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What is healthy eating?

The fundamentals of healthy eating, making the switch to a healthy diet, moderation: important to healthy eating, add more fruit and vegetables to your diet, healthy eating choosing healthy foods for a balanced diet.

Confused by all the conflicting nutrition advice out there? These simple tips can help you enjoy healthy foods and create a well-balanced diet that improves how you think and feel.

Healthy eating is not about strict limitations, staying unrealistically thin, or depriving yourself of the foods you love. Rather, it’s about eating well-balanced meals that leave you feeling great, having more energy, improving your health, and boosting your mood.

Healthy eating doesn’t have to be overly complicated. If you feel overwhelmed by all the conflicting nutrition and diet advice out there, you’re not alone. It seems that for every expert who tells you a certain food is good for you, you’ll find another saying exactly the opposite. The truth is that while some specific foods or nutrients have been shown to have a beneficial effect on mood, it’s your overall dietary pattern that is most important. Eating well involves eating more foods that are closer to the way nature made them. This can make a huge difference in how you think, look, and feel.

By using these simple tips, you can cut through the confusion and learn how to create—and stick to—a tasty, varied, and nutritious diet that is as good for your mind as it is for your body.

While some extreme diets may suggest otherwise, we all need a balance of protein, fat, carbohydrates, fiber, vitamins, and minerals in our diets to sustain a healthy body and mind. You don’t need to eliminate categories of food from your diet, but rather select a balance of options from each category.

Protein helps support your mood and cognitive function. Eating too much protein can be harmful to people with kidney disease, and it can displace other foods from your diet that provide important nutrients. However, research suggests that many of us need more high-quality protein in our diets, especially as we age. That doesn’t necessarily mean you have to eat more animal products. Including a variety of plant-based sources of protein each day can ensure your body gets all the essential protein it needs. Read: Choosing Health Protein»

Fat . Eating fats are helpful in a variety of biological functions, can make food taste good, and help you to feel satisfied after a meal. But not all fat is the same. While some fats, like saturated fats, have been linked to an increased risk of certain diseases, other, unsaturated fats protect your brain and heart health. In fact, omega-3 fats are vital to your physical and emotional health. Including more unsaturated fat in your diet can help improve your mood and protect your health. Read: Choosing Health Fats»

Carbohydrates are your body and brain’s main source of energy. Ideally, most carbs should come from complex, unrefined sources (such as vegetables, whole grains, and fruit) rather than sugars and refined carbs (such as donuts, white bread, and sugary drinks). Switching from simple, refined carbs to complex, unrefined carbs, and balancing your meals with with protein and unsaturated fat, can help prevent rapid spikes in blood sugar, and fluctuations in mood and energy. Read: Refined Carbs and Sugar»

Fiber . Eating foods high in dietary fiber (grains, fruit, vegetables, nuts, and beans) can help you stay regular and lower your risk for heart disease, stroke, and diabetes. It can also improve your skin and even help you to lose weight by feeling fuller longer. Read: High-Fiber Foods»

Calcium . As well as leading to osteoporosis, not getting enough calcium in your diet can also contribute to anxiety, depression, and sleep difficulties. Whatever your age or gender, it’s vital to include calcium-rich foods in your diet, limit those that deplete calcium, and get enough magnesium and vitamins D and K to help calcium do its job. Read: Calcium and Bone Health»

Switching to a balanced, nutritious diet doesn’t have to be an all or nothing proposition. You don’t have to be perfect, you don’t have to completely eliminate foods you enjoy, and you don’t have to change everything all at once—that usually only leads to cheating or giving up on your new eating plan.

A better approach is to make a few small changes at a time. Keeping your goals modest can help you achieve more in the long term without feeling deprived or overwhelmed by a major diet overhaul. Think of improving your diet as a number of small, manageable steps—like adding a salad to a meal once a day. As your small changes become habit, you can continue to add more healthy choices.

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Setting yourself up for success

To set yourself up for success, try to keep things simple. Eating a more balanced diet doesn’t have to be complicated. Instead of being overly concerned with counting calories, for example, think of your diet in terms of color, variety, and freshness. Focus on minimizing packaged and heavily processed foods and opting for more fresh ingredients whenever possible.

Prepare more of your own meals . Cooking more meals at home can help you take charge of what you’re eating and better monitor exactly what goes into your food. You may find that you feel less tired, bloated, and irritable, and don’t exacerbate symptoms of depression, stress, and anxiety.

Add balance to your diet . When changing your dietary habits, it’s important to focus on making changes that help improve the overall quality of your diet. Replacing saturated fats with healthy fats (such as switching fried chicken for grilled salmon) can make a positive difference to your health. Switching animal fats for refined carbohydrates, though (such as switching your breakfast bacon for a donut), won’t lower your risk for heart disease or improve your mood.

Read the labels . It’s important to be aware of what’s in your food as manufacturers often include ingredients in packaged food that your body just doesn’t need.

Focus on how you feel after eating . This will help foster healthy new habits and tastes. The more balanced and nutritious your food, the better you’ll likely feel after a meal.

Drink plenty of water . Water helps flush our systems of waste products and toxins, yet many of us go through life dehydrated—causing tiredness, low energy, and headaches. It’s common to mistake thirst for hunger, so staying well hydrated may also help you to eat less.

What is moderation? In essence, it means eating only as much food as your body needs. You should feel satisfied at the end of a meal, but not stuffed. For many of us, moderation means eating less than we do now. But it doesn’t mean eliminating the foods you love. Eating bacon for breakfast once a week, rather than every day, for example, could be considered moderation.

Try not to think of certain foods as “off-limits.” When you ban certain foods, it’s natural to want those foods more, and then feel like a failure if you give in to temptation. Start by increasing your mindfulness around those foods. Does your body want certain food or do you just eat out of habit? How do different foods make you feel after you eat them?

Think smaller portions . Serving sizes have ballooned recently. When dining out, choose a starter instead of an entree, split a dish with a friend, and don’t order supersized anything. At home, visual cues can help with portion sizes. Your serving of meat, fish, or chicken should be the size of a deck of cards and half a cup of mashed potato, rice, or pasta is about the size of a traditional light bulb. If you still feel hungry at the end of a meal, check in with what you need to feel satisfied—and ry to fill up on nutritious options, such as greens or fruit, rather than choosing heavily processed foods.

Take your time . It’s important to slow down and think about food as nourishment rather than just something to gulp down in between meetings or on the way to pick up the kids. It actually takes a few minutes for your brain to tell your body that it has had enough food, so eat slowly and stop eating before you feel full.

Eat with others whenever possible . Eating alone, especially in front of the TV or computer, often leads to mindless overeating.

Be mindful about snacking. While snacking can help to keep you going during the day between meals, it can also be a crutch when you are bored or stressed. Try to make balanced choices for snacks, that include carbohydrates, proteins, and fats, such as apple or crackers with cheese, or yogurt and granola.

Be aware of emotional eating. We don’t always eat just to satisfy hunger. Many of us also turn to food to relieve stress or cope with unpleasant emotions such as sadness, loneliness, or boredom. But by learning healthier ways to manage stress and emotions, you can better maintain a balanced diet.

[Read: Emotional Eating and How to Stop It]

It’s not just what you eat, but when you eat

Eat breakfast, and eat smaller meals throughout the day . A healthy breakfast can jumpstart your metabolism, while eating small, healthy meals keeps your energy up all day.

Try to avoid eating late at night . While the evidence is mixed, some studies have linked late-night eating with weight gain. This may be associated with non-hunger eating. Since many of us view the evening as a time to relax and unwind, it’s easy to become mindless with our eating.

Fruit and vegetables are nutrient dense, which means they are packed with vitamins, minerals, antioxidants, and fiber. Focus on eating the recommended daily amount of at least five servings of fruit and vegetables and it will naturally fill you up. A serving is half a cup of raw fruit or veg or a small apple or banana, for example. Most of us need to double the amount we currently eat.

To increase your intake:

• Add antioxidant-rich berries to your favorite breakfast cereal
• Eat a medley of sweet fruit—oranges, mangos, pineapple, grapes—for dessert
• Swap your usual rice or pasta side dish for a colorful salad
• Snack on vegetables such as carrots, snow peas, or cherry tomatoes along with a spicy hummus dip or peanut butter

How to make vegetables tasty

While plain salads and steamed veggies can quickly become bland, there are plenty of ways to add taste to your vegetable dishes.

