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Bulletin of the World Health Organization logoLink to Bulletin of the World Health Organization
. 2018 Oct 31;97(1):10–23. doi: 10.2471/BLT.18.217000

Multimorbidity and care for hypertension, diabetes and HIV among older adults in rural South Africa

Multimorbidité et traitement de l'hypertension, du diabète et du VIH chez les personnes âgées dans les zones rurales d'Afrique du Sud

Multimorbilidad y atención para la hipertensión, la diabetes y el VIH en los adultos de mayor edad de las zonas rurales de Sudáfrica

تعدد المراضة ورعاية ارتفاع ضغط الدم والسكري وفيروس نقص المناعة البشرية بين كبار السن في المناطق الريفية في جنوب أفريقيا

南非农村地区老年人高血压、糖尿病和人类免疫缺陷病毒 (HIV) 的多重病症和护理

Отягощенность несколькими заболеваниями и медицинская помощь при гипертензии, диабете и ВИЧ у пожилых пациентов в сельских районах Южной Африки

Angela Y Chang a,✉, F Xavier Gómez-Olivé b, Jennifer Manne-Goehler c, Alisha N Wade b, Stephen Tollman, b, Thomas A Gaziano d, Joshua A Salomon e
PMCID: PMC6307505  PMID: 30618461

Abstract

Objective

To examine how multimorbidity might affect progression along the continuum of care among older adults with hypertension, diabetes and human immunodeficiency virus (HIV) infection in rural South Africa.

Methods

We analysed data from 4447 people aged 40 years or older who were enrolled in a longitudinal study in Agincourt sub-district. Household-based interviews were completed between November 2014 and November 2015. For hypertension and diabetes (2813 and 512 people, respectively), we defined concordant conditions as other cardiometabolic conditions, and discordant conditions as mental disorders or HIV infection. For HIV infection (1027 people) we defined any other conditions as discordant. Regression models were fitted to assess the relationship between the type of multimorbidity and progression along the care continuum and the likelihood of patients being in each stage of care for the index condition (four stages from testing to treatment).

Findings

People with hypertension or diabetes plus other cardiometabolic conditions were more like to progress through the care continuum for the index condition than those without cardiometabolic conditions (relative risk, RR: 1.14, 95% confidence interval, CI: 1.09–1.20, and RR: 2.18, 95% CI: 1.52–3.26, respectively). Having discordant comorbidity was associated with greater progression in care for those with hypertension but not diabetes. Those with HIV infection plus cardiometabolic conditions had less progress in the stages of care compared with those without such conditions (RR: 0.86, 95% CI: 0.80–0.92).

Conclusion

Patients with concordant conditions were more likely to progress further along the care continuum, while those with discordant multimorbidity tended not to progress beyond diagnosis.

Introduction

Increases in ageing populations in low- and middle-income countries has contributed to a rising prevalence of multimorbidity, commonly defined as persons with more than one medical condition.1 Previous studies have found that multimorbidity is associated with poorer clinical outcomes,2 higher health expenditure and frequency of service use,3–6 higher use of secondary than primary care,7,8 and higher hospitalization rates among patients.3,6,9

One limitation in the existing literature is that studies of multimorbidity often focus on simple counts of medical conditions. However, different combinations of diseases may affect a person’s health and health care differently. To account for these differences, disease combinations can be categorized as either concordant (similar in risk profile and management) or discordant (not directly related in pathogenesis or management).10 Theoretically, concordant conditions are more likely to be diagnosed and treated along with the index condition, because clinical guidelines often incorporate their interactions. For discordant conditions, however, the competing demands of dealing with different conditions may affect the quality of care provided.11 Previous studies in high-income settings found that patients with diabetes12,13 or hypertension14,15 had higher odds of achieving testing and control goals when they had concordant conditions than discordant conditions. Diabetes patients with discordant conditions, on the other hand, had higher unplanned use of hospital services and specialized care than those with concordant conditions.16

Little is known about the care of patients with human immunodeficiency virus (HIV) and multimorbidity, although studies in the United States of America found that patients with HIV received poorer care for their coexisting conditions than did those without HIV.17–19 Much less is known about how the type of multimorbidity (concordant or discordant) affects a person’s progression along the continuum of care in low- and middle-income countries. Our study aimed to fill this gap by studying the progression along the care continuum among people in South Africa with hypertension, diabetes or HIV infection, all prominent conditions contributing to the complex health transition underway in the country. Furthermore, this study assessed the effect of the type of multimorbidity on HIV care (and not on non-HIV comorbidities) among patients infected with HIV.

