Reduced cardiovascular events through dynamic lifestyle modification
in individuals with prediabetes or prehypertension in Korea: a nationwide cohort
study
1Department of Cardiology, Korea University Anam Hospital, Seoul, Korea
2Department of Cardiology, Ewha Womans University Medical Center, Seoul, Korea
3Department of Gastroenterology, Ewha Womans University Medical Center, Seoul, Korea
4Clinical Trial Center, Ewha Womans University Medical Center, Seoul, Korea
*Corresponding author: Hye Ah Lee,
Clinical Trial Center, Ewha Womans University Medical Center, 1071,
Anyangcheon-ro, Yangcheon-gu, Seoul 07985, Korea, E-mail:
khyeah@ewha.ac.kr
*Corresponding author: Junbeom Park,
Department of Cardiology, Ewha Womans University Medical Center, 1071
Anyangcheon-ro, Yangcheon-gu, Seoul 07985, Korea, E-mail:
parkjb@ewha.ac.kr
*
These authors contributed equally to this work.
• Received: August 20, 2024 • Accepted: September 26, 2024
This is an Open-Access article distributed under the terms of the
Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits
unrestricted non-commercial use, distribution, and reproduction in any
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Objectives: There is limited knowledge regarding the impact of
lifestyle changes on cardiovascular events and mortality among individuals with
prehypertension or prediabetes.
Methods: This was a serial retrospective cohort study utilizing data
from the Korean National Health Insurance Service Health Screening Cohort. The
primary outcome considered in the study was major adverse cardiovascular events
(MACE).
Results: A higher risk of MACE was found in men with prehypertension
whose unhealthy lifestyle deteriorated (hazard ratio [HR], 1.13; 95% CI,
1.04–1.23; P=0.004), those who gained weight (HR, 1.15; 95% CI,
1.03–1.28; P=0.010), and those who began smoking (HR, 1.34; 95% CI,
1.17–1.55; P<0.001). Conversely, a reduced risk of MACE was
observed in men with prehypertension who improved their unhealthy lifestyle,
quit smoking, reduced alcohol consumption, or increased the frequency of
physical activity. In men with prediabetes, the risk of MACE was higher in those
whose unhealthy lifestyle worsened (HR, 1.23; 95% CI, 1.12–1.35;
P<0.001), those who gained weight (HR, 1.19; 95% CI, 1.06–1.33;
P=0.003), those who started smoking (HR, 1.41; 95% CI, 1.22–1.64;
P<0.001), and those who decreased their physical activity frequency (HR,
1.21; 95% CI, 1.09–1.35; P<0.001).
Conclusion: Preventive lifestyle changes reduce cardiovascular
events and mortality, particularly in men at risk of developing hypertension or
type 2 diabetes.
Hypertension and type 2 diabetes (T2D) are well-known cardiovascular risk
factors. Additionally, obesity, smoking, alcohol consumption, and decreased
physical activity are established risk factors associated with hypertension or
T2D [1,2]. Previous studies have highlighted that lifestyle modifications
can significantly reduce mortality risks in patients with hypertension or T2D
[3,4]. However, once patients are diagnosed with hypertension or
diabetes, they often begin treatment with medication, which means that analyses
on the effect of lifestyle modifications are very limited. Previous research has
primarily focused on how one specific lifestyle change affects hypertension or
T2D. Moreover, studies examining whether lifestyle modifications have a similar
clinical effect on cardiovascular events or mortality in the prehypertension or
prediabetes stages are somewhat scarce. For example, a weight loss of
approximately 10 kg may reduce systolic blood pressure by between 5 and 20 mmHg
[5]. Alcohol consumption is directly
correlated with elevated blood pressure; thus, reducing alcohol intake is
associated with lower blood pressure [6].
However, regardless of weight loss, engaging in at least 150 minutes of physical
activity per week has been shown to reduce the incidence of T2D by 44% [7]. Furthermore, there are correlations
among certain lifestyles, suggesting that individuals who engage in intensive
exercise may be more inclined to quit smoking or drinking. Therefore, it is
necessary to dynamically analyze the changes in various types of lifestyle
modifications rather than focusing on a single type. Furthermore, lifestyle
habits such as smoking, drinking, and exercise are influenced by gender.
Typically, men are more likely to smoke and drink, leading to the hypothesis
that the impact of rigorous management of unhealthy lifestyles on the occurrence
of cardiovascular events varies between genders. The frequency and intensity of
exercise also differ by gender.
Objectives
Thus, the present study investigated (1) how dynamic changes in lifestyle can
affect cardiovascular events; (2) how various lifestyles change organically; (3)
whether gender-specific lifestyle changes can affect the occurrence of
cardiovascular events, specifically in relation to prehypertension or
prediabetes.
