1,721,213 research outputs found
Neck circumference in Latin America and the Caribbean: a systematic review and meta-analysis
Full text linkAntecedentes: La circunferencia del cuello (CC) elevada se asocia con enfermedades que conllevan una gran carga en América Latina y el Caribe (ALC). La CC complementa las medidas antropométricas establecidas para la identificación temprana de enfermedades cardio-metabólicas y otras. Sin embargo, la evidencia sobre CC no se ha estudiado sistemáticamente en ALC. Objetivo: Estimar el promedio de CC y la prevalencia de CC alta en ALC. Material y Métodos: Revisión sistemática en MEDLINE, Embase, Global Health y LILACS. Los resultados de la búsqueda fueron seleccionados y estudiados por dos revisores de forma independiente. Realizamos un metanálisis de efectos aleatorios. Resultados: Se examinaron 182 reseñas, se revisaron 96 manuscritos y se resumieron 85 estudios (n = 51 978). Del total de estudios, 14 se realizaron en una muestra de la población general, 23 se realizaron con poblaciones cautivas y 49 estudios se realizaron con pacientes. El promedio de la CC en la población general fue de 35.69 cm (IC del 95%: 34.85 cm-36.53 cm; I²: 99.6%). En todas las poblaciones estudiadas, hubo varias definiciones de CC alto; por lo tanto, las estimaciones de prevalencia no fueron comparables. La prevalencia de CC alta osciló entre el 37.00% y el 57.69% en la población general. Conclusiones: El promedio de la CC en ALC parece estar en el rango de estimaciones de otras regiones del mundo. Existe la necesidad de establecer definiciones consistentes y comparables de CC para que pueda ser incorporado como un indicador antropométrico estándar en encuestas y estudios epidemiológicos.Background: High neck circumference (NC) is associated with diseases carrying large burden in Latin American and the Caribbean (LAC). NC complements established anthropometric measurements for early identification of cardio-metabolic and other illnesses. However, evidence about NC has not been systematically studied in LAC. Objectives: We aimed to estimate the mean NC and the prevalence of high NC in LAC. Materials and Methods: Systematic review in MEDLINE, Embase, Global Health and LILACS. Search results were screened and studied by two reviewers independently. We conducted a random-effects meta-analysis. Results: 182 abstracts were screened, 96 manuscripts were reviewed and 85 studies (n= 51 978) were summarized. From all the summarized studies, 14 were conducted in a sample of the general population, 23 were conducted with captive populations and 49 studies were conducted with patients. The pooled mean NC in the general population was 35.69 cm (95% IC: 34.85cm-36.53cm; I²: 99.6%). Across all studied populations, there were several definitions of high NC; thus, prevalence estimates were not comparable. The prevalence of high NC ranged between 37.00% and 57.69% in the general population. Conclusion: Mean NC in LAC appears to be in the range of estimates from other world regions. There is a need for consistent and comparable definitions of NC so that it can be incorporated as a standard anthropometric indicator in surveys and epidemiological studies
Mortality attributable to type 2 diabetes mellitus in Latin America and the Caribbean
Full text linkAntecedentes: Cuantificar los desenlaces a largo plazo (p. ej., mortalidad) de la diabetes mellitus tipo 2 (DMT2) a nivel poblacional permite comprender el perfil epidemiológico de la DMT2 y establecer prioridades. Objetivo: Estimar la mortalidad atribuible a DMT2 en personas de 20 a más años en América Latina y el Caribe (ALC) en los años 1990 y 2019. Métodos y Materiales: Integramos prevalencias de DMT2 de NCD-RisC, riesgos relativos de asociación entre DMT2 y mortalidad de un meta-análisis de cohortes de ALC, y mortalidad por todas las causas estimada por el Global Burden of Disease Study 2019. Calculamos fracciones atribuibles poblacionales (FAP) y estimamos el número absoluto de muertes atribuibles a DMT2 en 1990 y 2019 multiplicando las FAP por el total de muertes en cada país, año, sexo y grupo etario quinquenal. Resultados: Entre 1985 y 2014 en ALC, la proporción de muertes por todas las causas atribuibles a DMT2 aumentó desde 12,2% a 16,9% en varones y desde 14,5% a 19,3% en mujeres. En 2019, el número absoluto de muertes atribuibles a DMT2 fue 349 787 en varones y 330 414 en mujeres. Las tasas de mortalidad más elevadas (muertes por 100 000 personas) en 2019 se registraron en San Cristóbal y Nieves (325 en varones, 229 en mujeres), Guyana (313 en varones, 272 en mujeres) y Haití (269 en varones, 265 en mujeres). Conclusión: Una parte importante de la mortalidad por todas las causes se atribuye a DMT2 en ALC. Para reducir la mortalidad por DMT2 en esta región, se necesitan políticas que refuercen el diagnóstico y