ABSTRACT
-
Background
- Although metabolic syndrome (MetS) changes over time, the association between MetS remission and cardiovascular disease risk has not been adequately evaluated by diagnostic criteria or sex. Using current (National Cholesterol Education Program–Adult Treatment Panel III, International Diabetes Federation, Japan) and new criteria, with previously optimized thresholds for predicting cardiovascular disease, we examined whether changes in MetS status alter cardiovascular disease risk in men and women.
-
Methods
- A total of 201,007 men and 99,579 women, aged 20 to 72 years who underwent annual physical examinations between 2008 and 2020 and with no history of cardiovascular disease, were divided into four groups according to a changed MetS status over a 2-year baseline period (MetS-free, MetS-developed, MetS-remission, MetS-persisted). Subsequent cardiovascular disease was observed and multivariate Cox regression analysis was used to calculate each group’s hazard ratio (HR).
-
Results
- During a median follow-up of 5.0 years, 2,831 men (1.41%) and 330 women (0.33%) developed cardiovascular disease. MetS-developed showed significantly increased risk, from 1.5- to 1.8-fold in men and 1.6- to 2.6-fold in women, across all criteria. MetS-remission, by new criteria, showed significantly reduced risk compared to MetS-persisted in both men and women (HR for optimized criteria–1, 0.58; 95% confidence interval [CI], 0.51 to 0.67 for men; and HR for optimized criteria–1, 0.56; 95% CI, 0.35 to 0.91 for women). These risk modifications were greater for obesity and younger age.
-
Conclusion
- MetS onset was associated with increased cardiovascular disease risk by all criteria. MetS remission showed reduced risk, by approximately 40%, in both men and women for optimized criteria only. Thus, efforts to prevent and resolve MetS to reduce the risk of cardiovascular disease are supported.
-
Keywords: Cardiometabolic risk factors; Coronary artery disease; Female; Metabolic syndrome; Stroke; Waist circumference
GRAPHICAL ABSTRACT
Highlights
- • Multiple diagnostic criteria for metabolic syndrome (MetS) have been proposed.
- • We previously developed criteria with optimized cutoff values.
- • Developing MetS was associated with a risk of cardiovascular disease by all criteria.
- • MetS remission reduced the risk by 40% with optimized criteria.
- • We emphasize the importance of achieving MetS remission under optimized criteria.
INTRODUCTION
- Cardiovascular disease accounts for more than one-third of deaths worldwide and its burden is increasing [1]; therefore, correcting modifiable risk factors is important [2]. Metabolic syndrome (MetS) is an accumulation of modifiable cardiometabolic risk factors (other than low-density lipoprotein cholesterol [LDL-C] and smoking), namely abdominal obesity, hyperglycemia, dyslipidemia, and hypertension [3,4]. A recommendation of lifestyle modification [5] can lead to MetS-remission [6].
- However, few studies exist on whether MetS-remission reduces the risk of developing cardiovascular disease [7-9], all of which are based on modified National Cholesterol Education Program–Adult Treatment Panel III (NCEP-ATP III) criteria. Even if individual risk factors are below threshold, a MetS diagnosis increases awareness and discussion of risk status among patients and healthcare providers [10], motivating them to improve their lifestyle [11]. If MetS-remission is shown to reduce cardiovascular disease, and thus becomes an important goal, this also supports measures to reduce the burden of MetS [12].
- Multiple diagnostic criteria exist for MetS worldwide although debate exists about: (1) which one is better in predicting cardiovascular disease; (2) the lack of evidence for setting cutoff values and whether cutoff values for men and women are necessary; and (3) whether waist circumference (WC) should be mandatory [13-16]. Although MetS was originally proposed about 30 years ago as a predictor of cardiovascular disease, its broader inter-organ implications have recently gained attention. In a newly proposed metabolic dysfunction–associated steatotic liver disease [17] and cardiovascular-kidney-metabolic (CKM) syndrome [18], each component of MetS is treated as an important element. Recently, we calculated optimal cutoff values for all MetS components that predicted the incidence of cardiovascular disease in men and women, respectively, and developed modified criteria for optimizing cutoff values (optimized criteria) [19]. New optimized criteria can capture a population that is at high risk but can be missed by traditional criteria. By comparing MetS-remission defined by different criteria, we aimed to identify which definition best predicts a reduction in cardiovascular events.
- However, despite sex differences in the effect of MetS itself [20] and its components [21-24] on cardiovascular disease risk, no reports exist on the association between MetS status changes and subsequent cardiovascular disease in men and women separately, except for one study [9] lacking subgroup analyses due to its small cohort. Furthermore, in addition to analyses by sex, those by age and body mass index (BMI) may yield useful insights into prevention of cardiovascular disease risk in a higher risk population. For example, those developing MetS at a younger age are at higher risk [25], but this has not been examined separately for men and women. Even with a normal BMI, those with metabolic risk factors are at risk [26], but the association between a changed MetS status and BMI remains unknown.
- Therefore, we examined the association between change over time in MetS status (i.e., development, remission, and persistence) and the risk of developing cardiovascular disease according to three current criteria (NCEP-ATP III [27], International Diabetes Federation [IDF] for Asians [28], and Japanese criteria [29]) and our recently developed optimized criteria for each sex. We also examined associations stratified by age and BMI.
METHODS
- Study participants
- Individuals aged 20 to 72 years, who received annual health checkups three consecutive times within an eligible period (April 1, 2008 to January 31, 2017) but with the option to opt out, were included. We defined the earliest checkup and that 2 years later as the start and end, respectively, of a baseline period. Those observed for at least 3 years from the end of the baseline period were eligible for this analysis and continued to be monitored until September 30, 2019. Those with coronary artery disease (CAD) or cerebrovascular disease (CVD), before and during the baseline period, or type 1 diabetes mellitus and those without checkup data, including blood tests, were excluded. Finally, 201,007 men and 99,579 women were enrolled in this study.
- Data collection
- Information on age and sex was obtained from the latest health checkup during the baseline period. The BMI, blood pressure (BP), questionnaire data, and laboratory values were obtained from the earliest and latest health checkups of the baseline period. We collected information on diabetes, hypertension, and dyslipidemia medications from medical records before and during the baseline period. Information about current smoking was determined from the questionnaire provided at the latest health checkup of the baseline period. BP was measured using the oscillometric method according to Japanese Society of Hypertension guidelines. The mean BP was calculated from two measurements. The WC was measured by a skilled inspector at the level of the umbilicus at the end of expiration in a standing position. In Japan, the Ministry of Health, Labour and Welfare (MHLW) has implemented a ‘Specific Health Checkup’ program [30]. The MHLW established guidelines and informed relevant institutions about the required test items, testing methods, and questionnaire components [31]. In addition, the National Institute of Public Health supports standardization of the data. In this study, we used the Japan Medical Data Center Claims Database (JMDC Inc., Tokyo, Japan) [30,32]. Briefly, JMDC collects health insurance claims data for company employees and their dependents, and this database includes data from the health checkups described above.
