Reciprocal and Differential Influences of Mediterranean Diet and Physical Activity on Adiposity in a Cohort of Young and Older than 40 Years Adults.

Translational research has documented the conjoint beneficial relationships between dietary and physical activity habits concerning weight maintenance. However, the precise interplay between diet and exercise impacting body composition remains unclear, challenging personalized interventions. This study aimed to explore potential interactions and effect modifications of these factors affecting the body mass index (BMI) within an online adult cohort. Data from 11,883 NUTRiMDEA cohort participants were analyzed in this cross-sectional study, categorizing individuals by age, sex, and BMI using linear regression models to assess the interactions between lifestyle factors and adiposity. Significant differences emerged in anthropometry, lifestyle, and health-related quality of life (HRQoL) across categories. The combined effect of diet and physical activity had a greater impact on BMI than physical activity or Mediterranean diet adherence alone, with lower BMI as physical activity levels increased (ß: -0.5) and adherence to the Mediterranean diet decreased, where a modification effect between them was identified (ß: -0.28). Participants with lower Mediterranean diet adherence displayed superior BMI when physical activity was low, but when activity levels were higher, their BMI aligned with those with healthier dietary habits. An interaction link between lifestyle factors and BMI was found, showing the differential effects of the Mediterranean diet and physical activity combination concerning adiposity.

Corrigendum: Revisiting multi-omics-based predictors of the plasma triglyceride response to an omega-3 fatty acid supplementation.

[This corrects the article DOI: 10.3389/fnut.2024.1327863.].

Revisiting multi-omics-based predictors of the plasma triglyceride response to an omega-3 fatty acid supplementation.

Background: The aim of the present study was to identify the metabolomic signature of responders and non-responders to an omega-3 fatty acid (n-3 FA) supplementation, and to test the ability of a multi-omics classifier combining genomic, lipidomic, and metabolomic features to discriminate plasma triglyceride (TG) response phenotypes. Methods: A total of 208 participants of the Fatty Acid Sensor (FAS). Study took 5 g per day of fish oil, providing 1.9-2.2 g eicosapentaenoic acid (EPA) and 1.1 g docosahexaenoic (DHA) daily over a 6-week period, and were further divided into two subgroups: responders and non-responders, according to the change in plasma TG levels after the supplementation. Changes in plasma levels of 6 short-chain fatty acids (SCFA) and 25 bile acids (BA) during the intervention were compared between subgroups using a linear mixed model, and the impact of SCFAs and BAs on the TG response was tested in a mediation analysis. Genotyping was conducted using the Illumina Human Omni-5 Quad BeadChip. Mass spectrometry was used to quantify plasma TG and cholesterol esters levels, as well as plasma SCFA and BA levels. A classifier was developed and tested within the DIABLO framework, which implements a partial least squares-discriminant analysis to multi-omics analysis. Different classifiers were developed by combining data from genomics, lipidomics, and metabolomics. Results: Plasma levels of none of the SCFAs or BAs measured before and after the n-3 FA supplementation were significantly different between responders and non-responders. SCFAs but not BAs were marginally relevant in the classification of plasma TG responses. A classifier built by adding plasma SCFAs and lipidomic layers to genomic data was able to even the accuracy of 85% shown by the genomic predictor alone. Conclusion: These results inform on the marginal relevance of SCFA and BA plasma levels as surrogate measures of gut microbiome in the assessment of the interindividual variability observed in the plasma TG response to an n-3 FA supplementation. Genomic data still represent the best predictor of plasma TG response, and the inclusion of metabolomic data added little to the ability to discriminate the plasma TG response phenotypes.

Impact of maternal cardiometabolic status after bariatric surgery on the association between telomere length and adiposity in offspring.

The impact of bariatric surgery on metabolic and inflammatory status are reflected in the epigenetic profile and telomere length mediated by the changes in the metabolic status of the patients. This study compared the telomere length of children born before versus after maternal bariatric surgery as a surrogate to test the influence of the mother's metabolic status on children's telomere length. DNA methylation telomere length (DNAmTL) was estimated from Methylation-EPIC BeadChip array data from a total of 24 children born before and after maternal bariatric surgery in the greater Quebec City area. DNAmTL was inversely associated with chronological age in children (r = - 0.80, p < 0.001) and significant differences were observed on age-adjusted DNAmTL between children born before versus after the maternal bariatric surgery. The associations found between body mass index and body fat percentage with DNAmTL in children born after the surgery were influenced by maternal triglycerides, TG/HDL-C ratio and TyG index. This study reports the impact of maternal bariatric surgery on offspring telomere length. The influence of maternal metabolic status on the association between telomere length and markers of adiposity in children suggests a putative modulating effect of bariatric surgery on the cardiometabolic risk in offspring.

