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Profile of population of PURE Poland study at higher risk of developing chronic diseases according to AHEI-2010 score

Session Poster Session 2

Speaker Alicja Basiak-Rasala

Event : ESC Preventive Cardiology (Formerly EuroPrevent) 2018

  • Topic : preventive cardiology
  • Sub-topic : Nutrition, Malnutrition and Heart Disease
  • Session type : Poster Session

Authors : A Basiak (Wroclaw,PL), DGD Dagmara Gawel-Dabrowska (Wroclaw,PL), AT Andrzej Tukiendorf (Gliwice,PL), KPZ Katarzyna Poltyn-Zaradna (Wroclaw,PL), MW Maria Wolyniec (Wroclaw,PL), AS Andrzej Szuba (Wroclaw,PL), KZ Katarzyna Zatonska (Wroclaw,PL)

A Basiak1 , DGD Dagmara Gawel-Dabrowska1 , AT Andrzej Tukiendorf2 , KPZ Katarzyna Poltyn-Zaradna1 , MW Maria Wolyniec1 , AS Andrzej Szuba3 , KZ Katarzyna Zatonska1 , 1Wroclaw Medical University, Department of Social Medicine - Wroclaw - Poland , 2Center of Oncology - Maria Sklodowska-Curie Memorial Institute - Gliwice - Poland , 3Wroclaw Medical University, Division of Angiology - Wroclaw - Poland ,

European Journal of Preventive Cardiology ( May 2018 ) 25 ( Supplement 1 ), 82

Background The Alternate Healthy Eating Index (AHEI) is based on foods and nutrients of proven impact on the risk of chronic diseases. According to literature higher AHEI score is associated with lower risk of CVD, diabetes, colorectal cancer, heart failure, total cardiovascular mortality and breast cancer. Cardiovascular diseases are major cause of death worldwide. AHEI score is an important tool in prevention of chronic diseases. Purpose The aim of the study was to identify the socio-demographic profile of the population at risk of developing chronic diseases according to AHEI – 2010 score.  Methods Poland is one of the 21 countries enrolled in global Prospective Urban and Rural Epidemiology Study (PURE). Study population consists of  2026 participants aged between 30 and 85 years, who completed Food Frequency Questionnaire (FFQ). AHEI-2010 score was calculated according to methodology described by Chiuve et al.(1) with exclusion of trans unsaturated fatty acids due to lack of data. Statistical analysis of association between AHEI score and sex, urban and rural place of residence was calculated with the use of t-test. To assess the association between AHEI, age and level of education Pearson’s linear correlation was used (p<0,05).
Results: Participants living in rural areas had significantly (p<0,05) lower AHEI score of the diet than those living in urban areas (Mean: 56,04 vs. 58,97). Men had significantly (p<0,05) lower AHEI score than women (Mean 55,48 vs. 59.12). There was weak, but significant positive correlation between the AHEI score and age of participants (correlation of 0,1), as well as with level of education (correlation of 0,15). Marital status was not a significant factor differentiating risk of developing chronic diseases according to AHEI-2010 score.  Conclusions Dietary counselling in prevention of chronic diseases should be provided predominantly for middle aged men, living in rural areas, with lower level of education.

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