Articles 1
eas
oe
.
Associations of the glycaemic index and the glycaemicload
+
“_@®
with risk of type 2 diabetes in 127 594 people from
20 countries (PURE): a prospective cohort study
A Jenkins, Mahshid Dehghan, Kristie Srichaikul, Sumathy Rangarajan, Andrew Mente, Viswanathan Mohan,
Victoria Miller, David
Sumathi Swaminathan, Rosnah Ismail, Maria Luz Diaz, Rekha M Ravindran, Katarzyna Zatonska, Ahmad Bahonar, Yuksel Altuntas, Rasha Khatib,
Patricio Lopez-Jaramillo, Afzalhussein Yusufali, Karen Yeates, Jephat Chifamba, Romaina Iqbal, Rita Yusuf, Elizabeth Catherina Swart, Hu Bo,
Guoliang Han, Xiaocong Li, Khalid F Alhabib, Annika Rosengren, Alvaro Avezum, Fernando Lanas, Salim Yusuf, on behalf
and Rural Epidemiology (PURE) study investigators*
of the Prospective Urban
Summary
Background The association between the glycaemic index and the glycaemic load with type 2 diabetes incidence is Lancet Diabetes Endocrinol 2024
controversial. We aimed to evaluate this association in an international cohort with diverse glycaemic index and published online
glycaemic load diets.
Methods
April 5, 2024
https://doi.org/10.1016/
Py
A
sons
'$2213-8587(24)00069-X
The PURE study is a prospective cohort study of 127594 adults aged 35-70 years from 20 high-income, See Online/Comment
scorns
middle-income, and low-income countries. Diet was assessed at baseline using country-specific validated food jc)
frequency questionnaires. The glycaemic index and the glycaemic load were estimated on the basis of the intake of _s9713-2587(24)00003-7
seven categories of carbohydrate-containing foods. Participants were categorised into quintiles of glycaemic index — ~Members|isted
and
in the appendix
glycaemic load. The primary outcome was incident type 2 diabetes. Multivariable Cox Frailty models with random _ (pp 5-6)
intercepts for study centre were used to calculate hazard ratios (HRs).
Population Health Research
Institute, McMaster University,
Findings During a median follow-up of 11-8 years (IQR 9-0-13-0), 7326 (5-7%) incident cases of type 2 diabetes aime
apenas
no,
Spangarjan
seAMentePhO,
occurred. In multivariable adjusted analyses, a diet with a higher glycaemic index was significantly associated with
a higher risk of diabetes (quintile 5 vs quintile 1; HR 1-15 [95% CI 1-03-1.29). Participants in the highest quintile of _ProfSVusuF0Phi; Department
the glycaemic load had a higher risk of incident type 2 diabetes compared with those in the lowest quintile (HR 1-21, of Medicine, McMaster
95%
BMI C11-06-1-37). The glycaemic index was more strongly associated with diabetes among individuals with a higher (eee
sii por snes,
1-10 (quintile 5 vs quintile 1; HR 1-23 [95% CI 1-08-1-41)) than those with a lower BMI (quintile 5 vs quintile 1; pepartmentof Nutitional
[0-87-1- 39]; p interaction=0- 030).
Sciences and Medicine,
Faculty of Medicine,
Temerty
Interpretation Diets with a high glycaemic index and a high glycaemic load were associated with a higher risk of YnvesibefTorenio.
glycaemic
pAJenkinsMDPhD);
incident type 2 diabetes in a multinational cohort spanning five continents. Our findings suggest that consuming low (prof
index and low glycaemic load diets might prevent the development of type 2 diabetes.
Lika Shing Knowledge
Institute, St Michael's Hospital,
Funding Full funding sources are listed at the end ofthe Article.
Copyright © 2024 Published by Elsevier Ltd. All rights reserved.
er ecanae
K Stichaikul MD);Toronto 3D
knowledge Synthesisand
Clinical Trials Unit, Toronto,
Introduction
The glycaemic index ranks carbohydrate-containing QvConate Prof Alenkins):
In 2021, there were an estimated 537 million cases of foods based on the postprandial blood glucose response.” Modification Centre,
type 2 diabetes, with approximately three-quarters of cases The glycaemic load describes both the quality and StMichael’s Hospital, Toronto,
occurring
and middle-income
countries.’ quantity of carbohydrate in awoe
food, and is computed as ON.
Canadaof Endocrinology
(ProfD A Jenkins)
.
Division
Over the inpastlow-income
three decades, diabetes prevalence has the product of the glycaemic index and the amount jjsrabotam, and
markedly increased in all regions of the world and is of carbohydrate available in a serving.” Several meta- Hospital, Toronto,st Michae!t
projected
ON, Canada
to reach 643 million by 2030 without effective analyses of prospective cohort studies have reported that _ (Prof AJenkins); Department
interventions.
Preventing
the
onset
of
global priority, given its serious consequences,
diabetesis includa major _ load
diets arewithassociated
a high glycaemic
glycaemic omasterusivesiy
ofHealth Research Methods,
with a index
higherandriska high
of diabetes."
ing major burden of disease, and health-care costs.’
