Association of cooking patterns with inflammatory and cardio-metabolic risk biomarkers

nutrients Article Association of Cooking Patterns with Inflammatory and Cardio-Metabolic Risk Biomarkers Belén Moreno-Franco 1,2 , Montserrat Rodríguez-Ayala 3, Carolina Donat-Vargas 3,4,5, Helena Sandoval-Insausti 3,6, Jimena Rey-García3,7 , Esther Lopez-Garcia 3,4, JoséR. Banegas 3, Fernando Rodríguez-Artalejo 3,4 and Pilar Guallar-Castillón3,4,*   Citation: Moreno-Franco, B.; Rodríguez-Ayala, M.; Donat-Vargas, C.; Sandoval-Insausti, H.; Rey-García, J.; Lopez-Garcia, E.; Banegas, J.R.; Rodríguez-Artalejo, F.; GuallarCastillón, P. Association of Cooking Patterns with Inflammatory and Cardio-Metabolic Risk Biomarkers. Nutrients 2021,13, 633. https:// doi.org/10.3390/nu13020633 Academic Editor: Marta Guasch-Ferré Received: 29 December 2020 Accepted: 13 February 2021 Published: 16 February 2021 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). 1Department of Microbiology, Pediatrics, Radiology and Public Health, Universidad de Zaragoza, 50009 Zaragoza, Spain; [email protected] 2Instituto de Investigación Sanitaria Aragón, Hospital Universitario Miguel Servet, 50009 Zaragoza, Spain 3Department of Preventive Medicine and Public Health, School of Medicine, Universidad Autónoma de Madrid-IdiPAZ and CIBERESP (CIBER of Epidemiology and Public Health), 28029 Madrid, Spain; [email protected] (M.R.-A.); car[email protected] (C.D.-V.); [email protected] (H.S.-I.); jimena.reygar[email protected] (J.R.-G.); esther[email protected] (E.L.-G.); [email protected] (J.R.B.); [email protected] (F.R.-A.) 4IMDEA-Food Institute, CEI UAM+CSIC, 28049 Madrid, Spain 5Unit of Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, 17177 Stockholm, Sweden 6Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA 7Internal Medicine Department, Ramón y Cajal University Hospital, 28034 Madrid, Spain *Correspondence: mpilar[email protected] Abstract: Diet has been clearly associated with cardiovascular disease, but few studies focus on the influence of cooking and food preservation methods on health. The aim of this study was to describe cooking and food preservation patterns, as well as to examine their association with inflammatory and cardio-metabolic biomarkers in the Spanish adult population. A cross-sectional study of 10,010 individuals, representative of the Spanish population, aged 18 years or over was performed using data from the ENRICA study. Food consumption data were collected through a face-to-face dietary history. Cooking and food preservation patterns were identified by factor analysis with varimax rotation. Linear regression models adjusted for main confounders were built. Four cooking and food preservation patterns were identified. The Spanish traditional pattern (positively correlated with boiling and sautéing, brining, and light frying) tends to be cardio-metabolically beneficial (with a reduction in C-reactive protein ( − 7.69%)), except for high density lipoprotein cholesterol (HDL-c), insulin levels, and anthropometrics. The health-conscious pattern (negatively correlated with battering, frying, and stewing) tends to improve renal function (with a reduction in urine albumin ( − 9.60%) and the urine albumin/creatinine ratio ( − 4.82%)). The youth-style pattern (positively correlated with soft drinks and distilled alcoholic drinks and negatively with raw food consumption) tends to be associated with good cardio-metabolic health except, for lower HDL-c ( − 6.12%), higher insulin (+6.35%), and higher urine albumin (+27.8%) levels. The social business pattern (positively correlated with the consumption of fermented alcoholic drinks, food cured with salt or smoke, and cured cheese) tends to be detrimental for the lipid profile (except HDL-c), renal function (urine albumin +8.04%), diastolic blood pressure (+2.48%), and anthropometrics. Cooking and food preservation patterns showed a relationship with inflammatory and cardio-metabolic health biomarkers. The Spanish traditional pattern and the health-conscious pattern were associated with beneficial effects on health and should be promoted. The youth-style pattern calls attention to some concerns, and the social business pattern was the most detrimental one. These findings support the influence of cooking and preservation patterns on health. Keywords: cardiovascular risk factors; inflammatory markers; dietary patterns; cooking