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. Alternatively, many had relatively high levels of risk for CVD and other chronic diseases, including elevated baseline levels of blood pressure (BP) and smoking combined with relatively high levels of sedentary behaviours and overweight status (Table 1).
Table 1
Baseline characteristics according to survival status
|
Total
(n=79,626)
|
Alive
(n=40,431)
|
Dead
(n=39,195)
|
Demographic Profile
|
Women, %
|
40,353 (50.7)
|
21,037 (52.1)
|
19,316 (47.9)
|
Mean age at baseline (years)
|
49.1±18.0
|
35.7±9.6
|
62.9±13.6
|
Mean age at census (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)
|
9,082 (29.9)
|
23,886 (77.4)
|
Employment status,% (n=76,870)
Full-time employment
Non-employed
|
32,333 (42.1)
23,156 (30.1)
|
21,585 (56.2)
3,623 (9.4)
|
10,748 (28.0)
19,533 (50.8)
|
Health Status
|
Life Satisfaction,% (n=75,815)
Dissatisfied (Quite to Extremely)
Satisfied (Quite to Extremely)
|
2,005 (2.6)
62,342 (82.2)
|
630 (1.7)
32,967 (86.6)
|
1,375 (3.6)
29,375 (77.9)
|
General Health Status, % (n=76,863)
Bad
Poor
Good
Very Good
|
2,023 (2.6)
18,752 (24.4)
44,215 (57.5)
11,873 (15.4)
|
202 (0.5)
4,615 (12.0)
24,411 (63.6)
9,165 (23.9)
|
1,821 (4.7)
14,317 (36.7)
19,804 (51.5)
2,708 (7.0)
|
Physical Activity Status, % (n=57,212)
Inactive
Low
Moderate
High
|
27,145 (47.4)
18,730 (32.7%)
8,283 (14.5)
3,054 (5.3)
|
13,157 (45.1)
9,728 (33.3)
4,951 (17.0)
1,362 (4.7)
|
13,988 (49.9)
9,002 (32.1)
3,332 (11.9)
1,692 (6.0)
|
Alcohol intake, % (n=61,520)
>5-10 drinks in 14 days
Abstains
|
3,608 (5.9)
7,536 (12.2)
|
1,685 (5.5)
1,899 (6.2)
|
1,923 (5.1)
5,637 (18.3)
|
Current smoker, % (n=60,421)
|
20,667 (34.2)
|
10,885 (35.5)
|
9,782 (32.9)
|
Mean BMI kg/m2 (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/
Diastolic BP
|
139±23.5 /
84.6±15.2
|
127±15.2 /
80.9±15.2
|
150±25.0 /
88.5±11.7
|
Angina pectoris (%) (n=76,742)
|
3,450 (4.5)
|
113 (0.3)
|
3,337 (8.7)
|
AMI, % (n = 76, 723)
|
1,986 (2.6)
|
39 (0.1)
|
1,947 (5.1)
|
Stroke, % (n=76,794)
|
1,412 (1.8)
|
59 (0.2)
|
1,353 (3.5)
|
All-cause mortality
During the study period, there were 39,195 deaths (49.2%) comprising 19,879 (50.7%) men and 19,316 women. Age-adjusted mortality was slightly higher in men compared to women (5.3 and 4.6 deaths per 1000/annum, respectively); 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 (adjusted HR 1.11, 95% CI 1.11-1.12 per year), male sex (1.59, 1.55-1.64 versus women), lower education (1.15, 1.11-1.18 for ≤9 years education versus rest), greater unhappiness (1.30, 1.21-1.39 for any degree of life dissatisfacton versus rest), being divorced/separated (1.15, 1.06-1.20 versus unmarried), obesity (1.13, 1.09-1.18), being a current smoker (1.89, 1.79-1.91 versus rest), excessive alcohol intake (1.09, 1.02-1.16 for >10 drinks in 14-days versus abstinence; P= .017), an elevated heart rate (1.03, 1.02-1.03 per 5 beats/min), higher systolic (1.02, 1.02-1.03 per 5 mmHg) and diastolic BP (1.01, 1.00-1.02 per 5 mmHg), as well as a self-reported history of AMI (1.65, 1.55-1.76), angina pectoris (1.26, 1.20-1.33) and stroke/cerebral event (1.48, 1.36-1.60). Alternatively, being married (adjusted HR 0.80, 95% CI 0.77-0.83 versus unmarried), better self-reported general health (0.76, 0.74-0.79 for good/very good versus rest), mild alcohol intake (0.94, 0.91-0.97 1-4 drinks in 14-days versus abstinence) and greater levels of exercise (0.89, 0.86-0.92 for moderate to high adherence to recommended 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 (8,355 [43.6%] and 7,969 deaths [43.0%], respectively); cancer (5,051 [26.4%] and 4,150 deaths [22.4%]) and; respiratory disease/illness (1,599 [8.3%] and 1,606 [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 (1,343 [3.4%]), psychiatric disorders (1,118 [2.9%]) and external factors including motor vehicle accidents and violence (951 [2.5%]).
