The effect of metabolic health and obesity phenotypes on risk of hypertension: A nationwide population-based study using 5 representative definitions of metabolic health

Prevalence of combined metabolic health and weight status by various diagnosis criteria and association with cardiometabolic disease in Korean adults

The purpose of this study was to compare the cardiometabolic disease prevalence and risk factors between individuals categorized as metabolically unhealthy and healthy (MU vs. MH), with normal-weight and obesity (Nw vs. Ob), according to different established criteria for combined metabolic health and weight status; and to assess the optimal metabolic health diagnostic classifications to predict cardiometabolic disease risk factors. Data were obtained from the 2019 and 2020 Korean National Health and Nutrition Examination Surveys. We applied the nine accepted metabolic health diagnostic classification criteria. Statistical analysis was applied to frequency, multiple logistic regression, and ROC curve analysis. The prevalence of MHNw ranged from 24.6% to 53.9%, MUNw from 3.7% to 37.9%, MHOb from 3.4% to 25.9%, and MUOb from 16.3% to 39.1%. For hypertension, the MUNw had an increased risk ranging from 1.90 to 3.24 times compared with MHNw; MHOb ranged from 1.84 to 3.76 times; MUOb ranged from 4.18 to 6.97 times (all p < .05). For dyslipidemia, the MUNw had an increased risk ranging from 1.33 to 2.25 times compared with MHNw; MHOb ranged from 1.47 to 2.33 times; MUOb ranged from 2.31 to 2.67 times (all p < .05). For diabetes, the MUNw had an increased risk ranging from 2.27 to 11.93 times compared with MHNW; MHOb ranged from 1.36 to 1.95 times; MUOb ranged from 3.60 to 18.45 times (all p < .05). Our study findings revealed that AHA/NHLBI-02 and NCEP-02 can be the best diagnostic classifications criteria for cardiometabolic diseases risk factors.

Metabolically unhealthy phenotype in adults with normal weight: Is cardiometabolic health worse off when compared to adults with obesity?

The concept of metabolically healthy vs. unhealthy obese (MHO vs. MUO) was expanded to non-obese individuals as obesity-related comorbidities exist in a sub-group of normal weight (NW), i.e., MHNW vs. MUNW. It is unclear if MUNW differs from MHO with respect to cardiometabolic health.

PURPOSE

The purpose of this study was to compare cardiometabolic disease risk factors between MH vs. MU across weight status, NW, and obesity.

METHOD

A total of 8160 adults were included in the study from both the 2019 and 2020 Korean National Health and Nutrition Examination Surveys. Individuals with NW vs. obesity were further stratified as MH vs. MU by using AHA/NHLBI criterion for metabolic syndrome. A retrospective pair-matched analysis with respect to sex (male/female) and age ( ± 2 years) was performed to verify our total cohort analyses/results.

RESULTS

Despite a gradual increase in BMI and waist circumference from MHNW to MUNW to MHO to MUO, the surrogate estimates of insulin resistance and arterial stiffness were higher in MUNW vs. MHO. When compared to the MHNW, MUNW and MUO showed higher odds of hypertension (MUNW: 512%, MUO: 784%), dyslipidemia (MUNW: 210%, MUO: 245%), and diabetes (MUNW: 920%, MUO: 4012%), with no difference between MHNW and MHO.

CONCLUSION

Individuals with MUNW vs. MHO have greater vulnerability to cardiometabolic disease. Our data indicate that cardiometabolic risk is not solely dependent on adiposity, suggesting that early preventive efforts for chronic disease are needed for individuals with NW yet MU.

Sex-specific differences in the association between metabolically healthy overweight/obesity and the risk of hypertension in Chinese ethnic minorities

OBJECTIVE

To estimate and compare sex-specific differences between metabolically healthy overweight/obesity (MHOO) and the risk of hypertension among Dong, Bouyei, and Miao adults in southwest China.

METHODS

MHOO was diagnosed when the patient had a body mass index ≥24 kg/m² and the presence of ≤1 component of metabolic syndrome. The main outcome was the occurrence of hypertension after the diagnosis or measurement by a physician at the baseline survey. Multivariate logistic regression models were used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) between MHOO and the risk of hypertension.