methods; food preservation Nutrients 2021,13, 633. https://doi.org/10.3390/nu13020633 https://www.mdpi.com/journal/nutrients Nutrients 2021,13, 633 2 of 14 1. Introduction Unhealthy eating is associated with major causes of death, such as cardiovascular disease (CVD) and some types of cancer [ 1 ]. Food consumption guidelines for chronic disease prevention base their recommendations on data exclusively focused on nutrients, foods, food groups, and, more recently, dietary patterns; however, they hardly take into account the influence of cooking and food preservation methods on health. Cooking and food preservation methods modify the organoleptic conditions of food, making it more palatable, while influencing the bioavailability of nutrients, vitamins, and minerals. At the same time, some cooking and food preservation methods, (as in frying) increase fat and energy content, as well as the possible presence of toxic elements that may result, for example, from the cooking and reheating of food [2]. Frying is the cooking method most widely studied. When a food is fried, water is replaced by fat, and the composition of the food is modified. There is also an increase in trans-fatty acids as a result of deep frying [ 3 ]. The first relevant article on the health effects of frying was a cross-sectional analysis of 30,000 middle-aged adults. An increase in overall obesity and central obesity was observed among those with a high intake of fried food [ 4 ]. However, in longitudinal analyses, fried food consumption was not associated with coronary heart disease, stroke, or all-cause mortality [ 5 , 6 ]. Moreover, in a prospective cohort, a high consumption of fried food was also linked with weight gain, central obesity, and hypertension [ 7 – 9 ]. Other longitudinal analyses [ 10 , 11 ] have shown an association of fried food consumption with diabetes, CVD, and heart failure [ 12 ]. Thus, based on this evidence, the current recommendation is to consume fried food in moderation, while emphasizing an overall healthy diet [13]. Other cooking methods have barely been studied. Boiling and other cooking methods that use the application of heat lead to degradation of vitamins, as well as an increase in the glycemic index, leading to faster absorption of sugar [ 14 ], as well as the formation of toxic substances such as acrylamide when heating foods rich in starch [ 15 ] or heterocyclic amines when applying heat to meat products [ 16 ]. Furthermore, the increase in salt intake resulting from preservation methods such as brining, salt curing, or canning [ 17 ] are clear examples of how industrial processing has an impact on health. In addition, a result of this industrial processing is an increase in oxidative stress and inflammation [ 18 ]. On the contrary, diets composed exclusively of raw food have shown an association with negative health outcomes [ 19 , 20 ]. Research on other forms of cooking is very limited and mainly focuses on specific foods [21–25]. The study of dietary patterns provides a global approach concerning the association between food consumption and chronic diseases. Therefore, it seems reasonable to include the influence of cooking and food preservation methods when assessing diet as a whole. The aim of this study is to identify cooking and food preservation patterns in the Spanish adult population and to examine their association with inflammatory and cardio-metabolic biomarkers. Cooking methods, beyond the consumption of fried foods, are little analyzed and have never been studied as a pattern. 2. Materials and Methods 2.1. Study Design, Setting, and Participants Data were taken from the ENRICA study, whose methods have been described elsewhere [ 26 ]. In brief, this cohort was set up in 2008–2010 with 12,948 individuals aged ≥ 18 years, representative of the Spanish population. The ENRICA study was approved by the Clinical Research Ethics Committee of La Paz University Hospital (ethics approval code HULP-PI-1793). Study participants gave informed written consent. 