This review examines strategies for the prevention and management of obesity, hypertension, type 2 diabetes mellitus and dyslipidaemia, conditions that are increasing in Singapore, as components of individualised health plans in 'Healthier SG' and beyond. We describe cardiometabolic disease prevention and management initiatives in Changi General Hospital (CGH), including collaborations with SingHealth Polyclinics, Active SG, Exercise is Medicine Singapore and community partners in the Eastern Community Health Outreach programme, and highlight advances in curable hypertension (e.g., primary hyperaldosteronism) and novel cardiovascular risk markers such as lipoprotein(a). We also outline technology-based interventions, notably the CGH Health Management Unit, which demonstrate the utility and convenience of telemedicine, and digital therapeutics in the form of apps that have been shown to improve treatment adherence and clinical outcomes. Individual empowerment, in partnership with community and healthcare providers and supported by research and innovation of care delivery, is key to building a healthier and stronger nation.
Humans ; Singapore ; Diabetes Mellitus, Type 2/therapy* ; Hypertension/therapy* ; Obesity/therapy* ; Dyslipidemias/therapy* ; Telemedicine ; Cardiovascular Diseases/prevention & control* ; Exercise ; Metabolic Diseases/prevention & control*

Asthma is a diverse disease that can be categorized into various phenotypes and endotypes, including obesity-re-lated asthma and allergic asthma. "Treatable traits (TTs)" represent a new approach to managing asthma. Asthma accompanied by dyslipidemia would be a distinct asthma phenotype that is becoming increasingly common. Therefore, dyslipidemia can potentially serve as a target for the management of asthma. Nevertheless, it remains highly under-researched compared to other observable traits. Gaining knowledge about the clinical and inflammatory characteristics, underlying mechanisms, and potential therapeutic medications for asthma with dyslipidemia is crucial for its effective management. This review aimed to provide a comprehensive overview of asthma with dyslipidemia, consolidating existing knowledge and ongoing research.
Humans ; Asthma/complications* ; Dyslipidemias/epidemiology*

OBJECTIVES: To clarify the causal relationship between the level of cytoplasmic unactivated mineralocorticoid receptor (MR) and the development of tubulointerstitial nephritis (TIN), and to evaluate the impact of MR on dyslipidemia, particularly secondary hyperlipemia, in patients with diabetic kidney disease. METHODS: We conducted a two-sample Mendelian randomization study using genome-wide association study (GWAS) summary data. Genetic variants associated with MR levels were selected as exposures, with TIN and lipid profiles [including low-density lipoprotein cholesterol (LDL-C), triglyceride, and high-density lipoprotein cholesterol] as outcomes. A two-step Mendelian randomization approach was used to assess TIN as a mediator, employing inverse variance weighted regression as the primary analysis, supplemented by Mendelian randomization-Egger, weighted median, and sensitivity analyses. RESULTS: Cytoplasmic unactivated MR level exhibited a significant causal association with a decreased risk of TIN (OR = 0.8598, 95% CI [0.7775-0.9508], P < 0.001). Although no significant causal relationship was identified between MR level and secondary hyperlipemia, a potential association of cytoplasmic unactivated MR level with lower LDL-C levels was observed (OR = 0.9901, 95% CI [0.9821-0.9983], P = 0.018). Additionally, TIN exhibited causal links with secondary hyperlipemia (OR = 1.0016, 95% CI [1.0002-1.0029], P = 0.020) and elevated LDL-C (OR = 1.0111, 95% CI [1.0024-1.0199], P = 0.012), particularly LDL-C in European males (OR = 1.0230, 95% CI [1.0103-1.0358], P < 0.001). Inverse Mendelian randomization analysis revealed causal relationships between TIN and genetically predicted triglyceride (OR = 0.7027, 95% CI [0.6189-0.7978], P < 0.001), high-density lipoprotein cholesterol (OR = 1.1247, 95% CI [1.0019-1.2626], P = 0.046), and LDL-C (OR = 0.8423, 95% CI [0.7220-0.9827], P = 0.029). Notably, TIN mediated 16.7% of the causal association between MR and LDL-C levels. CONCLUSIONS MR plays a critical role in the development of TIN and lipid metabolism, highlighting the potential of MR-antagonists in reducing renal damage and lipid metabolism-associated complications.
Humans ; Mendelian Randomization Analysis ; Nephritis, Interstitial/metabolism* ; Receptors, Mineralocorticoid/genetics* ; Lipid Metabolism/genetics* ; Genome-Wide Association Study ; Male ; Female ; Polymorphism, Single Nucleotide ; Dyslipidemias/metabolism*

