Abstract P378: Association Between Height-to-Waist Ratio and Cardiovascular Disease Risk Factors in US Adolescents

Background: Although height-to-waist (HtW) ratio is strongly linked to cardiovascular disease (CVD) mortality in adults, the association between HtW and CVD risk factors in children and adolescents remain less unexplored. The purpose of this study was to examine the association between HtW and CVD risk factors in US adolescents (N = 9493), aged 12 to 17 years, from the NHANES (1999-2006). Methods: Waist circumference, body weight, height were assessed with standardized protocols for body composition measurement. High blood pressure (BP) was defined as a value at or above the 90 th percentile for age, sex, and height. Elevated fasting glucose level was defined using the American Diabetes Association guideline of 110 mg/dL or higher. Elevated total cholesterol (TC) level was classified as TC greater than 200 mg/dL. The CVD risk (yes/no) was defined as one or more of these 3 conditions (high BP, elevated glucose, high cholesterol levels). Multivariable logistic regression was used to investigate the association between HtW and CVD risk after adjustment for age, sex, race, physical activity, and dietary habits. We also used the area under a receiver operating characteristic (ROC curve) and a nadir point [(shortest distance from the ROC curve to the perfection (sensitivity = 100% and specificity = 100%)] to define the lowest CVD risk for HtW in boys and girls, respectively. Results: HtW was a strong risk factor for CVD risk in both boys and girls (All P<0.001). There was a strong inverse association between HtW and CVD risk in both boys and girls (All P<0.001), respectively. Minima on the receiver operating characteristics curves for CVD risk in boys and girls were 2.17 and 2.03, respectively. The HtW cutoff points of 2.17 (sensitivity = 67%; specificity = 59%; minimum ROC distance = 0.51) and 2.03 (sensitivity = 64%; specificity = 55%; minimum ROC distance = 0.57) in boys and girls were associated with the lowest CVD risk, respectively. Conclusions: Height-to-waist ratio was strong risk factor for CVD in boys and girls.

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Abstract P400: The Association Between Cross-sex Hormone Therapy and Cardiovascular Disease Risk Factors Among Male-to-female Transgender Persons in Chiang Mai, Thailand

Circulation ◽

10.1161/circ.141.suppl_1.p400 ◽

2020 ◽

Vol 141 (Suppl_1) ◽

Author(s):

Rebecca L Molinsky ◽

Kanokwan Kulprachakarn ◽

Sakaewan Ounjaijean ◽

Ryan Demmer ◽

Kittipan Rerkasem

Keyword(s):

Risk Factors ◽

Cardiovascular Disease ◽

Risk Factor ◽

Hormone Therapy ◽

Sex Hormone ◽

Cvd Risk Factors ◽

Cvd Risk ◽

Transgender Persons ◽

The Relationship ◽

Male To Female

Background: Cross-sex hormone therapy (CSHT) is prescribed to transition secondary sexual characteristics among individuals undergoing male-to-female (MtF) transitions (age range 18-41, mean age=24). Limited data exist to inform the cardiovascular disease (CVD) risk factor profile associated with CSHT. We investigated the relationship between CSHT and cardiovascular risk factors in MtF transgender persons and hypothesize that CSHT will be associated with adverse CVD risk factor profiles. Methods: A cross-sectional study was conducted from October 1 st , 2018 to November 30 th , 2018 in 100 MtF transgender people not receiving CSHT vs. 100 receiving CSHT. CSHT use was defined by self-report use of up to 23 medications. Serum testosterone and 17-beta estradiol were assessed to validate CSHT use. Systolic and diastolic blood pressure was measured. Lipid profiles, fasting plasma glucose (FPG), C-reactive protein, cardiac troponin I and pro b-type natriuretic peptide (proBNP) were assessed from fasting blood. Non-invasive arterial examinations included: carotid intima-media thickness (CIMT), ankle-brachial index (ABI), cardio-ankle vascular index (CAVI), and pulse wave velocity (PWV). Multivariable linear regression models, regressed CVD risk factors on CSHT status. Among the subgroup of CSHT users, we assessed the relationship between duration of use and CVD risk factors. Multivariable models included age, gender, education, income, drinking, smoking, exercise, and BMI. Results: Participant mean age was 24±0.38 years and did not differ by CSHT use. Mean±SE values of testosterone were in the CSHT vs. control group were 4.8±0.3 vs. 5.8±0.3 ng/ml, p=0.06 and 17-beta estradiol levels were 45.6±14.9 vs. 34.7±14.8, p=0.7). CIMT was modestly lower among CSHT vs. controls (0.35±0.01 vs. 0.38±0.01, p=0.09). The average duration of CSHT use was 6.65±0.522 years. Among CSHT users, for every 1-year increase in duration of CSHT use total cholesterol decreased by -2.360 ± 1.096, p=0.0341 mg/dL, LDL-cholesterol decreased by -3.076 ± 1.182, p=0.0109 mg/dL, ABI decreased by -0.006 ± 0.002, p=0.0087 while FPG increased by 2.558 ± 0.899 mg/dL, p=0.0055. Conclusion: Among MtF transgender persons, using CSHT was not associated with increased CVD risk factors levels.