Methods
Ethics statement
The Institutional Review Board (IRB) at Ewha Womans Medical College Mokdong
Hospital (IRB no. EUMC-2021-11-029) and the NHIS Big Data Steering Department
(NHIS-2022-2-197) granted approval for this study. As the NHIS data used were
completely anonymous and handled in accordance with the Personal Data Protection
Act, obtaining written consent from subjects was not required.
Study design
This is a nationwide, population-based cohort study. It has been described in
accordance with the STrengthening the Reporting of OBservational studies in
Epidemiology (STROBE) statement, which is available at: https://www.strobe-statement.org/.
Setting
In December 2022, the authors conducted a search on prediabetes and
prehypertension within the National Health Insurance Service–Health
Screening Cohort (NHIS-HEALS) database. Prediabetes is defined by the presence
of impaired fasting glucose, impaired glucose tolerance, or a hemoglobin A1c
level of 5.7%–6.4%, while prehypertension is characterized by a systolic
pressure of 120 to 139 mmHg or a diastolic pressure of 80 to 89 mmHg at the
initial health screening. The NHIS-HEALS database was established from a cohort
of 514,866 Koreans, aged 40 to 79 in 2002, who were randomly selected to
represent 10% of the national health screening subjects from 2002 to 2003.
Data source and study cohort
The source of data for this study was the Korean NHIS-HEALS, which is a
nationwide population-based cohort. Detailed information on the cohort has
already been published elsewhere [8].
Additional details on the study cohort can be found in the Supplement 1.
Participants (study population)
For this study, we constructed a sub-cohort based on the research hypothesis.
Initially, we excluded subjects with inconsistent examination dates, resulting
in a cohort of 514,795 individuals who had undergone at least one health
screening between 2002 and 2003. Of these, 334,937 subjects who also
participated in a health screening during the second period (2004–2005)
were included. We designated the date of the second health screening as the
index date (Fig. 1C). Subsequently, we
excluded individuals with a history of specific conditions prior to the index
date, as defined by the International Classification of Diseases, Tenth Revision
(ICD-10): heart failure (ICD-10: I50, n=668); cerebrovascular accident (I60-I69,
n=13,187); cardiovascular disease (CVD; I20-I25, I71, I72, n=25,528); or cancer
(C00-C96, n=3,921). Additionally, we excluded individuals with missing
lifestyle-related data (n=13; n=297,010).
Fig. 1.
Flow diagram of selection of the study population from the National
Health Insurance Service database. (A) Prehypertension subgroup; (B)
prediabetes subgroup; (C) overall schema of the study. NHIS, National
Health Insurance Service; HF, heart failure; CVD, cardiovascular
disease; CVA, cerebrovascular accident; HTN, hypertension; DM, diabetes
mellitus; BMI, body mass index.
Next, we defined cohorts for prediabetes and prehypertension. Detailed criteria
used to define these cohorts are available in the Supplement 1. The
prehypertension cohort included 95,152 subjects (60,084 men and 35,068 women),
while the prediabetes cohort comprised 57,865 subjects (37,836 men and 20,029
women). The flow diagram illustrating the selection of the study population is
displayed in Fig. 1A, B.
Outcome variables
The primary outcome of the study was major adverse cardiovascular events (MACE),
which were defined as death, non-fatal myocardial infarction (MI), or non-fatal
stroke resulting from CVD. Hospital admission data were used to identify
instances of CVD, including MI (ICD-10: I21), stroke (ICD-10: I60–I69),
and cardiovascular death (I20–I25, I71–I72, and I60–I69).
The secondary outcome of the study was all-cause mortality. The date of death
was obtained from the claims database, and this information was used to
determine all-cause mortality. The follow-up period began on the index date and
concluded either on the date of the first occurrence of the primary outcome or
on the last follow-up date (12/31/2015).
Measurement (assessment of lifestyle changes)
Regarding lifestyle factors, we considered body mass index (BMI), current smoking
status, alcohol intake categorized by weekly frequency (never; 2–3 times
a month; 1–2 times a week; 3–4 times a week; ≥5 times a
week), and physical activity also categorized by weekly frequency (never;
1–2 times a week; 3–4 times a week; 5–6 times a week; every
day). Changes in these lifestyle factors were assessed using health checkup data
from the first observation period (2002–2003) to the second
(2004–2005) as shown in Fig. 1C.
Detailed methods for evaluating changes in lifestyle factors are available in
the Supplement 1.
Study size
A sample size estimation was not performed, as all target subjects were
included.
Bias
Since subjects were selected from the cohort database according to the inclusion
criteria and disease criteria, selection bias was not a concern.
