The Effect of Physical Activity and High Body Mass Index on Health-Related Quality of Life in Individuals with Metabolic Syndrome

International Journal of Environmental Research and Public Health Article The Effect of Physical Activity and High Body Mass Index on Health-Related Quality of Life in Individuals with Metabolic Syndrome Alba Marcos-Delgado 1, Tania Fernández-Villa 1,* , Miguel Ángel Martínez-González 2,3,4 , Jordi Salas-Salvadó2,5,6,7 , Dolores Corella 2,8 , Olga Castañer 2,9 , J. Alfredo Martínez 2,10,11 ,Ángel M. Alonso-Gómez 2,12, Julia Wärnberg 2,13 , Jesús Vioque 14,15 , Dora Romaguera 2,16 , JoséLópez-Miranda 2,17, Ramon Estruch 2,18 , Francisco J Tinahones 2,19, JoséLapetra 2,20, J. LLuís Serra-Majem 2,21 , Laura García-Molina 14,22, Josep A. Tur 2,16,23 , JoséAntonio de Paz 1, Xavier Pintó2,24, Miguel Delgado-Rodríguez 25,26, Pilar Matía-Martín27, Josep Vidal 28,29, Clotilde Vázquez 2,30, Lidia Daimiel 31 , Emilio Ros 2,32 , Nancy Babio 2,5,7 , Ignacio M Gimenez-Alba 2,8, Estefanía Toledo 2,3 , María Dolores Zomeño 9, M. A. Zulet 10 , Jessica Vaquero-Luna 12, Jessica Pérez-López 2,13 , Ana Pastor-Morel 33, Aina M Galmes-Panades 2,16 , Antonio García-Rios 2,17, Rosa Casas 2,18 , María Rosa Bernal-López 2,34 , JoséManuel Santos-Lozano 2,20, Nerea Becerra-Tomás2,5,7,8, Carolina Ortega-Azorin 2,8 , Zenaida Vázquez-Ruiz 2,3 , Karla Alejandra Pérez-Vega 9, Itziar Abete 10 , Carolina Sorto-Sánchez 12, Antoni Palau-Galindo 2,5,7, Iñigo Galilea-Zabalza 2, Júlia Muñoz-Martínez 9and Vicente Martín1,14 for the PREDIMED-Plus Investigators † 1Institute of Biomedicine (IBIOMED), University of León, 24071 León, Spain; [email protected] (A.M.-D.); [email protected] (J.A.d.P.); [email protected] (V.M.) 2Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, 28040 Madrid, Spain; [email protected] (M.Á.M.-G.); [email protected] (J.S.-S.); [email protected] (D.C.); [email protected] (O.C.); [email protected] (J.A.M.); [email protected] ( Á .M.A.-G.); [email protected] (J.W.); [email protected] (D.R.); [email protected] (J.L.-M.); restr[email protected] (R.E.); [email protected] (F.J.T.); [email protected] (J.L.); [email protected] (J.L.S.-M.); [email protected] (J.A.T.); [email protected] (X.P.); [email protected] (C.V.); [email protected] (E.R.); [email protected] (N.B.); [email protected] (I.M.G.-A.); [email protected] (E.T.); [email protected] (J.P.-L.); [email protected] (A.M.G.-P.); [email protected] (A.G.-R.); [email protected] (R.C.); r[email protected] (M.R.B.-L.); [email protected] (J.M.S.-L.); [email protected] (N.B.-T.); [email protected] (C.O.-A.); [email protected] (Z.V.-R.); [email protected] (A.P.-G.); [email protected] (I.G.-Z.) 3Department of Preventive Medicine and Public Health, IdiSNA, University of Navarra, 31008 Pamplona, Spain 4Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA 5Departament de Bioquímica i Biotecnologia, Unitat de Nutrició, Universitat Rovira i Virgili, 43201 Reus, Spain 6Nutrition Unit, University Hospital of Sant Joan de Reus, 43204 Reus, Spain 7Institut d’InvestigacióSanitària Pere Virgili (IISPV), 43204 Reus, Spain 8Department of Preventive Medicine, University of Valencia, 46010 Valencia, Spain 9 Unit of Cardiovascular Risk and Nutrition, Institut Hospital del Mar de Investigaciones M é dicas Municipal d’InvestigacióMédica (IMIM), 08003 Barcelona, Spain; [email protected] (M.D.Z.); [email protected] (K.A.P.-V.); [email protected] (J.M.