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Triglyceride (TG) concentration is used as a marker of cardiometabolic risk. However, diurnal and possibly weekday variation exists in TG concentrations. The objective of this work was to investigate weekday variation in TG concentrations among 1.8 million blood samples drawn between 2008 and 2015 from patients in the Capital region of Denmark. Plasma TG was extracted from a central clinical laboratory information system. Weekday variation was investigated by means of linear mixed models. In addition to the profound diurnal variation, the TG concentration was 4.5% lower on Fridays compared with Mondays (P < 0.0001). The variation persisted after multiple adjustments for confounders and was consistent across all sensitivity analyses. Out-patients and in-patients, respectively, had 5.0% and 1.9% lower TG concentrations on Fridays compared with Mondays (both P < 0.0001). The highest weekday variations in TG concentrations were recorded for out-patients between the ages of 9 and 26 years, with up to 20% higher values on Mondays compared with Fridays (all P < 0.05). In conclusion, TG concentrations were highest after the weekend and gradually declined during the week. We suggest that unhealthy food intake and reduced physical activity during the weekend increase TG concentrations which track into the week. This weekday variation may carry implications for public health and future research practice.
Blood cholesterol and vascular mortality by age, sex, and blood pressure: a meta-analysis of individual data from 61 prospective studies with 55,000 vascular deaths.
), and treatment has focused on lowering total non-HDL-CH. However, some observational studies and a meta-analysis have indicated that high plasma triacylglycerol/triglyceride (TG) concentrations may be an independent atherogenic risk factor. All interventional studies have been based upon fasting or postprandial TG concentrations, yet nonfasting TG concentrations seem to be more strongly associated with CVD than fasting TG concentrations (
An improved understanding of biological variation in clinically measured compounds in human material may be useful for many purposes in clinical chemistry (
). There may, however, be several sources of variation that contribute to the biological variation. Many compounds such as CH, TG, and other lipids have diurnal and seasonal variation, in addition to variation due to lifestyle behavior (
). However, to our knowledge, no study has investigated the weekday variations of TG concentrations in a large sample, including adults.
Therefore, the aim of this study was to investigate whether and to what extent TG concentrations vary according to the day of week using approximately 1.8 million unselected blood samples analyzed at hospitals in the Capital region in Denmark from 2008 through 2015. We hypothesized that TG concentrations would be higher on Mondays compared with Fridays.
MATERIALS AND METHODS
The present study was based on anonymized data extracted from a common clinical laboratory information system (Labka II; CSC, Tysons, VA). The database contains millions of stored test results from in- and out-patients in the Capital region of Denmark with a population of about 1.8 million inhabitants. The samples were commissioned by general practitioners, specialists, and doctors during everyday life or hospitalization. Blood samples were obtained at various time points and for multiple reasons; thus, for routine checkups, suspicion of illness, hospital admission and readmission, during hospitalization, and before hospital discharge, they comprise measurements of various blood parameters from males and females of any age. The laboratory data were obtained from 13 hospital laboratories in the region with different instruments, varying both over time and by location. However, results were comparable due to common quality control systems and sample exchange. Most of the analyses were performed according to ISO-15189 accreditation.
The primary analytical sample comprised data from TG. Data of alanine transaminase (ALAT), hemoglobin (Hgb), and sodium were extracted to support the interpretation of the TG data. The test results for each blood sample were accompanied by information about the executive laboratory, date and time, patient-setting, fasting status, age, gender, and a unique subject identifier.
Analyses were mainly performed using Kone-lab, Espoo, Finland; Vitros 950/5.2 chemistry system (Johnson and Johnson, Rochester, NY); and Hitachi 912, Cobas Integra 400/800, Cobas Modular 6000/8000, Cobas Modular (Roche Diagnostics, Basel, Switzerland); Dimension Vista 1500 (Siemens Medical Solutions Diagnostics, Tarrytown, NY), and the Advia 120/2120 hematology system (Siemens); Sysmex XE, XI, or XN series (Sysmex, Kobe, Japan).
Colorimetric methods were used to measure TG in plasma according to the manufacturers' protocols. The relative expanded uncertainty for CH is approximately 10%, whereas for TGs it is approximately 22–23%. Plasma ALAT was measured according to the IFCC 2002 method, plasma sodium was measured with ion-selective electrodes, and blood Hgb with a non-cyanide method on automated hematology instruments.
