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Excess mortality at Christmas due to cardiovascular disease in the HUNT study prospective population-based cohort in Norway


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Background: Although it is known that winter inclusive of the Christmas holiday period is associated with an increased risk of dying compared to other times of the year, very few studies have specifically examined this phenomenon within a population cohort subject to baseline profiling and prospective follow-up. In such a cohort, we sought to determine the specific characteristics of mortality occuring during the Christmas holidays. Methods: Baseline profiling and outcome data were derived from a prospective population-based cohort with longitudinal follow-up in Central Norway - the Trøndelag Health (HUNT) Study. From 1984 to 1986, 88% of the target population comprising 39,273 men and 40,353 women aged 48 ± 18 and 50 ± 18 years, respectively, were profiled. We examined the long-term pattern of mortality to determine the number of excess (all-cause and cause-specific) deaths that occurred during winter overall and, more specifically, the Christmas holidays. Results: During 33.5 (IQR 17.1-34.4) years follow-up, 19,879 (50.7%) men and 19,316 (49.3%) women died at age-adjusted rate of 5.3 and 4.6 deaths per 1000/annum, respectively. Overall, 1540 (95% CI 43-45 deaths/season) more all-cause deaths occurred in winter (December to February) versus summer (June to August), with 735 (95% CI 20-22 deaths per season) of these cardiovascular-related. December 25th-27th was the deadliest 3-day period of the year; being associated with 138 (95% CI 96-147) and 102 (95% CI 72-132) excess all-cause and cardiovascular-related deaths, respectively. Accordingly, compared to 1st-21st December (equivalent winter conditions), the incidence rate ratio of all-cause mortality increased to 1.22 (95% CI 1.16-1.27) and 1.17 (95% 1.11-1.22) in men and women, respectively, during the next 21 days (Christmas/New Year holidays). All observed differences were highly significant (P < 0.001). A less pronounced pattern of mortality due to respiratory illnesses (but not cancer) was also observed. Conclusion: Beyond a broader pattern of seasonally-linked mortality characterised by excess winter deaths, the deadliest time of year in Central Norway coincides with the Christmas holidays. During this time, the pattern and frequency of cardiovascular-related mortality changes markedly; contrasting with a more stable pattern of cancer-related mortality. Pending confirmation in other populations and climates, further research to determine if these excess deaths are preventable is warranted.
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R E S E A R C H A R T I C L E Open Access
Excess mortality at Christmas due to
cardiovascular disease in the HUNT study
prospective population-based cohort in
Trine Moholdt
, Clifford Afoakwah
, Paul Scuffham
, Christine F. McDonald
, Louise M. Burrell
Simon Stewart
Background: Although it is known that winter inclusive of the Christmas holiday period is associated with an
increased risk of dying compared to other times of the year, very few studies have specifically examined this
phenomenon within a population cohort subject to baseline profiling and prospective follow-up. In such a cohort,
we sought to determine the specific characteristics of mortality occuring during the Christmas holidays.
Methods: Baseline profiling and outcome data were derived from a prospective population-based cohort with
longitudinal follow-up in Central Norway - the Trøndelag Health (HUNT) Study. From 1984 to 1986,88% of the target
population comprising 39,273 men and 40,353 women aged 48 ± 18 and 50 ± 18 years, respectively, were profiled.
We examined the long-term pattern of mortality to determine the number of excess (all-cause and cause-specific)
deaths that occurred during winter overall and, more specifically, the Christmas holidays.
Results: During 33.5 (IQR 17.134.4) years follow-up, 19,879 (50.7%) men and 19,316 (49.3%) women died at age-
adjusted rate of 5.3 and 4.6 deaths per 1000/annum, respectively. Overall, 1540 (95% CI 4345 deaths/season) more
all-cause deaths occurred in winter (December to February) versus summer (June to August), with 735 (95% CI
2022 deaths per season) of these cardiovascular-related. December 25th27th was the deadliest 3-day period of
the year; being associated with 138 (95% CI 96147) and 102 (95% CI 72132) excess all-cause and cardiovascular-
related deaths, respectively. Accordingly, compared to 1st21st December (equivalent winter conditions), the
incidence rate
ratio of all-cause mortality increased to 1.22 (95% CI 1.161.27) and 1.17 (95% 1.111.22) in men and women,
respectively, during the next 21 days (Christmas/New Year holidays). All observed differences were highly significant
(P< 0.001). A less pronounced pattern of mortality due to respiratory illnesses (but not cancer) was also observed.
(Continued on next page)
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* Correspondence:
Torrens University Australia, South Australia, Wakefield Campus, Adelaide, SA
5000, Australia
University of Glasgow, Glasgow, Scotland, UK
Full list of author information is available at the end of the article
Moholdt et al. BMC Public Health (2021) 21:549
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(Continued from previous page)
Conclusion: Beyond a broader pattern of seasonally-linked mortality characterised by excess winter deaths, the
deadliest time of year in Central Norway coincides with the Christmas holidays. During this time, the pattern and
frequency of cardiovascular-related mortality changes markedly; contrasting with a more stable pattern of cancer-
related mortality. Pending confirmation in other populations and climates, further research to determine if these
excess deaths are preventable is warranted.
Keywords: Population cohort, Longitudinal follow-up, Mortality, Cardiovascular disease, Seasonality
Although age-standardised mortality is typically reported
as the number of deaths per 1000 people at risk per
annum, deaths are rarely evenly distributed throughout
the year. Typically, more deaths due to cardiovascular
disease (CVD) occur in winter compared to summer [1].
Paradoxically, seasonal variations in cardiovascular-
related mortality are not simply explained by exposure
to environmental provocations such as cold tempera-
tures, reduced daylight hours, infections, or increased
pollution [25]. Rather, they appear to reflect a more
complex interplay between the environment and an indi-
viduals physical and psychological condition, their be-
haviours and the culture/society in which they live [4,6].
In Scandinavia, for example, an individual-to-societal
adaptation to extremely cold temperatures undoubtedly
mitigates the cyclic exposure and physiological responses
to seasonally driven provocations to cardiovascular
health [7].
Previous studies have sought to link clusters of in-
creased mortality to large earthquakes [8] and the FIFA
World Cup [9]. Beyond these exceptional events, there is
an event that has strong potential to be detrimental to
an individuals cardiovascular health on an annual basis
[10,11]. At Christmas, people around the world engage
in potentially stressful social interactions and provoca-
tive behaviours they would not normally expose them-
selves to. In those already at risk of seasonal patterns of
mortality (i.e., where Christmas coincides with winter),
these factors may act as additional, short-term triggers
for a broad range of cardiovascular-related events [12].
A number of studies based on administrative data have
previously demonstrated increased rates of mortality [12,
13], hospitalisation [11] and acute myocardial infarction
(AMI) in Sweden during the Christmas holidays [10].
Beyond these studies, however, this phenomenon re-
mains poorly characterised [1].
We hypothesised that over and beyond long-term sea-
sonal trends within a population periodically exposed to
cold winters, we would find an additional risk of dying
over the Christmas holidays. In effect this would repre-
sent an increased period of increased mortality within an
already high-risk period of the year. We also hypothe-
sised that CVD would be the major contributor to this
phenomenon and that we would find sex-specific differ-
ences in this regard.
Study context
Norway (population ~ 5.5 million people) has a long
tradition of undertaking insightful, longitudinal popula-
tion cohort studies. This includes the Tromsø Study in
Northern Norway [7,14], and the focus of this report,
the Trøndelag Health (HUNT) Study [15]. Although the
warm currents of the Gulf Stream moderate its weather,
given its northerly latitude, Norway experiences extreme
weather conditions. Central Norways Köppen Climate
Classification subtype is Continental Subarctic Climate
[16]. The coldest month is January (mean temperature
of minus 3 °C) and the warmest month is July (around
13 °C) with a mean annual temperature of 4.8 °C overall.
Although Norway enjoys relatively clean air, the winter
solstice and darkest days of the year coincide with
Study design
We examined the long-term pattern of mortality
within the prospective, longitudinal, population-based
HUNT Study cohort living in Central Norway [15,
17]. The present study was approved by the Regional
Committee for Ethics in Medical Research (REK-midt,
no. 2018/1509).