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Abstract 14592: Pregnancy Loss and Cardiovascular Disease Risk Factors in Early Adulthood: Preliminary Findings From Add Health

Circulation ◽

10.1161/circ.142.suppl_3.14592 ◽

2020 ◽

Vol 142 (Suppl_3) ◽

Author(s):

Yamnia I Cortes ◽

Shuo Zhang ◽

Diane C Berry ◽

Jon Hussey

Keyword(s):

Risk Factors ◽

Cardiovascular Disease ◽

Risk Factor ◽

Pregnancy Loss ◽

Recurrent Pregnancy Loss ◽

Early Adulthood ◽

Add Health ◽

Cvd Risk Factors ◽

Cvd Risk ◽

Live Births

Introduction: Pregnancy loss, including miscarriage and stillbirth, affect 15-20% of pregnancies in the United States annually. Accumulating evidence suggests that pregnancy loss is associated with greater cardiovascular disease (CVD) burden later in life. However, associations between pregnancy loss and CVD risk factors in early adulthood (age<35 years) have not been assessed. Objective: To examine associations between pregnancy loss and CVD risk factors in early adulthood. Methods: We conducted a secondary data analysis using the public-use data set for Wave IV (2007-2009) of the National Longitudinal Study of Adolescent to Adult Health (Add Health). Our sample consisted of women, ages 24-32 years, with a previous pregnancy who completed biological data collection (n=2,968). Pregnancy loss was assessed as any history of miscarriage or stillbirth; and as none, one, or recurrent (≥2) pregnancy loss. Dependent variables included physical measures and blood specimens: body mass index (BMI), blood pressure, diabetes status, and dyslipidemia. Associations between pregnancy loss and each CVD risk factor were tested using linear (for BMI) and logistic regression adjusting for sociodemographic factors, parity, pre-pregnancy BMI, smoking during pregnancy, and depression. Results: Six hundred and ninety-three women (23%) reported a pregnancy loss, of which 21% reported recurrent pregnancy loss. Women with all live births were more likely to identify as non-Hispanic White (73%) and report a higher annual income. After adjusting for sociodemographics (age, race/ethnicity, education, income), pregnancy loss was associated with a greater BMI (ß=0.90; SE,0.39). In fully-adjusted models, women with recurrent pregnancy loss were more likely to have hypertension (AOR, 2.50; 95%CI, 1.04-5.96) and prediabetes (AOR, 1.93; 95%CI. 1.11-3.37) than women with all live births; the association was non-significant for women with one pregnancy loss. Conclusions: Pregnancy loss is associated with a more adverse CVD risk factor profile in early adulthood. Findings suggest the need for CVD risk assessment in young women with a prior pregnancy loss. Further research is necessary to identify underlying risk factors of pregnancy loss that may predispose women to CVD.

