~0.951)	0.012	0.765 (0.643~0.909)	0.002	0.787 (0.661~0.937)	0.007
2	221	27.96	1.000		1.000		1.000
3	259	32.51	1.051 (0.891~1.240)	0.558	1.069 (0.906~1.262)	0.427	1.072 (0.907~1.266)	0.417
4	163	40.51	1.128 (0.933~1.364)	0.215	1.187 (0.981~1.436)	0.077	1.194 (0.983~1.451)	0.074
5	77	46.36	1.340 (1.044~1.721)	0.022	1.398 (1.089~1.796)	0.009	1.429 (1.108~1.845)	0.006
6	91	62.58	1.780 (1.408~2.250)	＜0.001	1.953 (1.544~2.470)	＜0.001	2.002 (1.572~2.551)	＜0.001
P_趋势 P_trend				＜0.001		＜0.001		＜0.001
任意2种疾病共病Comorbidities of any two diseases
BMI变化值分组Group of BMI change value
1	270	26.50	0.761 (0.631~0.918)	0.004	0.728 (0.604~0.879)	0.001	0.743 (0.615~0.897)	0.002
2	185	23.40	1.000		1.000		1.000
3	224	28.12	1.037 (0.868~1.238)	0.690	1.055 (0.883~1.259)	0.556	1.052 (0.880~1.258)	0.576
4	134	33.30	1.054 (0.857~1.297)	0.620	1.107 (0.899~1.362)	0.339	1.112 (0.899~1.374)	0.328
5	60	36.13	1.187 (0.897~1.571)	0.230	1.236 (0.934~1.636)	0.138	1.266 (0.953~1.682)	0.104
6	67	46.07	1.491 (1.140~1.949)	0.004	1.636 (1.251~2.140)	＜0.001	1.681 (1.275~2.217)	＜0.001
P_趋势 P_trend				0.001		＜0.001		＜0.001
3种疾病共病Comorbidities of three diseases
BMI变化值分组Group of BMI change value
1	38	3.73	1.077 (0.682~1.699)	0.751	1.025 (0.649~1.618)	0.916	1.110 (0.699~1.761)	0.658
2	36	4.55	1.000		1.000		1.000
3	35	4.39	1.150 (0.727~1.821)	0.551	1.174 (0.742~1.859)	0.494	1.205 (0.758~1.915)	0.430
4	29	7.21	1.657 (1.021~2.688)	0.041	1.766 (1.088~2.866)	0.021	1.817 (1.101~2.998)	0.019
5	17	10.24	2.441 (1.376~4.328)	0.002	2.568 (1.448~4.556)	0.001	2.634 (1.457~4.764)	0.001
6	24	16.50	3.851 (2.307~6.429)	＜0.001	4.214 (2.520~7.045)	＜0.001	4.207 (2.470~7.164)	＜0.001
P_趋势 P_trend				＜0.001		＜0.001		＜0.001
注：BMI变化值分组, 1组为BMI变化＜-1.0 kg/m²、2组为-1.0 kg/m²≤BMI变化＜1.0 kg/m²、3组为1.0 kg/m²≤BMI变化＜3.0 kg/m²、4组为3.0 kg/m²≤BMI变化＜5.0 kg/m²、5组为5.0 kg/m²≤BMI变化＜7.0 kg/m²、6组为BMI变化≥7.0 kg/m²。 ①为模型1：未调整任何因素; ②为模型2：调整性别和年龄(连续变量); ③为模型3：调整性别、年龄(连续变量)、地区、民族、现在吸烟、从不饮酒、经常锻炼、膳食得分和睡眠时间等因素。 Note: group of BMI change value, 1 group is BMI change＜-1.0 kg/m², 2 group is -1.0 kg/m²≤BMI change＜1.0 kg/m², 3 group is 1.0 kg/m²≤BMI change＜3.0 kg/m², 4 group is 3.0 kg/m²≤BMI change＜5.0 kg/m², 5 group is 5.0 kg/m²≤BMI change＜7.0 kg/m², 6 group is BMI change≥7.0 kg/m². ① Model 1: no factors are adjusted; ② Model 2: adjust gender and age (continuous variables); ③ Model 3, factors such as gender, age (continuous variable), region, ethnicity, current smoking, never drinking, regular exercise, diet score and sleep time were adjusted.

