Socio-economic inequalities in health in Lithuania: indicators for monitoring and latest situation

Transcription

1 Socio-economic inequalities in health in Lithuania: indicators for monitoring and latest situation Report, April 2, 22 Project financed by WHO PAE-ECHP (Allotment EU LIUCOO 2 RB) Prepared by: Prof.Zilvinas Padaiga Department of Preventive Medicine, Kaunas University of Medicine, Eiveniu str.4, LT-37, Kaunas, Lithuania

2 Contents Introduction. V.Grabauskas, Z.Padaiga 2 1. Social and territorial inequalities in mortality of Lithuanian population. R.Kalediene, J.Petrauskiene 5 2. Five-year changes of standardized avoidable mortality in Lithuania. A.Gaizauskiene Trends in health behavior in relation to social determinants. J.Klumbiene, J.Petkeviciene Socio-economic differences in health behaviors among Lithuanian school-aged children: results from 1994 and 1998 surveys. L.Sumskas, A.Zaborskis Changes in socio-economical differences of newborn health during Z.Padaiga, A.Gaizauskiene. 35 References

3 INTRODUCTION V.Grabauskas, Z.Padaiga Prior to the 199s researchers had demonstrated socioeconomic inequalities in health in Lithuania, which is a relatively homogeneous country. However, it was only through the stimulating role of WHO that a systematic research effort into health inequalities began in Under the auspices of this collaboration, Lithuania joined the Health Inequalities project. The data from the National Health Information Centre, the Ministries of Education, Health, Social Welfare and Labour, combined with the datasets from a number of research projects Countrywide Integrated Non-communicable Disease Intervention Programme (CINDI), Health Behaviour Monitoring among the Adult Population (within the Finnish Baltic Health Monitoring Programme), Health Behaviour Monitoring in Schoolchildren, National Household Survey, Newborn Register, Accessibility of Healthcare Project constituted the database for this project. The first report on health inequalities in Lithuania "Equity in health and healthcare in Lithuania. A situation analysis" was published in 1998 [1]. Results showed that extent of socioeconomic inequalities in health in Lithuania varied depending on the health and socioeconomic indicators selected. Data from the mortality register indicate that education, socioeconomic group and marital status were significant predictors of health inequality. A higher level of education, higher income and an urban place of residence were strongly positively related with self-reported health status and health behaviour, especially for smoking and alcohol abuse for men, and for more healthy nutrition. Large inequalities in neonatal health by the mother's level of education and marital status were discovered, with maternal smoking, alcohol and drug abuse accounting for a large proportion of the observed differences. Finally, socioeconomic inequalities were found for healthcare accessibility, lower socioeconomic status predicting worse access to services [2 5]. The research activities have resulted in policy formulation addressing health inequalities in Lithuania. The Lithuanian Health Programme [6], adopted by Parliament in July 1998, set three major objectives aiming to reduce mortality and increase average life expectancy, equality in health and healthcare, and improve quality of life. The programme contains a separate target on equality which states that By the year 21 differences in health and healthcare between various socioeconomic population groups should be reduced by 25 per cent. The first step in the strategy to achieve this is defined as follows: By the year inequalities in health and healthcare between different socioeconomic groups should be assessed and indicators for monitoring proposed. Further on, the problems of health inequalities have to be revised as stated: By the year 25, to supplement health policy by measures aimed at the reduction of inequalities in health and healthcare. The strategy includes intersectoral collaboration and systematic evaluation of the impact of all legal Acts on health inequalities. The National Board of Health is responsible for monitoring progress in this area. Following the adoption of the Health Programme the National Board of Health prepared its first annual report, in which it undertook to bring health inequalities and actions to the attention of Parliament in December 1998 [7]. The report was distributed, presented and discussed on several occasions at international, national, regional and municipal levels. Following the presentation of the report, parliament adopted a resolution requesting that action should focus on ensuring equal rights of access to health for all (by decreasing health differences among the rural and urban populations, and populations with different education, income level and age groups) by active cooperation of the state, local self-government institutions and non-governmental 2

4 organizations. In 1999 the Health Minister issued an order certifying the programme for competence assessment by heads of healthcare institutions involving socioeconomic health inequalities among other major topics. This report is based on continous research on health inequalities in Lithuania. As a first step, following the National Health Program, the list of indicators for monitoring socioeconomic inequalities in health and health care was developed (Table 1). Mortality-based indicators, newborn health, health behavior in adults and schoolchildren and health care accessibility will be monitored on assigned frequency using routine data sources or surveys (for health care accessibility). The next step was to analyze and present the latest available data on socioeconomic inequalities in health in all listed indicators group, except health care accessibility. Table 1. Indicators of socioeconomic inequalities in health and health care, frequency of monitoring and data sources. Health and health care Socioeconomic indicators Monitoring Data sources indicators frequency 1. Mortality (by gender and Place of residency: urbanrural Annually Mortality age groups): all causes, cardiovascular diseases, malignant neoplasms, external Administrative regions Every 3 yrs register causes, respiratory diseases, Education Every 1 yrs, other causes Marital status based on census data 2. Life expectancy (by gender) Place of residency: urbanrural Annually Administrative regions Every 3 yrs 3. Avoidable mortality Place of residency: urbanrural Every 5 yrs Administrative regions 4. Low birth weight newborns Mothers education Every 3 yrs Newborn and stillbirths 5. Health behavior of adult population (by gender and age groups): Self-assessed health; outpatient visits per year; stress during last month; depresion; oral health; smoking; alcohol use; nutrition; physical activity; traffic safety Mothers marital status Education Place of residency: urban/rural Income Every 4 yrs Every 2 yrs Every 2 yrs register Health Behaviour Monitoring among the Adult Population 6. Health behavior of schoolchildren (by gender): Self-assessed health; suicidal ideas; oral health; smoking; alcohol use; drug use; nutrition; physical activity; traffic safety Family wellbeing index Parents profession Place of residency Every 2-4 yrs Health Behaviour Monitoring in Schoolchildren 7. Health care accessibility Profession Education Every 3 yrs Surveys on representative samples of population 3