Add color . Not only do brighter, deeper colored vegetables contain higher concentrations of vitamins, minerals and antioxidants, but they can vary the flavor and make meals more visually appealing. Add color using fresh or sundried tomatoes, glazed carrots or beets, roasted red cabbage wedges, yellow squash, or sweet, colorful peppers.

Liven up salad greens . Branch out beyond lettuce. Kale, arugula, spinach, mustard greens, broccoli, and Chinese cabbage are all packed with nutrients. To add flavor to your salad greens, try drizzling with olive oil, adding a spicy dressing, or sprinkling with almond slices, chickpeas, a little bacon, parmesan, or goat cheese.

Cook green beans, broccoli, Brussels sprouts, and asparagus in new ways . Instead of boiling or steaming these healthy sides, try grilling, roasting, or pan frying them with chili flakes, garlic, shallots, mushrooms, or onion. Or marinate in tangy lemon or lime before cooking.

More Information

• U.S. Department of Agriculture and U.S. Department of Health and Human Services. Dietary Guidelines for Americans, 2020-2025, 9th Edition. (2020). Link
• Dietary Guidelines Advisory Committee. (2020). Scientific Report of the 2020 Dietary Guidelines Advisory Committee . U.S. Department of Agriculture and U.S. Department of Health and Human Services. Link
• Skerrett, P. J., & Willett, W. C. (2010). Essentials of Healthy Eating: A Guide. Journal of Midwifery & Women’s Health, 55(6), 492–501. Link
• Marx, W., Moseley, G., Berk, M., & Jacka, F. (2017). Nutritional psychiatry: The present state of the evidence. Proceedings of the Nutrition Society, 76(4), 427–436. Link
• Morris, M. C., Tangney, C. C., Wang, Y., Sacks, F. M., Barnes, L. L., Bennett, D. A., & Aggarwal, N. T. (2015). MIND diet slows cognitive decline with aging. Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association, 11(9), 1015–1022. Link
• Hu, F. B., Manson, J. E., & Willett, W. C. (2001). Types of dietary fat and risk of coronary heart disease: A critical review. Journal of the American College of Nutrition, 20(1), 5–19. Link
• Jakobsen, M. U., Dethlefsen, C., Joensen, A. M., Stegger, J., Tjønneland, A., Schmidt, E. B., & Overvad, K. (2010). Intake of carbohydrates compared with intake of saturated fatty acids and risk of myocardial infarction: Importance of the glycemic index. The American Journal of Clinical Nutrition, 91(6), 1764–1768. Link
• Hu, F. B., Stampfer, M. J., Manson, J. E., Rimm, E., Colditz, G. A., Rosner, B. A., Hennekens, C. H., & Willett, W. C. (1997). Dietary Fat Intake and the Risk of Coronary Heart Disease in Women. New England Journal of Medicine, 337(21), 1491–1499. Link
• Siri-Tarino, P. W., Sun, Q., Hu, F. B., & Krauss, R. M. (2010). Saturated Fatty Acids and Risk of Coronary Heart Disease: Modulation by Replacement Nutrients. Current Atherosclerosis Reports, 12(6), 384–390. Link
• F. Masana, M., Tyrovolas, S., Kollia, N., Chrysohoou, C., Skoumas, J., Haro, J. M., Tousoulis, D., Papageorgiou, C., Pitsavos, C., & B. Panagiotakos, D. (2019). Dietary Patterns and Their Association with Anxiety Symptoms among Older Adults: The ATTICA Study. Nutrients, 11(6), 1250. Link
• Conner, T. S., Brookie, K. L., Carr, A. C., Mainvil, L. A., & Vissers, M. C. M. (2017). Let them eat fruit! The effect of fruit and vegetable consumption on psychological well-being in young adults: A randomized controlled trial. PLOS ONE, 12(2), e0171206. Link
• Veronese, N., Solmi, M., Caruso, M. G., Giannelli, G., Osella, A. R., Evangelou, E., Maggi, S., Fontana, L., Stubbs, B., & Tzoulaki, I. (2018). Dietary fiber and health outcomes: An umbrella review of systematic reviews and meta-analyses. The American Journal of Clinical Nutrition, 107(3), 436–444. Link
• Blatt, Alexandria D., Liane S. Roe, and Barbara J. Rolls. “Increasing the Protein Content of Meals and Its Effect on Daily Energy Intake.” Journal of the American Dietetic Association 111, no. 2 (February 2011): 290–94. Link
• Krok-Schoen, J. L., A. Archdeacon Price, M. Luo, O. J. Kelly, and Christopher Alan Taylor. “Low Dietary Protein Intakes and Associated Dietary Patterns and Functional Limitations in an Aging Population: A NHANES Analysis.” The Journal of Nutrition, Health & Aging 23, no. 4 (2019): 338–47. Link
• Vujović, Nina, Matthew J. Piron, Jingyi Qian, Sarah L. Chellappa, Arlet Nedeltcheva, David Barr, Su Wei Heng, et al. “Late Isocaloric Eating Increases Hunger, Decreases Energy Expenditure, and Modifies Metabolic Pathways in Adults with Overweight and Obesity.” Cell Metabolism 34, no. 10 (October 4, 2022): 1486-1498.e7. Link

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Healthy and Unhealthy Food

Different foods contain various types of healthy and unhealthy fats, so you need to choose the food options that are good for your body. – powerpoint ppt presentation.

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How Do You Spot an Unhealthy Gut? 4 Subtle Ways to Improve Your Digestive Health

Your gut microbiome deserves a little TLC. Here's how to cater to your gut health.

• Added coconut oil to cheap coffee before keto made it cool.

Your gut microbiome is a half-teased tangle of connections to other aspects of your health and body. Imbalances or stress on other body systems can impact gut health and vice versa.

In the world of wellness, there are few topics as trendy as "gut health," and for good reason: Your gut microbiome has connections to other aspects of your health, and researchers have linked it to digestive function,  mental health , your  skin  and more. In some cases , researchers are trying to pin down whether an unhealthy gut microbiome is one cause of a symptom or health condition or a reaction to one.

Read more : Best Healthy Meal Delivery Services of 2024

The microbiome refers to the trillions of microorganisms (also called microbes) living in your body, such as bacteria, viruses and fungi. The gut microbiome, specifically, references the microbes in your intestines -- notably the large intestine. This helps you metabolize the food you can't digest, boost your immune function and control inflammation. These microbes also generate metabolites (substances that your body uses to break down food), including vitamins, enzymes and hormones, according to Gail Cresci, a microbiome researcher and registered dietician with Cleveland Clinic's pediatric gastroenterology, hepatology and nutrition department. 

You should think of your gut microbiome as "little pets living inside your intestinal tract," Cresci told CNET in 2023. What we eat feeds them, and our internal environment dictates how well they thrive.

As we learn more about the gut microbiome, there are a few basic tips you can use to keep it as healthy as you can.

Read more: 12 Probiotic Foods That Can Improve Your Gut Health

Signs of an unhealthy gut 

"If you're bloated or you have lots of gas, you may have a disrupted composition and function of the gut microbiome," Cresci said, adding that the only way to know for sure is to have it measured .

Other signs of an unhealthy gut may include vomiting or stomach upset, fatigue, trouble sleeping, food intolerance and other symptoms . Skin irritation or problems may be one particularly visible sign, as some research links skin issues like acne and psoriasis  to the gut. 

Researchers are also looking into how it impacts reproductive health and hormone levels. 

Read more: The ABCs of Apple Cider Vinegar: Benefits, Precautions and Proper Dosage

How to help your gut 

It's important to see a doctor to get to the root cause of your health concern and rule out other conditions. Making changes to your diet or routine that may improve your gut, and your overall health is a good first step. 

It's also important to keep in mind that there's no exact standard for the perfectly healthy gut microbiome, Cresci said, since everyone's composition is so different. Bearing that in mind, here are four things you can do to help keep it on the right track. 

1. Eat these gut-friendly foods

The gut microbiome prefers foods we can't digest. This includes foods with a lot of fiber, such as fresh fruits, vegetables, whole grains, legumes, seeds and nuts; foods we already know we should eat for their nutritional properties.

