Adherence to the Mediterranean Lifestyle and Desired Body Weight Loss in a Mediterranean Adult Population with Overweight: A PREDIMED-Plus Study

nutrients Article Adherence to the Mediterranean Lifestyle and Desired Body Weight Loss in a Mediterranean Adult Population with Overweight: A PREDIMED-Plus Study Cristina Bouzas 1,2,3 , Maria del Mar Bibiloni 1,2,3, Alicia Julibert 1,2,3, Miguel Ruiz-Canela 1,4 , Jordi Salas-Salvadó1,5,6 , Dolores Corella 1,7 , Maria Dolors Zomeño 1,8,9, Dora Romaguera 1,3 , Jesús Vioque 10,11 ,Ángel M. Alonso-Gómez 1,12 , Julia Wärnberg 1,13 , J. Alfredo Martínez 1,14,15, Luís Serra-Majem 1,16 , Ramon Estruch 1,17 , Francisco J. Tinahones 1,18, JoséLapetra 1,19, Xavier Pintó1,20, Antonio García Ríos 1,21, Aurora Bueno-Cavanillas 11,22 , JoséJ. Gaforio 11,23 , Pilar Matía-Martín24, Lidia Daimiel 25 , Vicente Martín-Sánchez 26,27 , Josep Vidal 28, Clotilde Vázquez 1,29, Emilio Ros 1,30 , Cesar Ignacio Fernandez-Lázaro 1,4 , Nerea Becerra-Tomás1,5, Ignacio Manuel Gimenez-Alba 1,7 , Julia Muñoz 1,8, Marga Morey 1,3, Alejandro Oncina-Canovas 10,11, Lucas Tojal-Sierra 2,12, Jéssica Pérez-López 1,13 , Itziar Abete 1,15 , Tamara Casañas-Quintana 1,16, Sara Castro-Barquero 1,17, M. Rosa Bernal-López 1,18 , JoséManuel Santos-Lozano 1,19, Ana Galera 1,20, Escarlata Angullo-Martinez 1,2,3,31, F. Javier Basterra-Gortari 1,4,32, Josep Basora 1,5, Carmen Saiz 1,7, Olga Castañer 1,8 , Marian Martín1,3, Leyre Notario-Barandiarán10,11, María C. Belló-Mora 1,12, Carmen Sayón-Orea 1,4,32, Jesús García-Gavilán1,5, Albert Goday 1,8 and Josep A. Tur 1,2,3,* 1CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029 Madrid, Spain; [email protected] (C.B.); mar[email protected] (M.d.M.B.); [email protected] (A.J.); [email protected] (M.R.-C.); [email protected] (J.S.-S.); [email protected] (D.C.); [email protected] (M.D.Z.); [email protected] (D.R.); [email protected] (Á.M.A.-G.); [email protected] (J.W.); [email protected]g (J.A.M.); [email protected] (L.S.-M.); restr[email protected] (R.E.); [email protected] (F.J.T.); [email protected] (J.L.); [email protected] (X.P.); [email protected] (A.G.R.); [email protected] (C.V.); [email protected] (E.R.); [email protected] (C.I.F.-L.); [email protected] (N.B.-T.); [email protected] (I.M.G.-A.); [email protected] (J.M.); marga.mor[email protected] (M.M.); jessicaper[email protected] (J.P.-L.); [email protected] (I.A.); [email protected] (T.C.-Q.); scastr[email protected] (S.C.-B.); r[email protected] (M.R.B.-L.); [email protected] (J.M.S.-L.); [email protected] (A.G.); [email protected] (E.A.-M.); [email protected] (F.J.B.-G.); [email protected] (J.B.); [email protected] (C.S.); [email protected] (O.C.); [email protected] (M.M.); [email protected] (M.C.B.-M.); [email protected] (C.S.-O.); [email protected] (J.G.-G.); [email protected] (A.G.) 2Research Group on Community Nutrition & Oxidative Stress, University of Balearic Islands, Guillem Colom Bldg, Campus, 07122 Palma de Mallorca, Spain; [email protected] 3Health Research Institute of the Balearic Islands (IdISBa), 07120 Palma de Mallorca, Spain 4Department of Preventive Medicine and Public Health, IdISNA, University of Navarra, 31008 Pamplona, Spain 5Universitat Rovira i Virgili, Department of Biochemistry and Biotechnology, Human Nutrition Unit, 43201 Reus, Spain 6Institut d’InvestigacióSanitària Pere Virgili (IISPV), 43201 Reus, Spain 7Department of Preventive Medicine, University of Valencia, 46100 Valencia, Spain 8 Unit of Cardiovascular Risk and Nutrition, Institut Hospital del Mar de Investigaciones M é dicas Municipal d’InvestigacióMèdica (IMIM), 08003 Barcelona, Spain 9Blanquerna School of Health Sciences, Universitat Ramon Llull, 08022 Barcelona, Spain 10 Unit of Nutritional Epidemiology, Miguel Hernández University, ISABIAL-UMH, 46020 Alicante, Spain; [email protected] (J.V.); [email protected] (A.O.-C.); [email protected] (L.N.-B.) Nutrients 2020,12, 2114; doi:10.3390/nu12072114 www.mdpi.com/journal/nutrients Nutrients 2020,12, 2114 2 of 18 11 CIBER Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III (ISCIII), 28029 Madrid, Spain; [email protected] (A.B.