Statistics
Weekday variation in TG, Hgb, ALAT, and sodium concentrations was described by means of linear mixed models; one model per outcome. Observations with missing data were excluded. Linear mixed models comprised fixed effects including gender, age-group (5 year intervals), fasting-status (fasting, nonfasting), hospitals, setting [out-patient, in-patient, in-between-patient (staying at the hospital during day time, but sleeping at home)], year, month, time of the day (hour), and subject-specific random effects. If appropriate, skewed variables were log-transformed and subsequently back-transformed. The majority of the TG and ALAT data was processed by this approach; whereas for Hgb and sodium, a log-transformation of the data was not required. Results were shown as mean concentrations with 95% CI, as estimated by the package, multcomp 1.4-4 (
). The difference between Monday and Friday was assessed through a pairwise comparison using a post hoc t-test. The same approach was used to test differences between weekdays and weekend days for hydration markers (Hgb and sodium). As hydration level was expected to be different on weekdays compared with weekend days, the difference between Monday and Friday for each marker was calculated. Sensitivity analysis for TG was performed in order to evaluate the robustness of the results in respect to various characteristics. Specifically, sensitivity analyses comprised aforementioned linear mixed models stratified according to samples ≤3.0 mmol/l (≤266 mg/dl) and ≤1.7 mmol/l (≤151 mg/dl), gender, patient-status, age (by each year), fasting-status, hospital, and sample time (year, month, hour). All the statistical analyses were conducted using R version 3.2.4 (
Characteristics of the 1,828,861 observations for TG, as well as for the observations for Hgb, sodium, and ALAT can be found in Table 1. The TG observations were obtained from a total of 633,123 subjects. A total of 80.6% of the TG samples were from out-patients, as were 40.1, 41.5, and 58.5% for sodium, Hgb, and ALAT, respectively. The overall proportion of TG concentrations ≥1.7 mmol/l (≥151 mg/dl) was 32.7%; with 34.8, 34.0, 32.8, 31.3, and 29.7% for Monday through Friday, respectively. TG concentrations were 4.5% (4.3%, 4.7%; P < 0.0001) lower on Fridays compared with Mondays when using mixed models (Table 2) . Furthermore, negligible differences were observed between Monday and Friday for Hgb and sodium concentrations (both P < 0.0001), whereas no difference was observed for ALAT (P = 0.11). Concentrations of Hgb on all of the weekdays were systematically higher compared with weekend days (all P < 0.0001), whereas this was the opposite for ALAT (all P < 0.0001).
TABLE 1Characteristics of the study population according to TG, Hgb, sodium, and ALAT status
Characteristics
TG
Hgb
Sodium
ALAT
Observations (n)
1,828,861
3,000,000
1,544,204
3,000,000
Gender (% female)
48.2
51.3
50.1
52.7
Age (years)
63 (36–80)
64 (29–84)
67 (33–85)
61 (28–81)
Setting (%)
Out-patient
80.6
41.5
40.1
58.5
In-patient
18.0
56.9
58.6
39.8
In-between-patient
1.4
1.6
1.3
1.7
Fasting-status (%)
Non-fasting
87.1
100
100
100
Fasting
12.9
—
—
—
Day (%)
Monday
21.0
19.3
19.3
20.7
Tuesday
22.3
18.4
18.4
19.9
Wednesday
20.0
17.8
17.5
18.7
Thursday
20.2
17.3
16.8
18.4
Friday
13.7
14.7
14.7
14.2
Saturday
1.4
6.3
6.6
4.0
Sunday
1.4
6.3
6.6
4.1
Year (%)
2008
1.3
1.2
—
0.9
2009
8.7
8.2
—
7.2
2010
11.2
10.4
—
9.7
2011
13.5
13.6
—
12.8
2012
14.8
15.5
—
15.2
2013
15.9
16.2
—
16.9
2014
17.0
17.3
100.0
18.4
2015
17.6
17.5
—
18.9
Data are expressed as n, median (10th to 90th percentile), or proportion.
TABLE 2Weekday variation in TG, Hgb, sodium, and ALAT status
Monday
Tuesday
Wednesday
Thursday
Friday
Saturday
Sunday
Diff. (%)
n
n
n
n
n
n
n
Mean (95% CI)
Mean (95% CI)
Mean (95% CI)
Mean (95% CI)
Mean (95% CI)
Mean (95% CI)
Mean (95% CI)
P for Diff.
TG (mmol/l)
383,523
407,973
366,510
368,983
249,996
25,926
25,950
−4.5 (−4.7;−4.3)
1.68 (1.68;1.69)
1.68 (1.68;1.68)
1.65 (1.65;1.65)
1.63 (1.62;1.63)
1.61 (1.61;1.61)
1.63 (1.62;1.63)
1.62 (1.61;1.63)
<0.0001
Hgb (mmol/l)
577,715
551,585
534,626
519,079
440,553
187,708
188,734
−0.4 (−0.4;−0.3)
7.78 (7.78;7.78)
7.78 (7.78;7.78)
7.76 (7.76;7.77)
7.76 (7.76;7.76)
7.75 (7.75;7.76)
7.66 (7.65;7.66)
7.68 (7.65;7.66)
<0.0001
Sodium (mmol/l)
298,186
284,574
269,718
259,389
227,653
102,178
102,506
−0.04 (−0.06;−0.03)
138.89 (138.88;138.91)
138.83 (138.81;138.84)
138.85 (138.83;138.87)
138.89 (138.87;138.91)
138.84 (138.82;138.86)
138.81 (138.79;138.84)
138.86 (138.84;138.89)
<0.0001
ALAT (U/l)
620,034
596,627
562,317
552,747
425,284
120,421
122,570
0.1 (0.0;0.3)
36.25 (36.11;36.38)
36.18 (36.12;36.24)
36.33 (36.27;36.39)
36.42 (36.35;36.48)
36.30 (36.23;36.37)
36.88 (36.77;36.98)
36.77 (36.66;36.88)
>0.11
Data are presented as mean and 95% CI per day using a linear mixed model adjusted for gender, age-group (5 year intervals), fasting-status (fasting, nonfasting), hospitals, setting (out-patient, in-patient, in-between-patient), year, month, time of the day (hour) as fixed effects. and subject as random effect. The mean and 95% CI are expressed as mmol/l. TG: 1 mmol/l is equivalent to 88.57 mg/dl; Hgb: 1 mmol/l is equivalent to 1.61 g/dl; sodium: 1 mmol/l is equivalent to 2.3 mg/dl. P for Diff. between Monday and Friday was obtained using pairwise comparisons. Diff., difference between Monday and Friday (negative percentage indicates a higher value on Monday compared with Friday); n, number of observations.