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Reversal Rate of Clustering of Cardiovascular Disease Risk Factors of Metabolic Syndrome in the General Population: The Niigata Preventive Medicine Study

Journal of Obesity ◽

10.1155/2010/623593 ◽

2010 ◽

Vol 2010 ◽

pp. 1-5 ◽

Cited By ~ 3

Author(s):

Shinsuke Okada ◽

Akiko Suzuki ◽

Hiroshi Watanabe ◽

Toru Watanabe ◽

Yoshifusa Aizawa

Keyword(s):

Risk Factors ◽

Cardiovascular Disease ◽

Metabolic Syndrome ◽

Risk Factor ◽

Disease Risk ◽

Fasting Blood Glucose ◽

Reversal Rate ◽

Cvd Risk Factors ◽

Cvd Risk ◽

The Metabolic Syndrome

The reversal rate from clustering of cardiovascular disease (CVD) risk factors—components of the metabolic syndrome (MetS) is not known.Methods and Results. Among 35,534 subjects who received the annual health examinations at the NiigataHealth Foundation (Niigata, Japan), 4,911 subjects had clustering of 3 or more of the following CVD risk factors: (1) body mass index (BMI) ≥25 Kg/m2, (2) blood pressure ≥130 mm Hg in systolic and/or ≥85 mm Hg in diastolic, (3) triglycerides ≥150 mg/dL, (4) high-density lipoprotein cholesterol ≤40 mg/dL in men, ≤50 mg/dL in women, and (5) fasting blood glucose ≥100 mg/dL. After 5 years 1,929 subjects had a reversal of clustering (39.4%). A reversal occurred more often in males. The subjects with a reversal of clustering had milder level of each risk factor and a smaller number of risk factors, while BMI was associated with the least chance of a reversal.Conclusion. We concluded that a reversal of clustering CVD risk factors is possible in 4/10 subjects over a 5-year period by habitual or medical interventions. Gender and each CVD risk factor affected the reversal rate adversely, and BMI was associated with the least chance of a reversal.

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User Engagement With Smartphone Apps and Cardiovascular Disease Risk Factor Outcomes: Systematic Review (Preprint)

10.2196/preprints.18834 ◽

2020 ◽

Author(s):

Erin M Spaulding ◽

Francoise A Marvel ◽

Rebecca J Piasecki ◽

Seth S Martin ◽

Jerilyn K Allen

Keyword(s):

Risk Factors ◽

Systematic Review ◽

Cardiovascular Disease ◽

Risk Factor ◽

Health Behavior Change ◽

User Engagement ◽

Smartphone Apps ◽

Cvd Risk Factors ◽

Cvd Risk ◽

The Relationship

BACKGROUND The use of mobile health (mHealth) interventions, including smartphone apps, for the prevention of cardiovascular disease (CVD) has demonstrated mixed results for obesity, hypercholesterolemia, diabetes, and hypertension management. A major factor attributing to the variation in mHealth study results may be mHealth user engagement. OBJECTIVE This systematic review aims to determine if user engagement with smartphone apps for the prevention and management of CVD is associated with improved CVD health behavior change and risk factor outcomes. METHODS We conducted a comprehensive search of PubMed, CINAHL, and Embase databases from 2007 to 2020. Studies were eligible if they assessed whether user engagement with a smartphone app used by an individual to manage his or her CVD risk factors was associated with the CVD health behavior change or risk factor outcomes. For eligible studies, data were extracted on study and sample characteristics, intervention description, app user engagement measures, and the relationship between app user engagement and the CVD risk factor outcomes. App user engagement was operationalized as general usage (eg, number of log-ins or usage days per week) or self-monitoring within the app (eg, total number of entries made in the app). The quality of the studies was assessed. RESULTS Of the 24 included studies, 17 used a randomized controlled trial design, 4 used a retrospective analysis, and 3 used a single-arm pre- and posttest design. Sample sizes ranged from 55 to 324,649 adults, with 19 studies recruiting participants from a community setting. Most of the studies assessed weight loss interventions, with 6 addressing additional CVD risk factors, including diabetes, sleep, stress, and alcohol consumption. Most of the studies that assessed the relationship between user engagement and reduction in weight (9/13, 69%), BMI (3/4, 75%), body fat percentage (1/2, 50%), waist circumference (2/3, 67%), and hemoglobin A<sub>1c</sub> (3/5, 60%) found statistically significant results, indicating that greater app user engagement was associated with better outcomes. Of 5 studies, 3 (60%) found a statistically significant relationship between higher user engagement and an increase in objectively measured physical activity. The studies assessing the relationship between user engagement and dietary and diabetes self-care behaviors, blood pressure, and lipid panel components did not find statistically significant results. CONCLUSIONS Increased app user engagement for prevention and management of CVD may be associated with improved weight and BMI; however, only a few studies assessed other outcomes, limiting the evidence beyond this. Additional studies are needed to assess user engagement with smartphone apps targeting other important CVD risk factors, including dietary behaviors, hypercholesterolemia, diabetes, and hypertension. Further research is needed to assess mHealth user engagement in both inpatient and outpatient settings to determine the effect of integrating mHealth interventions into the existing clinical workflow and on CVD outcomes.

