- Split View
-
Views
-
Cite
Cite
János Girán, István KISS, Antonio De Blasio, Then and now: a revision of the city health profile of the city of Pécs, Hungary, Health Promotion International, Volume 31, Issue 1, March 2016, Pages 153–162, https://doi.org/10.1093/heapro/dau067
- Share Icon Share
Abstract
The City of Pécs, a founding member, has participated in the World Health Organization European Healthy Cities Network (WHO-EHCN) since 1986. Each WHO-EHCN city prepares a city health profile (CHP) through which it supports local health-related activities. The first CHP of Pécs was carried out in 1996. The aim of more recent research has been to implement a comprehensive review of the first CHP and to make a comparative analysis between the results of the former and the updated CHPs. The data were received from different databases and a telephone survey. The review showed improvement in those areas that can be influenced through the measures of the city authorities. The survey showed that both the ratio of smokers and the amount of cigarettes smoked had decreased so that the ratio of regular smokers became the lowest among the youngest age group. The number of alcohol consumers increased, while the amount of alcohol consumed dropped slightly, meaning that alcohol consumption per capita decreased overall. The comparative analysis highlighted unhealthy diets, insufficient sleep duration and physical inactivity becoming significant health risk factors. To avoid a ‘reinventing the wheel’ situation, it would be worth comparing the results of health and lifestyle surveys of other WHO-EHCN cities and eventually jointly devise the best solutions.
INTRODUCTION
Based on the number of inhabitants (165 000), the city of Pécs is the fifth largest city of Hungary. It is a regional center, episcopal see and a university center. The city of Pécs, a founding member, has participated in World Health Organization European Healthy Cities Network (WHO-EHCN) since 1986. The primary goal of WHO-EHCN is to put health high on the social, economic and political agenda of city authorities. Work within WHO-EHCN includes the development of city health profiles, city health development programs, healthy urban planning, health impact assessment, community engagement and capacity building. These activities target the social determinants of inequalities in health (WHO, 2012).
The member cities of WHO-EHCN work in 5-year action phases based on the core themes of the given phase. From the beginning, to support local health-related strategic planning, every city realized the need for a status report that provides data and information on the physical and social dimensions and determinants of the daily life of its citizens, a need served through the elaboration of the city health profile (CHP). After drafting the methodological bases of CHP preparation (WHO, 1995), the WHO-EHCN cities agreed to develop their own CHP monitoring and to renew them on a regular basis.
THE CITY HEALTH PROFILE
The CHP is a public health report that collects and interprets baseline information on health and its determinants in the city. The CHP can serve as a trigger factor for actions handling current health challenges. It can also stimulate the local population, health professionals, politicians and policymakers to initiate community-based health promotion activities and to provide a focus for intersectoral actions and source allocations. The CHP can form the basis for a city health plan and city health development plan that set out strategies and programs of intervention to improve the health condition of its residents (WHO, 1998).
On elaborating the methodological basis for establishing the CHP, it was the experts' main priority to consider that the CHP needed to contain information and data going beyond mortality and morbidity conditions introduced earlier; it needed to be supplemented by the description of the social, economic and physical environment (WHO, 1998). The CHP uses indicators to describe health as well as the health services, the environment and the socio-economic features of the city.
To facilitate the implementation of CHPs, WHO-EHCN specialists developed a set of healthy city indicators (HCIs). The original set of HCIs contained 53 items. Its adequacy was reviewed comprehensively through the analysis of 47 WHO-EHCN city reports (Doyle et al., 1999). The revision resulted in a more concise set of 32 indicators (see Table 2), which are now used by the WHO-EHCN cities to prepare a CHP (Webster and Sanders, 2013).
Besides the factors described by the HCIs, individual lifestyle and health behavior are also essential parts of the CHP. The recommended method for data and information collecting is a specified survey. To baseline information for actions, the survey should target health behaviors and health circumstances and also their consequences on health. It is well known that individual responses to the physical, mental and social effects of illnesses on daily living influence the extent to which personal satisfaction with living conditions can be achieved. Furthermore, several aspects of personal behavior, such as diet, smoking, and alcohol consumption, are known to influence the health status and form the focus of health promotion. Obtaining data concerning the frequency of health-related behaviors is crucial to the planning of primary prevention programs (Garcia and McCarthy, 1996; Crown, 2003). The CHP results from the HCI and the survey parts as an empirical tool to inform the decision-makers of health policy and planning and to strengthen the public health agenda (Webster and Lipp, 2009).
STUDY OBJECTIVE
The first CHP of the city of Pécs (Füzesi and Tistyán, 1996), the first in Hungary, was prepared by the Fact Foundation of Pécs in cooperation with the Healthy City Foundation (HCF), which provides local WHO-EHCN management in the city. This CHP was published in 1996. The first part, using the HCIs, described health, health services, environment and socio-economic features of the city in 1994. The second part, based on the results of targeted survey, revealed the individual lifestyle and health behavior characteristics of its residents. This survey was conducted in 1995. Nearly two decades have passed since the elaboration of the first CHP. During this period, the fields described by the HCIs were updated from time to time. The health and lifestyle survey, however, has yet to be repeated.
One of the main aims of the recent research project was to provide a comprehensive review of the CHP, including both the updates of HCIs and the repeated health and life style survey. The other was to present a comparative analysis between the former and recent results.
METHODS
In the course of implementing the CHP, the data required to update the HCIs were obtained partly from the Hungarian Central Statistical Office (HCSO) and partly from open access online data bases [e.g. TEIR (National Spatial Development Information System; www.teir.hu)] and also from Pécs municipality's own databases.
