Browse the evidence

Dietary counseling and individual-based education interventions tend to widen socioeconomic inequalities in healthy eating outcomes.

When designing health programs, avoid relying solely on dietary counseling for lower socioeconomic groups. Instead, combine education with structural support to ensure equitable outcomes.

Integration of food and nutrition into healthcare systems requires sustainable funding, clinician education, and rigorous research to be effective and scalable.

Advocate for your healthcare system to integrate food interventions. This means pushing for sustainable funding, better clinician nutrition education, and rigorous research to ensure these programs are effective and accessible.

Elevated activation in the lateral orbitofrontal cortex (OFC) during initial orientation to appetizing food cues predicts future increases in BMI over a 1-year period.

If you find yourself automatically and rapidly orienting your attention to pictures of appetizing food, this neural pattern is associated with a higher risk of gaining weight over the next year. This suggests that training attention away from food cues or reducing exposure to food cues might be a useful strategy for weight management, as behavioral reaction times alone do not predict this risk.

Higher BMI is associated with greater activation in the anterior insula/frontal operculum and lateral OFC during initial orientation to appetizing food cues, and greater activation in the ventrolateral prefrontal cortex (vlPFC) and superior parietal lobe during orientation to unappetizing food cues.

Your brain's response to food cues, whether appetizing or unappetizing, is stronger if you have a higher BMI. This heightened neural activity in attention and reward centers suggests that food cues are more salient and motivating for you, making it harder to ignore them.

Higher BMI is associated with faster behavioral response times (attentional bias) to both appetizing and unappetizing food images, but not to neutral water images.

You may find yourself noticing food images faster than neutral objects, regardless of whether the food looks tasty or not. This automatic attentional bias is more pronounced in individuals with higher BMI and may contribute to overeating in cue-rich environments.

Current clinical guidelines and public health strategies are insufficient because they focus almost exclusively on increasing leisure-time physical activity (LTPA) while ignoring the health risks of sedentary behavior.

Advocate for a shift in how health is promoted. Support policies and personal habits that reduce sitting time, not just increase gym time. Recognize that sitting is a distinct health risk.

Consumers' actual use of nutrition labels on food packages is low (16.8% across six European countries), despite understanding of label formats being significantly higher, indicating that lack of use is driven by motivation rather than comprehension.

Knowing how to read a nutrition label is not enough to ensure you use it while shopping. If you find yourself ignoring labels, it is likely because your primary motivation for buying is taste, price, or habit, not health. To change this, you must consciously prioritize health/nutrition as a decision criterion, as the study shows that looking for information is significantly lower when health is not the main reason for choice.

Parental use of controlling parenting styles (e.g., restriction, threats, bribes) regarding children's eating is associated with increased consumption of unhealthy foods, with a significantly stronger negative effect observed in daughters compared to sons.

If you are a parent, avoid using controlling strategies like threats, bribes, or strict restrictions regarding your daughter's food intake, as this is linked to her eating more unhealthy foods. Instead, focus on positive reinforcement (praise) and monitoring (tracking intake) to encourage healthier choices.

YouTube is not a reliable source of medical and health-related information, as aggregated evidence shows content quality is average to below-average and popularity metrics (views/likes) do not correlate with quality.

Do not use YouTube as your primary source for medical decisions. The platform's algorithm promotes popular content, which is often low-quality or misleading. If you must use YouTube, look for videos from verified, reputable institutions (e.g., major hospitals, professional societies) and cross-reference the information with a healthcare provider. Be skeptical of videos with high view counts but low medical detail.

Food frequency questionnaires (FFQs) tend to overestimate carotenoid intake compared to weighed dietary records, potentially by two- to three-fold, due to the long list of food choices and lack of correction factors.

When using Food Frequency Questionnaires (FFQs) to track carotenoid intake, be aware that they tend to overestimate actual consumption by two- to three-fold compared to more precise methods like photographic atlases or weighed records. However, FFQs are still valuable for comparing relative intake between different populations or tracking changes over time, as the qualitative ranking of food sources remains accurate. Do not rely on FFQ data for precise dosing calculations.

The extent to which health behaviors (smoking, diet, physical activity, alcohol) explain socioeconomic differences in mortality is contingent on the strength of the social patterning of those behaviors; in contexts where unhealthy behaviors are strongly concentrated in lower socioeconomic groups, they act as major mediators of mortality inequality, whereas in contexts with weaker social patterning, they explain a minor proportion of the inequality.

If you are designing public health policy to reduce health inequalities, do not assume that promoting healthy behaviors (like quitting smoking or eating well) will automatically close the gap between rich and poor. The effectiveness of these behaviors in reducing inequality depends on how strongly those behaviors are linked to social status in your specific community. In places where unhealthy behaviors are concentrated among the poor, promoting them is a high-leverage strategy. In places where these behaviors are more evenly distributed, other structural factors may be more important.

In primary prevention clinical practice across Europe, less than half of treated hypertensive and dyslipidaemic patients achieve target blood pressure and lipid levels, and only one-third of treated diabetic patients achieve the HbA1c target.