Data collection
The original wave of population screening (HUNT1) was
undertaken during 19841986, with 88% of eligible in-
habitants aged 20 years in Nord-Trøndelag County re-
cruited. Here, we include the 79,626 men and women
who attended a clinical examination and filled out de-
tailed questionnaires about their health and lifestyle [15].
Specifically, data on socio-economic status, perceived
levels of health and life satisfaction, lifestyle behaviours,
and self-reported cardiovascular health CVD were de-
rived from validated questionnaires [15,17]. We used a
previously developed index of physical activity to cat-
egorise levels of leisure-time physical activity [18].
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Study outcomes
The unique personal identification number of all Norwe-
gian citizens allows linkage of each participants record
in the HUNT Study to information from the national
Cause of Death Registry on the timing and primary
cause of death. These are classified according to the
International Classification of Disease (ICD) with pre-
cise death coding data available until 1st January 2018.
Based on the listed causes of death and the pre-specified
hypotheses, the main codes of interest were - CVD (i.e.,
ICD-9: 390459 and ICD-10: I00-I99t inclusive of the
specific codes for coronary artery disease [CAD], acute
myocardial infarction [AMI], cerebral infarction, and
sudden cardiac death), as well as cancer/malignancy and
respiratory disease/illness. Regardless of cause of death
coding, data on the occurrence and timing of death were
available for the full follow-up period (1984 to 2020).
Using these data, the specific focus of this study was cal-
culating (if appropriate) the number of excess deaths (on
a crude and adjusted basis) occurring during the key
time-points of interest.
Data analyses
This study conforms to the STROBE guidelines for the
reporting of observational studies [19]. Deaths were ini-
tially grouped according to whether they occurred in
winter (December, January, and February), spring
(March, April, and May), summer (June, July, and
August) or autumn (September, October. and
November). Mortality data were also grouped into 3-day
rolling totals to identify potentially more specific periods
of increased mortality (including Christmas). Subse-
quently, three specific 21-day periods were purposefully
selected for more granular analyses and comparison 1)
the 21 days in which, on a statistical basis, the least num-
ber of all-cause deaths occurred (17th May-6th June); 2)
the 21 days of winter preceding Christmas (1st21st
December selected as the reference period for all com-
parisons) in which mortality rates were reflective of the
broader winter period and; 3) the subequent 21 days
inclusive of the Christmas holiday period (22nd
December-11th January) in which mortality rates were
elevated above the winter average. The main outcome
variable is the counts of deaths per day while the main
exposure variable is the time (for example, Christmas or
winter period). We modelled excess mortality by adjust-
ing for baseline characteristic such as sex, age at death,
month, and annual trends. The number of lower/excess
deaths per period was then estimated using the ordinary
least squares (OLS) method. A Poisson approach was
then used to estimate the increased/decreased risk of
mortality (incidence rate ratio [IRR] with 95% CIs) due
to exposure to the Christmas holiday period. Using the
variables summarised in Table 1, we generated adjusted
hazard ratios (HR) for all-cause mortality for the entire
cohort during the median study period of 33.5 (IQR 17.1
to 34.4) years follow-up using a Cox-Proportional Haz-
ard model (entry model using only those cases with full
profiling data). These same methods (Cox-Proportional
Hazard models) were used to directly compare the
correlates of dying in a) the first 21 days of winter
(December 1st to 21st) versus the lowest 21-day period
of deaths during the rest of the year (May 17th to June
6th) in 2894 participants who died during this combined
42-day period) and b) December 22nd to January 11th
(21 days inclusive of Christmas/New Year holidays) ver-
sus the preceding 21 days (December 1st to 21st) on a
sex-specific basis. All analyses were performed using
SPSS v26.0 and STATA v13. Statistical significance was
accepted at a 2-sided alpha of P< .05.
Cohort characteristics
The study cohort comprised 40,353 women (50.1%) and
39,273 men aged 50 ± 18 and 48 ± 18 years, respectively.
Two-thirds were married and just over half had < 10
years of formal education. Most participants reported
generally positive health and life-satisfaction levels. Al-
ternatively, many had relatively high levels of risk for
CVD and other chronic diseases, including elevated
baseline levels of blood pressure (BP) and smoking com-
bined with relatively high levels of sedentary behaviours
and overweight status (Table 1).
All-cause mortality
During the 35-year study period, there were 39,195
deaths (49.2%) comprising 19,879 (50.7%) men and 19,
316 (49.3%) women. As shown in Fig. 1, these deaths
were not evenly distributed over time. Age-adjusted
mortality was slightly higher in men compared to
women (5.3 and 4.6 deaths per 1000/annum, respect-
ively); rising from 1.6 to 224 deaths and from 1.1 to 183
deaths per 1000/annum in men and women initially
aged < 30 years and > 80 years, respectively. An increased
risk of all-cause mortality (P< .001 for all comparisons
unless indicated) was correlated with advancing age (ad-
justed HR 1.11, 95% CI 1.111.12 per year), male sex
(1.59, 1.551.64 versus women), lower education (1.15,
1.111.18 for 9 years education versus rest), greater
unhappiness (1.30, 1.211.39 for any degree of life
dissatisfacton versus rest), being divorced/separated
(1.15, 1.061.20 versus unmarried), obesity (1.13, 1.09
1.18), being a current smoker (1.89, 1.791.91 versus
rest), excessive alcohol intake (1.09, 1.021.16 for > 10
drinks in 14-days versus abstinence; P= .017), an ele-
vated heart rate (1.03, 1.021.03 per 5 beats/min), higher
systolic (1.02, 1.021.03 per 5 mmHg) and diastolic BP
(1.01, 1.001.02 per 5 mmHg), as well as a self-reported
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Table 1 Baseline characteristics according to survival status
(n= 79,626)
(n= 40,431)
(n= 39,195)
Demographic Profile
Women, % 40,353 (50.7) 21,037 (52.1) 19,316 (47.9)
Age Groups, %
Aged < 35 years 22, 208 (27.9) 20, 739 (50.4) 1469 (3.7%)
Aged 3544 years 15,556 (19.5) 12,602 (31.2) 2954 (7.5%)
Aged 4564 years 24,874 (31.2) 7063 (17.5) 17,811 (45.4%)
Aged 65+ years 16,988 (21.3) 27 (0.001) 16,961 (43.3%)
Mean age at baseline (years) 49.1 ± 18.0 35.7 ± 9.6 62.9 ± 13.6
Mean age at end follow-up (years) 74.9 ± 11.6 70.1 ± 11.4 79.9 ± 9.6
Married, % (n= 76,775) 52,709 (66.6) 26,532 (69.5) 26,177 (67.8)
9 years education, % (n= 61,240) 32,928 (53.9) 9082 (29.9) 23,886 (77.4)
Employment status, % (n= 76,870)
Full-time employment 32,333 (42.1) 21,585 (66.8) 10,748 (28.0)
Part-time employment/housework 21,381 (27.8) 13,219 (34.4) 8162 (21.2%)
Non-employed/ retired 23,156 (30.1) 3623 (15.6) 19,533 (50.8)
Health Status
Life Satisfaction, % (n= 75,815)
Dissatisfied (Quite to Extremely) 2005 (2.6) 630 (1.7) 1375 (3.6)
Satisfied (Quite to Extremely) 62,342 (82.2) 32,967 (86.6) 29,375 (77.9)
General Health Status, % (n= 76,863)
Bad 2023 (2.6) 202 (0.5) 1821 (4.7)
Poor 18,752 (24.4) 4615 (12.0) 14,317 (36.7)
Good 44,215 (57.5) 24,411 (63.6) 19,804 (51.5)
Very Good 11,873 (15.4) 9165 (23.9) 2708 (7.0)
Physical Activity Status, % (n=57,212)
Inactive 27,145 (47.4) 13,157 (45.1) 13,988 (49.9)
Low 18,730 (32.7%) 9728 (33.3) 9002 (32.1)
Moderate 8283 (14.5) 4951 (17.0) 3332 (11.9)
High 3054 (5.3) 1362 (4.7) 1692 (6.0)
Alcohol intake, % (n= 61,520)
4 or less drinks in 14 days 50,376 (81.9) 27,143 (88.3) 23,233 (76.6)
5 or more drinks in 14 days 3608 (5.9) 1685 (5.5) 1923 (5.1)
Abstains 7536 (12.2) 1899 (6.2) 5637 (18.3)
Current smoker, % (n= 60,421) 20,667 (34.2) 10,885 (36.7) 9782 (32.9)
Mean BMI kg/m
(n= 74,330) 25. ±3.9 24.2 ± 3.4 26.2 ± 4.1
Mean heart rate, bpm (n= 74,906) 74.9 ± 12.6 73.8 ± 11.9 76.0 ± 13.1
Mean BP, mmHg (n= 74,832)
Systolic BP/ 139 ± 23.5 / 127 ± 15.2 / 150 ± 25.0 /
Diastolic BP 84.6 ± 15.2 80.9 ± 15.2 88.5 ± 11.7
Angina pectoris (%) (n= 76,742) 3450 (4.5) 113 (0.3) 3337 (8.7)
AMI, % (n= 76, 723) 1986 (2.6) 39 (0.1) 1947 (5.1)
Stroke, % (n= 76,794) 1412 (1.8) 59 (0.2) 1353 (3.5)
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history of AMI (1.65, 1.551.76), angina pectoris (1.26,
1.201.33) and stroke/cerebral event (1.48, 1.361.60).