Methods

Study design

We analysed cross-sectional data from patients enrolled in the Health and Aging in Africa: a Longitudinal Study of an INDEPTH Community in South Africa. The main study is based the sub-district of Agincourt, in the Bushbuckridge area of Mpumalanga province in South Africa.20 The study enrolled 5059 participants aged 40 years and older. Household-based interviews were completed between November 2014 and November 2015 using a primary survey instrument to collect data about respondents’ demographic profile, medical conditions and economic status. More details on data collection are described elsewhere.21

The study received ethical approvals from the University of the Witwatersrand human research ethics committee, the Mpumalanga province research and ethics committee, and the Harvard T.H. Chan School of Public Health office of human research administration.

Study setting

The Agincourt sub-district has six clinics and two health centres, and there are three district hospitals located 25–60 km from the study site.20,22 Primary health-care services are free of charge and most of out-of-pocket health expenditure for patients is incurred for transport, caregiver costs or private health care.

The Integrated Chronic Disease Management model was recently introduced in South Africa to address several elements of managing multimorbidity, including standardized clinical care based on national treatment protocols, and promotion of disease monitoring and management among patients.23–25 In Agincourt, a patient with any symptom or disease arriving at a local clinic will be received by a nurse who is expected to address all the patient’s needs. Those who visit the clinic primarily for HIV testing are directed to a nearby building staffed by health workers tasked solely with HIV testing. Patients are referred for the same management as other patients only if they are diagnosed as HIV positive.

Definitions

For this analysis, we studied three index conditions: (i) hypertension; (ii) diabetes; and (iii) HIV infection. We defined an index condition as a reference condition for which the continuum of care was evaluated, not as the time sequence in occurrence or diagnosis of multiple conditions.26 For example, for an individual with hypertension plus other conditions, we assigned hypertension as the index condition and evaluated progression along the continuum of care for hypertension in relation to the presence of different types of either concordant or discordant multimorbidity. In addition to the three index conditions, we selected five others as concordant or discordant conditions: (i) dyslipidaemia; (ii) angina; (iii) depression; (iv) post-traumatic stress disorder; and (v) alcohol dependence. We ascertained the presence of the medical conditions based on the clinical diagnosis or clear clinical criteria (Box 1). We selected the medical conditions according to the data that were available in the main study, described in detail elsewhere.31

Box 1. Definitions of conditions in the study of multimorbidity and the care continuum in Agincourt sub-district, South Africa.

Index conditions

Hypertension was defined as either mean systolic blood pressure ≥ 140 mmHg and mean diastolic blood pressure ≥ 90 mmHg or patients’ self-report of receiving current treatment.

Diabetes was defined as fasting blood glucose ≥ 126 mg/dL (defined as patients whose last meal was > 8 hours before specimen collection), non-fasting blood glucose ≥ 200 mg/dL or self-reported current treatment.

Human immunodeficiency virus (HIV) status was ascertained either from collected dried blood spots that showed HIV infection or exposure to antiretroviral therapy or self-reported disease status.

Concordant and discordant conditions

Dyslipidaemia was one of the following criteria: self-reported disease status; elevated total cholesterol (≥ 6.21 mmol/L); low high-density lipoprotein cholesterol (1.19 mmol/L); elevated low-density lipoprotein cholesterol (> 4.10 mmol/L); elevated triglycerides (> 2.25 mmol/L).

Angina was diagnosed using the Rose chest pain questionnaire.27

Depression was defined as three or more symptoms of depression on the Center for Epidemiological Studies depression scale 8-item questionnaire.28

Post-traumatic stress disorder was diagnosed as four or more symptoms on a seven-symptom screening scale.29

Alcohol dependence was defined using the CAGE questionnaire.30

We determined concordance and discordance based on the risk factors and multimorbidities for diagnosis and treatment in the South African national guidelines for hypertension and diabetes.32–34 We found no definition of concordant diseases beyond opportunistic infections in the national HIV guidelines. For people with hypertension, we categorized other cardiometabolic conditions (dyslipidaemia, diabetes and angina) as concordant conditions, and mental disorders (depression, post-traumatic stress disorder and alcohol dependence) and HIV infection as discordant. Similarly, for people with diabetes, we classified other cardiometabolic conditions (hypertension, dyslipidaemia and angina) as concordant conditions, and mental disorders and HIV infection as discordant. For people with HIV, we considered any of the other conditions as discordant.

We defined the continuum of care for each index condition by four sequential stages of care for a patient: being tested for the disease (stage 1), knowing his or her diagnosis (stage 2), ever being initiated on treatment (stage 3) and currently being retained on treatment (stage 4). For hypertension and diabetes, the stage reached was determined from a patient’s self-reporting. For HIV, we relied on both self-reported status and blood test results to determine progression. Patients with dried blood-spot results that showed exposure to antiretroviral therapy (ART) were considered to have reached the treatment stage and all preceding stages, even if they self-reported otherwise.

