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LITHUANIAN UNIVERSITY OF HEALTH SCIENCES
ACADEMY OF MEDICINE
INSTITUTE OF CARDIOLOGY
SANTIAGO COTOBAL RODELES
The prevalence and trends in prevalence of lifestyle
cardiovascular disease risk factors among Kaunas city
inhabitants.
Final Master‘s Thesis
Supervisor: Prof. Dr. Habil. Abdonas Tamošiūnas
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1 Summary ... 3
2 Santrauka ... 4
3 Conflicts of interest. ... 5
4 Permission issued by the Ethics Committee ... 6
5 Abbreviations list ... 7
6 Terms ... 7
7 Introduction. ... 8
8 Aim and objectives of the thesis. ... 9
Aim ... 9
Objectives ... 9
9 Overview of literature ……….10
9.1 Obesity.………10
9.1.1 Prevalence of obesity……….……….…...10
9.1.2 Obesity and risk for healt…...………..……….11
9.1.3 Methods for detection of obesity...11
9.2 Alcohol………...12
9.2.1 Alcohol consumption habits……...12
9.2.2 Alcohol and risk for health...12
9.3 Tobacco smoking ... …...13
9.3.1 Prevalence of smoking...13
9.3.2 Tobacco and risk for health...14
9.4 Physical activity……….………. ..……….15
9.4.1 Prevalence of physical inactivity...15
9.4.2 Physical activity and health……...15
10 Research methodology and methods...17
10.1 Study sample………..………17
10.2 Variables determined using the questionnaire…,……..………17
10.3 Statistical analysis………..…...….……….…18
11 Results and their discussion...19
11.1 Socio-demographic characteristics of the study cohort...19
11.2 Prevalence of lifestyle risk factors during the initial survey...20
11.3 The prevalence of life-style risk factors in relation to socio-demographic characteristics of study participants...24
11.4 Comparison of the data on prevalence of lifestyle risk factors between the initial and follow up survey...34
12 Conclusions……….………...45
13 Practical recommendati..ons………...………...………47
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1 Summary
In this study Santiago Cotobal Rodeles will present the prevalence and time-trends of the life-style risk factors cardiovascular diseases (CVD) among the middle-aged and elderly urban population of Kaunas city surveyed twice in 2006 to 2008 and in 2016 using data from these surveys and review of literature. The aim of this study was to assess the prevalence and trend in the prevalence of life style risk factors among middle-aged and elderly urban population.
In 2006 to 2008 and during the follow-up survey in 2016, 4,251 people (1,780 men and 2,451 women) aged 45-72 years in the initial survey were screened and data on life-style risk factors (alcohol consumption smoking habits, quality of life, obesity and other factors) were collected using the questionnaire.
A review of 41 publications on the prevalence of life-style risk factors is presented in the chapter of the master thesis “Review of literature”.
Results of the study data analysis are presented as the prevalence of life-style risk factors in the initial survey and comparison of the prevalence of these indicators between the initial survey and follow-up survey using informative tables and graphs. The results of the study are discussed and compared with similar data from other countries. Data is analyzed according to sex, age and education groups.
According to the data analysis, during the initial survey most of our patients were obese, non-smokers, drinkers of low amounts of alcohol; rating as medium their self reported health and quality of life. 10 years later the results showed an increase of body mass index (BMI), a decrease in the proportion of smokers and alcohol drinkers drinking alcohol frequently, and an increase in proportion of individuals rating their quality of life as medium poor.
In conclusion, in the initial survey, the higher prevalence of smoking, overweight and frequent alcohol drinking was found in men as compared to women, whereas among women the higher prevalence of obesity was found. During the follow up survey after 10 years, in both gender groups decreased the prevalence of smoking, obesity, the proportions of individuals drinking alcohol relatively frequently, and increased the proportions consuming alcohol less frequently.
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2 Santrauka
Šiame tyrime Santiago Cotobal Rodeles pristatys Kauno miesto vidutinio ir senyvo
amžiaus amžiaus asmenų širdies ir kraujagyslių ligų (ŠKL) gyvensenos rizikos veiksnių paplitimą ir pokyčių tendencijas. Nuo 2006 iki 2008 metų ir nuo 2016-ųjų metų naudojantis apklausos duomenimis ir skaityta literatūra. Šio tyrimo tikslas buvo įvertinti paplitimą ir gyvensenos rizikos veiksnių paplitimo pokyčių tendencijas tarp vidutinio ir vyresnio amžiaus miesto gyventojų.
Pirministyrimasbuvoatliktas2006-2008metais, o pakartotinis – 2016 metais t.y. po 10 metų .Pirminio tyrimo metu buvo ištirti 4251 žmonės (1780 vyrų ir 2451 moteris), kurių amžius buvo 45-72 metai, ir duomenys apie jų gyvenimo būdo rizikos veiksnus(alkoholio vartojimas, rūkymo įpročiai, nutukimas, gyvenimo kokybė ir kiti veiksniai) buvo surinkti naudojant klausimyną.
Su gyvenimo būdu susijusių rizikos veiksnių paplitimo tyrimų apžvalga 41 literatūros šaltinyje pateikiama magistro darbo literatūros apžvalgos skyriuje.
Tyrimo duomenų analizės rezultatai pateikiami kaip gyvenimo būdo rizikos veiksnių paplitimas pirmojo tyrimo metu. Taip pat palyginti šių rodiklių paplitimas tarp pirminio tyrimo ir tolimesnio tyrimo. Tyrimo rezultatai pateikiami informacinėse lentelėse bei grafikuose Tyrimo rezultatai aptarti ir palyginti su kitų šalių panašiais tyrimų rezultatais. Tyrimai duomenys nagrinėti pagal lytį, amžių ir išsilavinimo grupes.
Remiantis duomenų analizės duomenimis, pirminio tyrimo metu dauguma mūsų tiriamųjų buvo nutukę, nerūkantys, mažai alkoholio vartojantys žmonės, vidutiniškai vertinantys savo gyvenimo kokybę. Po 10 metų rezultatai parodė padidėjusį kūno masės indeksą, sumažėjusią reguliariai rūkančiųjų bei dažnai vartojančių alkoholį dalį tarp visų tiriamųjų ir, priešingai, padidėjusią dalį vidutiniškai ir blogai vertinusių savo gyvenimo kokybę. .
Taigi, apibendrinant galima teigti, kad pradinio tyrimo metu vyrams nustatytas didesnis rūkymo bei antsvorio paplitimas ir dažnas alkoholio vartojimas, palyginti su moterimis, tuo tarpu moterims nustatytas didesnis nutukimo paplitimas. Pakartotino tyrimo po 10 metų metu abiejose lyties grupėse sumažėjo rūkymo, nutukimo paplitimas, ir asmenų, kurie geria alkoholį santykinai dažnai, dalis bei padidėjo rečiau vartojančių alkoholį dalis.
Raktažodžiai: kardiologija; Kaunas; Kardiologijos institutas; rizikos veiksniai; prevencinė
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3 Conflicts of interest.