Randomised controlled trials have shown that lifestyle
A systematic review by Reynolds and colleagues," which Hamilton, ON, canada
largely informed the recent WHO guideline on carbo- _(AMente), Department
interventions, including dietary modifications, are effec- hydrate intake," concluded that, compared with the Pisbstelosy MaisDiabetes
of
tive
with ata both
and controlling
evidenceindex
for dietary
and whole
gly- _p,Mohan‘s
diabetes
high preventing
glycaemic index
and a highdiabetes.“’
glycaemic Diets
load caemic
and thefibre
glycaemic
load grains,
might the
be less
specialties
have
entre,
chennai,
suggested to be associated with increase in useful measures of carbohydrate quality. In contrast, !ndia(Y
insulinbeenresistance
MohanDSc);StJohn’s
cell function, which asuming
2024 meta-analysis
of large cohorts found that con- seh ato Acdenyof
in turn might increaseandtheimpaired
a low glycaemic diet had similar beneficial
risk ofdiabetes."”
www.thelancet.com/diabetes-endocrinology Published online April 5, 2024 https://doi.org/10.1016/S2213-8587(24)00069-X
1
l Articles
Health Sciences, Bangalore,
India (Prof
Medgar
SSwaminathanP
teuiyefiedene
hD); Researchi
Evidence beforethis
n context. study
Universiti Kebangsaan, Kuala AWHO-sponsored meta-analysis on carbohydrate quality
Lumpur Malaysia
(ProfRismall
PH Estudios
.
127594 participants from 20 countries who did not have a
previous history of diabetes. Consistent with most
concluded thatthere was low quality evidence forthe effects of observational studies, but in contrast to 2023 dietary
the glycaemicindex on the risk ofdiabetes. In contrast, a2024 recommendations for carbohydrate intake in adults, we
vspesaria, Agenting meta-analysis of large cohort studies found that the association found that consuming a diet with a high glycaemic index and
(Luz Diaz MD); Department
of Health Sciences,
between the glycaemic index and diabetes was similartothe _a high glycaemic load was associated with an increased risk of
widely accepted associations for fibre and whole grain intake.
diabetes. We also found that the glycaemic index was most
stele
henntunshoy We systematically searched PubMed fromJan 1, 1960, to
strongly associated with the risk oftype 2 diabetes among
Health Action byPeople, July 1, 2023, for relevant articles on the glycaemic index and the _ individuals with a higher BMI.
Trivandrum, Kerala ndia
glycaemic load, using the search terms "glycemic index’,
implications
capetnentetihaam
alltheavailableevidence
—
gh/cemicload",
“carbohydrate
quality’,
and
“diabetes”.
Most
The
prevalenceofof diabetes
is markedly increasing, particularly
Medical University, Wroclaw,
studies that evaluated the association ofthe glycaemic index
in low-income and middle-income countries, andthe
(KZatonskamp);, andthe glycaemic load and diabetes were done in North
identification of modifiable risk factors is urgently needed.
enCardiovasc ‘America or Europe, and a few studies were done in China, Japan, findings
suggestthat consuming a low glycaemic index diet
Teearh incite ohana
might lower the risk ofdiabetes, especially among people with
esearch
Our
Poland
University of Medical Sciences,
ian,
an SaherHD):
Turkey, Faculty of Medicine,
Added value of this study
Weandinvestigated
the association of
the glycaemic load and risk of type 2 diabetes in
the glycaemic index
a higher BMI and in countries where high carbohydrate diets
are traditionally consumed.
Istanbul Sisli Hamidiye Etfal
Health Training Research
chlcvindgyand associations on the risk of diabetes as consuming a diet Procedures
Metabolism, sisliIstabul, high in fibre or whole grains.” Given the uncertainty Data on demographic factors, socioeconomic status (eg,
Turkiye
(rot AtwntssMO): regarding the importance ofthe glycaemic index and the _ education, employment, income, and household wealth
Institute, Milwaukee, wi,usa glycaemic load on diabetes prevention, we examined index), lifestyle (eg, physical activity, smoking, and diet),
PhO); Institute
(Rhatib
Community
ofthe associations between the glycaemic index and the health history and comorbidities (eg, hypertension,
and PublicHealth, glycaemic load with incident type 2 diabetes using data cardiovascular disease, diabetes, and cancer), medication
palestine
thatgeMedica!
te te
fromProspective
127594 individuals
countries enrolled
history questionnaires
of type 2 diabetes
were colResearchinstitute,
Urban andfrom
Rural20 Epidemiology
(PURE)in _ use,
lectedand
usingfamily
standardised
and procedures.
School, Universidadde study. We hypothesised that higher glycaemic index and Physical assessments included standardised measureSantander, Bucaramanga, glycaemic load diets, by virtue of their postprandial ments of height, weight, waist and hip circumference,
(Prof topesjornata Pho glycaemic effect," would be associated with higher and blood pressure. Education was categorised as low (no
Tamani Foundation, incidence of diabetes.
or primary school education), intermediate (secondary
Matemnwe, Zanzibar, Tanzania
school education), or high (completion of trade school,
(AYusufali MD);Divisionof ~Mlethods
college, or university). Data on household ownership
Nein Kingston,
nanttameny,
ON, canada The
design and
of the PURE study have been of
motorbike)
was used
to create television,
a household
Studydesign
andmethods
participants
14 assets and(eg, land
electricity,
car, computer,
or
(Profk Yeates MD); Department described previously.” The PURE study is a prospec- wealth index.” Data on physical activity were collected
of Biomedical Sciences, tive cohort study done in seven geographic regions _ using the long form of the International Physical Activity
UniversityofZimbabwe (North America and Europe, South America, the Questionnaire, and computed as the total of transporta-
(/chifamba DPhil); Department Middle East, South Asia, China, Southeast Asia, and tion, occupation, housework, and recreational physical
of Community HealthSciences, Africa). Adults aged 35-70 years at baseline were activity reported in metabolic equivalent minutes per
Agevrerteath
Khan universityKarchi
enrolled from 631 urban and rural communities using week. Total physical activity was categorised as low
Pepuavonsna country-specific recruitment and sampling methods (<600 metabolic equivalent minutes per week), moderate
Development, Independent
(appendix p 7). In this analysis, we include data on
(600 to <3000 metabolic equivalent minutes per week), or
University, Dhaka, Bangladesh
individuals from 20 countries: four high-income
high (£3000 metabolic equivalent minutes per week).
(Prof vss PRD): Department countries (Canada, Saudi Arabia, Sweden, and the Smoking status and alcohol intake were categorised as
Universityofthe Westerncape, United Arab Emirates), 11 middle-income coun- never, former, or current.