2.2. Dietary Assessment Food consumption data were collected with a validated face-to-face computerized diet history [ 27 ] obtained by trained interviewers. The dietary history allowed for the collection of standardized data on 860 foods. Each food was assigned a cooking or preservation Nutrients 2021,13, 633 3 of 14 method, including mixed forms of cooking (for example, vegetables that are first boiled and then sautéed) (Table A1). The software includes 127 sets of digitized photographs to help quantify the size of food portions. Habitual food consumption takes into account a typical week in the preceding year, and every food consumed at least once every 15 days was considered. The intake of macronutrients, micronutrients, and minerals from the foods was estimated using Spanish composition tables [28]. Twenty-four possible cooking and food preservation methods were assessed: fifteen cooking methods (raw (not cooked), dairy products (including milk, yogurts, and fresh uncured cheese), boiling, roasting, pan-frying, frying, toasting, sautéing, stewing, boiling and then sautéing, light frying (sofrito), battering (bread crumbed), steaming, barbecuing, and microwaving), five preserving methods (curing cheese, curing with salt or smoke, canning in oil, canning not in oil, and brining), and four groups for beverages (soft drinks, fermented alcoholic drinks, coffee or tea, and distilled alcoholic drinks). 2.3. Anthropometric, Clinical, and Biochemical Characteristics Height was measured twice with portable extendable stadiometers (model Ka We 44 444Seca), weight with an electronic scale (precision 100 g), and waist and hip circumferences with a flexible inelastic belt-type tape, following standardized protocols [ 29 ]. The weight of participants was taken in the morning, after 12 h of fasting, and in light clothes. The body mass index (BMI) was calculated as weight in kilograms divided by height in meterssquared. Blood pressure was measured using standard procedures [ 30 ] and validated automatic devices (Omron M6) with appropriate cuffs of three sizes. Biomarkers of inflammation and cardio-metabolic risk were determined in 12 h fasting blood samples. High-sensitivity C-reactive protein (Hs-CRP) was measured by latexenhanced nephelometry and fibrinogen by the coagulation method. Total cholesterol was measured by enzymatic methods using cholesterol esterase and cholesterol oxidase; high density lipoprotein cholesterol (HDL-c) by the direct method by elimination/catalase, and triglycerides by the glycerol phosphate oxidase method. Low density lipoprotein cholesterol (LDL-c) levels were calculated with the Friedewald equation [ 31 ]. Fasting glucose was measured by the glucose oxidase method and insulin by immunoradiometric assay. Homeostatic model assessment for insulin resistance (HOMA-IR) was calculated by multiplying fasting serum insulin ( µ IU/mL) by fasting serum glucose (mg/dL) and dividing by 405 [ 32 ]. Uric acid was measured by the uricase-peroxidase technique, creatinine by the Jafféalkaline picrate kinetic reaction, and albumin in urine by polyethylene glycol (PEG)-enhanced immunoturbidimetry. All the laboratory determinations were performed centrally at the Center of Biological Diagnosis of the Clinic Hospital in Barcelona according to standard procedures and using appropriate quality controls. 2.4. Other Variables Participants reported their sex, age, educational level (primary, secondary, and university), and smoking status (current, former, or never smoker). Physical activity at leisure time was assessed with the EPIC (European Prospective Investigation into Cancer and Nutrition) Spain cohort questionnaire [ 33 ] and expressed in metabolic equivalents (METs)-hours/week [ 34 ]. The number of hours per week spent watching TV was also reported. The interviewer collected the following self-reported diseases diagnosed by a physician: pneumonia, asthma or chronic bronchitis, heart infarction, stroke or heart failure, osteoarthritis/arthritis, hip fracture, cholecystolithiasis, intestinal polyps, stomach or duodenal ulcer, cirrhosis, urinary tract infection, cataract, depression requiring drug treatment, Parkinson’s disease, dementia, Alzheimer’s disease, and periodontal disease. Nutrients 2021,13, 633 4 of 14 2.5. Statistical Analysis The study sample comprised 12,948 individuals. Of these, those with a lack of data on diet, biomarkers of inflammation and cardio-metabolic risk, or other variables were excluded. Thus, the final analytical sample included 10,010 individuals. An exploratory factor analysis with varimax rotation was carried out to identify cooking and food preservation patterns. The factors were rotated by the varimax function. An orthogonal rotation was made to assimilate each variable with an