Determinants of Hypertensive treatment adherence among recent stroke survivors

Author

Dr Priscilla Abrafi Opare-Addo

Published

August 5, 2024

Please Note
  • Table 1 was not drawn because it is common for all papers
  • Hillbone was divided as “Low” & “High” when the score was less than or greater than the median
  • Only one person had Afib so it was dropped from the analysis
  • Everyone had hypertension so it was dropped as well
  • Average monthly income cannot be determined so categorized
  • Not sure where to get stroke severity and duration of stroke
  • Morisky was analyzed initially as dichotomized (Table 2) and then as raw scores (Table 4)

General Summary

Show the code 
table_0 <- 
    df_paper_05 %>% 
    select(hillbone, l_forget, l_decide, l_salty, l_shake, l_fasfood,
           l_appoint, l_missched, l_prescrip, l_runout, l_skipmed, 
           l_feelbet, l_feelsick, l_someone, l_careless, a_agebase, 
           a_gender, a_domicile, income, maristat,a_livingsit, educ,
           a_religion, side_effects) %>% 
    gtsummary::tbl_summary(
        statistic = list(
            gtsummary::all_continuous()~"{mean} ({sd})",
            gtsummary::all_categorical()~"{n} ({p})"),
        missing = "no") %>% 
    gtsummary::bold_labels()

Table 1

Show the code 
df_paper_05 %>% 
    filter(!is.na(hillbone_cat)) %>% 
    select(
        hillbone_cat, a_agebase, a_gender, a_domicile, educ, a_poccup3, 
        maristat, income, d_st_type, nihss_scale, bmi, , side_effects,
        tobacco_use, g_alcohol, dm, hyperlipidemia, hosp_cat) %>% 
    gtsummary::tbl_summary(
        by = hillbone_cat,
        statistic = list(
            gtsummary::all_continuous()~"{mean} ({sd})",
            gtsummary::all_categorical()~"{n} ({p})"),
        missing = "no",
        digits = list(gtsummary::all_categorical() ~ c(0,1))
        ) %>% 
    gtsummary::add_overall(last=TRUE) %>% 
    gtsummary::add_p(
        pvalue_fun = ~gtsummary::style_pvalue(.x, digits = 3)) %>% 
    gtsummary::bold_labels()%>% 
    gtsummary::bold_p() %>% 
    gtsummary::modify_caption(
        "**Table 1**: Sociodemographic and clinical characteristics 
        by treatment adherence status (Hillbone)")
Table 1: Sociodemographic and clinical characteristics by treatment adherence status (Hillbone)
Characteristic High, N = 2941 Low, N = 1971 Overall, N = 4911 p-value2
Age in years 59 (12) 57 (10) 58 (12) 0.005
Gender


0.348
    Male 159 (54.1) 115 (58.4) 274 (55.8)
    Female 135 (45.9) 82 (41.6) 217 (44.2)
Domicile


0.132
    Rural 14 (4.8) 18 (9.1) 32 (6.5)
    Semi-Urban 103 (35.0) 61 (31.0) 164 (33.4)
    Urban 177 (60.2) 118 (59.9) 295 (60.1)
Educational Status


0.002
    None 35 (11.9) 13 (6.6) 48 (9.8)
    Primary 129 (43.9) 74 (37.6) 203 (41.3)
    Secondary 78 (26.5) 84 (42.6) 162 (33.0)
    Tertiary 52 (17.7) 26 (13.2) 78 (15.9)
Primary Occupation


<0.001
    Skilled 142 (48.3) 89 (45.2) 231 (47.0)
    Manual 43 (14.6) 65 (33.0) 108 (22.0)
    Others 11 (3.7) 9 (4.6) 20 (4.1)
    Retired 42 (14.3) 15 (7.6) 57 (11.6)
    Unemployed 56 (19.0) 19 (9.6) 75 (15.3)
Marital Status