Belville South Africa tries (Argentina, Brazil, China, Chile, Colombia, Iran, __ Follow-up visits were done via telephone or in-person
(Prof€ Catherina Swart PhD); Malaysia, occupied Palestine territory, Poland, South visits at least every 3 years. Standard case-report forms
iomenaca
Researchand Africa, and Tiirkiye), and five low-income countries _ were used to collect incident type
Canterfortetiovessie
2 diabetes cases during
(Bangladesh,inTheeach
India,
Tanzania,
and follow-up.
analysis
included andall outcome
events that
PekingDiseases,
Zimbabwe).
studystudywasPakistan,
approved
by participants
local ethics
occurred
asThisof19April
3, 2023.
Union FuwaiHospital,
Medical College committees
centre,
and all
At baseline,
country-specific
nine region-specific
andchinese Academy of yrovided written informed consent.
2
(in India) validated food frequency questionnaires
www.thelancet.com/diabetes-endocrinology Published online April 5, 2024. https://doi.org/10.1016/S2213-8587(24)00069-X
Articles 1
(FFQ) were used to collect habitual food and beverage Plasma was immediately analysed for glucose locally or Medical Sciences, Beijing, China
intake. The food lists for the FFQs included between stored at 20°C to -70°C and shipped in temperature- (Prof #Bo PhD, G Han MM,
98beverage,
to 220 food
items per questionnaire. For each food or controlled containers for central measurements. Plasma *¥inc odes tana aha4
a standard portion size was used. Participants glucose was measured by standardised enzymatic Cardiac Center, College of
were asked how often on average during the previous year__ methods using hexokinase or glucose oxidase.
Medicine, ng Saud University
they had consumed a portion of each food item with
Medica Cy King a0
possible
frequencies
ranging
from
never
to
six
or
more
_
Statistical
analysis
habia Peat ance MBBS)
times per day. The daily intake of each food or beverage We summarised continuous variables as means (SD) _pepartmentof Molecolar and
was calculated by multiplying the daily frequency of intake and categorical variables as percentages. We calculated Clinical Medicine, institute of
by the portion size. Daily nutrient intakes were calculated _ the hazard ratios (HR) for incident type 2 diabetes using Medicine, Sahlgrenska
using the US Department of Agriculture food-composition multivariable shared frailty Cox regression with random _(avenyunsitirense
composition tables for local dishes. Details about the simultaneously adjustsfor clustering
for country
by study
and centre
region).(which
The Gothenburg,
(ProfARosengren
SwedenMD);
development
the appendix (pand11).validation
of thewithFFQs
are provided
random-effectIn our
termanalysis,
was assumed
normally
IntemationalResearch
enter
Participants
implausible
baselinein distributed.
the origintoandbe start
times EUNISA,
‘Séo Paulo, SP Brazil
database (release 18 and 21) and country-specific food- _ intercepts to account
energy intake (<500 or >3500 kcal per day for women and__ were the date of recruitment. The end time was all out- (prof Avezum MD);
<800 or >4200 kcal per day for men) were excluded from come events that occurred as ofApril 3, 2023. Participants _ Universidad
the
dela Frontera,
study.
The main exposures were the glycaemic index and the
who died (11875 [9- 3%] of 127594) or were lost to follow- Temuco, Chile (Prof Lanas MD)
up (150 [<1%] of 127594) were censored in the analysis. _Covespondenceto
glycaemic
the load. Details of the methods used to calculate Estimates of HRs and 95% Cis are presented for quintiles {to's MillePopulation
Heath
glycaemic index and the glycaemic load have been _ using the lowest glycaemic index or the lowest glycaemic University, Hamilton,
published.” International glycaemic index tables and load group as the reference. The proportionality ont8.2x2, canada
databases of tropical foods were used to obtain the
assumption of the Cox model was assessed by visual
vittoriamiller@phri.ca
glycaemic index for carbohydrate-containing foods _ inspection of initial stratified Kaplan—Meier curves by the _S¢¢ Online
forappendix
occurring at least four times on the FFQs.” The mean of _ variables in the model, and by log (-log survival) versus
the same foods from two or more studies was used when __ log time plots after fitting Cox models. The log-linearity
possible, and in cases where no data were found, the
glycaemic index value for a similar food was used. We used
the bread scale that uses 50 g of carbohydrate from white
bread as the control (glycaemic index value of 100). We
assumption was assessed by visual inspection of the
Martingale residuals plot. Model 1 adjusted for age, sex,
and centre. Model 2 further adjusted for urban or rural
location, education level, country-income category
of carbohydrate-containing food and beverage groups:
non-legume starchy foods (glycaemic index-93), sugarsweetened beverages (87), fruit (69), fruit juice (68), non-
activity, waist-to-hip ratio, family history of diabetes,
blood pressure medication use, and daily energy intake.
Model 3 included the covariates included in model 2 with
on weighted means of the individual food and beverage
grain intake (g per day; for glycaemic index exposure
categories of carbohydrate-containing food and beverage
groups are provided in the appendix (p 15). On the bread
scale, we considered a glycaemic index value of less than
79 as low, 79-99 as moderate, and more than 100 as high.
The selection of covariates was done a priori based on
expert knowledge of clinically meaningful risk factors
for diabetes, as well as a reviewing previous studies
to identify suspected or established factors associated
beverage groups by the net carbohydrate consumed in
each group to estimate each participant's mean glycaemic
index. To calculate each participant's glycaemic load, the
80% of participants had complete covariate data, with
missingness ranging from 0-4% for education level to
98% for family history of diabetes (appendix p 60). We
assigned a glycaemic index value to seven categories (economic region), wealth index, smoking status, physical
starchy vegetables (54), legumes (42), and dairy (38), based further adjustment for fibre intake (g per day), whole
groups (appendix pp 17-24). The definitions for the only), and dietary protein intake (percent energy per day).