- Definition of MetS
- Participants were determined to be either ‘MetS-present’ or ‘free from MetS’ at both the initiation and the end of the baseline period. We applied five sets of MetS criteria: NCEP-ATP III criteria, IDF criteria for Asians, Japanese criteria, threshold optimized criteria with a mandatory WC component (optimized-1), and threshold optimized criteria without a mandatory WC component (optimized-2) (Supplementary Table 1).
- Study groups
- We divided participants into four groups according to their changes in MetS status during the baseline period (Supplementary Fig. 1): MetS-free (consistently free from MetS), MetS-persisted (consistently met MetS criteria), MetS-developed (free from MetS at the beginning and met MetS criteria at the end of the baseline period), and MetS-remission (met MetS criteria at the beginning and were free from MetS at the end of the baseline period).
- Study outcomes
- CAD was defined by International Statistical Classification of Diseases and Related Health Problems, 10th revision (ICD-10) codes for cardiac events and procedure codes such as for percutaneous coronary intervention or coronary artery bypass grafting, and their combination. CVD was defined by ICD-10 codes for cerebrovascular events and procedure codes, such as for thrombolytic therapy or endovascular recanalization, and their combination. The definition used in this study has been validated and has an accuracy of over 95% [33]. We excluded events that occurred within 31 days after the end of the baseline period.
- Statistical analysis
- Categorical variables were presented as numerals (percentages) and were compared with χ2 tests. Continuous variables were presented as means±standard deviations and were compared with one-way analysis of variance. To evaluate relationships between a change in MetS status and the development of cardiovascular diseases, we used multivariate Cox regression analysis and calculated adjusted hazard ratios (HRs) and 95% confidence intervals using MetS-free as a reference. HRs were adjusted for age, smoking status, and LDL-C. We also calculated HRs for MetS-remission using MetS-persisted as a reference; both of these had MetS at the initiation of the baseline period to evaluate the effect of remission. Log–log survival plots were used to confirm the proportional hazards assumption. We conducted stratified analysis by age and BMI to evaluate relationships between age at MetS status change, BMI, and the development of cardiovascular diseases. We stratified participants by BMI (25 kg/m2) based on the World Health Organization’s Western Pacific Region Office definition of obesity for Asians [34].
- All analyses were performed by SPSS version 29 software (IBM Co., Armonk, NY, USA). P values were two-sided and P<0.05 was statistically significant.
- This research study was conducted retrospectively from data obtained for clinical purposes. The Ethics Committee of Niigata University approved this study (2015-2410). Informed consent was not required because all data in the JMDC database were anonymized.
RESULTS
- The median follow-up period was 5.00 years (interquartile range, 4.42 to 6.92). Participants were divided into four groups according to a changed MetS status during the baseline period using five sets of MetS criteria. Overall, of 201,007 men and 99,579 women, 2,831 (1.41%) men and 330 (0.33%) women developed CAD/CVD.
- Baseline characteristics by a change in MetS status are summarized in Supplementary Table 2. For all criteria, MetS-persisted and MetS-free cohorts consisted of the oldest and youngest age groups, respectively, for both men and women. Among men, the proportions of MetS-developed, MetS-remission, and MetS-persisted by optimized-2 criteria were the largest, followed by those by optimized-1, NCEP-ATP III, and Japanese criteria; IDF criteria proportions were the smallest. Among women, MetS-persisted by optimized-2 criteria was the largest proportion, followed by those by optimized-1, NCEP-ATP III, and IDF criteria; those by Japanese criteria were the smallest. The proportion experiencing a change in MetS status (sum of MetS-developed and MetS-remission) was greater than the proportion of MetS-persisted according to Japanese criteria in men and the three current criteria in women. For all criteria, the proportion of smokers was smallest in the MetS-free group.
- In men, the incidence of CAD/CVD was highest in MetS-persisted, followed by MetS-remission, MetS-developed, and MetS-free groups (Fig. 1, Supplementary Table 3). The same was true for all criteria. In women, the incidence of CAD/CVD was highest for MetS-persisted and lowest for MetS-free groups according to the four criteria other than Japanese criteria. With regard to changes in MetS status in women according to Japanese criteria, the incidence was higher in MetS-developed than in MetS-persisted groups; according to the four criteria other than IDF, the incidence was higher in MetS-developed than in MetS-remission groups, which differed from men in this respect. When comparing incidence rates between men and women in the same change of MetS status group, these were lower for women than for men in all groups for all criteria.
- In both men and women, adjusted HRs for CAD/CVD for MetS-developed and MetS-persisted compared with MetS-free groups were significantly higher for all criteria (Fig. 1, Supplementary Table 3). When comparing HRs for MetS-persisted men and women by the same criteria, these were higher for men than for women. In contrast, for the MetS-developed group, HRs for women were higher than those for men. By Japanese criteria, the HR for MetS-developed women was higher than that for MetS-persisted women.
- Adjusted HRs for MetS-remission compared to MetS-persisted groups were significantly lower in men for all criteria, significantly lower in women only for optimized criteria, and lowest for optimized criteria in both sexes. In women, adjusted HRs for MetS-remission compared to MetS-persisted according to all current criteria were less than 1 but were not significant.
- Adjusted HRs for MetS-developed and MetS-persisted compared to MetS-free groups were higher in those aged <50 years than in those aged ≥50 years for both men and women (Table 1, Supplementary Table 4). Adjusted HRs for MetS-remission compared to MetS-persisted were lower in men in those aged <50 years than in those aged ≥50 years. In contrast, for women <50 years, adjusted HRs for MetS-remission compared to MetS-persisted were not significantly different. In men, the adjusted HR for MetS-persisted compared to MetS-free was higher for participants with BMI ≥25 kg/m2 compared to <25 kg/m2 (Table 2, Supplementary Table 5). In comparison, participants with a BMI ≥25 kg/m2 had a lower adjusted HR for MetS-remission compared to MetS-persisted than those with a BMI <25 kg/m2. Under the three current criteria, adjusted HRs were significantly higher for participants who were MetS-free and with a BMI ≥25 kg/m2 compared to when MetS-free and with a BMI <25 kg/m2 for both men and women (Supplementary Table 6), with a trend toward higher HRs for the latter. According to optimized criteria, no significant change was evident in adjusted HRs for participants who were MetS-free and with a BMI ≥25 kg/m2 compared to those who were MetS-free and with a BMI <25 kg/m2. Adjusted HRs for those who were MetS-persisted tended to be greater for those with a BMI ≥25 kg/m2 than those with a BMI <25 kg/m2 for both men and women, while adjusted HRs for participants who were MetS-developed were comparable to those with a BMI ≥25 kg/m2 or a BMI <25 kg/m2.