0.386
    Currently Married 191 (65.0) 137 (69.5) 328 (66.8)
    Previously Married 91 (31.0) 50 (25.4) 141 (28.7)
    Never Married 12 (4.1) 10 (5.1) 22 (4.5)
Income in GHC


0.004
    0-100 92 (31.6) 81 (41.3) 173 (35.5)
    101-250 95 (32.6) 50 (25.5) 145 (29.8)
    251-500 74 (25.4) 32 (16.3) 106 (21.8)
    >500 30 (10.3) 33 (16.8) 63 (12.9)
Stroke Type (Choose One)


0.215
    Ischemic Stroke 193 (76.0) 120 (70.2) 313 (73.6)
    Intracerebral Hemorrhagic Stroke 55 (21.7) 42 (24.6) 97 (22.8)
    Ischemic With Hemorrhagic Transformation 5 (2.0) 5 (2.9) 10 (2.4)
    Untyped Stroke (no CT scan available) 1 (0.4) 4 (2.3) 5 (1.2)
NIH Stroke Scale 4.6 (5.3) 4.8 (5.3) 4.7 (5.3) 0.398
Body Mass Index 26.4 (5.8) 27.0 (5.1) 26.6 (5.5) 0.145
No. of Side Effects 1 (2) 2 (2) 2 (2) <0.001
History of tobacco use 23 (7.9) 22 (11.7) 45 (9.4) 0.164
Alcohol use


0.330
    Never used alcohol 183 (62.2) 103 (52.6) 286 (58.4)
    Currently uses alcohol 30 (10.2) 22 (11.2) 52 (10.6)
    Past 12 months 5 (1.7) 6 (3.1) 11 (2.2)
    Past 30 days 3 (1.0) 4 (2.0) 7 (1.4)
    Formerly used alcohol 59 (20.1) 49 (25.0) 108 (22.0)
    Stopped after the stroke occured 14 (4.8) 12 (6.1) 26 (5.3)
Diabetes Mellitus 103 (35.0) 64 (32.5) 167 (34.0) 0.559
Hyperlipidemia 93 (31.6) 65 (33.0) 158 (32.2) 0.751
Health institution category


<0.001
    Primary 87 (29.6) 61 (31.0) 148 (30.1)
    Secondary 41 (13.9) 75 (38.1) 116 (23.6)
    Tertiary 166 (56.5) 61 (31.0) 227 (46.2)
1 Mean (SD); n (%)
2 Wilcoxon rank sum test; Pearson’s Chi-squared test; Fisher’s exact test

Table 2

Show the code 
df_paper_05 %>% 
    filter(!is.na(morisky_4_cat)) %>% 
    select(
        morisky_4_cat, a_agebase, a_gender, a_domicile, educ, a_poccup3, 
        maristat, income, d_st_type, nihss_scale, bmi, tobacco_use, hosp_cat, 
        g_alcohol, dm, hyperlipidemia, o_headache_new:o_impotence_new, 
        side_effects) %>% 
    gtsummary::tbl_summary(
        by = morisky_4_cat,
        statistic = list(
            gtsummary::all_continuous()~"{mean} ({sd})",
            gtsummary::all_categorical()~"{n} ({p})"),
        missing = "no",
        digits = list(gtsummary::all_categorical() ~ c(0,1))
        ) %>% 
    gtsummary::add_overall(last=TRUE) %>% 
    gtsummary::add_p(
        pvalue_fun = ~gtsummary::style_pvalue(.x, digits = 3)) %>% 
    gtsummary::bold_labels() %>% 
    gtsummary::bold_p() %>% 
    gtsummary::modify_caption(
        "**Table 2**: Factors associated with medication adherence: 
        Morisky medication adherence scale dichotomized as  1-7 
        (Low) or 8 (High))")
Table 2: Factors associated with medication adherence: Morisky medication adherence scale dichotomized as 1-7 (Low) or 8 (High))
Characteristic High, N = 3281 Low, N = 1711 Overall, N = 4991 p-value2
Age in years 58 (12) 58 (11) 58 (12) 0.601
Gender