-M.) 10 Department of Nutrition, Food Sciences, and Physiology, Center for Nutrition Research, University of Navarra, 31009 Pamplona, Spain; [email protected] (M.A.Z.); [email protected] (I.A.) 11 Precision Nutrition and Cardiometabolic Health Program, IMDEA Food, CEI UAM +CSIC, 28049 Madrid, Spain 12 Bioaraba Health Research Institute, Cardiovascular, Respiratory and Metabolic Area, Osakidetza Basque Health Service, Araba University Hospital, University of the Basque Country UPV/EHU, 48940 Vitoria-Gasteiz, Spain; [email protected] (J.V.-L.); [email protected] (C.S.-S.) Int. J. Environ. Res. Public Health 2020,17, 3728; doi:10.3390/ijerph17103728 www.mdpi.com/journal/ijerph Int. J. Environ. Res. Public Health 2020,17, 3728 2 of 19 13 Department of Nursing, Institute of Biomedical Research in Malaga (IBIMA), University of Málaga, 29010 Málaga, Spain 14 CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, 28029 Madrid, Spain; [email protected] (J.V.); [email protected] (L.G.-M.) 15 Instituto de Investigación Sanitaria y Biomédica de Alicante, ISABIAL, 03010 Alicante, Spain 16 Health Research Institute of the Balearic Islands (IdISBa), University Hospital Son Espases, 07120 Palma de Mallorca, Spain 17 Department of Internal Medicine, Maimonides Biomedical Research Institute of Cordoba (IMIBIC), Reina Sofia University Hospital, University of Cordoba, 14004 Cordoba, Spain 18 Department of Internal Medicine, Institut d’Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), Hospital Clinic, University of Barcelona, 08036 Barcelona, Spain 19 Virgen de la Victoria Hospital, Department of Endocrinology, Instituto de Investigación Biomédica de Málaga (IBIMA), University of Málaga, 29010 Málaga, Spain 20 Department of Family Medicine, Research Unit, Distrito Sanitario Atención Primaria Sevilla, 29009 Sevilla, Spain 21 Research Institute of Biomedical and Health Sciences (IUIBS), University of Las Palmas de Gran Canaria & Centro Hospitalario Universitario Insular Materno Infantil (CHUIMI), Canarian Health Service, 35016 Las Palmas de Gran Canaria, Spain 22 Department of Preventive Medicine and Public Health, University of Granada, 18010 Granada, Spain 23 Research Group on Community Nutrition & Oxidative Stress, University of Balearic Islands, 07122 Palma de Mallorca, Spain 24 Lipids and Vascular Risk Unit, Internal Medicine, Hospital Universitario de Bellvitge, Hospitalet de Llobregat, 08907 Barcelona, Spain 25 Nutritional Genomics and Epigenomics Group, IMDEA Food, CEI UAM +CSIC, 28049 Madrid, Spain; [email protected] 26 Division of Preventive Medicine, Faculty of Medicine, University of Jaén, 23071 Jaén, Spain 27 Department of Endocrinology and Nutrition, Instituto de Investigación Sanitaria Hospital Clínico San Carlos (IdISSC), 28040 Madrid, Spain; [email protected] 28 CIBER Diabetes y Enfermedades Metabólicas (CIBERDEM), Instituto de Salud Carlos III (ISCIII), 28029 Madrid, Spain; [email protected] 29 Department of Endocrinology, Institut d’Investigacions Biomédiques August Pi Sunyer (IDIBAPS), Hospital Clinic, University of Barcelona, 08036 Barcelona, Spain 30 Department of Endocrinology and Nutrition, Hospital Fundaci ó n Jimenez D í az, Instituto de Investigaciones Biomédicas IISFJD, University Autonoma, 28040 Madrid, Spain 31 Nutritional Control of the Epigenome Group, Precision Nutrition and Obesity Program, IMDEA Food, CEI UAM +CSIC, 28049 Madrid, Spain; [email protected] 32 Lipid Clinic, Department of Endocrinology and Nutrition, Institut d’Investigacions Biom è diques August Pi Sunyer (IDIBAPS), Hospital Clínic, 08036 Barcelona, Spain 33 Centro de Salud Cabo Huertas, 03540 Alicante, Spain; apastormor[email protected] 34 Departament of Internal Medicine, Regional