5 1. SOCIAL AND TERRITORIAL INEQUALITIES IN MORTALITY OF LITHUANIAN POPULATION Introduction R. Kalediene, J. Petrauskiene During the last decade of the 2 th century Lithuania has experienced radical changes in political, social and economic situation, in the process of the shift from being a Soviet republic to that of being an independent state with newly developing market economy. Since the beginning of the political and economic reforms in 1989, and after the collapse of the Soviet Union, circumstances in Lithuania have changed dramatically and the population of the country has been exposed to a new unfamiliar social environment. Rapid political and economic changes exerted a great influence on social, demographic and health situation in Lithuania. Mortality of urban and rural populations The age-standardized overall mortality rates of the rural population in 199- exceeded those of the urban. This difference increased from 16.9% in 199 to 29.5% in (in males from 15.2% to 3.4%, and in females from 12.5% to 23.7% respectively). The most pronounced inequalities were observed in mortality of young and middle-aged population. Mortality of able-bodied rural population was times higher than that of urban. In 199 inequalities in mortality of urban and rural males were greater than of females, while in these inequalities became similar in males and in females. In elder ages inequalities in mortality of urban and rural populations were smaller, nevertheless, comparison of the years 199 and demonstrated unfavorable trends. Inequalities in mortality of urban and rural populations disappeared at the age 55-6 in 199, while in it became evident just at the age 7 (Figures 1.1 and 1.2). Fig Ratio of probability of death (q x ) of urban and rural males in 199- (q x of urban males = 1) 3 2,5 2 1,5 1 Times 199,5 Age

6 Fig Ratio of probability of death (q x ) of urban and rural females in 199- (q x of urban females = 1) 3,5 3 2,5 2 1,5 1 Times 199,5 Age It is obvious that the major causes of death of Lithuanian population are cardiovascular diseases (CVD), cancers and external causes. These three causes of death accounted for 86.3% of all causes of death in urban areas and 88.2% in rural areas in. The fourth place in the mortality structure was taken by respiratory diseases (3.1% of all causes of death in urban and 5.1% in rural areas). As it is demonstrated in Table 1.1, CVD made the most considerable contribution to inequalities in mortality between urban and rural males and females in (37.9% and 74.% respectively). Some 34.2% in males and 2.% in female s inequalities in overall mortality in urban and rural areas were caused by differences in mortality from external causes. Cancer did not have significant impact to inequalities in overall mortality of urban and rural females, nevertheless it caused 11.5% of inequalities in overall mortality of males. Although respiratory diseases took only a small part in the mortality structure, they contributed up to 14.% to the difference in mortality between the urban and rural males and 9.3% in females. Table 1.1. The contribution of the major causes of death to the differences in overall mortality of the urban and rural populations in Causes of death Males Females Mortality difference Mortality difference Per 1 Percent Per 1 Percent population population All causes Cardiovascular diseases Cancers External causes Respiratory diseases Other causes As can be seen from Fig. 1.3 and Fig. 1.4, mortality from all major causes of death, except cancers in females, is higher among rural populations. Age-standardized female cancer mortality rate in 199 was even lower in rural areas in comparison to the urban, however, in, due to decreasing cancer mortality in urban females and fairly stable in rural, cancer mortality rates became equal in urban and rural females. The most 5

7 considerable differences in urban and rural areas are observed in mortality from external causes (up to 1.6 times) and respiratory diseases (up to 2 times). Fig Comparison of mortality from the major causes of death among urban and rural males in 199 and (mortality among urban males = 1) 2,5 2 1,5 1 * * * * * * * * *,5 All causes Cardiovascular diseases Cancers Accidents Respiratory diseases 199 * - Mortality difference between urban and rural males statistically significant, p<.5 Fig Comparison of mortality from the major causes of death among urban and rural females in 199 and (mortality among urban females = 1) 2,5 2 1,5 1 * * * * * * * * *,5 All causes Cardiovascular diseases Cancers Accidents Respiratory diseases 199 * - Mortality difference between urban and rural females statistically significant, p<.5 Trends in mortality through the period 199- were not uniform in urban and rural areas. Both in urban and rural populations age-standardized overall mortality increased until 1994 (the period of the major social and economic changes). Since 1995 tendencies of decrease in mortality were observed. Mortality of urban population lowered till the level of 199 s only in , while of rural population in 1998, due to more rapidly decreasing mortality in urban areas (Fig 1.5 and 1.6). 6

