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May 31, 2006
- We are glad to introduce our readers to the updated list (May 2006) of the studies on passive smoke and lung cancer. This list includes the
separation by categories (i.e.: workplace, spousal); this explains the seemingly
doubling of the number of studies which, in reality, are
currently
slightly over 70. This list should put an end to the diatribe on passive
smoke since it conclusively demonstrates, step by step and in extremely simple
language accessible, to all the incredible misrepresentation of
evidence used to transform a non-danger into an "epidemic" and into a collective
hysteria phenomenon. |
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We recommend to
read the necessary information to better understand the meaning of
the tables.
(Skip
the information and go to the conditions required for epidemiological
validity)
(Skip all and go to the tables)
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Incidence of a
disease
– The frequency at which the disease appears in people.
Relative Risk
(RR), Odds Ratio
– A ratio between the incidence of diseases in a group of people believed
to be exposed to the risk (in our case, passive smoke) and the incidence in a
group of people believed not to be exposed to that risk.
RR
= |
Frequency of the disease (incidence) that appears in
people exposed
-----------------------------------------------------------------------------------------------------
Frequency of the disease (incidence) that appears in
people not exposed |
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If the
incidence of disease is the same in the exposed and in the non-exposed groups,
the ratio is 1 and there is no change in risk. If the incidence of
disease is greater in the people exposed, the ratio becomes greater than 1 and
the risk has increased. Conversely, the risk is smaller than 1 when the
incidence is lower in the exposed people, implying that the exposure protects
from the disease.
Confounder,
Concomitant Factor
– Factors and circumstances that contribute to the occurrence of the disease. As
we shall see later, many diseases are multifactorial, meaning that they can be
caused by different factors acting by themselves or in concert with others – as
opposed to mono-factorial diseases that have one cause, and whose risks can be
reliably measured. See the definitions below for further explanation.
Longitudinal or
cohort study
– Longitudinal or cohort studies identify groups of subjects exposed or not
exposed to potentially toxic conditions. Prospective studies identify groups of
subjects and follow them over time, often many years. Retrospective studies
identify groups of subjects with different incidences of diseases and attempt to
reconstruct their past exposures.
Retrospective
study: a study
based on memories of exposure by the subjects interviewed rather than on
direct measurement of exposure. A retrospective study has no way to check the
accuracy of memories.
Case-control study -
Case-control studies are utilized when it is only feasible to
observe differences of postulated toxic exposures in groups of people with or
without disease. Case-control studies are necessarily retrospective and their
weakness is that they do not measure differences of disease incidence. The
incidence is 0% in the controls and 100% in the cases, and therefore such
studies infer risks as differentials of exposure, and not as true
differentials of incidence.
In other words,
these studies try to guess the exposure of the subjects to passive smoke
- guess based solely on what the subjects say to remember. Then they
infer (guess) the risk purely on the basis of the difference of exposure
remembered by the subjects during the interview. Finally, the disease
that already exists - and that could have been caused by any combination of
co-factors - is attributed to passive smoke! The overwhelming majority
of the studies on passive smoke is retrospective and case control, and this is
the "mountain of evidence" we keep hearing about. It is on this
methodological quality that it is said that passive smoke "kills" or "hurts"
others - and this is the claimed basis of every single smoking ban in the
world.
Hypothesis:
A conjecture that must be demonstrated through experimentation.
Statistical
significance:
a numeric coherence indicating only that the data show either
benefit or risk as opposed to both, as it happens for the large
majority of the studies on passive smoke. Careful now, don't let them
con you: "statistical significance" does not mean that the date are
accurate, nor does it mean that the risk/benefit exists, not that it's
big. In short, a risk with "statistical significance" (or
"statistically significant") does not mean significant risk,
as "public health" and antismoking con men activists want us to
believe so that we keep on hating smokers.
