Long-Term Body Mass Index Variability, Weight Change Slope, and Risk of Cardiovascular Outcomes: 7-Year Prospective Study in Chinese Hypertensive ...
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Research Article
Obes Facts 2021;14:442–449 Received: April 6, 2020
Accepted: October 14, 2020
DOI: 10.1159/000512317 Published online: August 30, 2021
Long-Term Body Mass Index Variability, Weight
Change Slope, and Risk of Cardiovascular
Outcomes: 7-Year Prospective Study in Chinese
Hypertensive Subjects
Zefeng Cai a Weiqiang Wu b Zekai Chen a Wei Fang a Weijian Li a
Guanzhi Chen c Zhichao Chen b Shouling Wu d Youren Chen b
a Shantou University Medical College, Shantou, China; b Department of Cardiology, Second Affiliated Hospital of
Shantou University Medical College, Shantou, China; c China Medical University, Shenyang, China; d Department of
Cardiology, Kailuan General Hospital, Tangshan, China
Keywords CVD, stroke, and MI in the highest tertile were 1.21 (95% CI
Body mass index · Variability · Weight change slope · 1.05–1.39), 1.21 (95% CI 1.04–1.38), and 1.20 (95% CI 0.88–
Hypertension · Cardiovascular outcomes 1.62), respectively. Subgroup analysis showed that the HR
values for CVD in tertile 3 were 1.71 (95% CI 1.06–2.75) and
0.98 (95% CI 0.61–1.58) in the positive and the negative
Abstract weight change subjects, respectively. Conclusions: Higher
Background: The relationship between long-term body BMI variability was associated with increased risk of CVD in
mass index (BMI) variability, weight change slope, and risk of hypertensive subjects with weight gain but not in those with
cardiovascular outcomes in Chinese hypertensive patients weight loss, independent of traditional cardiovascular risk
has not been fully elucidated. Methods: A total of 20,737 pa- factors. © 2021 The Author(s)
tients with hypertension and three BMI measurements be- Published by S. Karger AG, Basel
tween 2006 and 2011 were included. Average real variability
(ARV) was used to evaluate variability, and the subjects were
divided into three groups: tertile 1 with BMI_ARV ≤0.86; ter- Introduction
tile 2 with 0.86 < BMI_ARV ≤ 1.60; and tertile 3 with BMI_ARV
>1.60. Cox proportional-hazards models were used to ana- The prevalence of overweight and obesity among
lyze the risk of cardiovascular and cerebrovascular diseases adults continues to increase. In 2015, the obese or over-
(CVD) in each group. Results: There were 1,352 cases of CVD weight population reached 2.2 billion, accounting for
during an average follow-up of 6.62 years. The 7-year cumu- 30.1% of the population worldwide [1]. The increasing
lative incidence rates of CVD, stroke, and myocardial infarc- prevalence of obesity has been associated with corre-
tion (MI) in tertile 3 were 7.53, 6.13, and 1.56%, respectively.
After adjustment for average BMI, weight change slope, and
other traditional risk factors, the hazard ratio (HR) values for Z. Cai and W. Wu contributed equally to this work.
karger@karger.com © 2021 The Author(s) Correspondence to:
www.karger.com/ofa Published by S. Karger AG, Basel Youren Chen, 13902779840 @ 139.com
This article is licensed under the Creative Commons Attribution-
NonCommercial-NoDerivatives 4.0 International License (CC BY-
NC-ND) (http://www.karger.com/Services/OpenAccessLicense).
