The Association between the Atherogenic Index of Plasma and Cardiometabolic Risk Factors: A Review
Abstract
:1. Introduction
CMR Factors | NCEP (National Cholesterol Education Programme) ATP3 | WHO (World Health Organisation) | IDF (International Diabetes Federation) | EGSIR (European Group for the Study of Insulin Resistance Criteria) | (AACE) American Association of Clinical Endocrinology |
---|---|---|---|---|---|
Based on | (Expert panel on detection, evaluation, and treatment of high blood cholesterol in adults, 2001) | (Alberti and Zimmet, 1998) | (Alberti et al., 2005) | (Balkau and Charles, 1999) | (Einhorn et al., 2003) |
IR | Blood glucose > 5.6 mmol/L (100 mg/dL) or drug treatment for elevated blood glucose | Blood glucose > 6.1 mmol/L (110 mg/dL), 2 h glucose > 7.8 mmol (140 mg/dL) | Blood glucose > 5.6 mmol/L (100 mg/dL) or diagnosed diabetes | Insulin levels > 75th percentile of non-diabetic patients; Blood glucose 110 mg/dL or greater | |
HDL-C | <1.0 mmol/L (40 mg/dL) in men, <1.3 mmol/L (50 mg/dL) in women or drug treatment for low HDL-C | <0.9 mmol/L (35 mg/dL) in men, <1.0 mmol/L (40 mg/dL) in women | <1.0 mmol/L (40 mg/dL) in men, <1.3 mmol/L (50 mg/dL) in women or drug treatment for low HDL-C | <39 mg/dL in men or women | <40 mg/dL in men and <50 mg/dL in women |
TG | >1.7 mmol/L (150 mg/dL) or drug treatment for elevated triglycerides | >1.7 mmol/L (150 mg/dL) | >1.7 mmol/L (150 mg/dL) or drug treatment for elevated triglycerides | 150 mg/dL or greater | 150 mg/dL or greater |
WC | >102 cm (men) or >88 cm (women) | Europeans: >94 cm (men) or >80 cm (women) South Asians and Chinese: >90 cm (men) >80 cm (women) Japanese: >85 cm (men) >90 cm (women) | 94 cm or greater in men, 80 cm or greater in women | ||
WHpR | >0.9 (men) or >0.85 (women) | ||||
BMI | >30 kg/m2 | 25 kg/m2 or greater | |||
HPT | >130/85 mmHg or drug treatment for hypertension | >140/90 mmHg | >130/85 mmHg or drug treatment for hypertension | 140/90 mmHg or greater or taking antihypertensive drugs | 130/85 mmHg or greater |
MetS diagnostic criteria | 3 or more factors | IR + 2 or more other factors | WC + 2 or more other factors | IR + 2 or more other factors | IGT + 2 or more factors |
2. Materials and Methods
2.1. Study Design and Rationale
2.2. Search Strategy
2.3. Study Selection and Inclusion/Exclusion Criteria
2.4. Quality Assessment of Included Studies
3. Results
3.1. AIP and Anthropometric Measurements
3.2. AIP and Blood Lipid Profile
3.3. AIP and Blood Glucose
3.4. AIP and Hypertension
4. Discussion
4.1. Interpretation of Main Findings and Pathophysiological Perspectives
4.2. Diet and Metabolic Syndrome
4.3. Strengths and Limitations
4.4. Implications for Practice and Direction of Future Research
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Amirabdollahian, F.; Haghighatdoost, F. Anthropometric Indicators of Adiposity Related to Body Weight and Body Shape as Cardiometabolic Risk Predictors in British Young Adults: Superiority of Waist-to-Height Ratio. J. Obes. 2018, 2018, 8370304. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Askhner, P. Metabolic Syndrome as a Risk Factor for Diabetes. Expert Rev. Cardiovasc. Ther. 2010, 8, 407–412. [Google Scholar] [CrossRef]
- Oliveira, R.G.; Guedes, D.P. Physical Activity, Sedentary Behavior, Cardiorespiratory Fitness and Metabolic Syndrome in Adolescents: Systematic Review and Meta-Analysis of Observational Evidence. PLoS ONE 2016, 11, e0168503. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Chen, X.; Zhang, Z.; Yang, H.; Qiu, P.; Wang, H.; Wang, F.; Zhao, Q.; Fang, J.; Nie, J. Consumption of Ultra-Processed Foods and Health Outcomes: A Systematic Review of Epidemiological Studies. Nutr. J. 2020, 19, 86. [Google Scholar] [CrossRef] [PubMed]
- Einarson, T.R.; Acs, A.; Ludwig, C.; Panton, U.H. Prevalence of Cardiovascular Disease in Type 2 Diabetes: A Systematic Literature Review of Scientific Evidence from Across the World in 2007–2017. Cardiovasc. Diabetol. 2018, 17, 83. [Google Scholar] [CrossRef] [Green Version]
- WHO. Cardiovascular Diseases. 2021. Available online: https://www.who.int/health-topics/cardiovascular-diseases#tab=tab_1 (accessed on 25 November 2021).
