Social and regional variations in health status and health behaviours among Swiss young adults

DOI: https://doi.org/10.4414/smw.2013.13901

Introduction

Collecting population data in order to monitor health and health behaviours is necessary for public health. These data help us to identify where and when interventions are needed. We need data that show and compare the distribution of health and its determinants across social strata and regions within each country. A growing body of statistical evidence from many countries demonstrates the “social gradient effect” of social stratification on health [1]. A “social gradient in health” is a continuous effect pattern in which health status or health behaviour worsens when social disadvantage increases. Likewise, higher social status confers continuous health advantage with continually increasing social resources [2–4].

In Switzerland, our ability to produce scientific reports on the social distribution of health, and to track the social gradient effect on health and health behaviours, is limited by a dearth of nationwide population data on morbidity, risk factors and health behaviours. Helpful data sources on the social and regional distribution of mortality exist [5–7]. However, the few data sets that provide information on health status and health behaviours represent subpopulations in a limited fashion (e.g. Swiss Health Survey) and include very few measures of health (e.g. Swiss Household Panel). Population-based data on youth health (the developmental phase from teenage to early adulthood) is even more limited: few studies to date have systematically examined health status and health behaviours among adolescents and young adults [8–10].

Youth is a period of social transition and increased vulnerability [11–13]. Data that show and compare the distribution of young people’s health and its determinants across social strata and regions is especially useful since it helps us to identify necessary interventions during the formative years, a period when many health risk behaviour patterns emerge (e.g. smoking and physical inactivity) [14, 15]. However, a current lack of sufficient data prevents researchers from analysing social and regional distribution patterns in health and health behaviour in younger age groups in Switzerland.

To address the need for more and better data collection, the long-established Swiss conscript studies [16, 17] recently set up “ch-x”, a new long-term project to monitor youth development in Swiss society. One of three major themes in this project is health and sport. This cross-sectional survey, first carried out in 2010/11 and scheduled for two more repetitions, collects data relevant to the health and health behaviours of young Swiss men and women ( http://www.chx.ch ). The ch-x surveys were specifically designed to link data on health status and health behaviours to more detailed information on their social determinants, and therefore include data on regional and social distributions.

The aims of this paper are to describe the methodological basis of the Swiss ch-x study and to report on the social and regional distribution of health and health behaviours among young Swiss men and women. We used logistic regression models to show variations in outcome variables associated with social factors, language region and urban vs. rural areas. We examined the links between health and health behaviours with respondents’ education and financial conditions and we tested for social gradient effects.

Methods

The ch-x first began collecting data in 2010/11. The dataset possesses the following properties. First, the ch-x examines young adults. Second, each survey samples a large number of young Swiss men (some n = 31,000) and a smaller number of young Swiss women (some n = 1,500); the same questionnaire is used for both sexes. Third, the sample covers the three main language regions, urban and rural areas, and all social strata, facilitating analyses of social and regional distributions. Fourth, the data set includes many measures to assess social determinants of health and health behaviours. Fifth, the survey will be repeated in 2014/15 and 2018/19, which will allow researchers to assess long-term stability or changes in health status and health behaviours, and their association with social and regional conditions.

The ch-x sample

Data for the male sample were collected at six national recruiting centres in Switzerland during recruitment for compulsory military service. The target population were Swiss male citizens aged 18 to 25 years (mean 19.7, standard deviation [SD] 1.1). Because local administrative records do not provide detailed information on the numbers of participants in the recruitment, the exact response rate could not be calculated. Reports from field staff showed that refusals were rare. Also, a recent study in two of those recruitment centres using a very similar sampling procedure reported a 95% response rate [18]. For additional information on the sample, we calculated the proportion of the eligible population on the basis of data from the register survey of the Swiss census. Our sample corresponded to 40.2% of the eligible population, which means that about 40% of the young men of that age group in Switzerland filled in the survey. Because recruitment is compulsory for all Swiss men, our sample included also individuals unfit for military service and individuals opting for civil service. Data for the female sample were collected with a mail-out survey to Swiss female citizens aged 18 to 21 years (mean 18.8, SD 0.4). Addresses for the female survey were drawn from official registers of 201 Swiss communities in a two-stage randomisation procedure [19]. Young women responded at a rate of 49.3%. Participation was voluntary and anonymous in both surveys. All variables were based on self-reports. The survey design and translation processes into the three national languages are described elsewhere [20].

The survey provides data on health status and health behaviour measures. Most health behaviour variables were collected using a supplementary questionnaire, administered to one-third of the participants. The other two thirds of participants received a supplementary questionnaire which focused either on their education and vocational career, or on their political and civil engagement. Supplementary questionnaires were delivered alternately in the classrooms for the male sample and alternately within the selected communities for the female sample. With a few exceptions, variables had fewer than 6% missing values (2.1%–5.9% in men and 0.8%–5.5% in women; see table 1). The exceptions were household equivalent income (20.3% in men and 19.6% in women) and parents’ education (9.6% in men and 4.2% in women).

