App · iOS 16 and later
A 12-item questionnaire that reads food and lifestyle habits against BMI, so that a raised risk of visceral fat can be flagged even where body weight alone looks healthy.
Twelve questions about the last 12 months, each answered on a six-point frequency scale from Never to Daily or most days. Items 1–6 cover food habits and score 0–30; items 7–12 cover lifestyle habits and score 0–30. The total runs 0–60.
The app also asks for your height and weight so it can calculate BMI. The score on its own describes habits; read against BMI, it says something more useful.
Two thresholds cross to give four outcomes: obesity with increased risk of visceral fat; absence of obesity and decreased risk; absence of obesity with increased risk, the “skinny fat” pattern; and obesity with decreased risk. These are screening categories, not diagnoses.
We anticipate the thresholds forming that matrix will be a Food and Lifestyle Score of 20 or above and a BMI of 30 or above. Both will be confirmed in the original study, to be conducted soon.
Existing psychology scales and medical equations capture eating behaviour, or a snapshot of visceral fat as it is now. Neither predicts the habits likely to build visceral fat over time in people whose weight looks unremarkable. This scale was written to close that gap.
Visceral fat is metabolically active tissue. It drives chronic, low-grade inflammation that raises the risk of type 2 diabetes, cardiovascular disease, and cancer — and a healthy BMI is a poor guarantee against carrying it.
Each completed assessment is saved with its scores, BMI, and category. If you opt in to the research programme, you can compare your scores against other participants in Australia and the United States, once at least ten other participants in a country have taken part.
The Food and Lifestyle Scale is a new instrument developed by Australian Psychological Research Pty Ltd. The original study has not yet been conducted. We anticipate a cut-off score of 20 or above, together with a BMI of 30 or above, will create the matrix of the four categories — and these categories will be confirmed in the original study, to be conducted soon.
The foods and lifestyle habits most strongly associated with obesity were identified from recent meta-analytic and systematic reviews. Each item maps to one habit, set out below with the mechanism, the supporting evidence, and the two references behind it — the same references listed in the app.
Item 1. How often did you drink sugary drinks? e.g., soft drink, cordial, energy drinks, sports drinks, sweetened iced tea, or fruit juice drinks.
Energy consumed as liquid produces weaker satiety signalling than the same energy eaten as solid food, so sugary drinks tend to be added to daily intake rather than substituted into it. Fructose is metabolised largely in the liver, where high loads favour de novo lipogenesis and fat deposition around the abdomen. Pooled prospective cohorts and randomised trials point the same way, making this one of the few dietary exposures graded as moderate-quality evidence in major dietary guideline reviews.
SourcesNguyen, Michelle, et al. 2023. "Sugar-Sweetened Beverage Consumption and Weight Gain in Children and Adults: A Systematic Review and Meta-Analysis of Prospective Cohort Studies and Randomized Controlled Trials." American Journal of Clinical Nutrition 117 (1): 160–74. DOI: https://doi.org/10.1016/j.ajcnut.2022.11.008.
Deierlein, Andrea L., et al. 2024. "Sugar-Sweetened Beverages and Growth, Body Composition, and Risk of Obesity: A Systematic Review with Meta-Analysis." Nutrition Evidence Systematic Review. Alexandria, VA: U.S. Department of Agriculture. DOI: https://doi.org/10.52570/NESR.DGAC2025.SR23.
Item 2. How often did you eat a main meal that was takeaway, home-delivered, or a ready-made packaged meal? e.g., burgers, pizza, fried chicken, food-court meals, or frozen or microwave meals.
Meals prepared outside the home are typically larger and more energy dense than meals cooked at home, and portion size is set by the vendor rather than the eater. A high fat-to-carbohydrate ratio has been shown to increase appetite and passive overconsumption independent of sugar content, so the effect is not only a matter of total calories. Cohort evidence links sustained fast-food consumption to greater weight gain over follow-up, and the association holds across different national food environments.