- Bos, M.; Agyemang, C. Prevalence and Complications of Diabetes Mellitus in Northern Africa, a Systematic Review. BMC Public Health 2013, 13, 387. [Google Scholar] [CrossRef] [Green Version]
- Bahall, M.; Legall, G.; Khan, K. Quality of Life Among Patients with Cardiac Disease: The Impact of Comorbid Depression. Health Qual. Life Outcomes 2020, 18, 189. [Google Scholar] [CrossRef] [PubMed]
- Saboya, P.P.; Bodanese, L.C.; Zimmermann, P.R.; Gustavo, A.D.; Assumpção, C.M.; Londero, F. Metabolic Syndrome and Quality of Life: A Systematic Review. Rev. Lat.-Am. Enferm. 2016, 24, e2848. [Google Scholar] [CrossRef] [Green Version]
- Hare, D.L.; Toukhsati, S.R.; Johansson, P.; Jaarsma, T. Depression and Cardiovascular Disease: A Clinical Review. Eur. Heart J. 2014, 35, 1365–1372. [Google Scholar] [CrossRef] [Green Version]
- Zurita-Cruz, J.N.; Manuel-Apolinar, L.; Arellano-Flores, M.L.; Gutierrez-Gonzalez, A.; Najera-Ahumada, A.G.; Cisneros-González, N. Health and Quality of Life Outcomes Impairment of Quality of Life in Type 2 Diabetes Mellitus: A Cross-Sectional Study. Health Qual. Life Outcomes 2018, 16, 94. [Google Scholar] [CrossRef] [PubMed]
- Dobiásová, M.; Frohlich, J. Nový Aterogenní Index Plazmy (AIP) Odpovídá Pomĕru Triglyceridů a HDL-Cholesterolu, Velikosti Cástic Lipoproteinů a Esterifikacní Rychlosti Cholesterolu: Zmĕny po Lécbĕ Lipanorem [The new Atherogenic Plasma Index Reflects the Triglyceride and HDL-Cholesterol Ratio, the Lipoprotein Particle Size and the Cholesterol Esterification Rate: Changes During Lipanor Therapy]. Vnitr. Lek. 2000, 46, 152–156. [Google Scholar] [PubMed]
- Dobiásová, M. AIP—Atherogenic Index of Plasma as a Significant Predictor of Cardiovascular Risk: From Research to Practice. Vnitr. Lek. 2006, 52, 64–71. [Google Scholar] [PubMed]
- Barua, L.; Faruque, M.; Banik, P.C.; Ali, L. Atherogenic Index of Plasma and its Association with Cardiovascular Disease Risk Factors among Postmenopausal Rural Women of Bangladesh. Indian Heart J. 2019, 71, 155–160. [Google Scholar] [CrossRef] [PubMed]
- Kammar-García, A.; López-Moreno, P.; Hernández-Hernández, M.E.; Ortíz-Bueno, A.M.; Martínez-Montaño, M. Atherogenic Index of Plasma as a Marker of Cardiovascular Risk Factors in Mexicans Aged 18 to 22 years. Bayl. Univ. Med. Cent. Proc. 2020, 34, 22–27. [Google Scholar] [CrossRef]
- Won, K.B.; Jang, M.H.; Park, E.J.; Park, H.B.; Heo, R.; Han, D.; Chang, H.J. Atherogenic Index of Plasma and the Risk of Advanced Subclinical Coronary Artery Disease Beyond Traditional Risk Factors: An Observational Cohort Study. Clin. Cardiol. 2020, 43, 1398–1404. [Google Scholar] [CrossRef]
- Sein, M.T.; Latt, T.S.; Ohnmar, D. Association of Waist Circumference with Atherogenic Cardiovascular Risks in Centrally Obese Myanmar Male Subjects. Int. J. Clin. Exp. Physiol. 2015, 2, 46–50. [Google Scholar] [CrossRef]
- Li, Y.W.; Kao, T.W.; Chang, P.K.; Chen, W.L.; Wu, L.W. Atherogenic Index of Plasma as Predictors for Metabolic Syndrome, Hypertension and Diabetes Mellitus in Taiwan Citizens: A 9-year Longitudinal Study. Sci. Rep. 2021, 11, 9900. [Google Scholar] [CrossRef]
- Dobiášová, M.; Frohlich, J.; Šedová, M.; Cheung, M.C.; Brown, B.G. Cholesterol Esterification and Atherogenic Index of Plasma Correlate with Lipoprotein Size and Findings on Coronary Angiography. J. Lipid Res. 2011, 52, 566–571. [Google Scholar] [CrossRef] [Green Version]
- Shin, H.R.; Song, S.; Cho, J.A.; Ly, S.Y. Atherogenic Index of Plasma and Its Association with Risk Factors of Coronary Artery Disease and Nutrient Intake in Korean Adult Men: The 2013–2014 KNHANES. Nutrients 2022, 14, 1071. [Google Scholar] [CrossRef]
- 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, 2486–2497. [Google Scholar] [CrossRef]
- Alberti, K.G.; Zimmet, P.Z. 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. J. Br. Diabet. Assoc. 1998, 15, 539–553. [Google Scholar] [CrossRef]
- Alberti, K.G.; Zimmet, P.; Shaw, J.; IDF Epidemiology Task Force Consensus Group. The metabolic syndrome—A New WorldWide Definition. Lancet 2005, 366, 1059–1062. [Google Scholar] [CrossRef]
- Balkau, B.; Charles, M.A. Comment on the Provisional Report from the WHO Consultation. European Group for the Study of Insulin Resistance (EGIR). Diabet. Med. J. Br. Diabet. Assoc. 1999, 16, 442–443. [Google Scholar] [CrossRef]
- Einhorn, D.; Reaven, G.M.; Cobin, R.H.; Ford, E.; Ganda, O.P.; Handelsman, Y.; Hellman, R.; Jellinger, P.S.; Kendall, D.; Krauss, R.M.; et al. American College of Endocrinology Position Statement on the Insulin Resistance Syndrome. Endocr. Pract. Off. J. Am. Coll. Endocrinol. Am. Assoc. Clin. Endocrinol. 2003, 9, 237–252. [Google Scholar] [CrossRef]
- Lo, C.K.L.; Mertz, D.; Loeb, M. Newcastle-Ottawa Scale: Comparing reviewers’ to authors’ assessments. BMC Med. Res. Methodol. 2014, 14, 45. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Eslami, O.; Shahraki, M.; Shahraki, T. Obesity Indices in Relation to Lipid Abnormalities among Medical University Students in Zahedan, South-East of Iran. Int. J. Prev. Med. 2019, 10, 15. [Google Scholar] [CrossRef] [PubMed]