0.278
    Male 179 (54.6) 102 (59.6) 281 (56.3)
    Female 149 (45.4) 69 (40.4) 218 (43.7)
Domicile


0.456
    Rural 23 (7.0) 10 (5.8) 33 (6.6)
    Semi-Urban 103 (31.4) 63 (36.8) 166 (33.3)
    Urban 202 (61.6) 98 (57.3) 300 (60.1)
Educational Status


0.097
    None 39 (11.9) 10 (5.8) 49 (9.8)
    Primary 130 (39.6) 73 (42.7) 203 (40.7)
    Secondary 101 (30.8) 63 (36.8) 164 (32.9)
    Tertiary 58 (17.7) 25 (14.6) 83 (16.6)
Primary Occupation


<0.001
    Skilled 182 (55.5) 55 (32.2) 237 (47.5)
    Manual 55 (16.8) 53 (31.0) 108 (21.6)
    Others 14 (4.3) 6 (3.5) 20 (4.0)
    Retired 40 (12.2) 18 (10.5) 58 (11.6)
    Unemployed 37 (11.3) 39 (22.8) 76 (15.2)
Marital Status


0.494
    Currently Married 217 (66.2) 116 (67.8) 333 (66.7)
    Previously Married 98 (29.9) 45 (26.3) 143 (28.7)
    Never Married 13 (4.0) 10 (5.8) 23 (4.6)
Income in GHC


<0.001
    0-100 86 (26.5) 88 (51.8) 174 (35.2)
    101-250 111 (34.2) 38 (22.4) 149 (30.1)
    251-500 88 (27.1) 21 (12.4) 109 (22.0)
    >500 40 (12.3) 23 (13.5) 63 (12.7)
Stroke Type (Choose One)


0.268
    Ischemic Stroke 196 (70.8) 122 (78.2) 318 (73.4)
    Intracerebral Hemorrhagic Stroke 72 (26.0) 28 (17.9) 100 (23.1)
    Ischemic With Hemorrhagic Transformation 6 (2.2) 4 (2.6) 10 (2.3)
    Untyped Stroke (no CT scan available) 3 (1.1) 2 (1.3) 5 (1.2)
NIH Stroke Scale 3.7 (4.8) 6.5 (5.8) 4.7 (5.3) <0.001
Body Mass Index 26.5 (5.7) 26.7 (5.1) 26.6 (5.5) 0.705
History of tobacco use 28 (8.8) 17 (10.1) 45 (9.3) 0.657
Health institution category


<0.001
    Primary 83 (25.3) 65 (38.0) 148 (29.7)
    Secondary 53 (16.2) 65 (38.0) 118 (23.6)
    Tertiary 192 (58.5) 41 (24.0) 233 (46.7)
Alcohol use