-C.); [email protected] (J.J.G.) 12 Bioaraba Health Research Institute; Osakidetza Basque Health Service, Araba University Hospital, University of the Basque Country UPV/EHU, 48013 Vitoria-Gasteiz, Spain 13 Department of Nursing, School of Health Sciences, University of Málaga-IBIMA, 29071 Málaga, Spain 14 Precision Nutrition Program, IMDEA Food, CEI UAM +CSIC, 28049 Madrid, Spain 15 Department of Nutrition, Food Sciences, and Physiology, Center for Nutrition Research, University of Navarra, 31008 Pamplona, Spain 16 Institute for Biomedical Research, University of Las Palmas de Gran Canaria, 35016 Las Palmas de Gran Canaria, Spain 17 Department of Internal Medicine, IDIBAPS, Hospital Clinic, University of Barcelona, 08036 Barcelona, Spain 18 Virgen de la Victoria Hospital, Department of Endocrinology, Biomedical Research Institute of Málaga (IBIMA), University of Málaga, 29010 Málaga, Spain 19 Department of Family Medicine, Research Unit, Distrito Sanitario Atención Primaria Sevilla, 41013 Sevilla, Spain 20 Lipids and Vascular Risk Unit, Internal Medicine, Hospital Universitario de Bellvitge, Hospitalet de Llobregat, 08907 Barcelona, Spain 21 Lipids and Atherosclerosis Unit, Department of Internal Medicine, Maimonides Biomedical Research Institute of Cordoba (IMIBIC), Reina Sofia University Hospital, University of Cordoba, 14004 Cordoba, Spain 22 Department of Preventive Medicine, University of Granada, 18071 Granada, Spain 23 Department of Health Sciences, Centro de Estudios Avanzados en Olivar y Aceites de Oliva, University of Jaen, 23071 Jaen, Spain 24 Department of Endocrinology and Nutrition, Instituto de Investigación Sanitaria Hospital Clínico San Carlos (IdISSC), 28040 Madrid, Spain; pilar[email protected] 25 Nutritional Genomics and Epigenomics Group, IMDEA Food, CEI UAM +CSIC, 28049 Madrid, Spain; [email protected] 26 CIBER Diabetes y Enfermedades Metabólicas (CIBERDEM), Instituto de Salud Carlos III (ISCIII), 28029 Madrid, Spain; [email protected] 27 Institute of Biomedicine (IBIOMED), University of León, 24071 León, Spain 28 Department of Endocrinology, IDIBAPS, Hospital Clinic, University of Barcelona, 08036 Barcelona, Spain; [email protected] 29 Department of Endocrinology, Fundación Jiménez-Díaz, 28040 Madrid, Spain 30 Lipid Clinic, Department of Endocrinology and Nutrition, Institut d’Investigacions Biom è diques August Pi Sunyer (IDIBAPS), Hospital Clínic, 08036 Barcelona, Spain 31 Escola Graduada Primary Health Care Center, IBSalut, 07002 Palma de Mallorca, Spain 32 Servicio Navarro de Salud, Osasunbidea, 31071 Pamplona, Spain *Correspondence: [email protected]; Tel.: +34-971-1731; Fax: +34-971-173184 Received: 2 June 2020; Accepted: 9 July 2020; Published: 16 July 2020   Abstract: Background. Body weight dissatisfaction is a hindrance to following a healthy lifestyle and it has been associated with weight concerns. Objectives. The aim of this study was to assess the association between the adherence to the Mediterranean lifestyle (diet and exercise) and the desired body weight loss in an adult Mediterranean population with overweight. Methods. Cross-sectional analysis in 6355 participants (3268 men; 3087 women) with metabolic syndrome and BMI (Body mass index) between 27.0 and 40.0 kg/m 2 (55–75 years old) from the PREDIMED-Plus trial. Desired weight loss was the percentage of weight that participants wished to lose. It was categorized into four cut-offs of this percentage (Q1: <10%, n=1495; Q2: 10–15%, n=1804; Q3: <15–20%, n=1470; Q4: ≥ 20%, n=1589). Diet was assessed using a validated food frequency questionnaire and a 17-item Mediterranean diet questionnaire. Physical activity was assessed by the validated Minnesota-REGICOR and the validated Spanish version of the Nurses’ Health Study questionnaire. Results. Participants reporting higher percentages of desired weight loss (Q3 and Q4) were younger, had higher real and perceived BMI and were more likely to have abdominal obesity. Desired weight loss correlated inversely to physical activity (Q1: 2106 MET min/week; Q4: 1585 MET min/week. Nutrients 2020,12, 2114 3 of 18 p<0.001) and adherence to Mediterranean diet (Q1: 8.7; Q4: 8.3. p<0.001). Conclusions. In older Mediterranean individuals with weight excess, desired weight loss was inversely associated with Mediterranean lifestyle adherence. Deeply rooted aspects of the MedDiet remained similar across groups. Longitudinal research is advised to be