Statistical analysis
Summary statistics for baseline characteristics were presented as means with SDs
for numerical data and as counts with percentages for categorical data. To
explore the impact of disease incidence and lifestyle behaviors according to
gender, we performed gender-stratified analyses. The incidence rate (per 10,000
person-years) of outcomes was estimated using a Poisson regression model. To
evaluate the influence of lifestyle changes on disease incidence, we calculated
hazard ratios (HRs) with 95% CIs using the Cox proportional hazards regression
model. Detailed descriptions of the covariates used for adjusting the HRs, as
well as the methodology for the sensitivity analysis, are available in the Supplement 1.
All statistical analyses were conducted using SAS 9.4 (SAS Institute, Cary, NC,
USA). Statistical significance was set to P<0.05.
Results
Males constituted 65.2% of the prehypertension cohort (n=60,084). Additionally, women
were found to consume less alcohol (32.0% vs. 80.7% for never drinking) and to
exercise less frequently (46.4% vs. 65.0% for never exercising) compared to men.
Among the men, 44.1% were current smokers (n=25,201), whereas only 1.7% of women
smoked currently (n=577). Similarly, in the prediabetes cohort, men made up 65.4% of
the subjects (n=37,836). The percentage of women who neither exercised (47.2% vs.
67.7%) nor consumed alcohol (29.8% vs. 80.9%) was lower compared to men. In this
cohort, 41.8% of men (n=15,144) were current smokers, while only 2.2% of women
(n=432) were smokers. Furthermore, the prevalence of BMI over 25.0 kg/m2
was lower in women than in men in both cohorts (32.3% vs. 28.5% in the
prehypertension cohort and 38.1% vs. 36.7% in the prediabetes cohort). The general
characteristics of subjects according to group are summarized in Table 1.
Table 1.
Participants’ characteristics based on the index examination of
National Health Insurance Service National Health Screening
Table 2 presents the incidence of diseases
during follow-up in subjects with prehypertension and prediabetes, categorized by
gender. In the prehypertension cohort, there were 3,979 MACE cases in men and 2,290
in women. The MACE incidence rates were similar between genders (62.6/10,000 PY for
men vs. 62.1/10,000 PY for women; P=0.724). However, a significant difference was
observed in all-cause mortality rates, with men showing a higher rate than women
(47.1/10,000 PY vs. 24.3/10,000 PY; P<0.001). In the prediabetes cohort,
3,435 MACE cases were recorded in men and 1,904 in women. The incidence rate of MACE
in women was slightly higher than in men, but this difference was not statistically
significant (88.0/10,000 PY for women vs. 92.8/10,000 PY for men; P=0.063). However,
there was a significant difference in all-cause mortality between men and women,
with men experiencing a higher rate (66.7/10,000 PY vs. 41.4/10,000 PY;
P<0.001).
Table 2.
Disease incidence rate between two biennial health screening
periods
1)MACE was defined as a composite of non-fatal MI, non-fatal stroke, and
CVD death.
As previously mentioned, lifestyle factors were defined as BMI, current smoking,
drinking, and physical activity. In the prehypertension and prediabetes cohorts,
26.6% and 26.1% of subjects, respectively, experienced a worsening in one or more
lifestyle factors. Conversely, 34.2% and 34.8% of subjects in these cohorts improved
in one or more lifestyle factors. Overall, fewer than 10% of subjects experienced a
decline or improvement in two or more lifestyle factors (Supplement 2).
By controlling for lifestyle and clinical factors at the initial health screening, we
evaluated the effects of lifestyle changes on major outcomes using a multivariate
model (Tables 3, 4). In the prehypertension group, 7,376 patients (7.75%) had
already been diagnosed with T2D, and 2,601 (2.73%) were taking anti-hyperglycemic
medication. Similarly, in the prediabetes group, 11,577 patients (20.01%) had been
diagnosed with HTN, and 8,962 (15.49%) were on antihypertensive medication (Table 1). To isolate the effects of medication,
the multivariate analysis accounted for the impact of antihypertensive drugs,
anti-hyperglycemic drugs, and aspirin. In men with prehypertension, the risk of MACE
increased if their lifestyle worsened (HR, 1.13; 95% CI, 1.04–1.23, P=0.004),
particularly if they gained weight (HR, 1.15; 95% CI, 1.03–1.28, P=0.010) or
started smoking (HR, 1.34; 95% CI, 1.17–1.55, P<0.001). For women with
prehypertension, the risk of MACE was higher for those who started smoking (HR,
1.69; 95% CI, 1.15–2.49, P=0.008) or reduced their physical activity (HR,
1.25; 95% CI, 1.06–1.47, P=0.010). Conversely, in men with prehypertension,
improving lifestyle factors reduced the risk of MACE (HR, 0.91; 95% CI,
