National Cholesterol Education Program Research Articles

The Independent Association Between Changes in Physical Activity Participation Time and Dyslipidemia Risk

Background and AimThis study aimed to examine the independent association between changes in participation time across different types of physical activities and dyslipidemia. Methods and ResultsThe study utilized data from a large-scale cohort survey of Koreans, comprising a total of 2,543 participants recruited during 2011-2012 and 2013-2014. Physical activity participation times by type were assessed using validated questionnaires, and changes in these participation times over two years were categorized into four groups(Consistently Inactive, Formerly Active, Newly Active, and Consistently Active). Dyslipidemia was classified according to the National Cholesterol Education Program Adult Treatment Panel III criteria. Multiple logistic regression analysis was used to calculate odds ratios (OR) and 95% confidence intervals (CI) to assess the association between changes in physical activity participation times and dyslipidemia. The analysis revealed that, when adjusting for sex and age, the Consistently Active group had a 40% lower odds ratio (OR=0.60, 95% CI=0.45, 0.81) of dyslipidemia compared to the Consistently Inactive group. Similar results were observed after adjusting for various confounding factors. Also, being newly active(OR=0.75, 95% CI=0.58, 0.97) or consistently active(OR=0.63, 95% CI=0.41, 0.97) in moderate-intensity physical activity, as well as being consistently active(OR=0.76, 95% CI=0.61, 0.95), in walking, independently reduced the risk of dyslipidemia after adjusting for various confounding variables. ConclusionsMaintaining a high level of physical activity was associated with a reduced risk of dyslipidemia. Therefore, national recommendations should focus on sustaining and increasing physical activity levels to manage dyslipidemia effectively.

Metabolic syndrome and related factors in Cameroonian women under contraceptive use.

Contraceptive is a device or drug that prevents a woman from becoming pregnant. Some types of contraceptive can cause a myriad of secondary effects such as overweight, increase of blood pressure triglycerides, and glucose intolerance. The combination of these secondary effects could, in the long term, develop metabolic syndrome in these women. The purpose of this study was to determine the prevalence of metabolic syndrome and related factors in Cameroonians women on contraceptives. This was a cross-sectional study that included 231 Cameroonians fasting women from 18 to 49 years of age, on contraceptives. Sociodemographic, lifestyle, anthropometric and biochemical characteristics were collected. Metabolic syndrome was diagnosed using the criteria of the National Cholesterol Education Program- Adult Treatment Panel III. After validation of the data, statistical analysis was performed using Epi-Info software version 7.2.2.16 and the statistical level of significance was set at 5.0%. 231 were using a modern contraceptive method, 28 were not using a contraceptive method, and 12 were non-consenting. The contraceptive method use rate was 89.19% and the most commonly used method was injectable contraception (49.35%). According to National Cholesterol Education Program criteria, almost 38.96% of these women were overweight and 50.65% had a serum high density lipoproteins cholesterol level of less than 0.50 g/L. Among women on contraceptives, the prevalence of metabolic syndrome was 22.08%. However, there was no significant association between contraceptive use and the occurrence of metabolic syndrome (p = 0.63). Contraceptive use was certain in all the participants, it's reported that, according to the NCEP-ATPIII a prevalence of 22.08% of metabolic syndrome among women using modern contraceptive methods in Douala, Republic of Cameroon. The high-risk groups were women using injectable method. Therefore, lipid profiles should be assessed in those women in order to manage them better.

The Occurrence of Metabolic Syndrome In Patients With Psoriasis

Objective: To determine occurrence of metabolic syndrome in patients of Psoriasis and to highlight any gender-based differences. Study Design: Cross-sectional study design. Place and Duration of Study: Pak-Emirates Military Hospital, Rawalpindi. Our research was conducted from July to December 2020 (6 months). Patients and Methods: A total of 80 patients diagnosed with psoriasis were selected using non-probability consecutive sampling. Informed written consent was obtained from each patient and a questionnaire was filled. Variables such as blood pressure, waist circumference, body surface area covered by psoriasis, and Psoriasis Area Severity Index were recorded on initial visit. Fasting blood sugar, serum triglyceride and HDL cholesterol levels were advised. Patients were diagnosed to have metabolic syndrome if 3 or more of the 5 criteria for the modified version of the National Cholesterol Education Program Adult Panel III were met. Results: There were 62 male & 18 female patients. A total of 39 patients (48.8%) met the criteria for metabolic syndrome. Amongst these, 26/62(41.9%) males & 13/18(72.2%) females fulfilled the criteria. The mean BMI of males was 26.0 and those of females was 28.3 & their comparison demonstrated a noteworthy difference (p=0.04). A statistically significant (p=0.038) positive correlation (r) of 0.233 was observed between body surface area and BMI. Conclusion: Metabolic syndrome is seen frequently in patients of Psoriasis. Female patients have a significant frequency of metabolic syndrome and tend to have a higher BMI than males.