University Hospital of Malaga, Instituto de Investigación Biomédica de Málaga (IBIMA), 29010 Málaga, Spain *Correspondence: [email protected]; Tel.: +34-987-291-000 (ext. 5034) †PREDIMED-Plus study investigators. Received: 12 April 2020; Accepted: 21 May 2020; Published: 25 May 2020   Abstract: The main objective of this study was to examine the relationship between the level of physical activity (PA) and the degree of obesity with health-related quality of life (HRQoL) in individuals with metabolic syndrome (MetS) who participated in the Predimed-Plus study. A total of 6875 subjects between 55 and 75 years of age with MetS were selected and randomized in 23 Spanish centers. Subjects were classified according to categories of body mass index (BMI). PA was measured with the validated Registre Giron í del Cor (REGICOR) questionnaire and subjects were classified according to their PA level (light, moderate, vigorous) and the HRQoL was measured with the validated short-form 36 (SF-36) questionnaire. By using the ANOVA model, we found a positive and statistically significant association between the level of PA and the HRQoL (aggregated physical and mental dimensions Int. J. Environ. Res. Public Health 2020,17, 3728 3 of 19 p<0.001), but a negative association with higher BMI in aggregated physical dimensions p<0.001. Furthermore, women obtained lower scores compared with men, more five points in all fields of SF-36. Therefore, it is essential to promote PA and body weight control from primary care consultations to improve HRQoL, paying special attention to the differences that sex incurs. Keywords: health-related quality of life; physical activity; obesity; body mass index; metabolic syndrome 1. Introduction According to the World Obesity Federation, obesity is a chronic, recurring disease, considered to be the epidemic of the 21st century, due to its increase in recent decades [ 1 ]. More than 1.5 trillion adults worldwide are overweight and 500 million of who suffer from obesity [ 2 , 3 ]. These figures have doubled since 1980 and currently almost three million deaths per year are attributed to excess weight, a trend that indicates overweight and obesity will cause more deaths worldwide than malnutrition [4,5]. Overweight/obesity and excess visceral fat in particular, represent a higher risk of morbidity and mortality [ 6 , 7 ]. It is also associated with diseases like type two diabetes, high blood pressure, dyslipidemia, cardiovascular diseases, sleep apnea [ 7 – 9 ], some types of cancer [ 10 ] and increased social stigma [ 11 ]. In addition to diseases being associated with obesity, a major obstacle to physical activity for adults with obesity, are impairments in movement and walking [ 12 , 13 ]. The epidemiological model of obesity describes diet as the main causative agent of excess weight and scarce physical activity (PA) as the second main driver [ 1 , 14 ]. Fast food, including consumption of ultraproccessed foods, is currently replacing traditional diet and the percentage of people who exercise regularly in their spare time is continuously decreasing and becomes even less frequent with age. In Spain, 12.4% of people between 45%–64% and 5.9% of people 65 years and older [ 15 ] exercise regularly. As such, obesity and lack of PA seem to have a negative effect on health-related quality of life (HRQoL) [16,17]. According to the World Health Organization’s (WHO) definition, we can associate HRQoL with the impact a disease has on our perception of happiness, position in life and on our physical, psychological, social and spiritual