If you are being treated for high blood pressure, high cholesterol, or diabetes, do not assume you are 'safe' just because you are taking medication. The study shows that most people on treatment still do not reach healthy target levels. You must actively engage with your healthcare provider to ensure your numbers are actually within the target range, and prioritize lifestyle changes like diet and exercise, as medication alone is often insufficient.

Lifestyle counseling, particularly written dietary advice and smoking cessation strategies, is poorly implemented in primary prevention clinical practice across Europe.

If you are seeing a doctor for prevention, do not rely on verbal advice alone. Ask for written dietary plans and smoking cessation strategies. The study shows that most patients do not receive these structured resources, which are crucial for making lasting lifestyle changes.

Actigraphy has very low specificity (approx. 50%) for detecting wakefulness during sleep, leading to significant overestimation of total sleep time and sleep efficiency, particularly in conditions with fragmented sleep or high wake propensity.

Do not rely on actigraphy (wrist-worn trackers) to assess your sleep quality if you have insomnia, sleep apnea, or shift work. These devices will likely overestimate how much you slept because they mistake lying still while awake for sleep. Use them for general trends, but not for clinical decision-making or detailed sleep analysis.

Self-reported sleep duration and quality using brief epidemiological questionnaires (1-3 items) show poor agreement with objective actigraphy measures, rendering them invalid for assessing sleep as a precise risk factor in large-scale studies.

If you are tracking your sleep for health decisions, do not rely solely on how you feel or a simple 'how many hours' question. These self-reports are often inaccurate. If precise sleep data is critical for your health management, consider using an objective tracking method like actigraphy, as subjective reports can significantly misrepresent actual sleep duration and quality.

Among Hispanic/Latino populations, non-US-born immigrants often exhibit a 'sleep health advantage' with shorter sleep durations and fewer insomnia symptoms compared to US-born counterparts and Whites, though this advantage may diminish with acculturation.

If you are a non-US-born immigrant, you may have inherited sleep habits that are healthier than those of your US-born peers. As you adapt to life in the US, be mindful of acculturation stress and maintain cultural practices that support good sleep.

Psychological factors, specifically depression and hostility, are prevalent in the population and differ by gender, with women showing higher rates of depressive symptoms.

Screen for depression and stress, especially if you are female, as rates are significantly higher. Mental health impacts physical health outcomes and should be addressed alongside cardiovascular risk factors.

Obesogenic environments (physical, social, and economic factors favoring obesity) are a primary driver of the obesity epidemic, exerting powerful influences that have consolidated over the past 20-30 years.

Recognize that your environment plays a huge role in your weight. If your surroundings (food availability, activity options, economic stress) favor obesity, individual willpower alone is often insufficient. Addressing environmental factors is key to prevention.

Higher levels of education and higher socio-economic status are causally associated with lower obesity rates in women, creating a steep socio-economic gradient.

For women, higher education and socio-economic status are linked to lower obesity rates. This suggests that investing in education and addressing socio-economic disparities can be effective public health strategies for obesity prevention.

Optogenetic inhibition of LHA-LHb glutamatergic fibers acutely increases the consumption of a palatable liquid caloric reward.

Inhibiting the neural pathway from the lateral hypothalamus to the lateral habenula increases the consumption of palatable, high-calorie liquids. This suggests that this specific brain circuit acts as a suppressor of reward-driven eating, and its dysfunction could contribute to overconsumption of palatable foods.

Prescribing a free, widely-used smartphone calorie-tracking app (MyFitnessPal) to overweight primary care patients for 6 months does not produce significant weight loss compared to usual care.

Giving patients a calorie-tracking app like MyFitnessPal is not a substitute for counseling or motivation. In this study, most users stopped using the app within a month because they found it tedious or were too busy. This intervention did not lead to weight loss. Clinicians should assess a patient's readiness and willingness to perform daily self-monitoring before prescribing such tools, as the app alone is insufficient for most patients.

The Body Checking Questionnaire (BCQ) is a valid, reliable, and multidimensional self-report measure that distinguishes between individuals with eating disorders and healthy controls, as well as between different types of eating disorders.

If you are concerned about body checking behaviors, a structured self-report questionnaire like the BCQ can help identify specific patterns (e.g., checking weight vs. checking shape). This tool is validated for distinguishing between different types of eating disorders and can be a useful first step in clinical assessment, though it should be interpreted by a professional.

Interventions targeting only Physical Activity (PA) or combined PA and Sedentary Behavior (PA/SB) do NOT significantly reduce sedentary time in adults.

Simply exercising more or combining exercise with sitting reduction advice does not necessarily reduce your total sitting time. To reduce sitting, you need specific strategies focused on breaking up sitting time, not just adding exercise.

The population point prevalence of eating disorder behaviors (binge eating, purging, and strict dieting/fasting) significantly increased between 1995 and 2005 in South Australia, with a more than two-fold rise in these behaviors across both genders.

This research highlights a significant public health trend: disordered eating behaviors like binge eating, purging, and strict dieting are becoming more common in the general population, affecting both men and women across different age groups. It suggests that societal pressures regarding weight and shape may be driving an increase in these behaviors, which are associated with significant functional impairment ('days out of role').