Usage and distribution for commercial purposes as well as any dis-
tribution of modified material requires written permission.sponding increases in the prevalence of hypertension, di- Staff members of the Kailuan Group were included as subjects
abetes, and cardiovascular and cerebrovascular diseases if they met the following criteria: (a) participated in three physical
examinations between 2006 and 2007, 2008 and 2009, and 2010
(CVD) [2, 3]. In 2017, the number of patients with CVD and 2011, and (b) had hypertension [14] (defined as [1] systolic
reached 485 million worldwide, which resulted in 17.8 blood pressure ≥140 mm Hg and/or diastolic blood pressure ≥90
million deaths and placed a heavy burden on the global mm Hg, or [2] systolic blood pressureTable 1. Baseline parameters of participants with hypertension in 2006 Variable Tertile 1 Tertile 2 Tertile 3 p value Subjects, n 6,848 6,912 6,977 – Age, years 52.58±10.80 53.22±10.89 53.51±11.46
Table 2. Hazard ratios and 95% confidence intervals of CVD
Events, n Per 1,000 Model 1 Model 2
person-years
CVD
Tertile 1 386 8.44 1 1
Tertile 2 464 10.14 1.20 (1.05–1.38) 1.15 (1.00–1.33)
Tertile 3 502 10.96 1.26 (1.10–1.44) 1.21 (1.05–1.39)
p value for trendTable 3. Baseline parameters of the participants with different weight change slopes in 2006
Variable Weight change Weight change p value
slope ≤0 slope >0
Subjects, n 11,047 9,690 –
mBMI, kg/m2 25.87±3.05 25.82±3.12 0.279
BMI_ARV, kg/m2 1.21 (0.75–1.95) 1.17 (0.70–1.84) 0 (n = 9,690)
Tertile 1 1 1 1
Tertile 2 1.17 (0.95–1.44) 1.22 (0.97–1.53) 0.97 (0.59–1.59)
Tertile 3 1.38 (1.11–1.72) 1.33 (1.04–1.70) 1.71 (1.06–2.75)
Weight change slope ≤0 (n = 11,047)
Tertile 1 1 1 1
Tertile 2 1.15 (0.94–1.40) 1.19 (0.96–1.48) 0.92 (0.59–1.43)
Tertile 3 1.11 (0.89–1.37) 1.11 (0.88–1.41) 0.98 (0.61–1.58)
Adjusted for age, sex, heart rate, mean body mass index, triglyceride, low-density lipoprotein cholesterol,
high-density lipoprotein cholesterol, estimated glomerular filtration rate, uric acid, high-sensitivity C-reactive
protein, weight change slope, physical exercise, smoking status, alcohol consumption, and diabetes. CVD, car-
diovascular and cerebrovascular diseases; MI, myocardial infarction.
BMI Variability and Outcomes The total population was further divided into two
Table 2 shows the correlation between BMI variability groups according to the direction of the weight change
and CVD according to Cox proportional-hazards regres- slope: ≤0 or >0. Among the 20,737 participants, 11,047
sion analysis. An incrementally higher risk of CVD, MI, (53.27%) experienced weight gain over the course of the
and stroke was observed for the higher tertiles compared three physical examinations (weight change slope >0),
with the lowest-tertile group. The associations between while 9,690 (46.73%) experienced weight loss (weight
BMI variability and outcomes were confirmed after ad- change slope ≤0). BMI_ARV was 1.21 (0.75–1.95) and
justing for baseline age, sex, heart rate, mean BMI, triglyc- the mean BMI was 25.87 ± 3.05 among the subjects with
eride, low-density lipoprotein cholesterol, high-density a weight change slope ≤0. BMI_ARV was 1.17 (0.70–
lipoprotein cholesterol, estimated glomerular filtration 1.84) and the mean BMI was 25.82 ± 3.12 among the sub-
rate, uric acid, high-sensitivity C-reactive protein, weight jects with a weight change slope >0 (Table 3).