0.566
    Never used alcohol 201 (61.5) 92 (53.8) 293 (58.8)
    Currently uses alcohol 34 (10.4) 18 (10.5) 52 (10.4)
    Past 12 months 7 (2.1) 4 (2.3) 11 (2.2)
    Past 30 days 5 (1.5) 2 (1.2) 7 (1.4)
    Formerly used alcohol 64 (19.6) 45 (26.3) 109 (21.9)
    Stopped after the stroke occured 16 (4.9) 10 (5.8) 26 (5.2)
Diabetes Mellitus 110 (33.5) 58 (33.9) 168 (33.7) 0.932
Hyperlipidemia 98 (29.9) 62 (36.3) 160 (32.1) 0.147
Headache 47 (14.3) 38 (22.2) 85 (17.0) 0.026
Dizziness 39 (11.9) 19 (11.1) 58 (11.6) 0.797
Thirst/ dry mouth 20 (6.1) 24 (14.0) 44 (8.8) 0.003
Edema 22 (6.7) 6 (3.5) 28 (5.6) 0.141
Cold hands or feet 3 (0.9) 6 (3.5) 9 (1.8) 0.069
Flush 9 (2.7) 5 (2.9) 14 (2.8) >0.999
Fatigue 53 (16.2) 41 (24.0) 94 (18.8) 0.034
Cough 15 (4.6) 6 (3.5) 21 (4.2) 0.574
Palpitations 20 (6.1) 18 (10.5) 38 (7.6) 0.077
Nausea/ indigestion/ vomiting 7 (2.1) 8 (4.7) 15 (3.0) 0.114
Change in bowel habit 23 (7.0) 7 (4.1) 30 (6.0) 0.193
Drowsiness 12 (3.7) 12 (7.0) 24 (4.8) 0.096
Insomnia 28 (8.5) 19 (11.1) 47 (9.4) 0.350
Dreams/Nightmares 9 (2.7) 3 (1.8) 12 (2.4) 0.759
Frequency of micturition 64 (19.5) 36 (21.1) 100 (20.0) 0.683
Dark Urine/Oliguria 3 (0.9) 7 (4.1) 10 (2.0) 0.036
Depression 15 (4.6) 18 (10.5) 33 (6.6) 0.011
Anxiety 20 (6.1) 8 (4.7) 28 (5.6) 0.513
Decreased libido 38 (11.6) 25 (14.6) 63 (12.6) 0.333
Erectile Dysfunction 9 (2.7) 5 (2.9) 14 (2.8) >0.999
No. of Side Effects 1 (2) 2 (2) 2 (2) 0.042
1 Mean (SD); n (%)
2 Wilcoxon rank sum test; Pearson’s Chi-squared test; Fisher’s exact test

Table 3

Show the code 
table_hillbone_crude <- 
    df_paper_05 %>% 
    select(
        hillbone, a_agebase, a_gender, a_domicile, educ, a_poccup3, 
        maristat, income, d_st_type, nihss_scale, bmi, tobacco_use, 
        g_alcohol, dm, hyperlipidemia, hosp_cat, side_effects) %>% 
    tbl_uvregression(
        y = hillbone, 
        method = lm,
        pvalue_fun = function(x) style_pvalue(x, digits = 3)) %>% 
    bold_labels() %>% 
    add_global_p() %>% 
    bold_p(t = 0.1)

table_hillbone_adj <- 
    df_paper_05 %>% 
    select(hillbone, a_agebase, educ, a_poccup3, income, g_alcohol, 
           hosp_cat, side_effects, a_gender) %>% 
    glm(hillbone ~ ., data = .) %>%
    tbl_regression(
        pvalue_fun = function(x) style_pvalue(x, digits = 3)) %>% 
    bold_labels() %>% 
    bold_p()

tbl_merge(
    list(table_hillbone_crude, table_hillbone_adj),
    tab_spanner = c("**Univariate**", "**Multivariate**")) %>%    
    modify_caption(
        caption = "**Table 3**:Univartiate and multivariate linear 
        regression for Hillbone")
Table 3:Univartiate and multivariate linear regression for Hillbone
Characteristic Univariate Multivariate
N Beta 95% CI1 p-value Beta 95% CI1 p-value
Age in years 491 0.04 0.01, 0.07 0.014 0.03 -0.01, 0.06 0.120
Gender 491

0.087


    Male
— —
— —
    Female
0.63 -0.09, 1.4
0.32 -0.45, 1.1 0.412
Domicile 491

0.171


    Rural
— —



    Semi-Urban
0.87 -0.67, 2.4



    Urban
1.3 -0.19, 2.8



Educational Status 491

0.004


    None
— —
— —
    Primary
-0.95 -2.2, 0.33
-0.60 -1.8, 0.62 0.336
    Secondary
-2.0 -3.3, -0.74
-1.5 -2.8, -0.23 0.022
    Tertiary
-0.64 -2.1, 0.82
-0.66 -2.2, 0.87 0.399
Primary Occupation 491