Statistical analyses

We first conducted descriptive analyses of the prevalence of the three index conditions as well as the prevalence of concordant and discordant conditions by key sociodemographic covariates. Next, we constructed a count variable for each index condition to signify how many stages each respondent with that index condition had advanced along the corresponding continuum of care for that index condition, with a minimum count of zero and maximum of four.

We fitted quasi-Poisson regression models to analyse the relationship between the number of stages respondents reached in the continuum of care and the type of multimorbidity. We used a series of logistic regression models to estimate the odds ratio (OR) and 95% confidence interval (CI) for associations between either concordant or discordant multimorbidities and the odds of advancing to each stage of the care continuum, conditional on having reached the previous stage. In the case of diagnosis, the logistic regression modelled the unconditional odds. We adjusted all regression models for sociodemographic covariates, including age, sex, education, country of origin, marital status, household size, employment status, having limitations in activities of daily living and wealth (measured in quintiles based on household asset ownership) and synthesized these using standard methods.35

All analyses were conducted in R software version 3.3.1 (R Foundation for Statistical Computing, Vienna, Austria).

Results

Complete data on disease prevalence and continuum of care were available for 4447 respondents (88% of the whole sample of 5059). We excluded 135 people due to missing data about disease status of at least one disease category and 477 people due to missing dried blood-spot samples.

Table 1 shows the prevalence of hypertension (63%, 2813 people), diabetes (12%, 512 people) and HIV (23%, 1027 people) as well as the prevalence of concordant and discordant conditions by sociodemographic covariates. Among patients with hypertension, 1535 (55%) had one or more additional cardiometabolic condition, 615 (22%) had one or more mental disorder and 480 (17%) were HIV positive. Among those with diabetes, 465 (91%) patients had other cardiometabolic conditions, 139 (27%) had mental disorders and 77 (15%) were HIV positive. Among patients with HIV infection, 728 (71%) presented with cardiometabolic conditions and 181 (18%) with mental disorders. Reflecting the wider population profile, people with HIV tended to be younger, poorer, in employment and separated from partners compared with those with hypertension and diabetes.

Table 1. Prevalence of concordant and discordant multimorbidity and sociodemographic profile of patients with hypertension, diabetes and HIV infection in Agincourt sub-district, South Africa, November 2014 to November 2015 .

Variable Index condition, no. (%) of people
Hypertension Diabetes HIV infection
Total 2813 (100) 512 (100) 1027 (100)
Other conditions
Cardiometabolic conditionsa (excluding index condition) 1535 (55) 465 (91) 728 (71)
Mental disordersb 615 (22) 139 (27) 181 (18)
HIV infection 480 (17) 77 (15) NA
Age group, years    
40–49 353 (13) 45 (9) 306 (30)
50–59 757 (27) 125 (24) 382 (37)
60–69 801 (28) 165 (32) 237 (23)
70–79 554 (20) 116 (23) 89 (9)
80+ 348 (12) 61 (12) 13 (1)
Sex
Male 1194 (42) 214 (42) 472 (46)
Female 1619 (58) 298 (58) 555 (54)
Education
No formal education 1333 (47) 217 (42) 419 (41)
Some primary education (1–7 years) 987 (35) 208 (41) 360 (35)
Some secondary education (8–11 years) 294 (10) 46 (9) 160 (16)
Completed secondary (12+ years) 199 (7) 41 (8) 88 (9)
Country of origin
South Africa 1998 (71) 408 (80) 672 (65)
Mozambique or other 815 (29) 104 (20) 355 (35)
Marital status
Never married 96 (3) 19 (4) 75 (7)
Currently married or living with partner 1457 (52) 269 (53) 409 (40)
Separated or divorced 350 (12) 54 (11) 207 (20)
Widowed 910 (32) 170 (33) 336 (33)
Household size
Living alone 281 (10) 49 (10) 152 (15)
Living with 1 other person 297 (11) 57 (11) 107 (10)
Living in 3–6 people household 1348 (48) 245 (48) 481 (47)
Living in 7+ people household 887 (32) 161 (31) 287 (28)
Employment status
Employed part- or full-time 397 (14) 61 (12) 220 (21)
Other 2416 (86) 451 (88) 807 (79)
Has limitations in activities of daily living
No 2558 (91) 444 (87) 964 (94)
Yes 255 (9) 68 (13) 63 (6)
Wealth index
Quintile 1 (poorest) 527 (19) 62 (12) 253 (25)
Quintile 2 545 (19) 84 (16) 206 (20)
Quintile 3 542 (19) 105 (21) 213 (21)
Quintile 4 600 (21) 121 (24) 195 (19)
Quintile 5 (richest) 599 (21) 140 (27) 160 (16)
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CI: confidence interval; HIV: human immunodeficiency virus; NA not applicable.

a Dyslipidaemia, angina, hypertension, diabetes.

b Depression, post-traumatic stress disorder, alcohol dependence.