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Abstract P267: Geographic Patterns of Cardiovascular Disease Risk Factor Prevalence in the Continental US

Circulation ◽

10.1161/circ.133.suppl_1.p267 ◽

2016 ◽

Vol 133 (suppl_1) ◽

Author(s):

Matthew S Loop ◽

George Howard ◽

Gustavo de los Campos ◽

Mohammad Z Al-Hamdan ◽

Monika M Safford ◽

...

Keyword(s):

Risk Factors ◽

Cardiovascular Disease ◽

Risk Factor ◽

Geographic Variation ◽

Smoking Prevalence ◽

Local Population ◽

Community Dwelling ◽

Cvd Risk Factors ◽

Cvd Risk ◽

Risk Factor Prevalence

Objectives: Our understanding of geographic variation in cardiovascular disease (CVD) risk factors is based upon self-reported variables or geographically limited coverage. Our objective was to explore geographic variation in measured hypertension, measured diabetes, measured dyslipidemia, and self-reported current smoking prevalence. Methods: We used baseline data from the REasons for Geographic and Racial Differences in Stroke (REGARDS) cohort, whose community-dwelling participants were recruited nationally between 2003 and 2007. Participants underwent a telephone interview and in-home examination. Hypertension, diabetes, and dyslipidemia were based on physiologic measures or reported medication use. Current cigarette smoking was self-reported. Using participants’ residential latitude and longitude, we tested for clustering of each risk factor using the difference in Ripley’s K functions test and, when we found evidence of clustering, used thin plate regression splines (TPRS) in a logistic regression framework to create age- race-, and sex-adjusted maps of risk factor prevalence. Results: Risk factor status and location data were available for 27,787 of the 30,239 participants (92%). Mean (±SD) age of these participants was 65(±9) years, 41% were black, 55% were women, 59% had hypertension, 22% had diabetes, 54% had dyslipidemia, and 15% were current smokers. We found statistically significant geographic clustering of hypertension, diabetes, and smoking prevalence, but not dyslipidemia. The regions with the highest prevalence varied across risk factors (Figure 1). Conclusions: Louisiana and Mississippi might require the most intense management of CVD risk factors. These maps show variation across and within administrative units, providing an accurate representation of geographic variation in risk factor prevalence. High resolution maps could be put to use by healthcare organizations to justify requests for higher reimbursement rates based upon local population health.

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Association of Oral Health and Cardiovascular Disease Risk Factors “Results from a Community Based Study on 5900 Adult Subjects”

ISRN Cardiology ◽

10.1155/2013/782126 ◽

2013 ◽

Vol 2013 ◽

pp. 1-6 ◽

Cited By ~ 2

Author(s):

Hamid Najafipour ◽

Tayebeh Malek Mohammadi ◽

Foad Rahim ◽

Ali Akbar Haghdoost ◽

Mitra Shadkam ◽

...