According to Cresci, foods to remove from your gut, or eat in lower amounts, include foods high in sugar and fat and low in fiber.

"These are all associated with the consumption of a Western diet, which is also associated with a disrupted microbiome," she said. 

Beyond a gut-healthy diet, which not-so-coincidentally coincides with a heart-healthy diet , eating fermented foods can help replace the good microbes and their metabolites. Cresci lists yogurt, kombucha and kefir as examples. 

Here's our full list of the best probiotic foods for gut health . 

2. Make note of the medications you're taking

It's a well-known fact that taking antibiotics disrupts, at least temporarily, the family of "good" bacteria thriving in your body. Some common side effects of taking antibiotics include nausea, diarrhea and developing yeast infections. If you're prescribed an antibiotic or have recurring infections that have you taking antibiotics often, ask your doctor about what you can do to help minimize the disruption to your microbiome.

Other medications that can disrupt our microbiomes, Cresci says, include those that alter the PH of the stomach and take away acid. Examples include proton pump inhibitors, aka PPIs, and histamine H2-receptor antagonists, or H2 blockers, which are used to reduce acid reflux symptoms and might be available over the counter. 

By keeping track of the medications you're taking, you can help pinpoint the cause of your symptoms and (with sign-off from your doctor) take the appropriate steps or substitutions if gut health is an issue.

3. Find the right probiotics or supplements 

In addition to incorporating more yogurt or fermented foods into their diet, some people may seek a probiotic in hopes of balancing their gut, as they're designed to mimic an intact microbiota . If you're considering taking a supplement, including probiotics, Cresci told CNET it's important to know that probiotics are strain-specific, and "each strain has their own method of action." 

For example, some probiotics are designed to help people with antibiotic-induced diarrhea, but that won't work for a person taking it for bowel regularity. 

"You want to take the one that has been studied for whatever it is your problem is," she said. 

Also, unfortunately, keep in mind that probiotics will not completely override what you eat. 

"If you have a bad diet, and you want to keep eating a bad diet but want to improve your microbiome, a probiotic isn't gonna help you," Cresci said. "You have to do the other part too." 

Whole grains, fruits and vegetables are great food choices if you want to start healing your gut.

4. Move your body every day and prioritize sleep 

"Get better sleep" or "exercise more" might sound like tired advice, but improving your sleep hygiene and squeezing in more physical activity  are tried and true ways to improve your health, including your gut health. 

Exercise may help your gut in different ways , including by improving your circulation, helping your metabolism and aiding your digestive muscles, according to information from the Cleveland Clinic. If you dread running or don't have time to go to the gym, don't worry: There are small ways you can get your body in the habit of moving every day or at least more frequently. 

Getting good sleep is another general piece of wellness advice tied directly to the health of our guts. According to Cresci, our microbiome adheres to the circadian rhythm , too. So if we're eating when our gut microbiome isn't ready, we won't be set up to properly process the nutrients of our food. 

Lacking sleep also triggers an increase in stress and cortisol, which have negative mental and physical impacts. 

"There's a lot going on with the gut-brain interaction, so that signals back to the microbiome, and vice versa," Cresci said. 

Perhaps most fundamental is the fact that when we're exhausted, we don't have the energy to check off many of the things that keep us healthy, including exercising or finding a nutritious meal -- both of which impact our gut health. 

"When you're sleepy, tired, exhausted, you tend not to do the things we know are good for microbiomes," Cresci said. "So it kind of perpetuates itself."

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HEALTHY AND UNHEALTHY FOOD.

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HEALTHY & UNHEALTHY FOOD

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The breakfast is a meal that we eat normally between half past six and eleven. The unhealthy foods of the breakfast are bacon, candies, cake, toast with a lot of jelly and snacks. The healthy foods of the breakfast are toast, milk, yogurt, scrambled and boiled eggs and cereals.

The lunch is a meal that we eat at the noon. Generally, is the principal and most complete meal in the dayThere are many foods in the lunch that we can divide into healthy and unhealthy. For example:Healthy foods: This is, unfortunately, the less varied sector of this meal. Examples: salads(with different combinations of vegetables or, if you want to, fruits), omelets and scarbled eggs, rice, pasta salad and foods that have vegetables for main ingredient like vegetable cake and mahed potatoes.Unhealthy foods: This is the most varied sector of this meal. Generally they are fast foods. Some examples are: hot dogs, fried chicken, fries, hamburgers, tacos and pizza

Dinner is the last meal of the day. It's consumed at dusk or at night. The amount of food consumed is determined by the customs of each country. It's advisable to eat light things.The healthy food that is recommended to eat for dinner is: stuffed peppers, salmon and rice, meatballs, mixed salad, steak.The unhealthy food that is not recommended to eat for dinner is: chocolate, cheese, yogurt, butter, ice cream, spicy.

All the dairy products are derivated of milk The healthy Dairy food are milk, homemade yogurt and cheese. The unhealthy food are cream, whipped cream and butter.

This foods have for main ingredient the flour. Some of them are eaten at the dessert. For example: Healthy foods: wholemeal bread, healthy crackers, and oatmeal cookies Unhealthy foods: some examples chocolate crackers and cookies, pretzels, pies, croissant, donuts, bagels and buns.

A snack is a small portion of food that is usually eaten between meals.For a healthy diet, we can choose to eat, for example, fruits, whole grain cookies, fruit smoothies, energy bars or nuts.We must avoid eating unhealthy food frequently, like chips, sweets, ice cream, soda, chocolate, or anything with a lot of sugar

Snacks and Desserts

A lot of healthy and unhealthy drinks accompany any meal and tastes differently depending on how they made it, the drinks can be divided in:Healthy drinks: Smoothies and milkshakes of Apple, grapes, orange, watermelon, melon, strawberry and grapefruit, Milk, Water infusions like tea,etc.Unhealthy drinks: Shakes with a lot of sugar, Sodas, Drinks with alcohol, Artificial juices.

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Open Access

Peer-reviewed

Research Article

Commercial determinants of mental ill health: An umbrella review

Roles Data curation, Formal analysis, Methodology, Visualization, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliation Department of Health Services Research and Policy, London School of Hygiene and Tropical Medicine, London, United Kingdom

Roles Formal analysis, Methodology, Supervision, Writing – review & editing

Affiliation Department of Public Health, Environments and Society, London School of Hygiene and Tropical Medicine, London, United Kingdom

Roles Conceptualization, Funding acquisition, Methodology, Supervision, Writing – review & editing

Affiliation School of Social and Political Science, University of Edinburgh, Edinburgh, United Kingdom

Roles Methodology, Writing – review & editing

Roles Conceptualization, Funding acquisition, Methodology, Writing – review & editing

• Kate Dun-Campbell, 
• Greg Hartwell, 
• Nason Maani, 
• Alice Tompson, 
• May CI van Schalkwyk, 
• Mark Petticrew

• Published: August 28, 2024
• https://doi.org/10.1371/journal.pgph.0003605
• Reader Comments

Mental ill health has complex and interrelated underlying causes, with wider determinants of health often overlooked as risk factors. The ‘commercial determinants of health’ are gradually receiving more attention and recognition but there is a relative lack of awareness of the commercial determinants of mental health. This aim of this umbrella review was to synthesise systematic review level evidence for the association between commercial determinants and mental health outcomes. This umbrella review included evidence from high, middle, and low-income countries. We included terms related to broader commercial activities and terms focused on six key unhealthy commodities (tobacco, alcohol, ultra-processed foods, gambling, social media, fossil fuels) and the impacts of fossil fuel consumption (climate change, air pollution, wider pollution). We included 65 reviews and found evidence from high quality reviews for associations between alcohol, tobacco, gambling, social media, ultra-processed foods and air pollution and depression; alcohol, tobacco, gambling, social media, climate change and air pollution with suicide; climate change and air pollution with anxiety; and social media with self-harm. There was a lack of evidence examining wider practices of commercial industries. Our umbrella review demonstrates that by broadening the focus on commercial determinants, the influence of commercial products and activities on mental ill health can be better understood. The lack of research examining broader commercial practices on mental ill health is an area that should be addressed. Our review highlights the existing base of high-quality evidence for many of these unhealthy commodities’ impacts on mental ill health and indicates that commercial determinants is a valuable framework for understanding the drivers of mental ill health.