We weighted the glycaemic indexes of the seven food and _ with either the exposure or outcome.” Approximately
glycaemic index was multiplied by the net carbohydrate
(grams per day) intake and divided by 100.*
Outcomes
The primary outcome was incident type 2 diabetes,
used a multiple imputation procedure with ten rounds of
imputation incorporating all covariates in the primary
analysis (demographic, lifestyle, dietary covariates, and
study centre) to impute missing data for covariates. To
check the robustness of our multiple imputation, we also
defined as a diagnosis of diabetes by a physician, oral _report complete-case analyses.
In subgroup analyses, we assessed the associations
fasting plasma glucose level of 7-0 mmol/L or more _ between the glycaemic index and the glycaemic load and
antidiabetic agents or insulin use, or a documented
(126 mg/dL) during follow-up in individuals without a
history of diabetes at baseline. Venipuncture was done by
diabetes by economic region (high-income countries,
middle-income countries, or low-income countries) and
centrifuged at the local site within 2 h of collection.”
America, the Middle East, South Asia, China, Southeast
health professionals, and the blood sample was _ by geographic region (North America and Europe, South
www.thelancet.com/diabetes-endocrinology Published online April 5, 2024 https://doi.org/10.1016/S2213-8587(24)00069-X
3
i Articles
Q1(n=25519)
Q2(n=25519)
Q3(n=25519)
Q4(n=25519)
Q5 (n=25518)
512(97)
504(98)
50:0(9:9)
497 (98)
49-5 (96)
10114 (39-6%)
15405 (60-4%)
10706 (42.0%)
14813 (58.0%)
10133 (39.7%)
15386 (603%)
10959 (42-9%)
14560 (571%)
11.792 (46.2%)
13726 (53-8%)
Urban residence
16 613 (65.1%)
16 383 (64-2%)
15286 (59:9%)
11688 (45:8%)
6533 (25-6%)
Low education level
9289 (36-4%)
10386 (40.7%)
10361 (40-6%)
10922 (428%)
13882 (54.4%)
Current smoker
4415 (17.3%)
4695 (18-4%)
5155 (20.2%)
5920 (23.2%)
7068 (27.7%)
Low physical activity
3904 (15.3%)
4440 (17-4%)
4466 (17.5%)
4747 (186%)
5231 (205%)
Demographics
Age, years
Sex
Male
Female
Wealth index
BMI, kg/m?
066 (089)
0:33 (097)
-0.084 (0:93)
-038 (089)
-0.67 (082)
272(53)
088 (0.089)
26.8
(5-4)
0-88 (0.088)
25:6
(5:1)
087 (0-084)
24-6
(47)
0-86 (0.079)
23:8
(45)
0-86 (0.077)
Family history of
7783 (305%)
6890 (270%)
4925 (193%)
3292 (12.9%)
2246 (8-8)
Blood pressure
4517 (17.7%)
3675 (14-4%)
2782 (109%)
1990 (7.8%)
1480 (5-8%)
North America and
South America
Europe
8375 (328%)
7478 (293%)
4562 (17-9%)
6637 (26-0%)
930 (36%)
4556 (17-9%)
116 (0.5%)
1555 (61%)
14 (0.05%)
485 (1.9%)
Middle East
5079 (19-9%)
4869 (19.1%)
1201 (47%)
141 (0.6%)
12 (0.05%)
South Asia
3442 (135%)
4914 (19.3%)
6019 (23-6%)
6356 (24.9%)
5961 (23.4%)
China
584 (23%)
2953 (11.6%)
9514 (373%)
13.839 (54.2%)
15.240 (59-7%)
Southeast Asia
296 (1.2%)
786 (3.1%)
2045 (8.0%)
2340 (9.2%)
2092 (82%)
Dairy, g per day
303 (172-518)
223 (86-322)
105 (21-240)
32 (0-137)
0(0-31)
Fruit, g per day
256 (135-443)
192 (97-318)
128 (59-225)
86 (40-152)
44 (21-83)
Waist-to-hip ratio
diabetes
medication use
Geographic region
Africa
265 (1.0%)
798 (3.1%)
1254 (4-9%)
1172 (4-6%)
1714 (67%)
Dietary factors
Fruit juice, g perday
51 (10-214)
20 (0-107)
2 (0-33)
0(0-16)
0(03)
Vegetables, g per day
337 (198-508)
250 (152-339)
236 (135-257)
247 (415-255)
180 (58-250)
Starchy foods,gperday
294 (210-405)
410 (307-543)
567 (418-753)
742 (570-959)
948 (732-1207)
Unprocessed red meat,
gper day
69 (31-115)
64 (21-116)
43 (42-100)
319-79)
20(5-54)
4(0-14)
Legumes, g per day
Soft drinks, g per day
62 (29-123)
33(0-51)
45 (22-90)
7(0-51)
43 (20-79)
0(0-23)
33 (14-60)
0(0-5)
143-34)
0(0-0)
Poultry, g per day
24 (10-60)
20 (6-51)
133-34)
70-21)
Seafood, g per day
333-30)
20-27)
110-31)
10 (0-32)
6 (0-24)
Energy, kcal per day
2085 (1637-2600)
2046 (1577-2587)
1908 (1480-2454)
1897 (1524-2393)
1964 (1529-2498)
Fibre, g per day
25 (18-35)
22 (15-31)
18 (11-25)
15 (10-25)
12.4(82-26-4)
Dietary protein,
168 (147-189)
16.0 (137-182)
1555 (13.0-17.6)
14-4 (123-463)
126 (111-143)
Dietary fat, percentage
of energy
289 (24-2-33-4)
28.0 (23-0-328)
243 (187-298)
18-2 (13-4-25-6)
12.6 (88-204)
Carbohydrate,
543 (483-60-4)
562 (50-2-62-4)
603 (536-663)
66:8 (593-729)
741 (658-793)
percentage of energy
percentage of energy
Glycaemic index
76-1 (738-777)
81,7 (80-4-82:9)
85-9 (850-867)
88-7 (88-1-89.2)
907 (90-2-91-4)
Glycaemic load, g per
191-9 (141-8-258-7)
214-3 (162-5-280-2)
259-6 (195-8-337:3)
314-4 (244-6-4037)
3857 (2985-4871)
day
Data are mean (SD), n (2%), or median (IQR). Total study population=127594. Excluded participants with implausible energy (<500 kcal per day and >3500 keal per day for
