Transcript PowerPoint - 埼玉医科大学総合医療センター 内分泌・糖尿病内科

Journal Club
de Ruyter JC, Olthof MR, Seidell JC, Katan MB.
A Trial of Sugar-free or Sugar-Sweetened Beverages and Body Weight in Children.
N Engl J Med. 2012 Sep 21.
Ebbeling CB, Feldman HA, Chomitz VR, Antonelli TA, Gortmaker SL, Osganian SK, Ludwig
DS.
A Randomized Trial of Sugar-Sweetened Beverages and Adolescent Body Weight.
N Engl J Med. 2012 Sep 21.
Qi Q, Chu AY, Kang JH, Jensen MK, Curhan GC, Pasquale LR, Ridker PM, Hunter DJ, Willett
WC, Rimm EB, Chasman DI, Hu FB, Qi L.
Sugar-Sweetened Beverages and Genetic Risk of Obesity.
N Engl J Med. 2012 Sep 21.
2012年9月27日 8:30-8:55
８階 医局
埼玉医科大学 総合医療センター 内分泌・糖尿病内科
Department of Endocrinology and Diabetes,
Saitama Medical Center, Saitama Medical University
松田 昌文
Matsuda, Masafumi
Man Drinking Fat. NYC Health Anti-Soda Ad. Are You Pouring on the Pounds?
http://www.youtube.com/watch?v=-F4t8zL6F0c&feature=player_embedded
New York City consists of five boroughs, each of which is a
state county. The five boroughs—The Bronx, Brooklyn,
Manhattan, Queens, and Staten Island—were consolidated
into a single city in 1898. With a Census-estimated 2011
population of 8,244,910 distributed over a land area of just
305 square miles (790 km2).
Super Size Me is a 2004 American documentary film
directed by and starring Morgan Spurlock, an American
independent filmmaker. Spurlock's film follows a 30-day
period from February 1 to March 2, 2003 during which he
ate only McDonald's food.
May 30, 2012
米ニューヨーク市のマイケル ブルームバーグ市長は、肥満対策に取り組むために、レストラン、映画館、
食料品店での高カロリーの清涼飲料の販売を規制するプランを発表した。
September 13, 2012
The New York City Board of Health approved a measure that says sugary
beverages with more than 25 calories per eight ounces can only be sold in
portions of 16 ounces or less. The ban on larger quantities applies to the
following food service establishments: restaurants, mobile food carts, delis and
concessions at movie theaters, stadiums and arenas. The new regulation, which
goes into effect on March 12, 2013, will give establishments six months to comply.
the Department of Health Sciences, EMGO Institute for Health and
Care Research, VU University Amsterdam, Amsterdam, the
Netherlands.
N Engl J Med 2012. DOI: 10.1056/NEJMoa1203034
Figure 1. Screening, Randomization, and
Follow-up of the Study Participants.
A total of 164 children
stopped consuming the
study beverages.
Measurements in 136 of
these children (79
children in the sugarfree group and 57 in the
sugar group) were
available at 18 months.
Thus, measurements in
28 children who did not
complete the study (15
children in the sugarfree group and 13 in the
sugar group) were not
available at 18 months.
We randomly assigned
641 children, not 642,
as previously reported,
since after unblinding,
one child whom we
believed to have
undergone
randomization had not
undergone
randomization.
Figure 2. Urinary Sucralose
Concentrations.
The sucralose concentration was determined in
spot urine samples by means of liquid
chromatography with mass spectrometry.21
Samples were obtained from randomly selected
children who completed the study. We assigned a
value of 0.01 to samples below the detection limit
of 0.02 mg per liter. The upper and lower ends of
the boxes indicate the 25th and 75th quartiles, the
black dots means, the horizontal lines within the
boxes medians, the upper whisker the maximum
value, and the lower whisker the minimum value.
Values for the sugar-free group are based on
samples obtained from 116 children at 6 months
and from 117 children at 12 and 18 months. Mean
(±SD) urinary sucralose concentrations were
6.3±3.7 mg per liter at 6 months, 6.6±4.5 mg per
liter at 12 months, and 7.0±5.6 mg per liter at 18
months; sucralose was undetectable in 3% of
samples at 6 months, 8% of samples at 12 months,
and 10% of samples at 18 months. Values for the
sugar group are based on samples obtained from
54 children at 6 months and 36 children at 12 and
18 months. Mean values were 0.04±0.13 mg per
liter at 6 months, 0.03±0.14 mg per liter at 12
months, and 0.31±0.56 mg per liter at 18 months;
sucralose was undetectable in 93% of samples at
6 months, 97% of samples at 12 months, and 67%
of samples at 18 months. We also pooled 543
samples from participants at baseline to produce
20 pools. The mean sucralose concentration in
these samples was 0.06±0.07 mg per liter.