Alternatively, being married (adjusted HR 0.80, 95% CI
0.770.83 versus unmarried), better self-reported general
health (0.76, 0.740.79 for good/very good versus rest),
mild alcohol intake (0.94, 0.910.97 14 drinks in 14-
days versus abstinence) and greater levels of exercise
(0.89, 0.860.92 for moderate to high adherence to rec-
ommended exercise versus rest) were associated with a
reduced risk of all-cause mortality.
Specific causes of death
The three most common causes of death in men and
women were CVD (8355 [43.6%] and 7969 deaths
[43.0%], respectively), cancer (5051 [26.4%] and 4150
deaths [22.4%]), and respiratory disease/illness (1599
[8.3%] and 1606 [8.7%] deaths). Collectively, these
accounted for 78 and 74% of all deaths in men and
women, respectively. Other causes of death included
endocrine disorders (1343 [3.4%]), psychiatric disorders
(1118 [2.9%]) and external factors including motor ve-
hicle accidents and violence (951 [2.5%]). Consistent
with all-cause mortality, there were marked fluctuations
(with clear peaks and troughs) in those deaths attribut-
able to CVD and respiratory disease.
Seasonal patterns of mortality
On an absolute basis, 1707 more deaths occurred in
winter (10,790 [27.5%]) compared to summer (9083
[23.2%]) during the 35-year study period. The differential
between cardiovascular- and respiratory-related mortal-
ity occurring in winter (4446 [27.4%] and 1037 [32.4%]
deaths) versus summer (3832 [23.5%] and 661 [20.6%]
deaths) contributed to 59% (1010 deaths) of the ob-
served variance between winter and summer. Although a
more stable pattern of mortality was observed in spring
(9900 [25.3%] deaths) and autumn (9442 [24.0%] deaths),
a seasonal pattern was still evident. On adjusted basis,
each winter there were 44 (95% CI 4345/annum) more
deaths when compared to the equivalent 3 months of
summer. The main contributors to the excess deaths oc-
curring in winter were CVD (21, 95% CI 2022 deaths/
annum), respiratory disease (13, 95% CI 1314 deaths/
annum) and other miscellaneous conditions (14, 95% CI
1314 deaths/annum). Alternatively, as indicated by
Fig. 2, over the entire 35-year study period, cancer-
related deaths occurred at a far more stable, seasonal
rate (the absolute difference between winter versus
summer-being 10 deaths).
The Christmas holiday effect
Regardless of the season, accumulative 3-day mortality
consistently fluctuated between 90 and 110 deaths, apart
from a clear increase in mortality commencing on the
22nd of December. The subsequent 3-day period over
Christmas was the deadliest of the year (Fig. 3) with 439
all-cause deaths occurring on 25th 27th December.
This was not a random phenomenon and was largely
driven by an increase in cardiovascular-related and, to a
lesser extent, cancer-related deaths (Fig. 4). On an ad-
justed basis, over the entire 35-year study period, an
additional 138 (95% CI, 114159) more all-cause deaths
occurred during this specific 3-day period compared to
those same calendar days during the rest of the year.
CVD (an extra 105 [95% CI 75138] deaths per day) was
the main contributor to this phenomenon. This elevated
mortality rate persisted until early January. During the
21 days from the 22nd of December, there were 2679
deaths (51.1% women) compared to 2351 deaths (49%
women) during the preceding 21 days versus 2016 deaths
Fig. 1 Fluctuating Patterns of Mortality. Total all-cause and cause-specific death counts were plotted in 3-monthly intervals (synchronised to each
distinctive season) over the entire 35-year study period
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(49.6% women) during the lowest 21 days of mortality
May 17th through June 6th.
Compared to the already elevated levels of mortality
observed during the first 21 days of December/winter,
over the 35-years study period, on an adjusted basis,
there were 28 (95% CI 2135) more deaths per day dur-
ing the subsequent Christmas/New Year period. The
major contributors to this phenomenon were CVD and
to lesser extent, cancer, and other causes Supplemen-
tary Figure S1. When compared to the preceding 21
days, the Christmas period was also notable in respect to
within and between differences among men and women
in respect to fatal AMI (78 versus 16 more deaths, re-
spectively), strokes (13 fewer versus 32 more deaths) and
heart failure (1 more versus 12 more deaths). Similarly,
in men and women, the number of cancer- (18 and 29
more deaths, respectively) and respiratory-related (19
and 33 more deaths, respectively) deaths also increased.
Winter and Christmas vulnerability
Overall, except for cancer-related mortality (both sexes)
and respiratory disease in men, compared to the first 21
days of December/winter, the risk of dying in the late
spring/early summer period of 17th May to 6th June was
significantly lower - Supplementary Figure S2. Alterna-
tively, except for an increased risk of dying from respira-
tory illnesses/disease among women, men had a higher
risk of dying over the equivalent 21-day Christmas
Fig. 2 Seasonal Comparisons of Mortality. The adjusted, annual number of deaths (error bars show 95% CI) occurring in spring, autumn, and
winter are plotted above and below the reference (low mortality) season of summer for - all-cause mortality (blue symbols) and those related to
cancer (orange), CVD (red), respiratory disease (green) and other causes (brown). The total difference in deaths for all-causes (with 95% CI) and
specific causes over the entire 35-years are also shown adjacent to each symbol
Fig. 3 3-Day Mortality Across the Calendar Year. This graph plots the 3-day, rolling average of all-cause deaths occurring during the entire 35-year
study period, starting with the calendar days of 1st 3rd July and ending in the 28th 30th June. The Christmas period of increased mortality is
highlighted in red
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period; the major contributor to this increased mortality
risk (from 6 to 22% higher overall) being CVD - Supple-
mentary Figure S3.
Beyond advancing age, a combination of baseline
demographic, health perceptions and clinical factors
were independently correlated with dying during 1)
late spring/early summer (May 17th to June 6th) versus
early winter (Dec 1st 21st), and then 2) early winter
(Dec 1st 21st) versus the Christmas holiday period
(Dec 22nd Jan 11th). Whilst these factors were broadly
similar for both sexes, including a 30% reduced risk dur-
ing the Christmas holidays associated with being married
at baseline, there were some notable differences. For ex-
ample, consistent with an excess number of strokes
among women, but not men, during the Christmas holi-
days, a pre-existing history of stroke conferred a 2-fold
risk of dying during this period among women. Educa-
tional status among women also appeared to modulate
the additional risk of dying during this period see
Table 2.
Sensitivity analyses
We conducted sensitivity analyses by estimating four dif-
ferent models to test if the phenomenon of Christmas-
related excess mortality is a reliable and consistent
observation. All four models supported the findings of a
significant increase in mortality over the Christmas
period Supplementary Table S1.
