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1.
Nutrients ; 10(10)2018 Oct 11.
Artigo em Inglês | MEDLINE | ID: mdl-30314363

RESUMO

Data on the nutritional situation and prevalence of micronutrient deficiencies in Azerbaijan are scarce, and knowledge about anemia risk factors is needed for national and regional policymakers. A nationally representative cross-sectional survey was conducted to assess the prevalence of micronutrient deficiencies, over- and undernutrition, and to disentangle determinants of anemia in children and women in Azerbaijan. The survey generated estimates of micronutrient deficiency and growth indicators for children aged 0⁻59 months of age (6⁻59 months for blood biomarkers) and non-pregnant women 15⁻49 years of age. Questionnaire data, anthropometric measurements, and blood samples were collected to assess the prevalence of under- and over-nutrition, anemia, iron deficiency, and iron deficiency anemia, in both groups. In children only, vitamin A deficiency and zinc deficiency were also assessed. In women only, folate and vitamin B12 deficiencies and vitamin A insufficiency were assessed. In total, 3926 household interviews were successfully completed with a response rate of 80.6%. In the 1455 children, infant and young child feeding practices were relatively poor overall; the prevalence of wasting and stunting were 3.1% and 18.0%, respectively; and 14.1% of children were overweight or obese. The prevalence of anemia was 24.2% in 6⁻59 months old children, the prevalence of iron deficiency was 15.0% in this age group, and the prevalence of iron deficiency anemia was 6.5%. Vitamin A deficiency was found in 8.0% of children, and zinc deficiency was found in 10.7%. Data from 3089 non-pregnant women 15⁻49 years of age showed that while undernutrition was scarce, 53% were overweight or obese, with increasing prevalence with increasing age. Anemia affected 38.2% of the women, iron deficiency 34.1% and iron deficiency anemia 23.8%. Vitamin A insufficiency was found in 10.5% of women. Folate and vitamin B12 deficiency were somewhat more common, with prevalence rates of 35.0% and 19.7%, respectively. The main risk factors for anemia in children were recent lower respiratory infection, inflammation and iron deficiency. In women, the main risk factors for anemia were iron deficiency and vitamin A insufficiency. Anemia is a public health problem in Azerbaijani children and women, and additional efforts are needed to reduce anemia in both groups.


Assuntos
Anemia/epidemiologia , Desnutrição/epidemiologia , Micronutrientes/deficiência , Estado Nutricional , Hipernutrição/epidemiologia , Adolescente , Adulto , Anemia/sangue , Anemia/etiologia , Anemia Ferropriva/sangue , Anemia Ferropriva/epidemiologia , Anemia Ferropriva/etiologia , Azerbaijão/epidemiologia , Pré-Escolar , Feminino , Ácido Fólico/sangue , Deficiência de Ácido Fólico/sangue , Deficiência de Ácido Fólico/complicações , Deficiência de Ácido Fólico/epidemiologia , Humanos , Lactente , Recém-Nascido , Ferro/sangue , Masculino , Desnutrição/sangue , Desnutrição/complicações , Micronutrientes/sangue , Pessoa de Meia-Idade , Hipernutrição/sangue , Hipernutrição/complicações , Prevalência , Fatores de Risco , Deficiência de Vitamina A/sangue , Deficiência de Vitamina A/complicações , Deficiência de Vitamina A/epidemiologia , Deficiência de Vitamina B 12/sangue , Deficiência de Vitamina B 12/complicações , Deficiência de Vitamina B 12/epidemiologia , Adulto Jovem , Zinco/sangue , Zinco/deficiência
2.
ScientificWorldJournal ; 2014: 753860, 2014.
Artigo em Inglês | MEDLINE | ID: mdl-25003153

RESUMO

Large exposure of skin area of an image is considered obscene. This only fact may lead to many false images having skin-like objects and may not detect those images which have partially exposed skin area but have exposed erotogenic human body parts. This paper presents a novel method for detecting nipples from pornographic image contents. Nipple is considered as an erotogenic organ to identify pornographic contents from images. In this research Gentle Adaboost (GAB) haar-cascade classifier and haar-like features used for ensuring detection accuracy. Skin filter prior to detection made the system more robust. The experiment showed that, considering accuracy, haar-cascade classifier performs well, but in order to satisfy detection time, train-cascade classifier is suitable. To validate the results, we used 1198 positive samples containing nipple objects and 1995 negative images. The detection rates for haar-cascade and train-cascade classifiers are 0.9875 and 0.8429, respectively. The detection time for haar-cascade is 0.162 seconds and is 0.127 seconds for train-cascade classifier.


Assuntos
Algoritmos , Literatura Erótica , Interpretação de Imagem Assistida por Computador/métodos , Reconhecimento Automatizado de Padrão/métodos , Humanos , Sensibilidade e Especificidade
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