In a recent study published in BMC Public Health, researchers investigated how health behaviors (HB) and socioeconomic position (SEP) were related to health and wellbeing.
Study: The relative importance of education and health behaviour for health and wellbeing. Image Credit: Pixel-Shot/Shutterstock.com
Background
An individual's SEP has a major effect on health behaviors, with a considerable correlation reported between SEP and HB. The social gradient in health implies that there is an underlying social gradient in health behaviors.
However, since it mediates the interaction, the role of HB in the relationship between health and socioeconomic position is difficult to determine. Further research is required to fully understand the combined effects of health habits and education on health outcomes.
About the study
In the present study, researchers investigated the importance of socioeconomic position and health behavior for well-being and health variations and the extent to which HB contributes to SEP health and well-being gradients.
The study included 14,713 Norwegian individuals between 40 and 63 years old. The team designed a composite indicator for unhealthy behaviors incorporating four lifestyle parameters: alcohol intake, smoking, body mass index (BMI), and physical activity.
Two regression models were used for subjective well-being [SWB, evaluated by the Satisfaction with Life Scale (SWLS)] and health-related quality of life (HRQoL) outcomes [5-level EQ-5D version (EQ-5D-5L) and EQ-visual analogue scale (EQ-VAS)], correcting for childhood financial circumstances (CFCs), age, and gender.
The researchers calculated the contribution of all predictors in the overall explained variance and that of HB to the link between education and health.
They examined the Troms survey participants’ data, including 21,083 individuals, of whom those born prior to 1952 were excluded since they had no exposure to policy innovations that significantly impacted higher education enrolment. Both predictors were divided into four categories.
Education was classified as follows: (i) primary (inclusive of lower secondary level); (ii) secondary (inclusive of vocational studies); (iii) tertiary low (lower than four years of attending university); and (iv) tertiary high (four years or more of university studies).
The composite HB indicator was based on four degrees of unhealthy behavior: super-healthy, semi-healthy, semi-healthy, and unhealthy.
Individuals who followed all four population health recommendations were included in the super-healthy group; they did not smoke or consume more than 14 alcoholic units per week, were physically fit (exercised more than 150 minutes per week), and had normal body mass index values.
The semi-healthy category comprised sub-groups that do not entirely meet the body mass index or physical activity standards. Individuals who are obese and physically inactive (defined as fewer than 60 minutes per week) are also included in the unhealthy category.
A sensitivity analysis was performed using the regression models after excluding 681 individuals who reported extreme or severe issues in one or more of the initial four EQ-5D-5L dimensions (pain and functioning).
In addition, the team assessed the strength of the findings on a limited sample, including ‘non-ill-health’ individuals, assuming that lower HRQoL scores would affect physical activity levels.
Results
The Troms Study participants were well educated, with 50% having a tertiary education. A closer look at semi-unhealthy individuals revealed that most were slightly overweight, moderately active, and consumed alcohol in modest quantities (916 individuals).
Excluding HB, the reference model showed persistent stepwise gradients for education in health-related QoL. On the EQ-5D-5L, the difference was 0.04 for education and 0.06 for the EQ-VAS.
Including HB considerably reduced the schooling impacts, resulting in HB accounting for the lion's share of explained variations in health. When assessed using EQ-5D-5L and EQ-VAS, HB contributed 29% and 40% to the health-education gradient, respectively. The team discovered a significant HB gradient in subjective well-being.
The greater the education within the various health behavior categories, the better the health-related QoL was for EQ-VAS and EQ-5D-5L Unlike the two study outcomes related to health, the team found no evidence of a gradient for education in subjective well-being.
The relationships between health behavior and the three study outcomes were consistently greater than those between education and the study outcomes.
With the exception of the highest level of education, which was favorably significant, there was no comparable education and well-being gradient.
Compared to the entire sample population, HB’s contribution to the gradient for education was smaller using EQ-5D-5L for assessment but comparable in the SWLS-3 and EQ-VAS models.
Conclusions
Based on the study findings, health practices explain greater diversity in health and well-being than educational achievement in a wealthy egalitarian society like Norway.
The findings indicated that the contribution of health behaviors to the HR-QoL gradient related to health and education in Norway was 29% to 40%. Health habits explain twice as much variance as educational achievement in EQ-5D-5L and 70% in the EQ-visual analog scale.
At each level of HB, there was a consistent improvement in subjective well-being. There was a bidirectional association between healthy behavior and life fulfilment but no gradient between education and well-being.
Childhood deprivation has a greater detrimental impact on well-being than health. Educated people with good habits are healthier and happier than less educated individuals with unhealthy lifestyles.
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