title: Demographic and clinical features of gout patients in Turkey: a multicenter study.
abstract: Gout results from multifactor interactions between gender, age, genetic and environmental factors. Environmental factors underlying gout and precipitating factors triggering acute attacks might vary in different populations with different lifestyles. In this study, we aimed to collect data regarding the demographic and clinical features, comorbid factors, and precipitating factors associated with the initiation of acute attacks in gout patients in Turkey. A total of 312 patients were included in this study (mean age, 58.8 ± 13.8 years; female/male ratio, 55/257). The demographic features, alcohol intake, clinical and laboratory features, and comorbid conditions including obesity, diabetes mellitus, hyperlipidemia, hypertension, and coronary heart disease were noted in a standard questionnaire. Precipitating factors initiating acute attacks (if any) were also noted. The patients were divided into 4 groups according to the region of location as central Anatolian region, southeast Anatolian region, Aegean region, and Trakya region. Our results were compared according to the gender and the location of the patients. The mean age at the start of the symptoms was 10 years higher in women (60.4 ± 14.8 and 50.6 ± 13.5 years in women and men, respectively, p < 0.001).Obesity was present in 40.1 %, diabetes mellitus in 17.9 %, hyperlipidemia in 30.1 %, hypertension in 53.5 %, coronary artery disease in 17 %, and nephrolithiasis in 21.8 % of patients. Precipitating factors triggering gout flares were as follows: diet (high consumption of meat or fish) in 46.5 %, alcohol consumption in 15.7 %, diuretics in 8.3 %, diet or diuretics in 5.1 %, diet or alcohol in 4.5 %, diet or alcohol or diuretics in 1.6 %, others in 4.2 %, and none in 14.1 %. The presence of diabetes and diuretic use was more common among women. Use of diuretics is a more common trigger for gout flares among women. On the other hand, various comorbid conditions, such as obesity and hypertension, and triggers for gout flares may differ between patients living in different geographic regions. In summary, we reported the first data regarding clinical and demographic characteristics of gout in Turkey. The majority of our patients could describe at least one "trigger" that initiated gout flare. Both comorbid conditions and triggers of attack might differ between men and women, and in different geographic areas. Better knowledge of the modifiable risk factors can be useful for the management strategy to optimize long-term patient outcomes in local clinics.
authors.affiliation: Division of Rheumatology, Department of Internal Medicine, Faculty of Medicine, Gazi University, Beşevler, Ankara, Turkey. makifozturk@yahoo.com
authors.forename: Mehmet Akif
authors.initials: MA
authors.lastname: Öztürk
authors.forename: Arif
authors.initials: A
authors.lastname: Kaya
authors.forename: Soner
authors.initials: S
authors.lastname: Şenel
authors.forename: Salim
authors.initials: S
authors.lastname: Dönmez
authors.forename: Ayşe
authors.initials: A
authors.lastname: Balkarlı
authors.forename: Veli
authors.initials: V
authors.lastname: Çobankara
authors.forename: Çiğdem
authors.initials: Ç
authors.lastname: Erhan
authors.forename: Mehmet
authors.initials: M
authors.lastname: Sayarlıoğlu
authors.forename: Yunus
authors.initials: Y
authors.lastname: Ugan
authors.forename: Ş Ercan
authors.initials: ŞE
authors.lastname: Tunç
authors.forename: Yavuz
authors.initials: Y
authors.lastname: Pehlivan
authors.forename: Bünyamin
authors.initials: B
authors.lastname: Kısacık
authors.forename: Abdurrahman
authors.initials: A
authors.lastname: Tufan
authors.forename: Ahmet Mesut
authors.initials: AM
authors.lastname: Onat
authors.forename: Engin
authors.initials: E
authors.lastname: Tezcan
authors.forename: Gözde
authors.initials: G
authors.lastname: Yıldırım Çetin
authors.forename: Omer Nuri
authors.initials: ON
authors.lastname: Pamuk
mesh_terms: D000328:Adult; D000367:Age Factors; D017668:Age of Onset; D000368:Aged; D000369:Aged, 80 and over; D000428:Alcohol Drinking / Q000009:adverse effects* / Q000453:epidemiology; D015897:Comorbidity; D003920:Diabetes Mellitus / Q000453:epidemiology; D005260:Female; D006073:Gout / Q000175:diagnosis* / Q000453:epidemiology / Q000209:etiology; D006801:Humans; D006949:Hyperlipidemias / Q000453:epidemiology; D006973:Hypertension / Q000453:epidemiology; D008297:Male; D008875:Middle Aged; D009765:Obesity / Q000453:epidemiology; D015995:Prevalence; D012307:Risk Factors; D012737:Sex Factors; D014421:Turkey / Q000453:epidemiology