Sucralose is an artificial sweetener.
Figure 3. Body-Mass Index (BMI) z Score in the 477 Children Who Drank the
Study Beverages for the Full 18 Months.
The z score for BMI is the BMI expressed as the number of standard deviations by which
a child differed from the mean in the Netherlands for his or her age and sex. Panel A
shows mean z scores for the two study groups over the 18-month study period. Panel B
shows the between-group difference in the mean change from baseline (the mean
change in the BMI z score in the sugar-free group minus the mean change in the sugar
group), as a function of time. T bars in both panels indicate standard errors.
the New Balance Foundation Obesity Prevention Center (C.B.E., D.S.L.) and
the Clinical Research Center (H.A.F., T.A.A., S.K.O.), Boston Children’s
Hospital, Boston; the Institute for Community Health, Cambridge (V.R.C.);
and the Department of Society, Human Development, and Health, Harvard
School of Public Health, Boston (S.L.G.) — all in Massachusetts.
N Engl J Med 2012. DOI: 10.1056/NEJMoa1203388
Figure 1. Screening, Randomization,
and Follow-up of the Study
Participants.
Among the 538
adolescents who were
excluded, 15 of the 49
who did not meet the
sugar-sweetened–
beverage (SSB) criterion
also had other reasons
and are included in the
counts for those reasons.
The weight and height of
all available participants
were measured at each
time point in order to
calculate BMI.
* Plus–minus values are means ±SD.
Means were compared with the use of the
Student’s t-test and proportions
compared with the use of Fisher’s exact
test. Percentages may not sum to 100
owing to rounding. GED denotes General
Educational Development, and MET
metabolic equivalent.
† Race and ethnic group were reported by
the parents of the participants. “Multiple”
included white–black (8 participants),
white–Asian (3), white–black–Asian (1),
and white–Arabic (1). “Other” included
Latino or Latina (8 participants), Hispanic
(7), Brazilian (2), Cape Verdean (2),
Puerto Rican (4), Latino or Latina–
Brazilian (1), Spanish (1), and American
(1). Comparisons of baseline
characteristics according to ethnic group
are provided in Table S1 in the
Supplementary Appendix.
‡ Participants at or above the 85th
percentile for BMI but below the 95th
percentile were classified as overweight,
and participants at or above the 95th
percentile were classified as obese. The
BMI range was 23.2 to 28.8 for
overweight participants and 26.7 to 50.7
for obese participants.
§ The educational level listed is for the
father or mother, depending on which
parent had the higher level of education.
*Plus–minus values for
unadjusted data are means
±SD, and plus–minus values
for changes from baseline are
means ±SE. Changes were
calculated at 1 year and 2 years
from the general linear model,
without adjustment for
covariates.
† The P values for changes from
baseline in each study group
are based on tests of the
hypothesis that the mean
change was zero.
‡ The P values for the betweengroup differences in changes
from baseline are based on
tests of the hypothesis that the
mean change was the same in
the two groups. There were no
significant ethnic group–study
group interactions for any of the
dietary variables.
*Plus–minus values for unadjusted data
are means ±SD, and plus–minus values
for changes from baseline are means
±SE. Changes were calculated at 1
year and 2 years from the general linear
model, and were adjusted for sex, race,
ethnic group, household income,
parental education, baseline BMI,
baseline beverage consumption (energy
from sugar-sweetened beverages and
fruit juices and servings of artificially
sweetened beverages and unsweetened
beverages), baseline total energy intake,
baseline sugar intake, and baseline
obesity-related behavioral measures
(physical activity and hours of television
viewing). Results specific to ethnic group
are from a model that included an
interaction term for study group and
ethnic group. For the change during the
2 years, before imputation, BMI data
were available for 166 non-Hispanic
participants (78 in the experimental
group and 88 in the control group) and
43 Hispanic participants (27 in the
experimental group and 16 in the control
group).
† The P values for changes from baseline
in each study group are based on tests
of the hypothesis that the mean change
was zero.