well-being [ 18 ]. Evidence suggests that doing 150 to 300 min of moderate PA per week and following the Mediterranean diet provide considerable benefits in maintaining health, healing and in HRQoL [ 17 , 19 – 24 ]. Overweight/obesity are the main determinants of metabolic syndrome (MetS) and there are increasing numbers of studies that use HRQoL in individuals with MetS, since it is considered a strong predictor of disability and long-term mortality [25–27]. Therefore, the main objective of our study is to evaluate whether higher body mass index (BMI) and doing PA are cross-sectionally associated with a better HRQoL in the participants of the multicenter randomized primary prevention trial Predimed-Plus. The final objective is to be able to incorporate strategies that improve the population’s HRQoL, since professionals at the primary care level are in a position to stimulate, reinforce, teach and facilitate healthy habits in patients. 2. Materials and Methods 2.1. Study Design A cross-sectional descriptive analysis was carried out with the participants in the Predimed-Plus study, a multicenter randomized trial, in which a total of 23 Spanish centers participated. The aim was to evaluate the effect of an intensive intervention with a hypocaloric Mediterranean diet associated with physical exercise and behavioral therapy compared to a control group that received a traditional Mediterranean diet for primary prevention of cardiovascular diseases in Spain. The protocol can be found at https://www.predimedplus.com/[28] and the study design was described elsewhere [29,30]. Int. J. Environ. Res. Public Health 2020,17, 3728 4 of 19 2.2. Ethical Considerations This trial was approved by the Institutional Review Boards of all recruitment centers where the study was conducted [ 29 ]. The investigations were carried out following the rules of the Declaration of Helsinki of 1975, revised in 2013. Participants signed a written informed consent. The trial was registered in 2014 at the International Standard Randomized Controlled Trial (ISRCTN89898870). 2.3. Participants The inclusion criteria of the participants in the Predimed-Plus study were men between the ages of 55–75 years and women between 60–75 years, overweight or obese (BMI ≥ 27 and <40 kg/m 2 ), who had at least three criteria of MetS [ 31 ] and did not have cardiovascular disease. A total of 6874 subjects were recruited and randomized. For the current analysis, we excluded 130 who did not answered REGICOR questionnaire for PA and 24 participants who did not have available data for BMI at the time. A total of 6720 participants were included for evaluation in the current study. The data in this analysis were collected before the intervention. 2.4. HRQoL The HRQoL was measured with the Spanish version of the SF-36 questionnaire [ 32 , 33 ], validated for the Spanish population and widely used as an accurate way to measure self-perceived HRQoL. This questionnaire consisted of 36 items that assessed eight dimensions or scales: physical functioning (PF), role—physical (RP), bodily pain (BP), general health (GH), vitality (VT), social functioning (SF), role—emotional (RE) and mental health (MH). These dimensions were grouped into two health components: the physical component summary (PCS) and the mental component summary (MCS). Cronbach’s α was used to measure the reliability of the SF-36 scales and found that the values for the Spanish population aged ≥60 years was higher than the proposed standard of 0.7. Each item received a numerical score that was encoded, summed up and put on a scale from 0 to 100. The higher the score, the better the quality of life in the analyzed field. 