- Ranjit, P.M.; Guntuku, G.; Pothineni, R.B. New Atherogenic Indices: Assessment of Cardio Vascular Risk in Postmenopausal Dyslipidemia. Asian J. Med. Sci. 2015, 6, 25–32. [Google Scholar] [CrossRef] [Green Version]
- ChhodenR, S.; Ferdous, M.; Adhikary, D.K.; Salim, M.A.; Banerjee, S.K.; Fariduddin, M.; Biswas. Expression of Neutrophil Elastase and Myeloperoxidase Genes in Coronary Atherosclerosis. Gene Rep. 2021, 25, 101336. [Google Scholar] [CrossRef]
- Chhezom, K.; Arslan, M.I.; Hoque, M.M.; Biswas, S.K. Biomarkers of Cardiovascular and Metabolic Diseases in Otherwise Healthy Overweight Subjects in Bangladesh. Diabetes Metab. Syndr. Clin. Res. Rev. 2017, 11, S381–S384. [Google Scholar] [CrossRef]
- Panjeta, E.; Jardic, R.; Panjeta, M.; Coric, J.; Dervisevic, A. Correlation of Serum Lipid Profile and Glycaemic Control Parameters in Patients with Type 2 Diabetes Mellitus. J. Health Sci. 2018, 8, 110–116. [Google Scholar]
- Bahijri, S.M.; Ajabnoor, G.M.; Hegazy, G.A.; Borai, A.A.; Eldakhakhny, B.M.; Alsheikh, L.N.; Harakeh, S.M. Diet Influences Levels of Plasma Lipopolysaccharide (LPS) and its Soluble Receptor (sCD14) in Saudis. J. Pak. Med Assoc. 2020, 70, 1956–1961. [Google Scholar] [CrossRef]
- Hanamatsu, H.; Ohnishi, S.; Sakai, S.; Yuyama, K.; Mitsutake, S.; Takeda, H.; Hashino, S.; Igarashi, Y. Altered Levels of Serum Sphingomyelin and Ceramide Containing Distinct Acyl Chains in Young Obese Adults. Nutr Diabetes 2014, 4, e141. [Google Scholar] [CrossRef] [Green Version]
- Olamoyegun, M.A.; Akinlade, A.T.; Fawale, M.B.; Ogbera, A.O. Dyslipidaemia as a Risk Factor in the Occurrence of Stroke in Nigeria: Prevalence and Patterns. Pan Afr. Med. J. 2016, 25, 72. [Google Scholar] [CrossRef] [PubMed]
- Manohar, S.M.; Vaikasuvu, S.R.; Deepthi, K.; Sachan, A.; Narashima, S.R.P.V. An Association of Hyperglycemia with Plasma Malondialdehyde and Atherogenic Lipid Risk Factors in Newly Diagnosed Type 2 Diabetic Patients. J. Res. Med. Sci. 2013, 18, 89–93. [Google Scholar] [PubMed]
- Agrawall, P.; Reddy, V.S.; Madaan, H.; Patra, S.K.; Garg, R. Urban-Rural Differences in Atherogenic Dyslipidaemia (URDAD Study): A Retrospective Report on Diabetic and Non-diabetic Subjects of Northern India. J. Health Popul. Nutr. 2014, 32, 494–502. [Google Scholar]
- Guzel, T.; Bilik, M.Z.; Arslan, B.; Kilic, R.; Aktan, A. The Effect of Atherogenic Plasma Index on Collateral Development in Patients with Chronic Coronary Total Occlusion. Exp. Biomed. Res. 2021, 4, 291–301. [Google Scholar] [CrossRef]
- Krivosikova, Z.; Gajdos, M.; Ebekova, K. Vitamin D Levels Decline with Rising Number of Cardiometabolic Risk Factors in Healthy Adults: Association with Adipokines, Inflammation, Oxidative Stress and Advanced Glycation Markers. PLoS ONE 2015, 10, e0131753. [Google Scholar]
- Li, S.; Ye, P.; Chen, H.; Li, Y.F.; Hua, Q.; Zhang, Y.; Xu, R.X.; Guo, Y.L.; Zhu, C.G.; Wu, N.Q.; et al. Lipid Profiles in Nontreated Chinese Patients with Stable Coronary Artery Disease: A Cross-Sectional Study. Clin. Lipidol. 2015, 10, 369–378. [Google Scholar]
- Cibičková, Ľ.; Langová, K.; Vaverková, H.; Lukeš, J.; Cibiček, N.; Karásek, D. Superior Role of Waist Circumference to Body-Mass Index in the Prediction of Cardiometabolic Risk in Dyslipidemic Patients. Physiol. Res. 2019, 68, 931–938. [Google Scholar] [CrossRef]
- Vaverková, H.; Karásek, D.; Halenka, M.; Cibíčková, L.; Kubíčková, V. Inverse Association of Lipoprotein (a) with Markers of Insulin Resistance in Dyslipidemic Subjects. Physiol. Res. 2017, 66, S113–S120. [Google Scholar] [CrossRef]
- Al-Bazi, M.M.; Elshal, M.F.; Khoja, S.M. Reduced Coenzyme Q(10) in Female Smokers and its Association with Lipid Profile in a Young Healthy Adult Population. Arch. Med. Sci. 2011, 7, 948–954. [Google Scholar] [CrossRef] [PubMed]
- Wang, L.; Chen, F.; Xiaoqi, C.; Yujun, C.; Zijie, L. Atherogenic Index of Plasma Is an Independent Risk Factor for Coronary Artery Disease and a Higher SYNTAX Score. Angiology 2020, 72, 181–186. [Google Scholar] [CrossRef] [PubMed]
- Yin, J.; Li, M.; Yu, L.; Hu, F.; Yu, Y.; Hu, L.; Bao, H.; Cheng, X. The Relationship Between the Atherogenic Index of Plasma and Arterial Stiffness in Essential Hypertensive Patients from China: A Cross-Sectional Study. BMC Cardiovasc. Disord. 2021, 21, 245. [Google Scholar] [CrossRef] [PubMed]
- Choudhary, M.K.; Eräranta, A.; Koskela, J.; Tikkakoski, A.J.; Nevalainen, P.I.; Kähönen, M.; Mustonen, J.; Pörsti, I. Atherogenic Index of Plasma is Related to Arterial Stiffness but not to Blood Pressure in Normotensive and Never-Treated Hypertensive Subjects. Blood Press. 2019, 28, 157–167. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Javardi, M.S.M.; Madani, Z.; Movahedi, A.; Karandish, M.; Abbasi, B. The Correlation Between Dietary Fat Quality Indices and Lipid Profile with Atherogenic Index of Plasma in Obese and non-Obese Volunteers: A Cross-Sectional Descriptive-Analytic Case-Control Study. Lipids Health Dis. 2020, 19, 213. [Google Scholar] [CrossRef]
