Diet, obesity, lifestyle and cancer prevention: epidemiologic perspectives

Diet, obesity, lifestyle and
cancer prevention:
Epidemiologic perspectives
Graham A Colditz, MD DrPH
Niess-Gain Professor
Chief, Division of Public Health Sciences
November, 2017

Department of Surgery
Division of Public Health Sciences
Outline
Review evidence on contribution of diet,
obesity, lifestyle and in particualr,
increasing burden of obesity on cancer
Identify:
Issues
Gaps in knowledge
Opportunities

Lifestyle: high income countries
Cause
% cancer
caused
Magnitude
possible
reduction
Time (yrs)
Smoking 33
Overweight/obesity 20
Diet 5
Lack of exercise 5
Occupation 5
Viruses 5-7
Family history 5
Alcohol 3
UV/ionizing radiation 2
Reproductive 3
Pollution 2 Colditz et al, Sci Transl Med 2012

Cause
% cancer
caused
Magnitude
possible
reduction
Time (yrs)
Smoking 33 75%
Overweight/obesity 20 50%
Diet 5 50%
Lack of exercise 5 85%
Occupation 5 50%
Viruses 5-7 100%
Family history 5 50%
Alcohol 3 50%
UV/ionizing radiation 2 50%
Reproductive 3 0
Pollution 2 0

Cause
% cancer
caused
Magnitude
possible
reduction
Time (yrs)
Smoking 33 75% 10-20
Overweight/obesity 20 50% 2-20
Diet 5 50% 5-20
Lack of exercise 5 85% 5-20
Occupation 5 50% 20-40
Viruses 5-7 100% 20-40
Family history 5 50% 2-10
Alcohol 3 50% 5-20
UV/ionizing radiation 2 50% 2-10
Reproductive 3 0 N/A
Pollution 2 0 N/A

Time course: lung & total mortality
Current smoker:
continuing

Medical interventions proven to
prevent cancer: high-income
Intervention
Target
Magnitude of
reduction
Time (yrs)
Aspirin Colon mortality 40% 20+
SERMs Breast incidence 40-50% 5+
Salpingo
oophorectomy
Familial breast cancer 50% 3+
Screening for
colorectal cancer
Colon cancer mortality 30-40% 10
Viruses - HPV Cervical cancer incidence 50-100% 20+
- Hep B Liver cancer incidence 70-100% 20+
Mammography Breast cancer mortality 30% 10-20
Serial CT lung Lung cancer mortality 20% 6+
Colditz et al, Sci Transl Med 2012

Histologically confirmed cervical
abnormalities, Vic, Australia
CIN2, CIN3
Brotherton et al MJA 2016

Pancreatic cancer
Yachida Nature 2010; Luebeck EG. Nature 2010

Summary of evidence: Adolescent exposures
relation to risk of BBD and breast cancer
Lifestyle Relative Risk BBD Breast Cancer
(premenopausal)
Alcohol
Peak Growth Velocity
Height
Nuts
Fiber
Carotenoids Fruit and veggies
Vegetable protein
Family history
Physical activity
Colditz Bohlke Berkey Br Ca Res Treat 2015, Colditz & Bohlke 2014

Alcohol intake, ages 18-22,
incident proliferative BBD
Alcohol
intake
(grams/
day)
Cases
(678)
Person-
year
RR (95% CI)
None 155 64,827 1.0 reference
0.1-4.9 193 78,365 1.11 (0.89, 1.38)
5.0-14.9 236 88,310 1.36 (1.09, 1.69)
>15 30 9519 1.35 (1.01, 1.81)
p, trend <0.01
Liu et al. – Pediatrics, 2012

Alcohol before first pregnancy,
NHSII
Liu, Colditz, Tamimi JNCI 2013

Adolescent fiber & proliferative BBD:
NHSII
Su et al. Cancer Causes Control 2010

Are we there yet?

Obesity and cancer, time line -
• 1990s WHO, US Dietary Guidelines, adopt
common cut points
• 2002 IARC report
• 2008 et seq WCRF report
• 2016 update of IARC report

IARC 2002 and Calle 2003
• Review of evidence on weight obesity and
physical activity in relation to cancer
• Calle: ACS cohort published after the
IARC review panel

IARC 2002
“Sufficient evidence in humans for cancer-
preventive effect of avoidance of weight
gain for cancers of the colon, esophagus
(adenocarcinoma), kidney (renal cell),
breast (postmenopausal), and corpus uteri”
Translate: Obesity causes cancer
IACR Handbooks of Cancer Prevention Vol 6, 2002

Review of Evidence, IARC 2002
Obesity
Level of
Evidence
Risk Increase Associated with Obesity

Small
(RR 1.09-1.34)
Moderate
(RR 1.35 - 1.99)
Large
(RR 2.0 - 4.9)
Very Large
(RR 5.0+)

Convincing
Colon Breast Esophagus
Uterus
Kidney

Probable

Calle et al 2003

Workgroup reviewed measures of adiposity; animal models;
mechanisms; and epidemiologic evidence.
Concluded lack of body fatness lowers risk,
or obesity causes cancer.
NEJM August 25, 2016

Evidence evolving
From only a couple of prospective cohorts in
2002, adding ACS mortality in 2003
• Now evidence from 30 to 50 or more
prospective cohorts
• Pooled analysis of individual participant
data from studies addressing BMI and less
common cancers

Why prospective studies and
pooled data
• Measure adiposity and risk of subsequent
cancer
• Avoid weight change due to disease

Individual participant data –
pooled analysis
IPD meta-analyses can improve the quality of data
and the type of analyses that can be done and
produce more reliable results (Stewart and Tierney
2002). For this reason they are considered to be a
‘gold standard’ of systematic review.
In fact, IPD meta-analyses have produced
definitive answers to clinical questions, which
might not have been obtained from summary data.
Cochrane Handbook Ch 18 and IPD methods

GI
• Gastric cardia
• Liver
• Pancreas
• Gall bladder

Pancreas
More than 20 prospective studies and case-
control studies indicating a positive dose-
response relation. Observed in the large
majority of studies and in both genders.
Compared to normal weigh, the RR for
overweight was 1.18 (1.03-1.36) and for
obesity 1.47 (1.23-1.75), estimated from
pooled analysis of 14 cohorts [Genkinger 2011].