SourcesHodge, Rebecca A., et al. 2023. "Consistent and Changing Consumption of Fast-Food and Full-Service Meals and 3-Year Weight Change in a Large Population Cohort Study." American Journal of Clinical Nutrition 117 (2): 392. DOI: https://doi.org/10.1016/j.ajcnut.2022.12.006.
He, Jinke, et al. 2025. "Fast Food Consumption and Risk of Non-Alcoholic Fatty Liver Disease: A Systematic Review and Meta-Analysis." Frontiers in Public Health 13. DOI: https://doi.org/10.3389/fpubh.2025.1600826.
Item 3. How often did you eat packaged snack foods? e.g., chips, crisps, biscuits, chocolate, lollies, or pastries.
Ultra-processed snack foods combine refined carbohydrate, fat and salt in ratios that occur rarely in whole foods and that delay satiety signalling, allowing large amounts to be eaten quickly. Where they are eaten between meals rather than at them, the energy is largely additive: intake at the next meal falls by less than the snack contributed. Pooled prospective cohorts show a dose-related association with obesity that is clearer than the one with overweight, which is consistent with a graded effect.
SourcesVitale, Marilena, et al. 2024. "Ultra-Processed Foods and Human Health: A Systematic Review and Meta-Analysis of Prospective Cohort Studies." Advances in Nutrition 15 (1). DOI: https://doi.org/10.1016/j.advnut.2023.09.009.
Tin, Justin, et al. 2025. "Ultra-Processed Food, Obesity, and Colon Cancer: A Systematic Review and Meta-Analysis." World Journal of Gastrointestinal Oncology 17 (2): 101211. DOI: https://doi.org/10.4251/wjgo.v17.i2.101211.
Item 4. How often did you eat processed meat? e.g., bacon, ham, sausages, salami, deli meats, or hot dogs.
Processed meats are energy dense, high in saturated fat and sodium, and are commonly eaten in combinations that raise the energy density of the whole meal. Proposed mechanisms include a pro-inflammatory effect of saturated fat and sodium-driven fluid and appetite changes. The association with adiposity replicates across observational cohorts, and the item is easy to recall accurately.
SourcesDaneshzad, Elnaz, et al. 2021. "Red Meat, Overweight and Obesity: A Systematic Review and Meta-Analysis of Observational Studies." Clinical Nutrition ESPEN 45: 66–74. DOI: https://doi.org/10.1016/j.clnesp.2021.07.028.
Mohamadi, Anahita, et al. 2023. "Inflammatory Markers May Mediate the Relationship between Processed Meat Consumption and Metabolic Unhealthy Obesity in Women: A Cross-Sectional Study." Scientific Reports 13. DOI: https://doi.org/10.1038/s41598-023-35034-6.
Item 5. How often was white bread, white rice, or white pasta the main starch in your meal?
Milling strips fibre and much of the micronutrient content from grains, raising the glycaemic index of the resulting food and producing a faster, larger rise in blood glucose and insulin after eating. The sharper post-prandial fall that follows returns hunger sooner, encouraging earlier and larger subsequent intake. The item asks which starch was on the plate rather than asking people to classify foods as refined, because a concrete question recalls better.
SourcesJenkins, David J. A., et al. 2024. "Association of Glycaemic Index and Glycaemic Load with Type 2 Diabetes, Cardiovascular Disease, Cancer, and All-Cause Mortality: A Meta-Analysis of Mega Cohorts of More Than 100,000 Participants." Lancet Diabetes & Endocrinology 12 (2): 107–18. DOI: https://doi.org/10.1016/S2213-8587%2823%2900344-3.
Sonestedt, Emily, and Nina Cecilie Øverby. 2023. "Carbohydrates — A Scoping Review for Nordic Nutrition Recommendations 2023." Food & Nutrition Research 67. DOI: https://doi.org/10.29219/fnr.v67.10226.
Item 6. How often did you have two or more alcoholic drinks in one day? e.g., a drink is a can or bottle of beer, a glass of wine, or a shot of spirits.