axis, reducing the complexity of the patterns and facilitating their interpretation [ 35 ]. Positive loading factors indicated that the individual cooking or preservation method was directly associated with the factors, while negative loading factors indicated an inverse association with the factors. Factorial loadings above 0.3 were considered to be major contributors to the factors [ 36 ]. Cooking patterns were named according to the cooking and food preservation methods that contributed the most. The associations between each cooking and preservation pattern with inflammatory and cardio-metabolic risk biomarkers were evaluated by multivariate linear regression. Each participant received a score for each pattern that indicated the degree of adherence of that participant to that specific pattern. So, cooking and preservation patterns were modeled in sex-specific quartiles, and the lowest quartile was used as reference. Inflammatory and cardio-metabolic biomarkers that did not follow a normal distribution were log-transformed prior to statistical analysis. For each quartile, the adjusted marginals of the biomarkers were calculated. The geometric mean ( ± SD) was obtained by inverse transformation. As a summary to aid interpretation, the relative differences between extreme quartiles were calculated and presented in a summary table ((value in the first quartile-value in the last quartile)/value in the first quartiles). The linear trend was calculated considering quartiles as a continuous variable. The linear regression models were adjusted for sex, age, educational level (primary, secondary, or university), smoking status (current, former, or never smoker), physical activity (MET-h/week), time spent watching TV (h/week), energy intake (kcal/day), and morbidity (to have at least one of the considered comorbidities). Only relative changes among extreme quartiles greater than 1% were considered for the description of the trends. All analyses were performed with STATA (version 15.0; StataCorp). Statistical tests were 2-tailed with a significance level of 5%. 3. Results The exploratory factorial analysis identified four cooking and food preservation patterns. The first pattern was positively associated with sautéing and boiling, brining, light frying (sofrito), roasting, boiling, canning in oil, and frying and negatively associated with pan-frying, and this was named the Spanish traditional pattern. The second factor was positively associated with toasting, brining, steaming, and canning in oil and negatively associated with battering, frying, and stewing, and this was named the health-conscious pattern. The third factor was positively associated with soft drinks and distilled alcoholic drinks and negatively associated with the consumption of raw food, coffee, and tea, and this was named the youth-style pattern. The fourth factor was positively associated with fermented alcoholic drinks, curing (salted or smoked), curing cheese, and distilled alcoholic drinks and negatively associated with the intake of dairy products, and this was named the social business pattern (Table 1). These four patterns accounted for 22% of the variance of total cooking and food preservation methods. Participants with a greater adherence to the Spanish traditional pattern were less physically active, watched less TV, and reported a greater intake of energy than those with a lower adherence to this pattern. Participants with a greater adherence to the healthconscious pattern were more educated, less frequently smoked, were more physically active, watched less TV, and reported a lower energy intake. Participants with a greater adherence to the youth-style pattern were younger, more educated, and more frequent smokers and performed more physical activity, watched less TV, reported a higher energy Nutrients 2021,13, 633 5 of 14 intake, and had fewer comorbidities. Finally, participants with a greater adherence to the social business pattern were more educated, more frequently smoked, performed less physical activity, spent less time watching TV, had a higher energy intake, and had fewer comorbidities compared to those with a lower adherence to this pattern (Table 2). Table 1. Varimax-rotated factor-loading matrix obtained using factor analysis. Cooking and Food Preservation Methods Grams Mean (SD) Spanish Traditional Pattern Health-Conscious Pattern Youth-Style Pattern Social Business