Metabolic phenotype and risk of obesity-related cancers in the Women's Health Initiative.

Body mass index (BMI) may misclassify obesity-related cancer (ORC) risk, as metabolic dysfunction can occur across BMI levels. We hypothesized that metabolic dysfunction at any BMI increases ORC risk compared to normal BMI without metabolic dysfunction. Postmenopausal women (n=20,593) in the Women's Health Initiative with baseline metabolic dysfunction biomarkers (blood pressure, fasting triglycerides, high-density lipoprotein-cholesterol, fasting glucose, Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) and high sensitive C-reactive protein (hs-CRP)) were included. Metabolic phenotype (metabolically healthy normal weight (MHNW), metabolically unhealthy normal weight (MUNW), metabolically healthy overweight/obese (MHO), metabolically unhealthy overweight/obese (MUO)) was classified using four definitions of metabolic dysfunction: (1) Wildman criteria, (2) National Cholesterol Education Program (NCEP) Adult Treatment Panel III (ATP III), (3) HOMA-IR, and (4) hs-CRP. Multivariable Cox proportional hazards regression, with death as a competing risk, was used to assess the association between metabolic phenotype and ORC risk. After a median (IQR) follow-up duration of 21 (IQR 15-22) years, 2,367 women developed an ORC. The risk of any ORC was elevated among MUNW (HR 1.12, 95% CI: 0.90-1.39), MHO (HR 1.15, 95% CI: 1.00-1.32), and MUO (HR 1.35, 95% CI: 1.18-1.54) compared with MHNW using Wildman criteria. Results were similar using ATP III criteria, hs-CRP alone, or HOMA-IR alone to define metabolic phenotype. Individuals with overweight or obesity with or without metabolic dysfunction were at higher risk of ORCs compared with metabolically healthy normal weight individuals. The magnitude of risk was greater among those with metabolic dysfunction, although the confidence intervals of each category overlapped.

Predictive ability of anthropometric indices for risk of developing metabolic syndrome: a cross-sectional study.

To determine the discriminatory ability of different anthropometric indicators of body fat percentage for diagnosing metabolic syndrome (MetS) in a Peruvian sample. This was a cross-sectional, non-experimental, diagnostic accuracy study. Anthropometric and biochemical data for 948 participants were analyzed. Waist circumference (WC), body mass index, relative fat mass (RFM), conicity index, body roundness index (BRI), waist-to-height ratio (WHtR), and A Body Shape Index were assessed for their MetS discriminatory ability. The National Cholesterol Education Program's Adult Treatment Panel III criteria were used to diagnose MetS. Receiver operating characteristic curves and area under the curve (AUC) were used to determine the predictive power of each anthropometric measurement to diagnose MetS. In both sexes, RFM, BRI, and WHtR showed the same predictive ability to diagnose MetS. In women, indicators incorporating WC showed high discriminatory ability: RFM, BRI, and WHtR (all AUC: 0.869, 95% confidence interval [CI]: 0.828-0.910). In men, WC had the highest AUC (0.829, 95% CI: 0.793-0.866). In both sexes, RFM, WC, BRI, and WHtR were the best predictors of MetS diagnosis. This is the first study to identify RFM as a potentially useful clinical predictor of MetS in a Peruvian sample of educational workers.

Comparison of the prevalence of metabolic syndrome between individuals with spinal cord injury and the general population based on the cutoff values of abdominal obesity