- Mondal, S.; Mondal, H.; Samantaray, R.; Das, D.; Biri, S.K.; Naskar, A.; Jana, S. Atherogenic Index of Plasma and Left Ventricular Ejection Fraction in Newly Diagnosed Type 2 Diabetes Mellitus Patients. Res. Cardiovasc. Med. 2021, 10, 73–78. [Google Scholar] [CrossRef]
- Anandkumar, M.H.; Chandrashekhar, D.M.; Jayalakshimi, M.K.; Babu, P.G. Anthropometric Measures of Obesity as Correlates of Atherogenic Index of Plasma in Young Adult Females. Natl. J. Physiol. Pharm. Pharmacol. 2019, 10, 84–88. [Google Scholar]
- Nam, J.S.; Kim, M.K.; Park, K.; Choi, A.; Kang, S.; Ahn, C.W.; Park, J.S. The Plasma Atherogenic Index is an Independent Predictor of Arterial Stiffness in Healthy Koreans. Angiology 2021, 73, 514–519. [Google Scholar] [CrossRef]
- Hosseini, S.A.; Aghamohammadi, V.; Ashtary-Larky, D.; Alipour, M.; Ghanavati, M.; Lamuchi-Deli, N. Are Young Iranian Women with Metabolically Healthy Obesity at Increased Risk of CVD Incidence? J. Vasc. Bras. 2020, 19, e20190106. [Google Scholar] [CrossRef]
- Cakirca, G.; Celik, M.M. Relationship Between Glycaemic Control and Platelet Indices, Atherogenic Index of Plasma Vitamin D in Patients with Type 2 Diabetes. EJCM 2019, 7, 147–152. [Google Scholar] [CrossRef]
- Lwow, F.; Bohdanowicz-Pawlak, A. Vitamin D and Selected Cytokine Concentrations in Postmenopausal Women in Relation to Metabolic Disorders and Physical Activity. Exp. Gerontol. 2020, 141, 111107. [Google Scholar] [CrossRef]
- Wang, Y.; Si, S.; Liu, J.; Wang, Z.; Jia, H.; Feng, K.; Sun, L.; Song, S.J. The Associations of Serum Lipids with Vitamin D Status. PLoS ONE 2016, 11, e0165157. [Google Scholar] [CrossRef]
- Al-Shaer, M.H.; Elzaky, M.M.; Farag, E.S.M.; Saad, M.O.M. In Type 2 Diabetes Mellitus Patients, the Atherogenic Index of Plasma as a Marker of Coronary Artery Disease. Indian J. Clin. Cardiol. 2021, 2, 217–221. [Google Scholar] [CrossRef]
- Nwagha, U.I.; Ikekpeazu, E.J.; Ejezie, F.E.; Neboh, E.E.; Maduka, I.C. Atherogenic Index of Plasma as Useful Predictor of Cardiovascular Risk Among Postmenopausal Women in Enugu, Nigeria. Afr. Health Sci. 2010, 10, 248–252. [Google Scholar] [PubMed]
- Czernichow, S.; Kengne, A.-P.; Huxley, R.; Batty, G.; De Galan, B.; Grobbee, D.; Pillai, A.; Zoungas, S.; Marre, M.; Woodward, M.; et al. Comparison of Waist-to-Hip Ratio and Other Obesity Indices as Predictors of Cardiovascular Disease Risk in People with Type-2 Diabetes: A Prospective Cohort Study from ADVANCE. Eur. J. Prev. Cardiol. 2011, 18, 312–319. [Google Scholar] [CrossRef]
- Bener, A.; Yousafzai, M.T.; Darwish, S.; Al-Hamaq, A.O.; Nasralla, E.A.; Abdul-Ghani, M. Obesity Index that Better Predict Metabolic Syndrome: Body Mass Index, Waist Circumference, Waist Hip Ratio, or Waist Height Ratio. J. Obes. 2013, 2013, 269038. [Google Scholar] [CrossRef] [Green Version]
- Niroumand, S.; Khajedaluee, M.; Khadem-Rezaiyan, M.; Abrishami, M.; Juya, M.; Khodaee, G.; Dadgarmoghaddam, M. Atherogenic Index of Plasma (AIP): A Marker of Cardiovascular Disease. Med. J. Islam. Repub. Iran 2015, 29, 240. [Google Scholar]
- Tao, L.X.; Yang, K.; Liu, X.T.; Cao, K.; Zhu, H.P.; Luo, Y.X.; Guo, J.; Wu, L.J.; Li, X.; Guo, X.H. Longitudinal Associations between Triglycerides and Metabolic Syndrome Components in a Beijing Adult Population, 2007–2012. Int. J. Med. Sci. 2016, 13, 445–450. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Chapman, M.J.; Le Goff, W.; Guerin, M.; Kontush, A. Cholesteryl Ester Transfer Protein: At the Heart of the Action of Lipid-Modulating Therapy with Statins, Fibrates, Niacin, and Cholesteryl Ester Transfer Protein Inhibitors. Eur. Heart J. 2010, 31, 149–164. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Cannon, C.P. High-Density Lipoprotein Cholesterol and Residual Cardiometabolic Risk in Metabolic Syndrome. Clin. Cornerstone 2007, 8, S14–S23. [Google Scholar] [CrossRef] [PubMed]
- Marques, L.R.; Diniz, T.A.; Antunes, B.M.; Rossi, F.E.; Caperuto, E.C.; Lira, F.S.; Gonçalves, D.C. Reverse Cholesterol Transport: Molecular Mechanisms and the Non-medical Approach to Enhance HDL Cholesterol. Front. Physiol. 2018, 9, 526. [Google Scholar] [CrossRef] [Green Version]
- Welty, F.K.; Lichtenstein, A.H.; Lamon-Fava, S.; Schaefer, E.J.; Marsh, J.B. Effect of Body Mass Index on Apolipoprotein A-I Kinetics in Middle-Aged Men and Postmenopausal Women. Metabolism 2007, 56, 910–914. [Google Scholar] [CrossRef] [Green Version]
- Mohammadpour, A.H.; Akhlaghi, F. Future of Cholesteryl Ester Transfer Protein (CETP) Inhibitors: A Pharmacological Perspective. Clin. Pharmacokinet. 2013, 52, 615–626. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Ohashi, R.; Mu, H.; Wang, X.; Yao, Q.; Chen, C. Reverse Cholesterol Transport and Cholesterol Efflux in Atherosclerosis. Int. J. Med. 2005, 98, 845–856. [Google Scholar] [CrossRef] [PubMed]