change slope, physical exercise, smoking status, alcohol An association of BMI variability with risk of CVD was
consumption, diabetes, and antihypertensive drug thera- present in the weight gain group. Additionally, higher BMI
py. Compared with the lowest tertile, the risk of CVD in- variability was associated with an increased risk of CVD,
creased by 21% (HR 1.21; 95% CI 1.05–1.39), while the stroke, and MI in the weight gain group, while no signifi-
risk of MI increased by 20% (HR 1.20; 95% CI 0.88–1.62), cant differences were observed across the BMI_ARV ter-
and that of stroke increased by 21% (HR 1.21; 95% CI tiles in the weight loss group. In the “weight change slope
1.04–1.41). >0” group, the adjusted HRs (95% CI) values for CVD,
446 Obes Facts 2021;14:442–449 Cai/Wu/Chen/Fang/Li/Chen/Chen/Wu/
DOI: 10.1159/000512317 ChenTable 5. Hazard ratios and 95% confidence intervals of CVD
Subjects CVD Stroke MI
Excluding 4,268 subjects with antihypertensive drug therapy
Tertile 1 1 1 1
Tertile 2 1.22 (1.04–1.45) 1.27 (1.06–1.53) 0.65 (0.62–1.35)
Tertile 3 1.27 (1.07–1.50) 1.30 (1.08–1.56) 1.29 (0.90–1.86)
Excluding 4,180 subjects with diabetes
Tertile 1 1 1 1
Tertile 2 1.13 (0.96–1.30) 1.16 (0.99–1.38) 0.85 (0.60–1.28)
Tertile 3 1.17 (1.01–1.35) 1.20 (1.04–1.43) 1.11 (0.83–1.64)
Excluding 273 subjects newly diagnosed with CVD within 1 year
Tertile 1 1 1 1
Tertile 2 1.18 (1.01–1.36) 1.20 (1.02–1.42) 0.92 (0.65–1.31)
Tertile 3 1.20 (1.03–1.39) 1.23 (1.05–1.45) 1.18 (0.85–1.65)
Adjusted for age, sex, heart rate, mean BMI, triglyceride, low-density lipoprotein cholesterol, high-density
lipoprotein cholesterol, estimated glomerular filtration rate, uric acid, high-sensitivity C-reactive protein, weight
change slope, physical exercise, smoking status, alcohol consumption, diabetes, and antihypertensive drug ther-
apy (nonadjusted after exclusion). CVD, cardiovascular and cerebrovascular diseases; MI, myocardial infarction.
stroke, and MI in tertile 3 were 1.38 (1.11–1.72), 1.33 (1.04– dent of traditional cardiovascular risk factors. Our study
1.70), and 1.71 (1.06–2.75), respectively, compared with showed that after adjustment for confounding factors in-
tertile 1. In the “weight change slope ≤0” group, the ad- cluding mean BMI, weight change slope, and traditional
justed HRs (95% CI) values for CVD, stroke, and MI in cardiovascular risk factors, compared with tertile 1, the
tertile 3 were 1.11 (0.89–1.37), 1.11 (0.88–1.41), and 0.98 risk of CVD increased by 15% in tertile 2 and by 21% in
(0.61–1.58), respectively, compared with tertile 1 (Table 4). tertile 3, and the risk of stroke increased by 18% in tertile
2 and by 21% in tertile 3. Our findings are consistent with
Sensitivity Analysis those of previous studies. According to the 32-year follow-
A sensitivity analysis was conducted to exclude sub- up of 3,171 subjects from the general population from the
jects who participated in only two physical examinations, Framingham study, those with higher BMI variability
those with diabetes, and those with newly diagnosed CVD have an increased risk of CVD compared with those with
within 1 year. The results showed that, in accordance with low BMI variability (men: 1.93 [1.35–2.77]; women: 1.55
the previous statistical results, higher variability in BMI [1.09–2.21]) [10]. Bangalore et al. [11, 12] found that each
led to a higher risk of CVD (Table 5). increase of 1 SD in BMI variability in patients with diabe-
tes or coronary artery disease increased the risk of CVD
by 1.08 and 1.04, respectively. However, we found no sig-
Discussion nificant association between BMI variability and MI.
Compared with the above studies, the incidence of MI in
To our knowledge, this is the first study to explore the our study was significantly lower. These discrepancies
relationship between BMI variability and CVD in patients may be attributed to differences in the populations studied
with hypertension. Our results showed that in hyperten- and racial disparities. Previous studies showed that the in-
sive subjects, higher BMI variability was associated with cidence of MI in Chinese subjects was lower than in Cau-
increased risk of CVD and stroke. This increased risk per- casians [22, 23]. Additionally, because of differences in the
sisted after adjustment for BMI and traditional cardiovas- methods used for assessment, and the absence of consen-
cular risk factors. However, we found no significant asso- sus on a standard definition of weight fluctuation, it was
ciation between BMI variability and MI. In addition, the difficult to make cross-study comparisons, thereby lead-
correlation between BMI variability and CVD existed only ing to challenges in drawing definitive conclusions [24].