We investigated the seasonal pattern of mortality within
the HUNT Study cohort living in Central Norway. This
population cohort is regarded as representative for the
Norwegian population as a whole, except for a lower
proportion of non-whites and the absence of large cities.
Our analyses revealed a striking long-term difference in
mortality occurring in winter compared to summer.
CVD accounted for half of this seasonality. Although not
the coldest, December proved to be the deadliest month,
with 22 more people dying each year compared to June.
Overall, the 3-day period of 25th27th December was
revealed to be the deadliest time of the year with CVD
the major contributor. Critically, both the frequency and
cause of death in men and women appeared to change
over the Christmas period. Compared to the same pre-
Christmas/wintery period, men were 22 and 17% more
likely to die from all-causes and CVD (particularly
AMI), respectively. In women, the equivalent risk in-
creases were 17 and 15%, with the contribution of CVD
(particularly stroke) even more prominent. Although
previous studies have also identified a specific Christmas
effect on mortality [1013,20], we are unaware of any
studies and findings equivalent to those reported here.
There is pre-existing evidence to support the hypoth-
esis that Christmas can be harmful to some individuals.
A study of the overall pattern of mortality in the US dur-
ing 19732001 revealed a holiday effectduring Christ-
mas, with ~ 5% excess deaths, after adjustment for the
winter season [12]. Similarly, data from a nationwide
coronary care unit registry in Sweden revealed a 15% in-
crease in AMI cases during the Christmas holidays [10].
A higher risk of 30-day mortality or readmission among
those hospitalised at Christmas in Ontario, Canada has
also been found [11]. From a Southern Hemisphere
Fig. 4 Excess Christmas Mortality. The adjusted, annual number of deaths (error bars show 95% CI) occurring during the 3-day period 25th27th
December are plotted against the reference period (deaths occurring during 25th27th day of every other calendar month) for - all-cause
mortality (blue symbols) and those related to cancer (orange), CVD (red), respiratory disease (green) and other causes (brown). The total
difference in deaths (with 95% CI) for all-causes and specific causes over the entire 35-years are also shown above each symbol
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perspective there is both supportive [13] and contrary
evidence [21] of an equivalent phenomenon occurring in
summer conditions. Overall, our population-based data,
suggest that like the US [12], there is an increased risk
of dying at Christmas in Norway. This likely applies to
similar regions across Europe. To put this phenomenon
into perspective, if the same pattern of excess deaths at
Christmas had occurred within the entire population of
Norway (a minimum of 3 million adults alive in 1980)
on an age- and sex-specific basis, there would have been
more than 11,000 excess deaths (around 350 more per
annum) over the Christmas holidays alone in the past
30 years.
In the (understandable) absence of prospective studies,
it is challenging to delineate between the overall impact
of winter and a Christmas-specific effect. As shown by
the Tromsø Study [14], there is evidence of winter peaks
in blood pressure, heart rate, body weight, total choles-
terol, and overall CVD risk. Seasonal variation in phys-
ical activity may also be an important consideration for
cardiovascular-related mortality [22]. Aerobic exercise,
especially with high intensity, can acutely lower systolic
BP in the hours following exercise [23].
As in many parts of the world, life in Central Norway
during the Christmas holiday period is characterised by
festive celebrations, travel away from home/central ser-
vices, and reduced health services. This typically begins
in early December and peaks (regardless of public holi-
days and weekends) during the week of December 23rd
to 31st (New Years Eve) with concurrent public holidays
on December 25th and 26th. Reduced access to follow-
up health care was noted to contribute to 26 excess
deaths (and 188 hospital readmissions) per 100,000 pa-
tients in Canada during the Christmas holidays [11].
However, this phenomenon does not fully explain the
size of the phenomenon we observed within our cohort
and the contributory reasons are likely to be multifactor-
ial. Consuming a high-fat diet for only 3 days exacer-
bates insulin resistance and glycolipid metabolism
disorders in men with obesity [24]. Even among healthy
men, decreasing physical activity for 13 weeks de-
creases insulin sensitivity and attenuates postprandial
lipid metabolism [25]. Vascular stiffness, due to impaired
endothelial function of the conduit vessels, is an import-
ant factor in the development of hypertension and an
independent risk factor for a fatal cardiovascular event
[25]. After a high-fat meal, which is typically consumed
during Christmas in Norway, endothelial function de-
creases substantially postprandially [26]. The potential
negative impact of increased emotional stress associated
with dealing with loneliness and family tensions [27]
with the potential for seasonally triggered depression
[28], also cannot be ignored. As suggested by our sex-
specific findings, any, or all of these stressorsmay
Table 2 Correlates of All-Cause Mortality at Key Periods of the Year
Dec 1st 21st (Winter) versus
May 17th June 6th (Summer)
Dec 22nd Jan 11th (Christmas/New Year)
versus Dec 1st 21st (Winter/Pre-Christmas)
(n= 1543)
(n= 1351)
(n= 1636)
(n= 1424)
Demographic profile, adjusted HR (95% CI)
Age at baseline (per year) 1.06 (1.051.07) .001 1.05 (1.041.06) .001 1.06 (1.051.07) .001 1.05 (1.041.06) .001
9 years education vs. rest 0.92 (0.721.78) .362 0.97 (0.781.21) .804 1.05 (0.901.15) .519 1.25 (1.031.52) .026
Married vs. rest 0.93 (0.561.49) .769 0.98 (0.551.69) .903 0.71 (0.590.86) .001 0.70 (0.5491) .001
Well-being, adjusted HR (95% CI)
Good/V. good physical health vs. rest 0.75 (0.640.87) .001 0.82 (0.700.95) .008 0.79 (0.680.92) .002 0.82 (0.700.95) .009
Life dissatisfaction vs. rest 1.65 (1.233.23) .004 1.52 (1.032.25) .036 0.76 (0.501.15) .194 1.13 (0.771.66) .530
Medical History, adjusted HR (95% CI)
Angina pectoris vs. rest 1.26 (0.981.63) .074 1.57 (1.192.08) .002 1.39 (1.061.80) .016 1.99 (1.051.84) .021
Acute myocardial infarction vs. rest 1.52 (1.112.07) .008 1.64 (0.922.91) .092 1.45 (1.061.99) .021 2.41 (1.463.80) .001
Stroke vs. rest 1.23 (0.781.94) .371 1.50 (0.872.58) .142 1.25 (0.781.97) .326 2.01 (1.283.17) .002
Lifestyle, adjusted HR (95% CI)
Current smoker vs. rest 1.28 (1.061.53) .009 1.24 (1.041.49) .018 1.39 (1.161.66) .001 1.51 (1.261.82) .001
Vital Signs, adjusted HR (95% CI)
Heart rate (per 5 beats/minute) 1.03 (1.011.06) .011 1.02 (0.981.05) .360 1.03 (1.0006) .045 1.02 (0.991.95) .152
Systolic BP (per 5 mm/Hg) 1.04 (1.021.07) .001 1.04 (1.0206) .001 1.03 (1.0105) .002 1.03 (1.0003) .019
Diastolic BP (per 5 mm/Hg) 0.98 (0.941.03) .445 1.07 (1.0309) .001 0.99 (0.961.04) .822 0.96 (0.921.01) 0.087
Moholdt et al. BMC Public Health (2021) 21:549 Page 8 of 11
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affect men and women differently. For example, it has
been demonstrated that diabetes, high-density lipopro-
tein levels and triglyceride levels have more impact on
cardiovascular health of women compared to men [29].
The emerging literature around Tako-tsubo cardiomy-
opathy with a predominance of women affected [30]is
notable when considering the small, but intriguing, in-
crease in deaths due to heart failure in women, but not
men, at Christmas.