diabetes status. The daily intake of rut juice was not measured in China and Bangladesh; data for Bangladesh are included under south Asia. The glycaemic index isthe
measure ofindex
how ofmuch
50 g of carbohydrate from a specific food raises the blood glucose level. To adjust the reference standard from the bread scale low glycaemic
alycaemic
white bread = 100 on the bread scale and 70 on the glucose scale. On the bread scale, we considered a glycaemic index value of <79toastheglucoses
cale:index,
‘women and <800 kcal per day and >4200 kcal per day for men), incomplete data on glycaemic index and glycaemic load, with baseline diabetes and missing baseline
79-99 as moderate glycaemic index, and =100 as high glycaemic index. Q1-5=quintile 1-5,
Table 1: Participant characteristics by quintiles of glycaemic index
4
www thelancet.com/diabetes-endocrinology Published online April 5, 2024. https://doi.org/10.1016/S2213-8587(24)00069-X
Articles 1
Qu (n=25519)
Q2 (n=25519)
Q3 (n=25519)
Q4(n=25519)
Q5 (n=25518)
Ptrend HR perunit
increment*
Glycaemic index
764 (738-777)
Peoplewithdiabetes
1673 (6-6%)
Model 1, HR (95% Cl)
1.0 (ref)
817 (80-4-82.9)
1669 (6.5%)
0-99 (0-92-1-06)
85,9 (850-867)
1410 (5:5%)
1-03 (0-95-1-13)
88:7 (88-1-89.2)
1364 (53%)
1.06 (0-96-1-13)
907(902-91-4)
1210 (47%)
0-97 (087-107)
0-93,
1.01 (0-95-1-07)
Model
2, HR (95% Cl)
1.0 (ref)
0.95 (089-102)
1.01 (093-141)
1.40 (0:99-1.21)
1.06 (096-118)
048
—1.04(0.98-1:10)
Model 3, HR (95% Cl)
1.0 (ref)
0.98 (0-91-1.04)
11.05 (096-115)
1.16 (1.04-1.29)
1.15 (103-129)
0.010
1.09 (1.02-1.16)
Glycaemic load
Peoplewithdiabetes
136.5 (110-6-155-9)
204-1 (188-6-2195)
264-9 (250-4-281.0)
344-2 (320-6-370-4)
4748 (4232-5563)
1482 (5-8%)
1477 (58%)
1443 (57%)
1424 (5.6%)
1500 (5-9%)
Model 1, HR (95% Cl)
1.0 (ref)
100 (0-92-1.07)
1.08 (1.00-1-17)
1.09 (101-119)
1.05 (0-95-15)
018 1.00 (0-99-1.01)
Model 2, HR (95% Cl)
1.0 (ref)
1.01 (0-94-1-09)
1.41 (1.01-1.21)
1:13 (1.02-1.25)
1.12 (0-99-27)
0.070 1.01 (0-99-1-02)
Model 3, HR (95% Cl)
10 (ref)
1-04 (096-112)
1.15 (1.05-1.26)
1:20 (107-133)
1.21 (106-137)
0.0060 1.01 (1-00-1.03)
(IQR)
or n (%), unless stated otherwise. Total study population=127594. Model 1: adjusted
for age, sex, centre (random effect).Model2: adjusted
rural are medianeducation,
forage, sex, centre (random effect), urban or
country-income category, wealth index, current smoker, physical activity, waist-to-hip ratio, family history of
adjustedlocation,
for age, sex, centre (random effect), urban or rural location, education, country-income category, wealth index, current smoker,
diabetes,
physical bloodpressure
activity, waist-to-hip
medication
ratio,use,
family
andhistory
energyofintake.
Model3:
diabetes,
blood
pressure medication use, energy intake, dietary fibre intake, whole grain intake (glycaemic index exposure only), and protein intake (percentage
of energy). Q1-5=quintile
1-5.HR=hazard ratio. *HR per 10-unit
glycaemic index increment and per 50-unit glycaemic load increment.
Data
Table 2: Association of glycaemic index and glycaemic load and diabetes, in the overall PURE cohort
Asia, and Africa). We also did subgroup analyses by BMI__Baseline characteristics are shown in table 1. Overall,
using region-specific median cutoffs to define low versus _ the median glycaemic index was 85-9 (IQR 804-892),
high BMI, and subgroup analyses by waist-to-hip ratio _ with the consumption of highest glycaemic index diets
using region-specific and sex-specific median cutoffs to
define low versus high waist-to-hip ratio. Tests of
heterogeneity were done with the / statistic between
observed in China (88-9 [86-8-90-3]), followed by
southeast Asia (88-2 [85-9-89-9]) and Africa (88-0
[84-8-90-5]; appendix p 60). The median glycaemic
excluding participants who reported diabetes in the first
2 years after recruitment, excluding participants with
baseline cardiovascular disease, further adjusting for
(appendix p 60). Compared with people who consumed
diets with the lowest glycaemic index, those who
consumed a diet with the highest glycaemic index were
unprocessed red meat, fish, poultry, total dietary fat,
smoking, had lower levels of physical activity, and had
categories ofthe glycaemic index and the glycaemic load _ load varied from 177-1 (136-0-227-0) in North America
and
these subgroups. We did sensitivity analyses by and Europe to 346-0 (204-0-466-0) in south Asia
non-carbohydrate containing foods and nutrients (eg, _ less educated, resided in rural areas, had higher rates of
saturated fat, or animal protein), and adjusting for
potential confounders following the disjunctive cause
criterion.” We also did a competing risk regression
analysis with death as the competing risk.