Weekday variation in TG concentrations remained after stratifying on age (Fig. 1, supplemental Table 1) , gender, truncation of values, fasting status, setting, hospital, year, and month (Table 3) . The variation from Monday to Friday was roughly 10% for 14–26 years of age, followed by gradually decreasing variations of about 4% around age 65. The decline in variation continued, reaching nonsignificance at the age of 80 years. Only 1.4% of the <1-year-old infants and 31% of the children between 1 and 9 years were out-patients. The proportion of out-patients exceeded 50% by the age of 9 years and increased linearly to 84% until the age of 74 years (data not shown). Out-patients had a Monday to Friday difference of −5.0%, while in-patients had a difference of −1.9% (both P < 0.0001). Out-patients had systematically larger weekday variation in each of the age groups, as shown in Fig. 1. The highest variations were recorded for out-patients between 9 and 26 years of age, with up to 20% higher values on Monday compared with Friday (all P < 0.05). The differences were −5.5% and −4.4% in fasting and nonfasting samples (both P < 0.0001), respectively. In view of the different seasons, the lowest Monday to Friday variations were observed in April and July (both −3.7%, P < 0.0001).
Fig. 1Difference (percent) in TG concentrations from Monday to Friday by age (years) for all observations and out-patients with more than 100 observations on each day. Data are presented as the percentage difference from Monday and are based on means using a linear mixed model with gender, fasting-status (fasting, nonfasting), hospitals, year, month, and time of the day (hour) as fixed effects, and subject as random effect. Additionally “All observations” are adjusted for setting (out-patient, in-patient, in-between-patient). Number of observations in out-patients ranging from 106 to 727 on each Monday or Friday during adolescence followed by gradually increasing numbers up to age 68 (n > 5,812) then decreasing gradually (n > 2,574 at age 79).
TABLE 3Weekday variation for TGs in different strata of the population
Monday
Tuesday
Wednesday
Thursday
Friday
Saturday
Sunday
Diff. (%)
n
n
n
n
n
n
n
Mean (95% CI)
Mean (95% CI)
Mean (95% CI)
Mean (95% CI)
Mean (95% CI)
Mean (95% CI)
Mean (95% CI)
P for Diff.
Gender
Female
183,405
196,780
177,491
178,531
120,598
12,065
12,094
−4.4 (−4.6;−4.2)
1.57 (1.56;1.57)
1.56 (1.55;1.56)
1.53 (1.53;1.53)
1.51 (1.51;1.51)
1.50 (1.49;1.50)
1.51 (1.50;1.52)
1.51 (1.50;1.52)
<0.0001
Male
200,118
211,193
189,019
190,452
129,398
13,861
13,856
−4.6 (−4.9;−4.4)
1.79 (1.79;1.80)
1.79 (1.79;1.79)
1.76 (1.75;1.76)
1.73 (1.72;1.73)
1.71 (1.71;1.71)
1.73 (1.72;1.74)
1.86 (1.72;1.74)
<0.0001
Truncation
TG ≤ 3.0 (mmol/l)
349,511
373,006
336,157
340,353
231,547
23,487
23,545
−4.4 (−4.5;−4.2)
1.40 (1.40;1.40)
1.39 (1.39;1.40)
1.37 (1.37;1.37)
1.35 (1.35;1.35)
1.34 (1.33;1.34)
1.34 (1.33;1.34)
1.34 (1.33;1.34)
<0.0001
TG ≤ 1.7 (mmol/l)
252,066
271,436
248,013
255,179
176,886
17,708
17,714
−3.4 (−3.6;−3.3)
1.09 (1.09;1.09)
1.09 (1.09;1.09)
1.07 (1.07;1.08)
1.06 (1.06;1.06)
1.05 (1.05;1.05)
1.05 (1.05;1.05)
1.05 (1.05;1.05)
<0.0001
Setting
Out-patient
315,205
345,408
307,861
306,749
197,633
614
1402
−5.0 (−5.2;−4.8)
1.68 (1.67;1.68)
1.67 (1.67;1.68)
1.64 (1.63;1.64)
1.61 (1.61;1.62)
1.60 (1.59;1.60)
1.57 (1.52;1.62)
1.67 (1.64;1.70)
<0.0001
In-patient
62,480
57,394
53,671
57,109
48,764