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4 Permission issued by the Ethics Committee
LIETUVOS SVEIKATOS MOKSL
UNIVERSITETAS BIOETIKOS CENTRAS
Kodas 302536989, Tiliés g. 18, LT- 47181, Kaunas, tel.: (8 37) 327233, www lsinuni It., el.p.: sochumkatedra‹ltlsmuni It
Medicinos akademijos (MA) 2017-10-23 Nr. éc’- 7YU
- Vientisqjq studijq programa — MEDICINA
VI k. stud. Santiago Cotobal Rodeles
DEL PRITARIMO TYRIMUI
LSMU Bioetikos centras, ivertinps (MA) vientisqjq studijq programos —
MEDICINE. VI k. stud. Santiago Cotobal Rodels (mokslinio darbo vadovas: prof. Abdonas Tamos“ifinas, LSMU Profilaktinés medicinos katedra) mokslinio-tiriamojo darbo temos: „The prevalence and trends in the prevalence of life style cardiovascular disease risk factors among Kaunas city inhabitants“ tiriamojo darbo anotacijq, tiriamojo asmens informavimo forint ir tiriamojo asmens informuoto sutikimo forint, kurie leid2ia sprpsti, jog
planuojamame tyrime neturétq bfiti pazeistos tiriamojo teisés, todél s’iam tyrimui pritariama.
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5 Abbreviations list BMI: Body Mass Index.
CDC: Centre for Disease Control and Prevention. CI: Confidence interval
CVD: Cardiovascular Disease.
MONICA: Multinational MONItoring of trends and determinants in CArdiovascular disease. NHANES: National Health and Nutrition Examination Survey.
NIH: National Institute of Health. OR: odds ratio.
SCORE: Systematic Coronary Risk Evaluation. USA: United States of America.
WHO: World Health Organization. 6 Terms
BMI (Body Mass Index: According to the National Institute of Health (NIH) is weight-to-height
ratio, calculated by dividing weight in kilograms by the square of height in meters and used as an indicator of obesity and underweight.
Cardiovascular disease: According to the World Health Organization (WHO) are a group of
disorders of the heart and blood vessels and they include: coronary heart disease, cerebrovascular disease, peripheral arterial disease, rheumatic heart disease, congenital heart disease, deep vein thrombosis and pulmonary embolism
Incidence: Is a measure of the number of new cases of a characteristic that arise in a population
over a given period.
Obesity: According to the NIH obesity means excessive fat tissue on body according to the WHO
it depends on the BMI been greater or equal to 30 kg/m2.
Prevalence: According to NIH, is the proportion of a population who have (or had) a specific
characteristic in a given time period – in medicine, typically an illness, a condition, or a risk factor such as depression or smoking.
Distribution T student: Is a method for test one hypothesis about the mean of a small sample for
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7 Introduction
Cardiovascular diseases (CVD) today are the largest single contributor to global mortality worldwide according to the World Health Organization (WHO) [1]. 17.7 million people died from CVD in 2015, representing 31% of all global deaths.
Coronary heart disease (CHD) is the main reason with more than 7.4 million deaths in 2015 and stroke the second one with more than 6.7 million deaths [1]. In Lithuania according to Eurostat, this is especially relevant because Lithuania is one of the countries of Europe with the highest standardized death rate from CVD with more than 3,800 deaths per 100,000 inhabitants and the one with the highest mortality from CHD: with more than 2,600 deaths per 100,000 inhabitants in 2014 [2].
The majority of the world population is at moderate or high risk due of them behavioral, biological and social risks [3].
Those risk factors for CVD where presented by Harrison and are tobacco smoking, arterial hypertension, low levels of high density lipoprotein (HDL) cholesterol, diabetes, history of
premature cardiopathy, age (45 men, 55 women), obesity, physical inactivity, high fat diet (later the alcohol consumption was added on those risk factors because the consumption of it increase the level of triglycerides) [4].
Some of those risk factors can’t be prevented but we should focus on avoiding those that can be prevented, those are regular smoking, diets rich on saturated fats that increase the incidence of obesity and decreases the level of HDL cholesterol while increasing the level of low density lipoprotein (LDL) cholesterol, the alcohol drinking and the sedentary life style (low physical activity that has been normalized in the world during this century). Those risk factors showed an increasing trend in the prevalence in the last years and at the same time show an increasing
morbidity of CVD in undeveloped and developing countries as China, the Russian Federation, and Indonesia [3,5,6,7]. A special mention must be made for Mediterranean countries which have change their traditional Mediterranean diet to a diet more rich on fats increasing CVD [8], on the other hand in other countries such as Canada or USA [10] the increasing tendency have been slowed due to the education on risk factors and the politics taken. We also can observe a
9 Knowing that those risk factors are responsible for the incidence of CVD, we can start primary prevention by explaining the importance of these factors to young persons, educating them on how to avoid those risk factors, giving them alternatives as reducing the animal fats from their diet, preventing smoking habit, preventing alcohol consumption, recommending the
consumption of fibbers and vegetables and reducing level of salt on diet [3].
Some legal actions can be suggested from Ministry of Health for preventing those risk factors, but health education have shown to be most effective [11,12].
Also, secondary prevention CVD by avoiding the evolution of it giving to patients with these diseases information about those risk factors and recommending them to avoid them and following up of the disease.
In this thesis I present descriptive statistical analysis of data received from the respondents about their lifestyle in the initial survey and 10 years after during the postal survey when we mailed to them a questionnaire with the same questions. Our purpose was to observe possible changes of their lifestyle and to see if secondary prevention was effective or not and also how they rate their health after those changes.
8 Aim and objectives of the thesis 8.1 Aim
To assess the prevalence and trend in the prevalence of life style risk factors among middle-aged and elderly urban population.
8.2 Objectives
1. Assessment of the prevalence of life-style risk factors and distribution of study population by self -rated health and quality of life at initial survey.
2. Evaluation of life-style risk factors at the initial survey according to socio-demographic characteristics.
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9 Review of literature 9.1 Obesity
9.1.1 Prevalence of obesity
The prevalence of obesity worldwide changes according to the country or the year when the text was made. In this review I just have used texts from the last years but some of them use data from before [13,14]. The most important study was the WHO MONICA study (World Health Organization, Multinational MONItoring of trends and determinants in CArdiovascular disease), this study compared all or most of the countries worldwide (the other studies are individual for each country, continent or just compare few countries) [5,9,10,15,16,17,18,19,20]. In the study made in 1990 the highest prevalence of obesity for Europe was in Lithuanian women with 45%, against Sweden with only 7%.
The highest prevalence I found on my review is in Australia ofoverweight andobesity [5] where the prevalence was 60%.
In United States of America (USA) the prevalence is exceeding 30% [10,15,19] according to the National Health and Nutrition Examination Survey (NHANES). In Europe the prevalence of obesity is lower than in Australia and USA [8]. The prevalence of this risk factor varies from 4% to 28.3% in men and from 6.2% to 26.5% in women. The highest prevalence is found in the Mediterranean part of Europe (Spain and Italy). In these countries the high prevalence is found because of the urbanization and the globalization of food market that have increased popularity of fast food making a decrease on the people who still consume the traditional Mediterranean diet on their daily life, in these countries the prevalence of obesity is higher than 25% for both sexes, also high prevalence of obesity, according to that study, we can find in countries of East Europe (Romania and Poland)or Czech republic. In Portugal [16], the prevalence of obesity was 14.2% and 39,4% of overweight in 2003-2005 for both sexes and the prevalence of obesity is higher for females more than 25% [8] but we don’t have information about the year of that study. The countries of north Europe and central Europe showed lower prevalence of obesity than previous ones [17]. In France the prevalence in 2006 was 13.1%, and in Sweden 9.7% [18].