Measurement

Categories, proportions and missing values of variables are given in table 1 below.

Social factors

Current family income was transformed into household equivalent income (square root scale) and categorised as low (below 2,500 CHF), middle (between 2,500 CHF and 5,000 CHF), and high (above 5,000 CHF). Education of respondents was categorised as mandatory, secondary vocational training, and secondary grammar school, or higher. Because young people often have not completed educational training, parents’ education was included and categorised as mandatory, secondary (vocational training or school), and tertiary (university or university of applied sciences). The highest level of education attained by either parent was used in the analyses. The ordinal categories of those three indicators of social inequality allowed us both to present basic distributions of social determinants and to test for the social gradient effect [2, 3].

Regional factors

Regional factors were assessed according to place of residence. We used the official spatial divisions of the Swiss Federal Statistical Office to assign language region (German, French, Italian) and urban/nonurban place of residence.

Health behaviours

Smoking status was categorised as daily smoking versus not smoking or occasional smoking. This decision was based on the public health relevance of daily smoking and on preliminary analyses of our data, which showed that occasional smoking was not associated with most of the social and regional indicators. Alcohol consumption was measured as average consumption of standard units on weekdays and weekends. Standard units were one glass of beer (3 dl), wine (1 dl), or liquor (0.2 dl). In line with published Canadian low-risk drinking guidelines [21], we considered more than 2 units per day for young men and more than one unit per day for young women as a meaningful distinction between low and high risk alcohol consumption. We coded risk drinking as consumption of 15 or more standard units per week for men, and 10 or more standard units per week for women.Physical activity was assessed with a single question about participation in physical activities or sports.

Health status

Self-rated health was measured on a five-point Likert scale [22]. This is a valid and reliable survey question to assess health status [23–25]; however, in the healthy age-group of young adults, scores are expected to skew towards the upper end of the scale (a high proportion of respondents will have maximum scores). In order to detect meaningful variation in health status, answers to this question were categorised as favourable (excellent or very good health) or unfavourable (good, fair or poor health). Overweight was defined as a Body Mass Index (BMI) of 25 or larger. Physical fitness (ability to perform physical tasks in everyday life, such as carrying a heavy bag) was assessed with the FFB-Mot short-form questionnaire [26]. The scores were standardised separately for men and women. As no standard reference data are available for this age group and, again, considering the healthy age-group of young adults we dichotomised the standardised score in low versus high physical fitness. Low physical fitness was defined as falling within the lowest quartile, high physical fitness represented the remaining three quartiles.

Statistical analysis

We conducted all analyses using Stata 12 [27]. Basic distributions (health status, health behaviours, social and regional characteristics) are presented in table 1 below. We calculated Chi² test statistics for gender differences in health status and health behaviour variables. We explored social and regional distribution patterns using logistic regression models yielding odds ratios (ORs) and accompanying confidence-intervals (95% CIs). Results were considered significant when the 95% CIs did not include 1. We estimated bivariate associations between predicting social factors (own and parents’ education, household equivalent income, language region, and rural vs. urban place of residence) and each outcome (daily smoking, risk drinking, physical inactivity, unfavourable self-rated health, overweight, and low physical fitness) for men (see table 2) and women (see table 3), controlling for age.

Results

Table 1 shows the social characteristics and regional distributions of respondents, as well as health status and health behaviour variations by gender. Prevalence of daily smoking was higher in males than in females (30.1% vs 16.9%; Chi²= 38.6, p <0.001). Men reported risk drinking twice as often as women (19.6% vs 9.8%; Chi²= 28.0, p <0.001). Physical inactivity (no participation in sports/physical exercise) was reported by 17.5% of men and by 14.0% of women (Chi²= 3.8, p = 0.05).

Of our health status indicators, reports of overweight were more than twice as high for men than for women (22.4% vs 10.5%; (Chi²= 110.5, p <0.001). Unfavourable self-rated health was slightly more common for female respondents than for males (females 40.1%; males 36.2%; Chi²= 9.0, p <0.05).

Health behaviours and health status in young Swiss men: variations by social and regional characteristics

Health behaviours

Table 2 shows that daily smoking was negatively associated with the respondent’s (OR 4.86, 95% CI 4.13‒5.73) and parents’ (OR 1.55, 95% CI 1.17‒2.05) education, and was more common in the Italian- than the German-language region (OR 1.24, 95% CI 1.05‒1.47). Risk drinking was more common in young men who had only mandatory schooling (OR 1.56, 95% CI 1.28‒1.89) or who attended or completed vocational training (OR 1.67, 95% CI 1.49‒1.88) than in those with more education. Risk drinking was less common in young men whose parents completed only mandatory schooling (OR 0.53, 95% CI 0.34‒0.83), but slightly more common among those whose parents completed upper secondary education (OR 1.13, 95% CI 1.02‒1.26). Men from households with a monthly income of less than 5,000 CHF were less likely to be risk drinkers (OR 0.81, 95% CI 0.68‒0.97; and OR 0.84, 95% CI 0.75‒0.95) than men from wealthier households. Physical inactivity was significantly associated with all social factors (from OR 1.24, 95% CI 1.11‒1.39 to OR 2.09, 95% CI 1.74‒2.51). Physical inactivity was more widespread in the Italian- (OR 2.95, 95% CI 2.47‒3.51) and French- (OR 1.68, 95% CI 1.48‒1.90) language regions, and in urban than rural areas (OR 1.13, 95% CI 1.00‒1.28).