Unfortunately, in the absence of specific interventions,
expert clinical guidelines rarely mention or address sea-
sonality. We are currently conducting a randomized trial
to address seasonal patterns of hospitalization in 300
vulnerable individuals with chronic heart disease in Mel-
bourne, Australia. Beyond ensuring appropriate vaccin-
ation against influenza [31], there is a strong justification
for more proactive screening and management of high-
risk patients by general practitioners leading up to
Christmas. The identification of educational levels in
women and marriage status as modifying mortality risk
in both sexes, reinforces the importance of considering
health literacy and the emotional well-being of individ-
uals leading up to provocative times of the year. Promo-
tion of a healthy lifestyle should occur all year round
[32], but should perhaps be highlighted and re-
emphasized in the lead-up to Christmas: a time of exces-
sive indulgence of all kinds with potentially tragic conse-
quences. The current COVID-19 pandemic both directly
(via residual cardio-pulmonary impairment post-
infection [33]) and indirectly (via its negative effects on
emotional and psychological well-being, patterns of so-
cial interaction, seeking care for pre-existing chronic
conditions and reduced exercise levels), has further po-
tential to exacerbate Christmas mortality [34].
Study limitations
To robustly test our primary hypothesis, we examined
patterns of long-term mortality within the HUNT cohort
[15,17] in Central Norway. Although this is a well-
characterised population, the pattern of risk and subse-
quent health outcomes in this semi-rural population
may not be reflective of the broader Norwegian popula-
tion or that of Western Europe. Nor was the study spe-
cifically designed to examine the issue of seasonal
patterns of disease. As previously noted, Norway has a
distinctive climate and culture, and these specific condi-
tions may have contributed to our specific findings.
Hence, there is a need to validate these findings in other
population cohorts with equivalent data. To maintain
the size of outcome data for analyses, we relied upon
baseline profiling of the original cohort and mortality
outcomes. For many individuals there may be multiple
contributing causes of death, so any findings from
cause-specific mortality data should be interpreted with
some caution. The administrative timing of reported
deaths (particularly over the Christmas period) may also
be disrupted during holiday periods. To date, we have
yet to examine the association between observed
changes in risk profiles over time with seasonal patterns
of mortality. Nor have we confirmed if the same pattern
of seasonality and increased risk of death at Christmas is
reflected in the pattern of hospital admissions. We have
plans to address these limitations. However, we will not
be able to ascertain the quality of care and extent of out-
patient follow-up at key times such as Christmas and the
New Year period. However, the timing of death (unless a
sudden cardiac death) is not indicative of exactly when a
person becomes unwell and/or is admitted to hospital
[11]. Moreover, we do not have specific data on seasonal
changes in risk behaviours (e.g. increased alcohol and
food intake) to correlate with the subsequent timing and
trajectory of illness and death. Finally, we examined the
pattern of mortality on a historical basis, during which
time, significant changes in the pattern of life-style be-
haviours and public health measures have occurred.
During long-term follow-up of the HUNT population
cohort, there was a distinctive pattern of a seasonal in-
crease in mortality during winter when compared to
summer months. Over and above this broad pattern, a
distinctive pattern of excess mortality predominantly,
but not exclusively linked to CVD, was evident over the
Christmas holiday period. The number of excess deaths
over Christmas was substantial.
AMI: Acute myocardial infarction; BP: Blood pressure; BMI: Body mass index;
CAD: Coronary artery disease; CVD: Cardiovascular disease; HUNT: Trøndelag
Health Study; OLS: Ordinary least squares
Supplementary Information
The online version contains supplementary material available at https://doi.
Additional file 1: Figure S1. 21-day Pattern of Mortality Pre-
Christmas versus Summer Low and Christmas Holiday Period. Figure S2.
Sex-Specific Risk of Mortality Pre-Christmas versus Summer Low Period.
Figure S3. Sex-Specific Risk of Mortality Pre-Christmas versus Christmas
Holiday Period. Table S1. Sensitivity analyses.
The Trøndelag Health Study is a collaboration between the HUNT Research
Centre (Faculty of Medicine and Health Sciences, Norwegian University of
Science and Technology), Trøndelag County Council, Central Norway
Regional Health Authority, and the Norwegian Institute of Public Health. We
thank all the individuals who contributed to the data collection in HUNT.
TM and SS contributed to the conception of the work. CA contributed to the
analysis of study data. PS, CM and LB contributed to the interpretation of
study data. TM and SS drafted the manuscript. CA, PS, CM and LB critically
Moholdt et al. BMC Public Health (2021) 21:549 Page 9 of 11
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
revised the manuscript. All gave their approval and agree to be accountable
for all aspects of the work, ensuring its integrity and accuracy.
SS is supported by the National Health and Medical Research Council of
Australia (GNT1135894).
Availability of data and materials
The Trøndelag Health Study has invited persons aged 13100 years to four
surveys between 1984 and 2019. Comprehensive data from more than
140,000 persons having participated at least once and biological material
from 78,000 persons are collected. The data are stored in HUNT databank
and biological material in HUNT biobank. HUNT Research Centre has
permission from the Norwegian Data Inspectorate to store and handle these
data. The key identification in the data base is the personal identification
number given to all Norwegians at birth or immigration, whilst de-identified
data are sent to researchers upon approval of a research protocol by the Re-
gional Ethical Committee and HUNT Research Centre. To protect participants
privacy, HUNT Research Centre aims to limit storage of data outside HUNT
databank, and cannot deposit data in open repositories. HUNT databank has
precise information on all data exported to different projects and are able to
reproduce these on request. There are no restrictions regarding data export
given approval of applications to HUNT Research Centre. For more informa-
tion see:
Ethics approval and consent to participate
The Trøndelag Health Study conforms to the Declaration of Helsinki and was
originally approved by the relevant ethics committee [15,17]. All study
participants provided written informed consent to be studied and followed-
up. The present study was approved by the Regional Committee for Ethics
in Medical Research (REK-midt, no. 2018/1509).
Consent for publication
Not applicable.
Competing interests
The authors have no conflicts of interest to declare.
Author details
Department of Circulation and Medical Imaging, Norwegian University of
Science and Technology, Trondheim, Norway.
The Womens Clinic, St.Olav
Hospital, Trondheim, Norway.
Centre for Applied Health Economics, Griffith
University, Nathan, Queensland, Australia.
Menzies Health Institute
Queensland, Griffith University, Southport, Queensland, Australia.
Department of Respiratory and Sleep Medicine, Austin Health, Institute for
Breathing and Sleep, University of Melbourne, Melbourne, Australia.
Department of Medicine, Austin Health, University of Melbourne,
Melbourne, Australia.
Torrens University Australia, South Australia, Wakefield
Campus, Adelaide, SA 5000, Australia.
University of Glasgow, Glasgow,
Scotland, UK.
Received: 7 December 2020 Accepted: 12 February 2021
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... Death from cardiovascular diseases, particularly AMI, is more during winter than summer. 20 Researchers suggest that the effect of infections on cardiovascular risk may be generic and is not linked to specific types of infection. 13 Large scale studies also show an increased risk of ischemic stroke (relative risk 1.30; P=0.007), myocardial infarction (relative risk 1.56, P<0.001), and vascular death (relative risk 1.51; P<0.001), among patients with high leukocyte count (>8.2x10(9)/L), compared to patients with low counts at baseline (<5.9x10(9)/L). ...
Full-text available
Objectives: To estimate the rates of symptomatic respiratory, gastrointestinal and urinary infections in patients hospitalized with acute heart failure and to describe the clinical characteristics of these patients. Methodology: A cross sectional study was conducted in a large tertiary care cardiology hospital and patients hospitalized due to non-infective causes of heart failure were invited to participate. Trained research assistants collected data using a semi-structured questionnaire. Patients’ medical records were also reviewed. Results: A total of 335 patients were recruited in the study and of them around two thirds (65.7%, 220/335) had the first-time heart failure and one third (34.5%, 115/335) had recurrent heart failure. Acute myocardial infarction rate was significantly higher in first-time heart failure patients, compared to recurrent heart failure patients (p value <0.001). Among all heart failure cases, 140 (41.8%) had symptoms of respiratory infections, 36 (10.7%) had symptoms of diarrhoea, 32 (9.5%) had symptoms of urinary infection, 77 (23.0%) had influenza like illness and 81 (24.2%) had fever during last 2 weeks. Rates of symptomatic respiratory infection, influenza like illness and fever were consistently higher in first-time heart failure patients, however, only respiratory infection during last week was significantly associated with first-time acute heart failure (OR 1.68, 95% CI, 1.02-2.77). Conclusion: This study showed high rates of respiratory and other symptomatic infections in acute heart failure patients. Like other precipitating factors, infections may trigger acute heart failure directly in elderly people. Elderly people should use influenza vaccines to protect from influenza and influenza like illness.
