Body mass index, abdominal fatness, and the risk of sudden cardiac death: a systematic review and dose–response meta-analysis of prospective studies
European Journal of Epidemiology
Body mass index, abdominal fatness, and the risk of sudden cardiac death: a systematic review and dose-response meta-analysis of prospective studies
Dagfinn Aune 0 1 2 3 4
Sabrina Schlesinger 0 1 2 3 4
Teresa Norat 0 1 2 3 4
Elio Riboli 0 1 2 3 4
0 Bjørknes University College , Oslo , Norway
1 Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London , St. Mary's Campus, Norfolk Place, Paddington, London W2 1PG , UK
2 & Dagfinn Aune
3 Institute for Biometrics and Epidemiology, German Diabetes Center (DDZ), Heinrich Heine University Du ̈sseldorf , Du ̈sseldorf , Germany
4 Department of Endocrinology, Morbid Obesity and Preventive Medicine, Oslo University Hospital , Oslo , Norway
Although overweight and obesity are established risk factors for some types of heart disease including ischemic heart disease, heart failure and atrial fibrillation, less is known about the association between adiposity and sudden cardiac death. We conducted a systematic review and meta-analysis of prospective studies to clarify the association between adiposity and risk of sudden cardiac death. PubMed and Embase databases were searched up to July 20th 2017. Summary relative risks (RRs) and 95% confidence intervals (CIs) were calculated using random effects models. The summary RR was 1.16 (95% CI 1.05-1.28, I2 = 68%, n = 14) per 5 unit increment in BMI, and 1.82 (95% CI 1.61-2.07, I2 = 0%, n = 3) per 0.1 unit increase in waist-to-hip ratio, and 1.03 (95% CI 0.93-1.15, I2 = 0%, n = 2) per 10 cm increase in waist circumference. The heterogeneity in the analysis of BMI and sudden cardiac death persisted across most subgroup analyses. The association was stronger among studies with longer follow-up compared to short follow-up and was observed in the European and American studies, but not in the Asian studies. There was a J-shaped association between BMI and sudden cardiac death and the lowest risk was observed in the normal weight range, however, the increased risk with a low BMI was attenuated among studies with a longer duration of follow-up. This meta-analysis suggest an increased risk of sudden cardiac death with increasing BMI and waist-to-hip ratio, however, further studies with stratification for smoking status are needed of waist circumference, weight changes and adiposity at younger ages.
Waist-to-hip ratio Sudden cardiac death
The prevalence of overweight and obesity has increased
rapidly over the last decades in all areas of the world [
Overweight and obesity are important risk factors for a
wide range of chronic diseases, including cardiovascular
diseases, type 2 diabetes, several types of cancer as well as
all-cause mortality [
], and the current trends are a
major challenge for public health both in terms of reduced
quality of life and increased medical costs [
Sudden cardiac death accounted for more than 350,000
deaths in the USA in 2014 [
]. Although clinical
guidelines focus on reducing risk in high-risk patients using
medical therapies, up to 75% of all sudden cardiac deaths
occur in patients not classified as high-risk by current
]. Although a substantial amount of data has
consistently showed that overweight and obesity increases
the risk of coronary heart disease [
], heart failure [
atrial fibrillation [
], all risk factors for sudden cardiac
death, data are more limited and less consistent regarding
the association between overweight and obesity and the
risk of sudden cardiac death [
]. Some studies showed
an increase in risk of sudden cardiac death with a greater
body mass index (BMI, weight in kg divided by height
squared in metres, kg/m2) [
16, 25, 27
], however, other
studies found associations only in non-current smokers
], no significant association [
15, 20, 21
], or even some
increase in risk with a low BMI [
]. Given the increased
prevalence of overweight and obesity globally establishing
whether excess BMI also is related to increased risk of
sudden cardiac death is of major public health importance
and could inform guidelines for prevention. For these
reasons we conducted a systematic review and
meta-analysis of prospective studies of adiposity and the risk of
sudden cardiac death. We aimed to clarify the direction and
strength of the association, shape of the dose–response
relationship and potential sources of heterogeneity between
Search strategy and inclusion criteria
We searched the PubMed and Embase databases up to July
20th 2017 for eligible studies (DA, and SS). A list of the
search terms used are provided in Supplementary Table 1
and 2. We followed standard criteria for reporting of
]. In addition, we searched the reference lists
of the relevant publications for further studies. Study
quality was assessed using the Newcastle–Ottawa scale
We included prospective and retrospective cohort studies
and nested case–control studies of the association between
adiposity measures (BMI, waist circumference,
waist-tohip ratio, hip circumference, and weight gain) and risk of
sudden cardiac death that were published in English.