tratamiento tempranos, junto con la prevención de complicaciones.Background: Quantifying long-term outcomes (e.g., mortality) of type 2 diabetes mellitus (T2DM) in the population provides insight into the epidemiological profile of T2DM. Objective: To estimate the mortality attributable to T2DM in people aged 20 years or older in Latin America and the Caribbean (LAC) in 1990 and 2019. Methods and Materials: We combined T2DM prevalence estimates from the NCD Risk Factor Collaboration, relative risks between T2DM and all-cause mortality from a meta-analysis of cohorts in LAC, and death rates from the Global Burden of Disease Study 2019. We estimated population-attributable fractions (PAFs) and computed the absolute number of attributable deaths in 1990 and 2019 by multiplying the PAFs by the total deaths in each country, year, sex, and 5-year age group. Results: Between 1985 and 2014 in LAC, the proportion of all-cause mortality attributable to T2DM increased from 12.2% to 16.9% in men and from 14.5% to 19.3% in women. In 2019, the absolute number of deaths attributable to T2DM was 349 787 in men and 330 414 in women. The highest death rates (deaths per 100 000 people) in 2019 were in Saint Kitts and Nevis (325 in men, 229 in women), Guyana (313 in men, 272 in women), and Haiti (269 in men, 265 in women). Conclusion: A substantial burden of all deaths is attributed to T2DM in LAC. To decrease the mortality attributable to T2DM in LAC, policies are needed to strengthen early diagnosis and management, along with the prevention of complications
Prevalencia de enfermedad renal crónica en la población general en Latinoamérica y el Caribe: una revisión sistemática y meta-análisis
Full text linkAntecedentes: Los proyectos globales han informado sobre la epidemiología de la enfermedad renal crónica (ERC) en América Latina y el Caribe (LAC), pero no existen esfuerzos regionales para contrastar o avanzar estas iniciativas globales. Nuestro objetivo fue resumir la prevalencia de la ERC en LAC. Métodos: Revisión sistemática, metanálisis de efectos aleatorios y meta-regresión. Se realizaron búsquedas en Embase, Medline, Global Health, Scopus y LILACS (11 de enero de 2021). Incluimos estudios observacionales que contaron con una muestra aleatoria de la población general en LAC. El resultado fue la prevalencia de la ERC, que debería haberse definido con un biomarcador. Resultados: La búsqueda identificó 5050 publicaciones y se incluyeron 15 reportes (16 estudios). La prevalencia de ERC definida solo con TFGe osciló entre 1,7% y 20,0%; la prevalencia agrupada fue del 7,0 % (IC del 95 %: 5,0 %-10,0 %; I2: 99 %). Esta prevalencia agrupada fue similar entre estudios nacionales y no nacionales: 8,0 % (IC 95 %: 4,0 %-12,0 %; I2: 99 %) y 7,0 % (IC 95 %: 3,0 %-10,0 %; I2: 99%). Esta prevalencia agrupada fue similar entre hombres y mujeres: 10,0 % (IC del 95 %: 5,0 %-14,0 %; I2: 98 %) y 8,0 % (IC del 95 %: 4,0 %-13,0 %; I2: 99%). La prevalencia de ERC definida con TFGe y/o otros biomarcadores osciló entre 12,0%-16,8%; la prevalencia agrupada fue del 13,0 % (IC del 95 %: 9,0 %-17,0 %; I2: 98 %). En las meta-regresiones, la prevalencia de ERC se correlacionó débilmente con el año de recolección de datos. Conclusiones: En LAC, la prevalencia de la ERC no es despreciable y es similar a la de otras enfermedades no transmisibles que han recibido mayor atención (p. ej., Diabetes). Se necesita con urgencia investigación para fortalecer la epidemiología de la ERC en LAC.Background: Global projects have informed about the epidemiology of chronic kidney disease (CKD) in Latin America and the Caribbean (LAC), yet there are no regional efforts to contrast or advance these global endeavours. We aimed to summarize the CKD prevalence in LAC. Methods: Systematic review, random-effects meta-analysis and meta-regression. We searched Embase, Medline, Global Health, Scopus and LILACS (January 11th, 2021). We included observational studies which enrolled a random sample of the general population in LAC. The outcome was CKD prevalence, which should have been defined by eGFR and/or with a biomarker. Results: The search identified 5,050 publications and 15 reports (16 studies) were included. The prevalence of CKD defined with eGFR only, ranged between 1.7%-20.0%; the pooled prevalence was 7.0% (95% CI: 5.0%-10.0%; I2: 99%). This pooled prevalence was similar between national and non-national studies: 8.0% (95% CI: 4.0%-12.0%; I2: 99%) and 7.0% (95% CI: 3.0%-10.0%; I2: 99%). This pooled prevalence was similar between men and women: 10.0% (95% CI: 5.0%-14.0%; I2: 98%) and 8.0% (95% CI: 4.0%-13.0%; I2: 99%). The CKD prevalence defined with eGFR and/or other biomarkers, ranged between 12.0%-16.8%; the pooled prevalence was 13.0% (95% CI: 9.0%-17.0%; I2: 98%). In meta-regressions, the CKD prevalence was weakly correlated with the year of data collection. Conclusions: In LAC, the CKD prevalence is non-negligible and similar to that of other non-communicable diseases which has received more attention (e.g., diabetes). Research is needed to generate more epidemiological data on CKD throughout LAC