Health status

Self-rated health was significantly associated with all that social factors we considered. Unfavourable health was more common in those from lower educational and income backgrounds (ranging from OR 1.13, 95% CI 1.08‒1.19 to OR 1.62, 95% CI 1.48‒1.77). Young men from the Italian-speaking part had a higher proportion of unfavourable health ratings than those from the German-language region (OR 1.11, 95% CI 1.01‒1.22), whereas those from the French-language region were less likely to have a low health rating than their German counterparts (OR 0.83, 95% CI 0.78‒0.88). Respondents from urban areas had a slight health disadvantage when compared with rural residents (OR 1.10, 95% CI 1.04‒1.16). Bodyweight and physical fitness showed similar patterns of association for the three social determinant variables: respondents with less educational and fewer financial resources were more likely to report overweight and low physical fitness (ranging from OR 1.16, 95% CI 1.06‒1.27 to OR 1.89, 95% CI 1.70‒2.10). Regional differences were evident: overweight was less common in the French- than in the German-language region (OR 0.84, 95% CI 0.78‒0.90). Low physical fitness was more common in the French-language region (OR 1.50, 95% CI 1.34‒1.67) and less common in the Italian-language region (OR 0.62, 95% CI 0.50‒0.77).

Health behaviours and health status in young Swiss women: variations by social and regional characteristics

Table 3 shows that many patterns of associations were similar in men and women. Confidence intervals were wider for women, mostly due to the smaller sample size.

Health behaviours

Where associations were statistically significant, unhealthy habits of smoking, drinking and physical inactivity among young women were associated with fewer educational and fewer financial resources. Largest effect sizes for social determinants were seen for physical inactivity (OR 5.83, 95% CI 1.30‒26.13 for parents’ education) and daily smoking (OR 3.15, 95% CI 1.19‒8.33 for own education).

Health status

All statistically significant associations showed that, for women, less favourable subjective health, overweight and low physical fitness were all associated with fewer educational and fewer financial resources. The strongest effects were found for parents’ education on overweight (OR 6.82, 95% CI 2.89‒16.10), and own education on low physical fitness (OR 2.81, 95% CI 1.18‒6.71). The only statistically significant regional variation was that unfavourable self-rated health was less common among young women from the French-language region than among those from the German-language region (OR 0.75, 95% CI 0.56‒0.99).

Social gradient effects among young Swiss adults

In both our male and female sample, daily smoking and physical inactivity showed a mostly consistent gradient pattern for education (see tables 2 and 3). The probability that a respondent engaged in daily smoking and was physical inactive increased as educational status (own and parents’ education) decreased. Those in the highest educational category (“tertiary”) had the lowest rate of daily smoking and physical inactivity. Similarly, the likelihood of physical inactivity was lower in all respondents as household income decreased (for the latter, only in the female sample was the middle-income category not statistically significant).

For health outcomes among men, the gradient effect was evident for all three social inequality measures, self-rated health, overweight and physical fitness, with two exceptions: physical fitness by own education and overweight by income. In seven of nine tested associations, diminishing educational or financial resources correlated with a decrease in health status. There is also some evidence that women’s risk of health disadvantage continually increased as educational resources decreased. Among females, gradient effects are seen for own education on self-rated health and physical fitness, and for parental education on overweight.

Limitations of the study

Implications for future research

Conclusion

The increased attention given to the unequal distribution of health has spurred calls for improvements in the monitoring of health and its social determinants. The new descriptive data we provide on the social and regional distribution of health status and health behaviours in Swiss youth advances that cause. We also offer new evidence that there is a social gradient effect on health status and health behaviours in young Swiss adults: fewer educational and fewer financial resources are associated with lower health status and an increase in unhealthy behaviours. In Switzerland, as in other countries, social inequality in health status and health behaviours tends to follow a pattern of a continuous health disadvantage associated with lowered levels of material and non-material resources.

Acknowledgements:The study used data from the ‘‘Swiss Federal Surveys of Adolescents (ch-x)’’ collected by the ch-x research consortium ch-x cc. Project management: Institute for the Management and Economics of Education, University of Teacher Education Central Switzerland Zug: Stephan Huber. Research partners: Institute for Education Evaluation, associated institute of the University of Zurich: Urs Moser; Institute of Social and Preventive Medicine, University of Bern: Thomas Abel; and the Department of Sociology, University of Geneva: Sandro Cattacin. We thank Kali Tal for her editorial contributions.

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