- In men, the incidence of CAD was higher than that of CVD for all changes in MetS status groups (Table 3). In women, the incidence of CVD was greater than that of CAD in all groups according to Japanese, optimized-1, and optimized-2 MetS criteria. For women, CVD was greater than CAD in all groups except MetS-persisted by IDF and NCEP-ATP III criteria.
- In men, adjusted HRs for MetS-developed and MetS-persisted compared to MetS-free for CAD were higher than adjusted HRs for the same MetS status change groups for CVD by all criteria. In women, adjusted HRs for MetS-persisted compared with MetS-free groups for CAD were higher than adjusted HRs for CVD for all criteria except Japanese criteria (Table 3, Supplementary Table 7).
- In men, adjusted HRs for CAD using either criterion were significantly lower for the MetS-remission compared to MetS-persisted group (Supplementary Table 8). In men, HRs for CVD were lower using either criterion but significant when using IDF and the two optimized criteria. In women, adjusted HRs for MetS-remission compared to MetS-persisted groups for CAD were lower but not significant for all available criteria. The HRs for CVD were lower in women for the two optimized criteria and significant only for optimized-2. Log–log plots suggested that the proportional hazards assumption was valid (Supplementary Fig. 2).
DISCUSSION
- We examined, for the first time, the association between changes in MetS status, as defined by multiple MetS criteria, and the risk of cardiovascular disease using a historical cohort of integrated national health examination and receipt data. By all criteria, the development of MetS significantly increased cardiovascular disease risk in both men and women. With optimized criteria, MetS-remission significantly reduced cardiovascular disease risk by about 40% in both men and women. These risk modifications were greater in those who were obese and younger.
- Previous studies on MetS status and cardiovascular disease risk used only NCEP-ATP III criteria. However, our study is the first to apply multiple MetS criteria to the same cohort. In addition, sex-specific studies have been limited. While meta-analyses suggested MetS status was a stronger risk factor for cardiovascular disease in women than in men [20], we examined these separately.
- Comparing the incidence of cardiovascular disease between criteria, using Japanese criteria led to the highest incidence in men in the MetS-persisted group, while the optimized-2 group showed the lowest incidence in both sexes in the MetS-free group. This may be because Japanese criteria include a mandatory item and higher thresholds for component items (only high-density lipoprotein cholesterol [HDL-C] is low), and only a group at higher risk is included in the diagnosis. In comparison, optimized-2 criteria do not include a mandatory item and have lower thresholds for the component items (only HDL-C is high), and a group at relatively lower risk is included in the diagnosis.
- When comparing cardiovascular disease risk due to the development or persistence of MetS using optimized-1 and optimized- 2 criteria, which have the same component thresholds but with only the former requiring the inclusion of WC, the latter showed a higher risk. The reason for this is that WC by itself is not as predictive of cardiovascular disease as other MetS components [19]; a cluster of risk factors other than WC may have contributed to cardiovascular disease risk. For example, most normal-weight obese individuals do not differ substantially from normal-weight non-obese individuals in WC; the proportion with abdominal obesity is as small as 3% but is more likely to have risk factors for cardiovascular disease than normal-weight non-obese individuals [35]. Thus, the importance of identifying and managing other risk factors is suggested, even if WC does not meet the criteria.
- The newly defined optimized criteria also showed a change in cardiovascular disease risk with changed MetS status. By including lower-risk individuals, optimized criteria had a comparable HR to the current criterion, although the proportions of MetS-developed and MetS-persisted individuals were considerably higher than for the current criteria. Since a MetS diagnosis may be an important tipping point for risk factor modification for patients and healthcare providers, optimized criteria would provide more patients with an opportunity for behavioral change.
- Furthermore, only optimized criteria showed a significant risk reduction for MetS-remission in women. However, the effect of remission on cardiovascular disease risk was not clearly captured by the three current criteria due to the small number of women with MetS and events. A MetS diagnosis using current criteria was likely affected by its low sensitivity to the development of cardiovascular disease [19]. Optimized criteria seemed to more sensitively reflect changes in cardiovascular disease risk associated with a changed MetS status. Thus, these may be more suitable in a clinical setting.
- Generally, cardiovascular disease has been understudied in women [36], although MetS causes a significantly increased risk in women [20]. The increased risk of MetS development tended to be greater in women than in men. In this regard, a previous report [9] supports our findings. One possible reason is that insulin resistance in women is more likely to be accompanied by a worsening of other risk factors [37].
- In a previous sex-specific analysis, the HR of remission compared to the persistence of MetS was not calculated [9], making it difficult to estimate the effect of remission on cardiovascular disease risk. With our larger sample size, optimized criteria showed a 40% risk reduction with remission in both men and women.
- Although a younger age at onset of MetS was associated with a higher risk of cardiovascular disease [25], this did not distinguish between risks for men and women. However, this study was the first to show that in young women with a low incidence of cardiovascular disease, the persistence of MetS conferred 2- to 4-fold greater risk than in those without MetS, depending on the criteria applied.
- Two possible reasons exist for this, one of which is that the risk of cardiovascular disease specific to women may have been affected. The incidence of MetS usually increases from menopausal transition to postmenopause [38]. However, premature menopause is also associated with MetS development. Premature menopause was considered to be a risk factor for cardiovascular disease [36]. Polycystic ovary syndrome, a common endocrine disorder in women of reproductive age, is interrelated with MetS and is also considered a risk factor for cardiovascular disease [36]. In our study, women who developed MetS at <50 years of age likely included many who had premature menopause or polycystic ovary syndrome associated with the development of MetS; this may have conferred a greater cardiovascular risk. Another possible reason is that younger women are at a disadvantage in terms of risk perception [39] and discussion of risk [40] resulting in inadequate risk factor management. Acute myocardial infarction has increased in young women [39]. Therefore, primary prevention in this age-sex group is urgently required, focusing on changes in MetS status.
- The coexistence of obesity and MetS was associated with a greater risk of cardiovascular disease than MetS alone. We showed that the modification of cardiovascular risk by obesity and non-obesity, which was previously confirmed in MetS by NCEP-ATP III criteria at a single time point [26], was observed with dynamic changes in MetS status using any of the criteria. Additionally, we also showed that even non-obese individuals who developed or persisted in MetS were at higher risk than obese individuals without MetS, and that non-obese individuals who developed MetS had a high risk comparable to that of obese individuals who developed MetS. Although previous studies revealed the increased cardiovascular risk of having multiple risk factors at a single time point, even in the absence of obesity [12,26], the present finding extends this to a dynamic change in MetS. The first diagnosis of MetS is an excellent opportunity for lifestyle intervention; it is important to show that even non-obese individuals are at risk at that time. Importantly, a reduction in risk was observed with MetS-remission in both obese and non-obese men, thus supporting the need for intervention in the non-obese population.