Dietary Iron, Anemia Markers, Cognition, and Quality of Life in Older Community-Dwelling Subjects at High Cardiovascular Risk.

Anemia causes hypo-oxygenation in the brain, which could lead to cognitive disorders. We examined dietary iron intake as well as anemia markers (i.e., hemoglobin, hematocrit, mean corpuscular volume) and diabetes coexistence in relation to neuropsychological function and quality of life. In this study, 6117 community-dwelling adults aged 55-75 years (men) and 60-75 years (women) with overweight/obesity and metabolic syndrome were involved. We performed the Mini-Mental State Examination (MMSE), the Trail Making Test parts A and B (TMT-A/B), Semantic Verbal Fluency of animals (VFT-a), Phonological Verbal Fluency of letter P (VFT-p), Digit Span Test (DST), the Clock Drawing Test (CDT), and the Short Form-36 Health Survey (SF36-HRQL test). Dietary iron intake did not influence neuropsychological function or quality of life. However, anemia and lower levels of anemia markers were associated with worse scores in all neurophysiological and SF36-HRQL tests overall, but were especially clear in the MMSE, TMT-B (cognitive flexibility), and the physical component of the SF36-HRQL test. The relationships between anemia and diminished performance in the TMT-A/B and VFT tasks were notably pronounced and statistically significant solely among participants with diabetes. In brief, anemia and reduced levels of anemia markers were linked to inferior cognitive function, worse scores in different domains of executive function, as well as a poorer physical, but not mental, component of quality of life. It was also suggested that the coexistence of diabetes in anemic patients may exacerbate this negative impact on cognition. Nevertheless, dietary iron intake showed no correlation with any of the outcomes. To make conclusive recommendations for clinical practice, our findings need to be thoroughly tested through methodologically rigorous studies that minimize the risk of reverse causality.

Heuristic Approach Uncovering Biological Significance of Gene-Lifestyle Interactions in Cardiometabolic Traits.

BACKGROUND: Gene-lifestyle interaction studies using genome-wide association studies (GWAS) data contribute to a better understanding of individual responses to environmental exposures. OBJECTIVES: Herein, we aimed at assessing the biological significance of overlapping genes reported in gene-lifestyle interaction studies in cardiometabolic health. METHOD: A heuristic analysis of genes reporting significant interactions related to cardiometabolic traits was performed to determine the biological pathways common to the different traits. RESULTS: A total of 873 genes were analyzed. Fine and condensed phenotypic solutions were obtained from overlapping genes common to more than one trait. CONCLUSIONS: This study revealed significant metabolic pathways associated with the impact of gene-environment interactions on cardiometabolic risk. Graphical Abstract: Publicly available data in cloud-based repositories were used to perform enrichment analyses of genes previously described in GWAS studies that showed interaction with lifestyles. From the enriched pathways, cluster analysis was performed to group enriched metabolic disorders.

A discriminant analysis of plasma metabolomics for the assessment of metabolic responsiveness to red raspberry consumption.

Background: Many studies show that the intake of raspberries is beneficial to immune-metabolic health, but the responses of individuals are heterogeneous and not fully understood. Methods: In a two-arm parallel-group, randomized, controlled trial, immune-metabolic outcomes and plasma metabolite levels were analyzed before and after an 8-week red raspberry consumption. Based on partial least squares discriminant analysis (PLS-DA) on plasma xenobiotic levels, adherence to the intervention was first evaluated. A second PLS-DA followed by hierarchical clustering was used to classify individuals into response subgroups. Clinical immune and metabolic outcomes, including insulin resistance (HOMA-IR) and sensitivity (Matsuda, QUICKI) indices, during the intervention were assessed and compared between response subgroups. Results: Two subgroups of participants, type 1 responders (n = 17) and type 2 responders (n = 5), were identified based on plasma metabolite levels measured during the intervention. Type 1 responders showed neutral to negative effects on immune-metabolic clinical parameters after raspberry consumption, and type 2 responders showed positive effects on the same parameters. Changes in waist circumference, waist-to-hip ratio, fasting plasma apolipoprotein B, C-reactive protein and insulin levels as well as Matsuda, HOMA-IR and QUICKI were significantly different between the two response subgroups. A deleterious effect of two carotenoid metabolites was also observed in type 1 responders but these variables were significantly associated with beneficial changes in the QUICKI index and in fasting insulin levels in type 2 responders. Increased 3-ureidopropionate levels were associated with a decrease in the Matsuda index in type 2 responders, suggesting that this metabolite is associated with a decrease in insulin sensitivity for those subjects, whereas the opposite was observed for type 1 responders. Conclusion: The beneficial effects associated with red raspberry consumption are subject to inter-individual variability. Metabolomics-based clustering appears to be an effective way to assess adherence to a nutritional intervention and to classify individuals according to their immune-metabolic responsiveness to the intervention. This approach may be replicated in future studies to provide a better understanding of how interindividual variability impacts the effects of nutritional interventions on immune-metabolic health.