able to establish causality. Keywords: body image; mediterranean lifestyle; overweight; obesity; older adults; desired weight loss; ideal weight; PREDIMED-Plus 1. Introduction Despite a recent meta-analysis describing that overweight or obesity may decrease mortality risk in elderly populations [1], this could be due to a higher resistance of the overweight people to severe physical stress, as would be the case for inpatients in intensive care units [ 2 ]. On the other hand, sarcopenic obesity increased risk for all-cause mortality [ 3 ]. Ju et al. described that other parameters closely related to obesity, such as metabolic syndrome, increase mortality. However, they do not describe in detail parameters of body composition when they refer to weight excess as a protective factor for mortality [ 1 ]. Moreover, the excess of body weight and body fat is associated with a higher risk of several diseases, which are direct causes of a decrease in quality of life and mortality [ 4 – 8 ]. Hence, body fat should be diminished to adequate levels, in order to avoid such outcomes. Aging comes to relevance especially since prevalence of non-communicable chronic diseases, such as those related to an excess of weight or susceptible of aggravating by weight, increases after 55 years of age [ 9 ]. Previous research established that the Mediterranean diet (MedDiet) is an adequate treatment to avoid cardiovascular harmful effects of excess weight and its comorbidities in population over 55 years old [ 10 ]. Several definitions of MedDiet are available through the literature. Reviews in this regard have found similarities and differences among definitions. Briefly, the MedDiet is a food pattern rich in fruits, vegetables, olive oil, whole grains, legumes, nuts, fish and a preference of white over read meat. Less consistent are the recommendations for fermentable dairy products and red wine in the literature [ 10 – 16 ]. From a holistic point of view, the MedDiet has been considered one of the key elements of the so-called Mediterranean lifestyle, which moreover adds to the diet qualities of eco-friendly and sustainability by the preference for locally produced, traditional and seasonal foods. Further from food itself, it also implies correct hydration, home-made food preparation, sociable eating with family or friends, regular outdoor physical activity, relaxation and rest [14,15]. Rather than the objective weight status, weight perception and ideal weight are more likely to boost weight management actions [ 16 ], as illustrated by Higgins’ regulatory focus theory regarding the relationship between motivations and pursuit of a goal [ 17 ]. Accordingly, overweight perception has been associated with spontaneous weight management, mainly by dieting and/or exercising [ 16 ]. Nowadays, checking for health advice in social media has become very popular [ 18 ]. Searches comprise a wide range, from searching symptoms online with the purpose of self-diagnosis, to self-prescribing a treatment [ 19 ]. There is an increasing tendency to self-prescribe a diet [ 19 ], however, unfortunately not all information available on internet is reliable [ 18 ]. As a consequence, body weight dissatisfaction is a risk factor for engaging in unhealthy lifestyles, and it might be a hindrance to following a healthy lifestyle [ 16 ]. Nonetheless, aging has been associated with lower weight concerns and lower overweight perception. Ignoring and not tackling the excess of fat may have a negative impact on lifestyle and general health, as mentioned above [ 4 , 16 ]. Moreover, aging has been associated with lower discrepancy between current weight and desired weight [ 20 ]. Thus, it is unclear whether aging offers a protective or harmful effect on the influence of ideal weight on healthful lifestyles. The lower concern might protect individuals from unreliable health information, while a decrease in awareness might decrease interest in maintaining a healthy lifestyle. Nutrients 2020,12, 2114 4 of 18 Body image (defined as a person’s perception of their physical self [ 21 ]) has been widely studied in the young population, but it has been scarcely reported on in the aged population [ 16 ]. Body image can be assessed as body image dissatisfaction, by comparing actual and