The data for the health and lifestyle survey were collected in June 2012. The sample represented the adult inhabitants of the city according to gender and age and comprised 800 individuals (Table 1). The design was a quota sampling based on the demographic structure of Pécs for the year 2011. Reference data were borrowed from the T-STAR HCSO database, which is based on the annual demographic report of Hungarian settlements. (In the case of the first CHP survey, face-to-face interviews were employed. The sample represented the adult inhabitants of the city according to gender and age and comprised 1200 individuals. The design was a quota sampling based on the demographic structure of Pécs for the year 1990. Reference data were borrowed from the National Census 1990 database of the HCSO.) There is no statistically significant difference between the sample's distribution and the reference data.
City of Pécs . | Hungary . | ||||||
---|---|---|---|---|---|---|---|
Age groups (years) . | Sex . | Total (%) . | Age groups (years) . | Sex . | Total (%) . | ||
Male (%) . | Female (%) . | Male (%) . | Female (%) . | ||||
18–29 | 8.2 | 9.1 | 17.3 | 18–29 | 9.8 | 9.4 | 19.2 |
30–39 | 9.6 | 10.9 | 20.5 | 30–39 | 10.0 | 9.6 | 19.7 |
40–49 | 7.1 | 8.5 | 15.6 | 40–49 | 7.9 | 7.9 | 15.8 |
50–59 | 5.6 | 12.0 | 17.6 | 50–59 | 8.1 | 9.2 | 17.4 |
60 and over | 11.9 | 17.1 | 29.0 | 60 and over | 10.8 | 17.1 | 27.9 |
Total | 42.4 | 57.6 | 100.0 | Total | 46.7 | 53.3 | 100.0 |
City of Pécs . | Hungary . | ||||||
---|---|---|---|---|---|---|---|
Age groups (years) . | Sex . | Total (%) . | Age groups (years) . | Sex . | Total (%) . | ||
Male (%) . | Female (%) . | Male (%) . | Female (%) . | ||||
18–29 | 8.2 | 9.1 | 17.3 | 18–29 | 9.8 | 9.4 | 19.2 |
30–39 | 9.6 | 10.9 | 20.5 | 30–39 | 10.0 | 9.6 | 19.7 |
40–49 | 7.1 | 8.5 | 15.6 | 40–49 | 7.9 | 7.9 | 15.8 |
50–59 | 5.6 | 12.0 | 17.6 | 50–59 | 8.1 | 9.2 | 17.4 |
60 and over | 11.9 | 17.1 | 29.0 | 60 and over | 10.8 | 17.1 | 27.9 |
Total | 42.4 | 57.6 | 100.0 | Total | 46.7 | 53.3 | 100.0 |
City of Pécs . | Hungary . | ||||||
---|---|---|---|---|---|---|---|
Age groups (years) . | Sex . | Total (%) . | Age groups (years) . | Sex . | Total (%) . | ||
Male (%) . | Female (%) . | Male (%) . | Female (%) . | ||||
18–29 | 8.2 | 9.1 | 17.3 | 18–29 | 9.8 | 9.4 | 19.2 |
30–39 | 9.6 | 10.9 | 20.5 | 30–39 | 10.0 | 9.6 | 19.7 |
40–49 | 7.1 | 8.5 | 15.6 | 40–49 | 7.9 | 7.9 | 15.8 |
50–59 | 5.6 | 12.0 | 17.6 | 50–59 | 8.1 | 9.2 | 17.4 |
60 and over | 11.9 | 17.1 | 29.0 | 60 and over | 10.8 | 17.1 | 27.9 |
Total | 42.4 | 57.6 | 100.0 | Total | 46.7 | 53.3 | 100.0 |
City of Pécs . | Hungary . | ||||||
---|---|---|---|---|---|---|---|
Age groups (years) . | Sex . | Total (%) . | Age groups (years) . | Sex . | Total (%) . | ||
Male (%) . | Female (%) . | Male (%) . | Female (%) . | ||||
18–29 | 8.2 | 9.1 | 17.3 | 18–29 | 9.8 | 9.4 | 19.2 |
30–39 | 9.6 | 10.9 | 20.5 | 30–39 | 10.0 | 9.6 | 19.7 |
40–49 | 7.1 | 8.5 | 15.6 | 40–49 | 7.9 | 7.9 | 15.8 |
50–59 | 5.6 | 12.0 | 17.6 | 50–59 | 8.1 | 9.2 | 17.4 |
60 and over | 11.9 | 17.1 | 29.0 | 60 and over | 10.8 | 17.1 | 27.9 |
Total | 42.4 | 57.6 | 100.0 | Total | 46.7 | 53.3 | 100.0 |
The residents were contacted by using the computer-assisted telephone interviewing system (CATI), calling landline phone numbers of permanent residents of Pécs. Matching the quota, a two-step selection method was applied: firstly, to select a reasonable number of potential respondents, a random digit dialling (RDD) method was applied to reach both listed and unlisted numbers. Secondly, within each reached household, the respondent was chosen by age and gender quota. Trained interviewers of the ‘Szocio-Graf’ Marketing and Public Opinion Research Institution made a total of 12 028 calls (6702 non-contact; 3361 refused; 71 broke off; 1094 out of quota/not eligible) that resulted in the final 800 completed interviews. According to the AAPOR ‘Response Rate 6’ definition (AAPOR, 2011), this result represents a 7.96% response rate. The sample was corrected by weighting; the weight values of the sample were between 0.78 and 1.43.