BackgroundMetabolic syndrome (MetS) is a cluster of cardiovascular disease (CVD) risk factors. Accurate diagnosis, in spinal cord injury (SCI) patients, is vital for effective CVD prevention. ObjectiveThis study aimed to identify factors related to MetS prevalence by comparing MetS prevalence trends in SCI and the general population (GP) and to examine differences in MetS prevalence in patients with SCI according to the cutoff reference value for abdominal obesity. MethodsThis retrospective cohort study analyzed data from the National Health Insurance Corporation from 2015 to 2019. MetS was defined using the National Cholesterol Education Program criteria with an adjusted waist circumference of 81.3 cm for patients with SCI. Data were collected on age, gender, smoking, alcohol consumption, BMI, waist circumference, lipid profiles, blood pressure, fasting glucose, and socioeconomic status. Each year, SCI patients (n=3,140, n=3,201, n=3,503, n=1,590, n=1,544) were matched with GP individuals (m=31,400, m=32,040, m=35,030, m=15,900, m=15,440). ResultsOver 5 years, MetS prevalence increased in both groups, consistently higher in the SCI group. Older age and lower income were risk factors in both groups (p<0.05). Smoking and alcohol intake were significant only in the GP (p<0.0001). Using the adjusted obesity criterion, MetS prevalence was 1.4 times higher in SCI patients than in the GP (p<0.0001). ConclusionsExclusively relying on GP criteria for diagnosing MetS in patients with SCI may lead to an underestimation of MetS prevalence and overlooked opportunities for CVD prevention. Therefore, the development of diagnostic and preventive strategies for MetS considering SCI characteristics is needed.

Increased dementia risk in patients with Parkinson's disease attributed to metabolic syndrome.

Metabolic syndrome (MetS) manifests resembling pathophysiological mechanisms with Parkinson's disease (PD). Current research on the overall population has emphasized MetS as a freestanding risk factor for cognition. This research aims to explore the impact of MetS on cognition in Parkinson's patients. We involved subjects identified as having early-stage PD patients. The MetS was diagnosed dependent on parameters overviewed in the National Cholesterol Education Program's Adult Treatment Panel III. The clinical severity and stages in patients with PD were dependent on the disease rating scales. The cognition was evaluated by the Turkısh version of the Montreal Cognitive Assessment Scale (MoCA-TR). The cases were categorized according to cognitive failure: mild cognitive impairment in PD (PD-MCI), and PD dementia (PDD). Metabolic syndrome was present in 39.6% of the participants. 22.0% of patients were in the normal cognition, 29.1% in the PD-MCI group, and 48.9% in the PD-D group. The cognitive scores in patients with MetS is considerably lower than MetS negative group. A statistically notable inverse association was detected between fasting blood glucose levels and the visual-spatial/executive functions, naming, language, and orientation scores. The multivariate logistic regression analysis showed individuals with MetS were found to have an 11.308 times higher risk of PD-D (odds ratio [OR]: 11,3, 95% confidence interval [CI]: 1.61-79.2 ). We discerned the occurrence of MetS in PD raises the possibility of advancing dementia. This suggests that considering MetS in this patient group could contribute to the effective management of dementia.

Red cell distribution width/albumin ratio as a marker for metabolic syndrome: findings from a cross-sectional study

BackgroundMetabolic syndrome (MetS) imposes a significant health burden on patients globally. Chronic low-grade inflammation is pivotal in the onset and progression of this condition. However, the role of the novel inflammatory marker, red cell distribution width to albumin ratio (RAR), in the development of MetS remains unclear.MethodsThis population-based cross-sectional study utilized data from the 2011–2020 National Health and Nutrition Examination Survey (NHANES). Participants included individuals over 18 years old with complete data on serum albumin concentration, red cell distribution, and MetS and its components. MetS was defined using the criteria established by the National Cholesterol Education Program Adult Treatment Panel III. The calculation formula for RAR is: RAR = Red cell distribution width (%)/serum albumin (g/dL). Study participants were stratified into four quartiles based on RAR levels. Logistic regression analysis and subgroup analysis were employed to explore the independent interaction between RAR and MetS, as well as investigate the relationship between RAR levels and the specific components of MetS. Finally, the receiver operating characteristic (ROC) curve was used to assess the predictive efficacy of RAR for MetS.ResultsA total of 4899 participants were included in this study, comprising 2450 males and 2449 females; 1715 individuals (35.01%) were diagnosed with MetS. As the quartile of RAR increased, the proportion of individuals with MetS also increased. Spearman correlation analysis indicated a positive correlation between RAR and the insulin resistance index HOMA-IR. Logistic regression analysis, adjusting for multiple confounding factors, showed that each standard deviation increase in RAR was associated with a significant 1.665-fold increase (95% CI, 1.404–1.975; P < 0.001) in the odds of MetS prevalence. In logistic regression analysis stratified by quartiles of RAR, the risks of MetS in Q1-Q4 were 1.372 (95% CI, 1.105–1.704; P = 0.004), 1.783 (95% CI, 1.434–2.216; P < 0.001), and 2.173 (95% CI, 1.729–2.732; P < 0.001), respectively. Subgroup analyses and interaction tests demonstrated that gender, age, race, education, smoking status, and physical activity modified the positive association between RAR and MetS (p for interaction < 0.05). Additionally, analysis of the area under the receiver operating characteristic (ROC) curve showed that the optimal cutoff value for predicting MetS using RAR was 3.1348 (sensitivity: 59.9%; specificity: 60.6%; and AUC: 0.628).ConclusionsIncreasing RAR levels are associated with a higher risk of MetS. Therefore, greater attention should be given to patients with high RAR levels for improved prevention and treatment of MetS.