... It is well established that the incidence of severe cardiovascular diseases exhibits a seasonal pattern, with more frequent relative occurrence during winter [4][5][6][7][8][9]. Several factors may contribute to these seasonal variations, such as activation of the sympathetic nervous system and increased cathecholamines [10], elevated serum cholesterol levels [11], prothrombotic shift in the hemostatic system via elevated fibrinogen levels [12,13], decreased physical activity [4], and vitamin D deficiency [14]. ...
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Background Seasonal variations in the ambient temperature may affect the exacerbation of cardiovascular diseases. Our primary objective was to evaluate the seasonality of the monthly proportion of cardiac surgeries associated with diabetes, smoking and/or elderly age at a tertiary-care university hospital in East-Central Europe with a temperate climate zone. As a secondary objective, we also assessed whether additional factors affecting small blood vessels (smoking, aging, obesity) modulate the seasonal variability of diabetes.Methods Medical records were analyzed for 9838 consecutive adult patients who underwent cardiac surgery in 2007-2018. Individual seasonal variations of diabetes, smoking, and elderly patients were analyzed monthly, along with the potential risk factors for cardiovascular complication. We also characterized whether pairwise coexistence of diabetes, smoking, and elderly age augments or blunts the seasonal variations.ResultsSeasonal variations in the monthly proportion of cardiac surgeries associated with diabetes, smoking and/or elderly age were observed. The proportion of cardiac surgeries of non-elderly and smoking patients with diabetes peaked in winter (amplitude of change as [peak-nadir]/nadir: 19.2%, p
... Thermoregulatory systems in mammals are robust and reliable after millions of years of evolution. Although cold (winter season) has been reported to increase cardiovascular disease morbidity and mortality rates (25,26), the effect of exposure to cold is unclear. The causes of these increases in morbidity and mortality are complex, and the winter season cannot fully represent exposure to cold. ...
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Harsh work environments can include very cold, hot, dusty, and noisy workplaces, as well as exposure in the workplace with chemicals and other fumes, cigarette smoke, and diesel exhaust. Although working in these harsh environments can have a negative effect on health, there are no effective biomarkers for monitoring health conditions until workers develop disease symptoms. Plasma protein concentrations, which reflect metabolism and immune status, have great potential as biomarkers for various health conditions. Using a Mendelian-randomization (MR) design, this study analyzed the effects of these harsh environments on plasma proteins to identify proteins that can be used as biomarkers of health status. Preliminary analysis using inverse variance weighted (IVW) method with a p-value cutoff of 0.05 showed that workplace environments could affect the concentrations of hundreds of plasma proteins. After filtering for sensitivity via MR-Egger, and Weighted Median MR approaches, 28 plasma proteins altered by workplace environments were identified. Further MR analysis showed that 20 of these plasma proteins, including UNC5D, IGFBP1, SCG3, ST3GAL6, and ST3GAL2 are affected by noisy workplace environments; TFF1, RBM39, ACYP2, STAT3, GRB2, CXCL1, EIF1AD, CSNK1G2, and CRKL that are affected by chemical fumes; ADCYAP1, NRSN1, TMEM132A, and CA10 that are affected by passive smoking; LILRB2, and TENM4 that are affected by diesel exhaust, are associated with the risk of at least one disease. These proteins have the potential to serve as biomarkers to monitor the occupational hazards risk of workers working in corresponding environments. These findings also provide clues to study the biological mechanisms of occupational hazards.
... These observations suggest that patients with more severe HF (and worse prognosis) are prone to decompensation during winter and that these patients and older patients with more advanced disease should be advised to avoid travelling to colder regions. Of note, a study from Norway reported that the Christmas winter period was associated with the highest rates of excess all-cause and cardiovascular deaths 45 . ...
Patients with heart failure are at a higher risk of cardiovascular events compared with the general population, particularly during domestic or international travel. Patients with heart failure should adhere to specific recommendations during travel to lower their risk of developing heart failure symptoms. In this Review, we aim to provide clinicians with a set of guidelines for patients with heart failure embarking on national or international travel. Considerations when choosing a travel destination include travel distance and time, the season upon arrival, air pollution levels, jet lag and altitude level because all these factors can increase the risk of symptom development in patients with heart failure. In particular, volume depletion is of major concern while travelling given that it can contribute to worsening heart failure symptoms. Pre-travel risk assessment should be performed by a clinician 4-6 weeks before departure, and patients should receive advice on potential travel-related illness and on strategies to prevent volume depletion. Oxygen supplementation might be useful for patients who are very symptomatic. Upon arrival at the destination, potential drug-induced photosensitivity (particularly in tropical destinations) and risks associated with the local cuisine require consideration. Special recommendations are needed for patients with cardiac implantable electronic devices or left ventricular assist devices as well as for those who have undergone major cardiac surgery.
Aims: We aimed to recruit a representative cohort of women and men with multimorbid chronic heart disease as part of a trial testing an innovative, nurse-coordinated, multi-faceted intervention to lower rehospitalisation and death by addressing areas of vulnerability to external challenges to their health. Methods and results: The prospective, randomised open, blinded end-point RESILIENCE Trial recruited 203 hospital inpatients (mean age 75.7 ± 10.2 years) of whom 51% were women and 94% had combined coronary artery disease, heart failure and/or atrial fibrillation. Levels of concurrent multimorbidity were high (mean Charlson Index of Comorbidity Score 6.3 ± 2.7), and 8.9% had at least mild frailty according to the Rockwood Clinical Frailty Scale. Including the index admission, 19-20% of women and men had a pre-existing pattern of seasonally-linked hospitalisation (seasonality). Detailed phenotyping revealed that 48% of women and 40% of men had ≥3 physiological factors, and 15% of women and 16% of men had ≥3 behavioural factors likely to increase their vulnerability to external provocations to their health. Overall, 61-62% of women and men had ≥4 combined factors indicative of such vulnerability. Additional factors such as reliance on the public health system (63% versus 49%), lower education (30% versus 14%) and living alone (48% versus 29%) were more prevalent in women. Conclusions: We successfully recruited women and men with multimorbid chronic heart disease and bio-behavioural indicators of vulnerability to external provocations to their health. Once completed, the RESILIENCE TRIAL will provide important insights on the impact of addressing such vulnerability (promoting resilience) on subsequent health outcomes.
Seasonal effects on subclinical cardiovascular functions (CVFs) are an important emerging health issue for people living in urban environment. The objectives of this study were to demonstrate the effects of seasonal variations of temperature, relative humidity, and PM2.5 air pollution on CVFs. A total of 86 office workers in Taipei City were recruited, their arterial pressure waveform was recorded by cuff sphygmomanometer using an oscillometric blood pressure (BP) device for CVFs assessment. Results of paried t-test with Bonferroni correction showed significantly increased systolic and diastolic BP (SBP, DBP), central end-systolic and diastolic BP (cSBP, cDBP) and systemic vascular resistance, but decreased heart rate (HR), stroke volume (SV), cardio output (CO), and cardiac index in winter compared with other seasons. After controlling for related confounding factors, SBP, DBP, cSBP, cDBP, LV dp/dt max, and brachial-ankle pulse wave velocity (baPWV) were negatively associated with, and SV was positively associated with seasonal temperature changes. Seasonal changes of air pollution in terms of PM2.5 were significantly positively associated with DBP and cDBP, as well as negatively associated with HR and CO. Seasonal changes of relative humidity were significantly negatively associated with DBP, and cDBP, as well as positively associated with HR, CO, and baPWV. This study provides evidence of greater susceptibility to cardiovascular events in winter compared with other seasons, with ambient temperature, relative humidity, and PM2.5 as the major factors of seasonal variation of CVFs.