Citation: Dun-Campbell K, Hartwell G, Maani N, Tompson A, van Schalkwyk MC, Petticrew M (2024) Commercial determinants of mental ill health: An umbrella review. PLOS Glob Public Health 4(8): e0003605. https://doi.org/10.1371/journal.pgph.0003605

Editor: Godfred Boateng, York University, CANADA

Received: January 31, 2024; Accepted: July 24, 2024; Published: August 28, 2024

Copyright: © 2024 Dun-Campbell et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: Data extracted from reviews (as in summary table) but no new data generated.

Funding: This work was supported by the Three NIHR Research Schools Mental Health Programme (award number: MH004) The grant was received by GH, NM, and MP. . MVS is funded by a National Institute for Health Research Doctoral Fellowship (Ref NIHR300156). MP is a co-investigator in the Spectrum consortium, which is funded by the UK Prevention Research Partnership (UKPRP), a consortium of UK funders (UK Research and Innovation research councils: Medical Research Council, Engineering and Physical Sciences Research Council, Economic and Social Research Council, and Natural Environment Research Council; charities: British Heart Foundation, Cancer Research UK, Welcome, and The Health Foundation; Government: Scottish Government Chief Scientist Office, Health and Care Research Wales, National Institute of Health Research and Public Health Agency. AT is also supported by the Spectrum consortium. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Factors that determine mental health are both complex and interrelated [ 1 ]. Globally, around 1 in 8 people are living with a diagnosed mental health disorder [ 1 ] - although this is likely an underestimate of the true proportion of people living with mental ill health. Existing research shows a focus on individual susceptibility and life experiences such as childhood trauma. This can overlook the context in which these experiences occur including the ways in which wider social, political, economic and commercial forces shape mental health and inequalities [ 2 , 3 ]. Recent research, reflecting a growing interest in the social determinants of health (SDOH), has focused on these wider factors – such as household income, employment and housing [ 4 , 5 ]. The commercial determinants of mental health (CDMH) in particular, have not yet been afforded a similar level of attention [ 6 ].

The commercial determinants of health (CDOH) can be thought of as “the systems, practices, and pathways through which commercial actors drive health and equity” [ 7 ]. This includes both the direct and indirect effects of the consumption of produced commodities - such as tobacco, alcohol, fossil fuels and unhealthy foods - and the drivers of consumption such as marketing and advertising [ 8 ]. In addition to analysis of specific unhealthy commodities, CDOH research also includes analysis of the role of commercial actors in shaping the political, structural, and cultural environments which affect health [ 9 ].

These commercial influences can impact not just physical but also mental health, since unhealthy commodity products directly affect and/or harm mental health [ 10 – 12 ]. There is already an evidence base, for instance, for the impact of alcohol consumption on depression and suicide [ 13 ] and smoking on depression and anxiety [ 14 ]. Yet the effects are also indirect; for example, the producers of harmful commodities frequently adopt framings of individual responsibility to place the blame for product harms on individuals themselves. This is often done though ‘responsibility’ campaigns and slogans such as “Gamble/Drink Responsibly” [ 15 ].

Despite the evidence for impacts of unhealthy commodity consumption on health outcomes, existing frameworks for the social determinants of health generally do not consider commercial determinants; nor do they typically include mental health [ 16 ]. There is a strong case for drawing together the existing evidence on mental ill health and commercial determinants. This is of value both for informing the further development of existing SDOH frameworks and identifying points at which to intervene on the CDMH.

This umbrella review therefore aimed to synthesise systematic review evidence on the effects of commercial determinants on mental ill health outcomes to map and identify gaps in the existing evidence base.

The review was developed according to the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) guidelines and the protocol registered on PROSPERO 2022 CRD42022320288 [ 17 ].

Eligibility criteria

Inclusion criteria were:

• Population: High, middle, and low-income countries.
• Intervention/exposure: Commercial determinants of mental health, including market strategies and non-market strategies, across six key unhealthy commodities (tobacco, alcohol, ultra-processed foods, gambling, social media, fossil fuels), and the results of fossil fuel consumption (climate change, air pollution, wider pollution).
• Outcome: Mental health outcomes, anxiety, depression, self-harm, and suicide. Any type of measure was included (e.g., self-reported or assessed by a clinician).
• Study design: Full-text articles, in the English language, between 2012-2023 (limited to the past 10 years to ensure a manageable number of results; and in the case of social media to ensure there were sufficient studies), systematic review, meta-analysis, narrative review, scoping review.

Exclusion criteria

Studies that examined mental well-being, or severe mental illness, including bipolar disorder, schizophrenia, and other psychotic disorders, and eating disorders were excluded. As noted- for reasons of feasibility- the review focused on six industries with major relevance to health: tobacco, alcohol, social media, ultra-processed foods, gambling, and fossil fuel products. We also chose to only include adverse impacts from large-multinational manufacturers [ 18 ]. Although the private sector often undertakes important social functions aligned with health benefits, these positive health impacts are already incentivised through the commercial incentives of profit-seeking, just as negative health impacts are. As Maani et al. have therefore argued [ 15 ], focusing research on areas where profit and health are misaligned is likely to contribute to greater short-term net health benefits. Similarly, the most significant scientific insights can be expected by focusing on the largest commercial entities rather than the manifold small and medium organisations than constitute a far smaller fraction of overall commercial impacts on health.

Search strategy

The literature search was developed in Medline and adapted for use in other databases (see S1 – S3 Figs for full search strategy). Search terms relating to the influence of commercial actors were developed based on Lee et al.’s (2022) ‘Conceptual Framework for the Study of the Commercial Determinants of Health’ – including market and non-market strategies [ 8 ]. KDC ran pilot searches to develop additional terms, then conducted searches of Medline, PubMed, PsychInfo, Scopus and the Cochrane database on 28 th March 2022 (Repeat searches were run on 7 th August 2023). See Fig 1 for PRISMA.

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PRISMA outlining the number of reviews found for each database searched, the number excluded, and the final number included.

https://doi.org/10.1371/journal.pgph.0003605.g001

Study selection

One reviewer (KDC) conducted initial screening by title. Two reviewers (KDC and GH) screened reviews in Covidence [ 19 ] by title and abstract; each screened 50% of the reviews with a sample of 100 screened by both to check agreement. This sample had high inter-rater reliability with Cohen’s Kappa of 0.8 (strong agreement). The full-text screening was undertaken by two independent reviewers (KDC and GH) using Covidence. We discussed disagreements between the reviewers, with high reliability (Cohen’s Kappa = 0.71, indicating substantial agreement). At this stage of the search, we had an unmanageable volume of reviews so decided to limit the included reviews to those that focused specifically on our exposures and outcomes of interest (as opposed to prevalence studies examining a very wide range of exposures or outcomes, of which only one or a small part would be relevant).

Data collection process and data items

We extracted information on the name of the review, authors, date, number of studies included, type of studies included (e.g., cohort, cross-sectional), measure of exposure, measure of outcome, pooled effect estimate (if available), summary of results, proposed mechanism for effecting mental health and funding. One reviewer (KDC) extracted the data, and results were grouped for each industry and sent to a second reviewer (GH) for review.

Quality assessment

We used the Scottish Intercollegiate Guidelines Network (SIGN) checklist for systematic reviews and meta-analyses [ 20 ] to assess each study’s quality.

Quality was rated as ‘low’, ‘acceptable’ and ‘high’ using the criteria set out in the guidance notes - “High quality (++): Majority of criteria met. Little or no risk of bias. Acceptable (+): Most criteria met. Some flaws in the study with an associated risk of bias. Low quality (-): Either most criteria not met, or significant flaws relating to key aspects of study design. Reject (0): Poor quality study with significant flaws. Wrong study type. Not relevant to guideline” [ 20 ]. For example, a review was unable to achieve a ‘high’ rating if the review did not assess the quality of its included studies. We included all reviews deemed to be of “high” and “acceptable” quality. Low-quality reviews were only included if they contained an exposure or outcome which was not well represented in the sample.

Synthesis of results

We used narrative synthesis to combine the findings across the included reviews. It was decided during our study design that meta-analysis was not appropriate due to heterogeneity in the measurement of exposures and outcomes across included studies – this is outlined in our protocol on PROSPERO 2022 CRD42022320288 [ 17 ].

