Heart-Failure-Paper-Two

Data Preparation

Code

df_hf <- 
    dget(file = "./Heart Failure/new_registry_data_clean")


df_for_hf_paper_two <- 
    df_hf %>% 
    select(
        tot_chol, ldl_chol, hdl_chol, trigly , age, 
        heart_failure_phenotype, blood_pressure_systolic_mm_hg, 
        blood_pressure_diastolic_mm_hg, gender, rbs, hba1c,
        dx_hhd, dx_arrhythmia, dx_cad, dx_rhd, dx_inf_endo, dx_chd, 
        dx_emf, dx_cor_pulmonale, dx_pericard, dx_pulm_emboli, 
        dx_dcm, dx_other) %>% 
    mutate(
        tot_chol_cat = case_when(
            tot_chol < 6.2 ~ "Normal", tot_chol >= 6.2 ~ "High") %>% 
            factor(levels = c("Normal", "High")),
        ldl_chol_cat = case_when(
            ldl_chol < 4.1 ~ "Normal", ldl_chol >= 4.1 ~ "High") %>% 
            factor(levels = c("Normal", "High")),
        hdl_chol_cat = case_when(
            (hdl_chol < 1 &  gender == "Male") ~ "Low", 
            (hdl_chol < 1.3 & gender == "Female") ~ "Low",
            hdl_chol > 1 ~ "Normal") %>% 
            factor(levels = c("Normal", "Low")),
        trigly_cat = case_when(trigly >= 2.3 ~ "High", trigly < 2.3 ~ "Normal") %>% 
            factor(levels = c("Normal", "High")),
        dyslipidemia = case_when(
            tot_chol_cat == "High" ~ "Yes",
            ldl_chol_cat == "High" ~ "Yes",
            hdl_chol_cat == "Low" ~ "Yes",
            trigly_cat   == "High" ~ "Yes",
            TRUE ~ "No"))

df_for_hf_paper_two_reg <- 
    df_for_hf_paper_two %>% 
    mutate(
        across(
            c(tot_chol, ldl_chol, hdl_chol, trigly , 
              age,blood_pressure_systolic_mm_hg, 
              blood_pressure_diastolic_mm_hg, rbs, hba1c),
            .fns = ~scale(.x)))

Summarise all data

Code

gtsummary::theme_gtsummary_eda()

Setting theme "Exploratory Data Analysis"

Code

gtsummary::theme_gtsummary_compact()

Setting theme "Compact"

Code

df_for_hf_paper_two %>% 
    gtsummary::tbl_summary(
        label = list(
            tot_chol_cal = "Total Cholesterol (mmol/L)", 
            ldl_chol_cat = "LDL Cholesterol (mmol/L)", 
            hdl_chol_cat = "HDL Cholesterol (mmol/L)",
            trigly_cat   = "Triglycerides (mmol/L)",
            dyslipidemia = "Dyslipidemia")) %>% 
    gtsummary::bold_labels()