OBJECTIVE: To explore the co-morbid influencing factors of postmenopausal osteoporosis(PMOP) and dyslipidemia, and to provide evidence-based basis for clinical co-morbidity management. METHODS: Based on the 2017 to 2018 Beijing community cross-sectional survey data, PMOP patients were included and divided into the dyslipidemia group and the uncomplicated dyslipidemia group according to whether they were comorbid with dyslipidemia. Demographic characteristics, living habits and disease history were collected through questionnaires, and bone mineral density and bone metabolism biomarkers (osteocalcin, blood calcium, serum typeⅠprocollagen N-terminal prepeptide, etc.) were detected on site. Co-morbidity risk factors were analyzed using binary logistic regression. RESULTS: Three hundred and twenty patients with PMOP were included, including the comorbid group (75 patients) and the uncomplicated group (245 patients). The results showed that history of cardiovascular disease [OR=1.801, 95%CI(1.003, 3.236), P=0.049], history of cerebrovascular disease [OR=2.923, 95%CI(1.460, 5.854), P=0.002], frying and cooking methods[OR=5.388, 95%CI(1.632, 17.793), P=0.006], OST results[OR=0.910, 95%CI(0.843, 0.983), P=0.016], and blood Ca results [OR=60.249, 95%CI(1.862, 1 949.926), P=0.021] were the influencing factors of PMOP complicated with dyslipidemia. CONCLUSION Focus should be placed on the influencing factors of PMOP and dyslipidemia co-morbidities, with emphasis on multidimensional assessment, combining lifestyle interventions with bone metabolism marker monitoring to optimize co-morbidity management.
Humans ; Dyslipidemias/epidemiology* ; Female ; Middle Aged ; Osteoporosis, Postmenopausal/metabolism* ; Aged ; Cross-Sectional Studies ; Risk Factors ; Bone Density

Objectives: We determined the clinical characteristics and prevalence of metabolic syndrome among adult Filipinos with overt hypothyroidism. Methodology: This is a cross-sectional study of 151 adults. Patients were recruited by sequential enrollment. Anthropometric and blood pressure measurements were performed followed by blood extraction for metabolic parameters and thyroid function tests. Clinical and laboratory characteristics were compared between patients with and without metabolic syndrome. Results: The prevalence of metabolic syndrome is 40.4% (95%CI: 32.5%, 48.7%). Patients with metabolic syndrome have a waist circumference of 88.4 ± 7.7 cm in females and 93.3 ± 9.0 cm in males. The median fasting blood glucose was 111.4 (52.2) mg/dL, median systolic blood pressure of 120 (30) mm Hg and diastolic blood pressure of 80 (20) mmHg, median serum triglycerides of 174.3 (114.2) mg/dL, median HDL-C of 42.3 (19.2) mg/dL and a proportion of patients with diabetes (23.0%) and hypertension (44.3%), respectively. The presence of increased waist circumference is the most prevalent component seen among hypothyroid patients. There were no differences in terms of age, sex, etiology of hypothyroidism and anti-TPO levels in those with and without metabolic syndrome. Conclusion The prevalence of metabolic syndrome in adult Filipinos with hypothyroidism is high. Emphasis must be placed on early screening using waist circumference and metabolic parameters among hypothyroid patients who are at high risk of developing metabolic syndrome.
Dyslipidemias ; Hypothyroidism ; Metabolic Syndrome ; Prevalence

Objective: To understand the relationship between secondhand smoke exposure and dyslipidemia among adults in Beijing and to provide a scientific basis for relevant intervention. Methods: Data were from Beijing Adult Non-communicable and Chronic Diseases and Risk Factors Surveillance Program in 2017. A total of 13 240 respondents were selected by multistage cluster stratified sampling method. The monitoring contents include a questionnaire survey, physical measurement, collection of fasting venous blood, and determination of related biochemical indicators. SPSS 20.0 software was used for the chi-square test and multivariate logistic regression analysis. Results: The prevalence of total dyslipidemia (39.27%), hypertriglyceridemia (22.61%), and high LDL-C (6.03%) were the highest among those exposed to daily secondhand smoke. Among the male respondents, the prevalence of total dyslipidemia (44.42%) and hypertriglyceridemia (26.12%) were the highest among those exposed to secondhand smoke daily. Multivariate logistic regression analysis after adjustment for confounding factors showed that compared with no exposure to secondhand smoke, the population with an average exposure frequency of 1-3 days per week had the highest risk of total dyslipidemia (OR=1.276, 95%CI: 1.023-1.591). Among the patients with hypertriglyceridemia, those exposed to secondhand smoke daily had the highest risk (OR=1.356, 95%CI: 1.107-1.661). Among the male respondents, those exposed to secondhand smoke for 1-3 days per week had a higher risk of total dyslipidemia (OR=1.366, 95%CI: 1.019-1.831), and the highest risk of hypertriglyceridemia (OR=1.377, 95%CI: 1.058-1.793). There was no significant correlation between the frequency of secondhand smoke exposure and the risk of dyslipidemia among female respondents. Conclusions: Secondhand smoke exposure in Beijing adults, especially men, will increase the risk of total dyslipidemia, especially hyperlipidemia. Improving personal health awareness and minimizing or avoiding exposure to secondhand smoke is necessary.
Adult ; Humans ; Female ; Male ; Tobacco Smoke Pollution/adverse effects* ; Beijing ; Dyslipidemias/epidemiology* ; Hypertriglyceridemia/epidemiology* ; Fasting