RESULTS

We enrolled 16,433 Chinese Dong, Bouyei, and Miao adults. Using the metabolically healthy normal weight (MHNW) as a reference and after adjusting for confounders, the association between MHOO and the risk of hypertension was stronger in Dong (OR = 1.46, 95% CI: 1.07-2.00) and Miao (OR = 2.05, 95% CI: 1.48-2.85) men and did not exist in Bouyei men (OR = 1.14, 95% CI: 0.81-1.60). After adjusting for the age, the association between MHOO and the risk of hypertension was stronger in men than in women among Dong adults aged 30-59 years (OR = 1.64, 95% CI: 1.12-2.40) and did not differ between men and women among Dong adults aged 60-79 years or among Miao or Bouyei adults.

CONCLUSION

The results of this study demonstrated sex-specific differences in the association between MHOO and the risk of hypertension and that sex-specific differences further differed among Dong, Bouyei, and Miao adults.

Clinical characteristics and classification of Cameroonians with obesity and metabolically normal phenotype in the West region of Cameroon

The objective of this study was to classify and suggest an adequate definition of the metabolically normal phenotype among Cameroonians with obesity in the western Region of Cameroon. A cross-sectional study was conducted in the West Cameroon Region from August 2016 to August 2017. A total of 324 subjects with BMI >27 kg/m2, aged of 20 years and older, and not treated for cardiometabolic diseases were included in the study. Sociodemographic and clinical parameters of the subjects were collected. Four definitions of metabolic status were tested to suggest the definition that best identifies the subjects with obesity but metabolically normal phenotype (MNO) in the study. The prevalence of the MNO phenotype varied from 2.50% to 29.60% according to the definitions used. According to the individual definitions, the prevalence of the MNO phenotype was 29.60% according to Hinnouho, 16.00% according to Mbanya, 7.40% according to Meigs and 2.50% according to Widman. Markers of inflammatory profile (high sensitivity C-reactive protein and tumor necrosis factor-alpha), carbohydrate homeostasis (fasting glucose and homeostasis model assessment), markers of lipid profile (total cholesterol and triglyceride), systolic blood pressure, nitric oxide, adiposity indices (Waist circumference and waist to hip ratio) were significantly lower in MNO subjects for the majority of definitions (p < 0.05). The modified Hinnouho definition showed better specificity (60.90%) and sensitivity (12.10%) for an area under the ROC curve of 0.98. The degree of agreement was low between the different pairs of definition of the MNO phenotype (Kappa< 0.61). There is poor agreement between the different definitions of the MNO phenotype among Cameroonians with obesity. Therefore, the adoption of a universal definition of MNO phenotype should be proposed to facilitate the management of metabolic health in people with obesity.

Association of dietary phytochemical index with metabolically unhealthy overweight/obesity phenotype among Iranian women: A cross-sectional study

Background

Phytochemicals have been recently studied as adjuvants for the treatment of obesity. No study has investigated the association of phytochemical-rich foods with metabolically unhealthy overweight/obesity phenotype (MUOW/O). This study aimed to determine the association of dietary phytochemical index (DPI) with MUOW/O based on Karelis criteria among Iranian female adults.

Methods

In this cross-sectional study, a total of 228 overweight and obese women aged 18–48 years were included. Anthropometric measurements were evaluated for all participants. A validated 147-item Food Frequency Questionnaire (FFQ) was used for dietary assessment. DPI was calculated as [dietary energy derived from phytochemical-rich foods (kcal)/total daily energy intake (kcal)] × 100. Participants’ body composition and biochemical parameters of Karelis criteria [triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), insulin, and high-sensitivity C-reactive protein (hs-CRP)] were determined.

Results

The mean age of the study participants was 36.69 ± 9.20, and the mean DPI score was 26.23 ± 9.48 among participants with MUOW/O phenotype. After controlling for potential confounders, women in the highest tertile of DPI had lower odds for MUOW/O phenotype [odds ratio (OR): 0.23, 95% confidence interval (CI): 0.07–0.68, P = 0.008] compared to the lowest tertile. Among the components of Karelis criteria, homeostatic model assessment for insulin resistance (HOMA-IR) was significantly associated with MUOW/O phenotype in the fully adjusted model (OR: 0.29, 95% CI: 0.10–0.79, P = 0.01).

Conclusion

We found a significant association between DPI and MUOW/O phenotype in Iranian women. Prospective studies are needed to confirm these findings.