Studies in high-risk populations (patient populations),
abstract only publications, grey literature and unpublished
studies were excluded. Adjusted relative risk estimates
(hazard ratio, risk ratio, or odds ratio) had to be available
with the 95% confidence intervals (CIs) in the publication
and for the dose–response analysis, a quantitative measure
of adiposity and the total number of cases and person-years
or non-cases had to be available in the publication. When
multiple publications were available from the same study
we used the study with the largest number of cases. A list
of the excluded studies and exclusion reasons are found in
the Supplementary Table 3.
We extracted the following data from each study: The first
author’s last name, publication year, country where the
study was conducted, study period, sample size, number of
cases/controls, exposure variable, exposure level, relative
risks and 95% confidence intervals for the highest versus
the lowest level of the exposure variable and variables
adjusted for in the analysis. Data were extracted by one
reviewer (DA) and checked for accuracy by a second
reviewer (SS). Any disagreements were resolved through
We calculated summary RRs and 95% CIs for a 5 unit
increment in BMI, a 0.1 unit increment in waist-to-hip
ratio, and 10 cm increase in waist circumference
(approximately equal to one standard deviation for each measure)
using a random effects model, which takes into account
heterogeneity between studies [
]. For the primary
analysis we used the model from each study that had the
greatest degree of control for potential confounding with
the exception of when potential intermediate risk factors
were adjusted for in a separate step (as an exploration of
how much of the association might be mediated by
cholesterol for example). The average of the natural
logarithm of the RRs was estimated and the RR from each
study was weighted according to the method of
DerSimonian and Laird [
]. A two-tailed p \ 0.05 was considered
statistically significant. If studies reported results
separately for men and women or other subgroups we combined
the subgroup-specific estimates using a fixed-effects model
to generate an overall estimate so that each study was only
represented once in the main analysis, but sex-specific
results are presented separately in subgroup analyses.
The method described by Greenland and Longnecker
] was used for the dose–response analysis of adiposity
measures and we calculated study-specific slopes (linear
trends) and 95% CIs from the natural logs of the reported
RRs and CIs across categories of each adiposity measures.
The mean level of BMI or WHR in each category was
assigned to the corresponding relative risk for each study
and for studies that reported the exposures in ranges we
calculated the average of the upper and the lower cut-off
point which was used as a midpoint. When the lowest or
highest category was open-ended or had an extreme range
we used the width of the adjacent interval to calculate an
upper or lower cut-off value. For studies that reported
continuous risk estimates per 1 BMI unit or per 3.3 BMI
units these risk estimates were converted to a risk estimate
per 5 BMI units by first taking the natural logarithm of the
RR (95% CI), then dividing the ln(RR, 95% CI) by the
increment reported, then multiplying by 5, and
backtransforming to non-logarithmic scale before inclusion in
the meta-analysis. A potential nonlinear dose–response
relationship between BMI, waist-to-hip ratio, and waist
circumference and risk of sudden cardiac death was
examined by using fractional polynomial models [
determined the best fitting second order fractional
polynomial regression model, defined as the one with the lowest
deviance. A likelihood ratio test was used to assess the
difference between the nonlinear and linear models to test
for nonlinearity [
]. Studies that only reported a
continuous risk estimate and not categorical data were excluded
in the nonlinear dose–response analysis as it requires that
data are reported for at least three categories of BMI.
Subgroup analyses stratified by sex, measurement versus
self-report of adiposity measures, duration of follow-up,
geographic location, number of cases, study quality scores,
and adjustment for confounders (age, smoking, alcohol,
physical activity) and potential intermediates
(hypertension, blood pressure, cholesterol, diabetes mellitus,
coronary heart disease, heart failure, and left ventricular
hypertrophy) were conducted to investigate potential
sources of heterogeneity and heterogeneity between studies
was quantitatively assessed by the Q test and I2 [
Metaregression analyses were used to examine between
subgroup differences in the summary estimates. Small study
effects, such as publication bias, were assessed by
inspecting the funnel plots for asymmetry and with Egger’s
] and Begg’s test [
] with the results considered to
indicate small study effects when p \ 0.10. Sensitivity
analyses excluding one study at a time were conducted to
clarify whether the results were simply due to one large
study or a study with an extreme result. The statistical
analyses were conducted using Stata software version 13.0
(StataCorp, College Station, TX, USA).