To conduct a comparative analysis, the questions were exactly the same in both the first and the second CHP surveys where the comparison between data from 1995 and 2012 is published. However, some supplementary questions were added which had not been asked in the earlier questionnaire.
Bearing in mind the core target areas of this article, several types of questions were applied. In eliciting feedback on the Health in everyday life and Knowledge on health consequences themes, closed-ended ordinal and interval measuring level scale-type questions were used with five ordered response levels ranging from scale 1 for the most negative opinion to scale 5 for the most positive. Smoking status was assessed using a standard item, asking respondents directly whether how often and how intensively they smoked cigarettes. According to this item, four categories were created: daily smokers, social smokers, those who have quit smoking and non-smokers. Data on alcohol consumption were collected using a question on weekly intake of beer, wine and/or liquor consumption. Heavy drinkers, moderate drinkers and non-drinkers were defined on the basis of the weekly consumed alcoholic drinks. (According to the classification of the HCSO, heavy drinkers comprised those women and men who consumed 7 or more units of alcohol and 14 or more units of alcohol, respectively, in the week preceding the survey. One unit of alcohol is equivalent to one pint of beer or 200 ml wine or 50 ml liquor [(HCSO, 2010) p. 6].) Daily sleep duration was measured using the question: how many hours do you sleep. The data were analyzed as a dichotomous variable (8 h or more sleep and <8 h sleep). To learn more about physical activity routines, the following question was asked: How often do you participate in sporting activities? The body mass index (BMI) calculation was based on the respondents' self-reported height and weight.
Data were analyzed using contingency table analysis, correspondence analysis and ANOVA tests. To check stochastic dominance, the chi-square test and t-test were applied. The relation was considered as significant when p ≤ 0.05. The main control variables were gender, age (based on the quota) and the self-reported education level.
RESULTS
In this article, there is no opportunity to detail all of the findings of the recent CHP survey; it therefore focuses only on reporting about the main tendencies and results. In the first CHP, the HCI data referred to the year 1994, whereas the data of the survey pertained to the year 1995. To demonstrate the differences between the former and the present situation in the case of HCI, the data of 1994 and 2011 were compared. In the case of the survey, the data for the years 1995 and 2012 were compared and the stochastic dominance was tested by the one-sample t-test. During these comparative analyses, the data of the survey carried out in 1995 were employed as test values and, in the case of p ≤ 0.05, the differences were considered as statistically significant. Concerning the data on the BMI and the awareness on health determinants, no comparisons were made, since the former CHP did not contain data regarding these factors. National and EU data were also provided where such data were available to support the evaluation of local results and their comparison with other figures.
Health services, environment and socio-economic indicators then and now
The majority of the HCIs are made up of the aggregate of part figures. Accordingly, the contents of most HCIs cannot typically be expressed with a single numerical value. However, the size limitation of this article does not allow for the publication of every single part figure with regards to every single indicator. We therefore chose a solution that involved comparing part figures from Pécs for a given HCI to the same average figures typical for the whole of the nation in that given year. As a result, the given HCI was classified as one of the three possible categories; the given HCI was esteemed Good when the majority of local part figures were more favorable than 110% of the national average values, while the HCI was deemed Average when the majority of local part figures produced a maximum of ±10% deviation from the national average values, and the HCI was classified as Weak when the majority of local part figures was below 90% of the national average values. For example, the Children's immunization rate indicator is made up of the part figures for diphtheria–pertussis–tetanus, morbilli–parotitis–rubella, poliomyelitis and BCG vaccinations. If three of the four part figures under review exceeded 110% of the national immunization rate, the immunization rate indicator was deemed Good (Table 2). These categories aggregate the data and information contents of the individual HCIs and by that they create the possibility to identify the main tendencies of changes.
Healthy city indicators . | 1994 . | 2011 . | Change . |
---|---|---|---|
Health | |||
Mortality | Weak | Weak | n.c. |
Main causes of mortalitya | Good | Average | Negative |
Low birth weight | Average | Average | n.c. |
Health services | |||
City health education programs | Average | Average | n.c. |
Children's immunization rates | Good | Good | n.c. |
Inhabitants per primary health-care practitioner | Weak | Good | Positive |
Inhabitants per nurse | Weak | Good | Positive |
Percentage of population covered by health insurance | n.a. | n.a. | n.a. |
Availability of services in foreign languages | n.a. | Good | Positive |
Health debates in city council | Average | Average | n.c. |
Environmental indicators | |||
Air pollution | Weak | Average | Positive |
Water quality | Average | Good | Positive |
Sewage collection | Average | Good | Positive |
Household waste collection | Average | Good | Positive |
Household waste treatment | Average | Good | Positive |
Relative surface area of green space | Good | Good | n.c. |
Public access to green space | Good | Good | n.c. |
Derelict industrial sites | Weak | Good | Positive |
Sport and leisure facilities | Average | Average | n.c. |
Pedestrianization | Average | Good | Positive |
Cycle routes | Weak | Weak | n.c. |
Public transport access | Average | Average | n.c. |
Public transport range | Average | Average | n.c. |
Living space | Average | Average | n.c. |
Socio-economic indicators | |||
Percentage of population in inadequate housing | Good | Good | n.c. |
Homelessness | Good | Weak | Negative |
Unemployment | Good | Weak | Negative |
Poverty | Good | Average | Negative |
Availability of child care | Average | Average | n.c. |
