Author

Charlotte M. Dieteren, Werner B. F. Brouwer & Job van Exel

Citation

Dieteren, C.M., Brouwer, W.B.F. & van Exel, J. How do combinations of unhealthy behaviors relate to attitudinal factors and subjective health among the adult population in the Netherlands?. BMC Public Health 20, 441 (2020). https://doi.org/10.1186/s12889-020-8429-y


Source
BMC Public Health
Release date
03/04/2020

How do combinations of unhealthy behaviors relate to attitudinal factors and subjective health among the adult population in the Netherlands?

Research article

Abstract

Background

Health behaviours like smoking, nutrition, alcohol consumption and physical activity (SNAP) are often studied separately, while combinations can be particularly harmful. This study aims to contribute to a better understanding of lifestyle choices by studying the prevalence of (combinations of) unhealthy SNAP behaviours in relation to attitudinal factors (time orientation, risk attitude) and subjective health (self-rated health, life expectancy) among the adult Dutch population.

Previous research had found that the clustering of heavy alcohol consumption and smoking was the most frequent combination of SNAP behavior.

Methods

In total 1006 respondents, representative of the Dutch adult population (18–75 years) in terms of sex, age, and education, were drawn from a panel in 2016. They completed an online questionnaire.

For example, respondents were asked to report their weekly alcohol consumption. Heavy alcohol use was defined as consuming six alcoholic drinks or more at least once a week, or when the weekly alcohol consumption exceeded 21 drinks (males) or 14 drinks (females).

Heavy alcohol use and smoking share are both addictive behaviours and are therefore regularly studied in combination. Hence, for this SNAP cluster the researchers provided further characteristics concerning the attitudinal factors and subjective health.

Groups comparisons and logistic regression analyses (crude and adjusted) were applied to analyse (combinations of) SNAP behaviours in relation to time orientation (using the Consideration of Future Consequences scale comprising Immediate (CFC-I) and Future (CFC-F) scales) and risk attitude (Health-Risk Attitude Scale; HRAS-6), as well as subjective health (visual analogue scale and subjective life expectancy).

Results

In the analyses, 989 respondents (51% men, average 52 years, 22% low, 48% middle, and 30% high educated) were included.

About 8% of respondents engaged in four unhealthy SNAP behaviours and 18% in none.

Self-rated health varied from 5.5 to 7.6 in these groups, whilst subjective life expectancy ranged between 73.7 and 85.5 years.

Logistic regression analyses, adjusted for socio-demographic variables, showed that smoking, heavy alcohol use and combining two or more unhealthy SNAP behaviours were significantly associated with CFC-I scores, which increased the odds by 30%, 18% and 19%, respectively.

Only physical inactivity was significantly associated with CFC-F scores, which increased the odds by 20%.

Three out of the four SNAP behaviours were significantly associated with HRAS-6, which increased the odds between 6% and 12%.

An unhealthy diet, heavy alcohol use, and physical inactivity were significantly associated with SRH, which decreased the odds by 11%.

Only smoking was significantly associated with subjective life expectancy, which decreased the odds by 3%.

The most prevalent combination (unhealthy diet and physical inactivity) showed values comparable to the study population averages on all characteristics. The combination smoking and heavy alcohol consumption occurred in only 7.5% of the sample. This group is significantly more focussed on immediate consequences and less on future consequences. They also appear to be relatively more risk seeking and had relatively low values on both SRH and SLE.

Conclusion

The study’s findings suggest that attitudinal factors and subjective health are relevant in the context of understanding unhealthy SNAP behaviours and their clustering. This emphasizes the relevance of a holistic approach to health prevention rather than focusing on a single unhealthy SNAP behaviour.

Discussion

In the current study, unhealthy SNAP behaviours were studied independently and in combination with each other. The prevalence of smoking, unhealthy diet and physical inactivity was comparable to figures for the general Dutch population.

However, the prevalence of heavy alcohol consumption (29%) was considerably higher than reported in official Dutch population statistics (9%).

Half of the study’s population was engaged in two or more unhealthy SNAP behaviours. The most prevalent combination was an unhealthy diet combined with physical inactivity (17%).

Smoking, using alcohol heavily and the lifestyle index were significantly associated with an increased focus on the immediate consequences of behaviour.

On the other hand, the researchers also found that being physically inactive was significantly associated with an increased focus on the future consequences of behaviour. This latter finding is contradictory to what one may expect.

These findings may have implications for public health policy, but need to be confirmed longitudinally.

Significance

The study findings emphasize the relevance of taking a holistic approach to health prevention rather than focusing on a single behaviour only.

The researchers conclude from this study that people who were engaged in none or one unhealthy SNAP behviour differ significantly on attitudinal factors and subjective health from people engaged in multiple unhealthy SNAP behaviours. However, the specific combination of unhealthy SNAP behaviours also seems to matter, as the most prevalent combination (physical inactivity and an unhealthy diet) showed an opposite relationship with time orientation as compared to the lifestyle index.

People who engage in just one unhealthy SNAP behaviour may lack willingness to change because they feel they compensate for this behaviour with other healthy habits.

On the other hand, people engaged in multiple unhealthy SNAP behaviours might be less easily affected by health promotion messages. Policy or specific interventions targeting lifestyle could incorporate the attitudinal factors analysed in this study to increase the probability of reaching the desired target group.