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1.
Int J Med Inform ; 125: 13-21, 2019 05.
Article in English | MEDLINE | ID: mdl-30914176

ABSTRACT

BACKGROUND AND OBJECTIVE: The last few years have seen the appearance many mobile applications aimed at improving health, but studies analyzing their effectiveness on cardiovascular risk factors (CVRFs) are few and far between. Our aim was to assess the effect on CVRFs such as hypertension, dyslipidemia, diabetes and global CVR, of adding the use of a smartphone app to an intervention consisting of standard counseling on physical activity and the Mediterranean diet. METHOD: This is a multicenter, randomized and controlled clinical trial. From January 2014 and September 2016, a total of 833 subjects selected by random sampling from six health centers participated. Of these, 415 were assigned to the counseling + app group (IG) and 418 to the counseling only group (CG). The IG additionally received training in the use of a mobile application. The main outcome was the change in CVRFs and estimated CVR at 3 and 12 months in the IG compared to the CG. RESULTS: No significant changes were observed at 3 or 12 months in terms of CVR. Nevertheless, an effect between groups was observed in favor of the CG at 12 months in some CVRFS: SBP, DBP, total cholesterol and triglycerides: 2.02 mmHg (95%CI: 0.43-3.61), 1.21 mmHg (95%CI: 0.20-2.24), 5.24 mg/dl (95%CI: 1.22-9.26) and 7.24 mg/dl (95%CI: 0.53-14.32). CONCLUSION: Adding an intervention with the use of an app for three months to standard counseling on diet and physical activity, does not provide additional benefits for improving CVRFs or the estimated CVR in the long term. TRIAL REGISTRATION NUMBER: ClinicalTrials.gov NCT02016014.


Subject(s)
Cardiovascular Diseases/prevention & control , Mobile Applications , Smartphone , Adult , Counseling , Diet, Mediterranean , Exercise , Female , Humans , Male , Middle Aged , Research Design , Risk Factors
2.
PLoS One ; 10(9): e0136870, 2015.
Article in English | MEDLINE | ID: mdl-26379036

ABSTRACT

OBJECTIVES: The use of brief screening tools to identify inactive patients is essential to improve the efficiency of primary care-based physical activity (PA) programs. However, the current employment of short PA questionnaires within the Spanish primary care pathway is unclear. This study evaluated the validity of the Spanish version of a Brief Physical Activity Assessment Tool (SBPAAT). METHODS: A validation study was carried out within the EVIDENT project. A convenience sample of patients (n = 1,184; age 58.9±13.7 years; 60.5% female) completed the SBPAAT and the 7-day Physical Activity Recall (7DPAR) and, in addition, wore an accelerometer (ActiGraph GT3X) for seven consecutive days. Validity was evaluated by measuring agreement, Kappa correlation coefficients, sensitivity and specificity in achieving current PA recommendations with the 7DPAR. Pearson correlation coefficients with the number of daily minutes engaged in moderate and vigorous intensity PA according to the accelerometer were also assessed. Comparison with accelerometer counts, daily minutes engaged in sedentary, light, moderate, and vigorous intensity PA, total daily kilocalories, and total PA and leisure time expenditure (METs-hour-week) between the sufficiently and insufficiently active groups identified by SBPAAT were reported. RESULTS: The SBPAAT identified 41.3% sufficiently active (n = 489) and 58.7% insufficiently active (n = 695) patients; it showed moderate validity (k = 0.454, 95% CI: 0.402-0.505) and a specificity and sensitivity of 74.3% and 74.6%, respectively. Validity was fair for identifying daily minutes engaged in moderate (r = 0.215, 95% CI:0.156 to 0.272) and vigorous PA (r = 0.282, 95% CI:0.165 to 0.391). Insufficiently active patients according to the SBPAAT significantly reported fewer counts/minute (-22%), fewer minutes/day of moderate (-11.38) and vigorous PA (-2.69), spent fewer total kilocalories/day (-753), and reported a lower energy cost (METs-hour-week) of physical activities globally (-26.82) and during leisure time (-19.62). CONCLUSIONS: The SBPAAT is a valid tool to identify Spanish-speaking patients who are insufficiently active to achieve health benefits.


Subject(s)
Family Practice , Language , Motor Activity , Surveys and Questionnaires , Adult , Aged , Aged, 80 and over , Female , Humans , Male , Middle Aged , Primary Health Care , Reproducibility of Results , Young Adult
3.
Br J Nutr ; 114(6): 943-51, 2015 Sep 28.
Article in English | MEDLINE | ID: mdl-26268844

ABSTRACT

Little is known about the clustering patterns of lifestyle behaviours in adult populations. We explored clusters in multiple lifestyle behaviours including physical activity (PA), smoking, alcohol use and eating habits in a sample of adult population. A cross-sectional and multi-centre study was performed with six participating groups distributed throughout Spain. Participants (n 1327) were part of the Lifestyles and Endothelial Dysfunction (EVIDENT) study and were aged between 20 and 80 years. The lifestyle and cardiovascular risk (CVR) factors were analysed using a clustering method based on the HJ-biplot coordinates to understand the variables underlying these groupings. The following three clusters were identified. Cluster 1: unhealthy, 677 subjects (51%), with a slight majority of men (58.7%), who were more sedentary and smokers with higher consumption of whole-fat dairy products, bigger waist circumference as well as higher TAG levels, systolic blood pressure (SBP) and CVR. Cluster 2: healthy/PA, 265 subjects (20%), including 24.0% of males with high PA. Cluster 3: healthy/diet, including 29% of the participants, with a higher consumption of olive oil, fish, fruits, nuts, vegetables and lower alcohol consumption. Using the unhealthy cluster as a reference, and after adjusting for age and sex, the multiple regression analysis showed that belonging to the healthy/PA cluster was associated with a lower waist circumference, body fat percentage, SBP and CVR. In summary, the three clusters were identified according to lifestyles. The 'unhealthy' cluster had the least favourable clinical parameters, the 'healthy/PA' cluster had good HDL-cholesterol levels and low SBP and the 'healthy/diet' cluster had lower LDL-cholesterol levels and clinical blood pressure.


Subject(s)
Cardiovascular Diseases/prevention & control , Endothelium, Vascular/physiology , Life Style , Motor Activity , Nutrition Policy , Patient Compliance , Adult , Aged , Aged, 80 and over , Alcohol Drinking/adverse effects , Cardiovascular Diseases/epidemiology , Cardiovascular Diseases/etiology , Cardiovascular Diseases/physiopathology , Cluster Analysis , Cross-Sectional Studies , Endothelium, Vascular/physiopathology , Female , Humans , Male , Middle Aged , Overweight/physiopathology , Risk Factors , Sedentary Behavior , Sex Factors , Smoking/adverse effects , Spain/epidemiology , Young Adult
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