‡ The P values for the between-group
differences in changes from baseline are
based on tests of the hypothesis that the
mean change was the same in the two
groups.
the Departments of Nutrition (Q.Q., M.K.J., D.J.H., W.C.W., E.B.R., F.B.H., L.Q.) and
Epidemiology (G.C.C., D.J.H., W.C.W., E.B.R., F.B.H.), Harvard School of Public Health; and
the Divisions of Preventive Medicine (A.Y.C., P.M.R., D.I.C.), Cardiovascular Disease (P.M.R.),
and Genetics (D.I.C.), and the Channing Division of Network Medicine ( J.H.K., G.C.C., L.R.P.,
D.J.H., W.C.W., E.B.R., F.B.H., L.Q.), Department of Medicine, Brigham and Women’s Hospital
and Harvard Medical School; and the Department of Ophthalmology (L.R.P.), Massachusetts
Eye and Ear Infirmary, Harvard Medical School — all in Boston.
N Engl J Med 2012. DOI: 10.1056/NEJMoa1203039
GENOTYPING
We selected 32 single-nucleotide polymorphisms (SNPs) that represent
all 32 loci that are known to be associated with BMI. SNP genotyping
and imputation have been described in detail elsewhere. Most of the
SNPs were genotyped or had a high imputation quality score (r2≥0.8),
as assessed with the use of MACH software, version 1.0.16 (Center for
Statistical Genetics, University of Michigan) (Table S1 in the
Supplementary Appendix).
GENETIC-PREDISPOSITION SCORE
The genetic-predisposition score was calculated on the basis of the 32
SNPs with the use of a previously reported weighting method; scores
range from 0 to 64, with higher scores indicating a higher genetic
predisposition to obesity. Each SNP was weighted according to its
relative effect size (β coefficient). To obtain a more accurate and precise
effect size of each SNP on BMI, we used β coefficients derived from a
meta-analysis of studies involving a total of approximately 126,000
persons. We rescaled the weighted score to reflect the number of risk
alleles: each point of the genetic-predisposition score corresponded to
one risk allele.
Chr: chromosome;
EAF: effect allele frequency.
*Allele coding based on the
forward strand.
†Effect sizes in kg/m2 of BMI
obtained from GWAS.
‡r2 refers to the
measurement of SNPs
imputation quality.
Figure S1 Genetic predisposition score and body mass index in three cohorts
The histograms represent the percentage of participants; and the means (±SE) of BMI
are plotted, with the trend lines across the genetic predisposition score.
* Plus–minus values are means
±SD. Baseline data were from
6934 women in the Nurses’
Health Study (NHS, 1980), 4423
men in the Health Professionals
Follow-up Study (HPFS, 1986),
and 21,740 women in the
Women’s Genome Health Study
(WGHS, 1992). Physical activity
was assessed in 1986 for the
NHS cohort. Television watching
was assessed in 1992 for the
NHS cohort and in 1988 for the
HPFS cohort.
† P values are for the trend across
the four categories of intake of
sugar-sweetened beverages.
‡ The body-mass index (BMI) is
the weight in kilograms divided
by the square of the height in
meters.
§ MET denotes metabolic
equivalents.
. Scores on the Alternative
Healthy Eating Index range from
2.5 to 87.5, with higher scores
indicating a healthier diet.
‖ The genetic-predisposition score
ranges from 0 to 64, with higher
scores indicating a higher
genetic predisposition to obesity.
In the NHS, there were 1107 incident cases of obesity
among 6402 initially nonobese women during 18
years of follow-up (1980 to 1998),
and in the HPFS, there were 297 incident cases of
obesity among 3889 initially nonobese men during 12
years of follow-up (1986 to 1998).
The results were similar in the WGHS cohort (Fig. 1),
in which 2280 women (of 18,127 women who were
nonobese at baseline) became obese during 6 years
of follow-up (1992 to 1998).
* Plus–minus values are β
coefficients ±SE. Data
were derived from
repeated-measures
analysis for women in the
NHS (five measures during
the period from 1980 to
1998) and for men in the
HPFS (three measures
during the period from 1986
to 1998). Data on beverage
intake were assessed 4
years before the
assessment of BMI.
† Data were adjusted for age
and source of genotyping
data.
‡ Data were further adjusted
for level of physical activity,
time spent watching
television, status with
respect to current smoking,
alcohol intake, Alternative
Healthy Eating Index score,
and total energy intake.