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Background Currently, little is known regarding seasonal variation for atrial fibrillation (AF) in the United States and whether quality of care for AF varies between seasons. Methods and Results The GWTG‐AFib (Get With The Guidelines–AFib) registry was initiated by the American Heart Association to enhance national guideline adherence for treatment and management of AF. Our analyses included 61 291 patients who were admitted at 141 participating hospitals from 2014 to 2018 across the United States. Outcomes included numbers of AF admissions and quality‐of‐care measures (defect‐free care, defined as a patient’s receiving all eligible measures). For quality‐of‐care measures, generalized estimating equations accounting for within‐site correlations were used to estimate odds ratios (ORs) with 95% CIs, adjusting patient and hospital characteristics. The proportion of AF admissions for each season was similar, with the highest percentage of AF admissions being observed in the fall (spring 25%, summer 25%, fall 27%, and winter 24%). Overall, AF admissions across seasons were similar, with no seasonal variation observed. No seasonal variation was observed for incident AF. There were no seasonal differences in care quality (multivariable adjusted ORs and 95% CIs were 0.93 (0.87–1.00) for winter, 1.09 (1.01–1.18) for summer, and 1.08 (0.97–1.20) for fall, compared with spring). Conclusions In a nationwide quality improvement registry, no seasonal variation was observed in hospital admissions for AF or quality of care for AF.
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Objective: Cardiovascular disease (CVD) is the leading cause of hospitalisations and deaths in Australia. This study estimates the excess CVD hospitalisations and deaths across seasons and during the December holidays in Queensland, Australia. Methods: The study uses retrospective, longitudinal, population-based cohort data from Queensland, Australia from January 2010 to December 2015. The outcomes were hospitalisations and deaths categorised as CVD-related. CVD events were grouped according to when they occurred in the calendar year. Excess hospitalisations and deaths were estimated using the multivariate ordinary least squares method after adjusting for confounding effects. Results: More CVD hospitalisations and deaths occurred in winter than in summer, with 7811 (CI: 1353, 14,270; p < 0.01) excess hospitalisations and 774 (CI: 35, 1513; p < 0.01) deaths compared to summer. During the coldest month (July), there was an excess of 42 hospitalisations and 7 deaths per 1000 patients. Fewer CVD hospitalisations (−20 (CI: −29, −9; p < 0.01)) occurred during the December holidays than any other period during the calendar year. Non-CVD events were mostly not statistically significant different between periods. Conclusion: Most CVD events in Queensland occurred in winter rather than during the December holidays. Potentially cost-effective initiatives should be explored such as encouraging patients with CVD conditions to wear warmer clothes during cold temperatures and/or insulating the homes of CVD patients who cannot otherwise afford to.
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Objective To quantify the impact of coronavirus disease 2019 (covid-19) on all cause mortality in Nembro, an Italian city severely affected by the covid-19 pandemic. Design Descriptive study. Setting Nembro, in the Bergamo province of Lombardy, northern Italy. Population Residents of Nembro. Main outcome measures Monthly all cause mortality between January 2012 and April 2020 (data to 11 April), number of confirmed deaths from covid-19 to 11 April 2020, and weekly absolute number of deaths between 1 January and 4 April across recent years by age group and sex. Results Nembro had 11 505 residents as of 1 January 2020. Monthly all cause mortality between January 2012 and February 2020 fluctuated around 10 per 1000 person years, with a maximum of 21.5 per 1000 person years. In March 2020, monthly all cause mortality reached a peak of 154.4 per 1000 person years. For the first 11 days in April, this rate decreased to 23.0 per 1000 person years. The observed increase in mortality was driven by the number of deaths among older people (≥65 years), especially men. From the outbreak onset until 11 April 2020, only 85 confirmed deaths from covid-19 in Nembro were recorded, corresponding to about half of the 166 deaths from all causes observed in that period. Conclusions The study findings show how covid-19 can have a considerable impact on the health of a small community. Furthermore, the results suggest that the full implications of the covid-19 pandemic can only be completely understood if, in addition to confirmed deaths related to covid-19, consideration is also given to all cause mortality in a given region and time frame.
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Climate change is a major contributor to annual winter peaks in cardiovascular events across the globe. However, given the paradoxical observation that cardiovascular seasonality is observed in relatively mild as well as cold climates, global warming may not be as positive for the syndrome of heart failure (HF) as some predict. In this article, we present our Model of Seasonal Flexibility to explain the spectrum of individual responses to climatic conditions. We have identified distinctive phenotypes of resilience and vulnerability to explain why winter peaks in HF occur. Moreover, we identify how better identification of climatic vulnerability and the use of multifaceted interventions focusing on modifiable bio-behavioural factors may improve HF outcomes.
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Background The effect of holiday season admission for stroke on mortality has not been investigated. Thus, we aimed to evaluate whether “holiday season” and “weekend” effects exist on mortality risk for stroke admission. Methods and Results A nationwide cohort study was conducted using Taiwan's National Health Insurance Research Database. We identified all patients admitted for stroke between 2011 and 2015 in Taiwan, and categorized them according to the admission date: holiday season (at least 4 days off) (n=3908), weekend (n=13 774), and weekday (n=49 045). We analyzed in‐hospital, 7‐day, and 30‐day mortality using multivariable logistic regression, adjusting for stroke severity and other confounders. Compared with weekday admissions, holiday season admission for stroke was significantly associated with a 20%, 33%, and 21% increase in in‐hospital, 7‐day, and 30‐day mortality, respectively. Compared with weekend admissions, holiday season admissions were associated with a 24%, 30%, and 22% increased risk of in‐hospital, 7‐day, and 30‐day mortality, respectively. However, mortality did not differ significantly between weekend and weekday admissions. Subanalyses after stratification for age, sex, and stroke type also revealed similar trends. Conclusions We report for the first time a “holiday season effect” on stroke mortality. Patients admitted during holiday seasons had higher mortality risks than those admitted on weekends and weekdays. This holiday season effect persisted even after adjusting for stroke severity and other important confounders. These findings highlight the need for healthcare delivery systems with a consistent quality of round‐the‐clock care for patients admitted for stroke.
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Objectives To study circadian rhythm aspects, national holidays, and major sports events as triggers of myocardial infarction. Design Retrospective observational study using the nationwide coronary care unit registry, SWEDEHEART. Setting Sweden. Participants 283 014 cases of myocardial infarction reported to SWEDEHEART between 1998 and 2013. Symptom onset date was documented for all cases, and time to the nearest minute for 88%. Interventions Myocardial infarctions with symptom onset on Christmas/New Year, Easter, and Midsummer holiday were identified. Similarly, myocardial infarctions that occurred during a FIFA World Cup, UEFA European Championship, and winter and summer Olympic Games were identified. The two weeks before and after a holiday were set as a control period, and for sports events the control period was set to the same time one year before and after the tournament. Circadian and circaseptan analyses were performed with Sunday and 24:00 as the reference day and hour with which all other days and hours were compared. Incidence rate ratios were calculated using a count regression model. Main outcome measures Daily count of myocardial infarction. Results Christmas and Midsummer holidays were associated with a higher risk of myocardial infarction (incidence rate ratio 1.15, 95% confidence interval 1.12 to 1.19, P<0.001, and 1.12, 1.07 to 1.18, P<0.001, respectively). The highest associated risk was observed for Christmas Eve (1.37, 1.29 to 1.46, P<0.001). No increased risk was observed during Easter holiday or sports events. A circaseptan and circadian variation in the risk of myocardial infarction was observed, with higher risk during early mornings and on Mondays. Results were more pronounced in patients aged over 75 and those with diabetes and a history of coronary artery disease. Conclusions In this nationwide real world study covering 16 years of hospital admissions for myocardial infarction with symptom onset documented to the nearest minute, Christmas, and Midsummer holidays were associated with higher risk of myocardial infarction, particularly in older and sicker patients, suggesting a role of external triggers in vulnerable individuals.