11 It is interesting to analyze how worldwide the prevalence of obesity have changed during the 00’s. [5,20]. In China, the prevalence of obesity has increase by 400% during the last 20 years [18]. In Sweden and Finland also have increase [9,18] Even though according to other studies the Finish prevalence has decrease. [8] Also we can find some countries like France [17] where the prevalence of this risk factor increased from 1997 to 2006 by 4.5%, but on the years closer years to the actual date this increase seems lower due to new politics, this is the situation for Canada and USA [10].
The most important factors for the control of obesity [21] according to the WHO are 1) limit energy intake from total fats and sugar, 2) increase consumption of fruit and vegetables, as well as legumes, whole grains and nuts and 3) engage in regular physical activity (60 minutes a day for children and 150 minutes spread through the week for adults).
9.1.2 Obesity and risk for health
Obesity is a risk factor for many chronic non-communicable diseases and chronic
conditions [3,14,15,22,23] like arterial hypertension, high LDL cholesterol, stroke, coronary heart disease (CHD), certain cancers, diseases of the articulations, and type 2 diabetes. The risk of CHD could be evaluated using SCORE (systematic coronary risk evaluation) system or charts [22].
The mortality from these diseases, even though have decrease thanks to a better control of them and the existence of drugs for decrease the symptoms of them, only hypertension have different data: some studies showed the increasing trend [15] while other studies shown a
decreasing trend [14]. Also, the lifestyle changes that induce weight decrease and healthier habits reduce the incidence of these diseases [13].
According to USA studies, the number of deaths per year due to obesity is 280.000 [23,24] but also obesity can help us to detect faster susceptible individuals to CVD by using biomarkers associated with obesity, [25] in USA for example we find the CDC (Centers for Disease Control and Prevention), the US Department of Agriculture and numerous reports by institute of medicine and US surgeon general organizations.
9.1.3 Methods for detection of obesity
12 height in meters. But BMI is not always an effective method for the evaluation of obesity
[8,14,23,26, 27] because the body composition is not the same always. The body composition of Asian population has higher body fat percentage than Caucasians, also black population have less fat than Caucasians and even in the same race we can see cases with the same body mass index but different fat percentile.
Even though if we use as it is recommended the waist circumference for measuring of obesity [14], the prevalence according to country doesn’t have a significant change on prevalence of obesity; for example, in USA the prevalence of obesity using for evaluation waist
circumference was 30.2% and according to BMI 30 %, and in India 2.2% and 5%, respectively.
9.2 Alcohol
9.2.1 Alcohol consumption habits
In USA during 2009-2011, the prevalence of alcohol drinking among adult population was 70.5%, with 29.3% of excessive drinking, 27.4% of binge drinking, and 3.5% of alcohol
dependence in the month before the publication of that study [28].
The prevalence was higher in men between 18 and 24 years and binge drinking was higher in those with high level of study and on the other hand, alcohol dependency was higher for those with low level of studies. Form this we can observe that people with university and college studies have higher prevalence of consuming an excessive amount of alcohol in a short period of time. While those with not university or college studies have higher prevalence of psychological dependence of alcohol.
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9.2.2 Alcohol and risk for health
The relation of alcohol and health differ according to the number of standard units of alcohol consumed per day.
1 unit [30] or 2 units [29] of alcohol consumed per day have been proved to decrease the risk of CVD, even though the studies show that doctors should never recommend it to patients, due to misunderstanding from patients who will increase their consumption and also the cardio protective factor of those beverage hasn’t been more than the one of consumption of nuts or other foods.
Alcohol is the leading cause of death among young adult men with 25% of mortality due to alcohol and 7.4% of disability in Europe [31]. Alcohol is responsible for increase of blood
pressure, increase of body weight, level of triglycerides, diabetes, liver diseases and psychological problems [30].
9.3 Tobacco smoking
9.3.1 Prevalence of smoking
Asia is the continent with highest consumption of tobacco [32]. In Russia, China, Japan, South Korea, Philippines and most of middle-east countries most of smokers are smoking more than 20 cigarettes per day, on contrast to it, in countries like India, Nepal and Myanmar, most of smokers are smoking less than 10 cigarettes per day [32].
In Australia, a consumption of more than 20 cigarettes per day is common for largest
14 Map 1. Prevalence of tobacco smoking in the world [32]
The prevalence of tobacco smoking increased for people who are between 15 and 29 years old and after this age decreased in both sexes in developed countries, while in developing
countries the peak of prevalence was determined for males between age from 45 years and 49 years and in women are almost always the same independently of age [32,33],but it change according to the level of studies being higher in those with lower level of studies in United Kingdom or Norway and higher in those with higher levels of studies in south Europe.
9.3.2 Tobacco and risk for health
The relation of smoking and health is really important, because tobacco smoking causes over half millions of deaths per year, making it the most important preventable cause of mortality in Europe for prevent hat on 2000 was made the declaration of Lisbon where new laws where present for prevention of it [33].
15 tobacco smoking and exposure tobacco smoke resulted in at least 443,000 premature deaths in USA [34]. [35].
The individuals who smoke less than 1 or between 1 and 10 cigarettes per day have already higher mortality risk than those who never had smoke [36], and is responsible for one in two deaths on their persistent users, been estimated that 8% of world population could eventually be killed by tobacco if their smoking patterns persist[35].
For prevention of tobacco smoking: we have [37] smoke free laws which prevent new smokers and protect second-hand smokers and have decreased hospitalization for cardiac and respiratory diseases, also the education about smoking habits by teachers is important [11,12,37] some studies defend the fear based campaigns [11] while others the promotion of healthy habits [38]. A large increase in taxes has been [12] the cornerstone by decreasing 10% or more the prevalence of smoking but [33] this method is controversial and big tobacco companies say that it only increase the contraband of it. Also, we can see mass media campaign (5 to 10%) and
advertising bans (6%).
9.4 Physical activity
9.4.1 Prevalence of physical inactivity
The prevalence of physical activity we can divide between low active, moderate and high [6,39]. The countries with highest proportion of low activity are Saudi Arabia 42.8%, Taiwan 41.3% and Japan 41.1%. While proportions of moderate physical activity were determined in Hong Kong 46.4%, India 37.8%, Brazil 34.9% and New Zealand 74% and Australia 65.8%. In Lithuania, the distribution of physical activity is: 15.9% - low physical activity, 28.3% - moderate physical activity, and 55.8% - high physical activity.
For almost all countries, males were more active as compared with women, whereas women where more active as compared with men only in Argentina, Portugal, and Saudi Arabia.