Age of mothers at time of birth | n.a. | n.a. | n.a. |
Abortion rate | Average | Average | n.c. |
Employment of disabled people | n.a. | n.a. | n.a. |
Healthy city indicators . | 1994 . | 2011 . | Change . |
---|---|---|---|
Health | |||
Mortality | Weak | Weak | n.c. |
Main causes of mortalitya | Good | Average | Negative |
Low birth weight | Average | Average | n.c. |
Health services | |||
City health education programs | Average | Average | n.c. |
Children's immunization rates | Good | Good | n.c. |
Inhabitants per primary health-care practitioner | Weak | Good | Positive |
Inhabitants per nurse | Weak | Good | Positive |
Percentage of population covered by health insurance | n.a. | n.a. | n.a. |
Availability of services in foreign languages | n.a. | Good | Positive |
Health debates in city council | Average | Average | n.c. |
Environmental indicators | |||
Air pollution | Weak | Average | Positive |
Water quality | Average | Good | Positive |
Sewage collection | Average | Good | Positive |
Household waste collection | Average | Good | Positive |
Household waste treatment | Average | Good | Positive |
Relative surface area of green space | Good | Good | n.c. |
Public access to green space | Good | Good | n.c. |
Derelict industrial sites | Weak | Good | Positive |
Sport and leisure facilities | Average | Average | n.c. |
Pedestrianization | Average | Good | Positive |
Cycle routes | Weak | Weak | n.c. |
Public transport access | Average | Average | n.c. |
Public transport range | Average | Average | n.c. |
Living space | Average | Average | n.c. |
Socio-economic indicators | |||
Percentage of population in inadequate housing | Good | Good | n.c. |
Homelessness | Good | Weak | Negative |
Unemployment | Good | Weak | Negative |
Poverty | Good | Average | Negative |
Availability of child care | Average | Average | n.c. |
Age of mothers at time of birth | n.a. | n.a. | n.a. |
Abortion rate | Average | Average | n.c. |
Employment of disabled people | n.a. | n.a. | n.a. |
Average, the exact value is ±10% of the national average; Good, the exact value exceeded 110% of the national average; Weak, the exact value is <90% of the national average; n.a., data is not available; n.c., no change.
aIn case of main causes of death indicator, the five most prevalent causes of death were taken into consideration. Regarding this indicator the Good appraisal means that the exact value is <90% of the national average in at least three out of five causes of death. The Average means the exact value is ±10% of the national average. The Weak means the exact value exceeds 110% of the national average.
Healthy city indicators . | 1994 . | 2011 . | Change . |
---|---|---|---|
Health | |||
Mortality | Weak | Weak | n.c. |
Main causes of mortalitya | Good | Average | Negative |
Low birth weight | Average | Average | n.c. |
Health services | |||
City health education programs | Average | Average | n.c. |
Children's immunization rates | Good | Good | n.c. |
Inhabitants per primary health-care practitioner | Weak | Good | Positive |
Inhabitants per nurse | Weak | Good | Positive |
Percentage of population covered by health insurance | n.a. | n.a. | n.a. |
Availability of services in foreign languages | n.a. | Good | Positive |
Health debates in city council | Average | Average | n.c. |
Environmental indicators | |||
Air pollution | Weak | Average | Positive |
Water quality | Average | Good | Positive |
Sewage collection | Average | Good | Positive |
Household waste collection | Average | Good | Positive |
Household waste treatment | Average | Good | Positive |
Relative surface area of green space | Good | Good | n.c. |
Public access to green space | Good | Good | n.c. |
Derelict industrial sites | Weak | Good | Positive |
Sport and leisure facilities | Average | Average | n.c. |
Pedestrianization | Average | Good | Positive |
Cycle routes | Weak | Weak | n.c. |
Public transport access | Average | Average | n.c. |
Public transport range | Average | Average | n.c. |
Living space | Average | Average | n.c. |
Socio-economic indicators | |||
Percentage of population in inadequate housing | Good | Good | n.c. |
Homelessness | Good | Weak | Negative |
Unemployment | Good | Weak | Negative |
Poverty | Good | Average | Negative |
Availability of child care | Average | Average | n.c. |
Age of mothers at time of birth | n.a. | n.a. | n.a. |
Abortion rate | Average | Average | n.c. |
Employment of disabled people | n.a. | n.a. | n.a. |
Healthy city indicators . | 1994 . | 2011 . | Change . |
---|---|---|---|
Health | |||
Mortality | Weak | Weak | n.c. |
Main causes of mortalitya | Good | Average | Negative |
Low birth weight | Average | Average | n.c. |
Health services | |||
City health education programs | Average | Average | n.c. |
Children's immunization rates | Good | Good | n.c. |
Inhabitants per primary health-care practitioner | Weak | Good | Positive |
Inhabitants per nurse | Weak | Good | Positive |
Percentage of population covered by health insurance | n.a. | n.a. | n.a. |
Availability of services in foreign languages | n.a. | Good | Positive |
Health debates in city council | Average | Average | n.c. |
Environmental indicators | |||
Air pollution | Weak | Average | Positive |
Water quality | Average | Good | Positive |
Sewage collection | Average | Good | Positive |
Household waste collection | Average | Good | Positive |
Household waste treatment | Average | Good | Positive |
Relative surface area of green space | Good | Good | n.c. |
Public access to green space | Good | Good | n.c. |
Derelict industrial sites | Weak | Good | Positive |
Sport and leisure facilities | Average | Average | n.c. |
Pedestrianization | Average | Good | Positive |
Cycle routes | Weak | Weak | n.c. |
Public transport access | Average | Average | n.c. |
Public transport range | Average | Average | n.c. |
Living space | Average | Average | n.c. |
Socio-economic indicators | |||
Percentage of population in inadequate housing | Good | Good | n.c. |
Homelessness | Good | Weak | Negative |
Unemployment | Good | Weak | Negative |
Poverty | Good | Average | Negative |
Availability of child care | Average | Average | n.c. |
Age of mothers at time of birth | n.a. | n.a. | n.a. |
Abortion rate | Average | Average | n.c. |
Employment of disabled people | n.a. | n.a. | n.a. |
Average, the exact value is ±10% of the national average; Good, the exact value exceeded 110% of the national average; Weak, the exact value is <90% of the national average; n.a., data is not available; n.c., no change.