Pattern Cooking methods Raw (not cooked) 356.5 (215.9) −0.574 Dairy products 276.9 (170.8) −0.436 Boiling 271.4 (138.8) 0.398 Roasting 197.0 (109.8) 0.426 Pan-frying 66.8 (65.1) −0.326 Frying 58.2 (55.3) 0.370 −0.451 Toasting 34.7 (44.0) 0.407 Sautéing 33.5 (38.2) Stewing 25.1 (37.8) −0.440 Boiling and then sautéing 23.3 (26.9) 0.558 Light frying (sofrito) 18.7 (21.9) 0.443 Battering (bread crumbed) 9.1 (21.6) −0.458 Steaming 2.2 (10.5) 0.368 Barbecuing 1.5 (10.5) Microwaving 0.8 (7.1) Preserving methods Curing cheeses 21.7 (33.1) 0.478 Curing (with salt or smoke) 17.8 (30.9) 0.487 Canning in oil 6.7 (11.2) 0.377 0.304 Canning (not in oil) 5.2 (15.8) Brining 4.4 (10.3) 0.449 0.383 Beverages Soft drinks 133.4 (252.1) 0.648 Fermented alcoholic drinks 127.9 (243.2) 0.583 Coffee or tea 113.3 (127.1) −0.400 Distilled alcoholic drinks 4.6 (18.5) 0.464 0.336 Loading factors of <0.30 are not shown. Regarding the association between the different identified patterns and the measured biomarkers, participants with a higher adherence to the Spanish traditional pattern had lower levels of Hs-CRP ( − 7.69%), fibrinogen ( − 1.79%), total cholesterol ( − 1.39%), LDLc ( − 1.44%), glucose ( − 1.09%), and urine albumin/creatinine ratio ( − 1.87%). On the contrary, they tended to present a detrimental profile for HDL-c ( − 2.28%), insulin (+1.58%), and anthropometric measurements (BMI +0.97%; waist circumference +1.75%; waist-tohip ratio +1.13%) (Table 3). The health-conscious pattern was associated with lower levels of urine albumin ( − 9.60%) and a low urine albumin/creatinine ratio ( − 4.82%) (Table 4). The youth-style pattern was associated with lower levels of Hs-CRP ( − 7.69%), fibrinogen ( − 5.62%), total cholesterol ( − 9.09%), LDL-c ( − 11.7%), triglycerides ( − 5.03%), glucose ( − 6.72%), uric acid ( − 4.42%), urine albumin/creatinine ratio ( − 6.36%), systolic and diastolic blood pressure ( − 5.82% and − 4.37% respectively), BMI ( − 4.26%), waist circumference ( − 5.19%), and waist-to-hip ratio ( − 4.49%). In contrast, it showed lower levels of HDL-c ( − 6.12%), insulin (+6.35%), and urine albumin (+27.8%) (Table 5). The social business pattern was associated with lower levels of fibrinogen ( − 3.56%), insulin (5.81%), and HOMA-IR ( − 5.71%). On the contrary, it presented higher levels of total cholesterol, LDL-c (+3.94%), HDL-c (+3.51%), triglycerides (+3.68%), uric acid (+4.42%), urine albumin (+8.04), diastolic blood pressure (+2.48%), and anthropometrics (BMI +1.44%; waist circumference +1.06%; waist-to-hip ratio +1.13%) (Tables 6and A2). Nutrients 2021,13, 633 6 of 14 Table 2. Characteristics of the study participants by quartiles of adherence to the cooking and food preservation patterns. The ENRICA study 2008–2010. Spanish Traditional Pattern Health-Conscious Pattern Youth-Style Pattern Social Business Pattern Q1 Q4 p-Value Trend Q1 Q4 p-Value Trend Q1 Q4 p-Value Trend Q1 Q4 p-Value Trend n= 2.315 n= 2.522 n= 2.516 n= 2.381 n= 2.464 n= 2.463 n= 2.452 n= 2.501 Men, n, % 1188 (51.3) 1258 (49.9) 0.787 1273 (50.6) 1195 (50.2) 0.938 1257 (51.0) 1236 (50.2) 0.956 1217 (49.6) 1246 (49.8) 0.711 Age, y 47.9 (0.42) 47.1 (0.48) 0.389 47.2 (0.49) 46.0 (0.52) 0.188 55.2 (0.41) 36.0 (0.42) <0.001 47.8 (0.51) 46.6 (0.52) 0.016 Education, n, % 0.114 <0.001 <0.001 <0.001 Primary 693 (29.9) 840 (33.3) 837 (33.3) 687 (28.9) 855 (34.7) 562 (22.8) 820 (33.4) 664 (26.5) Secondary 940 (40.6) 1022 (40.5) 1076 (42.7) 952 (40.0) 837 (34.0) 1340 (54.4) 976 (39.8) 1074 (42.9) University 682 (29.5) 660 (26.2) 603 (24.0) 742 (31.1) 772 (31.3) 561 (22.8) 656 (26.8) 763 (30.5) Smoking status, n, % 0.396 <0.001 <0.001 <0.001 Current smoker 653 (28.2) 660 (26.2) 769 (30.5) 612 (25.7) 499 (20.2) 898 (36.5) 524 (21.4) 850 (34.0) Former smoker 598 (25.8) 617 (24.5) 583 (23.2) 665 (27.9) 810 (32.9) 412 (16.7) 507 (20.7) 710 (28.4) Never smoker 1064 (46.0) 1245 (49.3) 1164 (46.3) 1104 (46.4) 1155 (46.9) 1152 (46.8) 1421 (57.9) 941 (37.6) Physical activity, MET-h/week 29.6 (21.5) 27.8 (23.0) <0.001 26.3 (21.6) 31.0 (22.6) <0.001 28.1 (20.1) 31.1 (24.8) <0.001 28.8 (22.4) 28.2 (22.3) <0.001 Time watching TV, h/week 14.0 (9.6) 13.7 (10.9) <0.001 13.9 (10.5) 13.5 (10.0) <0.001 14.2 (10.0) 13.2 (9.8) <0.001 14.3 (10.3) 13.2 (9.9) <0.001 Energy intake, kcal/day 1874.7 (549.3) 2600.1 (619.6) <0.001 2372.2 (674.7) 2265.1 (602.3) <0.001 2076.5 (573.7) 2457.0 (650.6) <0.001 2023.7 (592.5) 