2.5. PA and BMI PA was measured with a short version of the REGICOR questionnaire, validated for the Spanish population [ 34 ]. It included the type of PA, how often it was done in the past month (number of days) and the duration of each session, in minutes. The intensity of each PA was measured with metabolic equivalents (METs), according to the Compendium of Physical Activities [ 35 ]. The total energy expenditure was calculated by multiplying the METs assigned to each activity by the number of times done per months, minutes per day and divided by 4 weeks/month (METs. min/week) to classify PA as light, moderate or vigorous. Weight and height were collected the same way in all the centers, by trained personnel following a pre-established protocol. BMI was calculated by dividing the weight (Kg) by the squared height (m 2 ). Lastly, the sample population was categorized into four groups (BMI <30 kg/m 2 , between 30 kg/m 2 and 32.4 kg/m2, between 32.5 kg/m2and 34.9 kg/m2and ≥35 kg/m2). 2.6. Other Covariables The sociodemographic variables were collected with the general questionnaire administered at the first visit were sex, age, level of education (primary, secondary and higher education) and marital status (single, married, divorced/separated and widowed). Other covariates used for adjusted models were measurements for high blood pressure, smoking (non-smoker, smoker, ex-smoker), type 2 diabetes, depression, chronic obstructive pulmonary disease and previous history of cancer. Int. J. Environ. Res. Public Health 2020,17, 3728 5 of 19 2.7. Statistical Analysis Participants were divided in three categories of PA based on the intensity measured with the short version of the REGICOR questionnaire: Light PA (<1200 METs–min/week), moderate (1200–2700 METs–min/week) and vigorous (>2700 METs–min/week). The BMI variable was categorized in four categories: <30 kg/m 2 , between 30 kg/m 2 and 32.4 kg/m 2 , between 32.5 kg/m2and 34.9 kg/m2and ≥35 kg/m2. In the sample description, means and standard deviations for quantitative variables were calculated, as well as the percentages for qualitative variables, consistent with the defined categories for PA and BMI. PA levels were compared with age and BMI with ANOVA test and with type 2 diabetes, depression, blood pressure, history of cancer, history of lung disease, smoking status, marital status and educational level with a χ2test. The mean of each dimension of the SF-36 questionnaire and of the two additional fields in the three PA categories and BMI were compared with ANOVA models. The differences between groups were calculated using linear regression models, stratified by sex. Three adjustment models were done for each scale of the HRQoL questionnaire. The first model was adjusted for age and educational level (primary, secondary and higher education). In the second PA model, BMI (<30 kg/m 2 , between 30 kg/m 2 and 32.4 kg/m 2 , between 32.5 kg/m 2 and 34.9 kg/m 2 and ≥ 35 kg/m 2 ), smoking habit (non-smoker, smoker, ex-smoker) and marital status (single, married, divorced/separated, widowed) were included and, with BMI as a dependent variable, PA (light, moderate and vigorous) was included in the model as an adjustment variable. Lastly, the third model was adjusted for comorbidities that are associated with lower HRQoL, high blood pressure (yes/no), type 2 diabetes (yes/no), depression (yes/no), chronic obstructive pulmonary disease (yes/no) and previous history of cancer (yes/no). Benjamini-Hochberg Procedure (BH) was used as a correction test. Linear trends for the association of PA, BMI and HRQoL dimensions were also calculated. For this, we considered the PA and BMI categories to be a continuous quantitative variable included in the multivariate adjusted models. The data were analyzed using the available, complete PREDIMED-Plus database, dated 25/03/2019. All statistical analyses were done using the StataCorp statistical package. 