aIn case of main causes of death indicator, the five most prevalent causes of death were taken into consideration. Regarding this indicator the Good appraisal means that the exact value is <90% of the national average in at least three out of five causes of death. The Average means the exact value is ±10% of the national average. The Weak means the exact value exceeds 110% of the national average.
In the researched time frame, there were no available data in the case of three indicators. Fourteen indicators did not show any changes, while 4 indicators changed negatively and 10 indicators changed positively. The indicators of health typically showed stagnation, while improvement was observed in the area of health services. The majority of the environmental indicators changed positively or remained unchanged; there were no negative changes. In the case of socio-economic indicators, the situation is exactly the opposite: besides the unchanged indicators, only negative changes occurred.
Health in everyday life—data and opinions on the basis of the survey's results
As regards the issue of health in everyday life, the position of health as a value within the actual individual value-preference is essential. The respondents evaluated eight value categories based on where the given value was positioned among the values regarding their everyday life. The value categories and their formal and recent rank are shown in Table 3.
How important value is for you the … . | Rank in 1995 . | Rank in 2012 . | Change . | t-Value . | p-Value . |
---|---|---|---|---|---|
Proper health | 1 | 1 | 0 | 106.48 | 0.000 |
Harmonious family life | 2 | 2 | 0 | 84.84 | 0.000 |
Peace of mind | 6 | 3 | 3 | 151.07 | 0.000 |
Clean environment | 7 | 4 | 3 | 178.29 | 0.000 |
Good human relations | 8 | 5 | 3 | 146.93 | 0.000 |
Stable workplace | 4 | 6 | −2 | 68.69 | 0.000 |
Prosperity | 3 | 7 | −4 | 53.42 | 0.000 |
Professional success | 8 | 8 | 0 | 86.69 | 0.000 |
How important value is for you the … . | Rank in 1995 . | Rank in 2012 . | Change . | t-Value . | p-Value . |
---|---|---|---|---|---|
Proper health | 1 | 1 | 0 | 106.48 | 0.000 |
Harmonious family life | 2 | 2 | 0 | 84.84 | 0.000 |
Peace of mind | 6 | 3 | 3 | 151.07 | 0.000 |
Clean environment | 7 | 4 | 3 | 178.29 | 0.000 |
Good human relations | 8 | 5 | 3 | 146.93 | 0.000 |
Stable workplace | 4 | 6 | −2 | 68.69 | 0.000 |
Prosperity | 3 | 7 | −4 | 53.42 | 0.000 |
Professional success | 8 | 8 | 0 | 86.69 | 0.000 |
How important value is for you the … . | Rank in 1995 . | Rank in 2012 . | Change . | t-Value . | p-Value . |
---|---|---|---|---|---|
Proper health | 1 | 1 | 0 | 106.48 | 0.000 |
Harmonious family life | 2 | 2 | 0 | 84.84 | 0.000 |
Peace of mind | 6 | 3 | 3 | 151.07 | 0.000 |
Clean environment | 7 | 4 | 3 | 178.29 | 0.000 |
Good human relations | 8 | 5 | 3 | 146.93 | 0.000 |
Stable workplace | 4 | 6 | −2 | 68.69 | 0.000 |
Prosperity | 3 | 7 | −4 | 53.42 | 0.000 |
Professional success | 8 | 8 | 0 | 86.69 | 0.000 |
How important value is for you the … . | Rank in 1995 . | Rank in 2012 . | Change . | t-Value . | p-Value . |
---|---|---|---|---|---|
Proper health | 1 | 1 | 0 | 106.48 | 0.000 |
Harmonious family life | 2 | 2 | 0 | 84.84 | 0.000 |
Peace of mind | 6 | 3 | 3 | 151.07 | 0.000 |
Clean environment | 7 | 4 | 3 | 178.29 | 0.000 |
Good human relations | 8 | 5 | 3 | 146.93 | 0.000 |
Stable workplace | 4 | 6 | −2 | 68.69 | 0.000 |
Prosperity | 3 | 7 | −4 | 53.42 | 0.000 |
Professional success | 8 | 8 | 0 | 86.69 | 0.000 |
Comparing the results of the two surveys, good health used to be and remained the most important value for the adult citizens of Pécs. Harmonious family life is also crucial, while the significance of peace of mind, a clean environment and good human relations increased. The importance of a stable workplace and prosperity weakened, while the value of professional success remained unchanged.
As well as determining values, questions focused on what people feared the most in their everyday life. Every third adult citizen (30.3%) feared periods of ill-health the most. This fear is significantly higher among people with a higher education level than among people with a lower education level. Concerning everyday life, the importance of health was less visible, because the average of the answers, when applying a 5-point scale to the question How healthily do you live, was 3.49.