- Akinmolayemi, O.; Saldanha, S.; Joshi, P.H.; Deodhar, S.; Ayers, C.R.; Neeland, I.J.; Rohatgi, A. Cholesterol Efflux Capacity and its Association with Prevalent Metabolic Syndrome in a Multi-Ethnic Population (Dallas Heart Study). PLoS ONE 2021, 16, e0257574. [Google Scholar] [CrossRef] [PubMed]
- Guérin, M.; Le Goff, W.; Lassel, T.S.; Van Tol, A.; Steiner, G.; Chapman, M.J. Atherogenic Role of Elevated CE Transfer from HDL to VLDL(1) and Dense LDL in Type 2 diabetes: Impact of the Degree of Triglyceridemia. Arterioscler. Thromb. Vasc. Biol. 2001, 21, 282–288. [Google Scholar] [CrossRef] [Green Version]
- Shin, H.G.; Kim, Y.K.; Kim, Y.H.; Jung, Y.H.; Kang, H.C. The Relationship Between the Triglyceride to High-Density Lipoprotein Cholesterol Ratio and Metabolic Syndrome. Korean J. Fam. Med. 2017, 38, 352–357. [Google Scholar] [CrossRef] [Green Version]
- Zadeh-Vakili, A.; Tehrani, F.R.; Hosseinpanah, F. Waist Circumference and Insulin Resistance: A Community Based Cross Sectional Study on Reproductive Aged Iranian Women. Diabetol. Metab. Syndr. 2011, 3, 18. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Tabata, S.; Yoshimitsu, S.; Hamachi, T.; Abe, H.; Ohnaka, K.; Kono, S. Waist Circumference and Insulin Resistance: A Cross-Sectional Study of Japanese Men. BMC Endocr. Disord. 2009, 9, 1. [Google Scholar] [CrossRef] [Green Version]
- Karhapää, P.; Malkki, M.; Laakso, M. Isolated Low HDL Cholesterol: An Insulin-resistant State. Diabetes 1994, 43, 411–417. [Google Scholar] [CrossRef]
- Sesti, G. Pathophysiology of Insulin Resistance. Best Pract. Res. Clin. Endocrinol. Metab. 2006, 20, 665–679. [Google Scholar] [CrossRef]
- Glueck, C.J.; Khan, N.A.; Umar, M.; Uppal, M.S.; Ahmed, W.; Morrison, J.A.; Goldenberg, N.; Wang, P. Insulin Resistance and Triglycerides. J. Investig. Med. Off. Publ. Am. Fed. Clin. Res. 2009, 57, 874–881. [Google Scholar] [CrossRef] [PubMed]
- Hasan, B.F.; Ibrahim, N.A.K.; Hameedi, B.H. Atherogenic Index of Plasma and Insulin Resistance in Obese Diabetic Patients. Int. J. Sci. Res. 2016, 5. [Google Scholar] [CrossRef]
- Chiang, J.K.; Lai, N.S.; Chang, J.K.; Koo, M. Predicting Insulin Resistance Using the Triglyceride-to-High-Density Lipoprotein Cholesterol Ratio in Taiwanese Adults. Cardiovasc. Diabetol. 2011, 10, 93. [Google Scholar] [CrossRef] [Green Version]
- Li, Z.; Huang, Q.; Sun, L.; Bao, T.; Dai, Z. Atherogenic Index in Type 2 Diabetes and Its Relationship with Chronic Microvascular Complications. Int. J. Endocrinol. 2018, 2018, 1765835. [Google Scholar] [CrossRef] [PubMed]
- Liu, H.; Liu, J.; Liu, J.; Xin, S.; Lyu, Z.; Fu, X. Triglyceride to High-Density Lipoprotein Cholesterol (TG/HDL-C) Ratio, a Simple but Effective Indicator in Predicting Type 2 Diabetes Mellitus in Older Adults. Front. Endocrinol. 2022, 13, 828581. [Google Scholar] [CrossRef] [PubMed]
- Kim-Dorner, S.J.; Deuster, P.A.; Zeno, S.A.; Remaley, A.T.; Poth, M. Should Triglycerides and the Triglycerides to High-Density Lipoprotein Cholesterol Ratio be Used as Surrogates for Insulin Resistance? Metabolism 2010, 59, 299–304. [Google Scholar] [CrossRef] [PubMed]
- Sumner, A.E.; Finley, K.B.; Genovese, D.J.; Criqui, M.H.; Boston, R.C. Fasting Triglyceride and the Triglyceride–HDL Cholesterol Ratio are not Markers of Insulin Resistance in African Americans. Arch. Intern. Med. 2005, 165, 1395–1400. [Google Scholar] [CrossRef] [Green Version]
- Sumner, A.E.; Harman, J.L.; Buxbaum, S.G.; Miller, B.V.; Tambay, A.V.; Wyatt, S.B.; Taylor, H.A.; Rotimi, C.N.; Sarpong, D.F. The Triglyceride/High-Density Lipoprotein Cholesterol Ratio Fails to Predict Insulin Resistance in African-American Women: An Analysis of Jackson Heart Study. Metab. Syndr. Relat. Disord. 2010, 8, 511–514. [Google Scholar] [CrossRef] [Green Version]
- Kallioinen, N.; Hill, A.; Horswill, M.S.; Ward, H.E.; Watson, M.O. Sources of Inaccuracy in the Measurement of Adult Patients Resting Blood Pressure in Clinical Settings: A Systematic Review. J. Hypertens. 2017, 35, 421–441. [Google Scholar] [CrossRef] [Green Version]
- Guo, Q.; Zhou, S.; Feng, X.; Yang, J.; Qiao, J.; Zhao, Y.; Shi, D.; Zhou, Y. The Sensibility of the New Blood Lipid Indicator—Atherogenic Index of Plasma (AIP) in Menopausal Women with Coronary Artery Disease. Lipids Health Dis. 2020, 19, 27. [Google Scholar] [CrossRef] [Green Version]
- Wu, J.; Zhou, Q.; Wei, Z.; Wei, J.; Cui, M. Atherogenic Index of Plasma and Coronary Artery Disease in the Adult Population: A Meta-Analysis. Front. Cardiovasc. Med. 2021, 8, 817441. [Google Scholar] [CrossRef] [PubMed]
- Alexander, R.W. Hypertension and the Pathogenesis of Atherosclerosis. Hypertension 1995, 25, 155–161. [Google Scholar] [CrossRef]
- Shimizu, Y.; Sato, S.; Noguchi, Y.; Koyamatsu, J.; Yamanashi, H.; Nagayoshi, M.; Kadota, K.; Kawashiri, S.-Y.; Nagata, Y.; Maeda, T. Triglycerides and Blood Pressure in Relation to Circulating CD34-positive Cell Levels Among Community-Dwelling Elderly Japanese Men: A Cross-Sectional Study. Environ. Health Prev. Med. 2017, 22, 77. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Montefusco, L.; D’Addio, F.; Loretelli, C.; Ben Nasr, M.; Garziano, M.; Rossi, A.; Pastore, I.; Plebani, L.; Lunati, M.E.; Bolla, A.M.; et al. Anti-Inflammatory Effects of Diet and Caloric Restriction in Metabolic Syndrome. J. Endocrinol. Investig. 2021, 44, 2407–2415. [Google Scholar] [CrossRef] [PubMed]