2450.0 (624.0) <0.001 Morbidity, n, % 943 (40.7) 1051 (41.7) 0.473 1070 (42.5) 920 (38.6) 0.138 1185 (48.1) 799 (32.4) <0.001 1108 (45.2) 921 (36.8) <0.001 MET: metabolic equivalents. Nutrients 2021,13, 633 7 of 14 Table 3. Plasma and urine concentrations of inflammatory and cardio-metabolic biomarkers, blood pressure, and anthropometrics according to the quartiles of the Spanish traditional pattern. Spanish Traditional Pattern 1 Q1 Q2 Q3 Q4 p-Value for Trend Biomarkers High-sensitivity C-reactive protein (Hs-CRP) (mg/L) 20.13 (1.42) 0.13 (1.41) 0.13 (1.44) 0.12 (1.46) <0.001 Fibrinogen (g/L) 23.34 (1.09) 3.31 (1.09) 3.30 (1.09) 3.28 (1.09) <0.001 Total cholesterol (mg/dL) 2193.72 (1.07) 192.49 (1.07) 191.70 (1.07) 191.02 (1.07) <0.001 LDL-cholesterol (mg/dL) 2117.90 (1.08) 117.08 (1.08) 116.53 (1.09) 116.20 (1.09) <0.001 HDL-cholesterol (mg/dL) 252.08 (1.12) 51.76 (1.13) 51.39 (1.13) 50.89 (1.14) <0.001 Triglycerides (mg/dL) 295.70 (1.17) 94.70 (1.17) 94.81 (1.19) 95.06 (1.19) 0.425 Glucose (mg/dL) 292.14 (1.07) 91.49 (1.07) 91.31 (1.07) 91.13 (1.08) <0.001 Insulin (µIU/mL) 27.46 (1.12) 7.45 (1.12) 7.51 (1.13) 7.58 (1.14) <0.001 Homeostatic model assessment for insulin resistance (HOMA-IR) 21.70 (1.18) 1.68 (1.18) 1.70 (1.19) 1.71 (1.20) 0.319 Uric acid (mg/dL) 25.08 (1.17) 5.08 (1.18) 5.09 (1.19) 5.12 (1.20) 0.242 Urine albumin (mg/dL) 26.29 (1.21) 6.31 (1.21) 6.32 (1.22) 6.37 (1.23) 0.130 Urine albumin/creatinine ratio (mg/g creatinine) 25.34 (1.22) 5.26 (1.21) 5.26 (1.22) 5.24 (1.23) 0.034 Blood pressure Systolic blood pressure (mmHg) 129.52 (9.16) 128.59 (9.03) 128.25 (9.82) 128.24 (9.97) 0.002 Diastolic blood pressure (mmHg) 75.63 (3.11) 75.50 (3.09) 75.50 (3.32) 75.69 (3.38) 0.693 Anthropometrics Body mass index (kg/m2)26.64 (1.95) 26.57 (1.91) 26.68 (2.09) 26.90 (2.15) 0.001 Waist circumference (cm) 89.91 (8.20) 89.96 (8.17) 90.52 (8.93) 91.52 (9.12) <0.001 Waist-to-hip ratio 0.87 (0.06) 0.87 (0.06) 0.88 (0.07) 0.88 (0.07) 0.009 1 Values are adjusted for sex, age, educational level (primary, secondary, or university), smoking status (current, former, or never smoker), physical activity (MET-h/week), time spent watching TV (h/week), energy intake (kcal/day), and morbidity (yes, no). 2 Geometric means. LDL: Low density lipoprotein; HDL: high density lipoprotein. Table 4. Plasma and urine concentrations of inflammatory and cardio-metabolic biomarkers, blood pressure, and anthropometrics according to the quartiles of the health-conscious pattern 1. Health-Conscious Pattern 1 Q1 Q2 Q3 Q4 p-Value for Trend Biomarkers Hs-CRP (mg/L) 20.13 (1.45) 0.13 (1.43) 0.13 (1.42) 0.13 (1.42) 0.132 Fibrinogen (g/L) 23.29 (1.10) 3.32 (1.09) 3.32 (1.09) 3.31 (1.09) 0.048 Total cholesterol (mg/dL) 2192.06 (1.07) 192.63 (1.07) 192.84 (1.07) 191.22 (1.07) 0.184 LDL-cholesterol (mg/dL) 2117.00 (1.09) 117.29 (1.09) 117.28 (1.08) 116.00 (1.08) 0.018 HDL-cholesterol (mg/dL) 251.27 (1.14) 51.50 (1.13) 51.86 (1.12) 51.43 (1.13) 0.279 Triglycerides (mg/dL) 294.99 (1.19) 95.35 (1.18) 94.82 (1.18) 95.05 (1.18) 0.860 Glucose (mg/dL) 291.20 (1.08) 91.72 (1.07) 91.76 (1.07) 91.34 (1.07) 0.532 Insulin (U/mL) 27.49 (1.13) 7.49 (1.13) 7.47 (1.12) 7.54 (0.13) 0.263 HOMA-IR 21.69 (1.20) 1.70 (1.19) 1.70 (1.18) 1.70 (1.18) 0.344 Uric acid (mg/dL) 25.08 (1.19) 5.10 (1.18) 5.09 (1.18) 5.11 (1.18) 0.626 Urine albumin (mg/dL) 26.72 (1.24) 6.40 (1.22) 6.11 (1.20) 6.07 (1.21) <0.001 Urine albumin/creatinine ratio (mg/g creatinine) 25.36 (1.23) 5.34 (1.22) 5.26 (1.21) 5.13 (1.21) <0.001 Blood pressure Systolic blood pressure (mmHg) 129.00 (10.02) 129.02 (9.59) 128.60 (9.30) 127.87 (9.03) 0.001 Diastolic blood pressure (mmHg) 75.94 (3.40) 75.69 (3.26) 75.45 (3.13) 75.22 (3.08) <0.001 Anthropometrics Body mass index (kg/m2)26.73 (2.14) 26.68 (2.06) 26.63 (1.97) 26.75 (1.96) 0.969 Waist circumference (cm) 90.47 (9.15) 90.43 (8.73) 90.35 (8.41) 90.70 (8.31) 0.581 Waist-to-hip ratio 0.88 (0.07) 0.88 (0.07) 0.88 (0.06) 0.88 (0.06) 0.823 1 Values are adjusted for sex, age, educational level (primary, secondary, or university), smoking status (current, former, or never smoker), physical activity (MET-h/week), time spent watching TV (h/week), energy intake (kcal/day), and morbidity (yes, no). 