0.84–0.99, P=0.025), particularly through smoking cessation (HR, 0.79; 95%
CI, 0.70–0.89, P<0.001), drinking less (HR, 1.09; 95% CI,
1.00–1.20, P=0.048), or increasing physical activity (HR, 0.91; 95% CI,
0.84–0.99, P=0.027). In men with prediabetes, those whose lifestyle factors
worsened had a 23% higher risk of MACE compared to those with no lifestyle changes
(HR, 1.23; 95% CI, 1.12–1.35, P<0.001). An increased risk of MACE was
also observed in those who gained weight (HR, 1.19; 95% CI, 1.06–1.33,
P=0.003), started smoking (HR, 1.41; 95% CI, 1.22–1.64, P<0.001), or
decreased their physical activity (HR, 1.21; 95% CI, 1.09–1.35,
P<0.001). Additionally, in men with prediabetes, a reduction in alcohol
consumption was linked to a higher risk of MACE (HR, 1.17; 95% CI, 1.07–1.29,
P=0.001). In women with prediabetes, the risk of MACE was 1.24 times higher for
those who gained weight compared to those with no change in BMI levels (HR, 1.24;
95% CI, 1.06–1.45, P=0.006). As weight change can be a consequence of
lifestyle changes, the association between unhealthy lifestyles, excluding BMI, and
MACE was evaluated. Among pre-hypertensive men, those whose lifestyles worsened had
a higher risk of MACE (HR, 1.10; 95% CI, 1.02–1.20, P=0.022). Among
pre-hypertensive women, those whose lifestyles improved tended to have a lower MACE
risk, although this association was not statistically significant (HR, 0.91; 95% CI,
0.81–1.01, P=0.072) (Table 3, Supplement 3). In the
prediabetes group, men whose lifestyles worsened showed a significantly higher risk
of MACE (HR, 1.23; 95% CI, 1.12–1.35, P<0.001), while there was no
significant difference in MACE risk among comparative female subjects (Table 4, Supplement 4).
Table 3.
Multivariate analysis of total cardiovascular disease events and
mortality associated with lifestyle changes between two biennial health
screening periods in the prehypertension group
Adjusted covariates include age, income level (quantiles), current
smoking status, alcohol consumption, physical activity, CCI score, BMI,
systolic blood pressure, total cholesterol, fasting serum glucose level
at the first health screening, and usage of statin medication prior to
the index date.
MACE, major adverse cardiovascular events; BMI, body mass index; MI,
myocardial infarction; CVD, cardiovascular disease.
1)MACE was defined as a composite of non-fatal MI, non-fatal stroke, and
CVD death.
Table 4.
Multivariate analysis of total cardiovascular disease events and
mortality associated with lifestyle changes between two biennial health
screening periods in the prediabetes group
Adjusted covariates include age, income level (quantiles), current
smoking status, alcohol consumption, physical activity, CCI score, BMI,
systolic blood pressure, total cholesterol, fasting serum glucose level
at the first health screening, and usage of statin medication prior to
the index date. MACE, major adverse cardiovascular events; BMI, body
mass index; MI, myocardial infarction; CVD, cardiovascular disease.
1)MACE was defined as a composite of non-fatal MI, non-fatal stroke, and
CVD death.
To mitigate the risk of reverse causality, a sensitivity analysis was conducted by
excluding cardiovascular events that occurred within two years following the
observation of lifestyle changes. In the prehypertension male group, the risk of
MACE increased among subjects who experienced a decline in lifestyle quality, gained
weight, decreased their physical activity frequency, or began smoking between
biennial screenings. Conversely, the risk decreased in those who improved their
lifestyles or quit smoking. In the prehypertension female group, an increase in MACE
risk was observed in subjects who started smoking (Fig. 2A). In the prediabetes group, the MACE risk escalated in men who
worsened their lifestyle, gained weight, reduced their physical activity frequency,
or started smoking between the biennial screenings. In women, the risk increased
among those who gained weight (Fig. 2B).
Fig. 2.
Risk of cardiovascular disease events and mortality due to lifestyle
changes. (A) The prehypertension group; (B) the prediabetes group. For the
sensitivity analysis, events occurring 2 years after the observation of the
lifestyle changes were excluded and evaluated. MACE, major adverse
cardiovascular events; BMI, body mass index.
Discussion
Key results
This study highlights two significant findings: First, the risk of MACE increased
in men with prediabetes or prehypertension whose lifestyle factors deteriorated,
and this risk escalated even with the worsening of just one parameter. Second,
the impact on MACE risk varied slightly depending on lifestyle changes, with
smoking being strongly linked to an increased risk of MACE in both prediabetes
and prehypertension conditions, irrespective of gender.