reported desired body weight [ 22 ]. On one hand, reported weight and desired weight are shifting upward, contrary to the percentage of desired weight loss (DWL), which remained more stable through time. [ 23 , 24 ]. As aforementioned, evidence tackling the relationship between desired weight or DWL and dietary pattern in middle aged and aged populations without eating disorders is very limited. It would be interesting to study such associations in adults with overweight. The PREDIMED-Plus study offers a golden opportunity to evaluate relations between body image defined as DWL and Mediterranean lifestyle in adults over 55 years old. Therefore, the aim of this study was to assess the association between the adherence to Mediterranean lifestyle (understood as diet and exercise) and the desired body weight loss in an adult Mediterranean population with an excess of weight. 2. Methods 2.1. Study Design The PREDIMED-Plus trial is an ongoing 6-year multicenter, parallel-group, randomized trial. It is currently being conducted in 23 Spanish recruiting centers (universities, hospitals and research institutes). The PREDIMED-Plus trial was designed to compare the effect of a hypocaloric traditional MedDiet combined with physical activity promotion and behavioral support on cardiovascular disease morbimortality, compared with the usual care advice, consisting exclusively of an energy-unrestricted traditional MedDiet (control group). Further details on the study protocol can be found elsewhere [ 25 ] and at http://predimedplus.com/. The trial was registered in 2014 at the International Standard Randomized Controlled Trial (ISRCT; http://www.isrctn.com/ISRCTN89898870) with number 89898870. This present research is a cross-sectional analysis of baseline data within the frame of the PREDIMED-Plus trial. Because the present research is a cross-sectional analysis of baseline data, no differences were made in the analysis by treatment group allocation. 2.2. Participants, Recruitment and Ethics A total of 9677 people were contacted, of which 6874 participants were eligible for the study, and were included in the trial (Figure 1). Eligible participants were community-dwelling adults (men aged 55–75, women aged 60–75), who were overweight or obese (body mass index (BMI) between 27.0 and 40.0 kg/m 2 ) and meeting at least three criteria for metabolic syndrome according to the updated harmonized definition of the International Diabetes Federation, the American Heart Association and the National Heart, Lung and Blood Institute [ 26 ]. All participants provided written informed consent, and the study protocol and procedures were approved according to the ethical standards of the Declaration of Helsinki by all the participating institutions. 2.3. Dietary Assessment Registered dietitians assessed baseline dietary habits through dietary intake obtained with a semi quantitative 143-item food frequency questionnaire (FFQ) [ 27 ] which has been previously validated in the Spanish population [ 27 – 29 ]. For each item, a regular portion size was established, and consumption frequencies were registered in 9 categories, ranging from “never or almost never” to “ ≥ 6 times/day”. Energy and nutrient intakes were calculated as frequency multiplied by nutrient composition of specified portion size for each food item, using a computer program based on available information in Spanish food composition tables [ 30 , 31 ]. Intake of dietary supplements declared in the FFQ was also considered when assessing the total nutrient intake. Participants reporting extreme total energy intakes (<500 or >3500 kcal/day in women or <800 or >4000 kcal/day in men) were excluded from the analysis [ 32 ]. Because 241 participants reported extreme total energy intakes; therefore, our study sample was reduced to 6633 subjects. Nutrients 2020,12, 2114 5 of 18 Nutrients2020,12,xFORPEERREVIEW5of21  Figure1.Flowchartofparticipants. 