- Roche, H.; Phillips, C.; Gibney, M. The Metabolic Syndrome: The Crossroads of Diet and Genetics. Proc. Nutr. Soc. 2005, 64, 371–377. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Pitsavos, C.; Panagiotakos, D.; Weinem, M.; Stefanadis, C. Diet, Exercise and the Metabolic Syndrome. Rev. Diabet. Stud. RDS 2006, 3, 118–126. [Google Scholar] [CrossRef] [Green Version]
- Rochlani, Y.; Pothineni, N.V.; Kovelamudi, S.; Mehta, J.L. Metabolic Syndrome: Pathophysiology, Management, and Modulation by Natural Compounds. Ther. Adv. Cardiovasc. Dis. 2017, 11, 215–225. [Google Scholar] [CrossRef] [Green Version]
- Melanson, K.J. Nutrition Review: Diet and Metabolic Syndrome. Am. J. Lifestyle Med. 2008, 2, 113–117. [Google Scholar] [CrossRef]
- Ha, K.; Song, Y. Associations of Meal Timing and Frequency with Obesity and Metabolic Syndrome among Korean Adults. Nutrients 2019, 11, 2437. [Google Scholar] [CrossRef] [Green Version]
- Yoshida, J.; Eguchi, E.; Nagaoka, K.; Ito, T.; Ogino, K. Association of Night Eating Habits with Metabolic Syndrome and its Components: A Longitudinal Study. BMC Public Health 2018, 18, 1366. [Google Scholar] [CrossRef]
- Alkhulaifi, F.; Darkoh, C. Meal Timing, Meal Frequency and Metabolic Syndrome. Nutrients 2022, 14, 1719. [Google Scholar] [CrossRef] [PubMed]
- Sierra-Johnson, J.; Undén, A.L.; Linestrand, M.; Rosell, M.; Sjogren, P.; Kolak, M.; De Faire, U.; Fisher, R.M.; Hellénius, M.L. Eating Meals Irregularly: A Novel Environmental Risk Factor for the Metabolic Syndrome. Obesity 2008, 16, 1302–1307. [Google Scholar] [CrossRef] [PubMed]
- Esposito, K.; Ciotola, M.; Giugliano, D. Mediterranean Diet and the Metabolic Syndrome. Mol. Nutr. Food Res. 2007, 51, 1268–1274. [Google Scholar] [CrossRef] [PubMed]
- Esposito, K.; Maiorino, M.I.; Bellastella, G.; Chiodini, P.; Panagiotakos, D.; Giugliano, D. A Journey Into a Mediterranean Diet and Type 2 Diabetes: A Systematic Review with Meta-Analyses. BMJ Open 2015, 5, e008222. [Google Scholar] [CrossRef] [Green Version]
- Liu, Y.S.; Wu, Q.J.; Lv, J.L.; Jiang, Y.T.; Sun, H.; Xia, Y.; Chang, Q.; Zhao, Y.H. Dietary Carbohydrate and Diverse Health Outcomes: Umbrella Review of 30 Systematic Reviews and Meta-Analyses of 281 Observational Studies. Front. Nutr. 2021, 8, 670411. [Google Scholar] [CrossRef] [PubMed]
- Narain, A.; Kwok, C.S.; Mamas, M.A. Soft Drink Intake and the Risk of Metabolic Syndrome: A Systematic Review and Meta-Analysis. Int. J. Clin. Pract. 2017, 71, e12927. [Google Scholar] [CrossRef]
- Wei, B.; Liu, Y.; Lin, X.; Fang, Y.; Cui, J.; Wan, J. Dietary Fiber Intake and Risk of Metabolic Syndrome: A meta-Analysis of Observational Studies. Clin. Nutr. 2018, 37, 1935–1942. [Google Scholar] [CrossRef] [PubMed]
- Chen, J.P.; Chen, G.C.; Wang, X.P.; Qin, L.; Bai, Y. Dietary Fiber and Metabolic Syndrome: A Meta-Analysis and Review of Related Mechanisms. Nutrients 2017, 10, 24. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Sirigere, M.; Meera, S. Novel Lipid Indices as a Better Marker of Cardiovascular Disease Risk in Postmenopausal Women. Indian J. Med. Biochem. 2017, 21, 38–41. [Google Scholar] [CrossRef]
- Devaranavadgi, B.B.; Aski, B.S.; Kashinath, R.T.; Hundekari, I.A. Effect of Cigarette Smoking on Blood Lipids—A Study in Belgaum, Northern Karnataka, India. Glob. J. Med. Res. 2012, 12, 57–60. [Google Scholar]
Newcastle-Ottawa Quality Assessment Criteria | |||||
---|---|---|---|---|---|
Author and Year | Selection (MAX *** or **** Depending on Study Design) | Comparability (MAX **) | Outcome (MAX **) | Exposure (MAX ***) | Total Score |
Eslami et al., 2019 | **/3 | ** | ** | / | 6/7 |
Ranjit et al., 2015 | ***/4 | ** | / | ** | 7/9 |
ChhodenR et al., 2021 | */3 | ** | ** | / | 5/7 |
Chhezom et al., 2017 | */3 | * | ** | / | 4/7 |
Panjeta et al., 2018 | */3 | * | ** | / | 4/7 |
Bahijri et al., 2020 | */3 | ** | ** | / | 5/7 |
Hanamatsu et al., 2014 | ***/4 | ** | / | ** | 7/9 |
Olamoyegun et al., 2016 | */3 | * | ** | / | 4/7 |
Manohar et al., 2013 | ***/4 | ** | / | ** | 7/9 |
Agrawall et al., 2014 | */3 | ** | ** | / | 5/7 |
Guzel et al., 2021 | ***/4 | ** | / | *** | 8/9 |
Krivosikova et al., 2015 | */3 | ** | ** | / | 5/7 |
Li et al., 2015 | **/3 | ** | ** | / | 6/7 |
Cibičková et al., 2019 | **/3 | ** | * | / | 5/7 |
Vaverkova et al., 2017 | **/3 | ** | ** | / | 6/7 |
Al-Bazi et al., 2011 | /3 | * | ** | / | 3/7 |
Wang et al., 2020 | **/3 | ** | ** | / | 6/7 |
Yin et al., 2021 | ***/3 | ** | ** | / | 7/7 |
Choudhary et al., 2019 | **/3 | ** | ** | / | 6/7 |
Javardi et al., 2020 | **/3 | * | ** | / | 5/7 |
Mondal et al., 2021 | **/3 | ** | ** | / | 6/7 |
Anandkumar et al., 2019 | */3 | * | * | / | 3/7 |
Nam et al., 2021 | **/3 | ** | ** | / | 6/7 |
Hosseini et al., 2020 | **/3 | ** | ** | / | 6/7 |
Cakirca and Celik, 2019 | */3 | ** | ** | / | 5/7 |