Lastly, we did a random effects meta-analysis to include
the results of our study with the results of the Reynolds
and colleagues’ meta-analysis.* All reported p values
are two-tailed, with values less than 0-05 indicating statistical significance. All statistical analyses were done
with Stata version 15 and RStudio version 4.0.2.
alower mean BMI. They also had lower intakes of dairy,
fruit, vegetables, legumes, fruit juices, unprocessed red
meat and poultry, and higher intake of starchy foods
(table 1).
Table 2 shows the association of the glycaemic index
with incident type 2 diabetes. After multivariate
adjustment for demographic, lifestyle, health history, and
dietary factors (energy, fibre, and whole grain intakes),
higher glycaemic index was associated with incident type
2 diabetes and participants in the highest quintile of the
glycaemic index had a 15% (95% CI 3-29) greater risk
Role of the funding source
of diabetes compared with those in the lowest quintile.
In comparing highest versus lowest quintiles of the
data collection, data analysis, data interpretation, or
writing of the report.
glycaemic load in the fully adjusted model, we observed
a positive association with incident type 2 diabetes
Results
between the glycaemic index and
(HRThe1-21association
[95% CI 1-06-1-37}).
available in 145895 participants. After excluding participants with implausible energy (n=6827) and baseline
diabetes (n=11474), 127594 participants without known
glycaemic index was positively associated with diabetes
among participants from low-income countries (tertile 3
vs tertile 1; HR 1-32 [95% CI 1-11-1-56}), and a similar
‘The funder ofthe study had no role in the study design,
Data on the glycaemic index and the glycaemic load were _ diabetes varied by economic region (appendix p 62). The
diabetes were included in the analysis. During a median _ direction of association was found among participants
follow-up of 11-8 years (IQR 9-0-13-0), 7326 (5-796)
from middle-income countries (tertile 3 vs tertile 1; 1-10
incident cases of type 2 diabetes occurred.
{0-98-1-24]; appendix p 62). Among the participants
www.thelancet.com/diabetes-endocrinology Published online April 5, 2024 https://doi.org/10.1016/S2213-8587(24)00069-X
5
l Articles
HR (95% C)
Low BMI (n=63899)
a 26% (95% Cl 15-37) greater risk of diabetes
(n=624614 participants and 25 370 diabetes cases).” Our
findings for the glycaemic index and the glycaemic load
Quinte?
+00(00-209) | and diabetes are also in keeping with most studies of
Quintile 3 vs quintile1
1.08 (0:90-1:30)
Quintle2 vequintles
¥07(092425)
,
,
a
tooworaas,
|
example,
the
Shanghai
Women's
Health
Study,”
the
1:10 (087-139)
Japan Public Health Center-based Prospective Study,”
Quntle
tre gone
Quintle 5 vsquintle2
High BM(n-63658)
and the Tehran Lipid and Glucose Study" found that
Quintiles
Quintile 2 vs quintile
Quintile 3 vs quintile 1
Quintile
4vsquintile
Quintile
1oS
5 vs quintile 1
asian and Middle Eastern populations." For
100(100-100) | consuming diets with a high glycaemic index and
0.95 (088-204) | a high glycaemic load was positively associated with the
1.06 (095-117)
risk of diabetes incidence.
—_ a5 0 as 147(104-132)
=
123 (108-141)
To
Figure:
Low Association of the glycaemic index and diabetes, by BMI
and high BMI defined using region-specific median BMI cutoffs.
forRegion-specific
medianforBMIAfrica;cutoffs:26:3 22-4kg/m’kg/m’for southeast
for south Asia;
China; 24-9 kg/m’
Asia; 24:3
26-4 kg/m?
kg/m’ for
We found that the association ofthe glycaemic index
and diabetes was stronger among individuals with
a higher BMI. Similar findings have been reported by
the
Shanghai Cohort
Women’sStudy,”
HealthandStudy,*
Collaborative
amongthemenMelbourne
enrolled
.
.
in the Japan
Prospective
Cohort
Study.*Public
A 2021Health
PURECenter-based
study also reported
that
North America and Europe; 27-3 kg/m* for South America; and 28:2 kg/m*
BMI (<25 vs =25 kg/m?) significantly modified the
forlocation,
the Middle
East. Adjusted
for age, category,
sex, centre (randomindex,effect),
urbansmoker,
orrural aaciation of the glycaemic index
cardiovascular
physica activity,
education,
country-income
. with
waist-to-hip
ratio, family historywealth
of diabetes,current
blood pressure
«disease and all-cause mortality.”
Notably, this finduse, energy intake, dietary fibre intake, whole grain intake, and
medication
protein intake (percentage of energy). p interaction=0.030.
ing was consistent when BMI was defined using the
from high-income countries, a positive association was
seen for the middle tertile compared with the lowest
tertile (1-29 [1-05-1-57]), but not the highest tertile
region-specific cutoffs described in our current study
(appendix p 69).
Our findings on diabetes and studies on cardiovascular
disease earlier from PURE,” together show that
consuming
(n=66) in the highest tertile. The associations by geographic region are in the appendix (p 63).
When we examined the association of the glycaemic
index with diabetes by BMI, we found a stronger
reconsider current recommendations on the usefulness
of the glycaemic index as a measure of carbohydrate
quality."