2.3.DietaryAssessment Registereddietitiansassessedbaselinedietaryhabitsthroughdietaryintakeobtainedwitha semiquantitative143‐itemfoodfrequencyquestionnaire(FFQ)[27]whichhasbeenpreviously validatedintheSpanishpopulation[27–29].Foreachitem,aregularportionsizewasestablished, andconsumptionfrequencieswereregisteredin9categories,rangingfrom“neveroralmostnever” to“≥6times/day”.Energyandnutrientintakeswerecalculatedasfrequencymultipliedbynutrient compositionofspecifiedportionsizeforeachfooditem,usingacomputerprogrambasedon availableinformationinSpanishfoodcompositiontables[30,31].Intakeofdietarysupplements declaredintheFFQwasalsoconsideredwhenassessingthetotalnutrientintake.Participants reportingextremetotalenergyintakes(<500or>3500kcal/dayinwomenor<800or>4000kcal/day inmen)wereexcludedfromtheanalysis[32].Because241participantsreportedextremetotal energyintakes;therefore,ourstudysamplewasreducedto6633subjects. 2.4.MedDietAdherenceAssessment AdherencetoMediterraneandietarypatternswasassessedbyamodifiedversionofthe previouslyvalidatedquestionnaireusedinthePREDIMEDtrial.Registereddietitiansadministered the17‐itemMedDiet(17‐itemerMedDiet)questionnairemeasuringadherencetoan energy‐restrictedMedDiet[33,34]inwhicheachitemisrelatedtoafoodhabit(seeTable1). Compliancewithfoodhabitsscored1foreveryitem,otherwisescored0.Therefore,the17‐item Figure 1. Flow chart of participants. 2.4. MedDiet Adherence Assessment Adherence to Mediterranean dietary patterns was assessed by a modified version of the previously validated questionnaire used in the PREDIMED trial. Registered dietitians administered the 17-item MedDiet (17-item erMedDiet) questionnaire measuring adherence to an energy-restricted MedDiet [ 33 , 34 ] in which each item is related to a food habit (see Table 1). Compliance with food habits scored 1 for every item, otherwise scored 0. Therefore, the 17-item MedDiet questionnaire ranged between 0 and 17. Tertiles were made to define low, moderate or high adherence, ranging from 0 to 7, 8 to 10, and 11 to 17, respectively, as previously published [34]. Table 1. Description of the 17-item Mediterranean dietary questionnaire. Item Compliance with the Item 1Extra-virgin olive oil for cooking Use only extra-virgin olive oil for cooking, salad dressings, and spreads. 2Vegetables Consume ≥2 portions (200 g) of vegetables per day, at least one of them raw. 3Fruits Consume ≥3 portions of fruit per day (including natural fruit juices). 4Red and processed meat Consume ≤ 1 serving (100–150 g) of red meat, hamburgers, or meat products (ham, sausage, etc.) per week. 5Butter, margarine, cream. Consume less than 1 serving (12 g) of butter or cream per week. 6Sugar sweetened beverages Consume less than one sugary beverage or sugar-sweetened fruit juice per week. 7Legumes Consume ≥3 servings (150 g) of legumes per week. 8Fish and seafood Consume ≥3 servings of fish (100–150 g) or shellfish (200 g) per week. 9Sweets and pastries Consume <3 non-homemade sweets or pastries, such as cakes, cookies, sponge cake, or custard, per week. 10 Nuts Consume ≥3 servings of nuts (including peanuts) per week. 11 Preference white over red meat Consume chicken, turkey or rabbit meat instead of beef, pork, hamburgers or sausages. 12 Sofrito Use sofrito ≥2 times per week (Sofrito: tomato and onion sauce, with garlic and aromatic herbs, simmered in olive oil.). 13 Adding sugar to beverages Replace sugar with non-caloric artificial sweeteners for beverages. 14 White bread Reduce consumption of white bread to >1 serving (75 g)/day. 15 Whole grains Consume whole grain cereals and whole grain pasta ≥5 times per week. 16 Refined cereals Reduce consumption of non-whole grain pasta or rice <3 servings per week. 17 Wine Consume 2–3 glasses (200 mL/glass) of wine per day (men) or 1–2 glasses of wine per day (women). Nutrients 2020,12, 2114 6 of 18 2.5. Desired Weight-Loss (DWL) An eating disorder questionnaire [25] was administered at baseline. The questionnaire aimed to detect comorbid eating disorders according to DSM-IV criteria [ 35 ]. On it perceived weight and height, as well as maximum and minimum weight, were asked. Moreover, reported ideal weight (expressed in Kg) was asked to the participants in the aforementioned questionnaire. Weight and height were measured in duplicate by registered dietitians with calibrated scales (BC 418 MA Body Composition Analyzer/Scale, Tanita, Tokyo, Japan) and a wall-mounted stadiometer (Seca 213, HealthCheck Systems, Brooklyn, NY, USA), respectively. BMI was calculated as weight in kilograms divided by the square of height in meters. A total of 206 participants who did not report a subjective