Mednotes

L4 Metabolism Overview of the role of diet in health and disease

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tagsmetabolism, lecture
aliasesOverview of the role of diet in health and disease

18 min read

Overview

This lecture surveys the burden that diet places on health in affluent societies (New Zealand in particular), then works through the evidence linking diet to three major disease groups — type 2 diabetes, cardiovascular disease, and cancer — before turning to why the obesogenic food environment has proved so hard to change and what might be done about it. It explicitly excludes infant feeding, micronutrient deficiencies, food insecurity, and childhood obesity (covered elsewhere). The throughline is that diet is the single largest modifiable risk factor for health loss in New Zealand, that both genetic susceptibility and a “toxic” modern food environment contribute to the obesity/diabetes epidemic, that structured lifestyle intervention can meaningfully prevent and even reverse type 2 diabetes, and that translating this evidence into population-level change is hampered by industry tactics, confusing food labelling, and unresolved questions about whose responsibility prevention actually is.

Scope of the lecture

The lecture states it will not cover:

  • Infant feeding, including breastfeeding
  • Mineral and micronutrient deficiencies, especially iron, calcium, iodine, folate, vitamin D
  • Food insecurity
  • Topics covered in other lectures, e.g. childhood obesity

Images of severely malnourished children were shown only to illustrate food insecurity/malnutrition as a topic being explicitly set aside, not as content to be examined further [slide does not elaborate].

Diet as a driver of health loss in New Zealand

In the NZ Burden of Diseases, Injuries and Risk Factors Study (2013 data), health loss (DALYs) by leading condition differs by sex: for males the top contributors are CHD, back disorders, COPD, and lung cancer; for females, back disorders, CHD, depressive disorders, and COPD lead.

Slide 2 marks certain condition bars (e.g. diabetes, stroke, bowel cancer for males; breast cancer, stroke, lung cancer for females) with red arrows, but no legend or caption on the slide explains what these arrows signify — inferred only (possibly diet-related conditions), not confirmed.

Looking at risk factors rather than disease categories (2013 data), diet is the single largest contributor to health loss among all measured risk factors (~9.5% of total DALYs), ahead of high BMI (~9%), tobacco use (~8.5%), high systolic blood pressure (~8%), high fasting plasma glucose (~5.5%), high total blood cholesterol (~4.5%), alcohol use (~4%), low glomerular filtration rate (~3.5%), low physical activity (~3%), and drug use (~2%).

Diet is the single largest contributor to health loss in New Zealand among all measured risk factors — larger than high BMI, tobacco, or high blood pressure.

The “diet” risk factor is itself a composite of specific dietary patterns:

  • Low consumption of: fruit & vegetables, whole grains, fibre, total PUFA, ω3 PUFA, calcium
  • High consumption of: sodium, red meat, trans fat, sugar

Separately, tracking health loss attributable to BMI versus tobacco use from 1990–2015 shows tobacco-attributable DALYs declining gradually (from ~113,000 to ~95,000) while BMI-attributable DALYs rose steadily throughout (from ~75,000 to just over 100,000), with BMI overtaking tobacco as the larger contributor around 2010–2012.

Globally, of NCD deaths under age 70, cardiovascular disease and cancer together account for the majority of causes (cardiovascular disease is the largest single segment, just over a third; cancers roughly a third), with chronic respiratory diseases, digestive diseases, and diabetes making up smaller shares.

New Zealand adult obesity rose from about 10% in 1977 to roughly 14% by 1987, then more steeply to about 30–31% by 2012, with a hand-annotated (not originally plotted) continuation suggesting further rise toward 2021.

The red hand-drawn line extending the obesity trend to 2021 on Slide 9 is an annotation, not an original data point — its exact numeric value is not given.

Combined overweight-plus-obesity prevalence rose over the same period for both sexes: men from about 51% (1977) to about 68% (2011); women from about 37% (1977) to about 59% (2011), with men consistently higher than women throughout.