Seasonal patterns of mortality
A striking pattern of seasonal fluctuations in all-cause mortality was evident throughout the study period (Figure 1). Overall, 1,707 more deaths occurred in winter (10,790 [27.5%]) compared to summer (9,083 [23.2%]). The differential between cardiovascular- and respiratory-related mortality occurring in winter (4,446 [27.4%] and 1,037 [32.4%] deaths) versus summer (3,832 [23.5%] and 661 [20.6%] deaths) contributed to 59% (1,010 deaths) of the observed variance between winter and summer. Although a more even distribution of mortality was observed in spring (9,900 [25.3%] deaths) and autumn (9,442 [24.0%] deaths), a seasonal pattern was still evident. Overall, 44 (95% CI 43-45) more deaths occurred each winter when compared to summer; with CVD (21, 95% CI 20-22 more deaths per annum), respiratory disease (13, 95% CI 13-14) and other miscellaneous conditions (14, 95% CI 13-14) being the main contributors to this differential. Moreover, the winter-to-summer differential in mortality for cancer-related deaths was only 10 during the entire study period – see Figure 2.
Monthly patterns of mortality
All-cause mortality peaked in the winter months of December (3,675 deaths) and January (3,592 deaths). The lowest mortality occurred in June (2,920 deaths). The annual excess all-cause mortality occurring during each of the peak months of December and January versus the low of June accounted for 22 (95% CI 21-22) more deaths. Cardiovascular-related deaths were the main contributors to this phenomenon in both December (11, 95% CI 9-10 more deaths) and January (8, 95% CI 7-9 more deaths) – Supplementary Figure S1. Both respiratory disease and a range of other causes of death (6-8 more deaths/month) also contributed to this phenomenon – Supplementary Figure S2.
The Christmas Holiday Effect
Regardless of the season, accumulative 3-day mortality mainly fluctuated between 90-110 deaths. However, a clear increase in mortality commencing the 22nd December was evident. The subsequent 3-day period over Christmas was the deadliest of the year (Figure 3) with 439 all-cause deaths. This was not a random phenomenon and was largely driven by an increase in cardiovascular-related and, to a lesser extent, cancer-related deaths (Figure 4). Each year, there were 1.3 (95% CI, 1.1-1.5) more all-cause and 1.0 (95% CI 0.7-1.3) cardiovascular-related deaths/day (accumulated total of 3.9 and 3.0 deaths) over this specific period compared to any other time of the year. This elevated mortality rate persisted until early January. During the 21 days from the 22nd December, there were 2,679 deaths (51.1% women) compared to 2,351 deaths (49% women) during the preceding 21 days and 2,016 deaths (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, each year there were 0.8 (95% CI 0.6-1.0) more all-cause deaths/day during the Christmas/New Year period. The major contributors to this phenomenon were CVD and to lesser extent, cancer and other causes.– Supplementary Figure S3. 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, respectively), 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 S4. Alternatively, except for an increased risk of dying from respiratory illnesses/disease among women, men had a higher risk of dying over the equivalent 21-day Christmas period; the major contributor to this increased mortality risk (from 6% to 22% higher overall) being CVD - Supplementary Figure S5.