Lwow and Bohdanowicz-Pawlak, 2020 | **/3 | ** | ** | / | 6/7 |
Wang et al., 2016 | */3 | ** | ** | / | 5/7 |
Al-Shaer et al., 2021 | */3 | ** | ** | / | 5/7 |
Nwagha et al., 2010 | ****/4 | ** | / | * | 7/9 |
Author and Year | Population Characteristics and Ethnicity/Provenance | Design | Study Outcomes |
---|---|---|---|
Eslami et al., 2019 | 310 apparently healthy undergraduate students; 18–25 years old; Iran | Cross-sectional study | Males:
|
Ranjit et al., 2015 | 75 women;
| Not stated | Pre-menopausal women:
|
ChhodenR et al., 2021 | 64 adults suspected of coronary atherosclerosis;
| Cross-sectional study | CAD group:
|
Chhezom et al., 2017 | 90 apparently healthy subjects;
| Cross-sectional study | Normal weight:
|
Hanamatsu et al., 2014 | 23 students of 18–27 years;
| Not stated | Obese:
|
Manohar et al., 2013 | 104 subjects;
| Not stated | Newly diagnosed T2DM:
|
Krivosikova et al., 2015 | 411 apparently healthy adults;
Note: p-value compared to 0 CMR factors group. Not possible to establish if WC = high due to lack of gender stratification. | Cross-sectional study | 0 CMR factors:
|
Li et al., 2015 | 1772 clinically suspected CAD cases;
| Cross-sectional study | CAD diagnosed:
|
Vaverkova et al., 2017 | 607 asymptomatic dyslipidemic patients (mean age 45.6 ± 14.0 years, 295 males/312 females) Czech Republic Note: Not possible to establish if WC was high due to lack of gender stratification. | Not stated |
|
Al-Bazi, 2011 | 106 healthy adults age range 21–45 years;
Note: Total non-smokers n = 51; total smokers n= 55. | Not stated | Female non-smokers:
|
Wang et al., 2020 | 3600 suspected CAD cases divided based on SYNTAX score;
Note: p-value compared to non-CAD group. | Not stated | Non-CAD
|
Yin et al., 2021 | 4744 Chinese individuals with hypertension stratified based on AIP;
Note: Not possible to establish if WC = high due to lack of gender stratification. | Cross-sectional study | Q1:
|
Choudhary et al., 2019 | 615 normotensive (40.5%) AND never-treated subjects with primary hypertension 59.5%);
Note: p-values compared to T1. | Cross-sectional study | T1:
|
Javardi et al., 2020 | 157 individuals, age range 18–65 years, divided by weight;
| Cross-sectional, descriptive-analytic case–control study | Normal weight:
|
Mondal et al., 2021 | 140 patients newly diagnosed with T2DM; 57.6% males; Over 70% primary/below primary education India | Cross-sectional study |
|
Anandkumar et al., 2019 | 60 apparently healthy young females, age range 18–30 years; India | Cross-sectional study |
|
Nam et al., 2021 | 3468 healthy Koreans, stratified based on AIP;
| Cross-sectional study | Q1:
|
Hosseini et al., 2020 | 183 women; age range 20–35 years; stratified based on weight and metabolic state;
Note: Normal weight obese = BMI < 25 kg/m2 and body fat >30%. * = p-value between 1st and 3rd groups; ^ = p-value between 3rd and 4th groups. | Cross-sectional study | Metabolically healthy normal weight
|
Lwow and Bohdanowicz-Pawlak, 2020 | 318 post-menopausal Polish women of Caucasian origin (mean age 55.3 ± 2.8 years) Poland | Not stated |
|
Wang et al., 2016 | 1475 adults stratified by gender;
| Not stated | Men:
|
Author and Year | Population Characteristics and Ethnicity/Provenance | Design | Study Outcomes |
---|---|---|---|
Panjeta et al., 2018 | 60 adults with T2DM for ≥5 years;
Note: Not possible to determine if HDL is low in the second group due to lack of gender stratification. | Cross-sectional | HbA1C ≤ 7%
|
Bahijri et al., 2020 | 98 apparently healthy adults stratified by weight (although only mean BMI provided);Age range 18–55;
| Cross-sectional study | Underweight males:
|
Hanamatsu et al., 2014 | 23 students of 18–27 years;
| Not stated | Obese:
|
Olamoyegun et al., 2016 | 106 acute stroke patients;
Note: Not possible to determine if HDL = low in both groups due to lack of gender stratification. | Retrospective descriptive cross-sectional study | Haemorrhagic stroke:
|
Manohar et al., 2013 | 104 subjects;
Note: Not possible to determine if HDL= low in both groups due to lack of gender stratification. | Not stated | Newly diagnosed T2DM:
|
Agrawall et al., 2014 | 400 adults newly diagnosed with T2DM;
Note: Not possible to determine if HDL= low groups 1, 3, and 4 due to lack of gender stratification. India | Retrospective report | Urban controls:
|
Guzel et al., 2021 | 451 patients with chronic total occlusion (100% stenosis);
Note: Not possible to determine if HDL-C = low in both groups due to lack of gender stratification. | Not stated | Poor collateral:
|
Krivosikova et al., 2015 | 411 apparently healthy adults;
Note: p-values compared to 0 CMR factors group. | Cross-sectional study | 0 CMR factors:
|
Li et al., 2015 | 1772 clinically suspected CAD cases;
| Cross-sectional study | CAD diagnosed:
|
Cibickova et al., 2019 | 685 asymptomatic dyslipidemic subjects;
| Cross-sectional study | Hypertriglyceridemic waist present:
|