Notes: These data are based on a total of 4447 people who were tested for the index conditions during the household interview. Inconsistencies arise in some values due to rounding.

Continuum of care

Table 2 shows the number of patients reaching each stage of care for each index condition by sociodemographic covariates. The mean number of stages reached in the care continuum (maximum 4) were 2.44 (standard deviation, SD: 1.50) for hypertension, 2.29 (SD: 1.67) for diabetes and 2.99 (SD: 1.54) for HIV infection. People with hypertension or diabetes plus other cardiometabolic (i.e. concordant) conditions were more likely to proceed further along the care continuum for the index condition than those without cardiometabolic conditions (relative risk, RR: 1.14; 95% CI: 1.09–1.20 and RR: 2.18; 95% CI: 1.52–3.26 respectively; Table 3; Fig. 1). Patients with hypertension and discordant conditions were also more likely to progress further in hypertension care (RR: 1.10; 95% CI: 1.04–1.16 for mental disorders and RR: 1.08; 95% CI: 1.01–1.15 for HIV infection), but those with diabetes were not. Other covariates that were associated with the progression of care among people with hypertension included being older or female, having limitations in activities of daily living, higher education level, of South African origin and wealthier. For those with HIV infection, having cardiometabolic (i.e. discordant) conditions were associated with less advanced progression in HIV care compared with people without cardiometabolic conditions (RR: 0.86; 95% CI: 0.80–0.92). Other covariates that were associated with the further progression of care included being older, male and living in larger households.

Table 2. Progression through stages in the care continuum, by multimorbidity status and key sociodemographic covariates, among patients with hypertension, diabetes and HIV infection in Agincourt sub-district, South Africa, November 2014 to November 2015.

Variable Index condition by stage of care reached, no. of patients
Hypertension
 Diabetes
 HIV infection
Tested (all patients)a
 Tested (among those with condition)b Know statusb Ever treatedb Currently treatedb Tested (all patients)a Tested (among those with condition)b Know statusb Ever treatedb Currently treatedb Tested (all patients)a Tested (among those with condition)b Know statusb Ever treatedb Currently treatedb
Total observations 4447 2813 2084 1915 1508 4447 512 383 300 252 4447 1027 913 730 703
Reached stage 3116 2084 1915 1508 1115 2138 383 300 252 224 2993 913 730 703 699
Other conditions
Cardiometabolic conditions (excluding index condition) 1600 1252 1122 906 683 1782 369 288 245 219 2361 648 520 495 491
Mental disorders 694 503 493 403 301 470 112 83 68 64 595 163 134 130 129
HIV infection 717 360 326 239 176 473 52 43 37 30 913 913 730 703 699
Age group, years
40–49 506 229 183 107 71 337 27 19 15 15 613 262 205 191 189
50–59 847 546 471 348 247 574 93 75 68 62 946 355 285 276 275
60–69 831 615 576 464 356 590 119 95 74 72 793 216 170 167 166
70–79 582 430 429 363 271 403 96 75 63 49 437 69 62 62 62
80+ 350 264 256 226 170 234 48 36 32 26 204 11 8 7 7
Sex
Male 1361 804 682 512 378 1213 225 170 144 131 1651 486 387 367 364
Female 1755 1280 1233 996 737 925 158 130 108 93 1342 427 343 336 335
Education
No formal education 1454 1002 940 780 578 930 165 128 105 90 1193 365 288 279 277
Some primary (1–7 years of education) 1097 744 695 537 396 785 152 114 100 93 1127 327 267 260 258
Some secondary (8–11 years of education) 349 211 167 120 91 254 32 27 22 20 395 142 111 108 108
Secondary or more (12+ years of education) 216 127 113 71 50 169 34 31 25 21 278 79 64 56 56
Country of origin
South Africa 2174 1491 1404 1112 833 1548 305 241 203 184 2125 601 489 469 467
Mozambique or other 942 593 511 396 282 590 78 59 49 40 868 312 241 234 232
Marital status
Never married 152 61 55 38 28 80 11 11 8 7 159 64 48 45 45
Currently married or living with partner 1591 1069 949 723 531 1120 200 156 132 118 1600 363 293 281 281
Separated or divorced 388 245 214 173 124 276 41 30 24 20 405 191 150 146 145
Widowed 985 709 697 574 432 662 131 103 88 79 829 295 239 231 228
Household size
Living alone 316 187 174 142 106 199 37 29 23 19 295 133 99 97 97
Living with another person 345 234 212 169 120 229 47 37 28 27 331 97 78 73 72
Living with 3–6 persons 1486 977 908 708 525 1040 180 136 120 107 1455 437 355 343 340
Living with 7+ persons 969 686 621 489 364 670 119 98 81 71 912 246 198 190 190
Employment status
Employed part- or full-time 467 265 210 138 97 339 44 36 28 23 554 193 149 142 142
Other 2649 1819 1705 1370 1018 1799 339 264 224 201 2439 720 581 561 557
Has limitations in activities of daily living
No 2779 1858 1698 1304 968 1904 325 249 212 189 2753 849 681 656 652
Yes 337 226 217 204 147 234 58 51 40 35 240 64 49 47 47
Wealth quintile
Quintile 1 (poorest) 613 374 324 251 175 382 45 35 28 26 567 214 171 163 161
Quintile 2 613 403 354 284 203 390 58 45 41 37 578 190 146 142 141
Quintile 3 637 414 380 287 217 425 75 56 47 44 588 186 144 140 140
Quintile 4 610 435 404 329 252 450 95 71 59 48 610 174 149 142 141
Quintile 5 (richest)
 643 458 453 357 268 491 110 93 77 69 650 149 121 116 116
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a This column shows the number of people among the entire sample were tested for the disease by a provider (regardless of whether they had the index condition).