2 Geometric means. LDL: Low density lipoprotein; HDL: high density lipoprotein; Hs-CRP: High-sensitivity C-reactive protein; HOMA-IR: Homeostatic model assessment for insulin resistance. Nutrients 2021,13, 633 8 of 14 Table 5. Plasma and urine concentrations of inflammatory and cardio-metabolic biomarkers, blood pressure, and anthropometrics according to the quartiles of the youth-style pattern 1. Youth-Style Pattern 1 Q1 Q2 Q3 Q4 p-Value for Trend Biomarkers Hs-CRP (mg/L) 20.13 (1.43) 0.13 (1.45) 0.13 (1.47) 0.12 (1.42) 0.003 Fibrinogen (g/L) 23.38 (1.08) 3.35 (1.09) 3.32 (1.09) 3.19 (1.09) <0.001 Total cholesterol (mg/dL) 2200.39 (1.05) 195.46 (1.06) 191.24 (1.06) 182.16 (1.06) <0.001 LDL-cholesterol (mg/dL) 2123.49 (1.07) 119.48 (1.07) 116.09 (1.08) 109.02 (1.07) <0.001 HDL-cholesterol (mg/dL) 253.07 (1.13) 52.16 (1.13) 51.07 (1.13) 49.82 (1.12) <0.001 Triglycerides (mg/dL) 296.68 (1.19) 95.73 (1.18) 96.06 (1.19) 91.81 (1.17) <0.001 Glucose (mg/dL) 294.17 (1.07) 92.63 (1.07) 91.49 (1.07) 87.84 (1.06) <0.001 Insulin (µIU/mL) 27.22 (1.13) 7.41 (1.13) 7.67 (1.14) 7.71 (1.13) <0.001 HOMA-IR 21.68 (1.19) 1.70 (1.19) 1.73 (1.20) 1.67 (1.18) 0.903 Uric acid (mg/dL) 25.20 (1.19) 5.13 (1.18) 5.10 (1.19) 4.97 (1.18) <0.001 Urine albumin (mg/dL) 25.42 (1.19) 5.96 (1.19) 6.59 (1.20) 7.51 (1.18) <0.001 Urine albumin/creatinine ratio (mg/g creatinine) 25.35 (1.21) 5.34 (1.22) 5.39 (1.24) 5.01 (1.22) <0.001 Blood pressure Systolic blood pressure (mmHg) 131.78 (9.09) 129.93 (9.08) 128.70 (9.52) 124.11 (8.66) <0.001 Diastolic blood pressure (mmHg) 77.08 (3.02) 76.11 (2.95) 75.42 (3.13) 73.71 (2.92) <0.001 Anthropometrics Body mass index (kg/m2)27.18 (1.99) 26.86 (2.00) 26.73 (2.08) 26.02 (1.88) <0.001 Waist circumference (cm) 92.48 (8.59) 91.17 (8.39) 90.62 (8.77) 87.68 (8.14) <0.001 Waist-to-hip ratio 0.89 (0.07) 0.88 (0.06) 0.88 (0.07) 0.85 (0.06) <0.001 1 Values are adjusted for sex, age, educational level (primary, secondary, or university), smoking status (current, former, or never smoker), physical activity (MET-h/week), time spent watching TV (h/week), energy intake (kcal/day), and morbidity (yes, no). 2 Geometric means. LDL: Low density lipoprotein; HDL: high density lipoprotein; Hs-CRP: High-sensitivity C-reactive protein; HOMA-IR: Homeostatic model assessment for insulin resistance. Table 6. Plasma and urine concentrations of inflammatory and cardio-metabolic biomarkers, blood pressure, and anthropometrics according to the quartiles of the social business pattern 1. Social Business Pattern 1 Q1 Q2 Q3 Q4 p-Value for Trend Biomarkers Hs-CRP (mg/L) 20.13 (1.48) 0.13 (1.45) 0.13 (1.40) 0.13 (1.38) 0.337 Fibrinogen (g/L) 23.37 (1.10) 3.34 (1.09) 3.28 (1.09) 3.25 (1.08) <0.001 Total cholesterol (mg/dL) 2188.31 (1.08) 191.10 (1.07) 193.31 (1.06) 196.03 (1.06) <0.001 LDL-cholesterol (mg/dL) 2114.51 (1.09) 116.29 (1.09) 117.59 (1.08) 119.21 (1.08) <0.001 HDL-cholesterol (mg/dL) 250.65 (1.13) 51.19 (1.13) 51.78 (1.13) 52.43 (1.13) <0.001 Triglycerides (mg/dL) 293.20 (1.19) 94.74 (1.18) 95.49 (1.18) 96.77 (1.18) <0.001 Glucose (mg/dL) 291.59 (1.08) 91.73 (1.08) 91.40 (1.07) 91.31 (1.07) 0.128 Insulin (µIU/mL) 27.74 (1.12) 7.59 (1.12) 7.40 (1.12) 7.29 (1.12) <0.001 HOMA-IR 21.75 (1.19) 1.72 (1.19) 1.67 (1.18) 1.65 (1.18) <0.001 Uric acid (mg/dL) 24.97 (1.18) 5.07 (1.19) 5.15 (1.18) 5.20 (1.19) <0.001 Urine albumin (mg/dL) 26.06 (1.22) 6.22 (1.22) 6.41 (1.21) 6.59 (1.21) <0.001 Urine albumin/Creatinine ratio (mg/g creatinine) 25.27 (1.25) 5.29 (1.23) 5.24 (1.21) 5.28 (1.19) 0.994 Blood pressure Systolic blood pressure (mmHg) 128.89 (10.01) 128.94 (9.74) 128.46 (9.26) 128.26 (9.01) 0.038 Diastolic blood pressure (mmHg) 74.62 (3.31) 75.30 (3.26) 75.84 (3.14) 76.52 (3.13) <0.001 Anthropometrics Body mass index (kg/m2)26.51 (2.13) 26.67 (2.08) 26.71 (1.99) 26.90 (1.93) <0.001 Waist circumference (cm) 90.00 (8.78) 90.45 (8.73) 90.52 (8.55) 90.97 (8.52) 0.004 Waist-to-hip ratio 0.87 (0.07) 0.88 (0.07) 0.88 (0.07) 0.88 (0.07) 0.037 1 Values are adjusted for sex, age, educational level (primary, secondary, or university), smoking status (current, former, or never smoker), physical activity (MET-h/week), time spent watching TV (h/week), energy intake (kcal/day), and morbidity (yes, no). 