We identified 14 prospective studies (13 publications)
] that were included in the systematic review of
BMI, waist-to-hip ratio, and waist circumference and risk
of sudden cardiac death (Supplementary Table 4; Fig. 1).
Only one study reported on BMI in early adulthood (at age
18 years) [
] or weight change [
] and sudden cardiac
death and meta-analyses were therefore not possible for
these measures. All studies reported on BMI at baseline
and the studies were conducted mostly in middle-aged
populations. The age range or mean age for each study is
provided in Supplementary Table 4 and the lower and
higher age range across studies was 30 and 84 years,
respectively. The mean (median) duration of follow-up was
1994 records identified in total:
749 records identified in PubMed
1242 records identified in Embase
3 records from other searches
79 reporting on adiposity and sudden cardiac death
1915 excluded based on title or
14 not relevant exposure
9 not relevant outcome
5 patient populations
4 case-control study
3 cardiac arrest
2 survival after cardiac arrest
2 case only study
2 no risk estimates
1 comparison group was
survivors of myocardial infarction
1 metabolic syndrome
1 not relevant data
1 no confidence intervals
13 publications (14 studies) included
16.4 (11.8) years and ranged from 5.2 to 38 years. Three
studies included only men, two included only women and
nine studies included both men and women. Eight studies
were from Europe, three were from the USA, and three
were from Asia (Japan) (Supplementary Table 4).
Body mass index
Fourteen prospective studies (11 publications)
15–18, 20–22, 24–27
] were included in the linear dose–
response analysis of BMI and sudden cardiac death
incidence and included 3376 cases among 406,079
participants. The summary RR for a 5 unit increment in BMI was
1.16 (95% CI 1.05–1.28, I2 = 68.2%, pheterogeneity \
0.0001) (Fig. 2a). All but one of the studies found
increased risk, but the strength of the association differed
between studies. In sensitivity analyses excluding the most
influential studies, the summary RR ranged from 1.14 (95%
CI 1.03–1.27) when excluding the Nurses’ Health Study
] to 1.20 (95% CI 1.09–1.31) when excluding the Health
2002 study [
] (Supplementary Table 5). There was no
indication of publication bias with Egger’s test, p = 0.18,
Body mass index and sudden cardiac death, dose-response analysis, per 5 BMI units
1.30 ( 1.16, 1.46)
1.20 ( 1.04, 1.37)
1.48 ( 1.30, 1.69)
1.38 ( 1.15, 1.67)
1.09 ( 0.91, 1.31)
1.28 ( 1.10, 1.54)
1.05 ( 0.86, 1.22)
1.22 ( 0.95, 1.54)
0.86 ( 0.66, 1.05)
0.94 ( 0.72, 1.23)
0.61 ( 0.39, 0.96)
0.90 ( 0.59, 1.40)
1.33 ( 1.05, 2.58)
1.43 ( 1.03, 1.98)
1.16 ( 1.05, 1.28)
.75 1 1.5
Body mass index and sudden cardiac death, nonlinear dose-response analysis
or with Begg’s test, p = 0.27, and there was no evidence of
asymmetry by inspection of the funnel plot (Supplementary
Figure 1). Seven studies [
15, 18, 20, 21, 25–27
included in the nonlinear dose–response analysis. There
was evidence of a nonlinear J-shaped association between
BMI and sudden cardiac death, pnonlinearity \ 0.0001
(Fig. 2b, Supplementary Table 6) with a slight increase in
risk in the underweight categories, and a 14%, 60% and
2–3 fold increase in risk in the overweight, obese, and
severely obese categories. When the nonlinear
dose–response analysis was stratified by duration of follow-up the
association between low BMI and increased risk of sudden
cardiac death was stronger among the studies with \ 10
years follow-up than among studies with C 10 years
follow-up, and in addition, the optimal BMI was around 23
and 20–22 among the studies with short and long-follow-up
duration, respectively (Supplementary Figures 2, 3).