Our search returned 11,666 reviews across the five databases. Once duplicates were removed, 9,663 records were screened by title, of which 2,366 were uploaded to Covidence [ 19 ] for abstract screening. We then assessed 318 full texts for eligibility. This left a total of 220 reviews, of which 158 were excluded for being non-specific (as per ‘study selection’ above).

We included 65 reviews in the final synthesis, see Fig 2 for summary of reviews and Fig 3 for review characteristics and main findings. Fourteen reviews examined the impact of smoking on mental health outcomes. Eight were rated as high and six as acceptable quality. We included eleven reviews of alcohol consumption and mental health outcomes. We rated four as high, four as acceptable, and three as low-quality. Five reviews examined ultra-processed food as an exposure; we assessed three as high and two as acceptable quality. Three reviews examined the impact of gambling on mental health outcomes, we assessed one as high and two as acceptable quality. We identified 11 reviews that included social media as an exposure. Of these, we rated five as high, five as acceptable, and one as low-quality. We identified 21 reviews related to fossil fuel products and their impacts. 10 focused on air pollution, eight on climate ‘change’, and four on pesticides. We rated 11 reviews as high, nine as acceptable and one as low-quality.

A summary table of the number of reviews included by each exposure and outcome and the number of reviews of each quality. Note numbers may not total the number of reviews included as some reviews reported multiple outcomes.

https://doi.org/10.1371/journal.pgph.0003605.g002

Outlining the characteristics and main findings of each of the reviews included in our umbrella review. * As rated by SIGN criteria ** Includes suicidal ideation, planning, attempt and completed suicide *** Rounded to 2 decimal places by KDC **** Note this is the pooled effect using the fixed effects model as reported by the authors - given the high heterogeneity, it could be more appropriate to use the random effects model CI: Confidence interval; OR: Odds Ratio; PM: Particulate Matter; RR: Risk Ratio; HR: Hazard Ratio.

https://doi.org/10.1371/journal.pgph.0003605.g003

Smoking and mental ill health

We included fourteen reviews examining the impact of smoking on mental health outcomes [ 22 – 35 ].

There was evidence from high quality reviews for associations between second-hand smoke with depression in children and adolescents, second-hand smoke exposure in pregnancy and smoking in pregnancy with postnatal depression, smoking in pregnancy with suicidal ideation, and smoking and suicide. There was evidence from high quality reviews that smoking cessation improved symptoms of depression, anxiety and mixed anxiety and depressive disorder.

Of the included studies examining anxiety, there was evidence from an acceptable quality review that daily smokers had 5 times the odds of panic disorder at age 24 than non-daily smokers (Odds Ratio (OR) 5.1; 95% Confidence Interval (CI) 2.4-10.5) [ 31 ]. The same review reported 15 times the odds for smokers smoking more than 1 pack per day, than under 1 pack, for generalised anxiety disorder (OR 15.58; 95%CI 2.31-105.14). Another acceptable quality review reported two out of four included prospective observational studies found smoking status was predictive of anxiety [ 28 ].

One high [ 23 ] and three acceptable quality [ 24 , 25 , 30 ] reviews examined the association between smoking and depression. In addition, one review of prospective studies found a statistically significant 62% higher odds of depression at follow up among smokers vs never smokers. (OR 1.62 95%CI 1.10-2.40). A smaller effect size was found(32%), when only prospective studies with both baseline and follow up data were included (OR 1.32, 95%CI 1.02-1.71) [ 30 ].

Exposure to secondhand smoke

Three reviews examined second-hand smoke (SHS) [ 23 – 25 ]. One focused on children and adolescents specifically [ 23 ]; in this review there was no pooled effect size but six of the included eight studies found a positive association and a dose-response relationship between SHS exposure and depressive symptoms in children and adolescents (SHS exposure in the home and in public places were included as measures). Two included acceptable quality reviews found statistically significant associations between exposure to SHS and depression - one found 32% higher odds of depressive symptoms in those exposed to SHS (OR 1.32, 95%CI 1.25–1.39) and evidence of a dose-response effect [ 24 ], the other 60% higher odds of depressive symptoms with exposure to SHS (OR 1.60, 95%CI 1.35–1.90) [ 25 ].

Smoking in pregnancy

Two high-quality reviews examined smoking in pregnancy and reported statistically significant results. One found that engaging in prenatal smoking was associated with more than twice the odds of postpartum depression [ 22 ] and the second found that women exposed to second-hand smoke during pregnancy had 77% higher odds of postpartum depression and 75% higher odds of antenatal suicidal ideation [ 26 ]. In addition, one review [ 28 ] found 37 of the 51 studies they included (73%) reported that smoking increased the risk of subsequent depression. Among included prospective observational studies two out of four found smoking status was predictive of anxiety.

Three high-quality systematic reviews reported an association between smoking and suicide outcomes (including suicidal ideation, planning, attempt, and death by suicide) [ 27 , 29 , 32 ]. One review of prospective cohort studies found an 81% higher risk for completed suicide in those who were current smokers at the time of death vs non-smokers (Relative risk (RR) 1.81; 95%CI 1.50-2.19), with the risk of suicide increasing by 24% for each additional ten cigarettes smoked daily. Both these findings were statistically significant [ 29 ]. A second high-quality review, also including only prospective cohort studies, found that, compared with never-smokers, current smokers experienced 2.4 times the risk of death by suicide (RR 2.41; 95%CI 2.08-2.80) and nearly twice the risk of suicidal ideation (RR 1.84; 95%CI 1.21-2.78), with both findings statistically significant [ 27 ]. The third review [ 32 ] replicated these findings for suicidal ideation and death by suicide, with statistically significantly higher odds for current vs non-smokers - current smokers experienced more than twice the odds of suicidal ideation (OR 2.05 95%CI 1.53-2.58), planning (OR 2.36, 95%CI 1.69-30.02) and attempt (OR 2.84; 95%CI 1.49-4.19) and nearly twice the odds of death from suicide (RR 1.83; 95% CI 1.64-2.02).

Three reviews examined the effect of smoking cessation on mental health outcomes [ 33 – 35 ]. Two high-quality reviews [ 34 , 35 ] reported statistically significant reductions in risk of anxiety, mixed anxiety and depression, and depression from baseline smoking to follow-up after cessation. For example, Taylor et al. (2021) [ 35 ] found that the strength of the evidence was greatest for a reduction in risk of in mixed anxiety and depression. One acceptable quality review found lower odds of depression amongst those who had stopped smoking vs current smokers (OR 0.63; 95%CI 0.54-0.75) [ 33 ].

Alcohol and mental ill health

We included eleven reviews examining the impact of alcohol on mental health outcomes [ 36 – 46 ]. There was evidence from high quality reviews for associations between alcohol consumption with depression and suicide.

Amongst reviews examining depression, a high-quality systematic review and meta-analysis including only prospective cohort studies [ 46 ] found a statistically significant 57% higher risk of subsequent symptoms of depression in people with alcohol use disorder (RR 1.57; 95%CI 1.41-1.76). Examining dose effects, compared with non-heavy drinkers, heavy drinkers had a 13% higher risk of developing later depressive symptoms (RR 1.13; 95% CI 1.05-1.22). One acceptable quality review [ 39 ] found that prenatal alcohol exposure (via maternal drinking) was associated with increased depression and anxiety in children aged three years and over in 69% (9/14) of the included studies. One low-quality review examining older adults (≥50 years) [ 41 ] found statistically significant increased hazard ratios for depressive symptoms amongst long-term abstainers (Hazard ratio (HR) 1.14; 95%CI 1.08-1.21) and occasional (HR 1.16; 95%CI 1.10-1.21) and heavy alcohol drinkers (HR 1.22; 95%CI 1.13-1.30) when compared with moderate drinkers.