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参考文献(23)

[1]	World Health Organization. Primary health cared-now more than ever[J]. New York: World Health Report, 2008: 148.
[2]	Hu XL, Huang J, Lv YQ, et al. Status of prevalence study on multimorbidity of chronic disease in China: systematic review[J]. Geriatr Gerontol Int, 2015, 15(1): 1-10. DOI: 10.1111/ggi.12340.
[3]	Violan C, Foguet-Boreu Q, Flores-Mateo G, et al. Prevalence, determinants and patterns of multimorbidity in primary care: a systematic review of observational studies[J]. PLoS One, 2014, 9(7): e102149. DOI: 10.1371/journal.pone.0102149.
[4]	Boult C, Wieland GD. Comprehensive primary care for older patients with multiple chronic conditions: "Nobody rushes You through"[J]. JAMA, 2010, 304(17): 1936-1943. DOI: 10.1001/jama.2010.1623.
[5]	Barnett K, Mercer SW, Norbury M, et al. Epidemiology of multimorbidity and implications for health care, research, and medical education: a cross-sectional study[J]. Lancet, 2012, 380(9836): 37-43. DOI: 10.1016/S0140-6736(12)60240-2.
[6]	Kuwabara M, Kuwabara R, Niwa K, et al. Different risk for hypertension, diabetes, dyslipidemia, and hyperuricemia according to level of body mass index in Japanese and American subjects[J]. Nutrients, 2018, 10(8): 1011. DOI: 10.3390/nu10081011.
[7]	Global Burden of Disease Study 2015. Global Burden of Disease Study 2015 (GBD 2015) Obesity and Overweight Prevalence 1980-2015. Seattle, United States: Institute for Health Metrics and Evaluation (IHME). 2017.
[8]	Hu FF, Xu LZ, Zhou JL, et al. Association between overweight, obesity and the prevalence of multimorbidity among the elderly: evidence from a cross-sectional analysis in Shandong, China[J]. Int J Environ Res Public Health, 2020, 17(22): 8355. DOI: 10.3390/ijerph17228355.
[9]	Lebenbaum M, Zaric GS, Thind A, et al. Trends in obesity and multimorbidity in Canada[J]. Prev Med, 2018, 116: 173-179. DOI: 10.1016/j.ypmed.2018.08.025.
[10]	中国疾病预防控制中心, 中国疾病预防控制中心慢性非传染性疾病预防控制中心. 中国慢性病及危险因素监测报告: 2018[M]. 北京: 人民卫生出版社, 2021: 19-22. Chinese Center for Disease Control and Prevention, Chinese Center for Chronic Noncommunicable Disease Control and Prevention. Monitoring report of chronic diseases and risk factors in China: 2018[M]. Beijing: People's Medical Publishing House, 2021: 19-22.
[11]	中国高血压防治指南修订委员会, 高血压联盟(中国), 中华医学会心血管病学分会, 等. 中国高血压防治指南(2018年修订版)[J]. 中国心血管杂志, 2019, 24 (1): 24-56. DOI: 10.3969/j.issn.1007-5410.2019.01.002. Chinese Hypertension Prevention Guidelines Revision Committee, Hypertension Alliance (China), Chinese Medical Association Branch of Cardiology, et al. Chinese hypertension pevention guidelines (2018 revision)[J]. Chin J Cardiovasc Med, 2019, 24 (1): 24-56. DOI: 10.3969/j.issn.1007-5410.2019.01.002.