- Among men, we found the effect of MetS-remission on reducing the risk of cardiovascular disease was greater in obese individuals. This may reflect how an improvement in risk factors by lifestyle modification and weight loss can be greater in such individuals [41,42]. Notably, when patients with MetS by optimized criteria went into remission, the risk of cardiovascular disease was almost halved; the reduction was clearly greater than for other criteria. Optimized criteria have a lower threshold of risk factors and are more sensitive to the development of cardiovascular disease [19]; i.e., those who achieved remission by these criteria had a milder degree of risk factors. The potential for greater efficacy of interventions in obese people with MetS further motivates the efforts of people and healthcare providers.
- Under the current criteria, obesity was associated with an increased risk in both men and women, even in MetS-free individuals. In contrast, optimized criteria showed no significantly increased risk in that subgroup. Obesity without MetS in the current criteria is a risk for cardiovascular disease [43], suggesting obesity may lead to metabolic abnormalities later in life [44]. However, the results of this study suggested some obese individuals without MetS were at higher risk because of a degree of risk factors that did not reach a MetS diagnosis by the current criteria. This study also suggests optimized criteria detected the risk for obese individuals.
- For both men and women, the increased risk due to MetS development and persistence tended to be greater for CAD than for CVD. This may be because MetS promotes atherosclerotic changes based on insulin resistance, which is a greater risk factor in CAD and ischemic stroke [45], and that CVD includes types other than ischemic stroke. For CVD, the incidence of MetS development in women was comparable to that of MetS persistence, indicating a relatively large risk. The more rapid rise of BP in women than men, occurring as early as the third decade [46], may be strongly manifested in CVD affected by hypertension [24].
- In our study, the proportion of MetS-free individuals (75% in men, 87% in women) was similar to that reported for Korea [7] and higher than that in China (62%) [8]. The incidence rates (per 1,000 person-years) in our study were 1.7 (MetSfree) and 6.1 (MetS-persisted) for men, and 0.5 and 2.0 for women, respectively, which are close to the rates for Korea (1.9 and 8.5, respectively) but substantially lower than the rates for China (4.2 and 13.2). These differences may be due to the older age and higher proportion of men in the Chinese cohort. Moreover, the Chinese cohort used a Chinese-specific WC cutoff (85 cm for men) and lower treatment rates for dyslipidemia. Taken together, improving MetS at an early stage may be essential to reduce the risk of cardiovascular disease.
- This study has several limitations. First, we were unable to capture risk profile changes during the follow-up period due to the incomplete database. Therefore, time-dependent covariate analysis was not conducted. Second, a portion of the risk in women could not be evaluated due to the small number of events. Third, the observation period was relatively short. However, due to the large sample size, the present study was larger in person-years than some prior studies. Fourth, because grouping was based on the presence or absence of MetS at two time points, some participants may have been classified based on transient changes. However, a difference was not evident in the risk of cardiovascular disease associated with changes in MetS status compared with reports that excluded those who experienced transient changes, which accounted for as much as 20 to 30% of the total for three time points [7,8]. Thus, grouping based on MetS at two time points is practical in a clinical setting. Furthermore, for some criteria, the proportion of participants who experienced changes in MetS status (MetS-developed and MetS-remission combined) was greater than the proportion of MetS-persisted, emphasizing the wider range of application. In addition, we did not consider the duration of MetS prior to the baseline period. Fifth, because prior and present studies were conducted in East Asia and the Eastern Mediterranean, caution is required in interpreting the results for other ethnic groups. Finally, because health examination data were used, it was difficult to understand how and for how long changes in lifestyle habits occurred.
- In conclusion, the development of MetS increased the risk of cardiovascular disease from 1.5- to 1.8-fold in men and from 1.6- to 2.6-fold in women, regardless of the criteria. However, MetS-remission was associated with an approximately 40% reduction in risk for both sexes as determined by optimized criteria, although there was no significant change for women as determined by current criteria. Such risk reductions were greater in obese and younger individuals. These results further encourage efforts by clinicians and patients to prevent the development of MetS and to achieve remission with optimized criteria.
SUPPLEMENTARY MATERIALS
Supplementary materials related to this article can be found online at https://doi.org/10.4093/dmj.2025.0197.
Supplementary Table 4.
Age-adjusted hazard ratio and 95% confidence intervals for CAD/CVD according to a change in MetS status, stratified by age <50 or ≥50 years
dmj-2025-0197-Supplementary-Table-4.pdf
Supplementary Table 5.
Age-adjusted hazard ratio and 95% confidence intervals for CAD/CVD according to change in MetS status, stratified by BMI <25 or ≥25 kg/m2
dmj-2025-0197-Supplementary-Table-5.pdf
Supplementary Table 6.
Adjusted hazard ratio and 95% confidence intervals for CAD/CVD according to a change in MetS status and BMI compared with MetS-free and BMI <25 kg/m2
dmj-2025-0197-Supplementary-Table-6.pdf
Supplementary Fig. 1.
Four groups according to a change in metabolic syndrome (MetS) status. The triangles indicate the initial times of follow-up for outcomes. MetS-, free from MetS status; MetS+, MetS-present status.
dmj-2025-0197-Supplementary-Fig-1.pdf
Supplementary Fig. 2.
Log–log survival plots for four groups according to a change in metabolic syndrome (MetS) status. In each criterion, the figure on the left is for men and the figure on the right is for women. NCEP-ATP III, modified National Cholesterol Education Program–Adult Treatment Panel III criteria for Asians; IDF, International Diabetes Federation criteria for Asians; Optimized- 1, threshold optimization criteria with a waist circumference (WC) requirement; Optimized-2, threshold optimization criteria with no WC requirement.
dmj-2025-0197-Supplementary-Fig-2.pdf
NOTES
-
CONFLICTS OF INTEREST
No potential conflict of interest relevant to this article was reported.
-
AUTHOR CONTRIBUTIONS
Conception or design: H.T., K.F.
Acquisition, analysis, or interpretation of data: all authors.
Drafting the work or revising: all authors.
Final approval of the manuscript: all authors.
-
FUNDING
This work was supported by the Japan Society for Promotion of Science KAKENHI, Grant Number JP 21K11569, and the Ministry of Health, Labour and Welfare. The sponsor had no role in the design and conduct of the study.
-
ACKNOWLEDGMENTS
These data were presented in part at the American Diabetes Association 84th Scientific Sessions, Orlando, FL, USA, 21–24 June 2024 (https://doi.org/10.2337/db24-1313-P).
The authors thank Satomi Kawauchi and Arisa Adachi, Niigata University Faculty of Medicine, for excellent secretarial assistance.
DATA AVAILABILITY
Some or all datasets generated during and/or analyzed during the current study are not publicly available but are available from the corresponding author on reasonable request.