HRQoL and nutritional well-being dissimilarities between two different online collection methods: Value for digital health implementation.

Background: Online health data collection has gained a reputation over the last years to record and process information about health issues for implementing digital health. Objective: The research aim was to appraise two online methods (open and rewarded) to collect information about HRQoL and nutritional well-being and to compare the results between both surveyed populations. Methods: This cross-sectional study is framed on the NUTRiMDEA project. Online data through two different web-based methods (open survey and rewarded survey) were retrieved to assemble data related to sociodemographic, lifestyle (diet, physical activity and sleep patterns) and general health aspects, as well as HRQoL by an evidence-based form such as the SF-12 questionnaire, the IPAQ survey, and MEDAS-14, participants were adults (>18 years old). Results: Overall, 17,332 participants responded to the open survey (OS, n = 11,883) or the rewarded survey (RS, n = 5449). About 65.1% of the participants were female, while the mean age was in the range of 40-70 years. There were significant differences (p < 0.05) between surveyed populations in sociodemographic, lifestyle (diet and physical activity), health and HRQoL data. Conclusions: This investigation implemented an evidence-based online questionnaire that collected demographic, lifestyle factors, phenotypic and health-related aspects as well as compared differential outcomes in HRQoL and nutritional/lifestyle well-being depending on the online mode data collection. Findings demonstrated dissimilarities in most aspects of health, HRQoL, dietary intake and physical activity records between both populations. Overall, OS sample was characterized as a healthier population with superior lifestyle habits than RS participants.

Morbid liver manifestations are intrinsically bound to metabolic syndrome and nutrient intake based on a machine-learning cluster analysis.

Metabolic syndrome (MetS) is one of the most important medical problems around the world. Identification of patient´s singular characteristic could help to reduce the clinical impact and facilitate individualized management. This study aimed to categorize MetS patients using phenotypical and clinical variables habitually collected during health check-ups of individuals considered to have high cardiovascular risk. The selected markers to categorize MetS participants included anthropometric variables as well as clinical data, biochemical parameters and prescribed pharmacological treatment. An exploratory factor analysis was carried out with a subsequent hierarchical cluster analysis using the z-scores from factor analysis. The first step identified three different factors. The first was determined by hypercholesterolemia and associated treatments, the second factor exhibited glycemic disorders and accompanying treatments and the third factor was characterized by hepatic enzymes. Subsequently four clusters of patients were identified, where cluster 1 was characterized by glucose disorders and treatments, cluster 2 presented mild MetS, cluster 3 presented exacerbated levels of hepatic enzymes and cluster 4 highlighted cholesterol and its associated treatments Interestingly, the liver status related cluster was characterized by higher protein consumption and cluster 4 with low polyunsaturated fatty acid intake. This research emphasized the potential clinical relevance of hepatic impairments in addition to MetS traditional characterization for precision and personalized management of MetS patients.

One-year longitudinal association between changes in dietary choline or betaine intake and cardiometabolic variables in the PREvención con DIeta MEDiterránea-Plus (PREDIMED-Plus) trial.