Characteristic	N = 1,133¹
Total Cholesterol (mmol/L)
Median (Q1, Q3)	4.37 (3.30, 5.40)
Mean (SD)	6.86 (21.95)
Min, Max	1.10, 408.00
Unknown	683
LDL Cholesterol (mmol/L)
Median (Q1, Q3)	2.60 (1.79, 3.50)
Mean (SD)	3.76 (9.33)
Min, Max	0.20, 166.00
Unknown	708
HDL Cholesterol (mmol/L)
Median (Q1, Q3)	1.15 (0.80, 1.53)
Mean (SD)	1.68 (3.87)
Min, Max	0.00, 47.95
Unknown	718
Triglycerides (mmol/L)
Median (Q1, Q3)	1.03 (0.78, 1.43)
Mean (SD)	2.46 (10.89)
Min, Max	0.18, 140.00
Unknown	724
Age in years
Median (Q1, Q3)	57 (45, 67)
Mean (SD)	56 (16)
Min, Max	12, 93
Heart Failure Phenotype
HFmrEF	120 (10.6%)
HFpEF	283 (25.0%)
HFrEF	730 (64.4%)
Systolic Blood Pressure (mmHg)
Median (Q1, Q3)	126 (109, 146)
Mean (SD)	130 (29)
Min, Max	70, 270
Unknown	26
Diastolic Blood Pressure (mmHg)
Median (Q1, Q3)	80 (70, 91)
Mean (SD)	82 (18)
Min, Max	20, 186
Unknown	26
Gender
Female	567 (50.0%)
Male	566 (50.0%)
Random Blood Sugar (mmol/L)
Median (Q1, Q3)	7.3 (6.1, 9.4)
Mean (SD)	8.6 (5.5)
Min, Max	0.1, 66.0
Unknown	906
HbA1c (%)
Median (Q1, Q3)	5.90 (5.40, 7.00)
Mean (SD)	7.73 (8.44)
Min, Max	3.80, 97.00
Unknown	860
Hypertensive Heart Disease	599 (52.9%)
Arrhythmia	138 (14.9%)
Unknown	204
Coronary Artery Disease	100 (10.9%)
Unknown	216
Rheumatic valve disease	43 (3.80%)
Infective Endocarditis	9 (0.79%)
Congenital Heart Disease	8 (0.71%)
Unknown	2
EMF	8 (0.71%)
Cor pulmonale	22 (1.94%)
Pericardial disease	21 (1.85%)
Pulmonary Embolism	36 (3.18%)
Dilated Cardiomyopathy	360 (31.8%)
Other HF causes	194 (17.1%)
tot_chol_cat
Normal	386 (85.8%)
High	64 (14.2%)
Unknown	683
LDL Cholesterol (mmol/L)
Normal	359 (84.5%)
High	66 (15.5%)
Unknown	708
HDL Cholesterol (mmol/L)
Normal	210 (51.0%)
Low	202 (49.0%)
Unknown	721
Triglycerides (mmol/L)
Normal	377 (92.2%)
High	32 (7.82%)
Unknown	724
Dyslipidemia	275 (24.3%)
¹ n (%)

Figure 1: Causes of HF with 95%CI

Code

df_for_hf_paper_two %>% 
    select(
        dx_hhd, dx_arrhythmia, dx_cad, dx_rhd, dx_inf_endo, dx_chd, 
        dx_emf, dx_cor_pulmonale, dx_pericard, dx_pulm_emboli, 
        dx_dcm, dx_other) %>% 
    pivot_longer(cols = starts_with("dx")) %>% 
    drop_na(value) %>% 
    group_by(name) %>% 
    reframe(across(value, .fns = ~epiDisplay::ci.binomial(.x == "Yes"))) %>% 
    unnest(value) %>% 
    mutate(
        across(probability:exact.upper95ci, .fns = ~.x*100),
        name = factor(name) %>% 
            fct_recode(
                "Hypertensive Heart Disease" = "dx_hhd" ,
                "Arrhythmia" = "dx_arrhythmia",
                "Coronary Artery Disease" = "dx_cad", 
                "Rheumatic valve disease" = "dx_rhd",
                "Infective Endocarditis" = "dx_inf_endo",
                "Congenital Heart Disease" = "dx_chd",
                "EMF" = "dx_emf",
                "Cor pulmonale"  = "dx_cor_pulmonale",
                "Pericardial disease" = "dx_pericard", 
                "Pulmonary Embolism" = "dx_pulm_emboli",
                "Dilated Cardiomyopathy" = "dx_dcm",
                "Other HF causes" = "dx_other")) %>% 
    ggplot(aes(x = fct_reorder(name,-probability), y = probability)) + 
    geom_bar(stat = "identity", fill = "#75aadb", alpha = 0.6)+
    geom_errorbar(
        aes(ymin = exact.lower95ci, ymax = exact.upper95ci), 
        width = 0.2, color = "#3e6da9")+
    labs(x = NULL, y = "Percentage Prevalence (95%CI)")+
    theme_light()+
    coord_flip()+
    scale_y_continuous(expand = c(0,1))

Table 2: Association between HF aetiology and predictors (continuous)

Code

fxn_one <- function(x){
    df_for_hf_paper_two_reg %>% 
    select(
        tot_chol, ldl_chol, hdl_chol, trigly , age, 
        heart_failure_phenotype,blood_pressure_systolic_mm_hg, 
        blood_pressure_diastolic_mm_hg, gender, rbs, hba1c, all_of(x)
        ) %>% 
    gtsummary::tbl_uvregression(
        method = glm,
        method.args = list(family = binomial),
        y = x,
        exponentiate = TRUE,
        add_estimate_to_reference_rows = FALSE,
        hide_n = TRUE,
        label = list(
            tot_chol = "Total Cholesterol (mmol/L)", 
            ldl_chol = "LDL Cholesterol (mmol/L)", 
            hdl_chol = "HDL Cholesterol (mmol/L)",
            trigly = "Triglycerides (mmol/L)",
            rbs = "Random Blood Sugar (mmol/L)",
            hba1c = "HbA1c (%)",
            blood_pressure_systolic_mm_hg = "Systolic Blood Pressure (mmHg)", 
            blood_pressure_diastolic_mm_hg = "Diastolic Blood Pressure (mmHg)",
            age = "Age in years"))%>%
    gtsummary::bold_labels() %>% 
    gtsummary::bold_p()
}

tbl_hhd <-          fxn_one("dx_hhd")
tbl_dcm <-          fxn_one("dx_dcm")