Fig. 1.Risk for coronary artery disease (CAD)/cerebrovascular disease (CVD) according to a change in metabolic syndrome (MetS) status. (A) Incidence rate and risk compared with MetS-free cohort. (B) Risk compared with MetS-persisted cohort. Hazard ratio (HR) was estimated using a Cox regression model adjusted for age, smoking status, and low-density lipoprotein cholesterol. CI, confidence interval; NCEP-ATP III, modified National Cholesterol Education Program–Adult Treatment Panel III criteria for Asians; IDF, International Diabetes Federation criteria for Asians; Optimized-1, threshold optimization criteria with a WC requirement; Optimized-2, threshold optimization criteria with no WC requirement; WC, waist circumference.
Table 1.Adjusted hazard ratios and 95% confidence intervals for CAD/CVD according to a change in MetS status, stratified by age <50 or ≥50 years
|
Variable |
Men
|
Women
|
MetS-free as reference
|
MetS-persisted as reference
|
MetS-free as reference
|
MetS-persisted as reference
|
|
<50 years |
≥50 years |
<50 years |
≥50 years |
<50 years |
≥50 years |
<50 years |
≥50 years |
|
NCEP-ATP III |
MetS-free |
Reference |
Reference |
|
|
Reference |
Reference |
|
|
|
MetS-developed |
1.93 (1.60–2.34)a
|
1.40 (1.17–1.67)a
|
|
|
2.04 (1.09–3.81)a
|
1.59 (0.96–2.63) |
|
|
|
MetS-remission |
2.13 (1.72–2.63)a
|
1.70 (1.41–2.05)a
|
0.61 (0.49–0.76)a
|
0.74 (0.61–0.90)a
|
1.65 (0.67–4.06) |
1.63 (0.85–3.12) |
0.57 (0.21–1.53) |
0.57 (0.21–1.53) |
|
MetS-persisted |
3.49 (3.06–3.97)a
|
2.29 (2.05–2.56)a
|
Reference |
Reference |
2.91 (1.73–4.90)a
|
2.19 (1.54–3.12)a
|
Reference |
Reference |
|
IDF |
MetS-free |
Reference |
Reference |
|
|
Reference |
Reference |
|
|
|
MetS-developed |
1.70 (1.36–2.13)a
|
1.40 (1.14–1.72)a
|
|
|
1.90 (0.99–3.66) |
1.35 (0.79–2.31) |
|
|
|
MetS-remission |
1.85 (1.45–2.36)a
|
1.58 (1.28–1.96)a
|
0.60 (0.46–0.79)a
|
0.76 (0.60–0.97)a
|
1.77 (0.72–4.36) |
1.39 (0.71–2.75) |
0.54 (0.20–1.45) |
0.72 (0.35–1.48) |
|
MetS-persisted |
3.07 (2.66–3.53)a
|
2.08 (1.83–2.36)a
|
Reference |
Reference |
3.30 (1.99–5.48)a
|
1.95 (1.34–2.83)a
|
Reference |
Reference |
|
Japanese |
MetS-free |
Reference |
Reference |
|
|
Reference |
Reference |
|
|
|
MetS-developed |
1.86 (1.52–2.28)a
|
1.74 (1.47–2.06)a
|
|
|
4.05 (1.88–8.76)a
|
1.89 (0.93–3.85) |
|
|
|
MetS-remission |
2.53 (2.06–3.10)a
|
1.79 (1.48–2.16)a
|
0.67 (0.54–0.84)a
|
0.78 (0.63–0.95)a
|
NA |
NA |
NA |
NA |
|
MetS-persisted |
3.78 (3.30–4.33)a
|
2.30 (2.04–2.59)a
|
Reference |
Reference |
3.01 (1.23–7.38)a
|
1.59 (0.81–3.12) |
Reference |
Reference |
|
Optimized-1 |
MetS-free |
Reference |
Reference |
|
|
Reference |
Reference |
|
|
|
MetS-developed |
1.43 (1.17–1.74)a
|
1.37 (1.15–1.64)a
|
|
|
2.07 (1.27–3.38)a
|
1.43 (0.87–2.33) |
|
|
|
MetS-remission |
1.70 (1.38–2.10)a
|
1.35 (1.12–1.64)a
|
0.53 (0.43–0.65)a
|
0.63 (0.52–0.76)a
|
1.58 (0.82–3.08) |
0.85 (0.42–1.71) |
0.63 (0.32–1.25) |
0.49 (0.25–0.98)a
|
|
MetS-persisted |
3.23 (2.86–3.66)a
|
2.16 (1.94–2.41)a
|
Reference |
Reference |
2.50 (1.71–3.66)a
|
1.73 (1.25–2.41)a
|
Reference |
Reference |
|
Optimized-2 |
MetS-free |
Reference |
Reference |
|
|
Reference |
Reference |
|
|
|
MetS-developed |
1.62 (1.34–1.96)a
|
1.43 (1.20–1.70)a
|
|
|
2.03 (1.25–3.30)a
|
1.89 (1.18–3.04)a
|
|
|
|
MetS-remission |
1.82 (1.48–2.24)a
|
1.41 (1.17–1.71)a
|
0.54 (0.44–0.66)a
|
0.62 (0.51–0.75)a
|
1.42 (0.73–2.77) |
1.24 (0.66–2.33) |
0.57 (0.29–1.12) |
0.62 (0.34–1.13) |
|
MetS-persisted |
3.38 (2.98–3.84)a
|
2.29 (2.04–2.56)a
|
Reference |
Reference |
2.50 (1.71–3.66)a
|
2.01 (1.41–2.86)a
|
Reference |
Reference |
Table 2.Adjusted hazard ratios and 95% confidence intervals for CAD/CVD according to a change in MetS status, stratified by BMI <25 or ≥25 kg/m2
|
Variable |
Men
|
Women
|
MetS-free as reference
|
MetS-persisted as reference
|
MetS-free as reference
|
MetS-persisted as reference
|
|
BMI <25 kg/m2
|
BMI ≥25 kg/m2
|
BMI <25 kg/m2
|
BMI ≥25 kg/m2
|
BMI <25 kg/m2
|
BMI ≥25 kg/m2
|
BMI <25 kg/m2
|
BMI ≥25 kg/m2
|
|
NCEP-ATP III |
MetS-free |
Reference |
Reference |
|
|
Reference |
Reference |
|
|
|
MetS-developed |
1.45 (1.18–1.76)a
|
1.56 (1.30–1.88)a
|
|
|
1.84 (1.11–3.05)a
|
1.26 (0.65–2.46) |
|
|
|
MetS-remission |
1.84 (1.52–2.24)a
|
1.73 (1.39–2.14)a
|
0.84 (0.67–1.06) |
0.65 (0.53–0.79)a
|
2.27 (1.28–4.01)a
|
NA |
1.15 (0.59–2.25) |
NA |
|
MetS-persisted |
2.19 (1.89–2.55)a
|
2.66 (2.32–3.05)a
|
Reference |
Reference |
1.97 (1.27–3.06)a
|
2.02 (1.24–3.27)a
|
Reference |
Reference |
|
IDF |
MetS-free |
Reference |
Reference |
|
|
Reference |
Reference |
|
|
|
MetS-developed |
1.52 (1.06–2.18)a
|
1.26 (1.05–1.52)a
|
|
|
1.52 (0.86–2.69) |
1.22 (0.63–2.37) |
|
|
|
MetS-remission |
1.69 (1.27–2.25)a
|
1.42 (1.16–1.75)a
|
1.06 (0.65–1.71) |
0.67 (0.55–0.83)a
|
1.91 (1.03–3.53)a
|
NA |
0.83 (0.41–1.71) |
NA |
|
MetS-persisted |