A systematic review of Tuina for cervical hypertension: A protocol for systematic review and meta-analysis

BACKGROUND

Cervical hypertension is a secondary form of hypertension with a high incidence rate. As the main etiology of cervical hypertension is related to cervical spondylosis, commonly used antihypertensive drugs have poor efficacy in the treatment of cervical spondylosis, and improving the symptoms of cervical spondylosis can effectively reduce blood pressure. Massage can effectively improve the symptoms of patients with cervical hypertension, but there has been no systematic review of massage treatment for cervical hypertension. This study aimed to evaluate the efficacy and safety of massage in patients with cervical hypertension.

METHODS

Before February 10, 2022, a systematic literature search was conducted using the following databases: Embase, SinoMed (previously called the Chinese Biomedical Database), China Science and Technology Journal Database for Chinese Technical Periodicals, Chinese National Knowledge Infrastructure, and Wanfang Data. Review Manager software (version 5.3) will be used for statistical analysis. Quality and risk assessments of the included studies were performed, and the outcome indicators of the trials were observed.

RESULTS

This meta-analysis further confirmed the beneficial effects of massage in patients with cervical hypertension.

CONCLUSION

This study investigated the efficacy and safety of massage therapy in patients with cervical hypertension, providing clinicians and patients with additional options for the treatment of this disease.

Relationship between the triglyceride-glucose index and risk of cardiovascular diseases and mortality in the general population: a systematic review and meta-analysis

BACKGROUND

The triglyceride-glucose (TyG) index is a new alternative measure for insulin resistance. This meta-analysis was conducted to assess the associations of the TyG index with the risks of cardiovascular diseases and mortality in the general population.

METHODS

The PubMed, Cochrane Library and Embase databases were searched for randomized controlled trials or observational cohort studies reporting associations of the TyG index with cardiovascular diseases and mortality from inception to April 16, 2022. Effect sizes were pooled using random-effects models. Robust error meta-regression methods were applied to fit nonlinear dose-response associations. Evidence quality levels and recommendations were assessed using the Grading of Recommendations Assessment, Development and Evaluation system (GRADE).

RESULTS

Twelve cohort studies (6 prospective and 6 retrospective cohorts) involving 6,354,990 participants were included in this meta-analysis. Compared with the lowest TyG index category, the highest TyG index was related to a higher incidence of coronary artery disease (CAD) (3 studies; hazard ratio [HR] = 2.01; 95% confidence interval [CI] 1.68-2.40; I2 = 0%), myocardial infarction (MI) (2 studies; HR = 1.36; 95% CI 1.18-1.56; I2 = 35%), and composite cardiovascular disease (CVD) (5 studies; HR = 1.46; 95% CI 1.23-1.74; I2 = 82%). However, there was no association between the TyG index and mortality (cardiovascular mortality [3 studies; HR = 1.10; 95% CI 0.82-1.47; I2 = 76%] or all-cause mortality [4 studies; HR = 1.08; 95% CI 0.92-1.27; I2 = 87%]). In the dose-response analysis, there was a linear association of the TyG index with the risk of CAD (Pnonlinear = 0.3807) or CVD (Pnonlinear = 0.0612). GRADE assessment indicated very low certainty for CVD, MI, cardiovascular mortality and all-cause mortality, and moderate certainty for CAD.

CONCLUSIONS

Based on our current evidence, a higher TyG index may be associated with an increased incidence of CAD (moderate certainty), MI (very low certainty) and CVD (very low certainty) in the general population. There is a potential linear association of the TyG index with CAD and the composite CVD incidence. Further prospective studies (especially in non-Asians) are needed to confirm our findings.

Mediator or moderator? The role of obesity in the association between age at menarche and blood pressure in middle-aged and elderly Chinese: a population-based cross-sectional study

OBJECTIVE

We investigated the moderation/mediation between the age of menarche and obesity parameters in predicting blood pressure (BP) in middle-aged and elderly Chinese.

DESIGN

Our study is a population-based cross-sectional study.

SETTING

Participants in this study came from the China Health and Retirement Longitudinal Study (CHARLS).

PARTICIPANTS

The analytical sample included 4513 participants aged 45-96 years.

MAIN OUTCOME MEASUREMENTS

Data were selected from the CHARLS, a cross-sectional study. Between-group differences were evaluated using χ², t-test and one-way analysis of variance. The trend of related variables by characteristics was also tested using contrast analysis, as appropriate. Then, correlations between characteristics, moderator, mediator, and independent and dependent variables were used by Spearman's correlation test and Pearson's correlation test. Finally, the mediation analysis was performed by model 4 in PROCESS V3.3 macro for SSPSS, and moderation analysis was used by model 1 for assessment. All covariates were adjusted in the moderation or mediation models.