Internationally (OECD, 2012 data), New Zealand ranks near the highest for adult obesity (~31%), behind the United States (~35%) and Mexico (~32%), and above the OECD(34) average of 18.4%; lowest rates are in India, Indonesia, China, Japan, and Korea (~2–5%). Tracking obesity rates over time (1972–2012) across OECD countries, the USA rises highest throughout (to nearly 35% by 2012); Mexico, Australia, and Canada also rise steeply (to the mid-20s–33%); Korea remains lowest (under 5%) throughout.

Genetic versus environmental contributions to obesity

A quoted position frames the epidemic as an interaction of genetic susceptibility and environment: “the genetic background loads the gun, but the environment pulls the trigger” — i.e. although there is a genetic basis for obesity and diabetes, the current epidemic reflects the failure of ancient genes to cope with a modern “toxic” food/activity environment (Bray, Physiology & Behaviour, 2004).

Single-gene mutations associated with massive obesity (rare, monogenic causes) include: melanocortin-4 receptor, leptin, leptin receptor, pro-opiomelanocortin, and prohormone convertase 1.

Type 2 diabetes: prevalence, prediabetes, and lifestyle prevention

Prevalence and prediabetes. NZ diabetes prevalence (as at December 2015) rises with age across all ethnic groups, peaking in the 70–79 age band, then declining slightly in the oldest band: Pacific people and Indian populations peak highest (around 50–52%), Māori peak lower (~37%), and European/Other lowest (~18–19%).

Slide 5's left-hand graph has no visible legend or axis labels, so its source population or units cannot be confirmed.

Type 2 diabetes is increasing, with significant differences between ethnicities. In New Zealand, 25% of the adult population have prediabetes, carrying a 70% lifetime risk of progression to type 2 diabetes. Diet and lifestyle interventions can work, but translation of existing evidence into practice has been disappointing. (An iceberg image is used to convey that diagnosed/visible diabetes is a small fraction of the much larger, largely hidden burden of prediabetes.)

Projected type 2 diabetes prevalence by ethnicity (2018–2040) shows Pacific ethnicity with the highest and steepest rise (from ~10% in 2019 to ~16% by 2040); Asian and Māori rising from ~5% to ~7–8%; Other rising slightly to ~5–6%. Age-standardised comparisons (2018 vs 2040) show the same pattern more starkly: Pacific Island ~16% (2018) rising to ~25% (2040); Māori and Asian ~7–8% rising to ~10–11%; Other ~3–4% rising to ~4–5%.

Lifestyle prevention evidence. The Finnish Diabetes Prevention Study (Tuomilehto et al., N Engl J Med, 2001) set five lifestyle intervention targets for people with impaired glucose tolerance:

  • Weight reduction ≥ 5%
  • Moderate-intensity physical activity ≥ 30 min/day
  • Dietary fat < 30% of total energy (TE)
  • Dietary saturated fat < 10% TE
  • Dietary fibre ≥ 15 g/1000 kcal

Diabetes incidence during follow-up fell steeply and consistently as the number of targets achieved (the “success score,” 0–5) increased: approximately 34% incidence at score 0, ~19% at score 1, ~10% at score 2, ~5% at score 3, ~2% at score 4, and ~1% at score 5.

The DiRECT trial (Lean et al., Lancet, 2018) — a primary-care-led weight management trial for remission of type 2 diabetes — found at 12 months:

  • ≥15 kg weight loss achieved: 0% control vs 24% intervention (p<0.0001)
  • Diabetes remission: 4% control vs 46% intervention (odds ratio 19.7, 95% CI 7.8–49.8, p<0.0001)
  • A clear dose-response relationship between weight loss and remission: 0 kg lost → 0% remission; <5 kg → 7%; 5–10 kg → 34%; 10–15 kg → 57%; ≥15 kg → 86% (odds ratio per kg lost 1.32, 95% CI 1.23–1.41, p<0.0001)

DiRECT demonstrates that substantial, sustained weight loss can produce remission of type 2 diabetes, not merely improved control — remission rates rose steeply with the amount of weight lost.

Benefits of weight loss (summary).