Prevalence of Metabolic Syndrome and Its Association With Clinical Correlates and Caregiver Burden in Patients With Bipolar Disorder at a Tertiary Hospital.

Metabolic syndrome is a cluster of metabolic abnormalities, including obesity, insulin resistance, dyslipidemia, and hypertension. The prevalence of metabolic syndrome is recognized to be high among patients with bipolar disorder. This study is relevant given the limited number of Indian studies exploring the prevalence of metabolic syndrome and its association with clinical correlates in bipolar patients. This research aims to inform clinicians about the need for timely interventions in diagnosing and managing metabolic syndrome in this population, which may contribute to significant morbidity and poor clinical outcomes. A cross-sectional study was conducted in the inpatient and outpatient units of the psychiatry department involving 83 subjects diagnosed with bipolar disorder. Informed consent was obtained, and sociodemographic and clinical data were collected. The National Cholesterol Education Program (NCEP)-Adult Treatment Panel III (ATP III) criteria were used to diagnose metabolic syndrome. The Young Mania Rating Scale (YMRS) and Hamilton Depression Rating Scale (HAM-D) were applied to assess the severity of manic and depressive episodes, respectively. The Suicide Behaviors Questionnaire-Revised (SBQ-R) was used to assess suicidal risk, and the Burden Assessment Schedule (BAS) was utilized to evaluate caregiver burden. Statistical significance was tested using the independent-sample t-test and Mann-Whitney U test for continuous variables, along with the chi-square test for categorical variables. A p-value of <0.05 was considered significant. Metabolic syndrome was noted in 49 (59%) patients with bipolar disorder. Subjects with metabolic syndrome exhibited more severe manic episodes, had a higher number of lifetime episodes, were more likely to have a history of suicide attempts, and showed increased suicidal risk. Patients on polypharmacy were at higher risk of developing metabolic syndrome. Caregivers of patients with metabolic syndrome reported greater caregiver burden compared to those without the condition. There is a high prevalence of metabolic syndrome in patients with bipolar disorder. Metabolic syndrome is associated with adverse prognostic factors, including a higher number of lifetime episodes, greater severity of manic episodes, and increased suicidality. This underscores the necessity for routine monitoring of blood and anthropometric parameters.

Metabolic Syndrome, Adipokines, and Response to Advanced Therapies in Rheumatoid Arthritis.

We determined if metabolic syndrome, its components, and adipokines (adiponectin, leptin, Fibroblast Growth Factor-21) were associated with response to advanced therapies among patients with rheumatoid arthritis (RA). This study included participants with RA initiating either TNFi or non-TNFi biologic therapies from the Comparative Effectiveness Registry to studyTherapies forArthritis andInflammatory Conditions(CERTAIN) cohort within the CorEvitas registry. Metabolic syndrome was defined according to the National Cholesterol Education Program Adult Treatment Panel III definition. Adipokines were assessed on stored samples from a sub-sample of responders and non-responders (N=200). The primary outcome was the achievement of a change as large as the minimal clinically important difference (MCID) for the Clinical Disease Activity Index (CDAI) at 6 months. Among 2,368 participants, 687 (29%) had metabolic syndrome. Metabolic syndrome was associated with lower odds of achieving CDAI MCID [OR (95% CI): 0.69 (0.56,0.86) p=0.001] with a dose-dependent decrease in response rate according to the number of components present. Model fit was superior for metabolic syndrome compared to BMI. Associations between metabolic syndrome and MCID achievement were similar between patients receiving TNFi [OR (95% CI): 0.65 (0.49,0.87) p=0.003] v. non-TNF therapies [OR (95% CI): 0.76 (0.55,1.04) p=0.08)] (p-for-interaction=0.49). Adipokines were not associated with MCID achievement. Metabolic syndrome is associated with lower response rates with the initiation of an advanced therapy in RA, with similar effects for both TNFi and non-TNFi agents. Adipokines were strongly associated with metabolic syndrome but were not associated with clinical response.