b This column shows the numbers of people with the index condition who reached this care stage.

Table 3. Relative risk for progression through stages in the care continuum, by covariates, among patients with hypertension, diabetes and HIV infection in Agincourt sub-district, South Africa, November 2014 to November 2015.

Variable Index condition
Hypertension Diabetes HIV infection
Total no. of people 2813 512 1027
Mean no. (SD) of stages reached in the care continuuma 2.44 (1.50) 2.29 (1.67) 2.99 (1.54)
RR (95% CI) for progression in care
Other conditions
    Cardiometabolic conditionsb (excluding index condition) 1.14 (1.09–1.20)d 2.18 (1.52–3.26)d 0.86 (0.80–0.92)e
    Mental disordersc 1.10 (1.04–1.16)e 1.02 (0.88–1.19)e 0.99 (0.91–1.08)e
    HIV infection 1.08 (1.01–1.15)e 1.08 (0.89–1.31)e NA
Age group, years
    40–49 Ref. Ref. Ref.
    50–59 1.17 (1.07–1.29) 1.26 (0.94–1.71) 1.10 (1.01–1.21)
    60–69 1.30 (1.18–1.43) 1.23 (0.91–1.68) 1.07 (0.96–1.19)
    70–79 1.42 (1.28–1.57) 1.27 (0.92–1.77) 1.04 (0.90–1.20)
    80+ 1.36 (1.21–1.52) 1.21 (0.84–1.75) 1.00 (0.72–1.37)
Sex
    Male Ref. Ref. Ref.
    Female 1.24 (1.17–1.31) 0.99 (0.85–1.16) 0.92 (0.85–0.99)
Education
    No formal education Ref. Ref. Ref.
    Some primary (1–7 years of education) 0.98 (0.93–1.04) 1.00 (0.85–1.18) 1.06 (0.97–1.16)
    Some secondary (8–11 years of education) 0.90 (0.82–0.99) 1.11 (0.84–1.46) 1.04 (0.92–1.17)
    Secondary or more (12+ years of education) 0.86 (0.76–0.97) 1.19 (0.88–1.58) 1.01 (0.87–1.18)
Country of origin
    South Africa Ref. Ref. Ref.
    Mozambique or other 0.92 (0.87–0.98) 0.95 (0.79–1.14) 0.98 (0.91–1.07)
Marital status
    Never married 0.96 (0.83–1.11) 0.95 (0.62–1.40) 0.94 (0.81–1.08)
    Currently married or living with partner Ref. Ref. Ref.
    Separated or divorced 0.93 (0.86–1.01) 0.93 (0.72–1.19) 1.06 (0.97–1.17)
    Widowed 0.95 (0.90–1.01) 1.02 (0.86–1.22) 1.05 (0.96–1.14)
Household size
    Living alone Ref. Ref. Ref.
    Living with another person 1.06 (0.96–1.18) 1.02 (0.76–1.37) 1.09 (0.95–1.25)
    Living with 3–6 people 1.02 (0.93–1.11) 0.99 (0.77–1.28) 1.17 (1.05–1.30)
    Living with 7+ people 1.03 (0.94–1.13) 1.01 (0.78–1.33) 1.06 (0.95–1.20)
Employment status
    Employed part- or full-time 0.95 (0.88–1.03) 0.98 (0.77–1.23) 0.98 (0.90–1.07)
    Other Ref. Ref. Ref.
Has limitations in activities of daily living
    No Ref. Ref. Ref.
    Yes 1.12 (1.04–1.21) 1.23 (1.01–1.48) 1.11 (0.97–1.26)
Wealth quintile
    Quintile 1 (poorest) Ref. Ref. Ref.
    Quintile 2 1.04 (0.96–1.12) 0.95 (0.74–1.24) 1.05 (0.95–1.16)
    Quintile 3 1.08 (1.00–1.17) 0.96 (0.75–1.23) 1.01 (0.91–1.12)
    Quintile 4 1.09 (1.01–1.18) 0.97 (0.77–1.25) 1.05 (0.94–1.17)
    Quintile 5 (richest) 1.21 (1.11–1.31) 1.02 (0.80–1.32) 1.07 (0.95–1.21)
Constant 1.46 (1.26–1.69) 0.85 (0.48–1.48) 2.78 (2.35–3.28)
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CI: confidence interval; NA: not applicable; Ref.: reference group; RR: relative risk; SD: standard deviation.