Objective: To analyze the relationship and consistency between indexes of different abnormal weight and dyslipidemia in adults in Beijing City. Methods: From August to December of 2017, 4 975 residents aged 18 to 79 years old in 5 districts of Beijing were randomly selected as subjects by using a multi-stage stratified cluster sampling method. Questionnaire, physical examination and laboratory tests were conducted. The prevalence of overweight/obesity, high body fat rate, central obesity, and high waist-to-height ratio was calculated. Partial correlation was used to analyze the correlation of blood lipid with body mass index (BMI), body fat rate, waist circumference and waist-height ratio. Logistic regression analysis for complex sampling was used to analyze the relationship between indexes of different abnormal weight and dyslipidemia after controlling for relevant risk factors, including age, sex, smoking status, drinking, insufficiency intake of vegetable and fruit, physical inactivity. Kappa value was computed to analyze the consistency between indexes of different abnormal weight. Results: The weighted prevalence of dyslipidemia was 30.48%, and it was higher in men than that in women (40.16% vs. 20.52%, P<0.01). The weighted rate of overweight/obesity, high body fat rate, central obesity, and high waist-to-height ratio was 56.65%, 47.52%, 42.48% and 59.45%, respectively. BMI, body fat rate, waist circumference and waist-to-height ratio were positively correlated with the level of total cholesterol, triglyceride, low-density lipoprotein cholesterol, and non-high-density lipoprotein cholesterol, and negatively correlated with high-density lipoprotein cholesterol. Logistic regression analysis for complex sampling showed that the high body fat rate (OR=1.67, 95%CI: 1.35-2.07), overweight/obesity (OR=1.65, 95%CI: 1.26-2.14) and high waist-to-height ratio (OR=1.46, 95%CI: 1.09-1.96) were associated with dyslipidemias. Kappa values of high body fat rate with overweight/obesity, high waist-to-height ratio and central obesity were 0.65, 0.53 and 0.58, respectively (P<0.05). Conclusion: In 2017, the prevalence of dyslipidemia in adults in Beijing City is high, especially in men. Overweight/obesity, high body fat rate and high waist-to-height ratio are associated with dyslipidemia. The high body fat rate is most associated with dyslipidemia.
Male ; Adult ; Humans ; Female ; Adolescent ; Young Adult ; Middle Aged ; Aged ; Overweight/complications* ; Obesity, Abdominal/epidemiology* ; Beijing ; Obesity/complications* ; Body Mass Index ; Risk Factors ; Cholesterol ; Dyslipidemias/epidemiology* ; Waist Circumference