9.4.2 Physical activity and health
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10 Research methodology and methods
10.1 Study sample
Data from two surveys of the study among urban population aged 45-72 years were used in these analyses. The first – the baseline – survey was conducted in 2006-2008 using the Health, Alcohol and Psychosocial Factors in Eastern Europe (HAPIEE) study protocol [7]. The follow-up survey, using the postal questionnaire, was performed 10 years later in 2016. All these surveys were carried out in Kaunas, the second largest Lithuanian city (population 348,624 people). The random sample of men and women, stratified by gender and age, was randomly selected from the Kaunas
population register. The response rates were 64.8% at baseline survey and 68.7% at follow-up survey. A total of 7,087 individuals (3,218 men and 3,869 women) participated in the baseline survey. In 2016, all surviving participants at the baseline survey (6,210 individuals (2,569 men and 3,551 women) were invited to the follow-up survey which was performed using postal
questionnaires. 4,266 individuals responded and mailed back filled-in survey questionnaires.
10.2 Variables determined using the questionnaire
In the baseline and follow-up survey self-reported and rated health, self-rated quality of life and life style factors and habits – smoking, body weight and alcohol consumption were determined among study participants using the questionnaire.
The structured questionnaire included questions regarding the respondent’s age, education,
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10.3 Statistical analysis
Descriptive statistics were calculated for variables included in the data analysis. The
prevalence of lifestyle factors, self-rated health and quality of life was compared in gender, age and other groups via χ2 and Z tests.
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11 Results and their discussion
11.1 Socio- demographic characteristics of the study cohort
In this chapter of master thesis are presented socio-demographic characteristics of participants at initial survey (Figures 11.1.1 and 11.1.2).
Figure 11.1.1. Distribution of study participants at the initial survey by sex and age (in %)
As we can see in Figure 11.1.1 the proportions of male and female in age groups are quite close with the biggest difference of 1.9% in age groups 55-59 years and 65-69 years. The largest proportion of men was in age group 65-69 years (22.5%) and largest proportion of women was in age group 60-64 years (23.7%). Smallest proportion both of men and women was in youngest age group – 45-49 years. 11,9 13.2 20.3 22.1 22.5 10.1 12 15 18.4 23.7 20.6 10.3 12 14.2 19.2 23 21.4 10.2
45-49 years 50-54 years 55-59 years 60-64 years 65-69 years 70+ years
Men
Women
Total
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Figure 11.1.2. Distribution of study participants by sex and education level (in %).
The distribution of men and women by education level statistically significantly differed at initial survey (Figure 11.1.2). It is interesting, that the largest proportion in the distribution of the participants by education level at the initial study formed individuals with university education both among men and women. Only 4.2% women and 4.8% men had only primary education. As we can see, the proportions of individuals with secondary education and university education were significantly higher among men as compared to women, whereas the proportion of individuals who graduated college was significantly higher among women than among men.
11.2 Prevalence of lifestyle risk factors during the initial survey
In this chapter of master thesis results on the prevalence of life-style risk factors in the initial survey in 2006-2008 are presented.
Distribution of men and women by their category of BMI is presented in Table 11.2.1.
4.8 7.9 29.3 18.1 40 4.2 6.9 23.3 29.4 36.2 4.4 7.3 25.8 24.7 37.8
0
5
10
15
20
25
30
35
40
45
Primary Vocational Secondary College University
Men Women Total
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Table 11.2.1.Distributionof screened men and women by frequency of BMI at the initial survey. BMI kg/m2 Sex Total Men Women N % N % N <18.5 2 0.1 4 0.2 6 18.5-24.99 378 21.1 481 19.6 859 25.0-29.99 807 45.1 895 36.4* 1702 30.0+ 602 33.7 1078 43.8* 1680 Total 1789 100.0 2458 100.0 4247 χ2 = 48.3, p<0.001; *p<0.001 as compared to men.
The prevalence of overweight (category of BMI 25.0-29.99 kg/m2) was significantly higher among men as compared to women (45.1% and 36.4%, respectively), whereas the prevalence of obesity (category of BMI > 30.0 kg/m2) was significantly higher among women. There were no statistically significant differences in the distribution of normal weight between men and women.
Distribution of men and women by their smoking habits in the initial survey is presented in Table 11.2.2.
The proportion of regular smoking was significantly higher in men than in women (25.2% and 8.9%, p<0.001), same as proportion of ex-smokers: 30.6% in men and 7.0% in women, respectively (p<0.001). But the proportion of never-smokers was significantly higher among women as compared to men.
Distribution of men and women by frequency of alcohol drinking in the initial survey is presented in Table 11.2.3.
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Table 11.2.2.Distribution of screened men and women by smoking habits at the initial survey.
Smoking habits Sex Total
Men Women N % N % N Regular smokers 448 25.2 219 8.9* 667 Ex-smokers 544 30.6 171 7.0* 715 Never-smokers 788 44.2 2063 84.1* 2851 Total 1780 100.0 2453 4233
The distribution of men and women by smoking habits differs statistically significantly: χ2 = 755.4, p<0.0001; *p<0.001 as compared to men.
Table 11.2.3. Distribution of screened men and women by frequency of alcohol consumption at
the initial survey.
Alcohol consumption frequency Sex Total Men Women N % N % N % Every day or almost every day
89 5.0 25 1.0** 114 2.7
About 2-4 times per week
292 16.4 61 2.5** 353 8.3
About once per week 301 16.9 185 7.5** 486 11.5 About 1-3 times per month 618 34.7 819 33.4 1437 33.9
Less than once a month 406 22.8 1214 49.5** 1620 38.3 Never in last year 74 4.2 150 6.1* 224 5.3 Total 1780 100.0 2454 100.0 4234 100.0 χ2 = 579.1; p<0.001; *p<0.01, **p<0.001 as compared to men.
23 largest proportion of individuals among women indicated that they consumed alcohol less than once a month.
The distribution of participants at initial survey by self-rated health and quality of life is presented in Table 11.2.4 and Table 11.2.5.
Table 11.2.4. Distribution of screened men and women by self reported health status at initial
survey. Self-rated health Sex Total Men Women N % N % N % Very poor 159 8.9 353 14.4* 512 12.1 Medium 991 55.7 1532 62.4* 2523 59.5 Very good 631 35.4 570 23.2* 1201 28.4 Total 1781 100.0 2455 100.0 4236 100.0
χ2=87.6; p<0.001; *p<0.001 as compared with men.
Table 11.2.5. Distribution of screened men and women by quality of life at initial survey.
Self-rated quality of life Sex Total Men Women N % N % N % Poor 47 2.6 98 4.0* 145 3.5 Medium 783 44.0 1160 47.3* 1943 45.9 Good 912 51.3 1156 47.2** 2068 48.9 Very good 37 2.1 36 1.5 73 1.7 Total 1779 100.0 2450 100.0 4229 100.0
24 We can see that the distribution of self-rated health among men and women differed
statistically significantly. The higher proportions of individuals who rated their health as very poor and medium were among women as compared to men (14.4% and 62.4% - among women and 8.9% and 55.7% - among men, p<0.001), while proportion of individuals rating their health as very good was significantly higher among men than among women (35.4% and 23.2%).
