A cross-sectional study of self-reported general health, lifestyle factors, and disease: the Hordaland Health Study

Background

Patient-reported information has been acknowledged over the past decades as measures to capture subjective perspectives and inform and improve clinical practice. One of these measures is self-reported health (Ahmed et al., 2012). Jylha (2009) has proposed a conceptual model to help identifying the different types of information on which people base their health assessments. In this model, the evaluation of one’s own health encompasses a review of information, such as functional status, diseases, health-related behaviours, and socio-demographic factors. Additionally, the model consists of factors comprising contextual frameworks, such as cultural conventions. As an example of the significance of self-reported health, Idler & Benyamini (1997) reported that it predicted mortality in almost all of the 27 community studies they included in their review, and this connection may be seen as well established. However, the question of how people may understand and interpret the concept of self-reported health is not fully unravelled empirically.

Lifestyle factors are among the behaviours that individuals consider when they report their own general health (Manderbacka, 1998; Jylha, 2009) and previous research found that cigarette smoking and alcohol consumption were related to reduced physical and mental health (Riise, Moen & Nortvedt, 2003). In addition, obesity has been found as a predictor of self-rated health (Prosper, Moczulski & Qureshi, 2009). The experience of general health has also been found to be positively associated with levels of physical activity (Malmberg et al., 2005). One study, including several lifestyle factors, found a negative relationship between unhealthy lifestyle and mental and physical health (Pisinger et al., 2009). Another study (Manderbacka, Lundberg & Martikainen, 1999) examined whether different risk factors contributed to self-reported health, when the effect of various health problems were also included. In this study, the authors examined the relationship between risk factors, such as dietary habits, exercise, smoking, alcohol consumption, and body mass index (BMI), and self-reported health. The authors found that these associations were weakened or not significant at all when they were adjusted for health problems. However, these health problem variables were composed by, on the one hand, subjective phenomena including symptoms and functional problems, which may overlap the concept of self-reported health, and, on the other hand, objective medical diagnoses. Thus, the specific significance of the diseases was not revealed. Therefore, the aim of the present study was to examine associations between various lifestyle factors and self-reported health and the mediating effect of disease. The research question guiding the study was if lifestyle factors (smoking, alcohol consumption, leisure time physical activity, and BMI) worked as risk factors for self-reported general health in an adult Norwegian population, with adjustment for socio-demographic characteristics (gender, marital status, and educational level) and diseases (coronary heart disease, apoplexy, and diabetes).

Methods and Materials

Results

Discussion

In this population study we found that the risk of adverse self-reported health was related to obesity, current smoking, and consumption of 15 or more units of liquor per two weeks. On the other hand, a moderate intake of wine or beer and leisure time physical activity decreased the risk of unfavourable self-reported health.

Self-reported health, as measured by a one-item scale, has previously been well established as a predictor of mortality (Idler & Benyamini, 1997; Dalen et al., 2012) and previous studies also found that self-reported health was a predictor of diabetes (Naess et al., 2005) and lung cancer (Riise et al., 2014). The question of what kind of information each individual bases his or her evaluation on when answering this question, is previously discussed and encompasses a wide range of factors of both individual and contextual character. Among these factors are lifestyle behaviours (Manderbacka, 1998; Jylha, 2009).

Overweight and obesity have a broad spectrum of individual, social, and environmental explanatory factors, and can also be seen as lifestyle-related health problems (World Health Organization, 1998). Furthermore, it is a rising public health and clinical problem (Fruhbeck et al., 2013) and data from the Norwegian population show that the levels of body weight have increased during the recent decades (Midthjell et al., 2013). The prevalence of overweight among children and adolescents is high too (Dupuy et al., 2011). As in the present study, Prosper and colleagues found that high levels of BMI were predictors of adverse self-reported health (Prosper, Moczulski & Qureshi, 2009). Similar findings are reported with health-related quality of life (Soltoft, Hammer & Kragh, 2009). Previous research has also shown that high levels of BMI are associated with cardiovascular risk (Jonsson et al., 2002) and mortality (Flegal et al., 2013).