Keyword(s):

Risk Factors ◽

Cardiovascular Disease ◽

Risk Factor ◽

Oral Health ◽

Gingival Inflammation ◽

Cvd Risk Factors ◽

Cvd Risk ◽

High Blood Glucose ◽

Study Results ◽

Periodontal Index

Objectives. This study aimed to determine the association between some oral health status as a risk factor for cardiac diseases and other cardiovascular disease (CVD) risk factors in a sample of Iranian population in 2011. Methods. The study recruited 5900 inhabitants who aged 15–75 years old of Kerman city through a population based cluster sampling. Having collected informed consent, participants were interviewed for CVD risk factors. Some oral health indicators such as DMFT, Gingival Inflammation index, and Community Periodontal Index were assessed. The association between oral health indices and CVD risk factors was tested using multivariate regression models. Results. The mean age of participants was 33.5 years, and 45.1% were male. Moderate gingival inflammation was observed in 67.6% of participants. Presence of sub- or supragingival calculus was more common (90%) in participants. Older age (RR from 2.7 to 3.88), cigarette smoking (RR = 1.49), and high blood glucose (RR = 1.41) showed an increased risk for oral diseases after adjustment for different covariates including established CVD risk factors. Conclusion. The study results showed an increase in periodontal diseases in the presence of some CVD risk factors. Therefore there may be a bilateral but independent association for both conditions and common risk factor approach preventive program is highly recommended.

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Association of γ’ Fibrinogen with Risk Factors and Prevalent Cardiovascular Disease in the Framingham Heart Study.

Blood ◽

10.1182/blood.v110.11.131.131 ◽

2007 ◽

Vol 110 (11) ◽

pp. 131-131

Author(s):

Rehana S. Lovely ◽

Joseph F. Massaro ◽

Ralph B. D’Agostino ◽

Emelia J. Benjamin ◽

Steven C. Kazmierczak ◽

...

Keyword(s):

Risk Factors ◽

Cardiovascular Disease ◽

Framingham Heart Study ◽

Odds Ratio ◽

Inverse Association ◽

Cvd Risk Factors ◽

Case Control Studies ◽

Cvd Risk ◽

Heart Study

Abstract Background: γ’ fibrinogen is a newly-emerging cardiovascular disease (CVD) biomarker that has shown significant associations with coronary artery disease in small case/control studies. γ’ fibrinogen is an isoform with an altered γ chain, and constitutes ∼10% of total fibrinogen. Both elevated γ’ and total fibrinogen cause fibrinolytic resistance in vitro. However, data are lacking from community based studies on the association of γ’ fibrinogen with CVD risk factors or with clinical CVD. Methods: γ’ fibrinogen levels were measured using an ELISA assay in 3284 men and women in the Framingham Heart Study Offspring Cohort 7th examination cycle (2002–05). Associations of γ’ fibrinogen were examined using linear regression for continuous CVD risk factors and logistic regression for prevalent CVD and other dichotomous measures. Results: The ELISA CV was 9.3% at mean γ’ fibrinogen levels. Participants (mean age 60 years, 53.4% women) with prevalent CVD (0.297 ± 0.007 mg/ml; mean ± SE) had significantly higher mean concentrations than those without CVD (0.255 ± 0.002 mg/ml). There were significant (all p<0.05) associations between γ’ fibrinogen levels with several cardiovascular risk factors, including age, BMI, systolic blood pressure, diabetes mellitus, cigarette smoking, and total cholesterol, and an inverse association with HDL cholesterol. γ’ fibrinogen was associated with prevalent CVD with an odds ratio of 1.76 (95% CI 1.06–2.92) for the highest compared to the lowest tertile, after adjustment for all of the above risk factors. As expected, since γ’ fibrinogen constitutes a subset of total fibrinogen, γ’ fibrinogen was correlated with total fibrinogen. However, if we included both γ’ and total fibrinogen in further analyses of association with CVD, the odds ratio was 3.08 (95% CI 1.41–6.72) for the combined tertile of both the highest γ’ fibrinogen and highest total fibrinogen, an odds ratio that was substantially higher than that for either marker alone. Conclusions: γ’ fibrinogen is associated with multiple CVD risk factors and with prevalent CVD, accounting for CVD risk factors, over and above total fibrinogen alone. Prospective studies are warranted to examine the ability of γ’ fibrinogen to predict CVD.

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P6362Impact of the 2017 AHA/ACC hypertension guideline on hypertension prevalence and cardiovascular risk factors in a healthy older cohort

European Heart Journal ◽

10.1093/eurheartj/ehz746.0958 ◽

2019 ◽

Vol 40 (Supplement_1) ◽

Author(s):

E K Chowdhury ◽

M R Nelson ◽

M E Ernst ◽

K L Margolis ◽

L J Beilin ◽

...