The association between dietary carbohydrate intake and the risk of hyperlipidemia among reproductive-aged women in the US: A cross-sectional study.

The association between dietary carbohydrate intake and hyperlipidemia remained incompletely understood. This study aimed to explore the association between dietary carbohydrate intake and the risk of hyperlipidemia among reproductive-aged women in the US. The study utilized data from the National Health and Nutrition Examination Survey (NHANES) conducted from 2005 to 2020. Dietary intake information was assessed via interviews using 24-hour dietary recall interviews, and hyperlipidemia diagnosis adhered to the National Cholesterol Education Program guidelines. Univariate and multivariate logistic regression analyses, along with restricted cubic splines (RCS) and stratified analyses, were conducted to investigate the association between dietary carbohydrate intake and the risk of hyperlipidemia. A total of 6,791 women of reproductive age, with a mean age of 34.87 (±8.57) years, were included in the final analysis. In the multivariate logistic regression model adjusting for covariates, a higher percentage of energy from carbohydrate was positively correlated with the risk of hyperlipidemia (adjusted odds ratio (AOR): 1.014, 95% CI: 1.004-1.024). Analyzing the percentage of energy from carbohydrate as a categorical variable, compared to the lowest quartile, the third quartile (AOR: 1.263, 95% CI: 1.031-1.546) and the highest quartile (AOR: 1.411, 95% CI: 1.083-1.839) were associated with increased hyperlipidemia risk. Additionally, a linear relationship (P for nonlinearity = 0.088) existed between the percentage of energy from carbohydrate and the risk of hyperlipidemia, with an inflection point identified at 49.64. This study found that elevated dietary carbohydrate intake was associated with an increased the risk of hyperlipidemia in reproductive-aged women. These findings implied that reproductive-aged women should pay closer attention to reducing their carbohydrate intake.

A-217 Estimation of the Prevalence and the Patterns of Dyslipidemia in the Korean population

Abstract Background Dyslipidemia is one of the four major risk factors for the development of cardiovascular disease, along with hypertension, smoking, and diabetic mellitus. This countrywide study aimed to determine the prevalence and patterns of dyslipidemia and to describe their characteristics using data from the Korean population visiting local clinics. Methods We retrospectively reviewed the lipid profiles (total cholesterol (TC), low-density lipoprotein cholesterol (LDLC), high-density lipoprotein cholesterol (HDLC), and triglycerides (TG)) and fasting plasma glucose (FPG) test results from Korean patients visiting local clinics during December 2023. Dyslipidemia was defined as having one or more of TC ≥200 mg/dl, LDLC ≥100 mg/dl, HDLC &amp;lt;40 mg/dl for males and &amp;lt;50 mg/dl for females, or TG ≥150 mg/dl (National Cholesterol Education Program, Adult Training Program III, 2002). Glucose levels are considered hyperglycemic if blood glucose ≥126 mg/dl. The subjects comprised 1,232 patients who visited 57 local clinics nationwide were included. Lipid profile tests (except LDLC) and FPG were performed on Hitachi008AS automatic biochemistry analyzer and the LDLC test was calculated by the Friedewald equation. Data for TG ≥400 mg/dL were excluded. Results The study subject population comprised 610 males and 622 females aged 2 to 91 years. The overall prevalence of dyslipidemia was 53.3% (657/1,232), with 49.3% (301/657) males and 57.2 (356/657) females (p&amp;lt;0.001). TC, LDLC, and TG were high in 14.5% (95/657), 33.9% (184/657), and 23.6% (223/657) of patients, respectively; HDLC was low in 28.0% (155/657). The prevalence of dyslipidemia by age group was as follows: 2 to 19 years (36.4%, 4/11); 20 to 29 years (66.7%, 12/18); 30 to 39 years (52.5%, 52/99); 40 to 49 years (61.5%, 131/213); 50 to 59 years (57.0%, 167/293); 60 to 69 years (50.1%, 168/335); 70 to 79 years (48.4%, 91/188); 80 years or older, (42.7%, 32/75). There was a difference in the prevalence of dyslipidemia between the age group under 50 and the age group over 50 (p&amp;lt;0.001). The prevalence of dyslipidemia among males and females was TC (72.6% vs 28.4%), HDLC (55.4% vs 44.6%), LDLC (53.8% vs 46.2%), TG (42.6% vs 57.4%), respectively (p&amp;lt;0.001). Thirteen of the 1,232 patients had dyslipidemia accompanied by hyperglycemia. Seven of them had mixed dyslipidemia (including raised TC, LDLC, and TG (n=4), raised TG &amp; Low HDLC (n=2), raised TC and LDLC (n=1)). Conclusions The prevalence of dyslipidemia in Korean patients visiting local clinics was 53.3% and differed by gender, age group, and lipid profile. Considering that the prevalence of dyslipidemia is higher in diabetic patients compared to patients without diabetes, additional studies targeting a large number of patients are needed to promote disease prevention and control.