8 Fig Overall trends in mortality among the urban and rural populations, 199- Male Mortality per 1 Female Rural Urban Rural Urban Trends in mortality from CVD were similar to those in overall mortality. Fig Trends in cardiovascular diseases mortality of urban and rural population, Male Mortality per Rural Female Urban Rural Urban Trends in cancer mortality in urban and rural areas differed. Mortality of rural males was increasing significantly, while in urban areas the decrease was noted, which was mainly caused by the decline in mortality from lung cancer. Cancer mortality of females was decreasing in 199-, nevertheless, there were no significant changes registered in rural areas (Fig. 1.7). 7

9 Fig Trends in cancer mortality of urban and rural populations, Rural 28 Male Urban Mortality per Female Rural Urban The greatest increase in mortality from external causes was observed in Later mortality from these causes started to decline, however in it was still higher in comparison to 199 (Fig. 1.8). Fig Trends in mortality from external causes of death among urban and rural populations, Male Mortality per Rural Urban Female Rural Urban Mortality from respiratory diseases decreased continuously in , when it stopped, and only in started to decrease again (Fig. 1.9). 8

10 Fig Trends in mortality from respiratory diseases among urban and rural populations, Mortality per Male Rural 5 Female Urban Rural Urban Life expectancy started to increase since More rapid increase in urban population caused increasing inequalities in life expectancy between urban and rural areas. In, life expectancy of rural males was 5 years shorter than that of urban (64.4 and 69.4 respectively). Inequalities in life expectancy of rural and urban females were less pronounced 2.8 years (76.2 and 79. respectively) The reasons of inequalities in health of urban and rural populations are multiple. Social and economic changes that occurred during the period of exacerbated already existing social problems of rural population. Inequalities in health of urban and rural populations increased because of rapidly deteriorating health of rural population. Since 1995, entering the country into more stable period of development, inequalities in health of urban and rural populations increased due to more significantly improving health of urban population. Territorial inequalities in mortality Territorial inequalities in mortality and life expectancy of Lithuanian population were assessed, selecting three-year periods, in order to circumvent annual fluctuations in the data, which may have been occurring in the regions. Results of the studies performed for the periods , and , have been published earlier. The current analysis covers the period of The highest figures for territorial overall and CVD age-standardized mortality were twice as high as the lowest. These differences were similar in males and in females. Regional differences in cancer mortality were lower (1.5 times in males and 1.6 times in females), but in mortality from external causes - considerably higher (2.5 times both in males and females). Regional differences in mortality from respiratory diseases reached 5.9 times in males and 8.8 times in females. Comparison of exceptionally rural administrative regions suggested that the differences in overall mortality and mortality from major causes are smaller, but statistically significant (Table 1.2). 9

11 Table 1.2. The highest and lowest age-standardized mortality rates in administrative regions of Lithuania and the difference in mortality, 199- Causes of death Males Females Mortality per 1 Differen ce (times) Mortality per 1 All causes Cardiovascular diseases Cancers External causes Respiratory diseases Differenc e (times) Life expectancy of Lithuanian males was 66.5 years and of females 77.1 years in The longest life expectancy of males was observed in Marijampole and Druskininkai (7.3 and 7.2 years respectively), while the shortest in Salcininkai region (6.5 years). The longest life expectancy of females was registered in Druskininkai (81.8 years), and the shortest in Vilnius region (73.1 years). Comparison of the recent findings with the previous periods of investigation suggested that regional inequalities in life expectancy of females increased, while of males remained stable and were 9.8 and 8.7 years respectively in (Table 1.3). Table 1.3. Longest and shortest life expectancy (e ) and the difference (years) in Sex Longest e (95% CI) Males 7.3 ( ) Marijampole Females 81.8 ( ) Druskininkai Shortest e (95% CI) 6.5 ( ) Salcininkai region 73.1 ( ) Vilniaus region Difference Life expectancy of males in urban areas of Lithuania did not differ statistically significantly, while life expectancy of females was considerably longer in Druskininkai and Panevezys in comparison to Vilnius, Kaunas and Klaipeda. Among all rural administrative regions of Lithuania, the longest life expectancy of males was found in Utena region (67.8 years), which was 7.3 years shorter than in Salcininkai region. The longest life expectancy of females in rural areas was registered in Birzai region (78.4 years) and in Kaunas region (78.3 years). The difference from the shortest life expectancy in Vilnius region reached 5.3 years. The regions were divided into three groups: those with a shorter than Lithuanian average life expectancy, those where life expectancy was not statistically different from the average, and those with longer than average life expectancy. Maps were built up (Figures 1.1 and 1.11). 1

12 Figure 1.1. Life expectancy of males in administrative regions of Lithuania, (1 life expectancy shorter than the Lithuanian average for males, 2 not statistically significantly different from that of the Lithuanian average for males, 3 longer than the Lithuanian average for males) Lithuania, Lithuania, females males Fig Life expectancy of females in administrative regions of Lithuania, (1 life expectancy shorter than the Lithuanian average for females, 2 not statistically significantly different from that of the Lithuanian average for females, 3 longer than the Lithuanian average for females) Lithuania, females