Waist-to-hip ratio and waist circumference
Three prospective studies [
19, 21, 26
] were included in the
analysis of waist-to-hip ratio and risk of sudden cardiac
Waist-to-hip ratio and sudden cardiac death, nonlinear dose-response analysis
Waist-to-hip ratio and sudden cardiac death, dose-response analysis, per 0.1 units
death (817 cases, 179,117 participants) and the summary
RR for a 0.1 unit increment in waist-to-hip ratio was 1.82
(95% CI 1.61–2.07, I2 = 0%, pheterogeneity = 0.77)
(Fig. 3a). Although the test for nonlinearity was significant,
pnonlinearity = 0.02, there was no evidence of a threshold
effect and the association increased strongly even with
modest increases in waist-to-hip ratio (Fig. 3b,
Supplementary Table 7).
Two prospective studies [
] reported on waist
circumference and sudden cardiac death (312 cases, 15,972
participants) and the summary RR for a 10 cm increase
was 1.03 (95% CI 0.93–1.15, I2 = 0%, pheterogeneity =
0.54) (Fig. 4). Nonlinear dose–response analysis was not
possible because only one of the studies reported
In subgroup analyses of the association between BMI and
sudden cardiac death there was suggestive heterogeneity
when the analyses were stratified by duration of follow-up,
pheterogeneity = 0.06, with stronger associations among
studies with longer duration of follow-up, and when
analyses were stratified by geographic location, pheterogeneity =
0.09, with no association among the Asian studies, while
a positive association was observed among the European
and North American studies (Table 1). There was no
significant heterogeneity between the remaining subgroup
analyses and there were positive associations in most of
them although the association was not always significant
possibly because of the limited number of studies in
some subgroups. Study quality was high with a mean
(median) score of 7.6 [
] out of 9 points (Supplementary
This is to our knowledge is the first meta-analysis of
adiposity and the risk of sudden cardiac death. There was a
16% increase in the relative risk per 5 units increase in
BMI and an 82% increase in relative risk per 0.1 unit
increase in waist-to-hip ratio, based on eight and three
studies, respectively, however, no association was
observed among two studies of waist circumference. There
was evidence of a nonlinear J-shaped association between
BMI and sudden cardiac death, with a slight increase in
risk in the underweight categories, and a 14%, 60% and
2–3 fold increase in risk in the overweight, obese and
severely obese categories. The association between
waistto-hip ratio and sudden cardiac death was also nonlinear,
but the dose–response curve was slightly steeper at lower
levels of waist-to-hip ratio than at higher levels. Our
current findings are consistent with previous studies that have
found that adiposity increases the risk of other heart
conditions that increase the risk of sudden cardiac death
including coronary heart disease [
], heart failure [
atrial fibrillation [
Our meta-analysis has some limitations that need to be
mentioned. Confounding by other risk factors may have
influenced the results. We conducted several subgroup
analyses to try to clarify whether adjustment for specific
confounding factors influenced the summary estimates.
The association between BMI and sudden cardiac death
was in the direction of increased risk in most subgroup
analyses, however, it was not significant in every subgroup
analysis (possibly because there were few studies and low
statistical power in some subgroups). More importantly,
there was no heterogeneity between the subgroups analyses
stratified by adjustment for confounding factors and
potential intermediate factors. The association was not
significant among the studies that adjusted for hypertension
(which could be considered an intermediate factor),
however, the association was significant among the studies that
adjusted for blood pressure. The reason for the difference
might be a mix of chance and limited statistical power in
the analysis with adjustment for hypertension as there were
only four studies in that subgroup analysis, while there
were eight studies in the subgroup analysis with adjustment
n denotes the number of studies. The number of studies is not always equal to the total because the subgroup analyses were not applicable to
some studies or information was not provided in the publication
aP for heterogeneity within each subgroup
bP for heterogeneity between subgroups
cP for heterogeneity between men and women (excluding men/women combined)
for blood pressure. The association persisted among studies
that adjusted for serum cholesterol and coronary heart
disease, but not among studies that adjusted for diabetes
mellitus, but again there was no heterogeneity between the
There was suggestion of a stronger association between
BMI and sudden cardiac death among studies with longer
compared to shorter durations of follow-up. There was no
association among the studies with 5–\ 10 years of
followup, but a 12% increase in the relative risk per 5 BMI units
among studies with 10 \ 15 years follow-up and a 32%
and 28% increase in the relative risk among studies with
15–\ 20 and C 20 years follow-up, respectively. The
increased risk observed with a low BMI in the nonlinear
dose–response analysis was also substantially attenuated
among studies with longer (C 10 years) follow-up, while it
was stronger among the studies with shorter (\ 10 years)
follow-up and the optimal BMI was around 23 among the
studies with short follow-up, and around 20–22 among the
studies with longer follow-up. This is similar to what we
have previously found in relation to heart failure [
all-cause mortality [
] and might to some degree reflect
confounding by illness and associated weight loss which
may have a greater impact in studies with a short duration
of follow-up than among studies with a long duration of
], or alternatively it might reflect weight
gain over time which could contribute to increased risk
beyond that of baseline BMI . For example, if only a
baseline anthropometric assessment was conducted in the
included studies, people who were normal weight at
baseline might become overweight, and people who were
overweight might become obese (given trends with
increased weight gain in most populations over time [
but because of only the baseline assessment they would
still be categorized as normal and overweight, respectively.