§ Results for the two
cohorts were pooled by
means of inverse-variance–
weighted, fixed-effects
meta-analyses.
Figure 1. Relative Risk of the Development of Obesity per Increment of 10 Risk Alleles,
According to Intake of Sugar-Sweetened Beverages.
For the discovery phase, with data from the Nurses’ Health Study (NHS) and Health Professionals Follow-up Study (HPFS) cohorts,
the analyses were based on 18 years of follow-up for 6402 initially nonobese women (1980 to 1998, 1107 incident cases of obesity)
and 12 years of follow-up for 3889 initially nonobese men (1986 to 1998, 297 incident cases of obesity). Shown are the pooled
relative risks of incident obesity, with adjustment for age, source of genotyping data, level of physical activity, status with respect to
current smoking, alcohol intake, time spent watching television, Alternative Healthy Eating Index score, and total energy intake. For
the replication phase, with data from the Women’s Genome Health Study (WGHS) cohort, the analyses were based on a median of
6 years of follow-up for 18,127 initially nonobese women (1992 to 1998, 2280 incident cases of obesity). Shown are the relative risks
of incident obesity, with adjustment for age, geographic region, eigenvectors, level of physical activity, status with respect to current
smoking, alcohol intake, and total energy intake. Horizontal bars indicate 95% confidence intervals.
Figure 2. Difference in BMI Associated with One Serving of a Sugar-Sweetened
Beverage per Day, According to the Quartile of the Genetic-Predisposition Score.
Data are effect sizes (β coefficients [±SE]) of sugar-sweetened beverage intake (one serving per day) on body-mass index (BMI; the weight in
kilograms divided by the square of the height in meters), stratified according to the quartile of the genetic-predisposition score. In the NHS cohort,
the median scores across the quartiles were 24.5 (range, 13.1 to 26.3), 27.8 (range, 26.4 to 29.0), 30.3 (range, 29.1 to 31.7), and 33.6 (range,
31.8 to 43.4); in the HPFS cohort, 24.9 (range, 16.0 to 26.5), 27.9 (range, 26.6 to 29.1), 30.4 (range, 29.2 to 31.7), and 33.6 (range, 31.8 to 41.9);
and in the WGHS cohort, 24.7 (range, 15.3 to 26.5), 27.8 (range, 26.6 to 29.1), 30.3 (range, 29.2 to 31.6), and 33.4 (range, 31.7 to 43.4). In the
NHS and HPFS cohorts, the analyses were based on data from the first 4 years in women (1980 to 1984) and men (1986 to 1990), respectively,
with adjustment for age, source of genotyping data, level of physical activity, time spent watching television, status with respect to current
smoking, alcohol intake, and Alternative Healthy Eating Index score. In the WGHS cohort, the analyses were based on data from the first 3 years,
with adjustment for age, geographic region, eigenvectors, level of physical activity, status with respect to current smoking, and alcohol intake. P
values are for interaction. I bars indicate standard errors.
Message
3つの論文でSugar-Sweetened Beverages(糖で甘くした飲み物)に関するものがNew
York市で制限する法律が通るとほぼ同時にNew England Journal of Medicine誌に掲載
された！
オランダのDRINK研究。平均８歳の正常体重児641人を対象に、糖で甘くした飲み物の
代わりのノンカロリー飲料摂取による体重増加抑制効果を無作為化試験で検討。18カ
月の試験で、体重増加は人口甘味料使用の無糖飲料群で6.35kg、糖で甘くした飲み物
群で7.37kgだった。皮下脂肪厚、腹囲身長比、体脂肪量の増加も無糖群で有意に少な
かった。（差は小さい気もしますが。．．．）
ボストンで平均15歳での体重が多めの224人を１年ほど糖で甘くした飲み物の制限とそ
うでない群で検討。２年目は介入しないで両群を比較した。１年の介入で食事や体重
に差が出た（BMI (−0.57, P = 0.045) で体重(−1.9 kg, P = 0.04) )。特にHispanic
では２年めについても差が継続していた。
ボストン周辺の疫学研究で遺伝子を解析できる３つの研究（the Nurses’ Health
Study (NHS), Health Professionals Follow-up Study (HPFS), the Women’s Genome
Health Study (WGHS) ）について、肥満傾向の遺伝素因と糖で甘くした飲み物の量の
関連を検討。BMI増加と肥満の発生について肥満遺伝子あたりのリスクは糖で甘くした
飲み物が増えるほど影響が大きことが示された。