Keyword(s):

Risk Factors ◽

Cardiovascular Disease ◽

Risk Factor ◽

Cardiovascular Risk ◽

Disease Risk ◽

Cvd Risk Factors ◽

Cvd Risk ◽

Hypertension Prevalence ◽

Hypertension Guideline ◽

Healthy Elderly

Abstract Background The 2017 American Heart Association (AHA)/American College of Cardiology (ACC) hypertension guideline recommends a target blood pressure (BP) of <130/80 mmHg regardless of age, which is lower than previously recommended BP goals. Purpose We aimed to determine how much the updated classification for high BP would increase the overall prevalence of “hypertension” in an otherwise healthy elderly population. Additionally, we explored the cardiovascular disease (CVD) risk factor distribution in those newly classified “hypertensives” to determine whether the increased prevalence of hypertension was accompanied by an increase in other modifiable CVD risk factors. Methods We used baseline data from 19,114 participants (16,703 in Australia and 2,411 in the USA) aged ≥65 years who were enrolled in the ASPirin in Reducing Events in the Elderly (ASPREE) study between 2010 and 2014. Participants were classified as having hypertension using either: (a) pre-2017 thresholds (SBP ≥140 mmHg or mean DBP ≥90 mmHg and/or on anti-hypertensive) or (b) 2017 AHA/ACC guidelines (SBP ≥130 mmHg or DBP ≥80 mmHg and/or on anti-hypertensive). We assessed the presence of cardiovascular disease risk factors such as diabetes, hypercholesterolemia, smoking, obesity, reduced renal function among these hypertensive participants and also estimated their predicted risk over 10 years. Results Based on pre-2017 thresholds, 74% of the participants met the criteria for hypertension. Hypertension prevalence increased to 87% when the more stringent 2017 guideline was applied. 29% of this subset of newly classified hypertensive participants did not have any other identifiable traditional CVD risk factors. Further, a significantly lower 10-year predicted cardiovascular risk (22% versus 26%, p<0.001) among those newly classified hypertensive participants was observed in relation to those having hypertension based on pre-2017 guideline (Figure 1). Figure 1. 10-year predicted CVD risk among hyoertensive and newly classified hypertensive ASPREE participants by presence of CVD risk factor Conclusion As expected, the prevalence of hypertension increased among the healthy elderly when applying the new AHA-2017 guideline; however, the increased prevalence occurs despite lack of an accompanying increase in additional CVD risk factors or predicted 10-year risk. Our findings suggest an individualized approach is needed in evaluating high BP among the healthy elderly. Acknowledgement/Funding National Institute on Aging and the National Cancer Institute at NIH; NHMRC Australia, Monash University, Victorian Cancer Agency (Australia)

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User Engagement With Smartphone Apps and Cardiovascular Disease Risk Factor Outcomes: Systematic Review

JMIR Cardio ◽

10.2196/18834 ◽

2021 ◽

Vol 5 (1) ◽

pp. e18834

Author(s):

Erin M Spaulding ◽

Francoise A Marvel ◽

Rebecca J Piasecki ◽

Seth S Martin ◽

Jerilyn K Allen

Keyword(s):