Interpretation/comparison with previous studies
Smoking is a well-known risk factor for CVD risk. However, the precise level of
risk that smoking presents to CVD in the prehypertensive population has not been
clearly defined. The incidence of CVD is higher in people with a blood pressure
of 120–129/80–84 mmHg and 130–139/85–89 mmHg than in
normal blood pressure group in Europe and the United States [9]. Previous studies have demonstrated that
smoking significantly influences the progression from prehypertension to
hypertension by stiffening the arteries [10]. Furthermore, smoking increases the risk of developing
hypertension in a dose-response manner over long-term follow-up [11]. This study confirmed that MACE
increased as smoking habits worsened in both women and men. In prehypertensive
patients, smoking not only contributes to the progression to hypertension but
also independently elevates the risk of CVD. These findings underscore the
importance of smoking cessation in patient education for individuals with
prehypertension.
In a previous study, smoking was strongly associated with prediabetes in healthy
young individuals, showing a linear risk gradient with increased cumulative
smoking exposure [12]. Additionally,
prior epidemiological studies have indicated that smoking may be an independent
risk factor for T2D and is significantly associated with a higher risk of
coronary heart disease [13–16]. A meta-analysis of prospective cohort
studies revealed a relative risk of 1.55 (95% CI 1.46–1.64) for total
mortality and 1.29 (95% CI 1.29–1.71) for cardiovascular mortality,
assessing the relationship between smoking and mortality risk in diabetes
patients [17]. In this study, men with
prediabetes who started smoking showed an increased risk of MACE, while smoking
cessation decreased CVD death.
In this study, we also analyzed changes in the risk of MACE, specifically
excluding BMI to assess whether its inclusion as a factor influenced the
outcomes. Males in the prehypertension and prediabetes groups who experienced a
deterioration in their lifestyle had an increased risk of MACE, a trend that
persisted even when BMI was excluded. However, among women in both groups, the
risk of MACE did not show significant differences when unhealthy lifestyle
parameters were considered, with or without BMI (Tables 3, 4). Previous
research has demonstrated a U-shaped relationship between obesity and all-cause
mortality and a linear association between BMI and cardiovascular events [18–20]. In this context, changes in an individual's BMI category
do not directly correlate with an increase or decrease in CVD risk. For
instance, overweight patients with stable coronary heart disease exhibited lower
mortality compared to those of normal weight, and overweight patients with acute
coronary syndrome showed significantly lower in-hospital and 12-month mortality
[21–23]. Furthermore, BMI does not accurately reflect body
composition, such as muscle mass or fat distribution. This phenomenon, known as
'reverse causality,' suggests that BMI is often considered a
result influenced by other confounding factors rather than a standalone factor
in previous studies [24]. In particular,
the BMI values in this dataset do not indicate any intention to lose weight.
Additionally, a decrease in BMI could also result in a reduction in muscle mass.
Given these considerations, although the primary outcome based on lifestyle
changes, excluding BMI, revealed significant differences in MACE risk among male
groups, an analysis of the impact of BMI parameters on the detailed elements of
MACE yielded conflicting results (Supplementals 5, 6).
Previous studies have shown that women generally have lower rates of smoking and
obesity than men, while men are more likely to engage in regular and sustained
physical activity [25,26]. When comparing men and women, the
increase in MACE among men whose unhealthy lifestyles worsened could be linked
to differences in lifestyle patterns between the genders. Indeed, data from the
NHIS indicate gender-specific lifestyle patterns; men are more likely to smoke,
be obese, and consume more alcohol. A previous study demonstrated that moderate
to high physical activity during leisure time was associated with a lower risk
of MACE [27]. Specifically, Fig. 2 illustrates that a decreased frequency
of physical activity was associated with an increased risk of MACE in both the
prehypertension and prediabetes male groups.
Limitations
This study may have several limitations. First, there is a potential for
misclassification bias, as the diagnoses of prediabetes and prehypertension were
based on the recorded history in the NHIS and single measurements of blood
pressure or serum glucose levels. Second, the data on lifestyle patterns were
derived from self-reported questionnaires, which may have introduced some
misclassification. Third, further research is necessary to determine if similar
trends are observable in multi-racial populations beyond Asians. Fourth, the
study assessed changes in lifestyle by analyzing data collected at two distinct
time points, specifically between the index examination and the second
examination. However, it is possible that any lifestyle changes occurring after
the second examination were not captured.
Conclusion
In this retrospective cohort study, a worsening smoking habit was associated with
an increased incidence of MACE in populations with prehypertension and men with
prediabetes. This finding remained consistent after sensitivity analysis.
Specifically, a decline in healthy lifestyle habits among men significantly
increased the risk of MACE. Therefore, lifestyle modifications are crucial even
before the diagnosis of hypertension or T2D, as they can significantly reduce
cardiovascular events and mortality, particularly in men.
Authors' contributions
Project administration: Moon CM, Park J
Conceptualization: Kim Y, Song S, Moon CM, Lee HA, Park J
Methodology & data curation: Moon CM, Lee H, Park J
Funding acquisition: Lee HA, Park J
Writing – original draft: Kim Y, Song S
Writing – review & editing: Kim Y, Song S, Moon CM, Lee HA, Park
J
Conflict of interest
No potential conflict of interest relevant to this article was reported.
