Obez ve preobez hastalarda kardiyovasküler risk faktörlerinin antropometrik ve metabolik parametreler ile ilişkisi
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Dosyalar
Tarih
2018
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Düzce Üniversitesi
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
Amaç: Bu çalışmada, obezite polikliniğimize kilo verme isteğiyle başvuran hastalarda kardiyovasküler risk faktörlerinin, antropometrik ve metabolik parametreler ile arasındaki ilişki incelemeyi amaçladık. Yöntem: Retrospektif özellikteki çalışmamıza, Düzce Üniversitesi Tıp Fakültesi Aile Hekimliği Anabilim Dalı Obezite Polikliniği'ne Haziran 2016 – Haziran 2018 tarihleri aralığında başvuran ve çalışma kriterlerine uyan 963 kişi alındı. Hastaların antropometrik ve BİA ölçümleri, laboratuvar değerleri dosyalardan tarandı ve veriler elde edildi. FRS değerleri, framingham risk hesap cetvelinden hesaplandı. Kadınlar kendi içinde dört gruba, erkekler de kendi içinde dört gruba ayırılarak değerlendirildi. Bulgular: Çalışmamızın %73,4'ünü kadınlar oluşturuyordu. FRS seviyesi erkeklerde anlamlı seviyede daha yüksekti (p<0,001) ve obezite derecesi ile birlikte artış gösteriyordu (p=0,001). Kadınlarda FRS ile yaş, VKİ, VYY, VYO, BÇ, BKO, BBO, APG, TK, LDL-K, TG, SKB ve DKB arasında pozitif ilişki bulunmuştur (her biri için p<0,001). Erkeklerde FRS ile yaş, VYO, BKO, APG, TK, LDL-K, TG, SKB ve DKB arasında pozitif yönlü anlamlı ilişki bulunmuştur (p<0,001). Erkek grupları ve kadın gruplarının kendi içindeki VKİ, BÇ, KÇ, BBO, BMH, VYY, VYA, YVA, TVS, VYO, insülin, HOMA-IR, APG, SKB ve DKB seviyeleri preobezlerden evre 3 obezlere doğru anlamlı artış göstermiştir (p<0,05). Sonuç: Obezitenin kardiyovasküler risk faktörlerine, antropometrik ve metabolik parametrelere etkisi; cinsiyet ve obezite seviyesine göre değişmektedir. Hastalar multidispliner yaklaşımla ele alınmalı, hastaların takip ve tedavisini kişiye özel değerlendirmeli ve obezitenin komplikasyonları açısından dikkatli olunmalıdır. Birinci basamakta, normal kilolu bireyleri obeziteden korumalı, preobez ve obez bireylerin ideal kilolarına kavuşmaları için gerekli müdaheleler yapılmalıdır.
Aim: In this study, we aimed to investigate the relationship of cardiovascular risk factors to anthropometric and metabolic parameters in patients who applied to our obesity clinic with the desire to lose weight. Method: In our retrospective study, 963 people were included in the Obesity Outpatient Clinic of the Department of Family Medicine at Duzce University Faculty of Medicine, between June 2016 and June 2018. Anthropometric and BIA measurements, laboratory values of the patients were scanned and data were obtained. FRS values were calculated from the framingham risk calculator. Women were divided into four groups and men were divided into four groups. Results: 73.4 % of our study consisted of women. The level of FRS was significantly higher in males (p<0.001) and increased with obesity (p = 0.001). There was a positive correlation between FRS and age, BMI, BF%, VFR, WC, WHR, WHtR, FBG, TC , LDL-C, TG, SBP and DBP in women (p<0.001 for each). A significant positive correlation was found between FRS and age, VFR, WHR, FBG, TC, LDL-C, TG, SBP and DBP in males (p<0.001). The levels of BMI, WC, HC, WHtR, BMR, BF%, FM, FFM, TBW, VFR, insulin, HOMA-IR, FBG, SBP, and DBP were significantly increased from preobes to stage 3 obese among male and female groups (p< 0.05). Conclusion: The effects of obesity to cardiovascular risk factors, anthropometric and metabolic parameters changed with gender and obesity level. Patients should be treated with a multidisciplinary approach, follow-up and treatment of patients should be evaluated individually and obesity complications should be considered carefully. In primary care, obese individuals should be protected from obesity. Necessary interventions should be done for pre-obese and obese individuals to make them reach their ideal weight.
Aim: In this study, we aimed to investigate the relationship of cardiovascular risk factors to anthropometric and metabolic parameters in patients who applied to our obesity clinic with the desire to lose weight. Method: In our retrospective study, 963 people were included in the Obesity Outpatient Clinic of the Department of Family Medicine at Duzce University Faculty of Medicine, between June 2016 and June 2018. Anthropometric and BIA measurements, laboratory values of the patients were scanned and data were obtained. FRS values were calculated from the framingham risk calculator. Women were divided into four groups and men were divided into four groups. Results: 73.4 % of our study consisted of women. The level of FRS was significantly higher in males (p<0.001) and increased with obesity (p = 0.001). There was a positive correlation between FRS and age, BMI, BF%, VFR, WC, WHR, WHtR, FBG, TC , LDL-C, TG, SBP and DBP in women (p<0.001 for each). A significant positive correlation was found between FRS and age, VFR, WHR, FBG, TC, LDL-C, TG, SBP and DBP in males (p<0.001). The levels of BMI, WC, HC, WHtR, BMR, BF%, FM, FFM, TBW, VFR, insulin, HOMA-IR, FBG, SBP, and DBP were significantly increased from preobes to stage 3 obese among male and female groups (p< 0.05). Conclusion: The effects of obesity to cardiovascular risk factors, anthropometric and metabolic parameters changed with gender and obesity level. Patients should be treated with a multidisciplinary approach, follow-up and treatment of patients should be evaluated individually and obesity complications should be considered carefully. In primary care, obese individuals should be protected from obesity. Necessary interventions should be done for pre-obese and obese individuals to make them reach their ideal weight.
Açıklama
YÖK Tez No: 538661
Anahtar Kelimeler
Aile Hekimliği, Family Medicine, Antropometri, Anthropometry, Elektriksel impedans, Electric impedance, Kardiyovasküler hastalıklar, Cardiovascular diseases, Kardiyovasküler sistem, Cardiovascular system, Metabolizma, Metabolism, Obezite, Obesity, Risk analizi, Risk analysis, Risk faktörleri, Risk factors, Antropometrik ölçümler, biyoelektrik impedans analizi, framingham risk skoru, obezite, Anthropometric measurements, bioelectrical impedance analysis, framingham risk score, obesity