Cardiovascular disease prognostic models in Latin America and the Caribbean: a systematic review
Full text linkIntroducción: Los modelos de pronóstico cardiovascular guían la asignación de tratamientos y respaldan las decisiones clínicas. Objetivo: Identificar y evaluar críticamente modelos de pronóstico cardiovascular desarrollados, probados o recalibrados en poblaciones latinoamericanas. Métodos: La revisión sistemática siguió el marco CHARMS y fue registrada en PROSPERO CRD42018096553. Se utilizaron los siguientes buscadores: EMBASE, MEDLINE, Scopus, SCIELO y LILACS. La evaluación del riesgo de sesgo se realizó con PROBAST. No se realizó un resumen cuantitativo debido a la gran heterogeneidad. Resultados: A partir de 2506 resultados de búsqueda, se incluyeron 8 estudios (N = 130 482 participantes) para la síntesis cualitativa. No pudimos identificar ningún modelo de pronóstico cardiovascular desarrollado para las poblaciones de Latinoamérica. Solo 1 estudio incluyó población caribeña (Puerto Rico); 3 estudios fueron recuperados de Chile; 2 de Argentina, Brasil, Colombia y Uruguay; y 1 de México. El modelo de Framingham se evaluó 6 veces y la ecuación agrupada del ACC/AHA se evaluó dos veces. A través de los modelos de pronóstico evaluados, la calibración varió ampliamente de una población a otra, mostrando una gran sobreestimación particularmente en algunos subgrupos. La discriminación (p. ej., estadística C) fue aceptable para la mayoría de los modelos; para Framingham osciló entre 0,66 y 0,76. La ecuación combinada del ACC/AHA mostró la mejor discriminación (0,78). Conclusiones: No se han desarrollado modelos de pronóstico cardiovascular en Latinoamérica, lo que dificulta la evidencia clave para informar la salud pública y la práctica clínica. Los estudios de validación deben mejorar las cuestiones metodológicas.Background: Cardiovascular prognostic models guide treatment allocation and support clinical decisions. Objective: To identify and critically evaluate cardiovascular prognosis models developed, tested or recalibrated in Latin American populations. Methods: The systematic review followed the CHARMS framework and was registered in PROSPERO CRD42018096553. The following search engines were used: EMBASE, MEDLINE, Scopus, SCIELO and LILACS. Risk of bias assessment was performed using PROBAST. A quantitative summary was not performed due to high heterogeneity. Results: From 2,506 search results, 8 studies (N = 130,482 participants) were included for qualitative synthesis. We were unable to identify any cardiovascular prognostic model developed for Latin American populations. Only 1 study included a Caribbean population (Puerto Rico); 3 studies were retrieved from Chile; 2 from Argentina, Brazil, Colombia and Uruguay; and 1 from Mexico. The Framingham model was tested 6 times and the ACC/AHA pooled equation was tested twice. Across the forecast models evaluated, the calibration varied widely from one population to another, showing large overestimation particularly in some subgroups. Discrimination (e.g., C statistic) was acceptable for most models; for Framingham it ranged from 0.66 to 0.76. The combined ACC/AHA equation showed the best discrimination (0.78). Conclusions: Cardiovascular prognosis models have not been developed in Latin America, which makes it difficult to obtain key evidence to inform public health and clinical practice. Validation studies should improve methodological issues
Systematic review of diagnostic and prognostic models of chronic kidney disease in low-income and middle-income countries
Full text linkObjetivo: Resumir los modelos diagnósticos y pronósticos disponibles de la enfermedad renal crónica (ERC) en países de ingresos bajos y medios (PIBM). Métodos: Revisión sistemática. Se hicieron búsquedas en Medline, EMBASE, Global Health (estos tres a través de OVID), Scopus y Web of Science desde su inicio hasta el 9 de abril de 2021, el 17 de abril de 2021 y el 18 de abril de 2021, respectivamente. Primero se examinaron los títulos y los resúmenes, y luego se estudiaron en detalle los informes seleccionados; Ambas fases fueron realizadas por dos revisores de forma independiente. Se siguió la guía para la evaluación crítica y la extracción de datos para las revisiones sistemáticas y se utilizó la herramienta de evaluación del riesgo de sesgo del modelo de predicción para la evaluación del riesgo de sesgo. Resultados: La búsqueda recuperó 14,845 resultados, 11 informes fueron estudiados en detalle y 9 (n=61,134) fueron incluidos en el análisis cualitativo. La