Diet, physical activity (PA) and sedentary behavior are important, yet modifiable, determinants of obesity. Recent research into the clustering of these behaviors suggests that children and adolescents have multiple obesogenic risk factors. This paper reviews studies using empirical, data-driven methodologies, such as cluster analysis (CA) and latent class analysis (LCA), to identify clustering patterns of diet, PA and sedentary behavior among children or adolescents and their associations with socio-demographic indicators, and overweight and obesity. A literature search of electronic databases was undertaken to identify studies which have used data-driven methodologies to investigate the clustering of diet, PA and sedentary behavior among children and adolescents aged 5–18 years old. Eighteen studies (62% of potential studies) were identified that met the inclusion criteria, of which eight examined the clustering of PA and sedentary behavior and eight examined diet, PA and sedentary behavior. Studies were mostly cross-sectional and conducted in older children and adolescents (≥9 years). Findings from the review suggest that obesogenic cluster patterns are complex with a mixed PA/sedentary behavior cluster observed most frequently, but healthy and unhealthy patterning of all three behaviors was also reported. Cluster membership was found to differ according to age, gender and socio-economic status (SES). The tendency for older children/adolescents, particularly females, to comprise clusters defined by low PA was the most robust finding. Findings to support an association between obesogenic cluster patterns and overweight and obesity were inconclusive, with longitudinal research in this area limited. Diet, PA and sedentary behavior cluster together in complex ways that are not well understood. Further research, particularly in younger children, is needed to understand how cluster membership differs according to socio-demographic profile. Longitudinal research is also essential to establish how different cluster patterns track over time and their influence on the development of overweight and obesity.

Traditionally, nutrition research has focused on individual nutrients, and more recently dietary patterns. However, there has been relatively little focus on dietary intake at the level of a ‘meal’. The purpose of the present paper was to review the literature on adults' meal patterns, including how meal patterns have previously been defined and their associations with nutrient intakes and diet quality. For this narrative literature review, a comprehensive search of electronic databases was undertaken to identify studies in adults aged ≥  19 years that have investigated meal patterns and their association with nutrient intakes and/or diet quality. To date, different approaches have been used to define meals with little investigation of how these definitions influence the characterisation of meal patterns. This review identified thirty-four and fourteen studies that have examined associations between adults' meals patterns, nutrient intakes and diet quality, respectively. Most studies defined meals using a participant-identified approach, but varied in the additional criteria used to determine individual meals, snacks and/or eating occasions. Studies also varied in the types of meal patterns, nutrients and diet quality indicators examined. The most consistent finding was an inverse association between skipping breakfast and diet quality. No consistent association was found for other meal patterns, and little research has examined how meal timing is associated with diet quality. In conclusion, an understanding of the influence of different meal definitions on the characterisation of meal patterns will facilitate the interpretation of the existing literature, and may provide guidance on the most appropriate definitions to use.

SummaryDiet, physical activity, sedentary behaviour and sleep are typically examined independently with childhood adiposity; however, their combined influence remains uncertain. This review aims to systematically summarize evidence on the clustering of these behaviours through lifestyle patterns and evaluate associations with adiposity in children aged 5–12 years. Search strategies were run in six databases. Twenty‐eight papers met the inclusion criteria, six of which included all four behaviours. A range of lifestyle patterns were identified (healthy, unhealthy and mixed). Mixed patterns were most frequently reported. Unhealthy patterns comprising low physical activity and high sedentary behaviour were also frequently observed. Mixed patterns comprising healthy diets, low physical activity and high sedentary behaviour were more commonly seen in girls, whereas boys were more physically active, similarly sedentary and had unhealthier diets. Children from lower socio‐economic backgrounds tended to more frequently display unhealthy patterns. Unhealthy lifestyle patterns were more often associated with adiposity risk than healthy and mixed patterns. With few studies including all four behaviours, it is difficult to establish a clear picture of their interplay and associations with adiposity. Nonetheless, reliance on lifestyle patterns is likely more beneficial than individual behaviours in targeting adiposity and improving understanding of how these behaviours influence health.

Different approaches to the definition of EOs affect how eating patterns are characterized, with the neutral definition best predicting variance in total energy intake. Further research that examines how different EO definitions affect associations with health outcomes is needed to develop consensus on a standard EO definition.

Poor diet may represent one pathway through which lower socioeconomic position (SEP) leads to adverse health outcomes. This study examined the associations between SEP and diet quality, its components, energy, and nutrients in a nationally representative sample of Australians. Dietary data from two 24-h recalls collected during the cross-sectional Australian Health Survey 2011-13 (n = 4875; aged ≥ 19 years) were analysed. Diet quality was evaluated using the Dietary Guidelines Index (DGI). SEP was assessed by index of area-level socioeconomic disadvantage, education level, and household income. Linear regression analyses investigated the associations between measures of SEP and dietary intakes. Across all of the SEP indicators, compared with the least disadvantaged group, the most disadvantaged group had 2.5–4.5 units lower DGI. A greater area-level disadvantage was associated with higher carbohydrate and total sugars intake. Lower education was associated with higher trans fat, carbohydrate, and total sugars intake and lower poly-unsaturated fat and fibre intake. Lower income was associated with lower total energy and protein intake and higher carbohydrate and trans fat intake. Lower SEP was generally associated with poorer diet quality and nutrient intakes, highlighting dietary inequities among Australian adults, and a need to develop policy that addresses these inequities.