The quality of life self-rated is poor was determined only for 2.6% men and 4% women (p<0.05). The proportion of medium self-rated quality of life was significantly higher in women group as compared with men, while proportion of self-rated quality of life assessed as good, in contrast, was significantly higher in men group. Only 2.1% men and 1.5% women (p>0.05) rated their quality of life as very good.
11.3 The prevalence of life-style risk factors in relation to socio-demographic characteristics of study participants
In this chapter of master thesis is presented distribution of life-style risk factors in relation of socio-demographic characteristics of study participants: education level and age group.
We started presenting of results in this chapter by distribution of BMI by level of education (Table 11.3.1) and age group (Table 11.3.2) at initial survey.
As we can see results presented in the Table 11.3.1, the distribution of categories of BMI is related to education level of individuals at the initial survey. The largest proportion of individuals had BMI > 30.0 kg/m2 in primary, vocational and secondary education groups: the proportion varied from 43.2% to 52.4%. While in college and university education groups most individuals were in overweight category. The proportion of individuals with normal body weight (BMI
category 18.5-24.99 kg/m2) significantly increased with increasing of education level (from 11.8% among individuals with primary education to 24.5% among individuals with university education, p<0.001).
While the opposite tendency was registered when we analyzed the distribution of obesity
(category of BMI > 30.0 kg/m2) in relation to education level: the proportion of obese individuals decreased from 52.4% in primary education group to 34.3% in university education group,
25 <18.5 kg/m2 and 25.0-24.99 kg/m2 according to education level of study participants at initial
survey.
Table 11.3.1. Distribution of study participants by body mass index and education
level at the initial survey.
Body mass index (kg/m2)
Education group
Primary Vocational Secondary College University
N % N % N % N % N % <18.5 0 0 1 0.3 2 0.2 1 0.1 2 0.1 18.5-24.99 22 11.8 *** 46 14.9 *** 189 17.3 *** 208 19.9 ** 392 24.5 25.0-29.99 67 35.8 113 36.6 430 39.3 430 41.1 658 41.1 30.0+ 98 52.4 *** 149 48.2 *** 473 43.2 *** 406 38.9 * 549 34.3 Total 187 100 309 100 1094 100 1045 100 1601 100
χ2= 62,8; p<0.001; *p<0.05, **p<0.01, ***p<0.001 as compared with university level.
As it was presented in the review of literature chapter of the thesis, other authors also determined that lower education was related with higher mean of BMI. This probably could partially be explained by the lower salaries among persons with low education level and as a consequence lower probability follow a cardiovascular friendly diet because of the high cost of it, and the reduced knowledge of importance of smoking, fat food and alcohol consumption for cardiovascular risk.
The distribution of categories of BMI is related to age of individuals in the initial survey (Table 11.3.2). The largest proportion of individuals was in overweight category (BMI 25.0-29.99 kg/m2)
26 individuals in age group 45-49 years to 15.7% among individuals in oldest age group (age > 70 years), p<0.001).
Table 11.3.2. Distribution of study participants by body mass index categories and age groups at
the initial survey.
χ2 = 95.8, p<0.001; *p<0.05, ***p<0.001 as compared with age group 45-49 years.
While the opposite tendency was registered hen we analyzed the distribution of obesity in relation to age group: the proportion of obese individuals increased from 28.1% in youngest age group (45-49 years) to 47.2% in age group 70 years and older, p<0.001.The largest proportion of
individuals was in overweight category (BMI 25.0-29.99 kg/m2) in age groups 45-49 years, 50-54 years, and 55-59 years: the proportion varied from 40.9% to 43.2%. In other three age groups, most of individuals were obese: the prevalence of obesity varied from 41.5% to 47.2%. The proportion of individuals with normal body weight (BMI category 18.5-24.99 kg/m2) significantly decreased with increasing of age (from 30.5% among individuals in age group 45-49 years to 15.7% among individuals in oldest age group (age > 70 years), p<0.001). While the opposite tendency was registered, when we analyzed the distribution of obesity in relation to age group: the proportion of obese individuals increased from 28.1% in youngest age group (45-49 years) to 47.2% in age group 70 years and older, p<0.001.
27 As was explained on the literature review, as the age increase the BMI increases also, probably due to the decrease of physical activity.
The distribution of study participants by smoking habits according to education group and age group at the initial survey is presented in Table 11.3.3 and Table 11.3.4.
Table 11.3.3. Distribution of study participants by smoking habits and education level at the
initial survey.
Smoking habits
Education
Primary Vocational Secondary College University
N % N % N % N % N % Regular smokers 12 6.4 *** 43 13.9 233 21.3 *** 161 15.4 218 13.6 Ex-smokers 35 18.7 56 18.1 196 17.9 150 14.4 * 278 17.4 Never-smokers 140 74.9 210 68.0 663 60.8 *** 733 70.2 1105 69.0 Total 187 100 309 100 1092 100 1044 100 1601 100
χ2=53.5; p<0.001; *p<0.05, ***p<0.001 as compared with university level.
28
Table 11.3.4. Distribution of study participants by smoking habits and age groups at the initial
survey.
χ2=274.8; p<0.001; **p<0.01, ***p<0.001 as compared with age group 45-49 years.
The proportion of regular smokers significantly decreased with age (from 27.55% among individuals in age group 45-49 years to 2.3% among individuals in age group > 70 years,
p<0.001). While the opposite tendency was registered, when we analyzed the distribution of never smokers in relation to age group: the proportion of never smokers increased from 55.0% in
youngest age group (45-49 years) to 81.8% in age group 70 years and older, p<0.001. The distribution of study participants by alcohol consumption habits in relation to
education group and age group at the initial survey are presented in Table 11.3.5 and Table 11.3.6.
29 The largest proportion of individuals in all education groups (with exception of university education group) was category of drinkers drinking alcohol less than once a month, while
university education group the largest proportion of individuals were drinking alcohol about 1-3 times per month. The proportion of drinkers drinking alcohol about 1-3 times per month increased with increasing of education level while the proportion of drinkers less than once a month, in opposite, decreased (Table 11.3.5).
Table 11.3.5. Distribution of study participants by alcohol habits and education level at the initial
survey.
Alcohol consumption habits
Education
Primary Vocational Secondary College University
N % N % N % N % N % Every day or almost every day 3 1.6 13 4.2 36 3.3 20 1.9 42 2.6 About 2-4 times per week 13 7.0 21 6.8 86 7.9 82 7.8 151 9.4 About once per week 10 5.3 *** 33 10.7 114 10.4 *** 110 10.5 * 219 13.7 About 1-3 times per month 47 25.1 *** 80 25.9 *** 362 33.2 * 348 33.3 * 600 37.5 Less than once a month 83 49.7 145 46.9 427 39.1 *** 437 41.8 *** 518 32.4 Never in last year 21 11.2 ** 17 5.5 67 6.1 48 4.6 71 4.4 Total 187 100 309 100 1092 100 1045 100 1601 100
30 The largest proportions of individuals in the distribution by frequency of alcohol drinking was proportion of drinkers drinking alcohol about 1-3 times per month (age groups 45-59 years, 50-54 years, and 55-59 years) and drinking it less than once per month (age group 60-64 years, 65-69 years, and >70 years) (Table 11.3.6). The proportion of drinkers drinking alcohol once per week and about 1-3 times per month decreased with increasing of age. In opposite, the proportion of alcohol drinkers less than once per month and never in the last year increased with increasing of age.