<0.001


    Skilled
— —
— —
    Manual
-1.8 -2.8, -0.94
-1.6 -2.5, -0.66 <0.001
    Others
-0.58 -2.4, 1.2
-0.27 -2.2, 1.6 0.776
    Retired
0.83 -0.33, 2.0
0.45 -0.75, 1.6 0.465
    Unemployed
1.0 -0.01, 2.1
0.46 -0.68, 1.6 0.430
Marital Status 491

0.381


    Currently Married
— —



    Previously Married
0.54 -0.27, 1.3



    Never Married
-0.26 -2.0, 1.5



Income in GHC 487

0.010


    0-100
— —
— —
    101-250
0.81 -0.09, 1.7
0.18 -0.75, 1.1 0.709
    251-500
1.4 0.40, 2.4
0.68 -0.38, 1.7 0.209
    >500
-0.39 -1.6, 0.78
0.03 -1.2, 1.2 0.966
Stroke Type (Choose One) 425

0.153


    Ischemic Stroke
— —



    Intracerebral Hemorrhagic Stroke
-0.50 -1.4, 0.41



    Ischemic With Hemorrhagic Transformation
-1.7 -4.2, 0.84



    Untyped Stroke (no CT scan available)
-3.1 -6.6, 0.46



NIH Stroke Scale 479 -0.03 -0.10, 0.03 0.332


Body Mass Index 471 -0.03 -0.09, 0.04 0.442


History of tobacco use 479

0.221


    No
— —



    Yes
-0.78 -2.0, 0.47



Alcohol use 490

0.022


    Never used alcohol
— —
— —
    Currently uses alcohol
-0.19 -1.4, 1.0
0.17 -1.0, 1.4 0.772
    Past 12 months
-2.0 -4.5, 0.42
-1.9 -4.3, 0.56 0.131
    Past 30 days
-3.3 -6.3, -0.25
-3.1 -5.9, -0.19 0.037
    Formerly used alcohol
-1.3 -2.2, -0.36
-0.71 -1.6, 0.16 0.109
    Stopped after the stroke occured
-0.75 -2.4, 0.88
0.49 -1.1, 2.1 0.543
Diabetes Mellitus 491

0.666


    No
— —



    Yes
-0.17 -0.93, 0.60



Hyperlipidemia 491

0.865


    No
— —



    Yes
0.07 -0.71, 0.84



Health institution category 491

<0.001


    Primary
— —
— —
    Secondary
-2.2 -3.2, -1.3
-1.9 -2.8, -0.88 <0.001
    Tertiary
0.84 0.03, 1.7
0.50 -0.43, 1.4 0.292
No. of Side Effects 491 -0.32 -0.48, -0.16 <0.001 -0.18 -0.34, -0.01 0.037
1 CI = Confidence Interval

Table 4

Show the code 
table_morisky_crude <- 
    gtsummary::tbl_uvregression(
    df_paper_05,
    include = c(
        morisky_4_raw, a_agebase, a_gender, a_domicile, educ, a_poccup3, 
        maristat, income, d_st_type, nihss_scale, bmi, tobacco_use, hosp_cat,
        g_alcohol, dm, hyperlipidemia, side_effects),
    method = ordinal::clm,
    y = morisky_4_raw,
    exponentiate = TRUE,
    pvalue_fun = ~ gtsummary::style_pvalue(.x, digits = 3),
    add_estimate_to_reference_rows = TRUE,
    hide_n = TRUE,
    tidy_fun = function(x, ...) broom::tidy(x, ..., p.values = TRUE),
    ) %>%
    gtsummary::bold_labels() %>% 
    gtsummary::bold_p() 

table_morisky_adj <- 
    gtsummary::tbl_regression(
    ordinal::clm(
        morisky_4_raw ~ g_alcohol + educ + income + nihss_scale + 
        a_poccup3 + hosp_cat + side_effects, 
        data = df_paper_05), 
        exponentiate=TRUE,
        pvalue_fun = function(x) gtsummary::style_pvalue(x, digits = 3)
        ) %>% 
    gtsummary::bold_p() %>% 
    gtsummary::bold_labels()

tbl_merge(
    list(table_morisky_crude, table_morisky_adj),
    tab_spanner = c("**Univariate**", "**Multivariate**")) %>%    
    modify_caption(
        caption = "**Table 4**:Univartiate and multivariate Ordinal logistic 
        regression for Morisky")
Table 4:Univartiate and multivariate Ordinal logistic regression for Morisky
Characteristic Univariate Multivariate
OR1 95% CI1 p-value OR1 95% CI1 p-value
Domicile