proporción de mujeres en la población estudiada varió entre 24,5% y 76,6%, y la edad media varió entre 41,8 y 57,7 años. La prevalencia de ERC no diagnosticada osciló entre el 1,1% y el 29,7%. La edad, la diabetes mellitus y el sexo fueron los predictores más comunes en los modelos diagnóstico y pronóstico. La definición de resultado varió mucho, consistiendo principalmente en el coeficiente albúmina-creatinina urinaria y la tasa de filtración glomerular estimada. La métrica de rendimiento más alta fue el valor predictivo negativo. Todos los estudios mostraron alto riesgo de sesgo y algunos tuvieron limitaciones metodológicas. Conclusión: No hay pruebas sólidas para apoyar el uso de un modelo diagnóstico o pronóstico de la ERC en toda la PIBM. El desarrollo, la validación y la implementación de las puntuaciones de riesgo deben ser una prioridad de investigación y salud pública en PIBM para mejorar la detección oportuna de ERC.Objective: To summarise available chronic kidney disease (CKD) diagnostic and prognostic models in low-income and middle-income countries (LMICs). Method: Systematic review (Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines). We searched Medline, EMBASE, Global Health (these three through OVID), Scopus and Web of Science from inception to 9 April 2021, 17 April 2021 and 18 April 2021, respectively. We first screened titles and abstracts, and then studied in detail the selected reports; both phases were conducted by two reviewers independently. We followed the CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies recommendations and used the Prediction model Risk Of Bias ASsessment Tool for risk of bias assessment. Results: The search retrieved 14 845 results, 11 reports were studied in detail and 9 (n=61 134) were included in the qualitative analysis. The proportion of women in the study population varied between 24.5% and 76.6%, and the mean age ranged between 41.8 and 57.7 years. Prevalence of undiagnosed CKD ranged between 1.1% and 29.7%. Age, diabetes mellitus and sex were the most common predictors in the diagnostic and prognostic models. Outcome definition varied greatly, mostly consisting of urinary albumin-to-creatinine ratio and estimated glomerular filtration rate. The highest performance metric was the negative predictive value. All studies exhibited high risk of bias, and some had methodological limitations. Conclusion: There is no strong evidence to support the use of a CKD diagnostic or prognostic model throughout LMIC. The development, validation and implementation of risk scores must be a research and public health priority in LMIC to enhance CKD screening to improve timely diagnosis
A systematic review of diagnostic and prognostic models of chronic kidney disease in low- and middle- income countries
Full text linkObjective: To summarize available chronic kidney disease (CKD) diagnostic and prognostic models in Low- and Middle-Income countries (LMIC) Method: Systematic review (PRISMA guidelines). We searched Medline, EMBASE, Global Health (these three through OVID), Scopus and Web of Science from inception to April 9th, 2021, April 17th, 2021 and April 18th, 2021, respectively . We first screened titles and abstracts, and then studied in detail the selected reports; both phases were conducted by two reviewers independently. We followed the CHARMS recommendations and used the PROBAST for risk of bias assessment. Results: The search retrieved 14,845 results, 11 reports were studied in detail and nine (n= 61,134) were included in the qualitative analysis. The proportion of women in the study population varied between 24.5%-76.6%, and the mean age ranged between 41.8-57.7 years. Prevalence of undiagnosed chronic kidney disease ranged between 1.1%-29.7%. Age, diabetes mellitus and sex were the most common predictors in the diagnostic and prognostic models. Outcome definition varied greatly, mostly consisting of urinary albumin-to-creatinine ratio and estimated glomerular filtration rate. The highest performance metric was the negative predictive value. All studies exhibited high risk of bias, and some had methodological limitations. Conclusion: There is no strong evidence to support the use of a CKD diagnostic or prognostic model throughout LMIC. The development, validation and implementation of risk scores must be a research and public health priority in LMIC to enhance CKD screening to improve timely diagnosis
Clusters of people with type 2 diabetes in the general population: Unsupervised machine learning approach using national surveys in Latin America and the Caribbean
Full text linkIntroduction We aimed to identify clusters of people with
type 2 diabetes mellitus (T2DM) and to assess whether the
frequency of these clusters was consistent across selected
countries in Latin America and the Caribbean (LAC).