2015. Stata Statistical Software: Release 15. College Station, TX, USA: StataCorp LP. We considered a two-tailed value of 0.05 to be the threshold for statistical significance. 3. Results The descriptive characteristics of the sample in terms of PA levels and BMI are shown in Tables 1 and 2. A decrease in the prevalence in the pathologies studied was seen with increasing intensity of PA. Conversely, in the BMI categories, the lower the BMI, the lower the prevalence of chronic conditions such as type 2 diabetes, depression, high blood pressure and a history of lung disease. Furthermore, the prevalence of pathologies like depression and a history of cancer were higher in women and a higher percentage of women are smokers and have primary education. Tables S1 and S2 show the adjusted means of the eight dimensions that make up the HRQoL SF-36 questionnaire in the three PA categories. As shown, the higher the level of PA, the higher the average scores in HRQoL and, furthermore, all scores were lower in women than in men (Figures 1and 2). Using the third adjustment model as a reference, we observed statistically significant differences on all scales in women (p<0.001), while in men no differences were found in role—physical (p=0.1686), bodily pain (p=0.4762) and role—emotional (p=0.0756). Within the scales that make up the PCS, we observed a difference of ten points in the means between light activity, (PF 65.14 (95% CI 64.07–66.22) RP 61.73 (95% CI 59.59–63.87)); and vigorous activity (PF 75.27 (95% CI 74.00–76.54) RP 73.37 (95% CI 70.84–75.91)) in the PF and RP scales in women. On the BP and GH scales, the difference is eight points. In men, there is a five-point difference between the levels of PA in the PF and GH scales and a two-point difference in RF and BP scales. Int. J. Environ. Res. Public Health 2020,17, 3728 6 of 19 Table 1. Baseline characteristics of the participants according to baseline PA levels. Light =0–1200 METs–min/weeks; moderate =1200–1800 METs–min/week; vigorous= >2800 METs–min/week. Mean ± SD for age and body mass index (BMI). (%) for type 2 diabetes. depression. blood pressure. history of cancer. history of lung disease. smoking status. marital status and educational level. PA levels were compared with age and BMI with ANOVA test and with diabetes, depression, blood pressure, History of cancer, history of lung disease and smoking status. Marital status and educational level with a χ2test. Significant pvalues in bold. PA Total Men Women Light Moderate Vigorous p-Value Light Moderate Vigorous p-Value Light Moderate Vigorous p-Value METs–min/week 0–1200 1200–2800 >2800 0–1200 1200–2800 >2800 0–1200 1200–2800 >2800 N2217 2206 2297 977 1079 1417 1240 1127 880 Age (y) 64 (5) 65 (5) 65 (5) <0.001 62 (5) 64 (5) 64 (5) <0.001 66 (4) 66 (4) 66(4) 0.356 Body-mass index (kg/m2)33.2 (3.5) 32.4 (3.3) 32.0 (3.1) <0.001 33.0 (3.3) 32.1 (3.1) 31.9 (3.0) <0.001 33.4 (3.6) 33.7 (3.5) 32.2 (3.3) <0.001 Type 2 Diabetes at baseline (%) 29.4 26.1 26.3 0.048 30.6 28.8 28.5 0.579 28.4 23.5 22.7 0.017 Depression at baseline (%) 23.9 20.8 17.7 <0.001 12.4 13.1 10.9 0.248 32.9 28.1 28.5 0.021 