Prevalence of Metabolic Syndrome Among Healthy Personnel at Cukurova University

Yıl 2019, , 523 - 531, 20.12.2019

Ayşe Nur Topuz , Nafiz Bozdemir

https://doi.org/10.21763/tjfmpc.651406

Öz

Objective: The aim of this study was to evaluate the frequency of Metabolic
Syndrome (MetS) among healthy personal working for Cukurova University.
Also, we aimed to evaluate the Framingham risk score and Cardiovascular Disease Risk Factors Knowledge Level
(CARRF-KL) scale of participants and investigate the relationship with each
other. Methods: Total of 155 healthy volunteers working for
Cukurova University at academic and administrative staff was included. All
participants’ socio-demographic characteristics, anthropometric measurements were collected, and blood pressure and
serum parameters were measured. MetS was diagnosed using the criteria of the
International Diabetes Federation (IDF). All participants’ Framingham risk
score and CARRF-KL score were also determined. Results:
The mean age of the subjects was 45.6±7.8 years. We identified 29 (18.7%)
subjects with MetS according to IDF criteria. MetS group and control group had
similar mean value of CARRIF-KL score (21.2 ±2.7 vs 20.7±3.9, p=0.50). On the
other hand, MetS group had a higher Framingham score than the control group.
Also, MetS group had mildly elevated Pulse Wave Velocity of Aorta (PWVAo) value
than control group (8.4±1.36 vs 7.8±1.57, p=0.063). In linear regression analyses, gender, TG
and HDL-C level, BMI and Framingham score were found associated parameters for
the presence of MetS in all participants. Conclusions: Although there is an acceptable awareness in
terms of cardiovascular disease knowledge, it was founded almost a fifth of the
studied personnel has MetS. So, the components of MetS should be implied more
effectively as well as its importance to the healthy persons in primary
care.  

Amaç: Bu çalışmanın amacı Çukurova Üniversitesi'nde çalışan sağlıklı
personelde MetS sıklığını araştırmaktı. Ayrıca katılımcıların KV risk
faktörleri bilgi düzeyini (KARRIF-BD) ve Framingham risk skorunu hesaplayarak
bu değişkenlerin birbiriyle olan ilişkilerini incelemeyi amaçladık. Yöntem:
Çukurova Üniversitesi akademik ve idari kadroda çalışan toplam 155 sağlıklı
gönüllü katılımcı çalışmaya dahil edilmiştir. Tüm katılımcıların
sosyo-demografik özellikleri, antropometrik ölçümleri, kan basıncı değerleri ve
serum parametreleri kaydedildi. Katılımcılarda MetS tanısı için IDF
(International Diabetes Foundation) kriterleri kullanıldı.  Ayrıca tüm katılımcıların Framingham risk
skoru ve KARRIF-BD skoru hesaplandı. Bulgular: Tüm katılımcıların
ortalama yaşı 45,6 ± 7,8 yıl idi. IDF kriterlerine toplam 29 hastada (% 18,7)
MetS tanısı konuldu. MetS grubu ve kontrol grubu KARRIF-KL skoru ortalaması
birbirine benzer bulundu (21,2 ± 2,7 ve 20,7 ± 3,9, p = 0,50). Framingham skoru
ortalaması ise  MetS grubunda kontrol
grubuna göre daha yüksekti. Ayrıca MetS grubunda kontrol grubuna göre aortik
doku dopler hızı (PWVAo) hafif yüksek saptandı (8,4 ± 1,36 ve 7,8 ± 1,57, p =
0,063).  Doğrusal regresyon analizinde
cinsiyet, TG ve HDL-Kolesterol düzeyi, Vücut Kitle indeksi (VKI) ve Framingham
skoru tüm katılımcılarda MetS varlığı ile ilişkili parametreler olarak
saptandı. Sonuçlar: Mevcut çalışma sonuçlarına göre, çalışılan personelin
yaklaşık beşte birinde MetS bulunmaktadır. Çalışmada kardiyovasküler
hastalıklar bilgisi konusunda kabul edilebilir bir farkındalık bulunmasına
rağmen, çalışılan personelin yaklaşık beşte birinde MetS saptanmıştır. Bu
sebeple MetS önemi kadar bileşenleri de birinci basamakta sağlıklı kişiler için
yeterince vurgulanmalıdır.