13 Life expectancy both for males and females in towns of Lithuania was longer than the country average. The opposite situation was noted in rural areas, especially among males. The regions of the shortest life expectancy of males were concentrated mainly in the eastern part of Lithuania. In all regions around Vilnius life expectancy of males was years shorter than the average. At that time life expectancy of rural females in most regions did not differ statistically significantly from the Lithuanian average. The major contribution to territorial inequalities in life expectancy was made by differences in mortality from external causes and CVD. Inequalities in males life expectancy were mainly due to external causes, while in females CVD contributed most significantly. It could be concluded, that eastern part of Lithuania, as well as Jonava, Kaisiadorys, Silute, Siauliai and Pakruojis regions are the most unfavorable regions for health of Lithuanian population. We therefore suggest that it is necessary to aim at social equity in health through a strategy development, focusing on the most unfavorable regions for health in Lithuania. 2. FIVE-YEAR CHANGES OF STANDARDIZED AVOIDABLE MORTALITY IN LITHUANIA (OLD EUROPEAN STANDARD, BY PLACE OF RESIDENCE) A.Gaizauskiene Avoidable mortality in Lithuania during During the proportion of avoidable mortality in Lithuania accounted for 26 percent of overall mortality for the age group -64 years, the corresponding figures for and being 19.1 and 2.6 percent. Thus, avoidable causes of death remain relatively common and, consequently, they are of practical importance for public health and as well as for indirect assessment of health care effectiveness in Lithuania. Avoidable mortality of males and females, urban and rural population The differences in avoidable mortality observed between males and females during remained in The gap between sexes increased for tuberculosis (in the age group 5-64 years) and cirrhosis of liver (age group years). 12

14 Fig Changes in tuberculosis mortality during in the age group of 5-64 years urban rural Fig Changes in liver cirrhosis mortality during in the age group of years urban rural The gap for other diseases such as Hodgkin s disease (5-64), chronic rheumatic heart disease (5-44), appendicitis (5-64), hypertensive and cerebrovascular diseases (35-64) and for preventable diseases such as malignant neoplasms of trachea, bronchus and lung (5-64), motor vehicle accidents (5-64) slightly decreased. Fig Changes in chronic rheumatic heart disease mortality during in the age group of 5-44 years urban rural 13

15 Fig Changes in appendicitis mortality during in the age group of 5-64 years urban rural Fig Changes in hypertensive and cerebrovascular disease mortality during in the age group of years urban rural Fig Changes in malignant neoplasms of trachea, bronchus and lung mortality during in the age group of 5-64 years urban rural 14

16 Fig Changes in motor vehicle accidents mortality during in the age group of 5-64 years urban rural During differences in avoidable mortality have been also observed between the urban and rural populations being greater for the latter population. During the differences increased. Avoidable mortality of rural population increased from tuberculosis, malignant neoplasms of cervical cancer, hypertensive and cerebrovascular diseases and for two diseases requiring surgical interventions appendicitis and abdominal hernia. Regional differences in avoidable mortality The analysis of regional variations of avoidable mortality in Lithuania might be of interest for several reasons. First, local health politicians and administrators need to know, how effectively health care system is functioning in their administrative regions and what are the current political issues that would help balanced development of health care system. Second, if large differences in avoidable mortality were observed, this would mean there is substantial potential to change the situation. Third, the detailed analysis of regional differences could be helpful for detection of possible causes for the variations of health status of the population. The analysis performed had demonstrated that between statistically significant regional variations were observed in Lithuania as well. It was true for tuberculosis, malignant neoplasms of cervix uterus, hypertensive and cerebrovascular diseases, lung cancer, cirrhosis of liver and traffic accidents. The study indicated the regions where cause-specific SMR's were significantly higher than Lithuanian average (1%). The highest variance was found for tuberculosis, malignant neoplasms of cervix uterus and cirrhosis of liver. But it was highly significant only for few regions: Salcininku and Silute for tuberculosis, Silute and Jurbarkas for malignant neoplasms of cervical cancer, Jonavos, Raseiniu, Plunges for cirrhosis of liver. Table 2.1. Cities and regions, where SMR during differed significantly from 1% Cause of death, by age groups Region SMR SMR SMR96-99/ SMR92-95 Tuberculosis (5-64 yrs) Birzai r. 228*** 2*,9 Vilnius r * 1,9 Pasvalys r. 178* 221** 1,2 Salcininkai r *** 3,3 Silute r *** 1,7 Malignant neoplasms of cervical cancer (15-64 yrs) Silute r. 192* 229** 1,2 15