a Minimum = 0, maximum = 4. Stage 1: tested; 2: know status; 3 ever treated; 4: currently treated.

b Dyslipidaemia, angina, hypertension, diabetes.

c Depression, post-traumatic stress disorder, alcohol dependence.

d Concordant.

e Discordant.

Note: Dependent variable was progression in the care continuum (number of stages reached by each patient).

Fig. 1.

Association between concordant and discordant multimorbidity and progression in the care continuum for patients in Agincourt sub-district, South Africa, November 2014 to November 2015

CI: confidence interval; HIV: human immunodeficiency virus; RR: relative risk.

Notes: Coefficients from the Poisson regression models are expressed as RRs of progression in the care continuum. Covariates included in the model: age group, sex, education, country of origin, household size, marital status, employment status, having limitations in activities of daily living and wealth quintile. Progression in the care continuum is expressed as number of stages reached, minimum = 0, maximum = 4. Stage 1: tested; 2: know status; 3 ever treated; 4: currently treated.

Fig. 1

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Stages of care reached

Hypertension

Looking more closely at each stage of the continuum, having discordant medical conditions was associated with a higher likelihood of being tested for hypertension. This was true both among the entire sample (OR: 1.32; 95% CI: 1.11–1.57 for patients with mental disorders; OR: 1.20; 95% CI: 1.02–1.42 for those with HIV infection) and those with hypertension (OR: 1.44; 95% CI: 1.15–1.82 with mental disorders; OR: 1.29; 95% CI: 1.01–1.65 with HIV infection; Table 4; Fig. 2). Having mental disorders was also associated with a higher likelihood of being diagnosed with hypertension (OR: 1.52; 95% CI: 1.17–1.99), but was not associated with any of the remaining stages in the care continuum. Having HIV infection was not associated with progress in any stages of care among people with hypertension. In comparison, patients with one or more cardiometabolic (concordant) conditions were more likely to be diagnosed with hypertension (OR: 1.53; 95% CI: 1.24–1.88), ever-treated (OR: 1.52; 95% CI: 1.21–1.92) and currently on treatment (OR: 1.46; 95% CI: 1.08–1.97) for hypertension.

Table 4. Odds of progression through stages in the care continuum for patients with hypertension, diabetes and HIV infection and concordant or discordant multimorbidity in Agincourt sub-district, South Africa, November 2014 to November 2015.
Index condition Stage of care reached
Tested (all patients) Tested (among those with condition) Know status (among those tested) Ever treated (among those who know status) Currently treated (among those ever treated)
Hypertension
No. of observations 4447 2813 2084 1915 1508
aOR (95% CI) of associations with:
    Cardiometabolic conditionsa 1.13 (0.99–1.29) 1.17 (0.98–1.39) 1.53 (1.24–1.88) 1.52 (1.21–1.92) 1.46 (1.08–1.97)
    Mental disordersb 1.32 (1.11–1.57) 1.44 (1.15–1.82) 1.52 (1.17–1.99) 1.22 (0.91–1.64) 1.04 (0.74–1.50)
    HIV infectionb 1.20 (1.02–1.42) 1.29 (1.01–1.65) 1.31 (0.99–1.74) 0.85 (0.63–1.14) 1.26 (0.83–1.95)
Diabetes
No. of observations 4447 512 383 300 252
aOR (95% CI) of associations with:
    Cardiometabolic conditionsa 1.75 (1.51–2.04) 4.20 (2.19–8.19) 3.55 (1.34–9.64) 3.03 (0.67–12.21) 2.88 (0.27–22.57)
    Mental disordersb 1.13 (0.97–1.31) 1.36 (0.82–2.31) 0.76 (0.44–1.33) 0.72 (0.35–1.55) 1.68 (0.57–5.50)
    HIV infectionb 1.10 (0.94–1.28) 1.07 (0.60–1.98) 1.29 (0.62–2.87) 0.81 (0.32–2.18) 0.43 (0.14–1.40)
HIV infection
No. of observations 4447 1027 913 730 703
aOR (95% CI) of associations with:
    Cardiometabolic conditionsb 1.06 (0.90–1.25) 1.03 (0.66–1.58) 0.46 (0.30–0.69) 0.32 (0.09–0.87) 0.00 (NA)
    Mental disordersb 0.99 (0.85–1.17) 1.03 (0.61–1.83) 0.98 (0.64–1.53) 1.20 (0.41–4.44) 0.57 (0.06–12.26)
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aOR: adjusted odds ratio; CI: confidence interval; HIV: human immunodeficiency virus; NA: not applicable.

a Concordant conditions.

b Discordant conditions.