Funding
This research was supported by Basic Science Research Program through the
National Research Foundation of Korea (NRF) funded by the Ministry of Science,
ICT & Future Planning (NRF-2022R1A2C1093352), and by an Institute of
Information & Communications Technology Planning & Evaluation
(IITP) grant funded by the Korean government (MSIT) (No. RS-2022-00155966),
Artificial Intelligence Convergence Innovation Human Resources Development (Ewha
Womans University).
Data availability
The datasets generated and/or analyzed during the current study are available in
online repositories. The names of the repositories and accession numbers can be
found below: https://nhiss.nhis.or.kr.
Supplement 2. Distribution pattern according to the changes in lifestyle
pattern
Supplement 3. Univariate analysis of total cardiovascular disease events and
mortality associated with lifestyle changes between two biennial health
screening periods in the prehypertension group
Supplement 4. Univariate analysis of total cardiovascular disease events and
mortality associated with lifestyle changes between two biennial health
screening periods in the prediabetes group
Supplement 5. Multivariate analysis of all-cause death, non-fatal MI, and
non-fatal stroke associated with lifestyle changes between two biennial health
screening periods in the prehypertension group
Supplement 6. Multivariate analysis of all-cause death, non-fatal MI, and
non-fatal stroke associated with lifestyle changes between two biennial health
screening periods in the prediabetes group
1. Gong Q, Zhang P, Wang J, Ma J, An Y, Chen Y, et al. Morbidity and mortality after lifestyle intervention for people
with impaired glucose tolerance: 30-year results of the Da Qing Diabetes
Prevention Outcome Study. Lancet Diabetes Endocrinol 2019;7(6):452-461.
2. Faselis C, Doumas M, Kokkinos JP, Panagiotakos D, Kheirbek R, Sheriff HM, et al. Exercise capacity and progression from prehypertension to
hypertension. Hypertension 2012;60(2):333-338.
3. Lu Q, Zhang Y, Geng T, Yang K, Guo K, Min X, et al. Association of lifestyle factors and antihypertensive medication
use with risk of all-cause and cause-specific mortality among adults with
hypertension in China. JAMA Netw Open 2022;5(2):2146118.
4. Schlesinger S, Neuenschwander M, Ballon A, Nöthlings U, Barbaresko J. Adherence to healthy lifestyles and incidence of diabetes and
mortality among individuals with diabetes: a systematic review and
meta-analysis of prospective studies. J Epidemiol Community Health 2020;74(5):481-487.
6. Puddey IB, Beilin LJ, Vandongen R. Regular alcohol use raises blood pressure in treated hypertensive
subjects: a randomised controlled trial. Lancet 1987;329(8534):647-651.
7. Hamman RF, Wing RR, Edelstein SL, Lachin JM, Bray GA, Delahanty L, et al. Effect of weight loss with lifestyle intervention on risk of
diabetes. Diabetes Care 2006;29(9):2102-2107.
8. Seong SC, Kim YY, Park SK, Khang YH, Kim HC, Park JH, et al. Cohort profile: the National Health Insurance Service-National
Health Screening Cohort (NHIS-HEALS) in Korea. BMJ Open 2017;7(9):016640.
9. Lloyd-Jones DM, Evans JC, Levy D. Hypertension in adults across the age spectrum: current outcomes
and control in the community. JAMA 2005;294(4):466-472.
10. Kim JW, Park CG, Hong SJ, Park SM, Rha SW, Seo HS, et al. Acute and chronic effects of cigarette smoking on arterial
stiffness. Blood Press 2005;14(2):80-85.
11. Thuy AB, Blizzard L, Schmidt MD, Luc PH, Granger RH, Dwyer T. The association between smoking and hypertension in a
population-based sample of Vietnamese men. J Hypertens 2010;28(2):245-250.
12. Aeschbacher S, Schoen T, Clair C, Schillinger P, Schönenberger S, Risch M, et al. Association of smoking and nicotine dependence with pre-diabetes
in young and healthy adults. Swiss Med Wkly 2014;144(4142):w14019
13. Foy CG, Bell RA, Farmer DF, Goff DC Jr, Wagenknecht LE. Smoking and incidence of diabetes among U.S. adults: findings
from the Insulin Resistance Atherosclerosis Study. Diabetes Care 2005;28(10):2501-2507.
14. Will JC, Galuska DA, Ford ES, Mokdad A, Calle EE. Cigarette smoking and diabetes mellitus: evidence of a positive
association from a large prospective cohort study. Int J Epidemiol 2001;30(3):540-546.