There was a warning running `tbl_regression()` for variable "tot_chol". See
message below.
! glm.fit: fitted probabilities numerically 0 or 1 occurred and glm.fit: fitted
  probabilities numerically 0 or 1 occurred
There was a warning running `tbl_regression()` for variable "trigly". See
message below.
! glm.fit: fitted probabilities numerically 0 or 1 occurred and glm.fit: fitted
  probabilities numerically 0 or 1 occurred

Code

tbl_arrhythmia <-   fxn_one("dx_arrhythmia")
tbl_cad <-          fxn_one("dx_cad")

gtsummary::tbl_merge( 
    tbls = list(tbl_hhd, tbl_dcm, tbl_arrhythmia, tbl_cad),
    tab_spanner = c(
        "Hypertensive Heart Disease",
        "Dilated Cardiomyopathy",
        "Arrhythmia",
        "Coronary Artery Disease"))

Characteristic	Hypertensive Heart Disease			Dilated Cardiomyopathy			Arrhythmia			Coronary Artery Disease
Characteristic	OR	95% CI	p-value	OR	95% CI	p-value	OR	95% CI	p-value	OR	95% CI	p-value
Total Cholesterol (mmol/L)	1.52	1.01, 3.09	0.13	0.63	0.25, 1.01	0.2	0.93	0.53, 1.18	0.7	1.05	0.75, 1.31	0.6
LDL Cholesterol (mmol/L)	1.15	0.91, 1.73	0.4	0.94	0.64, 1.16	0.6	1.07	0.83, 1.33	0.5	0.99	0.61, 1.24	>0.9
HDL Cholesterol (mmol/L)	1.16	0.93, 1.67	0.3	0.67	0.31, 1.01	0.2	0.71	0.25, 1.10	0.4	1.05	0.68, 1.38	0.7
Triglycerides (mmol/L)	1.19	0.93, 1.93	0.3	0.61	0.14, 1.02	0.3	1.04	0.77, 1.27	0.8	1.42	1.08, 2.17	0.029
Age in years	1.57	1.39, 1.78	<0.001	0.73	0.64, 0.82	<0.001	1.73	1.43, 2.11	<0.001	1.88	1.50, 2.37	<0.001
Heart Failure Phenotype
HFmrEF	—	—		—	—		—	—		—	—
HFpEF	1.53	0.98, 2.38	0.062	0.44	0.23, 0.83	0.010	0.77	0.42, 1.45	0.4	0.26	0.11, 0.57	<0.001
HFrEF	0.55	0.37, 0.81	0.003	3.58	2.23, 6.00	<0.001	0.71	0.41, 1.25	0.2	0.75	0.43, 1.40	0.3
Systolic Blood Pressure (mmHg)	2.26	1.95, 2.64	<0.001	0.53	0.45, 0.61	<0.001	0.86	0.71, 1.04	0.13	0.93	0.74, 1.14	0.5
Diastolic Blood Pressure (mmHg)	1.64	1.44, 1.88	<0.001	0.80	0.70, 0.91	<0.001	0.81	0.67, 0.98	0.038	0.85	0.68, 1.05	0.15
Gender
Female	—	—		—	—		—	—		—	—
Male	1.12	0.88, 1.41	0.4	1.20	0.93, 1.54	0.2	1.64	1.14, 2.38	0.008	1.52	1.00, 2.33	0.051
Random Blood Sugar (mmol/L)	0.96	0.72, 1.26	0.8	0.95	0.69, 1.24	0.7	0.67	0.34, 1.10	0.2	1.53	1.09, 2.36	0.034
HbA1c (%)	1.67	1.04, 4.11	0.14	0.63	0.25, 1.01	0.2	0.83	0.31, 1.22	0.5	0.86	0.38, 1.24	0.6
Abbreviations: CI = Confidence Interval, OR = Odds Ratio

Table 3: Association between HF aetiology and predictors (categorical)