2 Geometric means. LDL: Low density lipoprotein; HDL: high density lipoprotein; Hs-CRP: High-sensitivity C-reactive protein; HOMA-IR: Homeostatic model assessment for insulin resistance. Nutrients 2021,13, 633 9 of 14 4. Discussion Four different cooking and food preservation patterns were identified. The derived patterns did not share almost any cooking or preservation method and were linked to different types of social behaviors. The Spanish traditional pattern tended to be beneficial, except for HDL-c, insulin, and anthropometrics. The health-conscious pattern showed better renal function. The youth-style pattern tended to be associated with beneficial cardio-metabolic health except for a decrease in HDL-c and an increase in insulin and urine albumin levels. Finally, the social business pattern tended to associate unfavorably with the lipid profile (except HDL-c), uric acid, urine albumin, diastolic blood pressure, and anthropometrics; on the contrary, it also tended to correlate with lower fibrinogen levels. The cooking methods of the Spanish traditional pattern correspond with the traditional Spanish and Mediterranean cuisine, which typically includes sautéing and boiling, brining, light frying (sofrito), and frying. In line with our results, numerous studies have shown that adherence to a Mediterranean dietary pattern, characterized by a high consumption of fresh and not processed foods mostly of plant origin, has been associated with health benefits, including clear anti-inflammatory and heart-healthy properties [ 37 ]. This Spanish traditional pattern was also associated with a detrimental anthropometric profile as well as high insulin resistance that could be explained by the high prevalence of obesity and metabolic syndrome in Spain [ 29 ]. Another possible explanation for these associations may be due to a higher energy intake associated with an elaborate and palatable diet made at home, including high-density food from frying and the consumption of food canned in oil, not accompanied by sufficient physical activity. In addition, there is some evidence that a greater intake of olive oil (as in the Mediterranean diet) is associated with obesity [ 7 ]. Additionally, those with a higher adherence to this pattern presented a decrease in HDL-c that could be partially explained by lower physical activity and low alcohol consumption, even when the models were adjusted for these factors. It is worth noting that brined foods, such as vegetables [ 38 ], are rich in nitrates and nitrites, which are related to cardiovascular benefits [ 39 ]. In addition, dietary phenolic compounds present in sofrito enhance glucose metabolism [ 40 ]. When considered as a whole, this pattern was healthy (except for anthropometrics). The health-conscious pattern included simpler food elaboration levels (toasting or steaming with no added oil), avoiding cooking methods such as battering, frying, or stewing. This pattern tended to improve renal function (low urine albumin and albumin/creatinine ratio). This could be explained by the fact that less elaborated food (toasted, brined, steamed, food canned in oil) leads to better preservation of antioxidant and mineral compounds (i.e. those present in vegetable fiber) that are associated with vascular benefits [ 41 ]. Moreover, this pattern was inversely related to energy intake, being the only pattern with this characteristic. A more active lifestyle and other healthy habits among these participants, such as not smoking, could also partially explain the beneficial effects of this pattern. The youth-style pattern with higher adherence among younger participants (mean age 55 and 36 years old in Q1 and Q4, respectively) was strongly associated with the consumption of soft drinks and distilled alcoholic beverages and negatively associated with the consumption of raw food, coffee, and tea. It was also related to a high prevalence of current smokers and high energy intake. Despite the above, in the highest quartile of adherence, participants tended to have a clear increase in anti-inflammatory biomarkers, a hypolipidemic and hypotensive profile, as well as healthier anthropometrics. However, this pattern presents some elements of concern: lower HDL-c and higher insulin levels. The latter is in accordance with a higher consumption of soft drinks [ 42 ], and it could be explained by the effect of sweeteners on glucagon-like-peptide 1 (GLP-1), that increases insulin secretion [ 42 – 44 ]. Regarding HDL-c levels, a study of 7343 participants from the United States had similar results [ 45 ]. It should be noted that, although regression model adjustment included several confounding factors (such as age, sex, energy consumption, physical activity, and morbidity), differences in age among quartiles are important, and