25,267
24,419
−1.9 (−2.4;−1.4)
1.69 (1.68;1.70)
1.69 (1.69;1.70)
1.68 (1.67;1.69)
1.67 (1.66;1.68)
1.66 (1.65;1.67)
1.66 (1.65;1.67)
1.66 (1.65;1.67)
<0.0001
In-between-patient
5,838
5,171
4,978
5,125
3,599
45
129
−2.7 (−4.3;−1.2)
1.87 (1.83;1.91)
1.85 (1.83;1.88)
1.85 (1.82;1.87)
1.83 (1.80;1.86)
1.82 (1.79;1.85)
1.76 (1.55;1.96)
1.79 (1.67;1.91)
0.0006
Fasting-status
Non-fasting
334,531
354,191
320,213
318,156
216,475
24,911
24,947
−4.4 (−4.6;−4.2)
1.70 (1.70;1.71)
1.69 (1.69;1.70)
1.66 (1.66;1.67)
1.64 (1.64;1.65)
1.63 (1.62;1.63)
1.64 (1.63;1.65)
1.64 (1.63;1.65)
<0.0001
Fasting
48,992
53,782
46,297
50,827
33,521
1,015
1,003
−5.5 (−6.0;−5.0)
1.58 (1.57;1.59)
1.58 (1.57;1.58)
1.54 (1.53;1.55)
1.51 (1.50;1.52)
1.49 (1.48;1.50)
1.50 (1.46;1.54)
1.54 (1.50;1.58)
<0.0001
Hospitals
A
22,163
21,104
18,621
22,781
13,350
1,212
1,533
−2.8 (−3.5;−2.0)
1.80 (1.78;1.82)
1.79 (1.78;1.80)
1.78 (1.76;1.79)
1.75 (1.74;1.77)
1.75 (1.74;1.77)
1.75 (1.71;1.79)
1.71 (1.67;1.74)
<0.0001
B
32,476
30,764
29,007
28,294
20,499
4,756
4,542
−3.8 (−4.6;−3.0)
1.82 (1.81;1.84)
1.82 (1.81;1.83)
1.80 (1.79;1.81)
1.78 (1.77;1.79)
1.76 (1.74;1.77)
1.73 (1.70;1.75)
1.76 (1.74;1.79)
<0.0001
C
30,861
30,229
28,924
29,337
24,256
4,122
4,114
−3.4 (−4.1;−2.7)
1.67 (1.66;1.69)
1.67 (1.66;1.68)
1.65 (1.64;1.66)
1.62 (1.61;1.63)
1.61 (1.60;1.63)
1.64 (1.61;1.66)
1.63 (1.60;1.65)
<0.0001
D
20,927
21,067
17,105
22,656
15,181
611
515
−4.7 (−5.4;−4.0)
1.55 (1.53;1.57)
1.55 (1.54;1.56)
1.51 (1.50;1.52)
1.49 (1.48;1.50)
1.48 (1.46;1.49)
1.50 (1.45;1.54)
1.55 (1.50;1.60)
<0.0001
E
9,286
10,489
9,245
9,014
8,550
1,387
1,213
−1.4 (−2.5;−0.3)
1.76 (1.72;1.80)
1.78 (1.76;1.80)
1.75 (1.73;1.77)
1.74 (1.72;1.76)
1.74 (1.72;1.76)
1.73 (1.69;1.77)
1.72 (1.67;1.76)
0.0158
F
123,210
138,333
120,704
120,035
79,826
2,200
2,255
−5.7 (−6.0;−5.4)
1.68 (1.67;1.68)
1.67 (1.67;1.68)
1.63 (1.63;1.63)
1.61 (1.60;1.61)
1.58 (1.58;1.59)
1.62 (1.59;1.64)
1.64 (1.62;1.67)
<0.0001
G
364
1,882
687
1,717
393
0
1
−0.9 (−6.0;4.2)
2.06 (1.87;2.24)
2.14 (2.04;2.24)
1.97 (1.87;2.06)
2.09 (1.99;2.19)
2.04 (1.93;2.14)
0 (0;0)
3.79 (1.50;6.07)
0.7369
H
33,101
36,172
34,041
32,155
19,911
534
538
−5.7 (−6.3;−5.1)
1.57 (1.55;1.58)
1.55 (1.55;1.56)
1.53 (1.52;1.54)
1.50 (1.49;1.51)
1.48 (1.47;1.49)
1.57 (1.52;1.61)
1.53 (1.49;1.58)
<0.0001
I
29,444
37,890
32,893
32,164
19,567
609
636
−5.3 (−5.9;−4.7)
1.63 (1.62;1.65)
1.63 (1.62;1.64)
1.59 (1.58;1.60)
1.56 (1.55;1.57)
1.55 (1.54;1.56)
1.62 (1.58;1.67)
1.57 (1.53;1.62)
<0.0001
J
26,391
27,745
25,544
22,998
7,934
494
522
−3.7 (−4.5;−2.9)
1.69 (1.67;1.70)
1.68 (1.67;1.69)
1.64 (1.63;1.65)
1.63 (1.62;1.64)
1.62 (1.61;1.64)
1.64 (1.59;1.69)
1.63 (1.57;1.68)
<0.0001
K
12,475
12,442
11,303
11,206
9,368
2,214
2,299
−1.6 (−2.7;−0.6)
1.65 (1.63;1.67)
1.66 (1.65;1.68)
1.63 (1.62;1.65)
1.63 (1.61;1.64)
1.62 (1.61;1.64)
1.62 (1.59;1.65)
1.62 (1.59;1.65)
0.0024
L
25,478
23,233
21,937
22,374
18,200
4,973
5,221
−2.0 (−2.7;−1.3)
1.74 (1.73;1.76)
1.73 (1.72;1.75)
1.71 (1.70;1.73)
1.70 (1.69;1.72)
1.71 (1.69;1.72)
1.72 (1.70;1.74)
1.70 (1.68;1.72)
<0.0001
M
17,347
16,623
16,499
14,252
12,961
2,814
2,561
−3.1 (−3.9;−2.2)
1.73 (1.72;1.75)
1.73 (1.72;1.75)
1.70 (1.68;1.71)
1.68 (1.67;1.70)
1.67 (1.65;1.68)
1.66 (1.63;1.69)
1.66 (1.63;1.69)
<0.0001
Year
2008
4,922
5,514
4,535
4,692
3,583
244
223
−6.4 (−8.5;−4.3)
1.61 (1.57;1.64)
1.60 (1.57;1.63)
1.55 (1.52;1.58)
1.55 (1.51;1.58)
1.50 (1.47;1.54)
1.52 (1.42;1.62)