Code

fxn_two <- function(x){
    df_for_hf_paper_two_reg %>% 
    select(
        tot_chol_cat, ldl_chol_cat, hdl_chol_cat, trigly_cat, age, 
        heart_failure_phenotype, blood_pressure_systolic_mm_hg, 
        blood_pressure_diastolic_mm_hg, gender, rbs, hba1c, all_of(x)
        ) %>% 
    gtsummary::tbl_uvregression(
        method = glm,
        method.args = list(family = binomial),
        y = x,
        exponentiate = TRUE,
        add_estimate_to_reference_rows = FALSE,
        hide_n = TRUE,
        label = list(
            tot_chol_cal = "Total Cholesterol (mmol/L)", 
            ldl_chol_cat = "LDL Cholesterol (mmol/L)", 
            hdl_chol_cat = "HDL Cholesterol (mmol/L)",
            trigly_cat = "Triglycerides (mmol/L)",
            rbs = "Random Blood Sugar (mmol/L)",
            hba1c = "HbA1c (%)",
            blood_pressure_systolic_mm_hg = "Systolic Blood Pressure (mmHg)", 
            blood_pressure_diastolic_mm_hg = "Diastolic Blood Pressure (mmHg)",
            age = "Age in years"))%>%
    gtsummary::bold_labels() %>% 
    gtsummary::bold_p()
}

tbl_hhd <-          fxn_two("dx_hhd")
tbl_dcm <-          fxn_two("dx_dcm")
tbl_arrhythmia <-   fxn_two("dx_arrhythmia")
tbl_cad <-          fxn_two("dx_cad")

gtsummary::tbl_merge( 
    tbls = list(tbl_hhd, tbl_dcm, tbl_arrhythmia, tbl_cad),
    tab_spanner = c(
        "Hypertensive Heart Disease",
        "Dilated Cardiomyopathy",
        "Arrhythmia",
        "Coronary Artery Disease"))

Characteristic	Hypertensive Heart Disease			Dilated Cardiomyopathy			Arrhythmia			Coronary Artery Disease
Characteristic	OR	95% CI	p-value	OR	95% CI	p-value	OR	95% CI	p-value	OR	95% CI	p-value
tot_chol_cat
Normal	—	—		—	—		—	—		—	—
High	2.20	1.24, 4.07	0.009	0.66	0.35, 1.20	0.2	0.75	0.31, 1.59	0.5	1.18	0.49, 2.56	0.7
LDL Cholesterol (mmol/L)
Normal	—	—		—	—		—	—		—	—
High	1.52	0.88, 2.70	0.14	1.05	0.58, 1.84	0.9	0.99	0.45, 2.01	>0.9	1.45	0.65, 3.01	0.3
HDL Cholesterol (mmol/L)
Normal	—	—		—	—		—	—		—	—
Low	0.80	0.54, 1.18	0.3	1.50	0.98, 2.30	0.062	1.28	0.75, 2.21	0.4	0.62	0.32, 1.15	0.13
Triglycerides (mmol/L)
Normal	—	—		—	—		—	—		—	—
High	1.76	0.82, 4.12	0.2	0.64	0.25, 1.44	0.3	1.17	0.37, 3.04	0.8	3.24	1.26, 7.78	0.010
Age in years	1.57	1.39, 1.78	<0.001	0.73	0.64, 0.82	<0.001	1.73	1.43, 2.11	<0.001	1.88	1.50, 2.37	<0.001
Heart Failure Phenotype
HFmrEF	—	—		—	—		—	—		—	—
HFpEF	1.53	0.98, 2.38	0.062	0.44	0.23, 0.83	0.010	0.77	0.42, 1.45	0.4	0.26	0.11, 0.57	<0.001
HFrEF	0.55	0.37, 0.81	0.003	3.58	2.23, 6.00	<0.001	0.71	0.41, 1.25	0.2	0.75	0.43, 1.40	0.3
Systolic Blood Pressure (mmHg)	2.26	1.95, 2.64	<0.001	0.53	0.45, 0.61	<0.001	0.86	0.71, 1.04	0.13	0.93	0.74, 1.14	0.5
Diastolic Blood Pressure (mmHg)	1.64	1.44, 1.88	<0.001	0.80	0.70, 0.91	<0.001	0.81	0.67, 0.98	0.038	0.85	0.68, 1.05	0.15
Gender
Female	—	—		—	—		—	—		—	—
Male	1.12	0.88, 1.41	0.4	1.20	0.93, 1.54	0.2	1.64	1.14, 2.38	0.008	1.52	1.00, 2.33	0.051
Random Blood Sugar (mmol/L)	0.96	0.72, 1.26	0.8	0.95	0.69, 1.24	0.7	0.67	0.34, 1.10	0.2	1.53	1.09, 2.36	0.034
HbA1c (%)	1.67	1.04, 4.11	0.14	0.63	0.25, 1.01	0.2	0.83	0.31, 1.22	0.5	0.86	0.38, 1.24	0.6
Abbreviations: CI = Confidence Interval, OR = Odds Ratio