Alpha-glucoside hydrolase inhibitors (ie, Acarbose) phar-
association in the higher BMI group (quintile 5 vs
macologically slows the rate of carbohydrate absorption
p interaction=0-030; figure). In analyses stratified by
waist-to-hip ratio, similar associations were found in the
high and low waist-to-hip ratio groups (appendix p 68).
are also consistent with the STOP-NIDDM trial” and the
ACE trial,“ which have shown that Acarbose reduces the
incidence of diabetes.
compared with the lowest tertile (0-34[0-05-2-47)),
a highof diabetes,
glycaemiccardiovascular
index diet is associated
with
due
likely mortality.
a higher riskThese
to the small number of events (n=1) and participants
findings provide
robust disease,
evidenceand
to
quintile 1; HR 1-23 [95% CI 1-08-1-41)) than in the group __ reducing the postprandial glycaemic response, and alters
with a lower BMI (quintile 5 vs quintile 1; 1-10 [0-87-1.39]; the glycaemic index ofthe diet.* As expected, our findings
tions
the glycaemic
index the
andpositive
the glycaemic
Discussion
Severalbetween
mechanisms
might explain
associaIn this large multinational prospective cohort study, we _ load and diabetes risk.** In experimental studies, higher
found that diets with a high glycaemic index and a high _ glycaemic index diets have been associated with circulat-
glycaemic load were associated with greater risk of
incident type 2 diabetes after adjustment for
ing free fatty acids,” lower insulin sensitivity, impaired
pancreatic B-cell and intestinal K cell function,“ elevated
demographic, lifestyle, and dietary factors. The glycaemic
index was most strongly associated with diabetes among
individuals with a higher BMI.
visceral adiposity, and poor glycaemic control.“ In
addition, postprandial hyperglycaemia has been shown
to increase oxidative stress, endothelial dysfunction, and
Several prospective studies of mostly USA and _ the release of proinflammatory factors.°”"
between
a positive association validated,
The strengths
of this analysis
use of
country-specific
FFQs, include
the longtheduration
European populations have found
the glycaemic index and the glycaemic load
and diabetes.*" In a 2019 dose-response meta-analysis _ of follow-up, the large sample size, and the inclusion of
glycaemic index was associated with a 27% (95% CI _ income countries, which provides information on a more
of observational studies, each ten-unit increase in the _ participants from high-income, middle-income, and low-
15-40) greater risk of diabetes (n=346465 participants
and 18063 diabetes cases) and each 80 g per day
increase in the glycaemic load was associated with
6
diverse range of glycaemic index and glycaemic load
than studies done in North American and European
populations only.
www.thelancet.com/diabetes-endocrinology Published online April 5, 2024. https://doi.org/10.1016/S2213-8587(24)00069-X
Articles 1
Potential limitations should also be considered. First, _ interpreting the data and drafting the manuscript. MD coordinated
diet was measured at baseline and intakes might have _ the entire nutrition component of the PURE study. SR coordinated the
changed over time, particularly for some lower-income — W2tlwide
study and reviewed and commented on drafts,Allother authors
coordinated the study in their respective countries, provided comments on
and middle-income countries that have had an economic
Grafts ofthe manuscript, and approved the final manuscript. The
transition. Second, diets were assessed via self-report, and
corresponding author attests that all listed authors meet authorship criteria
imprecision in measurement might lead to exposure
and that
of individual foods and beverages vary within the
pedarationofinterests
“cove
.
°€
no others meeting
the citeria have been omitted. SY is the
misclassification,
attenuating measures of association Tu cript. all authors approvedthe final manuscript
towards
the null. Third, the glycaemic index values responsibility for the decision to submit for publication. and had final
‘
ae
nan
guarantor. VMi, MD, and SR verified the underlying data reported in the
seven glycaemic index categories, which might have — yMi reports research grant from the Canadian Institutes of Health.
weighted the findings towards the null hypothesis. Research during the conduct of the study. DAJ reports research grants
Nevertheless, the categorical approach used mean _ fom the Soy Nutrition Institute and the Canadian Institutes of Health
index Sh
it-kindof California,
supplies forWalnut
trials asCouncil
a esearch
support fom
the
glycaemicic inindex values from international glycaemic
y
Almond Board
of California,
the Peanut
tables weighted on the basis of the frequency of occurrence Institute, Barilla, Unilever, Unico, Primo, Loblaw Companies, Quaker
in the country-specific FFQs, which broadly reflects the _ (Pepsico), Pristine Gourmet, Bunge, Kellogg Canada, and WhiteWave
foods most consumed by all cultures in the PURE study,
Fourth, ‘
:
.
24s: payment or honoraria for lectures or presentations from
Nutritional Fundamentals for Health-Nutramedica, Saint Barnabas
the possibility
given theof observational
we cannot
rule out — yfedical
RutgersGlycemic
New Jersey
School, Conference,
The UniversityAtlantic
of
unmeasured design,
confounding
and residual
Chicago, Center
2020 China
IndexMedical
International
Pain Conference, Academy
such
ofof Lifethe International
Longeae
Learning;Caalndene
and travel supportOcay from
ae eine
. we extensively adjusted for Hee
lutrition,een
DAJ is a co-chair
well as smoking.. However,
Carbohydrate Quality
confounding due to measurement error in confounders,
measured diabetes risk factors and the findings were Consortium and has been invited by the International Diabetes Federation
robust to adjustment. Fifth, the HR hasa built-in selection to join the committee on diabetes treatment and to take the lead in
bias, and we reported a single HR for the duration of our —_ writing the dietary guidelines for the treatment ofdiabetes. His wife,
study's follow-up, but the magnitude of the HR might — Alexandra
change dependi
fol
2 SixthSixth,
, due due my
Research
for thehaveFood
Industry his two daughters, Wendy Jenkins and
depending on the the k lengthoff follow-up.”
jenkins,
published
hange
LJenkins sa directorand partner ofINQUIS Clinical
to the relatively small number of participants and events the foods described here (Jenkinsa vegetarian
book AE,that Jenkins
promotesAL,the use of
WM, Jenkins
within regions, the power to detect region-specific
associations was limited, and the regional subgroup
Bnydson C. The portfolio dit for cardiovascular disease risk reduction.