1.54 (1.43;1.64)
<0.0001
2009
31,448
36,990
32,027
33,501
22,195
1,571
1,638
−5.4 (−6.1;−4.7)
1.60 (1.61;1.65)
1.63 (1.62;1.64)
1.60 (1.59;1.61)
1.57 (1.56;1.58)
1.54 (1.53;1.55)
1.55 (1.52;1.59)
1.56 (1.53;1.60)
<0.0001
2010
41,332
47,546
41,457
42,446
27,420
2,161
2,226
−5.5 (−6.2;−4.9)
1.63 (1.62;1.64)
1.63 (1.62;1.64)
1.59 (1.58;1.60)
1.56 (1.55;1.57)
1.54 (1.53;1.55)
1.59 (1.56;1.62)
1.59 (1.57;1.62)
<0.0001
2011
50,979
55,648
50,103
50,493
33,116
3,669
3,524
−5.4 (−6.0;−4.8)
1.66 (1.64;1.66)
1.66 (1.65;1.66)
1.63 (1.62;1.64)
1.60 (1.59;1.61)
1.57 (1.56;1.58)
1.61 (1.59;1.63)
1.62 (1.60;1.64)
<0.0001
2012
57,061
58,893
54,428
55,668
36,475
4,461
4,521
−4.5 (−5.1;−4.0)
1.65 (1.64;1.66)
1.65 (1.64;1.65)
1.62 (1.59;1.61)
1.60 (1.59;1.61)
1.58 (1.57;1.58)
1.60 (1.58;1.62)
1.58 (1.56;1.61)
<0.0001
2013
62,444
62,950
56,580
59,321
40,083
4,491
4,431
−4.7 (−5.2;−4.1)
1.69 (1.68;1.70)
1.68 (1.67;1.69)
1.65 (1.64;1.66)
1.63 (1.62;1.64)
1.61 (1.60;1.62)
1.61 (1.59;1.63)
1.62 (1.59;1.64)
<0.0001
2014
66,555
68,907
62,229
59,818
43,483
4,570
4,688
−4.3 (−4.8;−3.8)
1.73 (1.72;1.74)
1.73 (1.72;1.74)
1.69 (1.69;1.70)
1.68 (1.67;1.69)
1.66 (1.65;1.67)
1.69 (1.67;1.71)
1.65 (1.63;1.67)
<0.0001
2015
68,782
71,525
65,151
63,044
43,641
4,759
4,699
−4.3 (−4.8;−3.9)
1.74 (1.73;1.75)
1.73 (1.73;1.74)
1.71 (1.70;1.71)
1.68 (1.67;1.69)
1.67 (1.66;1.67)
1.66 (1.64;1.68)
1.68 (1.66;1.70)
<0.0001
Month
January
33,161
34,110
31,317
34,170
23,370
1,984
1,967
−4.9 (−5.6;−4.2)
1.72 (1.70;1.73)
1.70 (1.69;1.71)
1.67 (1.66;1.68)
1.65 (1.64;1.66)
1.64 (1.62;1.65)
1.71 (1.67;1.74)
1.64 (1.61;1.68)
<0.0001
February
28,644
30,217
28,164
28,139
19,023
1,868
1,815
−5.4 (−6.2;−4.6)
1.71 (1.69;1.72)
1.70 (1.69;1.71)
1.67 (1.66;1.68)
1.64 (1.63;1.65)
1.62 (1.60;1.63)
1.62 (1.58;1.65)
1.60 (1.58;1.65)
<0.0001
March
35,744
36,003
30,570
31,583
21,728
2,127
2,142
−5.6 (−6.3;−4.9)
1.67 (1.65;1.68)
1.66 (1.65;1.67)
1.63 (1.62;1.64)
1.60 (1.59;1.61)
1.57 (1.56;1.59)
1.60 (1.57;1.63)
1.63 (1.60;1.67)
<0.0001
April
26,969
35,394
31,941
28,801
17,433
1,984
2,014
−3.7 (−4.5;−2.9)
1.64 (1.62;1.65)
1.64 (1.63;1.66)
1.62 (1.61;1.63)
1.59 (1.58;1.60)
1.58 (1.56;1.59)
1.61 (1.58;1.64)
1.59 (1.56;1.62)
<0.0001
May
31,622
36,571
32,901
29,423
20,168
2,146
2,240
−4.6 (−5.3;−3.8)
1.63 (1.61;1.64)
1.62 (1.61;1.63)
1.60 (1.59;1.61)
1.58 (1.57;1.59)
1.55 (1.54;1.57)
1.57 (1.54;1.61)
1.57 (1.54;1.60)
<0.0001
June
33,357
36,135
31,932
31,061
20,861
2,152
2,144
−5.5 (−6.3;−4.8)
1.67 (1.66;1.69)
1.67 (1.66;1.68)
1.63 (1.62;1.64)
1.61 (1.60;1.62)
1.58 (1.57;1.59)
1.61 (1.58;1.64)
1.60 (1.56;1.63)
<0.0001
July
19,925
22,097
21,042
21,254
14,334
1,913
1,974
−3.7 (−4.7;−2.7)
1.67 (1.65;1.69)
1.67 (1.66;1.69)
1.64 (1.62;1.65)
1.62 (1.61;1.64)
1.61 (1.59;1.63)
1.59 (1.55;1.63)
1.63 (1.60;1.67)
<0.0001
August
33,831
33,240
29,855
31,212
21,689
2,225
2,174
−5.1 (−5.8;−4.3)
1.70 (1.68;1.71)
1.69 (1.68;1.70)
1.67 (1.66;1.68)
1.63 (1.62;1.65)
1.61 (1.60;1.62)
1.64 (1.61;1.67)
1.60 (1.56;1.63)
<0.0001
September
35,672
38,063
33,672
34,074
22,243
2,187
2,236
−5.0 (−5.7;−4.3)
1.69 (1.68;1.71)
1.69 (1.68;1.70)
1.66 (1.65;1.67)
1.63 (1.62;1.65)
1.61 (1.60;1.62)
1.61 (1.58;1.64)
1.60 (1.57;1.63)
<0.0001
October
34,407
34,852
32,741
35,663
24,424
2,387
2,268
−4.9 (−5.6;−4.2)
1.69 (1.67;1.70)
1.68 (1.67;1.69)
1.65 (1.64;1.66)
1.63 (1.62;1.64)
1.61 (1.59;1.62)
1.62 (1.59;1.65)
1.60 (1.57;1.63)
<0.0001
November
39,523
39,466
34,968
35,990
26,193