16. Morrish NJ, Stevens LK, Fuller JH, Jarrett RJ, Keen H. Risk factors for macrovascular disease in diabetes mellitus: the
London follow-up to the WHO Multinational Study of Vascular Disease in
Diabetics. Diabetologia 1991;34(8):590-594.
17. Pan A, Wang Y, Talaei M, Hu FB. Relation of smoking with total mortality and cardiovascular
events among patients with diabetes mellitus: a meta-analysis and systematic
review. Circulation 2015;132(19):1795-1804.
18. Flegal KM, Kit BK, Orpana H, Graubard BI. Association of all-cause mortality with overweight and obesity
using standard body mass index categories: a systematic review and
meta-analysis. JAMA 2013;309(1):71-82.
19. Adams KF, Schatzkin A, Harris TB, Kipnis V, Mouw T, Ballard-Barbash R, et al. Overweight, obesity, and mortality in a large prospective cohort
of persons 50 to 71 years old. N Engl J Med 2006;355(8):763-778.
20. Kong KA, Park J, Hong S, Hong YS, Sung YA, Lee H. Associations between body mass index and mortality or
cardiovascular events in a general Korean population. PLoS One 2017;12(9):0185024.
21. Romero-Corral A, Montori VM, Somers VK, Korinek J, Thomas RJ, Allison TG, et al. Association of bodyweight with total mortality and with
cardiovascular events in coronary artery disease: a systematic review of
cohort studies. Lancet 2006;368(9536):666-678.
22. Bundhun PK, Li N, Chen MH. Does an obesity paradox really exist after cardiovascular
intervention?: a systematic review and meta-analysis of randomized
controlled trials and observational studies. Medicine 2015;94(44):1910.
23. Patnode CD, Evans CV, Senger CA, Redmond N, Lin JS. Behavioral counseling to promote a healthful diet and physical
activity for cardiovascular disease prevention in adults without known
cardiovascular disease risk factors: updated evidence report and systematic
review for the US Preventive Services Task Force. JAMA 2017;318(2):175-193.
25. Chang SH, Chang YY, Wu LY. Gender differences in lifestyle and risk factors of metabolic
syndrome: do women have better health habits than men? J Clin Nurs 2019;28(11-12):2225-2234.
26. Caspersen CJ, Pereira MA, Curran KM. Changes in physical activity patterns in the United States, by
sex and cross-sectional age. Med Sci Sports Exerc 2000;32(9):1601-1609.
27. Holtermann A, Schnohr P, Nordestgaard BG, Marott JL. The physical activity paradox in cardiovascular disease and
all-cause mortality: the contemporary Copenhagen General Population Study
with 104 046 adults. Eur Heart J 2021;42(15):1499-1511.
Reduced cardiovascular events through dynamic lifestyle modification
in individuals with prediabetes or prehypertension in Korea: a nationwide cohort
study
Fig. 1.
Flow diagram of selection of the study population from the National
Health Insurance Service database. (A) Prehypertension subgroup; (B)
prediabetes subgroup; (C) overall schema of the study. NHIS, National
Health Insurance Service; HF, heart failure; CVD, cardiovascular
disease; CVA, cerebrovascular accident; HTN, hypertension; DM, diabetes
mellitus; BMI, body mass index.
Fig. 2.
Risk of cardiovascular disease events and mortality due to lifestyle
changes. (A) The prehypertension group; (B) the prediabetes group. For the
sensitivity analysis, events occurring 2 years after the observation of the
lifestyle changes were excluded and evaluated. MACE, major adverse
cardiovascular events; BMI, body mass index.
Fig. 1.
Fig. 2.
Reduced cardiovascular events through dynamic lifestyle modification
in individuals with prediabetes or prehypertension in Korea: a nationwide cohort
study
Participants’ characteristics based on the index examination of
National Health Insurance Service National Health Screening
1)MACE was defined as a composite of non-fatal MI, non-fatal stroke, and
CVD death.
Multivariate analysis of total cardiovascular disease events and
mortality associated with lifestyle changes between two biennial health
screening periods in the prehypertension group
Outcome
Parameter
Change
Men
Women
Adjusted hazard ratio
P-value
Adjusted hazard ratio
P-value
[95% CI]
[95% CI]
MACE1)
Unhealthy lifestyle
Worsened
1.13 [1.04–1.23]
0.004
1.10 [0.98–1.23]
0.121
Improved
0.91 [0.84–0.99]
0.025
0.94 [0.85–1.04]
0.243
Unhealthy lifestyle (exclude
BMI)
Worsened
1.10 [1.02–1.20]
0.022
1.03 [0.90–1.17]
0.718
Improved
0.92 [0.85–1.00]
0.052
0.91 [0.81–1.01]
0.072
BMI
Worsened
1.15 [1.03–1.28]
0.010
1.09 [0.95–1.25]
0.220
Improved
0.98 [0.88–1.09]
0.683
0.97 [0.85–1.11]
0.642
Currently smoking
Worsened
1.34 [1.17–1.55]
<0.001
1.69 [1.15–2.49]
0.008
Improved
0.79 [0.70–0.89]
<0.001
0.76 [0.48–1.21]
0.247
Frequency of drinking
Worsened
1.08 [1.00–1.18]
0.061
0.92 [0.78–1.08]
0.307
Improved
1.09 [1.00–1.20]
0.048
1.10 [0.88–1.38]
0.413
Frequency of physical
activity
Worsened
1.09 [0.99–1.21]
0.086
1.25 [1.06–1.47]
0.010
Improved
0.91 [0.84–0.99]
0.027
0.93 [0.83–1.03]
0.166
Adjusted covariates include age, income level (quantiles), current
smoking status, alcohol consumption, physical activity, CCI score, BMI,
systolic blood pressure, total cholesterol, fasting serum glucose level
at the first health screening, and usage of statin medication prior to
the index date.