Vaverkova et al., 2017 | 607 asymptomatic dyslipidemic patients (mean age 45.6 ± 14.0 years, 295 males/312 females) Czech Republic | Not stated |
|
Al-Bazi et al., 2011 | 106 healthy adults age range 21–45 years;
Note: Total non-smokers n = 51; total smokers n = 55. p-values between females and males. | Not stated | Female non-smokers:
|
Wang et al., 2020 | 3600 suspected CAD cases divided based on SYNTAX score;
Note: p-value compared to non-CAD group. | Not stated | Non-CAD
|
Yin et al., 2021 | 4744 Chinese individuals with hypertension stratified based on AIP;
| Cross-sectional study | Q1:
|
Choudhary et al., 2019 | 615 normotensive (40.5%) AND never-treated subjects with primary hypertension 59.5%;
Note: p-values compared to T1. | Cross-sectional study | T1:
|
Javardi et al., 2020 | 157 individuals, age range 18–65 years, divided by weight;
| Healthy weight:
| |
Mondal et al., 2021 | 140 patients newly diagnosed with T2DM; 57.6% males; Over 70% primary/below primary education; stratified by gender for blood markers only India | Cross-sectional study | Males:
|
Anandkumar et al., 2020 | 60 apparently healthy young females, age range 18–30 years India | Cross-sectional study |
|
Nam et al., 2021 | 3468 healthy Koreans, stratified based on AIP;
| Cross-sectional study | Q1:
|
Hosseini et al., 2020 | 183 women; age range 20–35 years; stratified based on weight and metabolic state;
Note: Normal weight obese = BMI <25 kg/m2 and body fat >30%. * = p-value between 1st and 3rd groups; ^ = p-value between 3rd and 4th groups. | Cross-sectional study | Metabolically healthy normal weight:
|
Cakirca and Celik, 2019 | 225 diabetic subjects stratified based on HbA1c;
Note: p-values compared to the lowest HbA1c group. | Retrospective study | HbA1c < 7%
|
Lwow and Bohdanowicz-Pawlak, 2020 | 318 post-menopausal Polish women of Caucasian origin (mean age 55.3 ± 2.8 years) Poland | Not stated |
|
Wang et al., 2016 | 1475 adults stratified by gender;
| Not stated | Men:
|
Al-Shaer et al., 2021 | 140 T2DM patients;
Note: No units stated for LDL. | T2DM with CAD:
| |
Nwagha et al., 2010 | 80 females;
| Apparently healthy post-menopausal women:
|
Author and Year | Population Characteristics and Ethnicity/Provenance | Design | Study Outcomes |
---|---|---|---|
Hanamatsu et al., 2014 | 23 students of 18–27 years;
| Not stated | Obese:
|
Guzel et al., 2021 | 451 patients with chronic total occlusion (100% stenosis);
Turkey | Not stated | Poor collateral:
|
Li et al., 2015 | 1772 clinically suspected CAD cases;
| Cross-sectional study | CAD diagnosed:
|
Wang et al., 2020 | 3600 suspected CAD cases divided based on SYNTAX score;
Note: p-value compared to non-CAD group. | Not stated | Non-CAD
|
Yin et al., 2021 | 4744 Chinese individuals with hypertension stratified based on AIP;
China | Cross-sectional study | Q1:
|
Hosseini et al., 2020 | 183 women; age range 20–35 years; stratified based on weight and metabolic state;
Note: Normal weight obese = BMI <25 kg/m2 and body fat >30%. * = p-value between 1st and 3rd groups; ^ = p-value between 3rd and 4th groups. | Cross-sectional study | Metabolically healthy normal weight:
|
Lwow and Bohdanowicz-Pawlak, 2020 | 318 post-menopausal Polish women of Caucasian origin (mean age 55.3 ± 2.8 years) Poland | Not stated | Glucose (mM): 4.97 ± 0.69 Insulin (μIU/mL): 6.8 ± 3.5 AIP: 0.35 ± 0.58 (high) |
Author and Year | Population Characteristics and Ethnicity/Provenance | Design | Study Outcomes |
---|---|---|---|
Krivosikova et al., 2015 | 411 apparently healthy adults;
| Cross-sectional study | 0 CMR factors:
|
Li et al., 2015 | 1772 clinically suspected CAD cases;
| Cross-sectional study | CAD diagnosed:
|
Wang et al., 2020 | 3600 suspected CAD cases divided based on SYNTAX score;
| Not stated | Non-CAD:
|
Choudhary et al., 2019 | 615 normotensive (40.5%) AND never-treated subjects with primary hypertension 59.5%);
Note: p-values compared to T1. | Cross-sectional study | T1:
|
Hosseini et al., 2021 | 183 women; age range 20–35 years; stratified based on weight and metabolic state;
Note: Normal weight obese = BMI < 25 kg/m2 and body fat >30%. * = p-value between 1st and 3rd groups; ^ = p-value between 3rd and 4th groups. | Cross-sectional study | Metabolically healthy normal weight:
|
Al-Shaer et al., 2021 | 140 T2DM patients;
| Not stated | T2DM with CAD:
|
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Lioy, B.; Webb, R.J.; Amirabdollahian, F. The Association between the Atherogenic Index of Plasma and Cardiometabolic Risk Factors: A Review. Healthcare 2023, 11, 966. https://doi.org/10.3390/healthcare11070966
Lioy B, Webb RJ, Amirabdollahian F. The Association between the Atherogenic Index of Plasma and Cardiometabolic Risk Factors: A Review. Healthcare. 2023; 11(7):966. https://doi.org/10.3390/healthcare11070966
Chicago/Turabian StyleLioy, Beatrice, Richard James Webb, and Farzad Amirabdollahian. 2023. "The Association between the Atherogenic Index of Plasma and Cardiometabolic Risk Factors: A Review" Healthcare 11, no. 7: 966. https://doi.org/10.3390/healthcare11070966