Neighbourhood socioeconomic status and cardiometabolic risk: Mediating roles of domain-specific physical activities and sedentary behaviours

Over 17.9 million people worldwide are estimated to die every year from cardiometabolic diseases (i.e., cardiovascular disease, diabetes mellitus, and chronic renal failure), which accounts for at least 32% of all deaths [46]. The burden of cardiometabolic diseases on society and the healthcare system has been increasing. The proportion of disability-adjusted life-years attributable to cardiometabolic diseases increased from 10.3% in 1990 to 16.9% in 2017 [34].

Cardiometabolic diseases and their risk factors are not evenly distributed [42]. For example, a meta-analysis showed that residents of lower socioeconomic status (SES) neighbourhoods had 45% higher odds of obesity and a 1.1 kg/m2 higher body mass index (BMI) than their higher SES counterparts [21]. Enhancing the health of the entire population by reducing such uneven distributions of disease risk is a public health priority [20].

The socioeconomic gradients in cardiometabolic risk may be partially mediated by physical activity and sedentary behaviour, as they have been previously shown to be socioeconomically patterned [16], [23], and are also related to cardiometabolic risk [18]. Extant studies investigating the contribution of these behaviours to socioeconomic inequalities in cardiometabolic risk have been primarily focused on total physical activity [26]. For instance, a Norwegian study reported that overall level of physical activity was one of the mediators of the association between area-level SES and cardiometabolic risk [41]. A prospective study from the UK also found that total physical activity had a mediating role in socioeconomic inequalities in coronary heart disease risk [15].

Little is known about how domain-specific physical activities and sedentary behaviours may be involved in socioeconomic inequalities in cardiometabolic risk. Socioeconomic gradients of physical activity and sedentary behaviour are likely to vary between activity domains and the settings in which these behaviours take place [12], [24], [29]. For instance, recreational physical activity has been found consistently to be less prevalent in socioeconomically disadvantaged areas than in more-advantaged areas [4], [8]. By contrast, inconsistent findings are reported for the relationship between transport-related physical activity and area-level SES [35], [43]. The associations of area-level SES with sedentary behaviours have also been found to differ by domain: TV viewing has been found to be more common in low SES areas [32], but with no difference between areas for computer use [31]. Furthermore, mixed findings have been reported regarding the relationships between area-level SES and car use [35], [47]. Therefore, using overall measures of physical activity and sedentary behaviour, in which behaviours in different domains are combined, may obscure the true socioeconomic variations in these behaviours and their roles in increasing disease risk.

One study to date has found that recreational and transport-related physical activity mediated the association of neighbourhood typology, which involved area-level SES, with BMI calculated with self-reported height and weight [9]. The study also examined total sitting time but found no evidence of mediation. However, the exposure of that study was not area-level SES but a category created based on SES and an environmental attribute (i.e., residential density). Thus, there is scope for improving the understanding of specific activity-related behavioural pathways that may explain the socioeconomic inequalities in cardiometabolic risk.

We examined the potential mediating roles of domain-specific physical activities and sedentary behaviours in the relationship of area-level SES with objectively measured cardiometabolic risk in Australian adults.

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