London: Elsevier, 2019) and his sister, Caroline Brydson, received funding
analyses .
°
through a grant from the St Michael's Hospital Foundation to develop
Lastly, diabetes
might diagnosis
also be might
subject have
to sparse-data
cookbook
for oneResearch
of his studies.
ARreports
been missedbias.or 4state,
the Swedish
Council,
and the funding
Swedish from
HearttheandSwedish
Lung
misclassified in some participants. Fasting blood glucose — Foundation. AA reports consulting fees from NovoNordisk; payment or
was available
for most participants and was used to sore ioratenlenen NovoNordisk;
cstavdl andtteparticipation
BeepsSoien
diabetes (>7-0 mmol/L). However, we found Cardiology Meeting fromesses
adiagnosis
on data Board;
high level of agreement between those with both self- _ safety monitoring board or advisory board for OPTIMAL-Stroke,
reported diabetes and fasting blood glucose measures.*
OPTIMAL Diabetes, and IMPACT-BP. All other authors declare no
In this large, multinational study of adults free of Competing interests
diabetes at baseline, consuming a diet with a high
we
5
Datasharing
Data from the PURE study are not available for public use. For the
glycaemic index and a high glycaemic load were PU pr mds srotcl sce
pwwheicn/pure
associated with higher incidence of type 2 diabetes. Our Acknowledg
findings provide evidence to support the importance of Ty.’ tudy was supported by the Population Health Research Institut,
low glycaemic
index and
glycaemic load diets to prevent — Hamilton Health Sciences Research Institute, the Canadian Institutes
develop
, including
.
a
\cknowledgments
diabetes
of Ontario, Strate,
world
the Middle
regi fEast,the [*of Patient
Health Orientedh, Researchidof theStrok Canadian
id: Institutes
f of Health By
not previously studied (eg,inAfrica,
liabetes
development,
including
in
the regions of
the
of Health
Research, Heart and
Stroke Foundation
South America,
‘| South Asia, Southeast Asia).
A Our study Support
ResearchUnit,
through
Patient-Oriented
Research
and thethe Ontario
Ontario Strategy
Ministryforof Health
and Long-Term
suggests that increasing the intake of low glycaemic
Care; by unrestricted grants from several pharmaceutical companies,
index foods, such as legumes, fruit, fruit juice, non- _ with major contributions from AstraZeneca (Canada), Sanofi-Aventis
starchy
and reducing
and Canada), BoehringerandIngelheim
(Germany
and Canada),
trientvegetables,
foods and withdairy,2 hich
eh ‘c theindex
indintakeandof‘q _ (France
_Setvier,and
additional
contributions
glycaemic
Novartis andGlaxoSmithKline;
King Pharma and frombyvarious
national
or local from
nutrient-poor foods with a high
high glycaemic load varieties of non-legume starchy _ organisations in participating countries as follows: Argentina:
foods might have a substantial effect on preventing — Fundacién Estudios Clinicos Latino America; Bangladesh:
diabetes incidence globally, particularly among people
!dependent University, Bangladesh, and Mitra and Associates; Brazil:
‘tri where
here hihigh — pairy
UnileverCouncil
Healthof Institute;
Dairy Agency
Farmers of Canada, National
withith aa hicher
Aigher BMI andand ini countries
the USA, Canada:
Public Health
carbohydrate
Contributors diets are traditionally consumed.
of Canada, and
Champlain Cardiovascular Disease Prevention Network; Chile:
drafted and revised the manuscript. DAJ, MD, and KS assisted with
alaysia: Ministryof Science, Technology, and Innovationof Malaysia,
SY conceived and initiated the PURE study, supervised its conduct,
and reviewed and commented on the draft. VMi did the analyses, and
Universidad de La Frontera; China: National Center for Cardiovascular
Diseases and ThinkTank Research Center for Health Development
nae
ene
NOT
www.thelancet.com/diabetes-endocrinology Published online April 5, 2024 https://doi.org/10.1016/S2213-8587(24)00069-X
7
l Articles
Ministry of Higher Education of Malaysia, Universiti Teknologi
16
MARA, and Universiti Kebangsaan Malaysia; Palestinian territory:
and International Development Research Centre, Canada; Philippines:
UN Relief and Works Agency for Palestine Refugees in the Near East
Geneva: World Health Organization, 2023
§, et al. Association ofglycaemic
—-17_Jenkins DJA, Willett WC, Yusuf
index and glycaemic load with type 2 diabetes, cardiovascular disease,
Philippine Council for Health Research and Development; Poland:
Polish
Ministry ofScience and Higher Education and Wroclaw Medical
University; Saudi Arabia: Saudi Heart Association, Dr Mohammad
Alfagih Hospital, The Deanship of Scientific Research at King Saud
University
numberof Coronary
RG-1436-013),
Hamza Serafi(Research
Chair forgroup
Research
HeartRiyadh,
Disease,Saleh
Umm
AlQura
University,
Makkah,
Saudi
Arabia;
South
Africa:
North-West
University, Netherlands Programme for Alternative Development,
ee eeeeee eee nh eileen
J
Africa,
a Sciences: q Sweden: Swedish government,, sSwedish Heart and
Health,
WHO. Carbohydrate intake for adults and children: WHO guideline.
cancer, and all-cause mortality: a meta-analysis of mega cohorts of
more than 100000 participants. Lancet Diabetes Endocrinol 2024;
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JKendallaM
Am Col Nutrhe2009;
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Chowepidemiology
CK VazM, Rangarajan
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the Heart and Stroke Foundation of Ontario.
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United ArabSyndrome
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