Two high-quality reviews [ 40 , 45 ] reported statistically significant associations between alcohol consumption and completed suicide. In one review that only included cohort studies, alcohol use was associated with a statistically significantly 74% increased odds (OR 1.74; 95%CI 1.31-2.31) of completed suicide [ 40 ]. A second review including cohort, case-control and cross-sectional studies found higher odds of suicidal ideation (OR 1.86; 95%CI 1.38-2.35), three times higher odds of suicide attempt (OR 3.13; 95% CI 2.45-3.81) and higher odds of completed suicide (OR 2.59; 95% CI 1.95-3.23) for people with alcohol use disorder, all statistically significant [ 45 ]. Amongst the acceptable quality reviews [ 36 , 37 ] examining suicide as an outcome, both found statistically significant associations between acute alcohol ingestion and risk of suicide attempt [ 36 ], as well as between any alcohol use and suicidal behaviours (ideation, attempt and completed suicide) [ 37 ].

Two included reviews looked at population-level impacts on suicidal outcomes. One high quality [ 42 ] and one acceptable quality [ 44 ] review found that alcohol policies restricting access to alcohol were associated with lower rates of suicide at the population level. The high-quality review [ 42 ] included “enforcing minimum legal drinking age (MLDA), dram shop laws, restrictions on hours of trading, privatization, outlets, and complete alcohol bans”. It did not include a pooled effect size but reported on studies that showed decreases of 3 suicides per 100,000 and 55.5 per 100,000, and a RR of 0.91 (95%CI 0.76-1.08) [ 42 ]. The acceptable quality review [ 44 ] included analyses of alcohol price and taxation, minimum legal drinking age laws, outlet density, ‘other alcohol policies’ and evaluations of changes in alcohol policy mix in countries other than the US; again it did not have a pooled effect size but reported lower suicide rates following these policies.

Of the two low-quality reviews with suicide as the outcome, one [ 43 ] estimated a greater suicide risk amongst ‘alcohol abusers’ vs the general population. The other [ 38 ] found that in 27% of suicide post-mortem samples, the blood alcohol level was above zero.

We did not identify any reviews reporting alcohol’s impact on anxiety in adults.

Ultra-processed foods and mental ill health

We included five reviews examining the impact of ultra-processed foods (UPFs) on mental health outcomes. There was evidence from high quality reviews for associations between UPF consumption and depression [ 47 – 51 ].

One high quality review [ 47 ] conducted a meta-analysis of prospective studies and found a 22% higher risk of subsequent depression associated with ultra-processed food consumption (HR 1.22; 95% CI 1.16-1.28). When including all studies, there was a higher odds of depression and anxiety together (OR 1.53; 95% CI 1.43-1.63) and separately (depression OR 1.44; 95% CI 1.14-1.82, anxiety OR 1.48; 95% CI 1.37-1.59).

One high-quality review [ 51 ] found a statistically significant 31% higher risk of depression amongst high consumers of sugar-sweetened beverages when compared with low consumers and with non-consumers (RR 1.31; 95%CI 1.24-1.39). This review also found a dose-response relationship, with an increased risk of 5% for 2 cups per day and 25% for 3 cans per day compared with non-drinkers of sugar sweetened beverages. The second high-quality review [ 49 ] found a statistically significant 8% higher risk of depression amongst people who ate red and processed meats vs those who did not (OR 1.08; 95% CI 1.04-1.12).

An acceptable quality review [ 48 ] analysed several different diets that posed a potential risk for depressive symptoms. The authors referred to these as “pro-inflammatory” diets and they included “sweets; refined flour; high-fat products; red and processed meat” [ 48 ]. The second acceptable quality review [ 50 ] examined dietary sugars but did not exclusively focus on sugar-sweetened beverages. These reviews reported no pooled effect sizes and found mixed results, though several included prospective cohort studies reported positive associations between added dietary sugars and subsequent risk of depression.

No identified reviews in this group examined self-harm or suicide as outcomes or specifically focused on anxiety. Several different mechanisms for these associations were proposed by the included reviews including systemic inflammation [ 48 , 50 ], disruption of the gut microbiota, disrupted dopamine function, insulin resistance, oxidative stress or generation of toxic advanced glycation end-products [ 51 ].

Gambling and mental ill health

We included three reviews examining the impact of gambling on mental health outcomes [ 52 – 54 ]. There was evidence from high quality reviews for associations between gambling with depression, and general mental health outcomes.

One high-quality review [ 52 ], which did not calculate pooled effect sizes, reported on a study that found onset of ‘problem gambling’ was significantly associated with nearly double the odds of incident major depressive disorder (Adjusted odds ratio (AOR) 1.98; 95%CI 1.14-3.44), and almost 4 times the odds of any mental disorder (AOR 3.84; 95%CI 1.89-7.79) at 3.5 years of follow-up [ 52 ]. This review also included several studies which found no association between gambling and later depression or anxiety. The review reported a 15 times higher standardised mortality ratio (SMR) for death by suicide in 20–74-year-olds who had a gambling disorder, compared with the public. For people aged 20-49, the SMR was even higher at 19.3 [ 52 ].

Amongst the acceptable quality reviews, one was not exclusively focused on gambling and mental health and included gaming and conduct problems (which are defined as aggressive or antisocial behaviour that impacts on functioning) in its analysis [ 53 ]. Focusing on gambling and depression, this review did not report any pooled effects, but 10 out of the 12 included cross-sectional studies found statistically significant positive associations between problem gambling and depressive symptoms [ 53 ]. The second acceptable quality review [ 54 ] examined online gambling, including only cross-sectional studies, and found several studies reporting a positive association between online gambling and depressive symptoms [ 54 ].

Social media and mental ill health

We included eleven reviews examining the impact of social media on mental health outcomes [ 55 – 65 ]. There was evidence from high quality reviews for associations between social media with depression, suicidal ideation, and self-harm.

There was mixed evidence for an association between social media use and depression. Of the four high-quality reviews [ 59 – 63 ], one [ 59 ] which focused on adolescents (11-18 years) and included only cross-sectional studies found a weak positive correlation ( r = 0.11 p<0.01). Another high-quality review [ 60 ], including mostly cross-sectional studies, reported mixed results - with a general association between social media and depression, but no pooled effect size - and noted potential confounders and methodological issues within the included studies [ 60 ]. One high-quality review [ 61 ] focusing on young people (10-24 years) examined effect sizes for different measures of online media use (including social media) – with greater effect sizes seen when only including studies that used a measure of ‘addiction’ rather than just time spent. A sub analysis based on media type found the effect size of social media to be significantly smaller than internet use.

Another high-quality review focused on adolescents [ 61 ] found a positive association between time spent on social media and depression symptoms – OR 1.60 (95%CI 1.45-1.75) with a stronger association for girls (OR 1.72; 95% CI 1.41-2.09) than boys (OR 1.20; 95% CI 1.05-1.37).

The finding that time spent on social media had a small significant positive association with depressive symptoms was replicated across four reviews – two high and two acceptable quality, with three reporting the same effect size [ 56 , 59 , 65 ]; r = 0.11 p<0.01, with time spent on social media accounting for around 11% of the depressive symptoms. Among the acceptable-quality reviews, two found statistically significant positive correlations between social media use and depression ( r = 0.11, 95%CI 0.086 – 0.13, and r = 0.11, 95% CI 0.08 - 0.14, p< 0.001) [ 56 , 65 ].

The remainder of the acceptable quality reviews including depression found a mix of positive and negative associations between social media use and depression [ 55 , 57 , 58 ] but for most of the reviews, these associations were positive.

There was evidence of an association between social media use and anxiety. An acceptable quality review [ 58 ] of studies conducted in China reported a significant positive correlation between the two across four included studies, with bivariate correlations ranging between 0.19-0.56.

A high-quality review [ 62 ] found nearly 3 times the odds of suicidal ideation amongst adolescents with “problematic” social media use (a definition was not given for this term), which was statistically significant (OR 2.81; 95%CI 1.72- 4.59) [ 55 ]. In addition, non-significant associations were found between high frequency of social media use and suicidal ideation (OR 1.45; 95%CI 0.95-2.23), suicidal plans (OR 1.47; 95%CI 0.33-6.43) and self-harm (OR 2.03; 95% CI 0.79-5.21).

A range of mechanisms for the associations between social media use and mental ill health were described in these studies, with many mentioning the mediating impacts of insomnia and other sleep disorders [ 60 , 62 ], cyber bullying [ 62 , 64 ] and sexting [ 57 , 62 ].