2,465
2,513
−5.3 (−5.9;−4.6)
1.70 (1.68;1.71)
1.68 (1.67;1.69)
1.66 (1.65;1.67)
1.63 (1.62;1.64)
1.61 (1.59;1.62)
1.60 (1.57;1.63)
1.60 (1.57;1.63)
<0.0001
December
30,668
31,825
27,407
27,613
18,530
2,488
2,463
−4.9 (−5.7;−4.1)
1.73 (1.71;1.74)
1.72 (1.71;1.73)
1.68 (1.67;1.69)
1.66 (1.65;1.67)
1.64 (1.63;1.66)
1.65 (1.62;1.68)
1.64 (1.61;1.68)
<0.0001
Data are presented as mean and 95% CI per day using a linear mixed model adjusted for gender, age-group (5 year intervals), fasting-status (fasting, nonfasting), hospitals, setting (out-patient, in-patient, in-between-patient), year, month, time of the day (hour) as fixed effects, except the adjustment against the very same predictor (e.g., the analysis between the year and the TG concentration is not adjusted for year) and subject as random effect. The mean and 95% CI are expressed as mmol/l. TG: 1 mmol/l is equivalent to 88.57 mg/dl. P for Diff. between Monday and Friday was obtained using pairwise comparisons. Diff., difference between Monday and Friday (negative percentage indicates a higher value on Monday compared with Friday); n, number of observations.
On all weekdays, TG concentrations were lowest around 7:00 AM, ranging from 1.61 mmol/l (143 mg/dl) on Mondays to 1.52 mmol/l (135 mg/dl) on Fridays. The time trends for out-patients were in accordance with the overall data (Fig. 2) . Patterns between 7:00 AM and 2:00 PM on each weekday were comparable; however with each subsequent day of the week, the TG concentrations declined. On average, the TG concentrations reached their peak at 2:00 PM each weekday with 23.3, 22.3, 24.3, 22.1, and 27.4% higher concentrations compared with concentrations at 7:00 AM on Monday to Friday, respectively. The highest number of observations was recorded at 7:00 AM with more than 50,000 observations on each weekday. After 1:00 PM the number of observations dropped rapidly to less than 700 observations at 2:00 PM on Friday. The weekday variation for plasma total-CH, LDL-CH, and HDL-CH were all less than 1% (supplemental Table 2).
Fig. 2TG concentration (millimoles per liter) in out-patients from Monday to Friday during laboratory hours (n = 1,251,825). Data are presented as mean using a linear mixed model with gender, age-group (5 year intervals), fasting-status (fasting, nonfasting), hospitals, year, and month as fixed effects and subject as random effect. Numbers of observations range from 57 on Friday at 4:00 PM to 84,510 on Tuesday at 7:00 AM. TG: 1 mmol/l is equivalent to 88.57 mg/dl.
In support of the hypothesis, TG varied according to weekdays, with higher concentrations on Mondays compared with Fridays. The overall observed variation of 4.5% between Mondays and Fridays in TG concentrations is based on more than 1.8 million samples and persisted after multiple adjustments. The phenomenon exists across gender, age, hospital, fasting state of the sample, year, month, hour of the day, and after truncation of abnormal values. The variation between Monday and Friday was negligible for total-CH, LDL-CH, HDL-CH, Hgb, and sodium, as well as not present for ALAT; this speaks against an effect on TG concentrations caused by variation in hydration level and suggests that it is not caused by high alcohol intake. Anticipating that the sampling on weekends is done more frequently on patients with more serious illnesses, results from weekend days need to be interpreted with caution.
