Foundations of Lifestyle Medicine and its Evolution.

Lifestyle Medicine (LM) is a rapidly growing discipline that focuses on the role of lifestyle factors in preventing, managing, and reversing chronic disease. At this point in the field's evolution, there is strong evidence that the 6 pillars of LM-a whole-food, plant-predominant eating pattern, physical activity, restorative sleep, stress management, avoidance of risky substances, and positive social connections-are central in the creation and maintenance of health. Previous publications, many of them randomized controlled studies and meta-analyses, have solidified the evidence base for the use of the 6 pillars within the field of LM. As data emerged, so did its governing body, the American College of Lifestyle Medicine (ACLM), and with it a rich history began to unfold. Several articles have been written on the early history of the ACLM and the growth of the field; however, this review article explores the history and foundation of LM, aiming to provide a comprehensive understanding of its relevance and impact on health care. It underscores landmark studies that have defined the field and provides a road map detailing national and global barriers and areas of potential future growth.

Paradigm Shift in Medicine: Integrating Naturopathic Care in the Treatment of Chronic Disease: Want to follow best practices in chronic disease treatment? Look to naturopathic physicians.

The current healthcare system too often relies on prescription drugs, leading to increased opioid use and addiction, despite major medical organizations recommending non-drug approaches as the primary treatment in many conditions. The importance of lifestyle changes to achieving whole-person health is increasingly recognized. Nature-based medicine, as routinely practiced by naturopathic physicians provide a valuable and noteworthy alternative approach featuring lifestyle intervention to chronic pain and disease management. These physicians undergo extensive training in holistic models of care and apply a systematic approach called the Therapeutic Order, which focuses on addressing the underlying cause of symptoms and using the least force necessary for treatment. Improved outcomes are realized with multifactorial personalized treatment plans including lifestyle, nutrition, stress management, and physical activity. Integrative medicine is on the rise and we support the shift to the inclusion of a patient-centered approach in the management of chronic pain and disease. Nothing in the practice of natural, holistic medicine precludes respect for science, and the reliance on evidence. Rather, medicine is at its best when practice can draw from the best offerings of all pertinent fields.

Dietary Assessment by Pattern Recognition: a Comparative Analysis.

Background: Diet quality photo navigation (DQPN) is a novel dietary intake assessment tool that was developed to help address limitations of traditional tools and to easily integrate into health care delivery systems. Prevailing practice is to validate new tools against approaches that are in wide use. Objective: This study aimed to assess 1) the validity of Diet ID in measuring diet quality, food group and nutrient intake against 2 traditional dietary assessment methods (i.e., food record [FR], food frequency questionnaire) and 2) the test reproducibility/reliability of Diet ID to obtain similar results with repeat assessments. Methods: Using a participant-sourcing platform for online research, we recruited 90 participants, 58 of whom completed DQPN, a 3-d FR (via the Automated Self-Administered 24-hour Dietary Assessment Tool), and a food frequency questionnaire (FFQ, via the Dietary History Questionnaire III). We estimated mean nutrient and food group intake with all 3 instruments and generated Pearson correlations between them. Results: Mean age (SD) of participants was 38 (11) y, and more than half were male (64%). The strongest correlations for DQPN when compared with the other 2 instruments were for diet quality, as measured by the Healthy Eating Index 2015; between DQPN and the FFQ, the correlation was 0.58 (P < 0.001), and between DQPN and the FR, the correlation was 0.56 (P < 0.001). Selected nutrients and food groups also showed moderate strength correlations. Test-retest reproducibility for measuring diet quality was evaluated for DQPN and showed a correlation of 0.70 (P < 0.0001). Conclusions: The current study offers evidence that DQPN is comparable to traditional dietary assessment tools for estimating overall diet quality. This performance, plus DQPN's ease-of-use and scalability, may recommend it in efforts to make dietary assessment a universal part of clinical care.

Rapid, Digital Dietary Assessment in Association with Cardiometabolic Biomarkers.