Notes: For hypertension, concordant conditions were other cardiometabolic conditions (dyslipidaemia, diabetes, angina); discordant conditions were mental disorders (depression, post-traumatic stress disorder, alcohol dependence) and HIV infection. For diabetes, concordant conditions were other cardiometabolic conditions (hypertension, dyslipidaemia, angina); discordant conditions were mental disorders (depression, post-traumatic stress disorder, alcohol dependence) and HIV infection. For HIV infection, there were no concordant conditions; discordant conditions were cardiometabolic conditions (hypertension, diabetes, dyslipidaemia and angina) and mental disorders (depression, post-traumatic stress disorder, alcohol dependence). Covariates included in the model: age group, sex, education, country of origin, household size, marital status, employment status, having limitations in activities of daily living, and wealth quintile.

Fig. 2.

Association between concordant and discordant multimorbidity and progression in the continuum of hypertension care for patients with hypertension in Agincourt sub-district, South Africa, November 2014 to November 2015

HIV: human immunodeficiency virus; OR: odds ratio.

Notes: Coefficients from the logistic regression models are expressed as ORs. Covariates included in the model: age group, sex, education, country of origin, household size, marital status, employment status, having limitations in activities of daily living and wealth quintile.

Fig. 2

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Diabetes

The effects of the types of multimorbidity on people with diabetes were greater. Having cardiometabolic (concordant) conditions was associated with higher odds of being tested for diabetes both among the whole sample (OR: 1.75; 95% CI: 1.51–2.04) and those with diabetes (OR: 4.20; 95% CI: 2.19–8.19; Table 4; Fig. 3). Among patients with diabetes, having cardiometabolic conditions was associated with higher odds of knowing their diabetes status (OR: 3.55; 95% CI: 1.34–9.64), but not of being initiated or retained on treatment. Having discordant conditions (mental disorder or HIV infection) was not associated with progression to each stage.

Fig. 3.

Association between concordant and discordant multimorbidity and progression in the continuum of diabetes care for patients with diabetes in Agincourt sub-district, South Africa, November 2014 to November 2015

HIV: human immunodeficiency virus; OR: odds ratio.

Notes: Coefficients from the logistic regression models are expressed as ORs. Covariates included in the model: age group, sex, education, country of origin, household size, marital status, employment status, having limitations in activities of daily living and wealth quintile.

Fig. 3

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HIV infection

In contrast with hypertension and diabetes, having HIV and cardiometabolic (discordant) conditions was associated with worse care for HIV patients. The odds were 54% lower for knowing their HIV status (OR: 0.46; 95% CI: 0.30–0.69) and 68% lower for ever receiving ART (OR: 0.32; 95% CI: 0.09–0.87; Table 4; Fig. 4).

Fig. 4.

Association between concordant and discordant multimorbidity and progression in the continuum of HIV care for patients with HIV infection in Agincourt sub-district, South Africa, November 2014 to November 2015

HIV: human immunodeficiency virus; OR: odds ratio.

Notes: Coefficients from the logistic regression models are expressed ORs. Covariates included in the model: age group, sex, education, country of origin, household size, marital status, employment status, having limitations in activities of daily living and wealth quintile.

Fig. 4

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Data for the adjusted odds ratios for each covariate by stage of care reached are available from the corresponding author.

Discussion

In line with theories and empirical findings from high-income settings,12–14 we found that having concordant conditions was associated with a higher likelihood of progressing further along the continuum of care for hypertension and diabetes in our study population. This may be explained by the emphasis that the South African hypertension guidelines place on diabetes and dyslipidaemia as important comorbidities, and the emphasis on hypertension and dyslipidaemia in the diabetes guidelines.32,33 These guidelines do not give much emphasis to HIV, although both mention it, and neither mention mental disorders. Moreover, providers may be more inclined to treat concordant conditions urgently to reach the target treatment outcomes for the index condition. For example, treating dyslipidaemia in patients may lead to targeting blood pressure control, because of the benefits of preventing the progression of coronary artery diseases.36

On the other hand, having discordant conditions was not associated with worse care progression for hypertension and diabetes, contrary to experience in high-income settings.11,13 Although some studies have shown that mental disorders are associated with poorer progression in care for cardiometabolic conditions,36 we did not find a significant effect. Negative findings were observed only among people with HIV, where the presence of cardiometabolic (discordant) conditions was associated with less progress in HIV care. This is a concerning finding given that both HIV infection and the use of ART have been associated with increased risk of coronary heart disease and myocardial infarction.37,38 Previous studies found lower quality of care for non-HIV conditions among HIV patients.17–19 Factors that may have contributed to those findings include the lack of specific guidelines for HIV patients for treating diseases other than opportunistic infections; prioritization of short-term health needs; and the difficulty of balancing the demands of caring for complex patients with other medical and psychosocial problems.