Confidence
Interval:
the margin of certainty that mistakes are not made. This interval is
95%. To read the table below, simply remember this easy rule: to have
statistical significance the two risk numbers that define the interval
must either be both grater than 1 (i.e.: 1.3-4.7), or smoller than 1
(i.e.: 0.6-0.9) to indicate a benefit. If the interval is straddling 1
(i.e.: 0.7-2.3) the study has no statistical significance, that is, it
demonstrates nothing.
With this
information we can now examine what a study needs to have real
epidemiological validity.
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Conditions required for
epidemiological validity |
- A study must warrant that its
numerical representations of individual lifetime PS exposure recalls are
true measures of actual exposures.
- A study must warrant that an
exposure recall bias affects cases and control groups, and exposed and
non-exposed groups at the same rate.
- A study must warrant that subject
selection and misclassification biases affect cases and control groups,
and exposed and non-exposed groups at the same rate.
- A study must warrant that known
causal confounders affect cases and control groups, and exposed and
non-exposed groups at the same rate.
- A study must warrant the accuracy
of pathological and diagnostic records.
- The results from different
studies addressing the same subject must be consistently reproducible.
- In any study, the statistical
margin of error of reported risks should reach no less than the 95% level
of significance.
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If the above criteria are met,
the results of a study should also be consistent with Hill’s criteria of
causality.
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Meta-analysis summations shall not be credible unless performed on the basis
of all available studies, which studies also must be of homogeneous design
and conduct, and must have met the above criteria of validity.
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The conditions
satisfied by the studies on passive smoke
For
sake of brevity and clarity we focus here on the epidemiologic studies
of PS and lung cancer, which their sponsors claim to represent the
best and strongest evidence of the risks of PS exposure. On this
basis, a consideration of the reliability of claims for other
conditions allegedly linked with PS exposure would be subordinate to
the considerations for lung cancer.
The credibility of
the criteria above is self-evident and accepted by epidemiology. It is
also easy to understand, and comprehensible to all who are interested
in the verification of evidence on the basis of facts. On such basis
we challenge anybody to disagree on what follows, which we state it
applies to any study and any meta-analysis on passive smoke so far.
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It is incontrovertible that no extant study can
warrant that the numerical representation of individual lifetime PS exposure
recalls is a reliable measure of actual exposures.
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It is incontrovertible that no extant study can
warrant that PS exposure recall bias affects cases and control groups, and
exposed and non-exposed groups at the same rate.
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It is incontrovertible that no extant study can
warrant that subject selection and misclassification biases (and other biases)
affect cases and control groups, and exposed and non-exposed groups at the
same rate.
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It is incontrovertible that no extant study can
warrant that known causal confounders affect cases and control groups, and
exposed and non-exposed groups at the same rate.
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It is incontrovertible that no extant study has
warranted the accuracy of pathological and diagnostic records.
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It is incontrovertible that results from different
studies addressing the same subject have been grossly inconsistent and not
reliably reproducible.
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It is incontrovertible that only for a random
minority of studies has the numerical margin of error of reported risks been
at or below the 95% confidence level of statistical significance.
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It is incontrovertible that no study of PS has met
Hill’s criteria of causality.
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It is incontrovertible that no meta-analysis
summation of PS studies has been performed on the basis of all available
studies, of studies that are of homogeneous design and conduct, and of studies
that have met the above criteria of validity.
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A detailed
consideration of each signle study on PS and lung cancer would make
this report not accessible to non-specialized persons. However, upon
request we commit to supply a detailed analysis of any of the studies
listed below with respect to what stated above.
That notwithstanding,
the points on coherence and statistical significance can be presented
and understood immediately with the simple list of the studies and
their reported risks. Summary pie charts are also supplied after the
list.
We remind the
reader that statistical significance concerns only the
numerical context of a study, and it refers only to the numeric error
field of a particular study. No statistical manipulation can improve
the quality of the base data - hence if the data are not reliable and
corrupt, each statistical estimate deriving from them is equally
unreliable and corrupt.