Table 4:

Code

df_for_hf_paper_two %>% 
    select(
        heart_failure_phenotype, dx_hhd, dx_arrhythmia, dx_cad, 
        dx_rhd, dx_inf_endo, dx_chd, dx_emf, dx_cor_pulmonale, 
        dx_pericard, dx_pulm_emboli, dx_dcm, dx_other) %>% 
    gtsummary::tbl_summary(
        by = heart_failure_phenotype) %>% 
    gtsummary::add_overall(last = T) %>% 
    gtsummary::add_p() %>% 
    gtsummary::bold_labels() %>% 
    gtsummary::bold_p()

Characteristic	HFmrEF N = 120¹	HFpEF N = 283¹	HFrEF N = 730¹	Overall N = 1,133¹	p-value²
Hypertensive Heart Disease	72 (60.0%)	197 (69.6%)	330 (45.2%)	599 (52.9%)	<0.001
Arrhythmia	19 (18.8%)	36 (15.2%)	83 (14.0%)	138 (14.9%)	0.5
Unknown	19	46	139	204
Coronary Artery Disease	16 (16.0%)	11 (4.66%)	73 (12.6%)	100 (10.9%)	0.001
Unknown	20	47	149	216
Rheumatic valve disease	9 (7.50%)	16 (5.65%)	18 (2.47%)	43 (3.80%)	0.004
Infective Endocarditis	1 (0.83%)	4 (1.41%)	4 (0.55%)	9 (0.79%)	0.3
Congenital Heart Disease	0 (0%)	3 (1.06%)	5 (0.69%)	8 (0.71%)	0.6
Unknown	1	0	1	2
EMF	1 (0.83%)	1 (0.35%)	6 (0.82%)	8 (0.71%)	0.8
Cor pulmonale	4 (3.33%)	14 (4.95%)	4 (0.55%)	22 (1.94%)	<0.001
Pericardial disease	4 (3.33%)	4 (1.41%)	13 (1.78%)	21 (1.85%)	0.4
Pulmonary Embolism	4 (3.33%)	26 (9.19%)	6 (0.82%)	36 (3.18%)	<0.001
Dilated Cardiomyopathy	21 (17.5%)	24 (8.48%)	315 (43.2%)	360 (31.8%)	<0.001
Other HF causes	31 (25.8%)	49 (17.3%)	114 (15.6%)	194 (17.1%)	0.022
¹ n (%)
² Pearson’s Chi-squared test; Fisher’s exact test

Table 5:

Code

gtsummary::reset_gtsummary_theme()
gtsummary::theme_gtsummary_compact()

Setting theme "Compact"

Code

# heart_failure_phenotype, dx_hhd, dx_arrhythmia, dx_cad, 
#         dx_rhd, dx_inf_endo, dx_chd, dx_emf, dx_cor_pulmonale, 
#         dx_pericard, dx_pulm_emboli, dx_dcm, dx_other

fxn_three <- function(x){
    df_for_hf_paper_two %>% 
    select(
        blood_pressure_systolic_mm_hg, gender,
        blood_pressure_diastolic_mm_hg, rbs, hba1c, age,
        tot_chol, ldl_chol, hdl_chol, trigly, all_of(x)
        ) %>% 
#    filter(x == "Yes") %>% 
    droplevels() %>% 
    gtsummary::tbl_summary(
        by = x,
        label = list(
            tot_chol = "Total Cholesterol (mmol/L)", 
            ldl_chol = "LDL Cholesterol (mmol/L)", 
            hdl_chol = "HDL Cholesterol (mmol/L)",
            trigly = "Triglycerides (mmol/L)",
            rbs = "Random Blood Sugar (mmol/L)",
            hba1c = "HbA1c (%)",
            blood_pressure_systolic_mm_hg = "Systolic Blood Pressure (mmHg)", 
            blood_pressure_diastolic_mm_hg = "Diastolic Blood Pressure (mmHg)",
            age = "Age in years",
            gender = "Sex"),
        statistic = gtsummary::all_continuous() ~ "{mean} ({sd})",
        missing = "no")%>%
    gtsummary::bold_labels() 
}

tbl_hhd         <-  fxn_three("dx_hhd")

Warning: Using an external vector in selections was deprecated in tidyselect 1.1.0.
ℹ Please use `all_of()` or `any_of()` instead.
  # Was:
  data %>% select(x)

  # Now:
  data %>% select(all_of(x))

See <https://tidyselect.r-lib.org/reference/faq-external-vector.html>.