Fossil fuel products, impact of their use and mental ill health

We included 21 reviews examining the impact of air pollution, ambient temperature increases, and pesticides on mental health outcomes [ 66 – 85 ]. There was evidence from high quality reviews for associations between air pollution with depression, anxiety and suicide; ambient temperature increases with risk of suicide; and pesticides with depression and suicide.

Air pollution and mental ill health.

We found six high quality reviews examining air pollution and depression [ 67 , 70 , 72 – 74 , 81 ]. The reviews found statistically significant but small associations between short term exposure to particulate matter (PM)10 [ 65 , 72 ], PM2.5 [ 67 ], NO2 [ 67 , 70 ] SO2 [ 67 ], or CO [ 67 ] and depression. Two reviews also found associations between long-term exposure to PM2.5 or NO2 and depression [ 67 , 72 ]. One of the reviews estimated a 10% increased risk in depression per 10μg/m3 increase in long term PM2.5 exposure [ 73 ]. While the effect sizes were small, the authors highlighted that the population level exposure contributes to a large burden of mental ill health.

One review focused specifically on the impact of air pollution on perinatal mental health and found an association between PM2.5 and NO2 on postnatal depression [ 74 ].

Two acceptable quality reviews [ 68 , 82 ] and one low-quality one [ 71 ] supported these findings. There was a strong association between air pollution and hospital admissions for depression in an acceptable quality review (no effect size calculated) [ 66 ].

There was also a general association between air pollution and anxiety in these reviews [ 73 , 76 ]. A statistically significant positive association was found between long-term air pollution and anxiety in two studies included within one high-quality review (the review did not perform meta-analyses due to the low number of studies) [ 73 ].

Three high-quality reviews found positive associations between air pollution and suicide. One of these found small positive associations per increased Inter Quartile Range (IQR) in PM2.5, PM10 and NO2 [ 75 ]. The second high quality review found statistically significant pooled effect sizes at days 0-2 per 10μg/m3 increase in PM10 [ 73 ]. The third found small positive associations between suicide and each 10μg/m3 increase in mean NO2 at a lag of 1-3 days in mean SO2 at 1-4 days and mean PM2.5 at 1 day [ 69 ]. Several mechanisms for this were proposed including reduced respiratory function leading to oxidative stress and hypoxia, the latter of which can in turn lead to depleted levels of serotonin [ 69 ]. Other suggested mechanisms were via reduced neurophysiological function, stress response pathways, neuroinflammation, decreased cerebral blood flow, cerebral oedema, and swollen nerve cells [ 75 ].

Temperature increases and mental ill health.

Evidence from high, acceptable, and low-quality reviews found ambient temperature increases to be associated with poor mental health outcomes, including risk of suicide. One high quality review found a 9% increased risk of suicide per increase of 7.1C in temperature [ 75 ]. Reviews also showed ambient temperature increases to be associated with mental ill health in adults. One high quality review found that each 1C increase in temperature led to an increased risk of mental health related mortality and morbidity [ 86 ].

Pesticides and mental ill health.

One high quality review looked at the impacts of pesticide exposure on anxiety, depression, and suicide in farmers [ 86 ] and found an association between exposure to pesticides and depression and suicide. Two acceptable-quality reviews examined pesticide exposure finding evidence of a positive association between pesticide exposure and depression and suicide [ 84 , 85 ]. Both reviews noted inconsistencies in the methodological approaches of included studies and mixed findings.

Wider practices/commercial actions and mental health

We identified two reviews examining impacts of introducing policies focused on reducing consumption in any of these six CDoH areas; these both looked at alcohol policy with suicide as the outcome, as discussed in the alcohol results section. Included policies were changes to alcohol pricing, changes to alcohol availability, changes to drink driving countermeasures, increased taxation, regulation of advertising and anti-alcohol advertising [ 42 , 43 ]. No other identified reviews examined the wider impacts of commercial practices and actions on mental health.

Fig 4 provides an overview of the highest quality of evidence (as rated by our reviewers) for positive relationships between respective exposures and outcomes. In summary, there is evidence from high quality reviews linking: tobacco, social media, UPF, pesticides, climate change and air pollution with anxiety; alcohol, tobacco, gambling, social media, ultra-processed foods, and air-pollution with depression; alcohol, tobacco, gambling, social media, climate change and air pollution with suicide; and social media with self-harm.

This figure outlines the highest quality of review evidence found for each exposure and outcome (as assessed by the review authors). Green reflects high quality, amber acceptable quality and no colour reflects no studies found. *From individual studies (no pooled effect sizes) ** Outcome was offspring anxiety and depression following maternal prenatal exposure.

https://doi.org/10.1371/journal.pgph.0003605.g004

Funding of reviews

Information was also collected on funding of reviews. Funding was not declared in 12 of the included reviews, 15 reported that they had received no funding, 4 that there were no competing financial interests (without outlining funders), and 2 that they had received funding from private foundations. None of the reviews declared any funding from industry but authors in 2 of the reviews reported they had previously received payment from pharmaceutical companies. The remaining 32 received funding from universities, governmental bodies, research organisations (e.g., Medical Research Council, NIHR) or international bodies (WHO and EU). None of the included reviews considered the funding of their included studies or stratified their results depending on industry funding.

To our knowledge, this is the first umbrella review examining the impact of commercial determinants on mental ill health. We found evidence from high quality reviews for associations between alcohol, tobacco, gambling, social media, ultra-processed foods, and air pollution with depression; alcohol, tobacco, gambling, social media, climate change and air pollution with suicide; climate change and air pollution with anxiety; and social media with self-harm. There was a lack of evidence examining wider practices of commercial industries and their impact on mental health.

We found evidence from high quality reviews for associations between five out of the six commodities examined and suicide [ 27 , 40 , 42 , 45 , 52 , 62 , 70 , 76 , 86 ] – the two highest quality reviews with alcohol as an exposure both found significant associations with completed suicide, for instance, while smoking reviews demonstrated a dose-response relationship with this outcome. One review [ 27 ] called for smoking to be included in risk assessments for suicide.

While suicide is clearly an extremely important outcome, it is important also to note the evidence base for other less serious but far more common mental health outcomes, such as anxiety and depression.

Overall, for exposures, there were fewer reviews identified for gambling and ultra-processed foods, with high heterogeneity of study design and definition of exposures. The studies included in the social media reviews were meanwhile mostly cross-sectional in design, with many using self-reported measures of both social media exposure and mental health outcomes, but there was high quality evidence for associations between social media use and depression, as well as suicide. The temporality of some of these relationships were, however, less clear than for other exposures (e.g., tobacco).

These identified gaps in the literature may, in part, reflect the well documented influence of industry on research, including research agendas [ 87 , 88 ]. For example, the limited amount of review-level evidence on gambling and mental health, particularly of high-quality, is remarkable given the nature of these products and their impacts. In this respect, it is noteworthy that the gambling industry has been the main funder of such research in many countries for approximately 40 years [ 89 , 90 ]. It was also striking that only one of the CDoH industries (alcohol) had been the focus of any research analysing relevant policies to tackle its impacts. It is also important to consider the wider mental health burden incurred by those close to someone affected by mental ill-health (for instance, the devastating impact of suicides on family and friend networks), a literature not included in this review. The mental health impacts on affected others should effectively be understood in the same way as other secondary exposures. Further consideration is similarly needed of the mental ill-health associated with the physical health impacts from these commercial determinants (e.g., lung cancer, liver cirrhosis, and violence). Finally, there are likely to also be mental ill-health burdens associated with wider harms such as the impact on communities from clustering of alcohol or gambling venues or the noise created by fossil-fuel based transport systems. Such considerations could inform future systems approaches to research on this topic and more comprehensive mappings of the commercial determinants of health.

Suggested pathways

Several similarities were identified in the potential pathways by which consuming these products may impact on health. For example, for tobacco products, alcohol, and ultra-processed foods - most studies highlighted the role of inflammation. For products that are not directly consumed into the body, e.g., social media or gambling, the pathways for mental health outcomes may be via wider impacts such as relational or financial factors.

Yet this review also identified key gaps in the evidence base in relation to pathways around wider commercial impacts on mental health. Such an agenda will also require a shift in how harm - and pathways or chains of harm - are conceptualised, as well as greater appreciation of the differences between how health and disease impact on individuals versus populations. Further research should focus on wider systems, practices and pathways through which commercial actors influence physical and mental health.