ideal weight were excluded from the analysis; therefore, the sample was reduced to 6427. Actual BMI was obtained with measured weight and height, while perceived BMI was calculated with reported (perceived) weight and height. The literature has described that desired weight and reported weight are shifting upward. Nevertheless, when desired weight was examined as the percentage of body weight, such tendencies were not found [ 23 , 24 ]. Therefore a new variable was computed by subtracting subjective ideal weight from measured weight at baseline. Outliers (defined as 3 or more standard deviations (SD) from both sides of the mean) of that variable were excluded from the analysis. 60 outliers were found, therefore the sample size reduced from 6427 to 6367. If the former variable ranged between 2 and − 2 kg, authors considered that subjective ideal and objective measured weight were similar [ 36 , 37 ]. Only 12 subjects reported higher desired than current weight. Since all participants were obese or overweight (BMI between 27.0 and 40.0), those twelve subjects were also excluded from the analysis. Therefore, the final sample included 6355 subjects, 3268 men and 3087 women. The desired weight-loss at baseline (DWL) was the weight that each participant would need to lose to reach their subjective ideal weight. In the present study, DWL was expressed as a percentage (percentage of weight that they wish to lose). DWL was obtained through the following equation: DWL(% desired weight loss)=(baseline weight −ideal weight) baseline weight ×100 (1) Subjects were initially categorized into quartiles of the absolute value of DWL for analysis. Due to the closeness of the cutting-percentiles (p75: 20.00%; p50: 14.65%; p25: 10.25%), cut-offs were made considering a 5% increase in DWL (Q1: <10% of DWL, n=1495; Q2: 10–15% of DWL, n=1804; Q3: <15–20% of DWL, n=1470; Q4: ≥ 20% of DWL, n=1589), which would make it easier to transfer results to everyday clinical practice. 2.6. Other Variables Information related to smoking habits, marital status, educational level, as well as medical history and current medication were obtained. Biochemical analyses (triglycerides, total cholesterol, HDL-cholesterol and fasting plasma glucose) were performed using overnight fasting blood samples by standard enzymatic methods. Blood pressure was measured in triplicate with a validated semi-automatic oscillometer (Omron HEM, 705CP, Hoofddrop, The Netherlands) in a seated position. Waist circumference was measured in duplicate, halfway between the last rib and the iliac crest by using an anthropometric tape. The validated Minnesota-REGICOR short physical activity questionnaire [ 38 – 40 ] and the validated Spanish version of the Nurses’ Health Study questionnaire [ 41 ] were used to assess physical activity and sedentary behaviors, respectively. 2.7. Statistics Analyses were performed with the SPSS statistical software package version 25.0 (SPSSS Inc., Chicago, IL, USA). Data are shown as mean, standard deviation (SD) and median, interquartile range (IQR). Differences among groups were tested with one-way ANOVA and Bonferroni’s post-hoc analysis Nutrients 2020,12, 2114 7 of 18 when variables followed normal distribution, or Kruskal–Wallis models in other cases. Prevalence is expressed in sample size and percentage. Difference in prevalence among groups was tested using χ2 (all pvalues are two-tailed). Multivariate analysis was used to assess association between the MedDiet 17 items (dependent variables) and percentage (cut-off) of desired body weight loss (independent variables). For each item, 3 Odds Ratio (OR) were calculated: crude, adjusted by sociodemographic factors (age, BMI, physical activity, diet, education level, marital status and smoking habit), and adjusted by both sociodemographic factors and presence of metabolic syndrome components. 