17 Hypertensive and cerebrovascular diseases (35-64) Jurbarkas r * 2,1 Vilnius city 14 11* 1,1 Vilnius r *** 1,5 Zarasai r * 1,5 Kaisiadorys r * 1,1 Pasvalys r * 1,6 Radviliskis r * 1,6 Salcininkai r ** 1,4 Svencionys r *** 1,3 Malignant neoplasms of trachea, bronchus and lung (5 - Vilkaviskis r. 147* 157** 1,1 64) Zarasai r * 1,6 Cirrhosis of liver (15-64) Motor vehicle accidents (5-64) Tuberculosis (5-64) Malignant neoplasms of cervical cancer (15-64) Hypertensive and cerebrovascular diseases (35-64) Jonava r. 195** 25*** 1,3 Klaipeda r * 3,9 Plunge r. 21*** 252*** 1,2 Raseiniai r. 243*** 212***,9 Telsiai r * 1,2 Silute r ** 1,3 Anyksciai r * 1,5 Vilkaviskis r * 1,3 Vilnius r. 152*** 14**,9 Kaunas r. 14** 143** 1, Klaipeda r *** 1,2 Kupiskis r * 1,4 Mazeikiai r * 1,4 Panevezys r * 1,2 Raseiniai r * 1,3 Trakai r. 142** 156*** 1,1 Šilute r * 1,2 Klaipeda city 75 67~,9 Panevezys city 76 53~~,7 Ignalina r.+visaginas city 57 25~~~,5 Utena r. 38~ 28~~,7 Svencionys r ~~,3 Vilnius city 63~~ 64~~ 1, Alytus city 67~ 67~ 1, Druskininkai city 68 46~,7 Kaunas city 92~~~ 78~~~,9 Siauliai city 77~ 68~~~,9 Alytus r. 5~~ 62~ 1,2 Sakiai r ~.6~ Vilnius city 81~~~ 82~~~ 1, Malignant neoplasms of trachea, bronchus and lung (5-64)Kaunas city 83~~~ 85~ 1, Panevezys city 99 63~~.6~ Vilnius city 76~~ 79~~ 1 Panevezys city ~.6~ Cirrhosis of liver (15-64) Alytus r ~,4 Ignalina r.+visaginas city 62 37~~,6 Motor vehicle accidents (5-64) Kaisiadorys r ~,6 Vilnius city 82~~~ 7~~~,9 Kaunas city 95~~~ 72~~~.8~~ Klaipeda city 87 7~~~,8 Panevezys city 87 75~,9 Siauliai city 78~ 68~~,9 *,~ p <.1, **, ~~ p <.1, ***, ~~~ p <.1 At the same time it is reasonable to stress that large amount of administrative areas have high level of SMR with less significance of the deviation. In case of Lithuania there are 16

18 2 administrative areas for tuberculosis, 1 - for cervical cancers, 6- for hypertensive and cerebrovascular diseases. For preventable causes of death there are 1 administrative area for malignant neoplasms of trachea, bronchus and lung, 3 - for cirrhosis of liver, and 7 - for motor vehicle accidents. According to M. Rosen, it would be less probable that a high rate depends on chance if the cause of death pattern points in the same direction for both sexes, for several age groups or for different time periods. The findings may also be stronger if they are found to be consistent with other health indicators. Therefore, further analyses of health problems and effectiveness of health care have to be performed in the regions listed above. Introduction 3. TRENDS IN HEALTH BEHAVIOR IN RELATION TO SOCIAL DETERMINANTS J.Klumbiene, J.Petkeviciene Regaining of the independence of Lithuania has been followed by major changes in the areas of politics and economics. The experience gained in other countries shows that the various socioeconomic groups are differently affected by those changes. Therefore, the assessment of the trends in health and health behavior of different socioeconomic groups in Lithuania is essential for planning of health promotion programs and evaluation of Lithuanian Health Program and health care reform. Since 1994 Lithuania has been participating in the international project FINBALT HEALTH MONITOR. Health behavior surveys have been carried out every two years. Data resulting from 1996 survey were presented in the report Equity in health and health care in Lithuania published in This report presents the trends in health behavior by age, gender, education, and place of residence. A national random sample of 3 inhabitants of Lithuania aged 2-64 has been taken out of National Population Register for every survey. In April the questionnaires were mailed and those who did not responded within a month received a second questionnaire in May. The response rates were 68.9% in 1996, 63.8% in 1998, and 74.4% in. The questionnaires contained questions on a use of health service, a self-assessment of health, smoking, dietary habits, alcohol consumption, physical activity, and traffic safety. The main questions of interest were kept unchanged to ensure comparability between the years studied. The direct adjustment of indices by age was performed while analyzing health behavior according to education and place of residence. Smoking. The prevalence of smoking is very high among males (half of all men are smokers) and not so common among females (15.8% in ). Over 4 years the increase in prevalence of smoking was especially obvious in females, in particular among the youngest groups (Fig. 3.1). 17

19 6 5 4 Fig Proportion (%) of daily smokers in Lithuanian population aged 2-64 in 1996, 1998, 47,3 48,5 51, % 3 2 9,4 12,5 15,8* 1 MALES FEMALES The proportion of daily smokers among females aged 2-34 has increased from 16.6% in 1996 to 2.2% in, in females aged from 11.4% to 21.3% respectively (p<.5). Smoking habits varied by educational level. Smoking was the most prevalent among the respondents with incomplete secondary education (59.9% in males and 19.5% in females in the year ) (Fig.3.2). Since 1996 the increase in prevalence of daily smoking has been observed in all educational groups, except males with university education (36.7% in 1996 and 3.4% in, p>.5). 8 Fig Proportion (%) of daily smokers by educational level in Lithuanian population aged 2-64 in ,9* 53* Males Females 5 % 4 3, ,5 16,5 13,3 1 Incomplete secondary Secondary University The differences in smoking rate by place of residence were the most obvious among females: in females in rural areas smoked less than did females in the cities. Since 18

20 1996 the significant increase in smoking has been observed only among females living in urban areas (Fig.3.3) Fig Proportion (%) of daily smokers by place of residence in Lithuanian population aged 2-64 in 1996 and 53, ,2 48, % ,5 * 2 1,9 11,7 1,7 1 Rural Urban Rural Urban Alcohol consumption. Proportion of persons drinking strong alcohol at least once a week was highest in compared with the previous years, both in males (33.9%) and in females (11.5%) (Fig. 3.4) Fig Proportion (%) of persons drinking strong alcohol at least once a week in Lithuanian population aged 2-64 in 1996, 1998, 28,7* 27,1* 33, % ,6* 6,7* 11,5 5 MALES FEMALES The most obvious changes were seen among females with university education: since 1996 proportion of females consuming strong alcohol at least once a week has almost doubled from 7.8% to 14.3% (p<.5) (Fig. 3.5). 19