Muscle strength as a marker of metabolic health in kidney transplant recipients: A cross-sectional study

BackgroundMuscle strength is often used as an indirect indicator of metabolic health across different age groups in healthy individuals. However, in kidney transplant recipients, this measure may be less accurate due to metabolic changes induced by immunosuppressive medications. AimTo compare muscle strength between kidney transplant recipients with metabolic syndrome (MS) and those without this condition. MethodsA cross-sectional analytical study was conducted with 29 participants (22 men and seven women) aged 18–50 years, having undergone a kidney transplant for over a year and without experiencing graft failure. To determine the presence of MS, the criteria proposed by the National Cholesterol Education Program (NCEP) Adult Treatment Panel III (ATP-III) was used. Biochemical markers (triglyceride, total cholesterol, HDL, LDL, and glucose levels) were evaluated through a capillary sample. Muscle strength was assessed through three tests: long jump, elbow flexion, and grip strength. ResultsThe mean age was 36 ± 11.3 years, and the average transplant time was 4.5 ± 2.8 years. The prevalence of MS was 58.6%. Transplant recipients with MS performed less in all tests assessing muscle strength than those without this condition (p < 0.001∗). ConclusionsThe main finding of this research is that kidney transplant patients with MS performed worse in muscle strength tests compared to those without the condition.

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Background: Dyslipidaemia has been proposed as a potential risk factor for breast cancer. This study aimed to evaluate the association between serum lipid profiles and breast cancer among women, comparing lipid levels between breast cancer patients and healthy controls. Methods: A hospital-based cross-sectional observational study was conducted at SMS Medical College and Hospital, Jaipur, from ethics committee approval until June 2024. The study included 100 breast cancer patients and 100 matched healthy controls. Inclusion criteria were individuals aged 18 years or older with informed consent, while exclusion criteria included critically ill patients, those with malignancies other than breast cancer, and those on lipid-lowering therapy. The lipid profile was assessed according to the National Cholesterol Education Program (NCEP) Adult Treatment Panel III (ATP III) guidelines. Data collection involved clinical examination, anthropometric measurements, and biochemical analysis of serum lipid levels. Results: The mean age of participants was 48.5 years for the Case Group and 45.92 years for the Control Group. Serum lipid profiles showed significantly higher levels of total cholesterol (TC), low-density lipoprotein cholesterol (LDL), and triglycerides (TG) in breast cancer patients compared to controls, with TC at 197 ± 42.2 mg/dl vs. 174.06 ± 38.46 mg/dl, LDL at 152.65 ± 32.57 mg/dl vs. 121.09 ± 24.56 mg/dl, and TG at 162.12 ± 15.64 mg/dl vs. 138.23 ± 22.99 mg/dl. High-density lipoprotein cholesterol (HDL) was significantly lower in breast cancer patients (36.0 ± 16.60 mg/dl vs. 50.60 ± 17.64 mg/dl). Subgroup analysis by age showed similar trends across different age groups. No significant differences were observed between premenopausal and postmenopausal women in lipid levels. Conclusion: Elevated serum lipid levels, particularly TC, LDL, and TG, are associated with breast cancer. Monitoring and managing lipid levels may offer potential benefits in breast cancer prevention and treatment strategies.