For example, no
statistical manoeuvre can improve the lack of reliability that comes
from the memory recall of the people examined in a given study. It
follows that a study with a risk elevation that has statistical
significance gives no assurance that the risk elevation is credible.
On the other hand, a study without statistical significance - that is,
showing a risk and a benefit at the same time - is doubly
unreliable: First because of the unreliability of the base
data, and second because the margin of error is not acceptable. At any
rate, the largest studies have a statistical advantage since the size
of the error is inversely proportional to the number of the subjects
examined by one particular study.
As
general table, here are all the studies available to date concerning
the exposure to PS and lung cancer, classified in three categories:
SPOUSAL STUDIES - On non smokers
living with smoking spouses.
WORKPLACE STUDIES - On non
smokers working in places where smoking is permitted
CHILDHOOD STUDIES - On non
smokers exposed to PS during childhood and adolescence. |
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COLOR CODE AND
NOTATIONS:
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Not
statistically significant risk elevation |
PASSIVE
SMOKE STUDIES 1981-2006 |
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Not
statistically significant risk reduction (protection) |
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Statistically significant risk elevation |
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Statistically significant risk reduction (protection) |
| ^
= |
From Final Report CALEPA 1997 |
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^^ = |
From Final Report CALEPA 2003 |
| SG
= |
1986 Surgeon General’s Report |
| (
) = |
Estimated. |
| NR
= |
No Risk.
Reported by the researchers as no correlation, that
is, RR=1.00. |
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See bibliographical
references at the end of the page |
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SPOUSAL
STUDIES |
| Studies
and Authors |
Year
|
Nation
|
Sex
|
Number of lung cancers |
Relative
Risk
(example: 1.18=18%
risk elevation)
|
95% Confidence Interval
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| Garfinkel
et al. 1 (SG) |
81
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United States
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F
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153 |
1.18
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0.90-1.54
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| Chan
et al. SG |
82
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Hong Kong
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F
|
84 |
0.8
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0.43-1.3
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Correa et al. (SG) |
83
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United States
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F
|
22 |
2.07
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0.81-5.25
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Correa et al.(SG) |
83
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United States
|
M
|
8 |
1.97
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0.38-10.32
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Trichopouls et al. (SG) |
83
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Greece
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F
|
77 |
2.08
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1.20-3.59
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| Buffler
et al. |
84
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United States
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F
|
41 |
0.8
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0.34-1.9
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| Buffler
et al. |
84
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United States
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M
|
11 |
0.51
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0.14-1.79
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Hirayama
et al. (SG) |
84
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Japan
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F
|
200 |
1.6
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1.00-2.4
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Hirayama
et al.
SG |
84
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Japan
|
M
|
64 |
2.24
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1.19-4.22
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| Kabat
et al. 1(SG) |
84
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United States
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F
|
24 |
0.79
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0.25-2.45
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| Kabat
et al. 1(SG) |
84
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United States
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M
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12 |
NR
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0.2-5.07
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| Garfinkel
et al. 2(SG) |
85
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United States
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F
|
134 |
1.23
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0.81-1.87
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Lam W.