21 No association between place of residence and strong alcohol consumption was found, although an increasing trend was observed among males living in cities and females living in the countryside. Beer drinking is becoming more and more popular in Lithuania. Since 1996 the proportion of persons drinking beer at least once a week has increased from 39.4% to 55,8% in males and from 8,1% to 18,3% in females (Fig. 3.6). % Fig Proportion (%) of persons using strong alcohol at least once a week by educational level in Lithuanian population aged 2-64 in 1996 and ,9 36,7 Incomplete secondary 24,7 29,7 University 5,1 Incomplete secondary 7,5 7,8 14,3* University 1996 % Fig Proportion (%) of persons drinking beer at least once a week in Lithuanian population aged 2-64 in 1996, 1998, 39,4 48,9* 55,8* 18,3* ,1 12,9 1 MALES FEMALES 2

22 Since 1996 proportion of persons drinking beer at least once a week has increased in all educational groups although the consumption of beer was higher among better-educated people (Fig. 3.7). Beer drinking was the most popular in urban population: 6.9% of males and 2.6% of females drank beer at least once a week in (Fig. 3.8). The increasing trends in consumption of beer have been observed in urban areas as well as in rural once. % Fig Proportion (%) of persons drinking beer at least once a week by educational level in Lithuanian population aged 2-64 in 1996 and 8 63,4* 7 54,6* 6 42,4 5 35,5 4 22* 3 13,5* 2 9,4 4,7 1 Incomplete secondary University Incomplete secondary University Fig Proportion (%) of persons drinking beer at least once a week by place of residence in Lithuanian population aged 2-64 in ,9* and 52,6* 46, % ,9 8,1 14,1 11,3 2,6* Rural Urban Rural Urban Food habits. A considerable part of the health behavior project deals with monitoring of food habits in Lithuanian population. Ten years of Lithuanian independence can be 21

23 distinguished by many social and economic changes in our society that have also influenced nutrition habits of Lithuanian people. The most remarkable changes have been estimated in the usage of vegetable oil for cooking. Since 1996 the proportion of persons using mostly vegetable oil for cooking has increased from 54% in1996 to 73.1% in males and from 68.8% to 88.4% in females (Fig. 3.9). The trend of increase in the usage of vegetable oil has been observed up to year No changes have been established over the last two years. Use of vegetable oil was more prevalent among better- educated people (Fig. 3.1). The consumption of vegetable oil has increased in all educational groups, but the increase has been especially obvious among females with incomplete secondary education. % Fig Proportion (%) of persons using mostly vegetable oil for cooking in Lithuanian population aged 2-64 in 1996, 1998, 86,5* 88,4* 73,5* 73,1* 68,8 54 MALES FEMALES % Fig Propotion of persons using vegetable oil for cooking by educational level in Lithuanian population aged 2-64 in 1996 and 93,7* 84,3* 83,4 75,8* 46,3 Incomplete secondary 63* 64,6 University 48,4 Incomplete secondary University

24 Males and females in urban areas prefer vegetable oil to those in rural areas. In 79.7% of males and 93.6% of females living in cities used vegetable oil for cooking, whereas in the countryside % and 83.6%, respectively. However, the increase of usage of vegetable oil was more evident among persons in rural areas. % Fig Proportion (%) of persons using mostly vegetable oil for cooking by place of residence in Lithuanian population aged ,6* in 1996 and 83,6 79,7* 78,4* 67,6 54,7* 45,3 39, Rural Urban Rural Urban The trend of decrease in usage of butter on bread has been observed between 1996 and (Fig. 3.12). Since 1996 the proportion of persons spreading butter on bread has decreased from 56% to 37.6% in males and from 5.6% to 38.2% in females. The greatest decrease has been observed between 1996 and No changes have occurred in the last two years. % Fig Proportion (%) of persons using mostly butter on bread in Lithuanian population aged 2-64 in 1996, 1998, 56 38* 37,6* 5,6 4,6* 38,2* MALES FEMALES 23

25 People with university education used butter on bread more often than people with incomplete secondary education (Fig. 3.13). The decrease in usage of butter on bread was higher among persons with incomplete secondary education than among bettereducated persons. Fig Propotion of persons using mostly butter on bread by educational level in Lithuanian population aged 2-64 in 1996 and 1 % ,7 32,6* 66,8 5,8* 49 32,6* 6,5 57, Incomplete secondary University Incomplete secondary University In urban population used butter on bread more often than population in rural areas. The trend of decrease in rural population was more evident than in urban population. Traditionally Lithuanian diet was characterized by low consumption of vegetables. However, our data show that some positive changes have occurred. Since 1996 the proportion of persons having consumed fresh vegetables at least on three days during the last week has more than doubled; from 18.1% to 43.6% in males and from 24.8% to 51,6% in females (Fig. 3.14). % Fig Proportion (%) of persons who have eaten fresh vegetables at least on 3 days during the last week in Lithuanian population aged ,6* 5* in 1996, 1998, 43,6* 36,8* 24,8 18, MALES FEMALES 24