Table 2
Correlates of All-Cause Mortality According to Baseline Profile
|
Dec 1st – 21st (Winter) versus
May 17th – June 6th (Summer)
|
Dec 22nd – Jan 11th (Christmas/New Year)
versus Dec 1st – 21st (Winter/Pre-Christmas)
|
|
Men
(n=1,543)
|
P
|
Women
(n= 1 351)
|
P
|
Men
(n=1,636)
|
P
|
Women
(n= 1,424)
|
P
|
Demographic profile, adjusted HR (95% CI)
|
Age at baseline (per year)
|
1.06 (1.05–1.07)
|
.001
|
1.05 (1.04–1.06)
|
.001
|
1.06 (1.05–1.07)
|
.001
|
1.05 (1.04–1.06)
|
.001
|
≤9 years education vs. rest
|
-
|
|
-
|
|
|
|
1.25 (1.03-1.52)
|
.026
|
Married vs. rest
|
-
|
|
-
|
|
0.71 (0.59-0.86)
|
.001
|
0.70 (0.54-91)
|
.001
|
Well-being, adjusted HR (95% CI)
|
Good/V. good physical health vs. rest
|
0.75 (0.64-0.87)
|
.001
|
0.82 (0.70-0.95)
|
.008
|
0.79 (0.68-0.92)
|
.002
|
0.82 (0.70-0.95)
|
.009
|
Life dissatisfaction vs. rest
|
-
|
|
1.52 (1.03-2.25)
|
.036
|
-
|
|
-
|
|
Past History, adjusted HR (95% CI)
|
Angina pectoris vs. rest
|
1.26 (0.98–1.63)
|
.074
|
1.57 (1.19–2.08)
|
.002
|
1.39 (1.06–1.80)
|
.016
|
1.99 (1.05–1.84)
|
.021
|
Acute myocardial infarction vs. rest
|
1.52 (1.11–2.07)
|
.008
|
-
|
-
|
1.45 (1.06–1.99)
|
.021
|
2.41 (1.46–3.80)
|
.001
|
Stroke vs. rest
|
-
|
|
-
|
|
-
|
|
2.01 (1.28–3.17)
|
.002
|
Lifestyle, adjusted HR (95% CI)
|
Current smoker vs. rest
|
1.28 (1.06–1.53)
|
.009
|
1.24 (1.04–1.49)
|
.018
|
1.39 (1.16–1.66)
|
.001
|
1.51 (1.26–1.82)
|
.001
|
Vital Signs, adjusted HR (95% CI)
|
Heart rate (per 5 beats/minute)
|
1.03 (1.01-1.06)
|
.011
|
-
|
|
1.03 (1.00-06)
|
.045
|
-
|
|
Systolic BP (per 5 mm/Hg)
|
1.04 (1.02-1.07)
|
.001
|
1.04 (1.02-06)
|
.001
|
1.03 (1.01-05)
|
.002
|
1.03 (1.00-03)
|
.019
|
Diastolic BP (per 5 mm/Hg)
|
-
|
|
1.07 (1.03-09)
|
.001
|
-
|
|
-
|
|
Beyond advancing age, a combination of baseline demographic, health perceptions and clinical factors were independently correlated with dying during – 1) late spring/early summer versus early winter, and then 2) early winter versus the Christmas holiday period. Whilst these factors were broadly similar for both sexes, including a 30% reduced risk during the Christmas holidays associated with being married at baseline, there were some notable differences. For example, consistent with an excess number of strokes among women, but not men, during the Christmas holidays, a pre-existing history of stroke conferred a 2-fold risk of dying during this period among women. Educational 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 different 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.