The evaluation of someone's own health condition in the researched time frame had improved since earlier; 38.7% of the respondents had considered it Good or Excellent. By the time of the second survey, this figure had increased to 50.2%. The tendency regarding contentment with their own life had also increased: 13.0% of the citizens were explicitly discontent with their lives in 1995, and by 2012 this figure had decreased to 9.4%.
To study the factors endangering health conditions, the respondents were asked to rate how various effects of their everyday lives threaten their health conditions on a scale of 1–5 (scale 1 indicated not at all and scale 5 indicated endangers significantly). Based on the averages of the risks of examined effects (Table 4), worrying about everyday problems was shown as the most health-threatening factor. Among the potential risk factors in connection with individual health behavior, respondents considered their own diet as the most dangerous risk to their health. Special attention has to be paid to the fact that the respondents considered alcohol consumption and smoking to be less harmful to their health than, for example, bad public security, environmental damage or emotional problems or problems in their relationship.
How much do the following impacts influence your health? . | Averages of scales . |
---|---|
Worrying about everyday problems | 3.20 |
Own financial circumstances | 3.07 |
Environmental damages | 3.02 |
Diet | 2.73 |
Bad public security | 2.71 |
Already existing illnesses | 2.66 |
Lack of sports or active exercises | 2.50 |
Unemployment or the possibility of it | 2.16 |
Living conditions | 2.02 |
Workplace conditions | 1.99 |
Emotional problems or problems in your relationship | 1.79 |
Smoking | 1.63 |
Alcohol consumption | 1.50 |
How much do the following impacts influence your health? . | Averages of scales . |
---|---|
Worrying about everyday problems | 3.20 |
Own financial circumstances | 3.07 |
Environmental damages | 3.02 |
Diet | 2.73 |
Bad public security | 2.71 |
Already existing illnesses | 2.66 |
Lack of sports or active exercises | 2.50 |
Unemployment or the possibility of it | 2.16 |
Living conditions | 2.02 |
Workplace conditions | 1.99 |
Emotional problems or problems in your relationship | 1.79 |
Smoking | 1.63 |
Alcohol consumption | 1.50 |
How much do the following impacts influence your health? . | Averages of scales . |
---|---|
Worrying about everyday problems | 3.20 |
Own financial circumstances | 3.07 |
Environmental damages | 3.02 |
Diet | 2.73 |
Bad public security | 2.71 |
Already existing illnesses | 2.66 |
Lack of sports or active exercises | 2.50 |
Unemployment or the possibility of it | 2.16 |
Living conditions | 2.02 |
Workplace conditions | 1.99 |
Emotional problems or problems in your relationship | 1.79 |
Smoking | 1.63 |
Alcohol consumption | 1.50 |
How much do the following impacts influence your health? . | Averages of scales . |
---|---|
Worrying about everyday problems | 3.20 |
Own financial circumstances | 3.07 |
Environmental damages | 3.02 |
Diet | 2.73 |
Bad public security | 2.71 |
Already existing illnesses | 2.66 |
Lack of sports or active exercises | 2.50 |
Unemployment or the possibility of it | 2.16 |
Living conditions | 2.02 |
Workplace conditions | 1.99 |
Emotional problems or problems in your relationship | 1.79 |
Smoking | 1.63 |
Alcohol consumption | 1.50 |
Smoking
According to the most recent data, 11.5% of the adult inhabitants in Pécs are daily smokers, which is a considerable improvement compared with the figure of 1995, which was 32.0%. The decreasing tendency in the number of smokers corresponds with the national average: while in 1995, 39% of the country's adult population smoked regularly (Fact, 1995), by 2013 this number had decreased to 20% (OEFI, 2013). During the study period, the smoking rate had also reduced in other EU countries: while in 1995, 30.35% of the population older than 15 years smoked regularly, in 2009 this number had dropped to 23.92%. Social smokers, who smoke at least once within a 2-week-long period, account for 11.1% of the local adult population. Two-thirds of adults have never smoked (65.4%), and 13.0% have quit smoking. The ratio of habitual smokers among the young generation is significantly lower (10.8%) than among any other age groups (p = 0.046). Most daily smokers in Pécs belong to the age group between 30 and 39 (16.1%, p = 0.024). There is no statistically significant difference in smoking concerning different education levels. Half of the regular smokers of Pécs smoke <10 cigarettes daily. Cigarettes between 11 and 20 are smoked daily by 40.3% of smokers. 9.6% smoke over 20 cigarettes daily. The correspondence analyses showed that social smokers evaluated their own smoking habits as a great health risk, whereas regular smokers considered it to be only a medium risk (p = 0.000).
Alcohol consumption
As regards alcohol consumption of the Hungarian population older than 15 years, in 1994 12.56 l of pure alcohol were consumed per capita per annum, whereas by 2009 this had changed to 11.51 l per capita per annum. Data among the EU countries have also undergone change: in 1994, the population older than 15 years consumed 11.28 l/capita pure alcohols annually. By 2009, this number had reduced to 10.7 l/capita. In Hungary, 4.6% of the adult population is formally heavy drinkers. {According to the classification of the HCSO, heavy drinkers comprise those women and men who consumed 7 or more units of alcohol and 14 or more units of alcohol, respectively, in the week preceding the survey. One unit of alcohol is equivalent to one pint of beer or 200 ml wine or 50 ml liquor [(HCSO, 2010) p. 6]}. Half of women and nearly one-fourth of men stated that they do not drink alcoholic drinks at all. The highest numbers of heavy drinkers are among middle-aged men (11.4%), and the most abstainers (66.9%) are found among elderly women (HCSO, 2010). Currently in Pécs, 4.7% of all adults are considered to be heavy drinkers. Most of them are males between the ages of 40 and 49 (7.4%). On the other hand, 60.5% of the respondents consume alcohol less than weekly or not at all. Most abstainers can be found among the female population between the ages of 50 and 59 (54.2%).