1.60 (1.08–2.38)a
|
2.12 (1.87–2.41)a
|
Reference |
Reference |
1.83 (1.10–3.02)a
|
1.94 (1.19–3.15)a
|
Reference |
Reference |
|
Japanese |
MetS-free |
Reference |
Reference |
|
|
Reference |
Reference |
|
|
|
MetS-developed |
1.72 (1.39–2.14)a
|
1.67 (1.40–2.00)a
|
|
|
NA |
2.14 (1.20–3.80)a
|
|
|
|
MetS-remission |
1.88 (1.53–2.31)a
|
2.09 (1.71–2.56)a
|
0.85 (0.65–1.12) |
0.75 (0.62–0.91)a
|
NA |
NA |
NA |
NA |
|
MetS-persisted |
2.21 (1.81–2.70)a
|
2.79 (2.44–3.18)a
|
Reference |
Reference |
NA |
1.40 (0.75–2.61) |
Reference |
Reference |
|
Optimized-1 |
MetS-free |
Reference |
Reference |
|
|
Reference |
Reference |
|
|
|
MetS-developed |
1.38 (1.16–1.64)a
|
1.38 (1.09–1.74)a
|
|
|
1.78 (1.22–2.61)a
|
1.31 (0.45–3.77) |
|
|
|
MetS-remission |
1.45 (1.21–1.73)a
|
1.56 (1.20–2.03)a
|
0.71 (0.58–0.86)a
|
0.55 (0.44–0.69)a
|
1.16 (0.69–1.96) |
NA |
0.67(0.39–1.17) |
NA |
|
MetS-persisted |
2.04 (1.79–2.33)a
|
2.83 (2.38–3.37)a
|
Reference |
Reference |
1.73 (1.25–2.40)a
|
1.94 (0.83–4.52) |
Reference |
Reference |
|
Optimized-2 |
MetS-free |
Reference |
Reference |
|
|
Reference |
Reference |
|
|
|
MetS-developed |
1.52 (1.30–1.79)a
|
1.41 (1.12–1.79)a
|
|
|
2.07 (1.43–2.98)a
|
1.32 (0.46–3.80) |
|
|
|
MetS-remission |
1.60 (1.35–1.90)a
|
1.47 (1.12–1.94)a
|
0.73 (0.61–0.88)a
|
0.51 (0.40–0.64)a
|
1.44 (0.89–2.33) |
NA |
0.75 (0.46–1.24) |
NA |
|
MetS-persisted |
2.20 (1.94–2.49)a
|
2.89 (2.43–3.45)a
|
Reference |
Reference |
1.91 (1.39–2.64)a
|
1.94 (0.83–4.52) |
Reference |
Reference |
Table 3.Incidence rates, adjusted hazard ratios, and 95% confidence intervals for CAD or CVD according to a change in MetS status
|
Variable |
Men
|
Women
|
Incidence rate, /1,000 person-yr
|
Adjusted HR (95% CI)
|
Incidence rate, /1,000 person-yr
|
Adjusted HR (95% CI)
|
|
CAD |
CVD |
CAD |
CVD |
CAD |
CVD |
CAD |
CVD |
|
NCEP-ATP III |
MetS-free |
1.14 |
0.79 |
Reference |
Reference |
0.18 |
0.36 |
Reference |
Reference |
|
MetS-developed |
2.48 |
1.18 |
1.82 (1.56–2.12)a
|
1.28 (1.04–1.58)a
|
0.62 |
0.78 |
2.13 (1.22–3.71)a
|
1.63 (1.01–2.64)a
|
|
MetS-remission |
3.11 |
1.27 |
2.19 (1.86–2.57)a
|
1.35 (1.06–1.72)a
|
0.53 |
0.91 |
1.77 (0.81–3.86) |
1.88 (1.04–3.40)a
|
|
MetS-persisted |
4.95 |
1.74 |
3.42 (3.11–3.78)a
|
1.69 (1.46–1.95)a
|
1.27 |
1.00 |
3.56 (2.40–5.27)a
|
1.78 (1.21–2.62)a
|
|
IDF |
MetS-free |
1.41 |
0.87 |
Reference |
Reference |
0.20 |
0.38 |
Reference |
Reference |
|
MetS-developed |
2.66 |
1.19 |
1.67 (1.40–1.98)a
|
1.26 (0.98–1.62) |
0.52 |
0.74 |
1.65 (0.90–3.03) |
1.52 (0.92–2.51) |
|
MetS-remission |
3.28 |
0.98 |
2.00 (1.67–2.39)a
|
0.99 (0.72–1.36) |
0.40 |
0.88 |
NA |
1.73 (0.94–3.20) |
|
MetS-persisted |
4.80 |
1.76 |
2.86 (2.57–3.18)a
|
1.70 (1.45–2.01)a
|
1.28 |
0.94 |
3.32 (2.24–4.94)a
|
1.65 (1.09–2.49)a
|
|
Japanese |
MetS-free |
1.25 |
0.79 |
Reference |
Reference |
0.26 |
0.41 |
Reference |
Reference |
|
MetS-developed |
3.00 |
1.28 |
2.00 (1.73–2.32)a
|
1.41 (1.13–1.75)a
|
1.13 |
1.27 |
2.71 (1.32–5.55)a
|
2.34 (1.19–4.57)a
|
|
MetS-remission |
3.32 |
1.55 |
2.20 (1.87–2.59)a
|
1.66 (1.32–2.09)a
|
0.29 |
0.60 |
NA |
NA |
|
MetS-persisted |
5.25 |
1.92 |
3.35 (3.02–3.71)a
|
1.88 (1.62–2.20)a
|
0.76 |
1.27 |
1.62 (0.71–3.69) |
2.13 (1.12–4.04)a
|
|
Optimized-1 |
MetS-free |
1.04 |
0.71 |
Reference |
Reference |
0.16 |
0.32 |
Reference |
Reference |
|
MetS-developed |
1.87 |
1.06 |
1.51 (1.29–1.76)a
|
1.34 (1.10–1.64)a
|
0.32 |
0.62 |
1.52 (0.87–2.66) |
1.70 (1.14–2.53)a
|
|
MetS-remission |
2.02 |
1.12 |
1.61 (1.36–1.91)a
|
1.37 (1.09–1.70)a
|
0.27 |
0.46 |
1.26 (0.62–2.55) |
1.22 (0.71–2.09) |
|
MetS-persisted |
4.13 |
1.65 |
3.03 (2.75–3.34)a
|
1.84 (1.61–2.10)a
|
0.66 |
0.75 |
2.43 (1.68–3.51)a
|
1.77 (1.31–2.39)a
|
|
Optimized-2 |
MetS-free |
0.95 |
0.67 |
Reference |
Reference |
0.14 |
0.29 |
Reference |
Reference |
|
MetS-developed |
1.87 |
1.10 |
1.63 (1.40–1.90)a
|
1.43 (1.17–1.73)a
|
0.31 |
0.67 |
1.66 (0.95–2.90) |
2.02 (1.38–2.96)a
|
|
MetS-remission |
1.98 |
1.08 |
1.71 (1.45–2.03)a
|
1.37 (1.09–1.70)a
|
0.35 |
0.38 |
1.87 (1.01–3.47)a
|
1.12 (0.64–1.97) |
|
MetS-persisted |
4.12 |
1.65 |
3.27 (2.96–3.61)a
|
1.89 (1.65–2.16)a
|
0.65 |
0.78 |
2.62 (1.78–3.87)a
|
2.01 (1.48–2.72)a
|
REFERENCES
- 1. GBD 2017 Causes of Death Collaborators. Global, regional, and national age-sex-specific mortality for 282 causes of death in 195 countries and territories, 1980-2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet 2018;392:1736-88.PubMedPMC
- 2. Roth GA, Mensah GA, Johnson CO, Addolorato G, Ammirati E, Baddour LM, et al. Global burden of cardiovascular diseases and risk factors, 1990-2019: update from the GBD 2019 study. J Am Coll Cardiol 2020;76:2982-3021.PubMedPMC
- 3. Alberti KG, Zimmet PZ. Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1: diagnosis and classification of diabetes mellitus provisional report of a WHO consultation. Diabet Med 1998;15:539-53.ArticlePubMed