PURPOSE: To examine the associations between dietary intake as assessed by a rapid, image-based digital tool and biomarkers of cardiometabolic health. DESIGN: Retrospective analysis of adults with blood biomarkers performed by Boston Heart Diagnostics (BHD) between December 2020 and March 2022. SETTING: Outpatient centers serviced by BHD. SUBJECTS: 546 adults, excluding those taking relevant medications and/or supplements known to affect blood test results. MEASURES: Laboratory assays of blood specimens were performed by Boston Heart Diagnostics. Nutrient intake and diet quality data were obtained using Diet Quality Photo Navigation (DQPN®; US Patent #11,328,810 B2) technique via Diet ID™ tool. ANALYSIS: Pearson correlation coefficients (for continuous variables) and Spearman coefficients (for ordinal variables) were used to evaluate associations between nutrient intake data and laboratory data for the full study sample. Two-sided P-values < .05 were considered statistically significant. RESULTS: Both continuous and ordinal measures of diet quality correlated significantly with HDL-C and triglycerides (n = 485; P < .0 01); with hs-CRP (n = 441; P < .001); with HgbA1c (n = 345; P < .01); with fasting insulin (n = 372; P < .001); and with HOMA-IR (n = 319; P < .001). CONCLUSION: Findings affirm that rapid, digital diet quality and composition assessment by pattern recognition rather than recall tracks significantly with key biomarkers of cardiometabolic health.

Interpreting global variations in the toll of COVID-19: The case for context and nuance in hypothesis generation and testing.

Key points: As of January 2022, the COVID-19 pandemic was on-going, affecting populations worldwide. The potential risks of the Omicron variant (and future variants) still remain an area of active investigation. Thus, the ultimate human toll of SARS-CoV-2, and, by extension, the variations in that toll among diverse populations, remain unresolved. Nonetheless, an extensive literature on causal factors in the observed patterns of COVID-19 morbidity and cause-specific mortality has emerged-particularly at the aggregate level of analysis. This article explores potential pitfalls in the attribution of COVID outcomes to specific factors in isolation by examining a diverse set of potential factors and their interactions. Methods: We sourced published data to establish a global database of COVID-19 outcomes for 68 countries and augmented these with an array of potential explanatory covariates from a diverse set of sources. We sought population-level aggregate factors from both health- and (traditionally) non-health domains, including: (a) Population biomarkers (b) Demographics and infrastructure (c) Socioeconomics (d) Policy responses at the country-level. We analyzed these data using (OLS) regression and more flexible non-parametric methods such as recursive partitioning, that are useful in examining both potential joint factor contributions to variations in pandemic outcomes, and the identification of possible interactions among covariates across these domains. Results: Using the national obesity rates of 68 countries as an illustrative predictor covariate of COVID-19 outcomes, we observed marked inconsistencies in apparent outcomes by population. Importantly, we also documented important variations in outcomes, based on interactions of health factors with covariates in other domains that are traditionally not related to biomarkers. Finally, our results suggest that single-factor explanations of population-level COVID-19 outcomes (e.g., obesity vs. cause-specific mortality) appear to be confounded substantially by other factors. Conclusions/implications: Our methods and findings suggest that a full understanding of the toll of the COVID-19 pandemic, as would be central to preparing for similar future events, requires analysis within and among diverse variable domains, and within and among diverse populations. While this may seem apparent, the bulk of the recent literature on the pandemic has focused on one or a few of these drivers in isolation. Hypothesis generation and testing related to pandemic outcomes will benefit from accommodating the nuance of covariate interactions, in an epidemiologic context. Finally, our results add to the literature on the ecological fallacy: the attempt to infer individual drivers and outcomes from the study of population-level aggregates.

Lifestyle Medicine and Climate Change: The Role of Providers in Addressing a Public Health Challenge.

Climate change threatens to undermine efforts to improve human health through lifestyle modification. Lifestyle medicine providers, however, may be well positioned to help patients create new healthful and climate-friendly habits, such as adopting a plant-based diet and limiting or eliminating car travel. Through each provider's own example and patient engagement efforts, as well as though new technology and the collective action of the American College of Lifestyle Medicine, the broader lifestyle medicine community can play an outsized role in addressing climate change.