Anahtar Kelimeler

Metabolic syndrome, Framingham score, CARRIF-KL

Kaynakça

• 1. P.J. Miranda, R.A. DeFronzo, R.M. Califf, J.R. Guyton. Metabolic syndrome: definition, pathophysiology, and mechanisms. Am. Heart J. 149, 33–45 (2005).
• 2. Alberti KG, Zimmet PZ. Definition, diagnosis and classification of diabetes mellitus and its complications: report of a WHO consultation. Geneva, World Health Organization; Diabet Med. 1998 Jul;15(7):539-53.
• 3. Balkau B, Charles MA. Comment on the provisional report from the WHO consultation. European Group for the Study of Insulin Resistance (EGIR). Diabet Med 1999, 16:442-443.
• 4. 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.
• 5. Einhorn D, Reaven GM, Cobin RH, Ford E, Ganda OP, Handelsman Y, Hellman R, Jellinger PS, Kendall D, Krauss RM, Neufeld ND, Petak SM, Rodbard HW, Seibel JA, Smith DA, Wilson PW. American College of Endocrinology position statement on the insulin resistance syndrome. Endocr Pract 2003, 9:237-252.
• 6. Alberti KG, Zimmet P, Shaw J. The metabolic syndrome--a new worldwide definition. Lancet 2005, 366:1059-1062.
• 7. Wilson PWF, D’Agostino RB, Levy D, Belanger AM, SilbershatzH, Kannel WB. Prediction of coronary heart diseaseusing risk factor categories. Circulation 1998;97:1837–1847.
• 8. Thanavaro JL, Moore SM, Anthony M, Narsavage G, Delicath T. Predictors of health promotion behavior in women without prior history of coronary heart disease. Applied Nursing Research 2006; 19: 149–55.
• 9. Arıkan İ, Metintaş S, Kalyoncu C, Yıldız Z. Kardiyovasküler hastalıklar risk faktörleri bilgi düzeyi (KARRIF-BD) Ölçeği’nin geçerlik ve güvenirliği. Türk Kardiyoloji Derneği Araştırmaları 2009; 37 (1): 35-40.
• 10. Kannel W, McGee D, Gordon T. A general cardiovascular risk profile: the Framingham Study. Am J Cardiol 1976;38:46-51.
• 11. O'Donnell CJ, Elosua R . Cardiovascular risk factors. Insights from Framingham Heart Study. Rev Esp Cardiol 61 (3):Mar 2008; 299–310.
• 12. Asmar R, Benetos A, Topouchian J, et al. Assesment of arterial distensibility by automatic pulse wave velocity measurment. Validation and clinical application studies.Hypertension 1996;26:485-90.).
• 13. Altan Onat, Süleyman Karakoyun, Tuğba Akbaş, Fatma Özpamuk Karadeniz, Yusuf Karadeniz, Hakan Çakır, Barış Şimşek, Günay Can. Turkish Adult Risk Factor survey 2014: Overall mortality and coronary disease incidence in Turkey’s geographic regions. Türk Kardiyol Dern Arş - Arch Turk Soc Cardiol 2015;43(4):326–332 doi: 10.5543/tkda.2015.80468.
• 14. Kozan O, Oguz A, Erol C, Senocak M, Ongen Z, Abacı A, et al. Results of METSAR. Metabolic Syndrome Research Group. Antalya: XX. National Congress of Cardiology; 2004. Available from: http://www.metsend.org/ pdf/Metsar-metsend.pdfMetabolik
• 15. Ozsahin AK, Gokcel A, Sezgin N, Akbaba M, Guvener N, Ozisik L, Karademir BM. Prevalence of the metabolic syndrome in a Turkish adult population. Diabetes Nutr Metab. 2004 Aug;17(4):230-4.
• 16. Oguz A, Sağun, G, Uzunlulu, M, et al. Frequency of abdominal obesity and metabolic syndrome in healthcare workers and their awareness levels about these entities. Turk Kardiyol Dern Ars 2008;36(5):302-09.
• 17. Tahsin Çelepkolu, Pakize Gamze Erten Bucaktepe, Hatice Yüksel, Yılmaz Palancı, Sercan Bulut Çelik, Hüseyin Can, Ahmet Yılmaz, Veysel Kars, Gökhan Usman, Necmi Arslan, Arzu Evliyaoğlu Taşkesen, İlknur Aslan, Özgür Erdem, Ata Akıl, Erkan Kıbrıslı, Bayram Başdemir, Hamza Aslanhan, Mehmet Halis Tanrıverdi. The prevalence and level of awareness for metabolic syndrome among primary health care professionals in the Southeastern Anatolia.. Türk Aile Hek Derg 2016;20 (3): 104-114. doi: 10.15511/tahd.16.21104.
• 18. Pereira, T, Maldonado, J, Polonia J, Silva J.A, Morais J, et al. Aortic pulse wave velocity and HeartSCORE: Improving cardiovascular risk stratification. A sub-analysis of the EDIVA (Estudo de DIstensibilidade VAscular) project Blood Pressure; 23: 109–115, 2014.
• 19. Willum-Hansen T, Staessen JA, Torp-Pedersen C et al.Prognostic value of aortic pulse wave velocity as index of arterial sertlik in the general population. Circulation, 2006;113:664–70.
• 20. Meaume S, Benetos A, Henry OF et al. Aortic pulse wave velocity predicts cardiovascular mortality in subjects .70 years of age. Arterioscler Thromb Vasc Biol, 21:2046–50, 2001.
• 21. Ben-Shlomo, Y. et al. Aortic Pulse Wave Velocity Improves Cardiovascular Event Prediction, An Individual Participant Meta-Analysis of Prospective Observational Data From 17,635 Subjects., Journal of the American College of Cardiology Vol. 63, No. 7, 2014.
• 22. Marso SP, Frutkin AD, Mehta SK, et al. Intravascular ultrasound measures of coronary atherosclerosis are associated with the Framingham risk score: an analysis from a global IVUS registry.EuroIntervention: 2009 Jun;5 (2):212-8.
• 23. Takeshita H, Shimada Y, Kobayashi Y, et al. Impact of body mass index and Framingham risk score on coronary artery plaque: Osaka City Med J. 2008 Jun;54 (1):31-9
• 24. Rinehart S, Qian Z, Vazquez G, et al. Demonstration of the Glagov phenomenon in vivo by CT coronary angiography in subjects with elevatedFramingham risk: Int J Cardiovasc Imaging. 2012 Aug;28 (6):1589-99.