According to the amount and kind of alcohol consumed in Pécs, the ratio of wine consumers has grown considerably (from 40.0 to 60.3% of the adult population); however, weekly wine consumption per capita has decreased (from 2.1 to 1.53 l/capita). The ratio of beer consumers has also increased (from 32.0 to 42.4%), but weekly beer consumption per capita has not really changed (3.2 l/capita). The rate of liquor consumers is 50% less (from 17.0 to 8.7%), whereas the amount consumed weekly has not changed a lot (0.30 l/capita). When asked about the health risks of alcohol consumption, the respondents did not consider their own rate of alcohol consumption to be harmful (p = 0.000). In the case of heavy drinkers, the feeling that their own drinking habits may harm their health does appear, but the scale of harm is ambiguous. Moderate drinkers clearly do not find the amount of alcohol they consume to be harmful to their health.
Daily sleep duration
As regards daily sleep duration, the formerly non-optimal situation has become even less optimal in Pécs. In 1995, 54.0% of the adult citizens of the city slept <8h a day. By 2012, this figure had increased to 61.3%. Regarding the daily sleep duration, the explanatory variables did not show statistically significant differences, and no comparable data were available either in national or in EU contexts.
Sporting activity
Globally, around 31% of adults aged 15 and over were insufficiently active in 2008 (men 28% and women 34%) (WHO, 2014). In comparison, half of the adult population of Hungary (49.7%) does not perform vigorous physical activity at all; one-third (33.4%) does not even perform moderate physical activity and one-fifth (21%) of them do not even walk for at least 10min a day (HCSO, 2010). The picture in Pécs shows nearly the same figures: almost half of all adult citizens (42.3%) do not do regular physical exercise. This has not changed since the former survey. The rate of those who do sporting activities more than once a week increases with higher education level: 29.5% of people with <12 completed grades and 43.2% with >13 completed grades do physical exercises more than once a week (p = 0.029). When observed according to the age group, the correspondence is the other way around: as age advances, the rate of people who do physical exercise weekly decreases. In the age group of 18–29 47.5%, while in the age group over 60, 36.6% of people do physical exercises more than once a week (p = 0.000). The correspondence analyses showed that the lack of sport and active physical exercise were not considered a health risk by those who do sports weekly, while those who do not do sports at all considered their lifestyle as a risk to their health, but they did not believe that it is a serious danger (p = 0.032).
Body mass index
The BMI of the respondents was calculated (BMI categories: <16 = severe underweight; 16.1–18.49 = underweight; 18.5–24.99 = optimal weight; 25.0–29.99 = overweight; 30.0–34.99 = obese; 35.0 ≤ morbid obese) on the basis of the respondents' self-reported height and weight as one of the possible indicators of a healthy lifestyle. [In the case of self-reported data, note that there is a tendency for people to underestimate their weight and overestimate their height (cf. Elgar and Stewart, 2009, Merril and Richardson, 2009).] According to the present situation, less than half of the adult citizens of Pécs (40.6%) have optimal weight, 53.7% are overweight or obese and 4.4% are morbidly obese. According to the results of the National Diet and Nutritional Status Survey of 2009, nearly two-thirds (61.8%) of the Hungarian adult population is overweight or obese. The prevalence of overweight and obesity together is very similar for men (63%) and women (61%). The results of the first Hungarian representative nutrition survey (1985–88) showed that 52% of adult men were overweight and 12% were obese. The level of obese men had more than doubled by 2009, among women a 50% increase was seen (NIFNS, 2010). Based on the latest available data, 52% of the adult population in the EU are overweight or obese (OECD, 2012).
Observing the Pécs situation, the optimal weight is typical in women under 40 with at least 13 completed grades. Overweight is mostly typical in men between 40 and 49 with maximum 12 finished classes. The problem of morbid obesity affects only a small group of people. They are typically men under 50 with maximum 12 finished classes. According to the results of the correspondence analyses, both severely underweight and morbidly obese individuals considered their own eating habits as a serious risk to their health. Underweight and obese respondents believed that their diet was not healthy; however, they did not consider it to be a risk (p = 0.034).
Awareness of health repercussions
Health behavior is obviously influenced by awareness and experience related to the health repercussions of different lifestyles. The health risks of which most citizens of Pécs are aware are smoking, alcohol consumption and hypertension. On the other hand, there is less awareness of risks such as drug consumption and diet. Although the respondents were entirely content with their own awareness and information about this topic, 38.6% of them required a fuller awareness of what contributes to a healthy life style and health promotion. To obtain information on health promotion and a healthy lifestyle, most respondents turn to the Internet (19.6%), a family doctor (14.7%), a magazine or other publication (12.9%), and TV and radio (11.7%).
DISCUSSION
WHO-EHCN has been running in the city of Pécs for over two decades. As a result of taking part in the program, several changes have been made to facilitate health-supporting environment for the city. Parts of these changes have become visible through the implementation of CHP; however, results show a specific dualism: those areas that can be influenced by city health development planning (WHO, 2001; Green et al., 2009) showing improvement (health services and environmental indicators). City health development planning, which has been operating in Pécs since 2002 with the initiation and professional support of HCF, has greatly contributed to this situation. Additionally, pilot projects aiming at the possibilities to integrate the health impact assessment to the local decision-making are being continuously elaborated.