  • Moderate weight loss (5–10%): decreased risk of diabetes and cancer mortality, reduced blood pressure, improved lipid profile, reduced rate of progression from prediabetes to diabetes, improved diabetes control, improved mobility
  • Substantial sustained weight loss (15 kg): remission of type 2 diabetes

Cardiovascular disease and diet

Age-standardised ischaemic heart disease (IHD) mortality in a long time series (1950–2012) rose to a peak around 1968 — coinciding with tobacco smoking prevalence peaking in 1963 (>50%) and saturated fat intake exceeding 40% of calories — then fell by more than two-thirds since that peak, attributed in part to the “Cardiac Care Revolution” (advances in medical/surgical treatment).

Despite this decline, New Zealand’s position is unfavourable relative to comparator countries: 2013 age-standardised IHD mortality placed NZ at a mid-to-upper rate (~140 per 100,000, versus a low of ~35 in Japan and a high of 404 in the Slovak Republic); and NZ’s percentage decline in IHD mortality from 1990–2013 (-53%) was real but smaller than many comparator countries (e.g. Denmark -77%, Netherlands -73%).

The precise numeric values aligned to New Zealand on both panels of Slide 20 are difficult to confirm exactly at the image resolution used, though the approximate values and overall message (NZ's decline is real but lags behind many comparators) are clear.

Cancer and diet

Evidence classification (WCRF/AICR, 2018) for the strength of the association between body fatness and cancer risk by site:

  • Convincing: oesophagus, pancreas, liver, colorectum, breast (postmenopausal), endometrium, kidney
  • Probable: mouth/pharynx/larynx, stomach, gall bladder, ovary, prostate

Dose-response analyses (Reynolds et al., 2019, The Lancet) show that as total dietary fibre intake increases, effect size (relative risk) declines across three outcomes — all-cause mortality, type 2 diabetes, and colorectal cancer — i.e. higher fibre intake is associated with lower risk across all three.

A proposed metabolic mechanism links poor diet to cancer risk independently of the classical “two-hit” tumour suppressor gene (TSG) model: normally, cancer requires both copies of a TSG (e.g. via genetic/epigenetic inactivation of the remaining wildtype copy) to be lost. An alternative route — a “metabolic bypass of Knudson’s two-hit paradigm” — proposes that oncogenes drive the Warburg effect (increased glycolysis), raising methylglyoxal (MGO); diabetes, metabolic disorders, or diet are proposed contributors to this increase. Elevated MGO can cause haplo-insufficiency of BRCA2 (impairing its function even with an intact gene copy present), leading to episodic mutation and tumorigenesis — a route to cancer that bypasses the need for both TSG copies to be lost.

The obesogenic food environment

Major changes to food and physical activity environments over the past 50 years:

  • Growth of the food industry
  • Changes in food composition: new additives (e.g. high-fructose corn syrup, palm oil)
  • Increasing portion size and availability
  • Snacks and energy-dense foods, ultraprocessed foods
  • Growth of marketing and promotion
  • Increased sedentary behaviour
  • Decreased physical activity / active transport
  • Lack of sleep

Marketing tactics illustrated include: vending machines and soft drink promotion in youth-facing settings; historical print advertisements pairing sugary drinks with food to imply nutritional balance (e.g. “a pie and L&P is a well-rounded meal”); and personalised branding of sugary drinks (e.g. bottles printed with individual names) to increase appeal.

A quoted WHO position (Dr Margaret Chan, 2013) states that public health must contend with “Big Food, Big Soda, and Big Alcohol,” which use shared tactics to resist regulation — front groups, lobbies, promises of self-regulation, lawsuits, and industry-funded research that confuses the evidence — alongside gifts and grants that present these industries as respectable corporate citizens. The quote asserts that no country has reversed its obesity epidemic across all age groups, framing this as a failure of political will rather than individual willpower.

No country has yet reversed its obesity epidemic across all age groups — framed in the lecture as a failure of political will, not individual willpower.

Despite multiple international policy frameworks existing (e.g. WHO’s Global Action Plan for NCDs, the “Ending Childhood Obesity” report, WHO recommendations on marketing food to children, and “Best buys” interventions for NCD prevention), implementation of these frameworks is described as “very patchy.”

