Unmet need for hypercholesterolemia care in 35 low- and middle-income countries: A cross-sectional study of nationally representative surveys.


Journal

PLoS medicine
ISSN: 1549-1676
Titre abrégé: PLoS Med
Pays: United States
ID NLM: 101231360

Informations de publication

Date de publication:
10 2021
Historique:
received: 16 04 2021
accepted: 08 10 2021
revised: 08 11 2021
pubmed: 26 10 2021
medline: 15 12 2021
entrez: 25 10 2021
Statut: epublish

Résumé

As the prevalence of hypercholesterolemia is increasing in low- and middle-income countries (LMICs), detailed evidence is urgently needed to guide the response of health systems to this epidemic. This study sought to quantify unmet need for hypercholesterolemia care among adults in 35 LMICs. We pooled individual-level data from 129,040 respondents aged 15 years and older from 35 nationally representative surveys conducted between 2009 and 2018. Hypercholesterolemia care was quantified using cascade of care analyses in the pooled sample and by region, country income group, and country. Hypercholesterolemia was defined as (i) total cholesterol (TC) ≥240 mg/dL or self-reported lipid-lowering medication use and, alternatively, as (ii) low-density lipoprotein cholesterol (LDL-C) ≥160 mg/dL or self-reported lipid-lowering medication use. Stages of the care cascade for hypercholesterolemia were defined as follows: screened (prior to the survey), aware of diagnosis, treated (lifestyle advice and/or medication), and controlled (TC <200 mg/dL or LDL-C <130 mg/dL). We further estimated how age, sex, education, body mass index (BMI), current smoking, having diabetes, and having hypertension are associated with cascade progression using modified Poisson regression models with survey fixed effects. High TC prevalence was 7.1% (95% CI: 6.8% to 7.4%), and high LDL-C prevalence was 7.5% (95% CI: 7.1% to 7.9%). The cascade analysis showed that 43% (95% CI: 40% to 45%) of study participants with high TC and 47% (95% CI: 44% to 50%) with high LDL-C ever had their cholesterol measured prior to the survey. About 31% (95% CI: 29% to 33%) and 36% (95% CI: 33% to 38%) were aware of their diagnosis; 29% (95% CI: 28% to 31%) and 33% (95% CI: 31% to 36%) were treated; 7% (95% CI: 6% to 9%) and 19% (95% CI: 18% to 21%) were controlled. We found substantial heterogeneity in cascade performance across countries and higher performances in upper-middle-income countries and the Eastern Mediterranean, Europe, and Americas. Lipid screening was significantly associated with older age, female sex, higher education, higher BMI, comorbid diagnosis of diabetes, and comorbid diagnosis of hypertension. Awareness of diagnosis was significantly associated with older age, higher BMI, comorbid diagnosis of diabetes, and comorbid diagnosis of hypertension. Lastly, treatment of hypercholesterolemia was significantly associated with comorbid hypertension and diabetes, and control of lipid measures with comorbid diabetes. The main limitations of this study are a potential recall bias in self-reported information on received health services as well as diminished comparability due to varying survey years and varying lipid guideline application across country and clinical settings. Cascade performance was poor across all stages, indicating large unmet need for hypercholesterolemia care in this sample of LMICs-calling for greater policy and research attention toward this cardiovascular disease (CVD) risk factor and highlighting opportunities for improved prevention of CVD.

Sections du résumé

BACKGROUND
As the prevalence of hypercholesterolemia is increasing in low- and middle-income countries (LMICs), detailed evidence is urgently needed to guide the response of health systems to this epidemic. This study sought to quantify unmet need for hypercholesterolemia care among adults in 35 LMICs.
METHODS AND FINDINGS
We pooled individual-level data from 129,040 respondents aged 15 years and older from 35 nationally representative surveys conducted between 2009 and 2018. Hypercholesterolemia care was quantified using cascade of care analyses in the pooled sample and by region, country income group, and country. Hypercholesterolemia was defined as (i) total cholesterol (TC) ≥240 mg/dL or self-reported lipid-lowering medication use and, alternatively, as (ii) low-density lipoprotein cholesterol (LDL-C) ≥160 mg/dL or self-reported lipid-lowering medication use. Stages of the care cascade for hypercholesterolemia were defined as follows: screened (prior to the survey), aware of diagnosis, treated (lifestyle advice and/or medication), and controlled (TC <200 mg/dL or LDL-C <130 mg/dL). We further estimated how age, sex, education, body mass index (BMI), current smoking, having diabetes, and having hypertension are associated with cascade progression using modified Poisson regression models with survey fixed effects. High TC prevalence was 7.1% (95% CI: 6.8% to 7.4%), and high LDL-C prevalence was 7.5% (95% CI: 7.1% to 7.9%). The cascade analysis showed that 43% (95% CI: 40% to 45%) of study participants with high TC and 47% (95% CI: 44% to 50%) with high LDL-C ever had their cholesterol measured prior to the survey. About 31% (95% CI: 29% to 33%) and 36% (95% CI: 33% to 38%) were aware of their diagnosis; 29% (95% CI: 28% to 31%) and 33% (95% CI: 31% to 36%) were treated; 7% (95% CI: 6% to 9%) and 19% (95% CI: 18% to 21%) were controlled. We found substantial heterogeneity in cascade performance across countries and higher performances in upper-middle-income countries and the Eastern Mediterranean, Europe, and Americas. Lipid screening was significantly associated with older age, female sex, higher education, higher BMI, comorbid diagnosis of diabetes, and comorbid diagnosis of hypertension. Awareness of diagnosis was significantly associated with older age, higher BMI, comorbid diagnosis of diabetes, and comorbid diagnosis of hypertension. Lastly, treatment of hypercholesterolemia was significantly associated with comorbid hypertension and diabetes, and control of lipid measures with comorbid diabetes. The main limitations of this study are a potential recall bias in self-reported information on received health services as well as diminished comparability due to varying survey years and varying lipid guideline application across country and clinical settings.
CONCLUSIONS
Cascade performance was poor across all stages, indicating large unmet need for hypercholesterolemia care in this sample of LMICs-calling for greater policy and research attention toward this cardiovascular disease (CVD) risk factor and highlighting opportunities for improved prevention of CVD.