Ethanol supplies 7 kcal per gram in a form that does not trigger compensatory reductions at later meals. Because the body has no way to store alcohol it is oxidised ahead of fat, so fat oxidation is suppressed for several hours while alcohol is cleared, and alcohol also disinhibits eating. Imaging work is the reason this item targets a threshold rather than any drinking: alcohol tracks visceral fat specifically rather than total fat, and the effect concentrates in heavier drinkers.
SourcesChesters, Joel, Matt J. Neville, and Fredrik Karpe. 2026. "Greater Visceral Fat Mass Accumulation with High Alcohol Consumption." International Journal of Obesity 50 (6): 1360–63. DOI: https://doi.org/10.1038/s41366-026-02030-5.
Golzarand, Mahdieh, Asma Salari-Moghaddam, and Parvin Mirmiran. 2022. "Association between Alcohol Intake and Overweight and Obesity: A Systematic Review and Dose-Response Meta-Analysis of 127 Observational Studies." Critical Reviews in Food Science and Nutrition 62 (29): 8078–98. DOI: https://doi.org/10.1080/10408398.2021.1925221.
Item 7. How often did you sleep less than 7 hours in a night?
Sleeping less than seven hours lowers leptin, the hormone signalling satiety, and raises ghrelin, the hormone signalling hunger — a combination described in the literature as a dual stimulus toward increased intake. Short sleep also lengthens the eating window, shifts food preference toward energy-dense options, and reduces the likelihood of physical activity the following day. Prospective cohorts link it to central adiposity specifically rather than to body weight alone, which is what makes this item relevant to a scale built around visceral fat.
SourcesKohanmoo, Ali, et al. 2024. "Short Sleep Duration Is Associated with Higher Risk of Central Obesity in Adults: A Systematic Review and Meta-Analysis of Prospective Cohort Studies." Obesity Science & Practice 10 (3): e772. DOI: https://doi.org/10.1002/osp4.772.
Gresser, Delaney, et al. 2025. "The Impact of Sleep Deprivation on Hunger-Related Hormones: A Meta-Analysis and Systematic Review." Obesities 5 (2): 48. DOI: https://doi.org/10.3390/obesities5020048.
Item 8. How often did you finish a main meal in less than 15 minutes?
Satiety signalling is slow: gut hormones including cholecystokinin, GLP-1 and peptide YY take roughly fifteen to thirty minutes to register centrally, so a meal finished inside fifteen minutes is over before the feedback that would have stopped it arrives. Faster eating also means less chewing, which reduces the oro-sensory exposure that contributes independently to satiation. Meta-analyses report that fast eaters are around twice as likely to have obesity as slow eaters, and the association extends to metabolic syndrome and to central obesity.
SourcesOhkuma, Toshiaki, et al. 2015. "Association between Eating Rate and Obesity: A Systematic Review and Meta-Analysis." International Journal of Obesity 39 (11): 1589–96. DOI: https://doi.org/10.1038/ijo.2015.96.
Yuan, Shu-qian, et al. 2021. "Association between Eating Speed and Metabolic Syndrome: A Systematic Review and Meta-Analysis." Frontiers in Nutrition 8: 700936. DOI: https://doi.org/10.3389/fnut.2021.700936.
Item 9. How often did you eat because you were feeling bored, stressed, down, or lonely rather than hungry?
This item asks about eating in response to boredom, stress, low mood or loneliness rather than physical hunger. Acute stress activates the HPA axis, and elevated cortisol shifts food preference toward energy-dense, highly palatable foods, while negative affect depletes the self-regulatory capacity needed to override that preference. Meta-analytic evidence links self-reported emotional eating to elevated BMI in adults, and it appears to mediate part of the association between depressive symptoms and obesity.
SourcesLederman, N., et al. 2026. "Emotional Eating and Weight Status: A Systematic Review and Meta-Analysis across Adolescents and Adults." British Journal of Health Psychology 31: e70070. DOI: https://doi.org/10.1111/bjhp.70070.