Photographic contrasts are used to illustrate food environment differences: a bookshop shelf of numerous commercial fad diet books (illustrating proliferation of fad diets); wholegrain versus refined white bread; and the “Hungry Planet” photo project comparing a week’s food supply per family across countries — the UK and USA families’ food is dominated by packaged/processed items (cereal, crisps, chocolate, soft drinks, fast food), while Ecuador and Mali families’ food is largely fresh/whole (vegetables, grains, fruit, legumes, staples).

A satirical cartoon (Glasbergen, 2008) depicts a patient dismissing “eat less and exercise more” as itself “the most ridiculous fad diet,” used to comment on how basic dietary advice is often perceived as inadequate or oversimplified.

Food labelling

A newspaper opinion piece (Derek Bussell, ODT, 21 May 2011) criticises food labelling as confusing — the writer cannot recall whether a given value (e.g. 10 mg of a nutrient) is high or low, and suggests a simplified 1–10 scoring system where 1 is very low and 10 is very high would be easier to interpret. This is shown alongside a Health Star Rating label (3.5 stars, with an Energy/Saturated Fat/Sugars/Sodium/Nutrient panel) and a US-style Nutrition Facts label (with %DV columns for 2,000 and 2,500 calorie diets).

The left edge of the newspaper clipping is cropped in the source, so parts of several lines of the article text are missing and cannot be transcribed in full; an accompanying handwritten annotation is also partially cut off.

Whose responsibility is prevention?

The lecture poses an open question — “Who are ‘WE’?” — regarding responsibility for addressing diet-related disease, listing candidate parties: government (national or local), the health sector, health professionals, individuals, and business. It also poses the framing question of whether the goal should be prevention and/or cure [slide does not elaborate on an answer].

Self-test

  1. List the risk factors ranked by contribution to health loss (DALYs) in New Zealand (2013 data), and state which one is the single largest contributor.
  2. Define prediabetes in terms of the New Zealand adult prevalence figure given, and state its associated lifetime risk of progression to type 2 diabetes.
  3. List the five lifestyle intervention targets used in the Finnish Diabetes Prevention Study.
  4. Describe the relationship shown between “success score” (targets achieved) and diabetes incidence in the Finnish Diabetes Prevention Study.
  5. Describe the DiRECT trial’s design and its two primary outcomes at 12 months (weight loss and diabetes remission).
  6. Explain the dose-response relationship between weight loss and diabetes remission found in DiRECT.
  7. Distinguish “moderate” weight loss from “substantial sustained” weight loss in terms of their described health benefits.
  8. Explain the quoted view on how genetics and environment jointly contribute to the obesity epidemic.
  9. List the single-gene mutations mentioned as causes of massive obesity.
  10. Describe the historical trend in IHD mortality from 1950 to 2012 and the two factors proposed to explain its peak around 1968.
  11. Explain why, despite a substantial decline in IHD mortality, New Zealand’s position among comparator countries is still considered unfavourable.
  12. List the cancer sites classified as having a “convincing” versus “probable” association with body fatness.
  13. Describe the proposed “metabolic bypass” mechanism by which diet-related metabolic changes could contribute to cancer, distinct from the classical two-hit tumour suppressor gene model.
  14. Describe the dose-response relationship between dietary fibre intake and the three outcomes examined by Reynolds et al. (2019).
  15. List the major changes to the food and physical activity environment over the past 50 years described in the lecture.
  16. Explain the industry tactics described as used by “Big Food, Big Soda, and Big Alcohol” to resist regulation.
  17. A patient tells you they struggle to interpret whether a nutrient value on a food label is high or low. What alternative labelling approach does the lecture’s cited source suggest would resolve this, and what existing label format is shown alongside it as a contrast?
  18. A 58-year-old Pacific patient with impaired glucose tolerance asks whether lifestyle change is worth the effort given their ethnicity’s rising projected type 2 diabetes prevalence. Using the evidence presented in the lecture (Finnish DPS and DiRECT), what would you tell them about the achievable impact of lifestyle and weight-loss intervention?
  19. Integrating the risk factor and disease-burden data with the diet-composition and mechanistic content: explain how “diet” as a single risk factor category links through to specific disease outcomes (cardiovascular disease, type 2 diabetes, cancer) via the mediating factors identified in the lecture (e.g. BMI, glycolysis/MGO, fibre intake).

Answers

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