Table 11.3.6. Distribution of study participants by alcohol habits and age group at the initial
survey
χ2=137.3, p<0.001; *p<0.05, **p<0.01, ***p<0.001 as compared with age group 45-49 years.
The table 11.3.7 and 11.3.8 presents the distribution of participants by their self-rated health according to the education and age groups, respectively.
31 The largest part of individuals in all education groups rated their health as medium: the proportion varied from 55.3% in university education group to 65.2% in primary education group (Table 11.3.7). The proportion of individuals, rating their health as poor or very poor and medium, decreased with increasing of education level and the proportion of individuals, rating health as good or very good, increased with increasing of education level.
Table 11.3.7. Distribution of study participants by self-rated health and education level at the
initial survey.
Self-rated health
Education
Primary Vocational Secondary College University
N % N % N % N % N % Poor/ very poor 34 18.2 *** 54 17.5 *** 162 14.8 *** 140 13.4 *** 122 7.6 Medium 122 65.2 ** 198 64.1 ** 662 60.5 ** 656 62.8 *** 885 55.3 Good/ver y good 31 16.6 *** 57 18.4 *** 270 24.7 *** 249 23.8 *** 594 37.1 Total 187 100 309 100 1094 100 1045 100 1601 100
32
Table 11.3.8.Distribution of study participants by self-rated health and age group at the initial
survey.
χ2=121.3, p<0.001; *p<0.05, **p<0.01, ***p<0.001 as compared with age group 45-49 years.
The largest part of participants in the the initial survey rated their health as medium in all age groups. The proportion of individuals, rating their health as medium, increased from 49.3% in age group 45-49 years to 65.3% in age group 70 years or older, p<0.001. Similar significant increase with age was registered for the proportion of self-rated health as poor or very poor. And, in contrast, the proportion of study participants, rating their health as good or very good, decreased with age.
We also analyzed the distribution of study participants by their evaluation of quality of life in relation to education level (Table 11.3.9) and age (Table 11.3.10).
The largest proportion of individuals rated their quality of life as medium (participants with primary, vocational, secondary, and college education) or good (participants with university education). The proportions of individuals, rating their quality of life as poor and medium
decreased with increasing of education level, and proportions of individuals rating their quality of life increased with increasing of education level.
33
Table 11.3.9. Distribution of study participants by self-rated quality of life and education level at
the initial survey.
Self rated quality of life
Education
Primary Vocational Secondary College University
N % N % N % N % N % Poor 15 8.2 *** 15 4.9 44 4.0 27 2.6 44 2.7 Medium 117 63.9 *** 191 61.8 *** 606 55.5 *** 515 49.3 *** 514 32.1 Good 50 27.3 *** 101 32.7 *** 423 38.8 *** 493 47.2 *** 1001 62.5 Very good 1 0.5 ** 2 0.6 *** 18 1.6 10 1.0 ** 42 2.6 Total 183 100 309 100 1091 100 1045 100 1601 100
χ2=273.4; p<0.001; **p<0.01, ***p<0.001 as compared with university level.
Table 11.3.10. Distribution of study participants by self-rated quality of life and age group at the
initial survey.
34 The largest part of participants at the initial survey rated their quality of life as good in age groups 45-49 years, 50-54 years, and 55-59 years and medium – in age groups 65-69 years and 70+ years. The proportion of individuals, rating their quality of life as medium, increased with age and proportion of individuals, rating quality of life as good and very good, decreased with age.
11.4 Comparison of the data on prevalence of lifestyle risk factors between the initial and follow up survey
In this chapter of the master thesis we analyzed and compared the lifestyle related risk factors among men and women at the initial survey and survey after 10 years (follow-up survey).
*p<0.001, **p<0.05 as compared with initial survey.
Figure 11.4.1. Distribution of screened men (in %) by BMI at the initial survey and survey after
10 years (follow-up survey)
As we can see in Figure 11.4.1, the proportion of male individuals with BMI <18.5
kg/m2(underweight category) increased by 0.2% (p>0.05).For men with BMI 18.5-24.99 kg/m2 (normal weight),we registered an increase in prevalence by 1.7% (p>0.05) and for those men with BMI 24.99-29.99kg/m2 (overweight) –a statistically significant (p=0.0275) increase by 3.7% (p<0.05).On the other hand, the proportion of obese individuals (BMI> 30 kg/m2) decreased by 5.6% 0.1 21.1 45.1 33.7 0.3 22.8 48.8 28.1 <18.5 kg/m2 18.5-24.99 kg/m2 25,0-29.99 kg/m2 >=30.0 kg/m2 Initial survey Follow-up survey
35 As we can see in Figure 11.4.2, the proportion of women with BMI <18.5 kg/m2 (underweight
category) increased by 0.5% (p<0.001). For women with BMI 18.5-24.99 kg/m2 (normal weight),
the increase in prevalence by 3.5% (p<0.001) was registered.
*p<0.001 as compared with initial survey.
Figure 11.4.2. Distribution of screened women (in %) by frequency of BMI (kg/m2) at the initial survey and survey after 10 years (follow-up survey).
For those women with BMI 24.99-29.99 kg/m2 (overweight) – no statistically significant changes were found (p>0.05), whereas the prevalence of obesity statistically significantly decreased from 43.9% at initial survey to 38.3% at follow-up survey.
As we can see from the presented results, the prevalence of obesity decreased in women and in men after 10 years from the baseline survey. The decrease is almost the same for both genders. This could be explained by changes in diet following the indications of family doctors, cardiologists and other specialists. Other authors also found [14,18] that with increase of age the
0.2 19.6 36.4 43.9 0,7 23.1 37.9 38.3 <18,5 kg/m2 18,5-24,99 kg/m2 25,0-29,99 kg/m2 >=30,0 kg/m2 Initial survey Follow-up survey
*
*
36
*
mean of BMI usually increase, one of the possible causes of it is the replacement of previous muscle with fat due to decrease of physical activity [14].
*p<0.001 as compared with initial survey
Figure 11.4.3. Distribution of screened men (in %) by tobacco smoking habits at the initial survey
and survey after 10 years.
As we can see from Figure 11.4.3, the proportion of male regular smokers after 10 years was significantly lower by10.8% as compared with same category of tobacco smoking habits in the initial survey (p<0.001), while the proportion of ex smokers significantly increased by 10.9% (p<0.001). We also could see that some of men changed their smoking habits about their smoking habits: less proportion of individuals at follow-up survey indicated that they never smoked tobacco (43.5% and 44.3%, p>0.05).
The distribution of screened women by tobacco smoking habits at the initial survey and survey after 10 years (follow-up survey) is presented in Figure 11.4.4.
25.8
30.6
44.3
15
41.5 43.5
regular ex-smoker never
Initial survey Follow-up survey
*
37 *p<0.01 as compared with initial survey.