RESULTS

In the correlation analysis, body mass index (BMI) and waist circle (WC) level were positively correlated with both systolic blood pressure (SBP) and diastolic blood pressure (DBP) in women (BMI and DBP: r=0.221, p<0.001; WC and DBP: r=0.183, p<0.001; BMI and SBP: r=0.129, p<0.001; WC and SBP: r=0.177, p<0.001). Age of menarche was negatively correlated with DBP (r=-0.060, p<0.001). However, the age of menarche was not significantly correlated with SBP (r=-0.014, p=0.335). In the moderator analysis, after controlling for the potential confounders, the interaction term of obesity parameters×age of menarche was not significant for predicting either DBP (BMI: B=0.0260, SE=0.0229, p=0.2556, 95% CI -0.0189 to 0.071; WC: B=0.0099, SE=0.0074, p=0.1833, 95% CI -0.0047 to 0.0244) or SBP (BMI: B=0.0091, SE=0.0504, p=0.8561, 95% CI -0.0897 to 0.108; WC: B=-0.0032, SE=0.0159, p=0.8427, 95% CI -0.0343 to 0.028). All correlations were significant correlation between age of menarche, obesity parameters and BP except the path of the menarche age→SBP (with the addition of the BMI indicator: β=-0.0004, B=-0.0046, p=0.9797, 95% CI -0.3619 to 0.3526; with the addition of the WC indicator: β=0.0004, B=0.0044, p=0.9804, 95% CI -0.3439 to 0.3526) in crude model. In general, after controlling for potential confounders, BMI (DBP: β=-0.0471, B= -0.2682, p=0.0021, 95% CI -0.4388 to -0.0976; SBP: β=-0.0515, B=-0.6314, p<0.001, 95% CI -0.9889 to -0.2739) and WC (DBP: β=-0.0474, B= -0.2689, p<0.001, 95% CI -0.4395 to -0.0984; SBP: β=-0.0524, B=-0.6320, p<0.001, 95% CI -0.9832 to -0.2807) partly mediated the relationship between age of menarche and BP.

CONCLUSIONS

The interaction term of obesity parameters×age of menarche was not significant for predicting either DBP or SBP in women. Moreover, obesity parameters partly mediated the relationship between the age of menarche and BP.

Data-driven identification of complex disease phenotypes

Disease interaction in multimorbid patients is relevant to treatment and prognosis, yet poorly understood. In the present work, we combine approaches from network science, machine learning and computational phenotyping to assess interactions between two or more diseases in a transparent way across the full diagnostic spectrum. We demonstrate that health states of hospitalized patients can be better characterized by including higher-order features capturing interactions between more than two diseases. We identify a meaningful set of higher-order diagnosis features that account for synergistic disease interactions in a population-wide (N = 9 M) medical claims dataset. We construct a generalized disease network where (higher-order) diagnosis features are linked if they predict similar diagnoses across the whole diagnostic spectrum. The fact that specific diagnoses are generally represented multiple times in the network allows for the identification of putatively different disease phenotypes that may reflect different disease aetiologies. At the example of obesity, we demonstrate the purely data-driven detection of two complex phenotypes of obesity. As indicated by a matched comparison between patients having these phenotypes, we show that these phenotypes show specific characteristics of what has been controversially discussed in the medical literature as metabolically healthy and unhealthy obesity, respectively. The findings also suggest that metabolically healthy patients show some progression towards more unhealthy obesity over time, a finding that is consistent with longitudinal studies indicating a transient nature of metabolically healthy obesity. The disease network is available for exploration at https://disease.network/.

The patterns of lifestyle, metabolic status, and obesity among hypertensive Korean patients: a latent class analysis

OBJECTIVES

This study aimed to identify latent classes in hypertensive patients based on the clustering of factors including lifestyle risk factors, metabolic risk factors, and obesity in each sex.

METHODS

This cross-sectional study included 102,780 male and 103,710 female hypertensive patients who underwent health check-ups at 16 centers in Korea, in 2018. A latent class analysis approach was used to identify subgroups of hypertensive patients. Multinomial logistic regression was performed to examine the association between latent classes and comorbidities of hypertension.