et al. |
85
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Hong Kong
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F
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60 |
2.01
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1.09-3.72
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| Wu
et al. (SG) |
85
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United States
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F
|
29 |
1.4
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0.4-4.2
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| Akiba
et al. (SG) |
86
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Japan
|
F
|
94 |
1.5
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0.9-2.8
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| Akiba
et al. (SG) |
86
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Japan
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M
|
428 |
1.8
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0.4-7.0
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| Lee
et al. (SG) |
86
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United Kingdom
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F
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41 |
1.00
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0.37-2.71
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| Lee
et al. (SG) |
86
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United Kingdom
|
M
|
22 |
1.3
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0.38-4.39
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| Bownson
et al. 1 |
87
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United States
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F
|
19 |
1.68
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0.39-6.9
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| Gao
et al. |
87
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China
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F
|
246 |
1.19
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0.82-1.73
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| Humble
et al. |
87
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United States
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F
|
20 |
2.2
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0.80-6.6
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Humble et al. |
87 |
United States
|
M
|
8 |
4.82
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0.63-36.56
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| Koo
et al. |
87 |
Hong Kong
|
F
|
86 |
1.64
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0.87-3.09
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Lam
T et al. |
87
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Hong Kong
|
F
|
199 |
1.65
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1.16-2.35
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| Pershagen
et al. (SG) |
87
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Sweden
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F
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70 |
1.2
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0.7-2.1
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| Butler
et al. |
88 |
United States
|
F
|
8 |
2.2
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0.48-8.56
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Geng
et al. |
88
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China
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F
|
54 |
2.16
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1.08-4.29
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|
Inoue et al. |
88 |
Japan
|
F
|
22 |
2.25
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0.8-8.8
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| Shimizu
et al. |
88
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Japan
|
F
|
90 |
1.08
|
0.64-1.82
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| Choi
et al. |
89
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Korea
|
F
|
75 |
1.63
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0.92-2.87
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| Choi
et al. |
89 |
Korea
|
M
|
13 |
2.73
|
0.49-15.21
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| Hole
et al. |
89
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Scotland
|
F
|
6 |
1.89
|
0.22-16.12
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| Hole
et al. |
89 |
Scotland
|
M
|
13 |
3.52
|
0.32-38.65
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| Svensson
et al. |
89 |
Sweden
|
F
|
34 |
1.26
|
0.57-2.81
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| Janerick
et al. |
90
|
United States
|
F&M
|
191 |
0.93
|
0.55-1.57
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|
Kalandidi
et al. |
90
|
Greece
|
F
|
90 |
2.11
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1.09-4.08
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| Sobue
et al. |
90
|
Japan
|
F
|
144 |
1.13
|
0.78-1.63
|
| Wu-Williams |
90 |
China
|
F
|
417 |
0.7
|
0.60-0.9
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| Liu
Z et al. |
91 |
China
|
F
|
54 |
0.77
|
0.30-1.96
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| Brownson
et al. 2 ^ |
92 |
United States
|
F
|
431 |
NR
|
0.80-1.2
|
| Stockwell
et al. ^ |
92
|
United States
|
F
|
62 |
1.6
|
0.80-3.0
|
| Liu
Q et al. ^ |
93 |
China
|
F
|
38 |
1.66
|
0.73-3.78
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| Wu
et al. |
93
|
China
|
F
|
75 |
1.09
|
0.64-1.85
|
|
Fontham
et al. ^ |
94 |
United States
|
F
|
651 |
1.29
|
1.04-1.60
|
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Zaridze
et al. |
94 |
Russia
|
F
|
162 |
1.66
|
1.12-2.46
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| Du
et al. |
95-96a |
China |
F |
69 |
1.19 |
0.66-2.16
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| Kabat
et al. 2 ^ |
95
|
United States
|
F
|
67 |
1.08
|
0.60-1.94
|
| Kabat
et al. 2 ^ |
95 |
United States
|
M
|
39 |
1.6
|
0.67-3.82
|
|
Wang
et al. |
96a |
China |
F |
99 |
2.5 |
1.3-5.1 |
| Wang
et al. |
96b |
China |
F |
92 |
1.11 |
0.65-1.88 |
| Schwartz
et al. ^ |
96
|
United States
|
F
|
175 |
1.1
|
0.72-1.68
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| Schwartz
et al. ^ |
96 |
United States
|
M
|
72 |
1.1
|
0.60-2.03
|
| Sun
et al. |
96 |
China
|
F
|
230 |
1.16
|
0.80-1.69
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|
Want SY
et al. |
96
|
China
|
F
|
82 |
2.53
|
1.26-5.10
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| Wang TJ
et al. |
96
|
China
|
F
|
135 |
1.11
|
0.67-1.84
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| Cardenas
et al. ^ ^^ |
97 |
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