3. Results Table 2shows sociodemographic characteristics according to cut-offs of DWL. Participants with higher DWL (Q3 and Q4) were younger, had higher BMI (actual and perceived) and higher rates of abdominal obesity. No other components of the metabolic syndrome were different among groups except for high blood pressure and hyperglycemia in women (Supplemental Tables S1 and S2). A total of 27% of the subjects were overweight while 73% were obese. The majority of the subjects with overweight were classified into Q1 (52%) and Q2 (35%). On the contrary, most of the subjects with obesity were in Q4 (33%), Q3 (28%) and Q2 (27%). Moreover, 68%, 87% and 97% of the subjects in quartile 2, 3 and 4, respectively, had obesity. Tackling lifestyle, Q4 registered the lowest physical activity rates (Q1: 2106 MET min/week; Q4: 1585 MET min/week. p<0.001). Although there was no difference in total energy intake according to DWL, adherence to the MedDiet decreased as DWL increased (Q1: 8.7; Q4: 8.3. p<0.001). Q1 had fewer participants living alone and more married participants than the other groups. This was especially significant among women. In women, higher DWL was related to higher education levels, as well as to higher likelihood of ever smoking, but also to higher rates of abandoning tobacco consumption (Supplemental Tables S1 and S2). MedDiet adherence evaluated with the 17-item MedDiet questionnaire is available in Table 3. Low MedDiet adherence scores were more likely to be found among participants with higher DWL (Q1: 32.6%; Q4: 37.8%. p=0.007), as opposed to high scores, more easily found as DWL decreased (Q1: 25.7%; Q4: 20.6%. p=0.007). Vegetables, fruits, nuts, red and processed meat, and sugary sweetened beverages were the most relevant items decreasing overall adherence to the MedDiet. Conversely, avoiding adding sugar to beverages was higher among Q4. Tackling genders (Supplemental Tables S3 and S4), items decreasing adherence for men were those regarding vegetables, fish and seafood and preference of white over red meat; while for women were those regarding fruits, red and processed meat, adding sugar to beverages or consumption of sugary sweetened beverages, and using olive oil for cooking. Lastly, crude and adjusted OR for adherence to the 17 item MedDiet questionnaire items across cut-offQ1–4 of DWL are presented in Table 4. Q1 (<10% DWL) was established as the reference. Crude and adjusted analysis shows that OR for Q3 and Q4 was 0.75–0.85 times lower than Q1 for adhering to the items regarding vegetables, fruits, red and processed meat, and sugary sweetened beverages; and 0.65–0.80 times lower for nuts. On the other hand, avoiding adding sugar to beverages in Q4 had a crude OR 1.25 times higher than the Q1, but it disappeared after adjustment. Some associations (crude OR) were found only for one gender (Supplemental Tables S5 and S6). In men, Q4 had an OR 0.75–0.80 times lower than Q1 to meet the recommendations of fish or seafood and to prefer white over red meat. In women, Q4 had an OR 1.35–1.40 times higher than Q1 to use extra virgin olive oil for cooking. Nutrients 2020,12, 2114 8 of 18 Table 2. Sociodemographic characteristics according to percentage of desired weight loss (DWL). Q1 § (n=1492) Q2 § (n=1804) Q3 § (n=1470) Q4 § (n=1589) Mean (SD) Median (IQR) Mean (SD) Median (IQR) Mean (SD) Median (IQR) Mean (SD) Median (IQR) P Age (years) 65.9 (5.0) 66.0 (8.0) a,b,c 65.0 (4.8) 65.0 (8.0) a,e 64.8 (4.9) 65.0 (7.0) b,f 64.3 (4.7) 64.0 (7.0) c,e,f <0.001 BMI (kg/m2)29.8 (2.2) 29.5 (2.9) a,b,c 31.5 (2.8) 31.2 (3.7) a,d,e 33.2 (2.9) 33.0 (4.0) b,d,f 35.5 (2.9) 35.5 (4.3) c,e,f <0.001 Perceived BMI (kg/m2)30.0 (2.7) 29.6 (3.1) a,b,c 31.5 (2.9) 31.2 (3.9) a,d,e 33.2 (3.3) 32.8 (4.1) b,d,f 35.4 (3.3) 35.4 (4.6) c,e,f <0.001 Physical activity (PA) † Total (PA) †2730.8 (2459.4) 2106.3 (2540.8) b,c 2583.7 (2242.9) 2055.9 (2641.6) d,e 2387.7 (2311.2) 1762.7 (2454.6) b,d,f 2173.4 (2194.7) 1585.1 (2394.4) c,e,f <0.001 Light PA †792.8 (974.7) 447.6 (1118.9) 753.9 (940.5) 447.6 (1118.9) 761.5 (949.6) 447.6 (1118.9) 758.8 (957.2) 447.6 (1118.9) 0.667 Moderate PA †1089.1 (1615.8) 507.0 (1573.4) b,c 1029.0 (1543.8) 338.0 (1573.4) e906.2 (1534.2) 279.7 (1398.6) b,f 758.7 (1374.1) 0.0 (1049.0) c,e,f <0.001 Intense PA †848.8 (1633.4) 86.7 (1118.9) c800.8 (1370.7) 111.9 (1118.9) d,e 720.0 (1384.8) 83.9 (925.4) d655.8 (1277.3) 55.9 (839.2) c,e <0.001 Diet Energy intake (kcal/d) 2361.1 (535.8) 2334.4 (708.6) 2368 (541.7) 2326 (733.4) 2376.2 (555.6) 2350.3 (771.2) 2356.4 (569.5) 2318.7 (780.0) 0.711 MedDiet Q score 8.7 (2.7) b,c 9.0 (4.0) 8.5 (2.7) 8.0 (3.0) 8.4 (2.6) b8.0 (4.0) 8.3 (2.6) c8.0 (4.0) <0.001 n(%) n(%) n(%) n(%) Gender (female) 