The association between psychosocial factors and change in lifestyle behaviour following lifestyle advice and information about cardiovascular disease risk

INTRODUCTION: Explaining what cardiovascular disease (CVD) risk means and engaging in shared decision-making regarding risk factor modification is challenging. An electronic CVD risk visualisation tool containing multiple risk communication strategies (Your Heart Forecast) was designed in 2009. AIM: To assess whether this tool facilitated explaining CVD risk to primary care patients. METHODS: Health professionals who accessed a Primary Health Organisation website or who attended educational peer groups over a three-month period were invited to complete questionnaires before and after viewing a four-minute video about the tool. Respondents were asked to make an informed guess of the CVD risk of a 35-year-old patient (actual CVD risk 5%) and rate the following sentence as being true or false: If there were 100 people like Mr Andrews, five would go on to have a cardiac event in the next five years. They also were asked to rank their understanding of CVD risk and confidence in explaining the concept to patients. RESULTS: Fifty health professionals (37 GPs, 12 practice nurses, one other) completed before and after questionnaires. Respondents CVD risk estimates pre-video ranged from <5% to 25% and nine rated the sentence as being false. After the video, all respondents answered these questions correctly. Personal rankings from zero to 10 about understanding CVD risk and confidence in explaining risk reduced in range and shifted towards greater efficacy. Discussion: Whether this tool facilitates discussions of CVD risk with patients and improves patient understanding and lifestyle behaviour needs to be evaluated in a randomised trial. KEYWORDS: Cardiovascular disease; risk communication.

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Cumulative psychosocial factors are associated with cardiovascular disease risk factors and management among African Americans in the Jackson Heart Study

BMC Public Health ◽

10.1186/s12889-020-08573-0 ◽

2020 ◽

Vol 20 (1) ◽

Cited By ~ 1

Author(s):

Mario Sims ◽

Lá Shauntá M. Glover ◽

Samson Y. Gebreab ◽

Tanya M. Spruill

Keyword(s):

Risk Factors ◽

Cardiovascular Disease ◽

African Americans ◽

Psychosocial Factors ◽

Disease Risk ◽

Cardiovascular Disease Risk ◽

Cardiovascular Disease Risk Factors ◽

Jackson Heart Study ◽

Heart Study

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Abstract P241: Psychosocial Profiles and Cardiovascular Disease Risk Factor Control: The Coronary Artery Risk Development in Young Adults (cardia) Study

Circulation ◽

10.1161/circ.141.suppl_1.p241 ◽

2020 ◽

Vol 141 (Suppl_1) ◽

Author(s):

Emily A Vargas ◽

Kiarri N Kershaw ◽

Mercedes R Carnethon ◽

Diana Chirinos ◽

Allison J Carroll ◽

...

Keyword(s):

Cardiovascular Disease ◽

Risk Factor ◽

Chronic Disease ◽

Psychosocial Factors ◽

Disease Risk ◽

Cardiovascular Disease Risk ◽

Cardiovascular Disease Risk Factor ◽

Disease Risk Factor ◽

Composite Control ◽

Psychosocial Profiles

Introduction: Psychosocial factors are associated with the onset of chronic disease, however few studies have examined the association between these factors and cardiovascular disease risk factor (CVDRF) control over time in individuals who already have a chronic disease. Thus, the goal of this study was to evaluate associations of psychosocial factors with a composite measure of CVDRF control. Methods: This study includes 1,018 CARDIA participants (51.6% Black; 41.6% Male) with prevalent hypertension (n = 604), hypercholesterolemia (n = 636), and/or diabetes (n = 210) in 2000-2001 (Year 15 follow-up exam). Latent Profile Analysis (LPA) was used to identify distinct psychosocial profiles based on a combination of personality, social life, and psychological health factors (Table). We used generalized estimating equations to determine associations of the psychosocial profiles with composite control, defined as HbA1c < 7.0%, systolic blood pressure (SBP) < 140 mm Hg, and LDL-cholesterol < 100 mm/dl, all measured in 2005-2016. Results: The LPA revealed an optimal model of three psychosocial profile groups (AIC 87,467.545; entropy = .895) namely “Healthy”, “Depressed Mood” and “Discriminated Against”. There were no significant differences in composite control across the profiles. Looking at HbA1C, SBP, and LDL separately in the unadjusted models, we found participants in the Depressed and Discriminated Against profiles were less likely to meet guidelines for SBP compared to individuals in the Healthy profile. Participants in the Discriminated profile were significantly less likely to meet the guidelines for HbA1C levels compared to the Healthy profile. These associations were attenuated with adjustment for sociodemographic covariates. Conclusions: Psychosocial profiles were associated with CVDRF control in unadjusted models, but not independent of socio-demographic characteristics.

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