Vasileiou, Vasiliki, et al. 2023. "Emotional Eating among Adults with Healthy Weight, Overweight and Obesity: A Systematic Review and Meta-Analysis." Journal of Human Nutrition and Dietetics 36 (5): 1922–39. DOI: https://doi.org/10.1111/jhn.13176.
Item 10. How often did you eat a meal or snack within 3 hours of going to bed?
Insulin sensitivity, glucose tolerance and diet-induced thermogenesis all follow a daily rhythm and are lower in the evening, so identical food eaten late is handled differently from the same food eaten earlier. A controlled trial found that a late dinner raised overnight glucose and impaired fat mobilisation compared with an earlier one of identical composition. Eating close to bedtime also shortens the overnight fasting window during which fat oxidation predominates, and cohort evidence links night eating to metabolic syndrome.
SourcesChaput, Jean-Philippe, et al. 2023. "The Role of Insufficient Sleep and Circadian Misalignment in Obesity." Nature Reviews Endocrinology 19 (2): 82–97. DOI: https://doi.org/10.1038/s41574-022-00747-7.
Peters, Beeke, et al. 2024. "Meal Timing and Its Role in Obesity and Associated Diseases." Frontiers in Endocrinology 15: 1359772. DOI: https://doi.org/10.3389/fendo.2024.1359772.
Item 11. How often did you spend 3 hours or more sitting in front of a screen, not related to work or study? e.g., TV, video games, computer, or scrolling on a smartphone.
Extended uninterrupted sitting suppresses lipoprotein lipase activity in muscle, reducing clearance of triglycerides from the blood. Screen use also displaces time that would otherwise involve movement, and it reliably co-occurs with snacking and with exposure to food advertising. Those in the highest screen-time brackets are meaningfully more likely to become overweight or obese, with a dose-response pattern across categories.
SourcesHaghjoo, Purya, et al. 2022. "Screen Time Increases Overweight and Obesity Risk among Adolescents: A Systematic Review and Dose-Response Meta-Analysis." BMC Primary Care 23: 161. DOI: https://doi.org/10.1186/s12875-022-01761-4.
Jang, Hajin, et al. 2024. "Recreational Screen Time and Obesity Risk in Korean Children: A 3-Year Prospective Cohort Study." International Journal of Behavioral Nutrition and Physical Activity 21: 112. DOI: https://doi.org/10.1186/s12966-024-01660-0.
Item 12. How often did you go a whole day without at least 30 minutes of activity that raised your breathing or heart rate? e.g., brisk walk, swimming, or heavy physical chores.
Prolonged inactivity suppresses lipoprotein lipase in skeletal muscle, the enzyme that clears triglycerides and glucose from the blood, and it does so through a pathway distinct from the one exercise activates. A single bout of activity elsewhere in the day does not fully offset a day spent sitting, which is the basis of the "active couch potato" phenomenon, where regular exercisers who are otherwise sedentary still carry elevated metabolic risk. The item is framed around whether any moderate activity occurred at all, rather than around sitting time, so that it distinguishes a person who sits all day and trains from one who sits all day and does nothing.
SourcesLiang, Zhi-de, et al. 2022. "Association between Sedentary Behavior, Physical Activity, and Cardiovascular Disease-Related Outcomes in Adults: A Meta-Analysis and Systematic Review." Frontiers in Public Health 10: 1018460. DOI: https://doi.org/10.3389/fpubh.2022.1018460.
Duncan, Mitch J., et al. 2023. "The Associations between Physical Activity, Sedentary Behaviour, and Sleep with Mortality and Incident Cardiovascular Disease, Cancer, Diabetes and Mental Health in Adults: A Systematic Review and Meta-Analysis of Prospective Cohort Studies." Journal of Activity, Sedentary and Sleep Behaviors 2: 26. DOI: https://doi.org/10.1186/s44167-023-00026-4.