Figure 11.4.4. Distribution of screened women (in %) by frequency of tobacco smoking at the
initial survey and survey after 10 years (follow-up survey).
The proportion of regular smokers among women significantly decreased from 8.9% at initial survey to 5.6% at survey 10 years later. At same time, the proportion of quitters significantly increased by 3.9% (from 7.0% at initial survey to 10.9% at follow-up survey, p<0.01
As we can see from presented results, the prevalence of tobacco smoking significantly decreased both among men and women. It could be explained by impact of age [33,34] smoking prevalence tends to increase between age15 years to 29 years and then decrease in both sexes in developed countries, and possibly as consequence of recommendations of family physicians, cardiologists and other specialists to quit smoking. [11,39].
8.9 7 84.1 5.6 10.9 83.5 0 10 20 30 40 50 60 70 80 90
regular sometimes ex smoker Never
Initial survey Follow-up survey
38 The distribution of screened men by alcohol consumption habits in the initial survey and survey after 10 years is presented in Figure 3.4.5.
We can see that in men group alcohol consumption habits in the follow-up survey after 10 years from initial survey significantly changed. The proportion of men who were consuming alcohol frequently (every day or almost every day and 2-4 times per week) in the next survey statistically significantly decreased as compared to the initial survey: from 5.0% to 2.6% (p<0.001) and from 16.4% to 6.4% (p<0.001), respectively. And in contrast, the proportion of men consuming alcohol rarely (less than once a month and never in last year) increased from 22.8% to
*p<0.001 as compared with initial survey.
Figure11.4.5. Distribution of screened men (in %) by frequency of alcohol consumption at the
initial survey and survey after 10 years (follow-up survey).
5 16.4 16.9 34.7 22.8 4.2 2.6 6.4 15.5 24.4 37.1 14.1 0 5 10 15 20 25 30 35 40 every day or almost every day about 2-4 times per week about once
per week about 1-3times per month less than once a month never in last year Initial survey Follow-up survey
*
*
*
*
39 37.1% (p<0.001) and from 4.2% to 14.1% (p<0.001), respectively. The proportions of men
drinking alcohol once a week did not significantly change between the initial and follow-up survey.
The distribution of screened women by alcohol consumption habits at initial survey and survey after 10 years (follow-up survey) is presented in Figure 11.4.6.
Same as in men group, Among women alcohol consumption habits in the follow up survey, 10 years after the initial survey, changed significantl. The proportion of women drinking alcoholic drinks relatively frequently (every day or almost every day, 2-4 times per week and once per week) in the follow-up survey statistically significantly decreased as compared to the survey:
*p<0.001 as compared with initial survey.
Figure 11.4.6. Distribution of screened women (in %) by frequency of alcohol consumption at the
initial survey and survey after 10 years (follow-up survey).
1 2.5 7.5 33.4 49.5 6.1 0.3 0.7 3.7 15.6 49.7 28.7 0 10 20 30 40 50 60 every day or almost every day about 2-4 times per week about once per week about 1-3 times per month
less than once a month
never in last year
Initial survey Follow-up survey
*
*
*
*
40 from 1.0% to 0.3% (p<0.001), from 2.5% to 0.7% (p<0.001), and from 7.5% to 3.7% (p<0.001), respectively.
We can see that both in men and women 10 years after the initial survey there was a decreased proportion of individuals drinking alcohol relatively frequently and increased the proportions consuming alcohol drinks less frequently, highly increasing the percentage of those that never drink at all. It could be explained by the impact of age [42], or after recommendations by physicians.
Figure 11.4.7 presents the distribution of men at the initial and follow-up surveys according to the evaluation of their health.
*p<0.001 as compared with initial survey.
Figure 11.4.7. Distribution of screened men (in %) by frequency of self reported health at the
initial survey and survey after 10 years (follow-up survey).
In the male group, after 10 years from the initial survey the proportion of individuals evaluating their health as good or very good decreased from 35.2% at initial survey to 29.0% (p<0.001). While the proportion of men with self-rated health as medium significantly increased from 55.7% to 61.7%. Changes of proportions of men, rating their health as poor or very poor, during two surveys were not statistically significant.
8.9 55.7 35.4 9.3 61.7 29 0 10 20 30 40 50 60 70
very poor/poor medium very good/good
Initial survey Follow-up survey
*
41 The distribution of women according to their health status at initial survey and survey after 10 years is presented in Figure 3.4.8.
In women group, we can see a decrease in proportion of individuals who rated their health as very poor or poor from 14.4% to 12.3% (p<0.05) between the initial and follow-up surveys. Other changes in evaluating self-rated status of health between two surveys were not statistically significant.
So, in the male and female population, changes of self-rated health between two surveys were not identical: the proportions of men, rating their health as very good or good decreased and rating health as medium increased, while among women the only significant change in evaluation of their health was decrease in the proportion of individuals rating their health as poor or very poor.
*p <0.05
Figure 11.4.8. Distribution of screened women (in %) by frequency of self reported health at the
initial survey and survey after 10 year (follow-up survey).
That’s opposite to what we could expect to find because among men and women there is a decrease of the prevalence of some risk factors here detected. We could suggest that this event happened because it had passed ten years from the first survey, so even if they reduced the risk factor levels, the general health of them will be affected by aging process. During the first survey, men and women were aged from 45 years to more than 70 years; it mean that 10 years later, we
14.4
62.4
23.2
12.3
64.9
22.8
0
10
20
30
40
50
60
70
very poor/poor
medium
very good/good
Initial survey
Follow-up survey
42 have a population of individuals aged from 55 to 80 years, most of them having one or two
chronic non-communicable diseases, mainly CVD.
Changes in evaluation of quality of life in the initial survey and ten years later are presented in Figure 11.4.9 (among men) and Figure 11.4.10 (among women).
*p<0.01, **p<0.001 as compared to initial survey.
Figure 11.4.9. Distribution of screened men (in %) by evaluation of quality of life at the initial
survey and survey after 10 years (follow-up survey).
2.6
44
51.3
2.1
7.8
49.2
41.7
1.3
0
10
20
30
40
50
60
poor
medium
good
very good
Initial survey
Follow-up survey
**
*
43 *p<0.001 as compared with initial survey.
Figure 11.4.10. Distribution of screened women (in %) by frequency of quality of life at the initial
survey and survey after 10 years (follow-up survey).
We could see from the results presented in the Figures that the change in the evaluation of self-rated quality of life was very similar both in men and women group. During the follow-up survey, the proportions of individuals rating their quality of life as poor and medium significantly
increased and proportion of individuals rating quality of life as good significantly decreased in both sexes when compared with same proportions in the initial survey. The decrease in frequency of evaluation of self-rated quality of life as very good was not statistically significant.
The results of five multivariate logistic regression models, showing OR and 95% CI of frequent alcohol consumption, regular smoking, poor self-rated health, poor self-rated quality of life, and having high BMI at follow-up survey are presented in Table 11.4.1.