BACKGROUND: Tri-ponderal mass index (TMI) has been reported to be a more accurate estimate of body fat than body mass index (BMI). This study aims to compare the effectiveness of TMI and BMI in identifying hypertension, dyslipidemia, impaired fasting glucose (IFG), abdominal obesity, and clustered cardio-metabolic risk factors (CMRFs) in 3- to 17-year-old children. METHODS: A total of 1587 children aged 3 to 17 years were included. Logistic regression was used to evaluate correlations between BMI and TMI. Area under the curves (AUCs) were used to compare discriminative capability among indicators. BMI was converted to BMI- z scores, and accuracy was compared by false-positive rate, false-negative rate, and total misclassification rate. RESULTS: Among children aged 3 to 17 years, the mean TMI was 13.57 ± 2.50 kg/m 3 for boys and 13.3 ± 2.33 kg/m 3 for girls. Odds ratios (ORs) of TMI for hypertension, dyslipidemia, abdominal obesity, and clustered CMRFs ranged from 1.13 to 3.15, higher than BMI, whose ORs ranged from 1.08 to 2.98. AUCs showed similar ability of TMI (AUC: 0.83) and BMI (AUC: 0.85) in identifying clustered CMRFs. For abdominal obesity and hypertension, the AUC of TMI was 0.92 and 0.64, respectively, which was significantly better than that of BMI, 0.85 and 0.61. AUCs of TMI for dyslipidemia and IFG were 0.58 and 0.49. When 85th and 95th of TMI were set as thresholds, total misclassification rates of TMI for clustered CMRFs ranged from 6.5% to 16.4%, which was not significantly different from that of BMI- z scores standardized according to World Health Organization criteria. CONCLUSIONS TMI was found to have equal or even better effectiveness in comparison with BMI in identifying hypertension, abdominal obesity, and clustered CMRFs TMI was more stable than BMI in 3- to 17-year-old children, while it failed to identify dyslipidemia and IFG. It is worth considering the use of TMI for screening CMRFs in children and adolescents.
Adolescent ; Child ; Child, Preschool ; Female ; Humans ; Male ; Body Mass Index ; Dyslipidemias ; East Asian People ; Hypertension ; Obesity, Abdominal ; Pediatric Obesity/diagnosis* ; Cardiometabolic Risk Factors

OBJECTIVE: To investigate the spatial patterns of the prevalence, awareness, treatment, and control rates of dyslipidemia at the provincial level in China. METHODS: A national and provincial representative cross-sectional survey was conducted among 178,558 Chinese adults in 31 provinces in mainland China in 2018-2019, using a multi-stage, stratified, cluster-randomized sampling design. Subjects, as households, were selected, followed by a home visit to collect information. Both descriptive and linear regression procedures were applied in the analyses. RESULTS: The overall prevalence of dyslipidemia was 35.6%, and wide geographic variations of prevalence, treatment, and control rates of dyslipidemia were identified among 178,558 eligible participants with a mean age of 55.1 ± 13.8 years. The highest-lowest difference regarding the provincial level prevalence rates were 19.7% vs. 2.1% for high low-density lipoprotein cholesterol, 16.7% vs. 2.5% for high total cholesterol, 35.9% vs. 5.4% for high triglycerides, and 31.4% vs. 10.5% for low high-density lipoprotein cholesterol. The treatment rate of dyslipidemia was correlated with the socio-demographic index ( P < 0.001), urbanization rate ( P = 0.01), and affordable basic technologies and essential medicines ( P < 0.001). CONCLUSION Prevailing dyslipidemia among the Chinese population and its wide geographic variations in prevalence, treatment, and control suggest that China needs both integrated and localized public health strategies across provinces to improve lipid management.
Humans ; Adult ; Middle Aged ; Aged ; Cross-Sectional Studies ; Prevalence ; East Asian People ; Dyslipidemias/prevention & control* ; China/epidemiology* ; Cholesterol, HDL ; Risk Factors ; Triglycerides

From January 2019 to December 2021, overweight and obese children who visited in health outpatient Center of Hunan Children's Hospital were studied to explore and analyze the rate, related factors and patterns of multimorbidity of overweight and obesity-related diseases in children in Hunan Province. Univariate and multivariate logistic regression models were used to analyze the multimorbidity-related factors of overweight and obesity-related diseases in children. Association rules (apriori algorithm) were used to explore the multimorbidity patterns of overweight and obesity-related diseases in children. A total of 725 overweight and obese children were included in this study. The multimorbidity rate of overweight and obesity-related diseases in children was 46.07% (334/725). Age, waist circumference, the frequency of food consumption such as hamburgers and fries and adding meals before bedtime were multimorbidity-related factors of overweight and obesity-related diseases in children. The multimorbidity associated with nonalcoholic fatty liver disease (NAFLD) was relatively common. The patterns with the top three support degrees were "NAFLD+dyslipidemia","NAFLD+hypertension" and "NAFLD+hyperuricemia". The patterns with the top three confidence and elevation degrees were "Hypertension+dyslipidemia => NAFLD","Hyperuricemia => NAFLD" and "NAFLD+hypertension => dyslipidemia".
Child ; Humans ; Overweight/complications* ; Non-alcoholic Fatty Liver Disease ; Pediatric Obesity/epidemiology* ; Hyperuricemia ; Multimorbidity ; Hypertension/epidemiology* ; Dyslipidemias ; Body Mass Index ; Risk Factors