    Rural 1.00 —



    Semi-Urban 0.78 0.34, 1.69 0.545


    Urban 1.00 0.44, 2.11 0.992


Age in years 1.00 0.99, 1.02 0.683


Gender





    Male 1.00 —



    Female 1.23 0.85, 1.78 0.269


Stroke Type (Choose One)





    Ischemic Stroke 1.00 —



    Intracerebral Hemorrhagic Stroke 1.42 0.88, 2.34 0.159


    Ischemic With Hemorrhagic Transformation 1.06 0.33, 4.02 0.926


    Untyped Stroke (no CT scan available) 0.95 0.19, 7.00 0.957


Alcohol use





    Never used alcohol 1.00 —
— —
    Currently uses alcohol 0.82 0.45, 1.55 0.534 0.50 0.25, 1.01 0.050
    Past 12 months 0.64 0.19, 2.51 0.486 0.44 0.12, 1.89 0.240
    Past 30 days 1.31 0.30, 9.00 0.742 1.23 0.26, 8.95 0.807
    Formerly used alcohol 0.61 0.39, 0.95 0.027 0.68 0.41, 1.13 0.134
    Stopped after the stroke occured 0.78 0.36, 1.79 0.538 1.48 0.62, 3.81 0.394
Educational Status





    None 1.00 —
— —
    Primary 0.49 0.22, 1.00 0.061 0.38 0.15, 0.85 0.024
    Secondary 0.40 0.18, 0.83 0.019 0.19 0.08, 0.45 <0.001
    Tertiary 0.61 0.25, 1.36 0.237 0.18 0.06, 0.49 0.001
Income in GHC





    0-100 1.00 —
— —
    101-250 2.59 1.64, 4.13 <0.001 1.95 1.14, 3.35 0.015
    251-500 3.78 2.22, 6.69 <0.001 3.51 1.77, 7.19 <0.001
    >500 1.50 0.86, 2.70 0.163 2.10 1.05, 4.29 0.038
Marital Status





    Currently Married 1.00 —



    Previously Married 1.13 0.75, 1.71 0.566


    Never Married 0.60 0.26, 1.42 0.228


Diabetes Mellitus





    No 1.00 —



    Yes 0.98 0.67, 1.43 0.899


Hyperlipidemia





    No 1.00 —



    Yes 0.81 0.55, 1.18 0.263


Body Mass Index 1.0 0.96, 1.03 0.757


History of tobacco use





    No 1.00 —



    Yes 0.90 0.50, 1.70 0.743


NIH Stroke Scale 0.91 0.88, 0.95 <0.001 0.97 0.93, 1.01 0.091
Health institution category





    Primary 1.00 —
— —
    Secondary 0.53 0.34, 0.84 0.007 0.52 0.31, 0.88 0.015
    Tertiary 3.20 2.04, 5.08 <0.001 1.89 1.05, 3.38 0.033
Primary Occupation





    Skilled 1.00 —
— —
    Manual 0.32 0.20, 0.52 <0.001 0.27 0.15, 0.48 <0.001
    Others 0.69 0.27, 2.01 0.460 1.03 0.36, 3.28 0.959
    Retired 0.76 0.41, 1.44 0.385 0.53 0.27, 1.09 0.079
    Unemployed 0.39 0.24, 0.65 <0.001 0.40 0.21, 0.76 0.005
No. of Side Effects 0.89 0.83, 0.97 0.005 0.96 0.87, 1.05 0.330
1 OR = Odds Ratio, CI = Confidence Interval