One of the main changes in health behaviours in the past years has been a decrease in physical activity both at work and at leisure, and the rise in overweight and obesity is often connected to this problem (Anderssen et al., 2008). One recent study found that obese participants had lower overall physical activity compared to normal weight participants (Hansen et al., 2013). Physical activity can also be positively associated with self-reported health, irrespective of an increased BMI (Herman et al., 2012). We found that both light and strenuous physical activity decreased the risk of fair or poor health. A similar finding is reported previously (Tran et al., 2013), and daily walking has been found to be inversely related to mortality among elderly people (Samawi, 2013).

We found that the consumption of 15 or more units of liquor per two weeks increased the odds ratio of fair or poor self-reported health, and this result is in accordance with previous research on binge drinking (Tsai et al., 2010). The results regarding a decreased risk of adverse health for individuals with a moderate intake of wine or beer, are more inconsistent. In examining the association between harmful patterns of alcohol consumption and self-reported health status measured by Euro-QoL Group’s five-dimension questionnaire (EQ5D), Petrie et al. (2008) found that all levels of risky alcohol use, including the low risk level, were associated with lower self-ratings of health. There was, however, a small effect for those with a moderate alcohol intake. On the other hand, previous studies, examining the association between moderate intake of alcohol and diseases, found that a moderate intake of alcohol, including red wine, reduced the risk of cardiovascular, cerebrovascular, and peripheral vascular diseases in populations (Szmitko & Verma, 2005), and one recent study confirmed these results, showing that moderate alcohol consumption was associated with lower risk of stroke in a population of women (Jimenez et al., 2012). Furthermore, our result, showing that smoking was associated with poor health, is supporting previous studies regarding self-reported health (Goldman, Glei & Chang, 2004; Tran et al., 2013) as well as health-related quality of life (Strine et al., 2008). Although the odds ratio was small, it was unexpected that the unadjusted analysis revealed better health in former smokers than in study participants who never smoked. Assocations between smoking cessation and positive affect (Branstrom et al., 2010) or mental health (Taylor et al., 2014) may serve as an explanation. However, Manderbacka, Lundberg & Martikainen (1999) and Kaleta et al. (2006) reported opposite results whereas Ho et al. (2003) found no statistical difference in self-rated health between former and never smokers. None of the studies, including the present, took time since smoking cessation into consideration.

Our finding that the disease variable did not mediate the effect of lifestyle factors on self-reported health differs from the results reported by Manderbacka, Lundberg & Martikainen (1999). However, as mentioned, they included not only medical diagnoses, but also a range of illnesses, functional problems, and symptoms in their operationalisation of health problems, leaving the question of the role of diseases unanswered.

In line with other studies (Eriksson, Unden & Elofsson, 2001; Nielsen et al., 2008), we found that female gender was associated with fair or poor health. The same counted for living alone. Joung et al. (1995) found that married men and women reported better health than unmarried, partly independent of lifestyle factors. Helweg-Larsen, Kjøller & Thoning (2003) found higher mortality in unmarried than married individuals. The positive association between length of education and self-rated health found in the present study was also reported by Mackenbach et al. (2008) and Liu & Hummer (2008).

The study population was aged 40–44 years which may limit the generalisability of our findings. Except for type 1 diabetes (Tao et al., 2010), the incidence of the medical conditions included in the disease variable of our study increases with age (World Health Organization, 2011). The impact of disease on self-rated health may vary between age groups. There was no information about the severity of the diseases we included in the disease variable, which may have influenced the results of our study.

The data collection was performed in 1997–99. Hence, the study provides knowledge from a time when one third of Norwegian adults were daily smokers, compared to the current situation where less than one in five smokes tobacco on a daily basis (Norwegian Institute of Public Health, 2014b), purchase of alcohol was lower (Norwegian Institute of Public Health, 2014a), physical activity levels were higher (Anderssen et al., 2008), and the proportion of individuals with overweight and obesity was at a rise (Midthjell et al., 2013). Changed patterns of lifestyle may affect cultural conventions which, according to Jylha (2009), play a role in subjective assessments of health.

Conclusion

A wide variety of factors are included when individuals are reporting how they evaluate their current health. Our study adds to the body of empirical knowledge, showing associations between unhealthy lifestyle and self-reported health which are not mediated by diseases in adults aged 40–44 years. As a supplement or alternative to health assessments and interpretations done by health professionals, the one-item question may be suitable for health professionals as an instrument to identify how patients or other recipients of health services evaluate their health and an indicator of when lifestyle should be targeted in relatively young individuals with or without disease.