Comparing across each stage in the continuum of care, both hypertension and diabetes patients with concordant or discordant conditions had a higher likelihood of reaching the first stages of care. This may be due to the lower opportunity costs involved for health-care providers and patients in relation to testing and diagnosis, versus those related to initiation and adherence to treatment. Testing and diagnosing hypertension involve simple procedures with relatively little effort required by providers, and thus the presence of any type of multimorbidity may increase the chance that the patient will be tested. However, the positive effect of discordant diseases may recede as the opportunity cost increases, as is the case for being initiated on and supported to adhere to treatment. More effort is required on the part of the practitioner to determine the right regimen, initiate the treatment, provide counselling on adherence and follow-up regularly to ensure the desired outcomes are met.

Patients who have non-diabetes cardiometabolic conditions may be tested for diabetes, given the overlap in the risk factors, pathophysiological pathways and treatment guidelines. We did not see this positive effect of multimorbidity among people who were HIV-infected, perhaps due to stigma, practitioners’ lower awareness of HIV among older people and the fact HIV testing requires more complex laboratory-based assessment than measuring blood pressure. Furthermore, we suggest that the negative association between HIV care and having cardiometabolic diseases may relate in part to how the clinics in Agincourt are organized. The separate procedure for HIV testing may explain why people with only HIV and no other conditions were more likely to be diagnosed with HIV conditional on being tested since they likely entered the clinic solely for receiving HIV care.

The findings also imply that the objective of the South Africa’s Integrated Chronic Disease Management model may not yet be realized. While not examined empirically in our study, barriers such as long waiting times, staff shortages and drug stock-outs may have negatively impacted the implementation of the management model and resulted in fewer visits made by the patients and shorter consultation times with providers.25 The nurses may not be trained to diagnose or manage all diseases, and, given time constraints, they are often only able to address the patient's chief complaint and, in some cases, the concordant diseases that are listed in the guidelines.25 For nationwide implementation of the integrated chronic disease management model, our findings suggest the need for improvements in leveraging one programme (such as the HIV programme) for scaling-up services for another condition (such as noncommunicable disease services), for example by putting more effort into ensuring patient engagement in stages with higher opportunity costs. There may be potential for benefits through the introduction of programmes, such as the Sustainable East Africa Research in Community Health’s campaign and the United States President’s Emergency Plan for AIDS Relief.39–41 Implementing such joint programmes would make cardiometabolic disease management available alongside HIV services to bring populations with different types of multimorbidity into care.

Our study is subject to several limitations. First, we assessed whether the presence of a concordant or discordant condition was associated with progression in the care continuum, not whether being in care for one disease leads to being in care for another. Due to the cross-sectional nature of this study, we could not determine the time sequencing of the conditions or the care progression. We were also unable to assess causality on which type of multimorbidity affects care progression. Second, while the prevalence of the three index conditions and the concordant and discordant conditions were based on clinical criteria, data on the stages to which people progressed were self-reported, and our results therefore may have over- or underestimated coverage of different services. As the excluded samples were most commonly due to missing HIV measurements (due to patients’ refusal to be tested), it is likely that we have underestimated the prevalence of HIV infection. The HIV prevalence within the sample is similar to the prevalence level found earlier in Agincourt.42 Third, all conditions within the cardiometabolic and mental conditions were weighted equally, whereas it is plausible that specific combinations of diseases are associated with higher likelihood of progressing further along the care continuum. Finally, the study’s comparability with existing studies and generalizability to settings with low HIV prevalence may be limited.

We conclude that the presence of any type of multimorbidity is associated with a higher likelihood of being in stages of care with lower opportunity costs, while the presence of concordant conditions is associated with higher likelihood of being in stages with higher opportunity costs. Our findings from a relatively typical setting in rural South Africa have policy implications for enhancing access to testing and treatment services to improve service coverage and population health in the country. While we could not corroborate causality, further research, informed by forthcoming waves of the main study, will improve our understanding of the impact of different types of multimorbidity on health outcomes and the use of health services.

Funding:

Health and Aging in Africa: a Longitudinal Study of an INDEPTH Community in South Africa was funded by the National Institute on Aging (P01 AG041710) and is nested within the Agincourt Health and Demographic Surveillance System site, supported by the University of the Witwatersrand and Medical Research Council, South Africa, and the Wellcome Trust, United Kingdom of Great Britain and Norther Ireland (grants 058893/Z/99/A; 069683/Z/02/Z; 085477/Z/08/Z; 085477/B/08/Z).

Competing interests:

None declared.

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