26 The consumption of fresh vegetables has increased among people of all educational groups, however, persons with university education consumed fresh vegetables more often than those with incomplete secondary education (Fig.3.15). % Fig Proportion (%) of persons using fresh vegetables at least 3 days per week by educational level in Lithuanian population aged 2-64 in 1996 and 7 57,7* 54,2* ,9 34,3* Incomplete secondary 24,1 University 14,1 34,8* Incomplete secondary 38 University 1996 According to the data of 1996 survey, the relationship between place of residence and frequency of use of fresh vegetables was observed only in females: those living in cities used vegetables more often than females living in the countryside (Fig. 3.16). While in the year proportion of persons eating fresh vegetables three days a week in the cities was higher than in the countryside both among males and females. Since 1996 consumption of fresh vegetables has increased in urban as well as in rural population. The greatest increase has been estimated among males living in cities and females living in rural areas Fig Proportion (%) of persons who have eaten fresh vegetables at least on 3 days during the last week by place of residence in Lithuanian population aged 2-64 in 1996 and 54,4* 5,4* 49,2* 36,6* 29, % ,4 2,5 18,1 1 Rural Urban Rural Urban 25

27 Self-rated health. In order to assess the health status of the adult population, respondents were asked to estimate their health. Health behavior monitoring data show that the number of persons rating their health as good or reasonable good has increased from 42.9% to 47.5% in males and from 31.2% to 4.2% in females (Fig.3.17). 1 Fig Proportion (%) of persons rating their health as "good" or "reasonable good" in Lithuanian population aged 2-64 in 1996, 1998, % ,9 41,7 47,5* 31,2 33 4,2* MALES FEMALES Conclusions: Since 1996 the positive changes in nutrition habits have occurred in Lithuanian population: the consumption of fresh vegetables, vegetable fat has increased, the intake of animal fat has decreased. The unfavorable trends in the prevalence of daily smoking, especially among females have been estimated between 1996 and. The highest consumption of alcohol has been observed in the year. Despite the rapid changes in some health behaviors the socioeconomic pattern of nutrition habits, smoking, and alcohol consumption seems to be rather stable. 4. SOCIO-ECONOMIC DIFFERENCES IN HEALTH BEHAVIORS AMONG LITHUANIAN SCHOOL-AGED CHILDREN: RESULTS FROM 1994 and 1998 SURVEYS Introduction L.Sumskas, A.Zaborskis The evidence from the epidemiological investigations indicates that differences in health status are found among socio-economic groups all societies. It was demonstrated that people from lower socio-economic groups are less healthy than people from more affluent groups. Socio-economic inequalities are considered to be of crucial importance for ill health and well being in adult and children populations. WHO through Health

28 initiative recognize the importance of health inequalities as a major determinant of illhealth. The life-style of school-aged children is strongly influenced by socio-economic determinants such as family affluence, parent s education as well as by school and peer influence. The changes of Lithuania s economic system has stimulated us to carry out the detailed evaluation on influence of socio-economic status of the family on some health and health behavior of school-aged children as well as investigate the trends during period Material and methods Data from 2 cross-sectional questionnaire surveys (1984 and 1998) were used to investigate health behavior inequalities in school-aged children. According to the international protocol (18) of Health Behavior Study in School-aged Children (HBSC) the data on national representative samples of 5688 and 4513 students aged 11, 13 and 15 years olds (5th, 7th and 9th year students) were collected and analyzed in 1994 and 1998 respectively. The respondents were sampled by clusters (by schools and student s classes), which were defined in five regions of Lithuania. Students were asked to answer anonymously in the classroom to the set of questions from the self-completion questionnaire concerning health behaviors. Questions on smoking and physical activity covered parameters of frequency of these behaviors in the course of the day, week or month. The respondent was attributed to the group of smokers if he or she smoked at least once a week or more often. Low physical activity was considered as exercising less than 2 hours per week. The students were attributed to the category of regular alcohol users if they indicated use of beer, vine, and spirits at least once a week. The respondents were asked to rate their health according such categories as "very healthy", "quite healthy" and "not very healthy". The questionnaire covered also questions on the parent s occupational status, questions indicating on family's affluence (owning the personal bedrooms by the respondent student, number of cars in the family, weekly pocket money spending). The question on perceived evaluation of their families economical status was incorporated into questionnaire too. We used the measure of social class based on non-occupational and non-educational status of the parents. Families were attributed to 4 SES classes according the following criteria: 1) owning personal bedroom by the respondent student; 2) owning the car in the family; 3) spending more than 7 Litas (1.75 in USD) of pocket money by the respondent student per week. Families fulfilling all 3 criteria were attributed to the category of high socio-economic status family (HSES) and families with score - to low socio-economic status family (LSES), with score 1 - to intermediate low SES category (ILSES) and with score 2 -to intermediate high (IHSES) category of families. The data were processed and analyzed by national team of researchers after the preliminary approval from international data Coordinating Center in Bergen (Norway). Statistical package SPSS was applied for data analysis. Statistical significance was tested by χ 2 and t test calculation. Mainly significant differences (p<.5) were reported. Odds ratio (OR) was calculated by using EPI-INFO statistical program. 27