The studies with the longest duration of follow-up would
then also be the studies were the weight increased the most
over time and if weight gain increases risk of sudden
cardiac death, those studies would show the strongest
associations. Lastly, smoking may be a strong confounding
factor of the association between BMI and health outcomes
because smoking is strongly associated with a number of
chronic diseases and mortality [
], but at the same time is
associated with lower BMI [
] and may therefore
confound and drive the optimal BMI upwards as observed in
our previous analysis of BMI and all-cause mortality [
and might also at least partly explain the observed slight
increase in risk of sudden cardiac death with a low BMI of
16.7–17.5 compared to a BMI of around 20–22.
Unfortunately it was not possible to conduct similar stratified
analyses by smoking status in the current meta-analysis
because only one of the included studies reported such
stratified analyses [
]. However, that study reported RRs
(95% CIs) of 1.73 (1.06–2.84), 1.94 (1.12–3.33), and 3.36
(1.86–6.07) for BMI categories of 25–29.9,
30–34.9, C 35.0 compared to 18.5–24.9 among
nonsmokers and 1.39 (0.43–4.50), 0.86 (0.55–1.33, 0.94
(0.53–1.65), 0.34 (0.08–1.41) for BMI categories
of \ 18.5, and 25–29.9, 30–34.9, C 35.0 compared to
18.5–24.9 among current smokers, strongly supporting a
negative confounding effect of smoking on the association
between BMI and sudden cardiac death.
Measurements of weight, height, waist and hip
circumferences may have been affected by measurement errors,
however, the association for BMI was significant only
among the studies that used measured weight and height,
not among those that used self-reported weight and height
or those where the assessment of weight and height was
unclear. This is probably also a chance finding as there was
only two studies with either self-reported or unclear
anthropometric measurements and because there was no
heterogeneity between the different measurements of
anthropometric factors. Validation studies have reported
high correlations between self-reported and measured
anthropometric measures [
]. BMI is an imperfect
measure of body fatness as it does not distinguish between
body fat and muscle mass. However, studies have shown
high correlations between BMI and waist measures and
body fat as measured by dual-energy x-ray absorptiometry
]. The association between adiposity and
sudden cardiac death was positive for both BMI and
waistto-hip ratio, although the dose–response relationship
appeared to be stronger for the latter. Although publication
bias or small study bias can affect the findings of
metaanalyses of published literature, we found no evidence of
such bias with Egger’s or Begg’s test. Because there was
only one study on BMI in early adulthood and weight
changes in relation to sudden cardiac death and because of
the limited number of studies on waist circumference
further studies are needed of these adiposity measures in
relation to risk of sudden cardiac death.
Several mechanisms could explain an association
between body fatness and increased risk of sudden cardiac
death. Adiposity is associated metabolic disturbances
including higher levels of total and LDL-cholesterol and
lower HDL cholesterol [
], dyslipidemia [
resistance and diabetes [
] and inflammation which
contributes to increased risk of sudden cardiac death
16, 46, 47
]. Adiposity increases hemodynamic stress
which activates the renin-antiotensin-aldosterone system
leading to elevated aldosterone levels, which again
increases blood volume and cardiac output and thereby
contributes to left ventricular hypertrophy [
Adiposity also contributes to increased risk of hypertension 
and higher resting heart rate [
], which increases the
risk of sudden cardiac death [
studies have shown that the heart adapts to obesity through
eccentric cardiac hypertrophy, but to hypertension through
concentric hypertrophy, and when both obesity and
hypertension coexists, features of both concentric and
eccentric ventricular hypertrophy results [
]. Obesity is
associated with the secretion of cytokines that influence the
heart’s physiology and structure. High levels of leptin
observed in obesity increases myocardial fat, reduces
contractility and hypertrophy [
]. Adiposity is associated
with low-grade inflammation and elevated levels of
inflammatory markers such as tumor necrosis factor-alpha
which reduces adiponectin and thereby increases left
ventricular hypertrophy through AMP kinase signaling and
alpha-adrenergic receptor stimulation [
resistance contributes to left ventricular hypertrophy through
IGF-1 receptor stimulation [
]. Obesity is also associated
with increased risk of cardiomyopathy [
increases the susceptibility to ventricular arrhytmia and
sudden cardiac death. Excess weight is also associated with
increased risk of medical conditions such as coronary heart
], heart failure [
], and atrial fibrillation [
which are established risk factors for sudden cardiac death
16, 46, 47, 61
]. Obese patients without and with eccentric
left ventricular hypertrophy have been shown to have
10-fold and 30-fold increased risk of premature ventricular
contractions, respectively, compared to lean persons .
