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
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
e1003841Subventions
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.
Références
JAMA Cardiol. 2016 Sep 1;1(6):700-7
pubmed: 27434662
Nat Rev Cardiol. 2018 Feb;15(2):106-119
pubmed: 28933782
Bull World Health Organ. 2011 Feb 1;89(2):92-101
pubmed: 21346920
Clin Chem. 1972 Jun;18(6):499-502
pubmed: 4337382
Ir J Med Sci. 2017 Nov;186(4):1009-1017
pubmed: 28283862
BMC Neurol. 2019 Dec 30;19(1):349
pubmed: 31888526
J Epidemiol Community Health. 2012 Nov;66(11):1050-5
pubmed: 22245720
Lancet. 2011 Feb 12;377(9765):578-86
pubmed: 21295847
Eur Heart J. 2020 Jan 1;41(1):111-188
pubmed: 31504418
PLoS Med. 2019 Mar 1;16(3):e1002751
pubmed: 30822339
Am J Cardiol. 2013 Sep 1;112(5):664-70
pubmed: 23726177
BMJ Glob Health. 2018 Mar 06;3(2):e000543
pubmed: 29527356
Bull World Health Organ. 2005 Nov;83(11):820-9
pubmed: 16302038
Nat Rev Cardiol. 2014 Oct;11(10):586-96
pubmed: 25027487
Lancet. 2018 Nov 10;392(10159):1736-1788
pubmed: 30496103
Circulation. 2004 Jul 27;110(4):405-11
pubmed: 15238453
PLoS One. 2014 May 09;9(5):e96808
pubmed: 24817067
Lancet. 2015 Apr 11;385(9976):1397-405
pubmed: 25579834
Clin Endocrinol (Oxf). 2006 Mar;64(3):292-8
pubmed: 16487439
Diabetes Care. 2020 Dec;43(12):3094-3101
pubmed: 33060076
Lancet Diabetes Endocrinol. 2019 Mar;7(3):200-212
pubmed: 30733182
Lancet. 2007 Dec 1;370(9602):1829-39
pubmed: 18061058
Clin Endocrinol (Oxf). 2011 Nov;75(5):621-7
pubmed: 21575024
NCHS Data Brief. 2013 Oct;(132):1-8
pubmed: 24165064
J Am Heart Assoc. 2014 Feb 26;3(1):e000650
pubmed: 24572249
Bull World Health Organ. 2019 Feb 1;97(2):129-141
pubmed: 30728619
Lancet. 2016 Jan 2;387(10013):61-9
pubmed: 26498706
Ir Med J. 2015 Jul-Aug;108(7):204-7
pubmed: 26349349
Lancet. 2019 Aug 24;394(10199):652-662
pubmed: 31327566
Curr Opin HIV AIDS. 2016 Jan;11(1):102-8
pubmed: 26545266
Br J Gen Pract. 2012 Mar;62(596):e224-6
pubmed: 22429442
Prim Care. 2013 Mar;40(1):195-211
pubmed: 23402469
Clin Biochem. 2010 Mar;43(4-5):515-8
pubmed: 19961841
Lipids Health Dis. 2017 Mar 23;16(1):61
pubmed: 28330492
Annu Rev Biomed Eng. 2008;10:107-44
pubmed: 18358075
Lancet. 2016 Nov 19;388(10059):2532-2561
pubmed: 27616593
Am J Epidemiol. 2004 Apr 1;159(7):702-6
pubmed: 15033648
Clin Chim Acta. 2015 Jun 15;446:263-6
pubmed: 25952166
PLoS One. 2014 Nov 04;9(11):e111812
pubmed: 25369455
Med Sante Trop. 2018 May 1;28(2):201-205
pubmed: 29997081
J Clin Lipidol. 2018 Nov - Dec;12(6):1471-1481.e4
pubmed: 30195823
Cardiovasc J S Afr. 2005 Mar-Apr;16(2):112-7
pubmed: 15915279
Ann Intern Med. 2014 Nov 18;161(10):681-9
pubmed: 25402511