Risk Factors ◽

Systematic Review ◽

Cardiovascular Disease ◽

Risk Factor ◽

Health Behavior Change ◽

User Engagement ◽

Smartphone Apps ◽

Cvd Risk Factors ◽

Cvd Risk ◽

The Relationship

Background The use of mobile health (mHealth) interventions, including smartphone apps, for the prevention of cardiovascular disease (CVD) has demonstrated mixed results for obesity, hypercholesterolemia, diabetes, and hypertension management. A major factor attributing to the variation in mHealth study results may be mHealth user engagement. Objective This systematic review aims to determine if user engagement with smartphone apps for the prevention and management of CVD is associated with improved CVD health behavior change and risk factor outcomes. Methods We conducted a comprehensive search of PubMed, CINAHL, and Embase databases from 2007 to 2020. Studies were eligible if they assessed whether user engagement with a smartphone app used by an individual to manage his or her CVD risk factors was associated with the CVD health behavior change or risk factor outcomes. For eligible studies, data were extracted on study and sample characteristics, intervention description, app user engagement measures, and the relationship between app user engagement and the CVD risk factor outcomes. App user engagement was operationalized as general usage (eg, number of log-ins or usage days per week) or self-monitoring within the app (eg, total number of entries made in the app). The quality of the studies was assessed. Results Of the 24 included studies, 17 used a randomized controlled trial design, 4 used a retrospective analysis, and 3 used a single-arm pre- and posttest design. Sample sizes ranged from 55 to 324,649 adults, with 19 studies recruiting participants from a community setting. Most of the studies assessed weight loss interventions, with 6 addressing additional CVD risk factors, including diabetes, sleep, stress, and alcohol consumption. Most of the studies that assessed the relationship between user engagement and reduction in weight (9/13, 69%), BMI (3/4, 75%), body fat percentage (1/2, 50%), waist circumference (2/3, 67%), and hemoglobin A1c (3/5, 60%) found statistically significant results, indicating that greater app user engagement was associated with better outcomes. Of 5 studies, 3 (60%) found a statistically significant relationship between higher user engagement and an increase in objectively measured physical activity. The studies assessing the relationship between user engagement and dietary and diabetes self-care behaviors, blood pressure, and lipid panel components did not find statistically significant results. Conclusions Increased app user engagement for prevention and management of CVD may be associated with improved weight and BMI; however, only a few studies assessed other outcomes, limiting the evidence beyond this. Additional studies are needed to assess user engagement with smartphone apps targeting other important CVD risk factors, including dietary behaviors, hypercholesterolemia, diabetes, and hypertension. Further research is needed to assess mHealth user engagement in both inpatient and outpatient settings to determine the effect of integrating mHealth interventions into the existing clinical workflow and on CVD outcomes.

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Cardiovascular disease and preventive care among cancer survivors: A population-based study.

Journal of Clinical Oncology ◽

10.1200/jco.2017.35.15_suppl.10081 ◽

2017 ◽

Vol 35 (15_suppl) ◽

pp. 10081-10081 ◽

Cited By ~ 1

Author(s):

Kevin A. Pearlstein ◽

Ramsankar Basak ◽

Ronald C. Chen

Keyword(s):

Risk Factors ◽

Cardiovascular Disease ◽

Risk Factor ◽

Cancer Survivors ◽

Preventive Care ◽

Multivariable Analysis ◽

Population Based ◽

Current Status ◽

Cvd Risk Factors ◽

Cvd Risk

10081 Background: Cardiovascular disease (CVD) has been identified as a leading cause of mortality among cancer survivors, particularly long-term survivors. However, studies examining the prevalence of CVD risk factors and CVD-specific preventive care among US cancer survivors are lacking. We utilize the National Health Interview Survey (NHIS) data to address this knowledge gap. Methods: NHIS is an annual survey among roughly 88,000 individuals across the US, and its data are representative of US population-based estimates of health status, healthcare behavior, and healthcare utilization. 15,747 individuals surveyed from 2011 to 2015 who reported a history of cancer (except non-melanomatous skin cancer) were included in this study. Prevalence of CVD risk factors and preventive care received were calculated incorporating NHIS sample weights. A multivariable logistic regression model was used to evaluate factors associated with risk factor monitoring. Results: 55% of the cohort was ≥6 years out from cancer diagnosis and 53% were 65 years or older. CVD risk factors were prevalent across the entire cohort (Table). Among survivors < 50 years, 30% were active smokers, and 35% obese. Among survivors ≥65, 40% had known CVD. Among survivors with each risk factor, rates of monitoring and management of each is reported in Table. On multivariable analysis, seeing a generalist was strongly associated with monitoring of blood pressure (OR 18), cholesterol (OR 8), and fasting glucose (OR 3). Conclusions: This study provides the current status of preventive care among US cancer survivors, illustrating that CVD and its risk factors are common. Rates of monitoring of hypertension and hyperlipidemia are high, but there is room for improvement in interventions targeting obesity and smoking cessation. [Table: see text]

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