29 Results Characteristics of samples and prevalence, trends of behavioral risk factors. The representative national samples were formed from the students of 84 and 93 schools or 255 and 248 classes respectively in 1994 and The student s response rate was 88.7% and 87.2%. The characteristics of two samples by age, sex are presented in the Table 4.1. Table 4.1. Baseline characteristics of study samples according to age and gender Age group (years) Study Number and percentage of respondents Age average (years) Boys Girls Total Boys Girls Total n % n % n % mean±sd mean±sd mean±sd ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± Our HBSC data from 1994 and 1998 revealed minor differences in age and sex distribution between two surveys. Only boys and girls from age group of 11 years old were more mature by age in the sample of 1998 (p<.5). This indicates on comparability of demographical composition of analyzed samples and allows comparison the data of two surveys. Changes of socio-economical status and other indicators of family s affluence. The economical status of the families as well as the prevalence of behavioral risk factors in the separate SES groups was one of the baseline points of our investigation. Table 4.2 presents the structure of SES according the index of affluence (scores from to 3) in surveys of 1994 and

30 Table 4.2. Percentage of families with the different socio-economic status by age in 1994 and Age Survey of 1994 Survey of 1998 (years) LSES ILSES IHSES HSES LSES ILSES IHSES HSES Total Total 11 n % n % n % n % χ2 test χ2= 88.2; df=6; p<.1 χ2=8.2; df=6; p<.1 χ2=113.9; df=3; p<.1 According the Table 4.2 the percentage of families with high SES increased in the period of observation from 13.1% to 21.% (p<.5). At the same time percentage of low SES families decreased from 15.5% in 1994 to 12.8% in 1998 (p<.5). We have analyzed the changes of some other economic indicators in the period The respondents more often answered about owning the personal bedrooms in families (increase from 54.2 to 56.9, p<.1). The percentage of students with spending of pocket money more than 7 Litas per week increased from 27.9% to 42.2% (p<.1). Owning of the cars by the families increased non significantly from 63.7% to 65.1% (p>.5). The perceived feeling of student s family s affluence has changed as well. Analysis of data indicates that the percentage of "very well of" and "well of" families increased during the observation from 12.7% to 22.2% (p<.1). It corresponds with the increase more positive perceived health rating by our respondents. Changes of the prevalence of behavioral risk factors among students during These changes are presented presented in the Table

31 Table 4.3. Prevalence of smoking, regular use of alcohol, low physical activity and low self-related health by age and sex in surveys of 1994 and 1998 Boys Girls Risk factor Smoking (>once/week) Alcohol abuse (>once/week) Low physical activity (< 2 hours/week) Self related health "not very healthy" Survey of 1994 n=2429 Survey of 1998 n=2999 p between 1994 and 1998 Survey of 1994 n=215 Survey of 1998 n=25138 p between 1994 and ( ) 19.8( ) p<.1 3.6( ) 8.5( ) p< ( ) 12.2( ) p< (3.6-5.) 6.( ) P< ( ) 37.8( ) p< ( ) 64.5( ) p> ( ) 9.9( ) p<.1 27.( ) 21.2( p<.1 Smoking. Analysis of data on smoking shows that the prevalence of smoking has increased in period in boys from 11.3% to 19.8% (p<.1) in girls from 3.6% to 8.5% (p<.1). Alcohol. The regular use of alcohol have changed significantly from 9.4% to 12.2, respectively in boys, and from 4.2% to 6.% in girls. Low physical activity. The prevalence of boys who were exposed to low physical activity (less than 2 hours per week) dropped from 42.1% to 37.8% (p<.5), but was unchanging and high in girls (64.6% and 64.5%, p>.5) in surveys of 1994 and 1998 Self-related health evaluation. The proportion of respondents who perceived themselves as "not very healthy" decreased in boys from 14.2% to 9.9% as well as from 27.% to 21.2% in girls (p<.1) in period Odds ratios for smoking, low physical activity, regular use of alcohol and perception of health in the different SES groups. Tables 4.4 and 4.5 presents distribution of odds ratios for the mentioned health indicators by SES groups. 3

32 Table 4.4. Distribution of odds ratios (OR) for smoking and regular alcohol use in different socio-economic groups according gender and the year of observation. Health indicator Gender SES group Odds ratio OR (95% CI) Survey of 1998 Odds ratio OR (95%CI) Survey of 1998 LSES Boys ILSES 1.28( ) 1.16( ) IHSES 1.18( ) 1.24( ) HSES 2.15( )* 1.82( )* Smoking LSES Girls ILSES.69( ).78(( ) IHSES.95( ) 1.52( ) HSES 2.55( )* 2.3( * LSES Boys ILSES.94( ) 1.6( ) IHSES 1.42( ) 1.17( ) Regular use HSES 2.65( )* 2.46( )* of alcohol LSES Girls ILSES 1.27 ( ) 2.1( ) IHSES 2.36( )* 2.99( )* HSES 5.87( )* 4.16( )* * p<.5 for OR=1. The pattern of curve for OR on smoking in different SES groups was quite different for boys and girls (Table 4.4). OR in boys was increasing in the intermediate SES groups and was significantly higher in high SES group(1.; 1.28; 1.18 and 2.15 in 1994; 1.; 1.16; 1.24 and 1.82 in 1998) than in low SES group. The pattern of J shape curve was observed 31