Ventricular ectopy (three or more premature beats per
hour) or ventricular tachycardia are associated with
increased risk of mortality among patients with coronary
artery disease, valvular disease and cardiomyopathy and
has been shown to be responsible for three out of four
ventricular fibrillation episodes [
]. Necropsy studies
have found epicardial fat infiltration of the sinus node, fatty
and fibrotic changes involving the atrioventricular node,
and myocyte hypertrophy in morbidly obese subjects
]. Studies have also found that obesity and morbid
obesity is associated with alterations of the heart rate, pulse
rate interval, QRS duration, QTc interval, P-, QRS-,
T-wave axes and low QRS voltage [
], which have
been associated with increased risk of sudden cardiac death
], and that weight loss by bariatric surgery reduced
some of these alterations [
]. In one study the
multivariable-adjusted hazard ratio for a BMI of C 35 versus
21.0–22.9 was 2.18 (95% CI 1.44–3.28) and when further
adjusted for potential intermediates, including high
cholesterol, hypertension, diabetes, angina, and heart
failure it was attenuated to 1.72 (95% CI 1.13–2.60),
suggesting that part of the association might be mediated by
these traditional risk factors, but that other risk factors (e.g.
left ventricular hypertrophy, resting heart rate and others)
also could contribute to the increased risk.
Our meta-analysis has several strengths including the
prospective design of the included studies which avoids
recall bias and reduces the possibility for selection bias,
and with [ 3300 cases and [ 406,000 participants there
was sufficient statistical power to detect moderate
associations. Additional strengths include the detailed
dose–response analyses which clarified the shape of the dose–
response relationship and the robustness of the findings in
multiple subgroup analyses as well as the high study
quality of the included studies.
The findings have important clinical and public health
implications because of the increasing prevalence of
overweight and obesity worldwide [
], thus if current
trends continue unabated it might contribute to an
increased rates of sudden cardiac death.
In conclusion, this meta-analysis suggest an increased
risk of sudden cardiac death with increasing BMI and
waist-to-hip ratio, however, further studies with adjustment
for confounding factors and with stratified analyses by
smoking status are needed of waist circumference, weight
changes and adiposity at younger ages.
Acknowledgements This work has been supported by funding from
the Imperial College National Institute of Health Research (NIHR)
Biomedical Research Centre (BRC) and the South-East Regional
Health Authorities of Norway. The study sponsor had no role in the
study design, collection of data, analysis, and interpretation of data.
D. Aune takes primary responsibility for the integrity of the data and
the accuracy of the data analysis. We thank Darren C. Greenwood
(Biostatistics Unit, Centre for Epidemiology and Biostatistics,
University of Leeds, Leeds, United Kingdom) for providing the Stata
code for the nonlinear dose–response analysis.
Open Access This article is distributed under the terms of the
Creative Commons Attribution 4.0 International License (http://crea
tivecommons.org/licenses/by/4.0/), which permits unrestricted use,
distribution, and reproduction in any medium, provided you give
appropriate credit to the original author(s) and the source, provide a
link to the Creative Commons license, and indicate if changes were
Author’s contributions DA: Conceived and designed the research.
DA, SS: Acquired the data. DA, SS, TN, ER: Analyzed and
interpreted the data. DA: Performed statistical analysis. ER, TN: Handled
funding and supervision. DA: Drafted the manuscript. DA, SS, ER,
TN: Made critical revision of the manuscript for intellectual content.
DA, SS: Reference screening.
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