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Objective To determine whether patients discharged from hospital during the December holiday period have fewer outpatient follow-ups and higher rates of death or readmission than patients discharged at other times. Design Population based retrospective cohort study. Setting Acute care hospitals in Ontario, Canada, 1 April 2002 to 31 January 2016. Participants 217 305 children and adults discharged home after an urgent admission, during the two week December holiday period, compared with 453 641 children and adults discharged during two control periods in late November and January. Main outcome measures The primary outcome was death or readmission, defined as a visit to an emergency department or urgent rehospitalisation, within 30 days. Secondary outcomes were death or readmission and outpatient follow-up with a physician within seven and 14 days after discharge. Multivariable logistic regression with generalised estimating equations was used to adjust for characteristics of patients, admissions, and hospital. Results 217 305 (32.4%) patients discharged during the holiday period and 453 641 (67.6%) discharged during control periods had similar baseline characteristics and previous healthcare utilisation. Patients who were discharged during the holiday period were less likely to have follow-up with a physician within seven days (36.3% v 47.8%, adjusted odds ratio 0.61, 95% confidence interval 0.60 to 0.62) and 14 days (59.5% v 68.7%, 0.65, 0.64 to 0.66) after discharge. Patients discharged during the holiday period were also at higher risk of 30 day death or readmission (25.9% v 24.7%, 1.09, 1.07 to 1.10). This relative increase was also seen at seven days (13.2% v 11.7%, 1.16, 1.14 to 1.18) and 14 days (18.6% v 17.0%, 1.14, 1.12 to 1.15). Per 100 000 patients, there were 2999 fewer follow-up appointments within 14 days, 26 excess deaths, 188 excess hospital admissions, and 483 excess emergency department visits attributable to hospital discharge during the holiday period. Conclusions Patients discharged from hospital during the December holiday period are less likely to have prompt outpatient follow-up and are at higher risk of death or readmission within 30 days.
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Objective: The STrengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement provides guidance on reporting observational studies. Many extensions have been created for specialized methods or fields. We determined endorsement prevalence and typology by journals in extension-related fields. Study design and setting: A published protocol defined search strategies to identify journals publishing observational studies (2007 - 2017) across seven fields relating to STROBE extensions. We extracted text regarding STROBE, 7 STROBE extensions, reporting guidelines CONSORT and PRISMA, and transparent reporting documents/groups: ICMJE, COPE, and the EQUATOR Network. Relationships between endorsing STROBE, endorsing other guidelines and journal impact factor were tested using Chi-square and Mann-Whitney. Results: Of 257 unique journals, 12 (5%) required STROBE on submission, 22 (9%) suggested use, 12 (5%) recommended a "relevant guideline", 72 (28%) mentioned it indirectly (via editorial policies or ICMJE Recommendations), and 139 (54%) did not mention STROBE. The relevant extension was required by 2 (<1%) journals; 4 (1%) suggested use. STROBE endorsement was not associated with journal impact indices but was with CONSORT and PRISMA endorsement. Conclusion: Reporting guideline endorsement rates are low; information is vague and scattered. Unambiguous language is needed to improve adherence to reporting guidelines and increase the quality of reporting.
Aims: An increase in out-of-hospital cardiac arrest (OHCA) incidence has been reported in the very early phase of the COVID-19 epidemic, but a clear demonstration of a correlation between the increased incidence of OHCA and COVID-19 is missing so far. We aimed to verify whether there is an association between the OHCA difference compared with 2019 and the COVID-19 epidemic curve. Methods and results: We included all the consecutive OHCAs which occurred in the Provinces of Lodi, Cremona, Pavia, and Mantova in the 2 months following the first documented case of COVID-19 in the Lombardia Region and compared them with those which occurred in the same time frame in 2019. The cumulative incidence of COVID-19 from 21 February to 20 April 2020 in the study territory was 956 COVID-19/100 000 inhabitants and the cumulative incidence of OHCA was 21 cases/100 000 inhabitants, with a 52% increase as compared with 2019 (490 OHCAs in 2020 vs. 321 in 2019). A strong and statistically significant correlation was found between the difference in cumulative incidence of OHCA between 2020 and 2019 per 100 000 inhabitants and the COVID-19 cumulative incidence per 100 000 inhabitants both for the overall territory (ρ 0.87, P < 0.001) and for each province separately (Lodi: ρ 0.98, P < 0.001; Cremona: ρ 0.98, P < 0.001; Pavia: ρ 0.87, P < 0.001; Mantova: ρ 0.81, P < 0.001). Conclusion: The increase in OHCAs in 2020 is significantly correlated to the COVID-19 pandemic and is coupled with a reduction in short-term outcome. Government and local health authorities should seriously consider our results when planning healthcare strategies to face the epidemic, especially considering the expected recurrent outbreaks.
Atherosclerosis can have various etiologies, including several newly recognized immunoinflammatory mechanisms. A growing body of evidence suggests that influenza infection is chronologically linked to acute myocardial infarction (AMI), and thus that the virus is a novel cardiovascular disease (CVD) risk factor. Morbidity and mortality rates for both influenza infection and AMI rise markedly with age. Epidemiological studies have demonstrated that influenza vaccination (IV) has a cardioprotective effect, especially in people aged 65 and over; hence, IV may be of value in the management of CVD. These observations justify efforts to better understand the underlying mechanisms and to identify therapeutic targets in older adults. In view of the above, the objective of the present study was to review the literature data on the cellular mechanisms that link IV to the prevention of atherosclerotic complications. Given the greater burden of CVD in older subjects, we also questioned the impact of aging on this association. The most widely recognized benefit of IV is the prevention of influenza infection and the latter’s cardiovascular complications. In a new hypothesis, however, an influenza-independent effect is driven by vaccine immunity and modulation of the ongoing immunoinflammatory response in individuals with CVD. Although influenza infection and IV both induce a proinflammatory response, they have opposite effects on the progression of atherosclerosis – suggesting a hormetic phenomenon. Aging is characterized by chronic inflammation (sometimes referred to as “inflammaging”) that progresses insidiously during the course of aging-related diseases, including CVD. It remains to be determined whether vaccination has an effect on aging-related diseases other than CVD. Although the studies of this topic had various limitations, the results highlight the potential benefits of vaccination in protecting the health of older adults, and should drive research on the molecular immunology of the response to IV and its correlation with atheroprotective processes.
Objectives Cardiovascular events and mortality have shown a higher incidence within the Christmas holiday period in previous studies and in the northern and southern hemisphere. Our study aimed to assess changes in cardiovascular and stroke mortality variation around the Christmas period in Australia. Study design The study design is a population-based case-control study. Methods Daily mortality data attributed to stroke and cardiovascular was compiled from Australia between 1989 and 2015, amounting to approximately 700,000 and 250,000 deaths, respectively. A locally weighted polynomial regression line was used to estimate expected mortality rates during that period and compared with actual results. Results There was a non-significant increase of 1.08% (P = 0.35) and 0.20% (P = 0.87) for coronary heart disease and stroke mortality, respectively, in the Christmas holiday period. Conclusions There is no evidence of an increase in cardiovascular and stroke mortality in the Christmas holiday period in Australia.
This study aimed to assess, for the first time, the change in vascular reactivity across the full spectrum of cardiometabolic health. Systematic searches were conducted in MEDLINE and EMBASE databases from their inception to March 13, 2017, including studies that assessed basal vascular reactivity in two or more of the following health groups (aged ≥18 years old): healthy, overweight, obesity, impaired glucose tolerance, metabolic syndrome, or type 2 diabetes with or without complications. Direct and indirect comparisons of vascular reactivity were combined using a network meta-analysis. Comparing data from 193 articles (7226 healthy subjects and 19344 patients), the network meta-analyses revealed a progressive impairment in vascular reactivity (flow-mediated dilation data) from the clinical onset of an overweight status (−0.41%, 95% CI, −0.98 to 0.15) through to the development of vascular complications in those with type 2 diabetes (−4.26%, 95% CI, −4.97 to −3.54). Meta-regressions revealed that for every 1 mmol/l increase in fasting blood glucose concentration, flow-mediated dilation decreased by 0.52%. Acknowledging that the time course of disease may vary between patients, this study demonstrates multiple continuums of vascular dysfunction where the severity of impairment in vascular reactivity progressively increases throughout the pathogenesis of obesity and/or insulin resistance, providing information that is important to enhancing the timing and effectiveness of strategies that aim to improve cardiovascular outcomes.