Systolic blood pressure ≥140 mmHg (%) 44.4 47.7 48.6 0.013 46.3 51.5 53.3 0.003 43 44.1 41 0.382 Systolic blood pressure ≥90 mmHg (%) 18.5 18.9 19.1 0.865 24.8 23.9 22.2 0.325 13.6 14.1 14.1 0.907 History of cancer (%) 8.5 7.3 5.8 0.002 4 5.9 4.2 0.068 12.1 8.6 8.4 0.004 History of lung disease (%) 5.2 4.1 4.3 0.157 5.7 4.5 4.7 0.415 4.9 3.7 3.5 0.238 Smoking status (%) <0.001 <0.001 0.002 Current smoker 47.4 44.9 39.9 22.6 19.6 23.1 66.9 69 66.9 Former smoker 37.8 43.4 48.9 56.4 63.8 62.5 23.2 24 27.2 Never smoker 14.8 11.7 11.2 21 16.6 14.5 10 7 5.9 Marital status (%) 0.004 0.150 10 0.234 Married 74.7 75.8 78.9 82.8 84.7 86.5 68.3 67.2 66.8 Single 5.4 5 5.1 5.6 4.3 4 5.2 5.6 7 Divorced 9.1 7.6 7.1 8.7 7.6 6.3 9.4 7.5 8.4 Widowed/widower 10.9 11.7 8.8 2.9 3.4 3.3 17.1 19.7 17.8 Educational level (%) 0.939 0.006 0.468 Primary school or less 49.7 48.9 48.4 35.2 37.5 42 61.1 59.8 58.8 Secondary school 28.6 29.1 29.2 33.9 32.3 32 24.4 26.1 24.7 High school or university 21.7 22 22.4 30.9 30.2 26 14.4 14.1 16.6 Int. J. Environ. Res. Public Health 2020,17, 3728 7 of 19 Table 2. Baseline characteristics of the participants according to baseline BMI categories <30 kg/m 2 ; 30–32.4 kg/m 2 ; 32.5–34.9 kg/m 2 ; ≥ 35 kg/m 2 . Mean ± SD for age and METs.min/week. (%) for type 2 diabetes, depression, blood pressure, history of cancer, history of lung disease, smoking status, marital status and educational level. BMI categories were compared with age and METs.min/week with ANOVA test and with diabetes, depression, blood pressure, history of cancer, history of lung disease, smoking status, marital status and educational level with a χ2test. Significant pvalues in bold. BMI Total Men Women kg/m2<30 30–32.4 32.5–34.9 >35 p-Value <30 30–32.4 32.5–34.9 ≥35 p-Value <30 30–32.4 32.5–34.9 ≥35 p-Value N1.747 1.846 1.517 1.610 959 1.032 780 702 788 814 737 908 Age (SD) 65 (5) 65 (5) 65 (5) 65 (5) 0.093 64 (5) 64 (5) 63 (5) 63 (5) 0.003 66 (4) 67 (4) 66 (4) 66 (4) 0.352 PA (Mets-min/week) 2724.6 (2309.4) 2595.1 (2376.1) 2473.1 (2381.4) 2014.7 (2059.5) <0.001 3108.9 (2524.7) 2944.7 (2667.0) 2852.5 (2711.9) 2369.6 (2377.2) <0.001 2256.8 (1916.9) 2151.9 (1854.8) 2071.6 (1893.0) 1740.3 (1727.5) <0.001 Type 2 diabetes at baseline (%) 26.3 26.1 27.5 29.4 0.116 29.7 27.8 29 30.8 0.192 22.1 23.8 25.9 28.4 0.121 Depression at baseline (%) 17.9 19.9 21.6 24 <0.001 10.5 11.8 13.4 12.7 0.306 26.8 30 30.4 32.7 0.068 Systolic blood pressure ≥140 mmHg (%) 42.9 48.2 46 50.8 <0.001 47.3 50.5 51.4 55.1 0.019 37.4 45.3 40.3 47.4 <0.001 Diastolic blood pressure ≥90 mmHg (%) 15.3 19.1 20.4 20.9 <0.001 19.7 23.6 25.5 26.2 0.006 9.9 13.5 15.1 16.7 0.001 History of cancer (%) 7.6 6.7 7.2 7.5 0.736 6 4.3 5.1 3.1 0.048 9.5 9.7 9.4 10.8 0.749 History of lung disease (%) 4.1 3.9 5 5.2 0.155 4.5 3.9 5.5 6.3 0.106 3.7 3.8 4.5 4.4 0.798 Smoking status (%) <0.001 0.120 <0.001 Current smoker 42.6 40.5 44.7 48.8 23 21.5 20.6 22.2 66.4 64.7 70.2 69.3 Former smoker 42.1 46.8 43.4 41.2 57.5 62.8 63.8 60.9 23.4 26.5 21.9 26 Never smoker 15.3 12.7 11.9 10 19.5 15.7 15.7 16.9 10.2 8.9 7.9 4.8 Marital status (%) 0.078 0.113 0.702 Married 77 77.8 77.5 73.6 84.5 85.1 86.7 83 67.7 68.4 67.8 66.3 Single 5 4.9 4.8 5.9 3.2 5 4.3 6 7.1 4.9 5.4 5.8 Divorced 8.7 7.6 7.3 8.1 8.6 7.2 5.9 7.6 8.7 8.1 8.7 8.5 Widowed/widower 9.5 9.7 10.4 12.6 3.7 2.7 3.1 3.4 16.5 18.6 18.1 19.5 Educational level (%) <0.001 0.259 0.003 Primary school or less 44.1 48.3 51.9 52.4 35.7 38.8 41 40.2 54.3 60.4 63.4 61.9 Secondary school 30.2 29.4 27.9 28.3 33 32.8 32.1 32.6 26.8 25.1 23.5 24.9 High school or university 25.8 