Code

tbl_dcm         <-  fxn_three("dx_dcm")
tbl_arrhythmia  <-  fxn_three("dx_arrhythmia")

204 missing rows in the "dx_arrhythmia" column have been removed.

Code

tbl_cad         <-  fxn_three("dx_cad")

216 missing rows in the "dx_cad" column have been removed.

Code

tbl_others      <-  fxn_three("dx_other")

gtsummary::tbl_merge( 
    tbls = list(tbl_hhd, tbl_dcm, tbl_arrhythmia, tbl_cad, tbl_others),
    tab_spanner = c(
        "Hypertensive Heart Disease",
        "Dilated Cardiomyopathy",
        "Arrhythmia",
        "Coronary Artery Disease", 
        "Others"))

Characteristic	Hypertensive Heart Disease		Dilated Cardiomyopathy		Arrhythmia		Coronary Artery Disease		Others
Characteristic	No N = 534¹	Yes N = 599¹	No N = 773¹	Yes N = 360¹	No N = 791¹	Yes N = 138¹	No N = 817¹	Yes N = 100¹	No N = 939¹	Yes N = 194¹
Systolic Blood Pressure (mmHg)	119 (23)	139 (31)	135 (30)	119 (23)	130 (29)	126 (28)	129 (29)	127 (31)	130 (30)	127 (28)
Sex
Female	275 (51%)	292 (49%)	398 (51%)	169 (47%)	412 (52%)	55 (40%)	420 (51%)	41 (41%)	451 (48%)	116 (60%)
Male	259 (49%)	307 (51%)	375 (49%)	191 (53%)	379 (48%)	83 (60%)	397 (49%)	59 (59%)	488 (52%)	78 (40%)
Diastolic Blood Pressure (mmHg)	77 (15)	85 (20)	83 (19)	79 (16)	82 (18)	78 (18)	82 (18)	79 (19)	82 (19)	80 (17)
Random Blood Sugar (mmol/L)	8.7 (6.9)	8.5 (3.6)	8.7 (4.3)	8.4 (6.8)	9.0 (6.2)	7.7 (3.1)	8.4 (3.8)	12.0 (12.3)	8.7 (5.8)	8.1 (3.7)
HbA1c (%)	6.49 (2.42)	8.41 (10.30)	8.22 (9.89)	6.51 (2.07)	7.87 (9.45)	6.83 (2.17)	8.09 (9.80)	7.08 (3.30)	6.78 (3.47)	13.73 (20.41)
Age in years	53 (17)	59 (14)	58 (15)	53 (16)	55 (16)	63 (14)	55 (16)	65 (12)	57 (15)	55 (17)
Total Cholesterol (mmol/L)	4.95 (7.21)	8.22 (28.06)	7.74 (26.02)	4.85 (5.69)	7.55 (26.23)	6.26 (9.36)	6.82 (24.58)	8.52 (14.30)	7.32 (23.97)	4.59 (4.69)
LDL Cholesterol (mmol/L)	3.21 (4.34)	4.12 (11.51)	3.90 (10.56)	3.41 (5.35)	3.78 (10.44)	4.71 (8.53)	4.00 (10.76)	3.87 (5.37)	3.43 (5.12)	5.48 (20.20)
HDL Cholesterol (mmol/L)	1.42 (2.97)	1.87 (4.39)	1.87 (4.49)	1.25 (1.57)	1.86 (4.58)	1.26 (1.33)	1.59 (3.50)	1.77 (2.20)	1.52 (2.98)	2.49 (6.74)
Triglycerides (mmol/L)	1.67 (6.79)	2.98 (12.89)	2.94 (12.93)	1.33 (1.75)	2.56 (12.11)	3.07 (11.17)	1.68 (4.97)	6.43 (22.02)	2.44 (11.15)	2.56 (9.52)
¹ Mean (SD); n (%)