The Financial Case for Food as Medicine: Introduction of a ROI Calculator.

Diet quality is now established as the single leading predictor of perennial premature death in modern countries. However, practice at scale in modern medicine is driven as much by financial as clinical imperatives and yet, the ability to quantify the potential ROI of Food as medicine (FaM) interventions is limited by a lack of data. Utilizing a novel advance in dietary assessment and data from the peer-reviewed literature, we constructed and tested a web-based calculator simulating the return-on-investment associated with FaM interventions.

Fit and Tipsy? The Interrelationship between Cardiorespiratory Fitness and Alcohol Consumption and Dependence.

PURPOSE: To examine whether higher levels of cardiorespiratory fitness are related to increased alcohol consumption and dependence among a large sample of adults attending a preventive medicine clinic. METHODS: A cross-sectional study of 38,653 apparently healthy patients who visited the Cooper Clinic (Dallas, TX) for preventive medical examinations (1988-2019) and enrolled in the Cooper Center Longitudinal Study. The primary independent variable was cardiorespiratory fitness, based on a maximal treadmill test, and the dependent variables were alcohol consumption and dependence (self-reported). The relations between fitness category (low, moderate, high) and alcohol consumption (low, moderate, heavy) and suggested alcohol dependence (Cut down, Annoyed, Guilty, Eye opener score ≥2) among women and men were estimated via multivariable regression while adjusting for covariates (e.g., age, birth year cohort, marital status, and body mass index). RESULTS: Women within the moderate and high fitness categories had 1.58 (95% confidence interval [CI], 1.32-1.91) and 2.14 (95% CI, 1.77-2.58) greater odds of moderate/heavy alcohol consumption, respectively, in comparison to their low fitness counterparts. Similarly, moderate and high fit men had 1.42 (95% CI, 1.30-1.55) and 1.63 (95% CI, 1.49-1.80) times greater odds of moderate-to-heavy alcohol consumption, respectively, in comparison to the low fitness group. In addition, among men who were heavy drinkers (but not women), higher fitness levels were related to lower rates of suggested alcohol dependence. Specifically, these men had 45.7%, 41.7%, and 34.9% proportions of clinically relevant alcohol problems across low, moderate, and high fitness categories (adjusted P for trend <0.001). CONCLUSIONS: Higher fitness levels are significantly related to greater alcohol consumption among a large cohort of adult patients. Interventions focusing on increasing fitness (via physical activity promotion) might consider concurrently aiming to reduce alcohol consumption.

Post-prandial effects of high-polyphenolic extra virgin olive oil on endothelial function in adults at risk for type 2 diabetes: A randomized controlled crossover trial.

BACKGROUND: Effects of olive oil on cardiovascular risk have been controversial. We compared the effects of high-polyphenolic extra virgin olive oil (EVOO) and refined olive oil without polyphenols on endothelial function (EF) in adults at risk for Type 2 diabetes mellitus (T2DM). METHODS: Randomized, controlled, double-blind, crossover trial of 20 adults (mean age 56.1 years; 10 women, 10 men) at risk for T2DM (i.e., as defined by either prediabetes or metabolic syndrome) assigned to one of two possible sequence permutations of two different single dose treatments (50 mL of high-polyphenolic EVOO or 50 mL of refined olive oil without polyphenols), with 1-week washout. Participants received their olive oils in a smoothie consisting of ½ cup frozen blueberries and 1 cup (8 oz) low-fat vanilla yogurt blended together. Primary outcome measure was EF measured as flow-mediated dilatation. Participants were evaluated before and 2 h after ingestion of their assigned olive oil treatment. RESULTS: EVOO acutely improved EF as compared to refined olive oil (1.2 ± 6.5% versus -3.6 ± 3.8%; p = 0.0086). No significant effects on systolic or diastolic blood pressure were observed. CONCLUSIONS: High-polyphenolic EVOO acutely enhanced EF in the study cohort, whereas refined olive oil did not. Blood pressure effects were not observed. Reports on the vascular effects of olive oil ingestion should specify the characteristics of the oil. CLINICAL TRIAL REGISTRATION NUMBER: NCT04025281.