BACKGROUND: Choline and betaine intakes have been related to cardiovascular health. OBJECTIVES: We aimed to explore the relation between 1-y changes in dietary intake of choline or betaine and 1-y changes in cardiometabolic and renal function traits within the frame of the PREDIMED (PREvención con DIeta MEDiterránea)-Plus trial. METHODS: We used baseline and 1-y follow-up data from 5613 participants (48.2% female and 51.8% male; mean ± SD age: 65.01 ± 4.91 y) to assess cardiometabolic traits, and 3367 participants to assess renal function, of the Spanish PREDIMED-Plus trial. Participants met ≥3 criteria of metabolic syndrome and had overweight or obesity [BMI (in kg/m2) ≥27 and ≤40]. These criteria were similar to those of the PREDIMED parent study. Dietary intakes of choline and betaine were estimated from the FFQ. RESULTS: The greatest 1-y increase in dietary choline or betaine intake (quartile 4) was associated with improved serum glucose concentrations (-3.39 and -2.72 mg/dL for choline and betaine, respectively) and HbA1c levels (-0.10% for quartile 4 of either choline or betaine intake increase). Other significant changes associated with the greatest increase in choline or betaine intake were reduced body weight (-2.93 and -2.78 kg, respectively), BMI (-1.05 and -0.99, respectively), waist circumference (-3.37 and -3.26 cm, respectively), total cholesterol (-4.74 and -4.52 mg/dL, respectively), and LDL cholesterol (-4.30 and -4.16 mg/dL, respectively). Urine creatinine was reduced in quartile 4 of 1-y increase in choline or betaine intake (-5.42 and -5.74 mg/dL, respectively). CONCLUSIONS: Increases in dietary choline or betaine intakes were longitudinally related to improvements in cardiometabolic parameters. Markers of renal function were also slightly improved, and they require further investigation.This trial was registered at https://www.isrctn.com/ as ISRCTN89898870.

Appraisal of Gene-Environment Interactions in GWAS for Evidence-Based Precision Nutrition Implementation.

PURPOSE OF REVIEW: This review aims to analyse the currently reported gene-environment (G × E) interactions in genome-wide association studies (GWAS), involving environmental factors such as lifestyle and dietary habits related to metabolic syndrome phenotypes. For this purpose, the present manuscript reviews the available GWAS registered on the GWAS Catalog reporting the interaction between environmental factors and metabolic syndrome traits. RECENT FINDINGS: Advances in omics-related analytical and computational approaches in recent years have led to a better understanding of the biological processes underlying these G × E interactions. A total of 42 GWAS were analysed, reporting over 300 loci interacting with environmental factors. Alcohol consumption, sleep time, smoking habit and physical activity were the most studied environmental factors with significant G × E interactions. The implementation of more comprehensive GWAS will provide a better understanding of the metabolic processes that determine individual responses to environmental exposures and their association with the development of chronic diseases such as obesity and the metabolic syndrome. This will facilitate the development of precision approaches for better prevention, management and treatment of these diseases.

Longwise Cluster Analysis for the Prediction of COVID-19 Severity within 72 h of Admission: COVID-DATA-SAVE-LIFES Cohort.

The use of routine laboratory biomarkers plays a key role in decision making in the clinical practice of COVID-19, allowing the development of clinical screening tools for personalized treatments. This study performed a short-term longitudinal cluster from patients with COVID-19 based on biochemical measurements for the first 72 h after hospitalization. Clinical and biochemical variables from 1039 confirmed COVID-19 patients framed on the "COVID Data Save Lives" were grouped in 24-h blocks to perform a longitudinal k-means clustering algorithm to the trajectories. The final solution of the three clusters showed a strong association with different clinical severity outcomes (OR for death: Cluster A reference, Cluster B 12.83 CI: 6.11−30.54, and Cluster C 14.29 CI: 6.66−34.43; OR for ventilation: Cluster-B 2.22 CI: 1.64−3.01, and Cluster-C 1.71 CI: 1.08−2.76), improving the AUC of the models in terms of age, sex, oxygen concentration, and the Charlson Comorbidities Index (0.810 vs. 0.871 with p < 0.001 and 0.749 vs. 0.807 with p < 0.001, respectively). Patient diagnoses and prognoses remarkably diverged between the three clusters obtained, evidencing that data-driven technologies devised for the screening, analysis, prediction, and tracking of patients play a key role in the application of individualized management of the COVID-19 pandemics.

Cardiometabolic Health Status, Ethnicity and Health-Related Quality of Life (HRQoL) Disparities in an Adult Population: NutrIMDEA Observational Web-Based Study.