Identifiants

pubmed: 34695124
doi: 10.1371/journal.pmed.1003841
pii: PMEDICINE-D-21-01767
pmc: PMC8575312
doi:

Substances chimiques

Biomarkers 0

Types de publication

Journal Article Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Pagination

e1003841

Subventions

Organisme : NCATS NIH HHS
ID : KL2 TR003143
Pays : United States
Organisme : NIAID NIH HHS
ID : T32 AI007433
Pays : United States

Déclaration de conflit d'intérêts

The authors have declared that no competing interests exist.

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Auteurs

Maja E Marcus (ME)

Department of Economics & Centre for Modern Indian Studies, University of Goettingen, Göttingen, Germany.

Cara Ebert (C)

RWI-Leibniz Institute for Economic Research, Essen (Berlin Office), Germany.

Pascal Geldsetzer (P)

Division of Primary Care and Population Health, Department of Medicine, Stanford University, Stanford, California, United States of America.
Heidelberg Institute of Global Health, Heidelberg University and University Hospital, Heidelberg, Germany.

Michaela Theilmann (M)

Heidelberg Institute of Global Health, Heidelberg University and University Hospital, Heidelberg, Germany.

Brice Wilfried Bicaba (BW)

Ministry of Health, Ouagadougou, Burkina Faso.

Glennis Andall-Brereton (G)

Caribbean Public Health Agency, Port of Spain, Trinidad and Tobago.

Pascal Bovet (P)

Ministry of Health, Victoria, Seychelles.
University Centre for General Medicine and Public Health (Unisanté), Lausanne, Switzerland.

Farshad Farzadfar (F)

Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.

Mongal Singh Gurung (M)

Health Research and Epidemiology Unit, Ministry of Health, Thimphu, Bhutan.

Corine Houehanou (C)

Laboratory of Epidemiology of Chronic and Neurological Diseases, Faculty of Health Sciences, University of Abomey-Calavi, Abomey-Calavi, Benin.

Mohammad-Reza Malekpour (MR)

Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.

Joao S Martins (JS)

Faculty of Medicine and Health Sciences, Universidade Nacional Timor Lorosa'e, Dili, Timor-Leste.

Sahar Saeedi Moghaddam (SS)

Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.

Esmaeil Mohammadi (E)

Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.

Bolormaa Norov (B)

National Center for Public Health, Ulaanbaatar, Mongolia.

Sarah Quesnel-Crooks (S)

Caribbean Public Health Agency, Port of Spain, Trinidad and Tobago.

Roy Wong-McClure (R)

Office of Epidemiology and Surveillance, Caja Costarricense de Seguro Social, San Jose, Costa Rica.

Justine I Davies (JI)

Institute for Applied Health Sciences, University of Birmingham, Birmingham, United Kingdom.
MRC/Wits Rural Public Health and Health Transitions Research Unit, School of Public Health, University of Witwatersrand, Johannesburg, South Africa.
Centre for Global Surgery, Department of Global Health, Stellenbosch University, Cape Town, South Africa.

Mark A Hlatky (MA)

Department of Medicine, Stanford University, Stanford, California, United States of America.

Rifat Atun (R)

Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America.

Till W Bärnighausen (TW)

Heidelberg Institute of Global Health, Heidelberg University and University Hospital, Heidelberg, Germany.
Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America.
Africa Health Research Institute, Somkhele, South Africa.

Lindsay M Jaacks (LM)

Global Academy of Agriculture and Food Security, University of Edinburgh, Edinburgh, United Kingdom.
Public Health Foundation of India, New Delhi, Delhi NCR, India.

Jennifer Manne-Goehler (J)

Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America.
Division of Infectious Diseases, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States of America.

Sebastian Vollmer (S)

Department of Economics & Centre for Modern Indian Studies, University of Goettingen, Göttingen, Germany.

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