There are, however, such areas, where CHP has been unable to present any positive changes. These areas consist of socio-economic indicators, individual health behavior and lifestyle characteristics, and also related health indicators. Typically negative changes in socio-economic indicators can be traced back to the structural economic difficulties of the city in the first place (Faragó, 2012). These difficulties have been only limitedly offset through interventional local decision-making.
Nevertheless, as regards the areas of individual health behavior and lifestyle characteristics, it is extremely promising that both the ratio of smokers and the amount of cigarettes smoked have decreased, and also that the ratio of regular smokers is the lowest among the youngest age group. While the number of alcohol consumers has increased, at the same time the amount of alcohol drunk has slightly decreased, which shows a reduction in alcohol consumption per capita. Further reinforcement of these changes is a strategic issue, since smoking and drinking alcohol are striking risk factors, especially among men (Mackenbach et al., 2008). Several solutions can be applied for the sake of health prevention on a local level. The results of this survey can significantly contribute to this.
The increasingly negative effects of urban life and environment (Galea and Vlahov, 2005; ICSU, 2011) can be seen in those results that show how people live their everyday lives without being health conscious. Among these results, attention must be raised to the fact that fewer people receive sufficient sleep. Apart from the fact that lack of sleep causes malaise as a result of altered metabolism, the risk of diabetes and obesity increases significantly (Buxton, et al., 2012). These diseases, especially among the urban population, cause increasing problems for national health (McMichael and Butler, 2006).
Obesity and subsequent chronic illnesses are key urban health issues (WHO, 2010). The risk factors of these health problems have increased in Pécs, since almost half of the adult population does not exercise physically on at least a weekly level and, regarding their BMI, their weight is already over average values. Furthermore, the citizens of Pécs are insufficiently educated as regards healthy eating habits.
Problems regarding health consciousness partly arise, because although overweight and obese adults, heavy drinkers and sedentary people are aware of the health risks of their lifestyle, they evaluate them differently. Representing the attitude of ‘unrealistic optimism’ (Weinstein, 1987), they do not find it to be a severe health risk. Consequently, raising health awareness as part of preventative activity by supporting health conscious everyday activities inevitably becomes a responsibility.
Taking everything into consideration, the comparative analysis of the first and present CHP of the city of Pécs showed significant changes concerning both the urban environment and the health behavior of the citizens. We must realize, as a result of the impacts of changes on health characteristics, that aspects of the average life style such as unhealthy diet, insufficient sleep duration and physical inactivity have become increasingly significant health risks. The results of CHP provide information on the basis of which local decision-makers, HCF specialists and other health development professionals can assess these challenges in a structured way, systematically identifying where the problems lie and developing appropriate strategies with which to improve the health of the local population.
The present comprehensive study was adequately supported by the applied data collection technique and methods of analysis. Use of landline calls was a cost-effective solution that could provide access to large samples considerably more quickly than would personal interviews and instant results (compared with mailed surveys). RDD could select reasonably random samples by reaching unlisted numbers and recent connections. Telephone interviews could facilitate ready responses to sensitive questions in contrast with personal interviews and were less likely to lead to socially desirable answers (cf. Choi, 2004). CATI could log interviewer activity, schedule repeat calls, select interviewees randomly, remove numbers from the call queue, produce operational reports and perform automatic dialling. Checks could be in-built, and an immediate warning given if a reply was inconsistent with previous replies. The number of missing values could be reduced to zero and accuracy of data could be enhanced. This is important because 88.9% of households in Pécs have a landline. This landline phone penetration could have caused some bias if a random sample design had been applied, because people from social groups who typically do not have landline telephones would have had a smaller chance of being included in the sample, which would have resulted in the underrepresentation of these groups compared to their actual proportion in the population. This would have meant that their lifestyle attributes under survey would have been exposed less accurately or not at all. We have managed to avoid this potential bias impact, which could have resulted in further biases in the case of every single question under survey, by simultaneously applying the quota sampling design, the two-step random selection and weighting methods. In this way, the published results, taking into account the sample's margin of error, were worded with regard to the full population, which is also confirmed by the proximity to zero of the values used for weighting (0.78–1.43).
The contingency table analysis helped to identify the basic interactions among the categorical variables, whereas the ANOVA test was applied to compare means. The correspondence analysis acted as a support in revealing any relationship that would not be recognized in any pairwise comparisons of variables and to assign order to unordered categories.
Utilization of all these methods, combined with quota sampling, provided us with valid results in harmony with other research results and reinforced the claim that CHP is not an end in itself but an important element in the process of health improvement, thereby moving closer to the reality of ‘a healthy city’ (Webster and Lipp, 2009).
CONCLUSION
One of the conclusions resulting from the implementation of CHP is that, in addition to the areas affected by the city health development plan, it is necessary to focus increased attention upon the continuous follow-up of individual lifestyles for the sake of effective intervention. It was also concluded that the health risks accompanying average lifestyle activities have been on the increase and that this is probably a challenge not only for Pécs but also for other member cities of WHO-EHCN. To combat these challenges, which are among the themes of Phase V (WHO, 2009), we must use all those options available through the support of WHO-EHCN. For the sake of this, it may be worth applying the standardized methods of CHP on performing surveys. It might also be worth comparing the results of health and lifestyle surveys, besides comparing HCI when carrying out the comparative analysis of the CHPs of the WHO-EHCN cities. Following this, it may be worth considering possible joint solutions.