4
47.3
47.2
1.5
9.1
56.8
33.2
0.9
0
10
20
30
40
50
60
poor
medium
good
very good
Initial survey
Follow-up survey
*
44
Table 11.4.1. Odds ratios (OR) of frequent alcohol consumption, poor self-rated health, poor self-rated
quality of life, regular smoking and high body mass index at follow-up survey (multivariate logistic regression models)
Dependent variables at follow-up survey
Independent variables at initial survey Alcohol consumptio n Physical activity Self-rated health Self rated quality of life BMI Smoking OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI) Frequent alcohol consumption 5.15 (4.20-6.33) -- 0.76 (0.52-1.10) -- -- 1.23 (0.97-1.57) Poor self-rated health 0.80 (0.60-1.07) 1.14 (0.90-1.45) 4.78 (3.80-6.02) 2.47 (1.64-3.71) -- 1.42 (1.05-1.92) Poor self-rated quality of life -- 1.17 (0.90-1.52) 3.42 (2.64-4.43) 3.87 (2.61-5.76) -- 1.54 (1.13-2.11) Regular smoking 1.29 (0.94-1.77) -- -- -- 0.99 (0.72-1.37) 75.8 (53.2-108.0) High BMI (> 25.0 kg/m2) 0.93 (0.73-1.18) -- 1.72 (1.25-2.37) -- 34.8 (28.2-42.9) 1.12 (0.85-1.48) Age as continuous variable and sex as categorized variable (1. Male, 2. Female) were included into each multivariate logistic regression model. Variables in the initial survey as independent variables were included into each multivariable model in case if they were significant predictors in univariate logistic regression model. Both independent and dependent variables were categorized: alcohol
consumption (1. Frequent alcohol consumption (every day or almost every day, 2-4 times per week). 2. Rest of consumers); self-rated health (1. Very poor and poor self-rated health, 2. Medium, good and very good self-rated health); self-rated quality of life (1. Poor and very poor self-rated quality of life, 2. Medium, good and very good quality of life), smoking (1. Regular smokers, 2. Never smokers and quitters); BMI (1. High BMI > 25.0 kg/m2, 2. BMI < 25.0 kg/m2). Physical activity was determined at
initial survey only (1. Physically active, 2. Physically inactive). CI – confidence interval, BMI – body mass index.
45 smoking habits in the initial survey. The odds of having high BMI in the follow-up survey was significantly related with BMI and self-rated health in the initial survey.
46
12 Conclusions
1) The prevalence of overweight and obesity in the initial survey of men and women aged 45-72 years was high.
The prevalence of overweight was significantly higher among men as compared to women (45.1% and 36.4%), whereas the prevalence of obesity was significantly higher among women (43.8% and 33.7%).
The proportion of individuals with normal body significantly decreased with increasing of age, while the proportion of obese individuals, increased from 28.1% in youngest age group to 47.2% in oldest group.
The proportion of individuals with normal body weight significantly increased and the proportion of obese individuals significantly decreased with increasing of education level. 2) The prevalence of regular smoking decreased and the proportion of ex-smokers increased
both among men and women when data was compared between the follow up survey and initial survey being significantly higher in men as compared to women.
The proportion of regular smoking changed with age and education level. The largest proportion of regular smokers was among individuals with secondary education (21.3%) and the smallest one was among individuals with primary education (6.4%).
The prevalence of tobacco smoking significantly decreased with age.
3) In men, the largest proportion of individuals indicated in the initial survey that they consumed alcohol about 1 to 3 times per month and in women, the largest proportion of individuals indicated that they consumed alcohol less than once a month.
The proportion of individuals drinking alcohol relatively less frequently increased with increasing of education level and age. In both gender groups, after 10 years from initial survey decreased the proportions of individuals drinking alcohol relatively frequently and increased the proportions consuming alcohol drinks less frequently.
4) Most of the screened men and women rated their health at the initial survey as medium and quality of life as medium or good.
The proportions of individuals rating their health and quality of life as good and very good increased with increasing of education level but decreased with increasing of age.
47 significant change was A decrease in the proportion of individuals rating their health as poor or very poor.
During the follow up survey, the proportions of individuals rating their quality of life as poor and medium significantly increased and proportion of individuals rating quality of life as good decreased both in men and women.
5) The odds of frequent alcohol consumption, regular smoking, poor self-rated health, poor self-rated quality of life, and having high BMI in the follow-up survey were significantly related with same lifestyle variables determined in the initial survey using multivariate logistic regression analysis. Poor self-rated health and poor self-rated quality of life in the follow-up survey were also related with smoking habits determined 10 years earlier: during the initial survey. Poor self-rated health after 10 years from the initial survey was related with self-rated quality of life and poor self-rated quality of life was related with self-rated health determined at the start of the study. The odds of having high BMI in the follow-up survey was significantly related with BMI and self-rated health at initial survey.
48
13 Practical recommendations.
As it was presented, chronic non-communicable diseases, mainly CVD and malignant neoplasm, are responsible for death worldwide and they are intrinsically ligated to some risk factors that we should avoid and educate the population about them for prevention of the high prevalence of these diseases, and avoid the evolution of them on those patients that already suffer from CVD and that by avoiding those risk factors could prolong their life.
Those modifications should be recommended:
Overweight and obesity - diet: We should recommend to decrease the body weight for
overweight and obese individuals, for this the first recommendation is change in the diet - decrease the level of animal fats, control of salt consumption, increase in consumption of
vegetables and other products rich in fiber if needed some medications can be provide for ensure the loss of weight.
Overweight and obesity- physical activity: As important as diet is to increase physical activity,
thus should be recommended, even if body weight is normal. It is recommended at least 150 minutes per week of moderate exercise, like walking or also as alternative we can recommend 75 minutes per week of vigorous exercise.
Alcohol use: We should recommend the decrease of alcohol consumption because it is responsible
of an increase in the level of triglycerides and damage our organism. Some recommendations of the consumption of one standard drink of wine per day due to some possible cardio-protective effect didn’t have prove better results than that achieved by consumption of nuts or fresh olive oil So, we should not recommend alcohol consumption as cardio-protective measure in order to avoid misunderstandings and due possibility that some patients could consume more than one drink of alcohol per day.
Tobacco smoking: we should recommend to regular smokers to stop smoking and offer them
49
14 Literature list
1. World Health Organization (WHO). Cardiovascular diseases (CVDs): World Health Organization; 2017 May. Available from:
http://www.who.int/cardiovascular_diseases/en
2. Eurostat. Causes of death statistics – people over 65. 3 October 2017. Available
from:http://ec.europa.eu/eurostat/statisticsexplained/index.php/File:Major_causes_of_deat h_for_persons_aged_65_or_over,_2014_(standardised_death_rates_per_100_000_inhabit ants)_HLTH17.png
3. Institute of medicine (US) committee on preventing the global epidemic of cardiovascular disease: meeting the challenges in developing countries; Fuster V, Kelly BB, editors. Promoting cardiovascular health in the developing world: A critical challenge to achieve global health. Washington (DC): National academies press (US); 2010. 2 ISBN-13: 978-0-309-14774-3ISBN-10: 0-309-14774-3
4. Sanchez BR, Maldonado M. Book: Medicina preventiva, epidemiologia y bioestadística. Asturias Oviedo: Imprime I. Gofer. 2017. p. 160-9.
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