Associations between area socioeconomic status, individual mental health, physical activity, diet and change in cardiometabolic risk amongst a cohort of Australian adults: A longitudinal path analysis.

Suzanne J Carroll,Mark Daniel,Michael J Dale,Anne W Taylor,Theophile Niyonsenga,Sakari Suominen

doi:10.1371/journal.pone.0233793

Suzanne J Carroll, Mark Daniel + Show 4 more

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https://doi.org/10.1371/journal.pone.0233793

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Abstract

Presumed pathways from environments to cardiometabolic risk largely implicate health behaviour although mental health may play a role. Few studies assess relationships between these factors. This study estimated associations between area socioeconomic status (SES), mental health, diet, physical activity, and 10-year change in glycosylated haemoglobin (HbA1c), comparing two proposed path structures: 1) mental health and behaviour functioning as parallel mediators between area SES and HbA1c; and 2) a sequential structure where mental health influences behaviour and consequently HbA1c. Three waves (10 years) of population-based biomedical cohort data were spatially linked to census data based on participant residential address. Area SES was expressed at baseline using an established index (SEIFA-IEO). Individual behavioural and mental health information (Wave 2) included diet (fruit and vegetable servings per day), physical activity (meets/does not meet recommendations), and the mental health component score of the 36-item Short Form Health Survey. HbA1c was measured at each wave. Latent variable growth models with a structural equation modelling approach estimated associations within both parallel and sequential path structures. Models were adjusted for age, sex, employment status, marital status, education, and smoking. The sequential path model best fit the data. HbA1c worsened over time. Greater area SES was statistically significantly associated with greater fruit intake, meeting physical activity recommendations, and had a protective effect against increasing HbA1c directly and indirectly through physical activity behaviour. Positive mental health was statistically significantly associated with greater fruit and vegetable intakes and was indirectly protective against increasing HbA1c through physical activity. Greater SES was protective against increasing HbA1c. This relationship was partially mediated by physical activity but not diet. A protective effect of mental health was exerted through physical activity. Public health interventions should ensure individuals residing in low SES areas, and those with poorer mental health are supported in meeting physical activity recommendations.

Highlights

The prevalence of cardiometabolic disease (CMD) such as cardiovascular disease (CVD; i.e., all diseases of the heart and blood vessels including coronary heart disease and stroke) and type 2 diabetes mellitus (T2DM) continues to rise worldwide, presenting a substantial challenge to public health [1, 2]
Estimated latent variables were statistically significant with the estimated slopes indicating that glycosylated haemoglobin (HbA1c) increased over time (β 0.035% points per year [95%CI: 0.029, 0.041], p
Our findings suggest that individual-level factors that relate to mental health may relate to area of residence and explain the apparent association in unadjusted models

Summary

Introduction

The prevalence of cardiometabolic disease (CMD) such as cardiovascular disease (CVD; i.e., all diseases of the heart and blood vessels including coronary heart disease and stroke) and type 2 diabetes mellitus (T2DM) continues to rise worldwide, presenting a substantial challenge to public health [1, 2]. Though there is some suggestion that trajectories of age-standardised CVD prevalence rates have plateaued, even declined in some countries, these rates remain high and may further rise given increases in obesity and T2DM, both key risk factors for CVD [1, 3,4,5]. Various individual-level factors are well-established as linked to CMD and cardiometabolic risk (CMR). These include sociodemographic factors such as older age, male sex, and lower socioeconomic status (SES), education [7, 8], along with behavioural factors including smoking, poor diet and insufficient physical activity [9,10,11,12,13]. Given the established benefits of compliance with physical activity and diet recommendations, these behaviours are often targeted by interventions intending to improve population health

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