Vitality and metabolic responses to integrated naturopathy and yogic interventions among metabolic syndrome – A protocol for randomized controlled trial

BackgroundMetabolic Syndrome (MetS) refers to a collection of interrelated physiological, biochemical, clinical, and metabolic variables that significantly raise the risk of type 2 diabetes, cardiovascular disease, and all-cause mortality. This trial aims to assess the effect of Naturopathy and Yogic Interventions on Vitality and Metabolic responses among patients with MetS. MethodThis trial is a single Centre Randomized Controlled Trial (RCT) and will be conducted at Nature Cure and Yoga Centre in the Southern part of India. Enrolled subjects with MetS, who fulfilled National Cholesterol Education Program Adult Treatment Panel III [NCEP ATP III Criteria], will be randomly allocated at a 1:1 ratio into Intervention and control groups. The Intervention group will receive Intensive Naturopathy and Yoga Intervention whereas the control group will receive a lifestyle advice during the initial consultation. The primary outcome will be measured by Heart Rate Variability (HRV), Blood Pressure Measurement, Biochemical Analysis, Anthropometric Measurement, Vitality Questionnaire, and Framingham Risk Score (FRS) which will be performed at the baseline and after 10 days of intervention and follow up will be taken at the 60th day. DiscussionA larger clinical trial will be possible as a result of this study's contribution to the understanding of the effectiveness of Yogic Interventions and Integrated Naturopathy for MetS and associated risk factors.

Association of physical activity and risk of cardiac disease among adults

Background: Nowadays the level of physical activity is compromised among all, especially in young adults, which may contribute to early development risk of cardiac disease. Objective: To determine the association of risk of cardiac disease with physical activity among young adults. Methods: A cross-sectional study was conducted from January 2024 to April 2024 at Iqra National University, Peshawar after approval from the ethical committee. A total of n=102 undergraduate male and female students between the age of 18-24 years were included in the study. To determine the physical activity of the participants International Physical Activity Questionnaire - Short Form was used. To evaluate the risk of cardiac disease was observed according to the National Cholesterol Education Program. Results: The mean age and BMI of the n=102 study participants were 23.22±3.4 years and 23.37±5kg/m2 respectively. The risk of cardiac disease was found in n=45(44.1%) while most of the participants (n=33) were moderately and (n=42) highly physically active with a mean METs score of 2881.51±2704.83. Physical activity (PA) is not significantly associated (p=0.44) with the risk of cardiac disease. However, gender showed a strong association (p&lt;0.001) with the risk of cardiac disease among the participants. A total of n=24(88.8%) females had the risk, out of n=27, while n=21(28%) males had the risk of cardiac disease out of n=75 males. Conclusion: The study concluded that physical activity had a non-significant relation with the risk of cardiac disease while in the case of gender females are more prone to have the risk of cardiac disease. Keywords: Cardiac diseases, physical activity, risk factors

Association between Metabolic Syndrome and the Severity of Ischemic Heart Disease

Ischemic Heart Disease (IHD) was a leading cause of mortality worldwide, often complicated by metabolic syndrome, which includes hypertension, hyperglycemia, and dyslipidemia. Objective: To investigate the association between metabolic syndrome and the severity of ischemic heart disease. Methods: Data were collected from the cohort’s existing records, including clinical assessments, laboratory tests, and self-reported questionnaires. Metabolic syndrome components were evaluated using the National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP III) criteria. Participants were classified as having metabolic syndrome if they met three or more of the following criteria: abdominal obesity, elevated blood pressure, elevated fasting glucose, high triglycerides, and low HDL cholesterol. IHD incidence was determined through medical records, hospital admissions, and mortality data, defined as non-fatal myocardial infarction, unstable angina, or coronary revascularization. Statistical analysis included calculating the incidence rate of IHD for participants with and without metabolic syndrome, expressed as IHD cases per 1,000 person-years. Cox proportional hazards regression models were used to assess the association between metabolic syndrome and IHD incidence, adjusting for confounders such as age, sex, smoking status, physical activity, and family history of cardiovascular disease. Hazard Ratios (HRs) with 95% Confidence Intervals (CIs) were reported. Results: The incidence of IHD was significantly higher in participants with metabolic syndrome. Cox regression showed metabolic syndrome was associated with increased IHD incidence (HR: 2.70, 95% CI: 1.50–4.80, p &lt; 0.001). Conclusion: Metabolic syndrome was significantly associated with IHD incidence. Early identification and management were essential to reduce IHD risk.