[12]	中华医学会糖尿病学分会. 中国2型糖尿病防治指南(2017年版)[J]. 中国实用内科杂志, 2018, 38(4): 292-344. DOI: 10.19538/j.nk2018040108. Diabetes Branch of Chinese Medical Association. Guidelines for prevention and treatment of type 2 diabetes in China (2017 edition)[J]. Chin J Pract Intern Med, 2018, 38(4): 292-344. DOI: 10.19538/j.nk2018040108.
[13]	中国成人血脂异常防治指南修订联合委员会. 中国成人血脂异常防治指南(2016年修订版)[J]. 中国循环杂志, 2016, 31(10): 937-953. DOI: 10.3969/j.issn.1000-3614.2016.10.001. Joint Committee for Revision of Guidelines for the Prevention and Treatment of Adult Dyslipidemia in China. Guidelines for prevention and treatment of dyslipidemia in adults in China (revised in 2016)[J]. Chin Circ J, 2016, 31(10): 937-953. DOI: 10.3969/j.issn.1000-3614.2016.10.001.
[14]	中华人民共和国卫生部疾病控制司. 中国成人超重和肥胖症预防控制指南[M]. 北京: 人民卫生出版社, 2006: 2-4. Department of Disease Control, Ministry of Health of the People's Republic of China. Guidelines for adult overweight and obesity prevention and control in China[M]. Beijing: People's Medical Publishing House, 2006: 2-4.
[15]	Vaněčková I, Maletínská L, Behuliak M, et al. Obesity-related hypertension: possible pathophysiological mechanisms[J]. J Endocrinol, 2014, 223(3): R63-R78. DOI: 10.1530/JOE-14-0368.
[16]	Matsuzawa Y, Funahashi T, Nakamura T. The concept of metabolic syndrome: contribution of visceral fat accumulation and its molecular mechanism[J]. J Atheroscler Thromb, 2011, 18(8): 629-639. DOI: 10.5551/jat.7922.
[17]	Gao Y, Ping ZG, Pei XT, et al. Multi-correspondence analysis of the status and related factors of chronic diseases multimorbidity in middle-aged and elderly people in China in 2009[J]. J Hyg Res, 2020, 49(5): 844-849. DOI: 10.19813/j.cnki.weishengyanjiu.2020.05.026.
[18]	Chen Y, Wang YY, Xu KL, et al. Adiposity and long-term adiposity change are associated with incident diabetes: a prospective cohort study in southwest China[J]. Int J Environ Res Public Health, 2021, 18(21): 11481. DOI: 10.3390/ijerph182111481.
[19]	Liu RR, Mi BB, Zhao YL, et al. Long-term body mass trajectories and hypertension by sex among Chinese adults: a 24-year open cohort study[J]. Sci Rep, 2021, 11(1): 12915. DOI: 10.1038/s41598-021-92319-4.
[20]	Liu M, Wang JH, Zeng J, et al. Association of NAFLD with diabetes and the impact of BMI changes: a 5-year cohort study based on 18, 507 elderly[J]. J Clin Endocrinol Metab, 2017, 102(4): 1309-1316. DOI: 10.1210/jc.2016-3440.
[21]	Xu JH, Zhang R, Guo RR, et al. Trajectories of body mass index and risk of incident hypertension among a normal body mass index population: a prospective cohort study[J]. J Clinical Hypertension, 2021, 23(6): 1212-1220. DOI: 10.1111/jch.14241.
[22]	Ren Q, Su C, Wang H, et al. Change in body mass index and its impact on incidence of hypertension in 18-65-year-old chinese Adults[J]. Int J Environ Res Public Heslth, 2016, 13(3).
[23]	Wing RR, Lang W, Wadden TA, et al. Benefits of modest weight loss in improving cardiovascular risk factors in overweight and obese individuals with type 2 diabetes[J]. Diabetes Care, 2011, 34(7): 1481-1486. DOI: 10.2337/dc10-2415.