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ABSTRACT: The purpose of this study was to identify the main dietary patterns in the Lithuanian urban population and to determine their association with socio-demographic factors.
Data from the survey performed in the framework of the HAPIEE (Health, Alcohol, Psychosocial factors In Eastern Europe) study were presented. A random sample of 7,087 individuals aged 45-72 years was screened in 2006-2008.
Factor analysis of the main dietary patterns revealed a five-factor solution, which accounted for 47.8% of the variance: "fresh vegetables and fruit"; "sweets"; "porridge and cereals"; "potatoes, meat, boiled vegetables and eggs"; "chicken and fish". "Fresh vegetables and fruits" factor and "sweets" factor were inversely associated with age both in men and women: older people consumed less frequent than average of the particular food groups. Dietary patterns of people with good self-rated health and university education were healthier than among people with lower education and poorer health.
Nutrition education efforts should focus on improving food diversity, with particular targeting of lower educated, single and older people.
International Journal of Public Health 04/2011; 56(2):209-16. · 2.54 Impact Factor
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ABSTRACT: Depression is one of the most common problems after stroke. Depression is not only frequently occurring outcome of stroke, but stroke is also a clear risk factor for depression. Depression after stroke can affect anyone regardless of his/her age, sex, background, or the severity of stroke. It can develop immediately after the stroke or weeks or months later. Many people are not routinely assessed for depression after stroke, and only a minority are properly diagnosed and treated. Patients with poststroke depression have lower functional status, increased cognitive impairment, and higher mortality rates than stroke patients without depression. Poststroke depression is also associated with poor psychosocial outcome and poor quality of life; therefore, there is a strong case for the early diagnosis and treatment of poststroke depression.
Medicina (Kaunas, Lithuania) 02/2007; 43(1):1-9. · 0.42 Impact Factor
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ABSTRACT: The aim of the study was to evaluate the suitability of the SF-12 questionnaire for the evaluation of the quality of life in 25-84-year-old inhabitants of Kaunas city and to compare quality of life between men and women as well as between socially and demographically different groups.
The study sample consisted of randomly selected inhabitants of Kaunas city, stratified by age and sex. The suitability of the questionnaire for the evaluation of the quality of life in the selected contingent was verified using Cronbach's alpha coefficient. The convergent validity of the questionnaire was assessed by the strength of the linear relationship between the domains of the questionnaire, calculating Pearson's correlation coefficients. We calculated mean ranges of the values of the questionnaire and compared the distribution of values.
Cronbach's alpha values indicated a very strong internal consistency of the mental and physical domains of the SF-12 questionnaire (0.87 and 0.88, respectively). Women reported lower quality of life in the domains of mental health and physical health-pain as compared to men. People who were not living alone, with higher level of education, and employed reported better physical and mental health than those living alone, with lower level of education, or unemployed. In addition to that, people who were engaged in mental work during the study or had worked such work before reported better physical and mental health.
The questionnaire SF-12 is suitable for the evaluation of the quality of life in the population of Kaunas city. Women reported lower quality of life in mental health domain than men did. The evaluations of the quality of life worsened with increasing age and lower social and demographic status.
Medicina (Kaunas, Lithuania) 02/2007; 43(6):501-7. · 0.42 Impact Factor
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ABSTRACT: The aim of the study was to compare the quality of life among stroke survivors and healthy controls and to evaluate the influence of age, sex, and social and demographic factors on the quality of life. Contingent and methods. The case group consisted of 508 inhabitants of Kaunas city who were 25-84 years of age and had experienced their first stroke. The control group consisted of age- and sex-stratified randomly selected 508 stroke-free inhabitants of Kaunas city. The quality of life was evaluated using the SF-12 questionnaire. The study compared the quality of life between stroke survivors and controls in eight domains of quality of life and compared the evaluation of quality of life considering social and demographic features. RESULTS: In the domain of physical and mental health, stroke survivors presented poorer evaluation of their quality of life compared to controls except for the evaluations of mental health in the age groups of 25-34 and 35-44 years. As compared to healthy controls, stroke survivors presented poorer evaluation of their quality of life in all domains except for pain. Only in the control group, females presented poorer evaluation of physical health, whereas no differences in the evaluation of mental health between sexes were found. The evaluation of physical health in both groups worsened with age. Both stroke survivors and controls presented better evaluation of their physical health if they were living not alone, were better educated, and were employed compared to those who were living alone, had poorer education level, and were unemployed. In addition, controls who were currently or previously engaged in mental work evaluated their physical health better. CONCLUSIONS: Stroke survivors presented poorer evaluations of their quality of life in both physical and mental health domains compared to controls. Only in the control group, females evaluated their physical health worse than males did. In both groups studied, poorer evaluation of physical health was associated with older age and lower social and demographic status. Relationship between mental health and subjects' social and demographic status was not statistically significant in either of the studied groups.
Medicina (Kaunas, Lithuania) 02/2007; 43(9):736-45. · 0.42 Impact Factor
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ABSTRACT: The quality of life after stroke and the methods of measuring this aspect of the disease have been viewed with a growing interest. The measurement has been focused on the physical, psychological, social, and functional aspects of living and is generally based on the patients' subjective perception of his/her general health and well-being. Seven generic measurement scales and three recently developed stroke-specific scales have been assessed and discussed. The stroke-specific quality of life measures described in this review are as follows: the Stroke Adapted Sickness Impact Profile, the Stroke Impact Scale, and the Stroke-Specific Quality of Life Measure. The various factors leading to a deterioration of the quality of life and influencing the quality of life scores are discussed and defined. Moreover, the necessity of further research is stressed.
Medicina (Kaunas, Lithuania) 02/2006; 42(9):709-16. · 0.42 Impact Factor