Research design and methods We analyzed 13
population-based national surveys in nine countries
(n=8361). We used k-means to develop a clustering model;
predictors were age, sex, body mass index (BMI), waist
circumference (WC), systolic/diastolic blood pressure
(SBP/DBP), and T2DM family history. The training data set
included all surveys, and the clusters were then predicted
in each country-year data set. We used Euclidean distance,
elbow and silhouette plots to select the optimal number
of clusters and described each cluster according to the
underlying predictors (mean and proportions).
Results The optimal number of clusters was 4. Cluster
0 grouped more men and those with the highest mean
SBP/DBP. Cluster 1 had the highest mean BMI and WC, as
well as the largest proportion of T2DM family history. We
observed the smallest values of all predictors in cluster 2.
Cluster 3 had the highest mean age. When we reflected
the four clusters in each country-year data set, a different
distribution was observed. For example, cluster 3 was the
most frequent in the training data set, and so it was in 7
out of 13 other country-year data sets.
Conclusions Using unsupervised machine learning
algorithms, it was possible to cluster people with T2DM
from the general population in LAC; clusters showed
unique profiles that could be used to identify the
underlying characteristics of the T2DM population in LA
Aggregation and combination of cardiovascular risk factors and their association with 10-year all-cause mortality: The PERU MIGRANT Study
Full text linkObjective
To estimate the association between the aggregation and pair-wise combination of selected cardiovascular risk factors (CVRF) and 10-year all-cause mortality.
Methods
Secondary data analysis of the PERU MIGRANT study, a prospective population-based cohort. Ten-year all-cause mortality was determined for participants originally enrolled in the PERU MIGRANT Study (baseline in 2007) through the National Registry of Identification and Civil Status. The CVRF included hypertension, type 2 diabetes mellitus, hypercholesterolemia, and overweight/obesity. Exposures were composed of both the aggregation of the selected CVRF (one, two, and three or more CVRF) and pair-wise combinations of CVRF. Cox regression models were used to calculate hazard ratios (HR) and 95% confidence intervals (95% CI).
Findings
Of the 989 participants evaluated at baseline, 976 (98.8%) had information about vital status at 10 years of follow-up (9992.63 person-years), and 63 deaths were recorded. In the multivariable model, adjusting for sociodemographic and lifestyle variables, participants with two CVRF (HR: 2.48, 95% CI: 1.03–5.99), and those with three or more CVRF (HR: 3.93, 95% CI: 1.21–12.74) had higher all-cause mortality risk, compared to those without any CVRF. The pair-wise combinations associated with the highest risk of all-cause mortality, compared to those without such comorbidities, were hypertension with type 2 diabetes (HR: 11.67, 95% CI: 3.67–37.10), and hypertension with overweight/obesity (HR: 2.76, 95% CI: 1.18–6.71).
Conclusions
The aggregation of two or more CVRF and the combination of hypertension with type 2 diabetes or overweight/obesity were associated with an increased risk of 10-year all-cause mortality. These risk profiles will inform primary and secondary prevention strategies to delay mortality from cardiovascular risk factors
Intermediate hyperglycaemia and 10-year mortality in resource-constrained settings: The PERU Migrant Study
Full text linkAim
To determine whether intermediate hyperglycaemia, defined by fasting plasma glucose and HbA1c criteria, is associated with mortality in a 10‐year cohort of people in a Latin American country.