Of particular interest, out-patients showed higher weekday variation than in-patients and the weekday variation was highest in adolescence with gradually decreasing differences by age. The explanation for this phenomenon could be that lifestyle factors are less controlled in out-patients that probably continue their usual diet, drinking, and exercise habits compared with the more restricted hospital environment.
The average alcohol consumption among Danes is higher from Friday to Sunday compared with Monday through Thursday (
Moderate alcohol consumption and changes in postprandial lipoproteins of premenopausal and postmenopausal women: a diet-controlled, randomized intervention study.
) 1 and 3 h after consumption of 30 g of alcohol together with a meal, TG concentration returns to baseline after an overnight fast. In support of this, the present study was unable to detect weekday variation in 3 million ALAT observations. Alcohol intake and ALAT have been linearly associated in men (
); however, the role of ALAT as a sensitive marker for acute alcohol intake is questionable, as it has a long half-life time and fluctuates within and between days (
). Therefore, we cannot exclude alcohol as a mediator of the observed weekday variation in TG. Against the hypothesis of an alcohol-mediated effect is the large TG variation in 9- to 14-year-old out-patient children in the present study, and the 28% higher TG concentrations on Mondays compared with Fridays in 8- to 11-year-old healthy children found in another Danish observational study (
). We speculate that these age groups are unlikely to consume any alcohol and our observed weekday variation in TG concentrations is, therefore, most likely not related to alcohol intake.
Previous studies suggest that carbohydrate (CHO)-rich diets induce hypertriglyceridemia (
). Switching from a high-fat (70%) diet to a high-CHO (75%) diet, TG concentrations have been found to rise significantly within 1 week and reach their peak after 4 weeks. After shifting back, TG concentrations declined gradually over a course of weeks with the largest changes in the first week (
). In another study of 14 healthy postmenopausal women, the habitual diet was changed gradually to reduce dietary fat intake and increase CHO intake over a period of 3 months. In response, the TG concentrations increased from 2.1 mmol/l (186 mg/dl) to 2.5 mmol/l (221 mg/dl) between the first and the second half of the study with the diets comprising 60% CHO and 67% CHO, respectively (
). Long-chain polyunsaturated omega-3 fatty acids (n-3 PUFAs), particularly EPA and DHA, are known to lower fasting TG concentrations by 20–40%, depending on the n-3 dose and the TG baseline value (
Efficacy and tolerability of adding prescription omega-3 fatty acids 4 g/d to simvastatin 40 mg/d in hypertriglyceridemic patients: an 8-week, randomized, double-blind, placebo-controlled study.
). Even though it is evident that n-3 PUFAs reduce TG concentrations, intervention periods are commonly greater than 4 weeks with average intakes of 3–4 g of EPA and DHA daily (
Efficacy and tolerability of adding prescription omega-3 fatty acids 4 g/d to simvastatin 40 mg/d in hypertriglyceridemic patients: an 8-week, randomized, double-blind, placebo-controlled study.
). Acute effects of n-3 PUFA have only been recorded with a single dose of 20 g fish oil (68% n-3 PUFA), which reduced TG concentrations by 33% 14 h after the ingestion (
Previous literature shows that energy intake above the individual requirement results in the overproduction of VLDL in the liver and consequently increases TG concentrations (
). Current research suggests that the effect of positive energy balance on TG metabolism is determined by the macronutrient consumed in excess. Overfeeding of CHO for a period of 4–7 days increased the concentration of TGs up to 79% (
A single 1-h bout of evening exercise increases basal FFA flux without affecting VLDL-triglyceride and VLDL-apolipoprotein B-100 kinetics in untrained lean men.
Am. J. Physiol. Endocrinol. Metab.2007; 292: E1568-E1574
). A session of exercise equal to approximately 3 MJ expended energy reduces plasma TG concentrations the following day in the postprandial state by 17–33% (
). Therefore, the major cause of the TG-lowering effect during weekdays is plausibly energy expenditure. Furthermore, evidence emerges that the energy expenditure threshold can also be overcome by a combination of mild dietary restriction and light exercise (
Exercise of low energy expenditure along with mild energy intake restriction acutely reduces fasting and postprandial triacylglycerolaemia in young women.
A recent survey found Danish children to have about 10–12% higher energy consumption on Fridays and weekends compared with the remaining days of the week with more added sugar comprising some of this difference (
). There is no indication that additional exercise compensates for the excess energy intake on weekend days, considering that children are less physically active and more sedentary on these days (
Seasonal variation in objectively measured physical activity, sedentary time, cardio-respiratory fitness and sleep duration among 8-11 year-old Danish children: a repeated-measures study.
). Based on these results, energy imbalance may be speculated to be a rationale for the observed Monday to Friday variation. In support of this energy imbalance theory between weekdays and weekends, higher leptin and lower ghrelin have been found in children on Mondays compared with Fridays with a gradual decline from Monday to Friday (
). In the present study, Monday to Friday variations were largest in late childhood until young adulthood and gradually decreased with age. The dietary and physical activity (PA) patterns for children are highly structured due to school during the week, whereas the patterns for adults have larger variability and are likely to change during different cycles of life, e.g., moving out, parenthood, or retirement, therefore patterns are not as generalizable as those of children. Hence, the complexity of adult PA behavior may also be speculated to reflect the lower Monday to Friday variation compared with children.