Genkinhger et al 2011
2135 cases
During 846,340 py
Forest plot of RR for
BMI >30 vs 21-22.9
Baseline BMI

BMI in early adulthood

Relative risk of ovarian cancer by BMI and HT use
Collaborative Group on Epidemiological Studies of Ovarian Cancer (2012) Ovarian Cancer and Body Size: Individual Participant Meta-Analysis
Including 25,157 Women with Ovarian Cancer from 47 Epidemiological Studies. PLoS Med 9(4): e1001200. doi:10.1371/journal.pmed.1001200
http://journals.plos.org/plosmedicine/article?id=info:doi/10.1371/journal.pmed.1001200
Never use HT
Ever use

Evidence, 2016

Risk Increase Associated with Obesity

Level of
Evidence
Small
(RR 1.09-1.34)
Moderate
(RR 1.35 - 1.99)
Large
(RR 2.0 - 4.9)
Very Large
(RR 5.0+)

Convincing
Ovary Colon Breast Esophagus
Thyroid Gastric cardia
Liver
Kidney Uterus
Gall bladder
Pancreas
Meningioma
Multiple
myeloma

Probable
Male breast
Fatal prost.
Diffuse Large B-
cell lymphoma

Time
course
obesity
Increase in childhood
adiposity

Pancreatic
cancer US incidence 1992 to
2014
Age 20 to 49
Rising incidence
0.9% per year
(significant)

Colorectal
cancer US incidence 1992 to
2014
Age 20 to 49
Rising incidence
1.7% per year
(significant)

Childhood and early adult
adiposity
• Often consistent with adult adiposity and
risk
• Analysis not always clear
• Methods, correlated variables, and interpretation
• Challenges in breast cancer
• Inverse relation with adiposity at ages 5, 10, before menarche
• Weight gain increases risk
• How does childhood adiposity reduce risk for life?

0 10 18 30 47 Age
(years)
Premenopausal Postmenopausal
50
+kg
Post-menopausal
Breast Cancer
Risk
-
1 0.80 0.98
1.36 (weight change from 18 to attained)
Adiposity
1.37 (weight change after menopausal to attained)
Reference: Rosner, B., Eliassen, A. H., Toriola, A. T., Chen, W. Y., Hankinson, S. E., Willett, W. C., ... & Colditz, G. A. (2017). Weight and weight changes in early
adulthood and later breast cancer risk. International journal of cancer, 140(9), 2003-2014.
+kg
+kg
Age
(years)
-
1
Pre-menopausal
Breast Cancer
Risk
0.66 0.74
1.0

0 10 18 30 47 Age
(years)
Premenopausal Postmenopausal
50
+kg
Post-
menopausal
Breast Cancer
Risk
-
1 0.80 0.98
1.36
1.36 (weight change from 18 to attained)
Adiposit
y
1.37 (weight change after menopausal to attained)
Reference: Rosner, B., Eliassen, A. H., Toriola, A. T., Chen, W. Y., Hankinson, S. E., Willett, W. C., ... & Colditz, G. A. (2017). Weight and weight changes in early adulthood and later breast cancer
risk. International journal of cancer, 140(9), 2003-2014.
+kg
+kg
Age
(years)
-
1
Pre-menopausal
Breast Cancer
Risk 0.66 0.74
1.0
ER-/PR-
Breast Cancer Risk
RR / 30kg
0.73
(0.55-0.98)
0.70
(0.46-1.05) Weight change unrelated to risk

Top priorities to advance the
science –obesity and cancer
Improved (consistent) approaches to
modeling weight gain across life course and
cancer risk
Quantify benefits of weight loss
Measures of adiposity
• Do we have it right, do measures vary by
age; race/ethnicity; region of the world

Top priorities to advance the
science – diet, lifestyle and cancer
Improved (consistent) approaches to
modeling exposure in time course of cancer
development
Measures of diet lifestyle in childhood
adolescence
• Can biomarkers in blood banks replace
recall of childhood adolescent exposures?

Behavioral, Social, and Policy interventions
that impact Cancer Prevention
Intervention Target Type of Ix Evidence
review
Reduce tobacco
use
Children and
Adolescents
Smokers to quit
Combined
Pharmaco/behavioral Ixs
Smoke-free policies
Tobacco taxes
Surgeon
General
Increase physical
activity
Individuals and
community norms
Urban design
Stairs and workplace
Surgeon
General
Reduce Obesity Population School & work environment
Physical activity
Food & beverage
IOM report
2012
Limit alcohol intake Population Taxes WHO
Reduce UV exp Children, AYA All of above WHO

Wall-e
Captain
Will we all have
access to
driverless cars?
What will our
cancer risk be?

Diet, obesity, lifestyle and cancer prevention: epidemiologic perspectives

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