Associations between body fat anthropometric indices and mortality among individuals with metabolic syndrome

BackgroundThe distribution of body fat and metabolic health may contribute to the onset of metabolic syndrome (MetS), but the associations between body fat anthropometric indices (AIs) and mortality in individuals with MetS remain unclear.MethodsParticipants aged 18 years or older with MetS were recruited from the NHANES 1999–2018. The body fat anthropometric indices included the a body shape index (ABSI), body roundness index (BRI), cardiometabolic index (CMI), visceral adiposity index (VAI), waist triglyceride index (WTI), lipid accumulation product (LAP), atherogenic index of plasma (AIP), and triglyceride‒glucose (TyG) index. MetS was defined according to the National Cholesterol Education Program Adult Treatment Panel III (NCEP ATPIII) criteria. Mortality data were obtained from the National Death Index through December 31, 2019.ResultsData were collected from 8,379 individuals with MetS, with a median follow-up of 8.5 years, of whom 1,698 died from all causes and 568 from the CCD. The random survival forest (RSF) analysis indicated that the ABSI had the strongest predictive power for both all-cause mortality and CCD mortality among the eight body fat AIs. After adjusting for multiple variables, the ABSI was found to be linearly and positively associated with all-cause and CCD mortality in individuals with MetS. Participants in the highest quartile of ABSI had an increased risk of all-cause (HR = 1.773 [1.419–2.215]) and CCD (HR = 1.735 [1.267–2.375]) mortality compared with those in the lowest quartile. Furthermore, the ABSI predicted areas under the curve (AUCs) of 0.735, 0.723, 0.718, and 0.725 for all-cause mortality at 3, 5, 10, and 15 years, respectively, and 0.774, 0.758, 0.725, and 0.715 for CCD mortality, respectively.ConclusionAmong eight body fat AIs, the ABSI exhibited the strongest predictive power for mortality in individuals with MetS. Higher ABSI values significantly increased all-cause mortality and CCD mortality in participants with MetS.

Prevalence Of Metabolic Syndrome in Peri and Postmenopausal Women Aged 40- 65 Years in a Tertiary Care Centre

Metabolic syndrome (MetS) is a constellation of interrelated risk factors of metabolic origin— metabolic risk factors—that appear to directly promote the development of atherosclerotic cardio-vascular disease (ASCVD). Menopausal transition with its incidental hormonal changes is considered to contribute to the development of MetS. This was a hospital based cross sectional descriptive study conducted in the Obstetrics and Gynaecology department of Nepal Medical College Teaching Hospital, Attarkhel, Gokarneshwor-8, Kathmandu, from the 1st of September 2023 till the 29th of February 2024 after clearance from the IRC (Ref. No: 56-080/081). Convenience sampling was used among women who fulfilled the inclusion criteria. The aim of the study was to determine the prevalence of MetS among the peri and postmenopausal women and to determine which component of the diagnostic criteria of MetS was more strongly associated with MetS in our population. Women were evaluated to have MetS using both the International Diabetes Federation (IDF) and the National Cholesterol Education Program- Adult Treatment Panel III (NCEP-ATPIII criteria). The prevalence of MetS by the IDF criteria was 54% among the perimenopausal women and 61% among the postmenopausal women. Similarly, the prevalence of MetS according to NCEP-ATPIII was 53.5% among the perimenopausal and 65% among the postmenopausal women. All the MetS diagnostic markers showed a strong correlation with MetS (p&lt;0.001). The prevalence of MetS is high in our population by both the IDF and NCEP-ATP III criteria, being higher in the postmenopausal population, though not statistically significant.

Patients with psoriatic arthritis followed in tertiary centers in Southern Brazil have a high prevalence of metabolic syndrome

Introduction/ObjectivePatients with psoriatic arthritis (PsA) have a significant prevalence of metabolic syndrome (MS), however studies conducted in Latin America describing comorbidities of PsA patients are still scarce. The aim of the present work was to estimate the prevalence of MS in patients attending PsA clinics in tertiary university centers in the south region of Brazil and to evaluate the achievement of the minimal disease activity criteria among those with and without MS. Materials and methodsA cross-sectional study was conducted; patients were recruited in two university hospitals and data collected during a routine clinic visit. The prevalence of MS was estimated using the National Cholesterol Education Programme's Adult Treatment Panel III (NCEP/ATP III). The prevalence of patients achieving the MDA criteria was compared between individuals with and without MS using Chi-square test. ResultsOne hundred and five patients with PsA were evaluated, 81 in center A (Rio Grande do Sul) and 24 in center B (Paraná); 54.3% were female (N=57), the average age was 55.7 (SD 11.6) years and the median time of diagnosis in years was 7.4 (.16–42.2). A total of 51.9% (N=54) were diagnosed with MS., hypertension was found in 51.4% (N=54) and obesity in 38.1% (N=40) of the sample. There was no statistically significant association between MS and MDA. ConclusionPatients followed in PsA clinics in university tertiary centers in the south of Brazil have a significant prevalence of MS. This work emphasizes the importance of the screening and treatment of comorbidities in PsA.