MACE, major adverse cardiovascular events; BMI, body mass index; MI,
myocardial infarction; CVD, cardiovascular disease.
1)MACE was defined as a composite of non-fatal MI, non-fatal stroke, and
CVD death.
Multivariate analysis of total cardiovascular disease events and
mortality associated with lifestyle changes between two biennial health
screening periods in the prediabetes group
Outcome
Parameter
Change
Men
Women
Adjusted hazard ratio
P-value
Adjusted hazard ratio
P-value
[95% CI]
[95% CI]
MACE1)
Unhealthy lifestyle
Worsened
1.23 [1.12–1.35]
<0.001
1.09 [0.96–1.24]
0.199
Improved
1.05 [0.96–1.14]
0.304
0.96 [0.85–1.07]
0.425
Unhealthy lifestyle (exclude
BMI)
Worsened
1.23 [1.12–1.35]
<0.001
0.97 [0.83–1.13]
0.671
Improved
1.08 [0.99–1.17]
0.084
0.97 [0.86–1.09]
0.64
BMI
Worsened
1.19 [1.06–1.33]
0.003
1.24 [1.06–1.45]
0.006
Improved
0.93 [0.83–1.04]
0.214
0.93 [0.80–1.07]
0.315
Currently smoking
Worsened
1.41 [1.22–1.64]
<0.001
0.88 [0.46–1.69]
0.693
Improved
0.91 [0.80–1.03]
0.138
1.08 [0.69–1.70]
0.741
Frequency of drinking
Worsened
1.08 [0.99–1.18]
0.102
0.96 [0.81–1.14]
0.65
Improved
1.17 [1.07–1.29]
0.001
1.06 [0.82–1.38]
0.659
Frequency of physical
activity
Worsened
1.21 [1.09–1.35]
<0.001
1.05 [0.86–1.28]
0.661
Improved
0.98 [0.90–1.07]
0.632
0.99 [0.88–1.12]
0.912
Adjusted covariates include age, income level (quantiles), current
smoking status, alcohol consumption, physical activity, CCI score, BMI,
systolic blood pressure, total cholesterol, fasting serum glucose level
at the first health screening, and usage of statin medication prior to
the index date. MACE, major adverse cardiovascular events; BMI, body
mass index; MI, myocardial infarction; CVD, cardiovascular disease.
1)MACE was defined as a composite of non-fatal MI, non-fatal stroke, and
CVD death.
Table 1.
Participants’ characteristics based on the index examination of
National Health Insurance Service National Health Screening
MACE was defined as a composite of non-fatal MI, non-fatal stroke, and
CVD death.
Table 3.
Multivariate analysis of total cardiovascular disease events and
mortality associated with lifestyle changes between two biennial health
screening periods in the prehypertension group
Adjusted covariates include age, income level (quantiles), current
smoking status, alcohol consumption, physical activity, CCI score, BMI,
systolic blood pressure, total cholesterol, fasting serum glucose level
at the first health screening, and usage of statin medication prior to
the index date.
MACE, major adverse cardiovascular events; BMI, body mass index; MI,
myocardial infarction; CVD, cardiovascular disease.
MACE was defined as a composite of non-fatal MI, non-fatal stroke, and
CVD death.
Table 4.
Multivariate analysis of total cardiovascular disease events and
mortality associated with lifestyle changes between two biennial health
screening periods in the prediabetes group
Adjusted covariates include age, income level (quantiles), current
smoking status, alcohol consumption, physical activity, CCI score, BMI,
systolic blood pressure, total cholesterol, fasting serum glucose level
at the first health screening, and usage of statin medication prior to
the index date. MACE, major adverse cardiovascular events; BMI, body
mass index; MI, myocardial infarction; CVD, cardiovascular disease.
MACE was defined as a composite of non-fatal MI, non-fatal stroke, and
CVD death.
