The current study identifies discernible patterns of health related behaviours in the Irish population. Using SLÁN 2007 data, six clusters of health-related behaviours were identified: Former Smokers, Temperate, Physically Inactive, Healthy Lifestyle, Multiple Risk Factor, and Mixed Lifestyle. Former Smokers (21%) accounted for the largest percentage of the Irish population while the Healthy Lifestyle accounted for the smallest (9%). Similar to findings in the Dutch population, nearly 20% of the population had three unfavourable health-related behaviours . Healthier clusters (Former Smokers, Temperate and Healthy Lifestyle) reported higher levels of energy vitality, lower levels of psychological distress, better self-rated health and better quality of life. In contrast, those in the Multiple Risk Factor cluster had the lowest levels of energy and vitality and the highest psychological distress. Identification of these discernible patterns is important because of their relationship with mortality, morbidity and longevity [1, 46].
The identification of clusters of health-related patterns in the Irish population is similar to the findings of other countries [7, 8]. Health-related behaviours tend to cluster in specific patterns, which Poortinga (2006) argues might explain some of the various combinations of risk that have been found in other studies . There were a similar number of clusters (n = 6) identified in the Irish population and in other European populations . There is evidence to suggest that the number of clusters may differ based on age group, with van Nieuwehuijzen (2009) finding two clusters for young adults (12-15 years) in the Dutch population and three clusters for older adolescents (16-18 years) and adults (19-40 years).
Consistent with other countries, clustering at both ends of the spectrum was found, with people having all or none of the unhealthy health related behaviours. Individuals were found to have multiple unhealthy behaviours, with those in the Multiple Risk Factor and Physically Inactive clusters having multiple unhealthy behaviours . The coexistence of healthy and unhealthy behaviours in other countries  was also confirmed in this study. A positive relationship was found between physical activity levels and hazardous alcohol consumption and a negative relationship was found between physical activity and propensity to smoke [7, 8, 14].
Contextualising our findings is challenging for a number of reasons, in particular, a lack of available data from other countries . Cross-country comparisons are also difficult because of the use of different health behaviour measures, cut-off points and categorisations [6, 8]. Furthermore, studies which have previously reported clustering have investigated biological risk risks . Identification of clusters of health-related behaviour patterns in national populations have been relatively limited, with the majority of studies to date focusing on specific population subgroups, including those aged 12-40 years  and older people .
To date, research on the association between health-related behaviours and mental self-rated health and quality of life has been limited . This study looked at the clusters in relation to mental health and well-being. As expected, individuals with healthier behaviour patterns  were more likely to report positive mental health and more positive perceptions of their health . This study also found that a higher proportion of individuals who had healthy patterns reported better quality of life than those in an unhealthy cluster. Therefore, it is argued that future intervention strategies to promote healthier health-related behaviour patterns should note the interconnected nature of mental health and behaviour patterns. More research is needed to see if patterns of behaviours and the associated health outcomes change over time.
The results show that there are specific groups of the population who are more likely to adopt an unhealthy health-related behaviour pattern. In contrast to other studies, this study examined different age cohorts in the population. Those in the Healthy Lifestyle group were most likely to be women aged 65 years and over and least likely to be aged 18-29 years while those in the Multiple Risk Factor and Physically Inactive were most likely to be men aged 18-29 years. One fifth of those in the Physically Inactive cluster reported that they were inactive due to an injury/disability/medical condition, while 40% cited a lack of time as the main reason. The most commonly cited reason amongst all of the clusters for being physically inactive was a lack of time. This might explain why those aged 65 years and over were most likely to be in the Former Smokers cluster, with high physical activity levels. In contrast to other studies , clustering of unhealthy behaviours was more pronounced for men than women.
As expected, the lower social classes accounted for a disproportionate share of those in the Physically Inactive cluster. Social classes 1-2 were the least likely of the social classes to fall into this cluster. Social classes 5-6 were the most likely of the social classes to be in the Physically Inactive or Multiple Risk Factor clusters. In contrast, social classes 1-2 were the most likely to be in the Temperate or Health Lifestyle clusters. Consistent with other studies, women were more likely than men to have no risk factors.
The findings of this study must be viewed in light of methodological considerations. First, only 7,350 responses of a potential 9,223 possible responses were eligible for inclusion in this study. Second, the data used in this study is self-reported, so social desirability in responses may be an issue. Third, the design of SLÁN is cross-sectional, which means that the data only provides a snapshot of the patterns of health behaviours amongst the population. It also means that it not possible to establish whether a causal relationship exists between lifestyle patterns and mental health, self-rated health or quality of life.