22.3 20.2 19.3 31.4 28.5 26.9 27.2 18.9 14.5 13.2 13.2 Int. J. Environ. Res. Public Health 2020,17, 3728 8 of 19 Int. J. Environ. Res. Public Health 2020, 17, x FOR PEER REVIEW 11 of 23 Figure 1. Adjusted means (points) for each of the 8 dimensions and aggregated physical/mental dimensions of health‑related quality of life (HRQoL) by baseline categories of PA (metabolic equivalents (METs).min/week). Figure 1. Adjusted means (points) for each of the 8 dimensions and aggregated physical/mental dimensions of health-related quality of life (HRQoL) by baseline categories of PA (metabolic equivalents (METs).min/week). Int. J. Environ. Res. Public Health 2020,17, 3728 9 of 19 Int. J. Environ. Res. Public Health 2020, 17, x FOR PEER REVIEW 12 of 23 Figure 2. Mean differences and confidence intervals in the HRQoL dimensions according to PA categories in the Predimed‑Plus trial. Within the scales that make up the PCS, we observed a difference of ten points in the means between light activity, (PF 65.14 (95% CI 64.07–66.22) RP 61.73 (95% CI 59.59–63.87)); and vigorous activity (PF 75.27 (95% CI 74.00–76.54) RP 73.37 (95% CI 70.84–75.91)) in the PF and RP scales in women. On the BP and GH scales, the difference is eight points. In men, there is a five‑point difference between the levels of PA in the PF and GH scales and a two‑point difference in RF and BP scales. In the MCS component there were significant differences (p < 0.0001) in all scales between the average scores found in terms of the PA category in women and men (the higher the level of physical exercise, the higher the HRQoL scores) except in the RE scale in men (p = 0.092). In women there was a difference of ten points in all fields except MH, where the difference was nine points. The greatest PR BP GH* PF* Aggr. physical* -1 0 1 2 3 4 5 6 7 Beta coefficients Physical dimensions Men VT* SF* RE MH* Aggr. mental* -1 0 1 2 3 4 5 6 7 Beta coefficients Light Moderate Vigorous Light Moderate Vigorous Light Moderate Vigorous Light Moderate Vigorous Light Moderate Vigorous Physical Activity Categories * p value for linear trend <0.05 Mental dimensions Men PR* BP* GH* PF* Aggr. physical* -1 0 1 2 3 4 5 6 7 8 9 10 11 12 Beta coefficients Physical dimensions Women VT* SF* RE* MH* Aggr. mental* -1 0 1 2 3 4 5 6 7 8 9 10 11 12 Beta coefficients Light Moderate Vigorous Light Moderate Vigorous Light Moderate Vigorous Light Moderate Vigorous Light Moderate Vigorous Physical Activity Categories * p value for linear trend <0.05 Mental dimensions Women Figure 2. Mean differences and confidence intervals in the HRQoL dimensions according to PA categories in the Predimed-Plus trial. In the MCS component there were significant differences (p<0.0001) in all scales between the average scores found in terms of the PA category in women and men (the higher the level of physical exercise, the higher the HRQoL scores) except in the RE scale in men (p=0.092). In women there was a difference of ten points in all fields except MH, where the difference was nine points. The greatest difference in men was found in the VT field, where VT was seven points over the PA average, in SF and RE, the difference was three points and in MH there was a difference of four points. Tables S4 and S5 show the average scores obtained in the eight dimensions of the SF-36 questionnaire in relation to the BMI categories. In the PCS component, the higher the BMI, the lower the average score of the dimensions in both sexes. All scores were lower in women than in men (Figures 3and 4). 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