Methodological challenges

This review identified many methodological challenges in measuring commercial determinants of health. Even when considering relatively easier exposures, such as smoking or alcohol, there are substantial differences in approaches to measurement. It becomes more challenging still when considering more difficult exposures, such as air pollution and ultra-processed food consumption; when consumption is part of our everyday experience, it can be difficult to recall or measure accurately. For example, variable measurements were used for alcohol, including both self-reported unit intake and blood alcohol levels, while some studies used “ever use” of alcohol as an exposure. This latter measure obscures important insights given the substantial proportion of the population that has consumed alcohol at any point in their lives. Indeed, substantial methodological challenges are involved in measuring alcohol consumption, with intake often underreported and misremembered - alcohol consumed in the home, for instance, is unlikely to be served in recommended or standard measures. Social media was another exposure with specific methodological challenges. There are two components to social media that can be difficult to disentangle: (1) the platforms on which users can engage and the ways these platforms influence people’s use of social media and its roles in their lives, and (2) the content created by the users themselves to which others are then exposed.

Use of the term “problem” user was found across unhealthy commodity industries and was ill defined in all of these. Likewise, research has shown that terms such as “responsible drinking” are often poorly defined and can be used to provide pro industry framings of product harm [ 91 ]. The authors of one high-quality review [ 81 ] highlight key methodological challenges in the climate change/air pollution space, particularly due to the linking of events to climate change, the difficulties in temporal measurements before and after an event and the difficulty of controlling for confounders. Finally, it should also be noted that there is substantial overlap between different industries, even within our review; for example, the food industry is involved in pesticide usage as well as the production of highly processed food products.

Strengths and limitations

This umbrella review is the first to consider the commercial determinants of mental ill health as a primary focus. In drawing together and mapping the evidence both for the unhealthy commodities and wider practices, we can identify where the evidence is strongest and where the evidence gaps are most clear. This makes this review useful for informing development of frameworks of mental health, as well as development of mental health policy.

Our study included both middle, and low-income countries in our search terms and so was not limited just to high income countries.

We made some changes to the review design following pilot searches. Firstly, we established it was not feasible to stratify the results by PROGRESS-Plus due to the number of studies identified, and substantial variations across the evidence base. Following reflection and discussion between the review group about the complexity of obesity-related research, including the confounding role of physical activity, it was agreed that obesity would no longer be included as an outcome. Addiction was also excluded as an outcome due to the large volume of search results returned that were judged not relevant for this review (e.g., focusing on the addictive properties of social media). Following discussion, in the context of this review, addiction seemed to be more of a confounder or a mediator of these relationships. In classing it as an outcome or an exposure, the focus of the review might therefore have shifted to examine whether products were addictive or if addiction itself was associated with mental ill health.

As we limited the included reviews to those that focused specifically on our exposures and outcomes of interest during the search, to avoid a large amount of irrelevant material, we may have excluded some additional findings that were not included in specific reviews. However, we felt that reviews specifically focused on our exposures and outcomes of interest were likely to include most of any relevant evidence. Finally, including only papers in the English language does mean that we could have missed findings from papers published in other languages. We were also unable to comprehensively examine inequalities in commercial determinants of mental ill health. This was due to both the number of papers available and the small number that considered differences in demographic groups. Although wider search terms were included for all industries, this review was also limited to six key industries. It did not include other key and interlinking industries such as the meat and dairy, chemical, beauty, and pharmaceutical industries. Many of these industries have overlapping practices and actors, so separating them can be challenging. For example, although online gambling was included, online gaming was mostly excluded, despite a large overlap between the two and the fact that many online gaming products include gambling elements. Examining the impact of fossil fuels was also particularly challenging – given, for instance, there are clear links with climate change and pollution, but fossil fuels are not the only cause. Finally, we restricted this umbrella review to include only reviews and not primary research papers. This may have led to the exclusion of relevant or new research (that is yet to be included in a review). Throughout the review, discussion with the wider review group aimed to guide these decisions. Overall, this umbrella review is the first that the authors are aware of that maps the evidence base for the ‘commercial determinants’ of mental health. While previous reviews have focused on individual unhealthy commodities (e.g., tobacco products), analysing these commodities within the context of a wider range of industries can lead to a greater understanding of the concept of CDoH, as well as the need to act across various industries and settings to reduce health-harming practices, and improve mental health.

Conclusions

In conclusion, there is strong evidence that smoking, alcohol, and air pollution are associated with mental ill health. The evidence bases for ultra-processed foods, gambling, social media, and climate change are less developed but already include high-quality reviews demonstrating associations between these industries and various negative mental health outcomes. There is a striking lack of research examining the wider actions of corporations on mental health outcomes. Given these findings, commercial determinants should be routinely included within frameworks to examine and improve mental health.

Supporting information

S1 fig. search strategy medline..

Search strategy for our umbrella review using Medline.

https://doi.org/10.1371/journal.pgph.0003605.s001

S2 Fig. Search strategy Embase.

Search strategy for our umbrella review using Embase.

https://doi.org/10.1371/journal.pgph.0003605.s002

S3 Fig. Search strategy PsychInfo.

Search strategy for our umbrella review using PsychInfo.

https://doi.org/10.1371/journal.pgph.0003605.s003

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« Unhealthy food »

Jan 08, 2020

170 likes | 234 Views

« Unhealthy food ». Made by Tsyglakova Tatiana Kasyrgulova Aida form 9v school 32 Norilsk 2007.

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• flavoring additives
• fizzy drinks
• children eat depends
• pupils receive 50 roubles

Presentation Transcript

«Unhealthy food»

Made by Tsyglakova Tatiana Kasyrgulova Aida form 9v school 32 Norilsk 2007

Healthyeating is very important in our days. The great amount of different productshave appeared on Russian market lately. Most of these products became very popular. But are all of them useful? What the children eat depends on their parents. Healthy eating is the basis of physical and mental health. The problem of this research lies in the fact that the students don’t follow the right eating, don’t know enough about some unhealthy products and eat them very often. Problem

The aim of research: to substantiate the negative influence of some food on human’s organism. The task: to collect information on this problem using a sociological poll. The object of the research: the students of the 5 – 10 classes.

The topic of research: the teenagers’ attitude to their health trough different food. The methods of research: an opinion poll. The hypothesis of the research: the students have little knowledge in this sphere of life, they don’t have enough habits of healthy eating.

Unhealthy products Fizzy drinks Cereal or soup in tins (1-2 times a month) Noodles for fast preparation (1-2 times a month) Mashed potatoes for fast preparation (once a month) Crisps and pieces of dried bread Mayonnaise (once a week) Saveloys or sausages (once a week) French fries Chewing gum (2-3 minutes 1 -2 times a day)

The most harmful products The most harmful food is a sausage with lemonade. 1. Sweet fizzy drinks are not made for slating the thirst but for provoking it. They have enormously much sugar. There are not less than five teaspoons of sugar in one glass of such drink. 2. Potato crisps, which are made from mashed potato. It is a mixture of carbohydrates and fats and artificial flavoring additives. 3. Sweet chocolate sticks. The combination of great amount of sugar and different chemical additives provides the highest calorie content and a wish for eating them again and again. 4. Saveloys, sausages, boiled sausage, patesand many other products with so called hidden fats. They have lard, internal fat, pig’s skin, which form 40 % of the weight. They are masking as meat with the help of flavoring additives.

Diseases Allergy diseases Gastritis and other gastro-intestinal diseases Dermatitis Obesity Vitamin deficiency

The main products

Unhealthy food

Eating in school canteen Every day 54% of pupils receive 50 roubles for eating in school canteen from their parents. 46% of pupils don’t eat at school because they don’t have money for this purpose. The pupils prefer to buy pizzas, rolls and tea.

The pupils’ wishes about eating in the school canteen 1) to reduce prizes of the products; 2) to make the range of products more various; 3) to make free packed lunches of rolls and tea or juice after the 4th lesson.

Gastro-intestinal diseases

Conclusion The pupils don’t have good habits about healthy eating. They don’t take care of their health, don’t follow a right diet and daily routine. The most students know about harmful influence of some products but continue to eat them very often. Some parents don’t have enough time to prepare good food for their children because they are overworked and they find the way out of situation buying junk food. Digestive disorders of the pupils are increasing at school.

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