RESULTS

A four-class model provided the best fit for each sex. The following latent classes were identified: Class I (male: 16.9%, female: 1.7%; high risk of lifestyle behaviors [HB] with metabolic disorders and obesity [MO]), Class II (male: 32.4%, female: 47.1%; low risk of lifestyle behaviors [LB] with MO), Class III (male: 15.3%, female: 1.8%; HB with metabolic disorders and normal weight [MNW]), Class IV (male: 35.5%, female: 49.4%; LB with MNW). Lifestyle patterns in the latent classes were classified as high-risk or low-risk according to smoking and high-risk drinking among male, and presented complex patterns including physical inactivity alone or in combination with other factors, among female. Stage 2 hypertensive or diabetic individuals were likely to belong to classes including obesity (HB-MO, LB-MO) in both sexes, and additionally belonged to the HB-MNW class in male.

CONCLUSIONS

Metabolic disorders were included in all latent classes, with or without lifestyle risk factors and obesity. Hypertensive females need to manage obesity, and hypertensive males need to manage lifestyle risk factors and obesity. Sex-specific lifestyle behaviors are important for controlling hypertension.

All-cause mortality in metabolically healthy individuals was not predicted by overweight and obesity

BACKGROUND

Metabolically healthy obesity (MHO) and metabolically healthy overweight (MH-OW) have been suggested to be important and emerging phenotypes with an increased risk of cardiovascular disease (CVD). However, whether MHO and MH-OW are associated with all-cause mortality remains inconsistent.

METHODS

The association of MHO and MH-OW and all-cause mortality was determined in a Chinese community-based prospective cohort study (the Kailuan study), including 93,272 adults at baseline. Data were analyzed from 2006 to 2017. Participants were categorized into 6 mutually exclusive groups, according to BMI and metabolic syndrome (MetS) status. The primary outcome was all-cause death, and accidental deaths were excluded.

RESULTS

During a median follow-up of 11.04 years (interquartile range, 10.74–11.22 years), 8977 deaths occurred. Compared with healthy participants with normal BMI (MH-NW), MH-OW participants had the lowest risk of all-cause mortality (multivariate-adjusted HR [aHR], 0.926; 95% CI, 0.861–0.997), whereas there was no increased or decreased risk for MHO (aHR, 1.009; 95% CI, 0.886–1.148). Stratified analyses and sensitivity analyses further validated that there was a nonsignificant association between MHO and all-cause mortality.

CONCLUSIONS

Overweight and obesity do not predict increased risk of all-cause mortality in metabolic healthy Chinese individuals.

FUNDING

National Natural Science Foundation of China (NSFC; 81673247, 81872682 and 81773527), the NSFC Joint Project, and the Australian National Health and Medical Research Council (NHMRC; NSFC 81561128020-NHMRC APP1112767).

Obesity does not predict increased risk of all-cause mortality in metabolic healthy Chinese individuals.

Prevalence and clinical characteristics of metabolically unhealthy obesity in an Iranian adult population

PURPOSE

The incidence of obesity is globally increasing and it is a predisposing factor for morbidity and mortality. This study assessed the prevalence of metabolically unhealthy (MU) individuals and its determinants according to body mass index (BMI).

MATERIALS AND METHOD

In our cross-sectional study, 891 persons aged 30 years or older participated. Participants were classified as obese (BMI ≥30 kg/m²), overweight (BMI 25-<30 kg/m² and normal weight (BMI <25 kg/m²). Metabolic health status was defined using four existing cardio-metabolic abnormalities (elevated blood pressure, elevated serum concentrations of triglyceride and fasting glucose and a low serum concentration of high density lipoprotein cholesterol). Then, two phenotypes were defined: healthy (existence of 0-1 cardio-metabolic abnormalities) and unhealthy (presence of 2 or more cardio-metabolic abnormalities).

RESULT

Overall, 10.9% (95% confidence interval (CI): 8.8-13.0) and 7.2% (95% CI: 5.5-8.9) of participants were MU obese and metabolically healthy obese, respectively. The prevalence of MU was higher in overweight (55.6%; 95% CI: 50.6-60.6, p<0.001) and obese (60.2%; 95% CI: 52.8-67.6, p=0.001) subjects than in individuals with a normal weight (37.5%; 95% CI: 29.4-42.6). Multiple logistic regression analysis showed an association of a MU state with age and dyslipidaemia in the BMI subgroups and with female sex in the normal weight individuals.

CONCLUSION

The prevalence of a MU state increased with increasing BMI. Ageing and dyslipidaemia were associated with an unhealthy metabolic state in normal weight, overweight and obese subjects and with the female sex in normal weight subjects.