Precision public health supported on online tools is increasingly emerging as a potential strategy to achieve health promotion and disease prevention. Our aim was to assess the relationships of sociodemographic variables, anthropometric data, dietary habits and lifestyle factors with health-related quality of life (HRQoL), cardiometabolic health status and ethnicity in an online recruited adult population (NutrIMDEA Study). NutrIMDEA Study is a web-based cross-sectional survey that included 17,333 adults. Self-reported sociodemographic characteristics, anthropometric data, clinical and family history of cardiometabolic illnesses, dietary habits, lifestyle factors and HRQoL features were collected. Diseased individuals showed significative poorer MedDiet and worse HRQoL than those in the healthy cardiometabolic status group (p < 0.05). In comparison, European/Caucasian individuals reported a significantly better HRQoL, higher MedDiet and HRQoL values compared with those of other ethnicities (p < 0.05). We obtained a total of 16.8% who reported poor/fair, 56.5% good and 26.6% very good/excellent HRQoL. Respondents with very good/excellent HRQoL showed lower BMI, greater adherence to a Mediterranean diet (MedDiet) and higher physical activity. The results suggest the presence of interactions between the mental and physical components of HRQoL with obesity, sedentarism and dietary intake, which were dependent on disease status and ethnicity. Online HRQoL assessment could contribute to wider implementation of precision public health strategies to promote health targeted interventions with policy implications to community health promotion.

Interaction of ACEI antihypertensive agent's administration with the inflammatory status at admission concerning COVID-19 clinical stay outcomes.

Interactions between anti-hypertensive agents (ACEI), comorbidities, inflammation, and stress status may impact hospital stay duration in COVID-19 patients. This retrospective study analyzed epidemiological data, comorbidities, metabolic/inflammatory markers, and clinical information from 165 SARS-CoV-2 positive patients. In a multiple linear regression model, an IL-6 higher than 100 mg/L, glucose at admission (baseline levels at the hospital entry), and the interaction between ACEI administration and LDH predicted the days of hospital admission (P < 0.001). In conclusion, hypertensive patients suffering more severe inflammatory condition assessed by LDH levels clinically benefited more and reduced the hospital stay when prescribed ACEI agents than those with lower systemic baseline inflammation at admission.

Integrative development of a short screening questionnaire of highly processed food consumption (sQ-HPF).

BACKGROUND: Recent lifestyle changes include increased consumption of highly processed foods (HPF), which has been associated with an increased risk of non-communicable diseases (NCDs). However, nutritional information relies on the estimation of HPF consumption from food-frequency questionnaires (FFQ) that are not explicitly developed for this purpose. We aimed to develop a short screening questionnaire of HPF consumption (sQ-HPF) that integrates criteria from the existing food classification systems. METHODS: Data from 4400 participants (48.1% female and 51.9% male, 64.9 ± 4.9 years) of the Spanish PREDIMED-Plus ("PREvention with MEDiterranean DIet") trial were used for this analysis. Items from the FFQ were classified according to four main food processing-based classification systems (NOVA, IARC, IFIC and UNC). Participants were classified into tertiles of HPF consumption according to each system. Using binomial logistic regression, food groups associated with agreement in the highest tertile for at least two classification systems were chosen as items for the questionnaire. ROC analysis was used to determine cut-off points for the frequency of consumption of each item, from which a score was calculated. Internal consistency of the questionnaire was assessed through exploratory factor analysis (EFA) and Cronbach's analysis, and agreement with the four classifications was assessed with weighted kappa coefficients. RESULTS: Regression analysis identified 14 food groups (items) associated with high HPF consumption for at least two classification systems. EFA showed that items were representative contributors of a single underlying factor, the "HPF dietary pattern" (factor loadings around 0.2). We constructed a questionnaire asking about the frequency of consumption of those items. The threshold frequency of consumption was selected using ROC analysis. Comparison of the four classification systems and the sQ-HPF showed a fair to high agreement. Significant changes in lifestyle characteristics were detected across tertiles of the sQ-HPF score. Longitudinal changes in HPF consumption were also detected by the sQ-HPF, concordantly with existing classification systems. CONCLUSIONS: We developed a practical tool to measure HPF consumption, the sQ-HPF. This may be a valuable instrument to study its relationship with NCDs. TRIAL REGISTRATION: Retrospectively registered at the International Standard Randomized Controlled Trial Registry ( ISRCTN89898870 ) on July 24, 2014.

Corrigendum: Role of NAFLD on the health related QoL response to lifestyle in patients with metabolic syndrome: The PREDIMED plus cohort.

[This corrects the article DOI: 10.3389/fendo.2022.868795.].

Lifestyle and Health-Related Quality of Life Relationships Concerning Metabolic Disease Phenotypes on the Nutrimdea Online Cohort.