- 4. Wilson PW, D’Agostino RB, Parise H, Sullivan L, Meigs JB. Metabolic syndrome as a precursor of cardiovascular disease and type 2 diabetes mellitus. Circulation 2005;112:3066-72.ArticlePubMedPMC
- 5. Grundy SM, Cleeman JI, Daniels SR, Donato KA, Eckel RH, Franklin BA, et al. Diagnosis and management of the metabolic syndrome: an American Heart Association/National Heart, Lung, and Blood Institute Scientific Statement. Circulation 2005;112:2735-52.ArticlePubMedPMC
- 6. Yamaoka K, Tango T. Effects of lifestyle modification on metabolic syndrome: a systematic review and meta-analysis. BMC Med 2012;10:138.ArticlePubMedPMCPDF
- 7. Park S, Lee S, Kim Y, Lee Y, Kang MW, Han K, et al. Altered risk for cardiovascular events with changes in the metabolic syndrome status: a nationwide population-based study of approximately 10 million persons. Ann Intern Med 2019;171:875-84.ArticlePubMedPDF
- 8. He D, Zhang X, Chen S, Dai C, Wu Q, Zhou Y, et al. Dynamic changes of metabolic syndrome alter the risks of cardiovascular diseases and all-cause mortality: evidence from a prospective cohort study. Front Cardiovasc Med 2021;8:706999.ArticlePubMedPMC
- 9. Ramezankhani A, Azizi F, Hadaegh F. Gender differences in changes in metabolic syndrome status and its components and risk of cardiovascular disease: a longitudinal cohort study. Cardiovasc Diabetol 2022;21:227.ArticlePubMedPMCPDF
- 10. Smith SR. Importance of diagnosing and treating the metabolic syndrome in reducing cardiovascular risk. Obesity (Silver Spring) 2006;14 Suppl 3:128S-34S.ArticlePubMed
- 11. Jumean MF, Korenfeld Y, Somers VK, Vickers KS, Thomas RJ, Lopez-Jimenez F. Impact of diagnosing metabolic syndrome on risk perception. Am J Health Behav 2012;36:522-32.ArticlePubMedPMC
- 12. Iso H, Cui R, Takamoto I, Kiyama M, Saito I, Okamura T, et al. Risk classification for metabolic syndrome and the incidence of cardiovascular disease in japan with low prevalence of obesity: a pooled analysis of 10 prospective cohort studies. J Am Heart Assoc 2021;10:e020760.ArticlePubMedPMC
- 13. Greenland P. Critical questions about the metabolic syndrome. Circulation 2005;112:3675-6.ArticlePubMed
- 14. Sattar N, McConnachie A, Shaper AG, Blauw GJ, Buckley BM, de Craen AJ, et al. Can metabolic syndrome usefully predict cardiovascular disease and diabetes?: outcome data from two prospective studies. Lancet 2008;371:1927-35.PubMed
- 15. Kahn R, Buse J, Ferrannini E, Stern M. The metabolic syndrome: time for a critical appraisal: joint statement from the American Diabetes Association and the European Association for the Study of Diabetes. Diabetes Care 2005;28:2289-304.PubMed
- 16. Kahn R. Metabolic syndrome: what is the clinical usefulness? Lancet 2008;371:1892-3.ArticlePubMed
- 17. Rinella ME, Lazarus JV, Ratziu V, Francque SM, Sanyal AJ, Kanwal F, et al. A multisociety Delphi consensus statement on new fatty liver disease nomenclature. J Hepatol 2023;79:1542-56.PubMed
- 18. Ndumele CE, Neeland IJ, Tuttle KR, Chow SL, Mathew RO, Khan SS, et al. A synopsis of the evidence for the science and clinical management of Cardiovascular-Kidney-Metabolic (CKM) syndrome: a scientific statement from the American Heart Association. Circulation 2023;148:1636-64.ArticlePubMed
- 19. Yamazaki Y, Fujihara K, Sato T, Harada Yamada M, Yaguchi Y, Matsubayashi Y, et al. Usefulness of new criteria for metabolic syndrome optimized for prediction of cardiovascular diseases in Japanese. J Atheroscler Thromb 2024;31:382-95.ArticlePubMedPMC
- 20. Mottillo S, Filion KB, Genest J, Joseph L, Pilote L, Poirier P, et al. The metabolic syndrome and cardiovascular risk a systematic review and meta-analysis. J Am Coll Cardiol 2010;56:1113-32.PubMed
- 21. Cai X, Zhang Y, Li M, Wu JH, Mai L, Li J, et al. Association between prediabetes and risk of all cause mortality and cardiovascular disease: updated meta-analysis. BMJ 2020;370:m2297.ArticlePubMedPMC
- 22. Peters SA, Huxley RR, Woodward M. Diabetes as risk factor for incident coronary heart disease in women compared with men: a systematic review and meta-analysis of 64 cohorts including 858,507 individuals and 28,203 coronary events. Diabetologia 2014;57:1542-51.ArticlePubMedPDF
- 23. Peters SA, Huxley RR, Woodward M. Diabetes as a risk factor for stroke in women compared with men: a systematic review and meta-analysis of 64 cohorts, including 775,385 individuals and 12,539 strokes. Lancet 2014;383:1973-80.ArticlePubMed
- 24. Rapsomaniki E, Timmis A, George J, Pujades-Rodriguez M, Shah AD, Denaxas S, et al. Blood pressure and incidence of twelve cardiovascular diseases: lifetime risks, healthy life-years lost, and age-specific associations in 1·25 million people. Lancet 2014;383:1899-911.ArticlePubMedPMC