In-patients have to adapt to hospital procedures, such as meal choice and PA independent of weekday, whereas out-patients are autonomous in their eating and PA behavior. The rather small weekday variation for in-patients and fairly large weekday variation for out-patients therefore may support that eating and PA behavior are among the main drivers of this weekday variation in TG. As it was recently found that objectively measured PA of children varies considerably more between weekdays and weekend days during winter compared with spring (
Seasonal variation in objectively measured physical activity, sedentary time, cardio-respiratory fitness and sleep duration among 8-11 year-old Danish children: a repeated-measures study.
), this behavior theory may be further supported by our weekday variation being largest in November, February, and March and lowest during April, May, and July.
TG concentrations fluctuate in response to dietary intake. Most individuals eat regularly throughout the day, hence TG concentrations are very dynamic and lowest concentrations are usually measured in the morning after overnight fasting. It has been shown that TG concentrations increase up to 20% and remain elevated up to 6 h subsequently to the last meal (
Fasting is not routinely required for determination of a lipid profile: clinical and laboratory implications including flagging at desirable concentration cut-points–a joint consensus statement from the European Atherosclerosis Society and European Federation of Clinical Chemistry and Laboratory Medicine.
). The present study was able to confirm this daily variation in TG with differences ranging from 22% to 27% between 7:00 AM and 2:00 PM on each weekday. Fluctuations in CH concentrations have been suggested to range between 5% and 10% (
Moderate alcohol consumption and changes in postprandial lipoproteins of premenopausal and postmenopausal women: a diet-controlled, randomized intervention study.
). The present study observed only minor weekly variation for CH concentrations.
Moreover, it has been suggested that the occurrence of acute myocardial infarction, sudden death, and cardiac arrest is higher on Monday compared with the rest of the week (
Strengths of the present study include the large amount of samples representing a wide range of subjects across all ages from 13 different hospitals and making subgroup analysis possible without limiting power. Furthermore, Hgb and sodium measurements were used to investigate the potential differences in hydration status. Multiple covariates were used to adjust the analyses and reduce confounding. TG measurements performed at the hospitals are in most cases not affected by the potential disease or treatment of the patients. Results for out-patients, especially, may therefore be reasonably generalizable to the entire population in Denmark due to the rather homogenous lifestyle during weekends and non-weekend days among the 5.5 million Danes. Potential deviations from this weekday pattern in other countries around the world may be helpful for identification of its causes.
A limitation of the study is that the study relied solely on samples collected from patients. Certain subgroups, such as the children below 1 year of age cannot be generalized to the general populations, as these children most likely suffer from severe illness. Another limiting factor is the scarcity of patient characteristics, lacking information about the reason for TG measurement, educational concentration, ethnicity, alcohol consumption, dietary intake, and PA; residual confounding may persist. Moreover, based on the observational nature of the data and the lack of recorded exposures in the present study, no causal relationship can be established. Rather, this comprehensive analytic exploration of a large amount of data and the ensuing discussion of key findings are intended to serve as a starting point to generate hypotheses for future research on this topic. An important and initial question is to what extent the variation in TG during weekdays occurs also in other countries or if it is caused by a specific lifestyle in Denmark during the weekends. However, as TG is a component of the metabolic syndrome and a prevalent outcome measurement used in various areas of research, careful planning of future studies may help to avoid undesirable differences attributed to the day and the time of the day the measurement was obtained.
In conclusion, TG concentrations were higher after the weekend and gradually improved during the weekdays. This variation was consistent across all strata, persisted after multiple adjustments, and was likely not attributed to hemodilution or alcohol consumption. We suggest that, in addition to increased concentration of TG that lasts for a few hours after food intake during the day, alterations in food intake and amounts of PA during the weekend increase TG concentrations to a smaller extent, which tracks into the week. A potential difference in research results due to weekday variation may carry implications for public health and may have major implications for future research practice.
Acknowledgments
The authors thank the laboratories and hospital staff for the provision of the enormous amount of data.
Blood cholesterol and vascular mortality by age, sex, and blood pressure: a meta-analysis of individual data from 61 prospective studies with 55,000 vascular deaths.
Moderate alcohol consumption and changes in postprandial lipoproteins of premenopausal and postmenopausal women: a diet-controlled, randomized intervention study.
Efficacy and tolerability of adding prescription omega-3 fatty acids 4 g/d to simvastatin 40 mg/d in hypertriglyceridemic patients: an 8-week, randomized, double-blind, placebo-controlled study.
A single 1-h bout of evening exercise increases basal FFA flux without affecting VLDL-triglyceride and VLDL-apolipoprotein B-100 kinetics in untrained lean men.
Am. J. Physiol. Endocrinol. Metab.2007; 292: E1568-E1574
Exercise of low energy expenditure along with mild energy intake restriction acutely reduces fasting and postprandial triacylglycerolaemia in young women.
Seasonal variation in objectively measured physical activity, sedentary time, cardio-respiratory fitness and sleep duration among 8-11 year-old Danish children: a repeated-measures study.
Fasting is not routinely required for determination of a lipid profile: clinical and laboratory implications including flagging at desirable concentration cut-points–a joint consensus statement from the European Atherosclerosis Society and European Federation of Clinical Chemistry and Laboratory Medicine.