Obesity, diabetes and cardiovascular events are non-communicable diseases (NCDs) directly related to lifestyle and life quality. Rises on NCDs rates are leading to increases in early deaths concerning metabolic morbidities. Health-related quality of life (HRQoL) has been described as a subjective perception about the influence of health and personal features on human well-being. This study aimed to characterize phenotypic and lifestyle roles on the occurrence of metabolic diseases and determine the potential mutual interactions and with HRQoL. Data from an online adult population (NUTRiMDEA study, n = 17,332) were used to estimate an adapted Obesogenic Score (ObS), while logistic regression analyses were fitted in order to examine relevant factors related to the prevalence of different metabolic diseases including HRQoL. Sex and age showed significant differences depending on lifestyle and metabolic health (p < 0.05). Adherence to the Mediterranean diet and physical activity showed a mutual interaction concerning ObS (p < 0.001), as well with metabolic health (p = 0.044). Furthermore, metabolic diseases showed own features related to sociodemographic and lifestyle characteristics in this population. Metabolic syndrome components may be differently influenced by diverse lifestyle or socioeconomic factors which in turn affect the perceived HRQoL. These outcomes should be taken into account individually for a precision medicine and public health purposes.

Appraisal of Triglyceride-Related Markers as Early Predictors of Metabolic Outcomes in the PREVIEW Lifestyle Intervention: A Controlled Post-hoc Trial.

Background: Individuals with pre-diabetes are commonly overweight and benefit from dietary and physical activity strategies aimed at decreasing body weight and hyperglycemia. Early insulin resistance can be estimated via the triglyceride glucose index {TyG = Ln [TG (mg/dl) × fasting plasma glucose (FPG) (mg/dl)/2]} and the hypertriglyceridemic-high waist phenotype (TyG-waist), based on TyG x waist circumference (WC) measurements. Both indices may be useful for implementing personalized metabolic management. In this secondary analysis of a randomized controlled trial (RCT), we aimed to determine whether the differences in baseline TyG values and TyG-waist phenotype predicted individual responses to type-2 diabetes (T2D) prevention programs. Methods: The present post-hoc analyses were conducted within the Prevention of Diabetes through Lifestyle intervention and population studies in Europe and around the world (PREVIEW) study completers (n = 899), a multi-center RCT conducted in eight countries (NCT01777893). The study aimed to reduce the incidence of T2D in a population with pre-diabetes during a 3-year randomized intervention with two sequential phases. The first phase was a 2-month weight loss intervention to achieve ≥8% weight loss. The second phase was a 34-month weight loss maintenance intervention with two diets providing different amounts of protein and different glycemic indices, and two physical activity programs with different exercise intensities in a 2 x 2 factorial design. On investigation days, we assessed anthropometrics, glucose/lipid metabolism markers, and diet and exercise questionnaires under standardized procedures. Results: Diabetes-related markers improved during all four lifestyle interventions. Higher baseline TyG index (p < 0.001) was associated with greater reductions in body weight, fasting glucose, and triglyceride (TG), while a high TyG-waist phenotype predicted better TG responses, particularly in those randomized to physical activity (PA) of moderate intensity. Conclusions: Two novel indices of insulin resistance (TyG and TyG-waist) may allow for a more personalized approach to avoiding progression to T2D. Clinical Trial Registration: https://clinicaltrials.gov/ct2/show/NCT01777893 reference, identifier: NCT01777893.

Interactions of Comorbidity and Five Simple Environmental Unhealthy Habits Concerning Physical and Mental Quality of Life in the Clinical Setting.

The objective of this study was to examine the interactions between comorbidity and five lifestyle single habits concerning different subscales of quality of life (QoL). For the study, 302 patients were consecutively recruited at the internal medicine department of a tertiary teaching hospital. Lifestyle habits, comorbidities and QoL were recorded according to validated questionnaires. Five single unhealthy habits, such as tobacco consumption, dietary intake of ultra-processed pastries, raw nuts or carbonated drinks, sleep time and physical activity patterns were selected according to previously published data. The main outcomes of the study were the scores of the eight subscales of the SF-36 QoL survey. The aggregate of unhealthy habits showed statistically significant association to every category in the SF-36 questionnaire, both in the univariate and the multivariate analysis when adjusting by age, sex and comorbidity. An interaction was found between comorbidity and unhealthy habits in both physical and mental summaries of SF-36. In conclusion, the lifestyle assessment according to five unhealthy habits is associated with a worse QoL. The interaction between comorbidity and unhealthy habits is especially clear in diseased patients due to the interplay between illness and lifestyle in the prediction of QoL.