- 25. Huang Z, Wang X, Ding X, Cai Z, Li W, Chen Z, et al. Association of age of metabolic syndrome onset with cardiovascular diseases: the Kailuan study. Front Endocrinol (Lausanne) 2022;13:857985.ArticlePubMedPMC
- 26. Meigs JB, Wilson PW, Fox CS, Vasan RS, Nathan DM, Sullivan LM, et al. Body mass index, metabolic syndrome, and risk of type 2 diabetes or cardiovascular disease. J Clin Endocrinol Metab 2006;91:2906-12.ArticlePubMed
- 27. Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults. Executive summary of the third report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, And Treatment of High Blood Cholesterol In Adults (Adult Treatment Panel III). JAMA 2001;285:2486-97.ArticlePubMedPMC
- 28. Alberti KG, Zimmet P, Shaw J. The metabolic syndrome: a new worldwide definition. Lancet 2005;366:1059-62.ArticlePubMedPMC
- 29. Definition and the diagnostic standard for metabolic syndrome: committee to evaluate diagnostic standards for metabolic syndrome. Nihon Naika Gakkai Zasshi 2005;94:794-809.PubMed
- 30. Fukasawa T, Tanemura N, Kimura S, Urushihara H. Utility of a specific health checkup database containing lifestyle behaviors and lifestyle diseases for employee health insurance in Japan. J Epidemiol 2020;30:57-66.ArticlePubMedPMC
- 31. Ministry of Health, Labour and Welfare. Guidance for Smooth Implementation of Specific Health Examination and Specific Health Guidance (version 4.2). Tokyo: MHLW; 2025.
- 32. Fujihara K, Igarashi R, Yamamoto M, Ishizawa M, Matsubayasi Y, Matsunaga S, et al. Impact of glucose tolerance status on the development of coronary artery disease among working-age men. Diabetes Metab 2017;43:261-4.ArticlePubMed
- 33. Fujihara K, Yamada-Harada M, Matsubayashi Y, Kitazawa M, Yamamoto M, Yaguchi Y, et al. Accuracy of Japanese claims data in identifying diabetes-related complications. Pharmacoepidemiol Drug Saf 2021;30:594-601.PubMed
- 34. Obesity: preventing and managing the global epidemic: report of a WHO consultation. World Health Organ Tech Rep Ser 2000;894:i-xii. 1-253.PubMed
- 35. Correa-Rodriguez M, Gonzalez-Ruiz K, Rincon-Pabon D, Izquierdo M, Garcia-Hermoso A, Agostinis-Sobrinho C, et al. Normal-weight obesity is associated with increased cardiometabolic risk in young adults. Nutrients 2020;12:1106.ArticlePubMedPMC
- 36. Vogel B, Acevedo M, Appelman Y, Bairey Merz CN, Chieffo A, Figtree GA, et al. The Lancet women and cardiovascular disease Commission: reducing the global burden by 2030. Lancet 2021;397:2385-438.ArticlePubMed
- 37. Du T, Fernandez C, Barshop R, Guo Y, Krousel-Wood M, Chen W, et al. Sex differences in cardiovascular risk profile from childhood to midlife between individuals who did and did not develop diabetes at follow-up: the Bogalusa heart study. Diabetes Care 2019;42:635-43.ArticlePubMedPMCPDF
- 38. Janssen I, Powell LH, Crawford S, Lasley B, Sutton-Tyrrell K. Menopause and the metabolic syndrome: the Study of Women’s Health Across the Nation. Arch Intern Med 2008;168:1568-75.ArticlePubMedPMC
- 39. Arora S, Stouffer GA, Kucharska-Newton AM, Qamar A, Vaduganathan M, Pandey A, et al. Twenty year trends and sex differences in young adults hospitalized with acute myocardial infarction. Circulation 2019;139:1047-56.ArticlePubMedPMC
- 40. Leifheit-Limson EC, D’Onofrio G, Daneshvar M, Geda M, Bueno H, Spertus JA, et al. Sex differences in cardiac risk factors, perceived risk, and health care provider discussion of risk and risk modification among young patients with acute myocardial infarction: the VIRGO study. J Am Coll Cardiol 2015;66:1949-57.PubMedPMC
- 41. Fujihara K, Khin L, Murai K, Yamazaki Y, Tsuruoka K, Yagyuda N, et al. Incidence and predictors of remission and relapse of type 2 diabetes mellitus in Japan: analysis of a nationwide patient registry (JDDM73). Diabetes Obes Metab 2023;25:2227-35.ArticlePubMed
- 42. Yang S, Zhou Z, Miao H, Zhang Y. Effect of weight loss on blood pressure changes in overweight patients: a systematic review and meta-analysis. J Clin Hypertens (Greenwich) 2023;25:404-15.ArticlePubMedPMC
- 43. Eckel N, Meidtner K, Kalle-Uhlmann T, Stefan N, Schulze MB. Metabolically healthy obesity and cardiovascular events: a systematic review and meta-analysis. Eur J Prev Cardiol 2016;23:956-66.ArticlePubMedPMCPDF
- 44. Lin H, Zhang L, Zheng R, Zheng Y. The prevalence, metabolic risk and effects of lifestyle intervention for metabolically healthy obesity: a systematic review and meta-analysis: a PRISMA-compliant article. Medicine (Baltimore) 2017;96:e8838.PubMedPMC
- 45. Li X, Li X, Lin H, Fu X, Lin W, Li M, et al. Metabolic syndrome and stroke: a meta-analysis of prospective cohort studies. J Clin Neurosci 2017;40:34-8.ArticlePubMed
- 46. Ji H, Kim A, Ebinger JE, Niiranen TJ, Claggett BL, Bairey Merz CN, et al. Sex differences in blood pressure trajectories over the life course. JAMA Cardiol 2020;5:19-26.ArticlePubMedPMC
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