Methods
Analysis of the PERU MIGRANT Study was conducted in three different population groups (rural, rural‐to‐urban migrant, and urban). The baseline assessment was conducted in 2007/2008, with follow‐up assessment in 2018. The outcome was all‐cause mortality, and the exposure was intermediate hyperglycaemia, using three definitions: (1) impaired fasting glucose, defined according to American Diabetes Association criteria [fasting plasma glucose 5.6–6.9 mmol/l (100–125 mg/dl)]; (2) prediabetes defined according to American Diabetes Association criteria [HbA1c levels 39–46 mmol/mol (5.7–6.4%)]; and (3) prediabetes defined according to the International Expert Committee criteria [HbA1c levels 42–46 mmol/mol (6.0–6.4%)]. Crude and adjusted hazard ratios and 95% CIs were estimated using Cox proportional hazard models.
Results
At baseline, the mean (sd) age of the study population was 47.8 (11.9) years and 52.5% of the cohort were women. The study cohort was divided into population groups as follows: 207 people (20.0%) in the rural population group, 583 (59.7%) in the rural‐to‐urban migrant group and 198 (20.3%) in the urban population group. The prevalence of intermediate hyperglycaemia was: 6%, 12.9% and 38.5% according to the American Diabetes Association impaired fasting glucose definition, the International Expert Committee HbA1c‐based definition and the American Diabetes Association HbA1c‐based definition, respectively, and the mortality rate after 10 years was 63/976 (7%). Intermediate hyperglycaemia was associated with all‐cause mortality using the HbA1c‐based definitions in the crude models [hazard ratios 2.82 (95% CI 1.59–4.99) according to the American Diabetes Association and 2.92 (95% CI 1.62–5.28) according to the International Expert Committee], whereas American Diabetes Association‐defined impaired fasting glucose was not [hazard ratio 0.84 (95% CI 0.26–2.68)]. In the adjusted model, however, only the American Diabetes Association HbA1c‐based definition was associated with all‐cause mortality [hazard ratio 1.91 (95% CI 1.03–3.53)], whereas the International Expert Committee HbA1c‐based and American Diabetes Association impaired fasting glucose‐based definitions were not [hazard ratios 1.42 (95% CI 0.75–2.68) and 1.09 (95% CI 0.33–3.63), respectively].
Conclusions
Intermediate hyperglycaemia defined using the American Diabetes Association HbA1c criteria was associated with an elevated mortality rate after 10 years in a cohort from Peru. HbA1c appears to be a factor associated with mortality in this Peruvian population
Estimating the gap between demand and supply of medical appointments by physicians for hypertension care: A pooled analysis in 191 countries
Full text linkIntroduction: With a growing number of people with hypertension, the limited number of
physicians could not provide treatment to all patients. We quantified the gap between medical
appointments available and needed for hypertension care, overall and in relation to hypertension
treatment cascade metrics.
Methods: Ecological descriptive analysis. We combined country-year-specific data on
hypertension prevalence, awareness, treatment and control (from NCD-RisC) and number of
physicians (from WHO). We estimated from 1 to 12 medical appointments per year for
hypertensive patients. We assumed that physicians could see 25 patients per day, work 200 days
per year, and dedicate 10% of their time to hypertension care.
Results: We studied 191 countries. Forty-one countries would not have enough physicians to
provide at least 1 medical appointment per year to all the population with hypertension; these
countries were low/lower-middle income and in Sub-Saharan Africa or East Asia and Pacific.
Regardless of the world region, ≥50% of countries would not have enough physicians to provide
≥8 medical appointments to their population with hypertension. Countries where the demand
exceeded the offer of medical appointments for hypertension care had worse hypertension
diagnosis, treatment and control rates than countries where the demand did not exceed the offer.
There were positive correlations between the physician density and hypertension diagnosis
(r=0.70, p<0.001), treatment (r=0.70, p<0.001) and control (r=0.59, p<0.001).
Conclusions: Where physicians are the only healthcare professionals allowed to prescribe
antihypertensive medications, particularly in low- and middle-income countries, the healthcare
system may struggle to deliver antihypertensive treatment to hypertensive patients
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