in subjects with weight gain, not in those with weight loss. The relationship between BMI variability and CVD in
Among subjects with hypertension, higher BMI vari- patients with hypertension was related to both the level
ability was associated with higher risk of CVD, indepen- and the direction of variation of changes in weight. In the
BMI Variability and Cardiovascular Obes Facts 2021;14:442–449 447
Outcomes DOI: 10.1159/000512317“weight change slope >0” group, the adjusted HR (95% CI) of events [35]. However, we excluded participants diag-
for incident CVD was 1.38 (1.11–1.72) in the highest tertile nosed with CVD or cancer during the measurement of
compared with tertile 1. Weight gain was associated with weight changes, as well as subjects with diabetes in the
higher risk of CVD [25, 26]. In addition, we found that in- sensitivity analysis, thereby minimizing the interference
creased BMI variability during the process of weight gain of diseases. Second, this was an observational study, and
was a risk factor for incident CVD. However, we did not it was therefore impossible to unravel cause-effect rela-
observe a significant association between BMI variability tionships. To minimize the potential effects of reverse
and any cardiovascular or cerebrovascular event in sub- causality, we excluded subjects newly diagnosed with
jects with weight loss (Table 4). More specifically, accord- CVD within 1 year and showed consistent results. Third,
ing to our results, increased BMI variability during the in the present study, only three BMI measurements per
process of weight loss did not increase the risk of CVD. participant were available, which was a considerable limi-
Weight loss strategies for preventing and treating obesity- tation. Finally, this study was conducted in a Chinese pop-
related diseases are strongly supported by this important ulation and most participants were male. The conclusions
finding. Previous studies have shown that in overweight may therefore not apply to other racial or ethnic groups.
and obese patients with hypertension, sustained weight Despite these limitations, our study provides a very novel
loss reduces blood pressure in a dose-response manner, and informative opinion on the relationship between BMI
and improves blood lipid parameters, blood glucose, and variability and CVD in a large hypertensive population.
insulin resistance [7], which can effectively modify the re-
lated risk factors for CVD. However, our subjects with
weight loss had had a higher BMI at baseline (Table 3), Conclusion
which has the potential to adversely affect CVD [2, 3]. Fur-
ther study is required to follow up the subjects with weight BMI variability was an independent risk factor for
loss in order to assess their cardiovascular outcomes. CVD in this hypertensive population. In addition, we
The mechanisms underlying the adverse effects of found that BMI variability was associated with a higher
BMI variability on CVD remain incompletely under- risk of CVD with positive weight change, not with nega-
stood. However, plausible explanations have been sug- tive weight change.
gested in several studies. According to a mouse study,
weight cycling induced greater adipose tissue inflamma-
tion and insulin resistance than a consistent obese state Statement of Ethics
[27]. A positive association was found between fasting in- The present study was approved by the Ethics Committee of
sulin concentration and history of weight fluctuations in Kailuan General Hospital in accordance with the Declaration of
a cross-sectional analysis of 1,932 middle-aged Japanese Helsinki, and each participant signed the informed consent forms.
men [28]. Individuals with larger weight fluctuations had
significantly higher fasting insulin (r = 0.125, p < 0.001).
Conflict of Interest Statement
Insulin resistance is a core pathological feature of CVD
[29]. Furthermore, some studies showed that traditional The authors have no conflicts of interest to declare.
cardiovascular risk factors, such as blood pressure, heart
rate, blood glucose, and blood lipids, are also significant-
ly associated with high BMI variability [30]. This patho- Funding Sources
logical mechanism also occurs in weight gain. Several This work has been supported by the National Natural Science
studies showed that weight gain leads to insulin resis- Foundation of China (No. 81870312).
tance, adipocyte inflammation, and abnormal metabo-
lism, resulting in increased oxidative stress and endothe-
Author Contributions
lial dysfunction, which ultimately promote the occur-
rence of atherosclerosis [31–34]. Y.C. conceived the study idea and designed the study together
This study has several limitations. First, we were un- with S.W., Zefeng Cai, and W.W.; W.W., Zekai Chen, W.F., W.L.,
aware whether weight changes were intentional or unin- G.C., and Zhichao Chen analyzed and interpreted the data; Zefeng
Cai drafted the manuscript, which was critically revised by S.W.
tentional. Intentional weight loss may be associated with and Y.C.; S.W. and Y.C. approved the manuscript and are the guar-
a reduction in cardiovascular events, whereas uninten- antors of this work and take responsibility for the integrity of the
tional weight loss may be associated with an increased rate data and the accuracy of the data analyses.
448 Obes Facts 2021;14:442–449 Cai/Wu/Chen/Fang/Li/Chen/Chen/Wu/
DOI: 10.1159/000512317 ChenReferences
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BMI Variability and Cardiovascular Obes Facts 2021;14:442–449 449
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