662 (21.4) 837 (23.0) 709 (23.0) 879 (28.5) <0.001 BMI classification <0.001 Overweight (BMI <30) 877 (51.4) 588 (34.4) 190 (11.1) 52 (3.0) Obesity (BMI >30) 615 (13.4) 1214 (26.4) 1267 (27.6) 1502 (32.7) Education level 0.089 Primary 773 (52.1) 852 (47.5) 684 (47.1) 778 (49.5) Secondary 399 (26.9) 528 (29.4) 448 (30.9) 462 (29.4) Tertiary 312 (21.0) 413 (23.0) 320 (22.0) 332 (21.1) Smoking habit 0.177 Current smoker 174 (11.7) 241 (13.4) 179 (12.3) 195 (12.3) Former smoker 617 (41.6) 770 (42.8) 661 (45.2) 712 (44.9) Never smoked 693 (46.7) 787 (43.8) 621 (42.5) 678 (42.8) Marital status 0.001 Married 1172 (79.0) 1391 (77.3) 1123 (76.6) 1174 (74.1) Divorced/separated 89 (6.0) 143 (7.9) 116 (7.9) 140 (8.8) Widower 173 (11.7) 166 (9.2) 151 (10.3) 175 (11.0) Other k50 (3.4) 99 (5.5) 76 (5.2) 96 (6.1) Living alone ‡155 (10.4) 238 (13.2) 176 (12.0) 211 (13.3) 0.047 Smoking habit 0.177 Current smoker 174 (11.7) 241 (13.4) 179 (12.3) 195 (12.3) Former smoker 617 (41.6) 770 (42.8) 661 (45.2) 712 (44.9) Never smoked 693 (46.7) 787 (43.8) 621 (42.5) 678 (42.8) MetS components High blood pressure 1373 (92.0) 1643 (91.1) 1368 (93.1) 1462 (92.0) 0.227 Hyperglycemia 1138 (76.3) 1330 (73.7) 1096 (74.6) 1231 (77.5) 0.056 Hypertriglyceridemia 835 (56.0) 1000 (55.4) 837 (56.9) 869 (54.7) 0.644 Low HDL-cholesterol 657 (44.0) 752 (41.7) 604 (41.1) 694 (43.7) 0.262 Abdominal obesity 1341 (89.9) 1735 (96.2) 1445 (98.3) 1585 (99.7) <0.001 Abbreviations: BMI. Body Mass Index. PA. Physical activity. MedDiet Q. 17-item Mediterranean Diet Questionnaire HDL-cholesterol. High density lipoprotein cholesterol. § Desired body weight loss =[(current body weight − ideal body weight)/current body weight] × 100. Due to the closeness of the cutting-percentiles, cut-offs were made considering a 5% of increase in desired body weight: Q1: <10% desired body weight loss; Q2: 10–15% desired body weight loss; Q3: 15–20% desired body weight loss; Q4: ≥ 20% desired body weight loss. † Measured in MET (Metabolic equivalent of task) min/week. k Other marital status were single and religious. ‡ Living alone regardless of marital status. Difference in means between groups were tested by one-way ANOVA and Bonferroni’s post-hoc when normally distributed or Kruskal-Wallis test when otherwise. Differences in prevalence’s across groups were examined using χ2 . Different letters indicate statistically significant differences between groups (a–f) according to Bonferroni’s post-hoc analysis. Nutrients 2020,12, 2114 9 of 18 Table 3. Adherence to the Mediterranean Diet 17-items according to the percentage of desired weight loss (DWL). Q1 § (n=1492) Q2 § (n=1804) Q3 § (n=1470) Q4 § (n=1589) MedDiet 17-items n(%) n(%) n(%) n(%) P 1: EVOO for cooking 1152 (77.2) 1454 (80.6) 1151 (78.3) 1262 (79.4) 0.100 2: Vegetables 609 (40.8) 631 (35.0) 526 (35.8) 546 (34.4) 0.001 3: Fruits 758 (50.8) 829 (46.0) 675 (45.9) 698 (43.9) 0.001 4: Red and processed meat 772 (51.7) 856 (47.5) 654 (44.5) 745 (46.9) 0.001 5: Butter, margarine, cream. 1209 (81.0) 1460 (80.9) 1161 (79.0) 1246 (78.4) 0.149 6: Sugar sweetened beverages 1155 (77.4) 1354 (75.1) 1081 (73.5) 1162 (73.1) 0.029 7: Legumes 297 (19.9) 341 (18.9) 262 (17.8) 306 (19.3) 0.532 8: Fish and seafood 690 (46.2) 875 (48.5) 684 (46.5) 714 (44.9) 0.215 9: Sweets and pastries 908 (60.9) 1079 (59.8) 871 (59.3) 905 (57.0) 0.151 10: Nuts 650 (43.6) 814 (45.1) 550 (37.4) 545 (34.3) <0.001 11: Preference white over red meat 1114 (74.7) 1325 (73.4) 1092 (74.3) 1177 (74.1) 0.879 12: Sofrito 855 (57.3) 1036 (57.4) 826 (56.2) 885 (55.7) 0.701 13: Adding sugar to beverages 940 (63.0) 1104 (61.2) 945 (64.3) 1080 (68.0) 0.001 14: White bread 688 (46.1) 776 (43.0) 679 (46.2) 725 (45.6) 0.198 15: Whole grains 418 (28.0) 481 (26.7) 416 (28.3) 412 (25.9) 0.398 16: Refined cereals 486 (32.6) 534 (29.6) 449 (30.5) 473 (29.8) 0.250 17: Wine 342 (22.9) 463 (25.7) 329 (22.4) 317 (19.9) 0.001 MedDiet Adherence 0.007 Low adherence (0–7) 487 (32.6) 655 (36.3) 550 (37.4) 600 (37.8) Moderate adherence (8–10) 621 (41.6) 719 (39.9) 591 (40.2) 662 (41.7) High adherence (11–17) 384 (25.7) 430 (23.8) 329 (22.4) 327 (20.6) § Desired body weight loss =[(current body weight − ideal body weight)/current body weight] × 100. 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