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Beidelman ET, Rosenberg M, Wade AN, Crowther NJ, Kalbaugh CA. Prevalence of and Risk Factors for Peripheral Artery Disease in Rural South Africa: A Cross-Sectional Analysis of the HAALSI Cohort. J Am Heart Assoc 2024; 13:e031780. [PMID: 38156447 PMCID: PMC10863815 DOI: 10.1161/jaha.123.031780] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Accepted: 11/16/2023] [Indexed: 12/30/2023]
Abstract
BACKGROUND The burden of peripheral artery disease (PAD) is increasing in low- and middle-income countries. Existing literature from sub-Saharan Africa is limited and lacks population-representative estimates. We estimated the burden and risk factor profile of PAD for a rural South African population. METHODS AND RESULTS We used data from 1883 participants from a rural, low-income cohort of South African adults aged 40 to 69 years with available ankle-brachial index measurements. We defined clinical PAD as ankle-brachial index ≤0.90 or >1.40, and borderline PAD as ankle-brachial index >0.90 and ≤1.00. We compared the distribution of sociodemographic variables, biomarkers, and comorbidities across PAD classifications. To identify associated factors, we calculated unadjusted and age-sex-adjusted prevalence ratios (PRs) with log-binomial models. Overall, 6.6% (95% CI, 5.6-7.7) of the sample met the diagnostic criteria for clinical PAD, while 44.7% (95% CI, 42.4-47.0) met the diagnostic criteria for borderline PAD. Age (PR: 1.9 [95% CI, 1.2-3.1] for ages 50-59 years compared with 40-49 years; PR: 2.5 [95% CI, 1.5-4.0] for ages 60-69 years compared with 40-49 years); diagnosed hypertension (PR: 1.53 [95% CI, 1.08-2.17]); and C-reactive protein (PR: 1.08 [95% CI, 1.03-1.12]) were associated with increased prevalence of clinical PAD. All other examined factors were not significantly associated with clinical PAD. CONCLUSIONS We found high PAD prevalence for younger age groups compared with previous research and a lack of statistical evidence for the influence of traditional risk factors for this rural, low-income population. Future research should focus on identifying the underlying risk factors for PAD in this setting. South African policymakers and clinicians should consider expanded screening for early PAD detection in rural areas.
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Affiliation(s)
- Erika Teresa Beidelman
- Department of Epidemiology and BiostatisticsIndiana University Bloomington School of Public HealthBloomingtonINUSA
| | - Molly Rosenberg
- Department of Epidemiology and BiostatisticsIndiana University Bloomington School of Public HealthBloomingtonINUSA
| | - Alisha N. Wade
- MRC/Wits Rural Public Health and Health Transitions Research Unit, School of Public HealthUniversity of the Witwatersrand Johannesburg, South Africa Faculty of Health SciencesJohannesburgSouth Africa
- Division of Endocrinology, Diabetes and MetabolismPerelman School of Medicine, University of PennsylvaniaPhiladelphiaPAUSA
| | - Nigel J. Crowther
- Department of Chemical PathologyNational Health Laboratory Service, University of the Witwatersrand Johannesburg Faculty of Health SciencesJohannesburgSouth Africa
| | - Corey A. Kalbaugh
- Department of Epidemiology and BiostatisticsIndiana University Bloomington School of Public HealthBloomingtonINUSA
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Individual and joint effects of borderline ankle-brachial index and high plasma total homocysteine on all-cause death in hypertensive adults. J Geriatr Cardiol 2022; 19:522-530. [PMID: 35975022 PMCID: PMC9361165 DOI: 10.11909/j.issn.1671-5411.2022.07.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND The cardiovascular hazards of total homocysteine (tHcy) are long known. In addition, despite the acknowledgment on the importance of low ankle-brachial index (ABI) (< 0.9), borderline ABI (0.91-0.99) was once commonly overlooked. This study aims to explore the independent and joint effect of tHcy level and borderline ABI on all-cause death in hypertensive population. METHODS This study included 10,538 participants from China H-type Hypertension Registry Study. ABI was described into two groups: normal ABI (1.00-1.40) and borderline ABI. tHcy level was also divided into two groups: < 15.02 and ≥ 15.02 μmo/L. Four groups were analyzed, using COX proportional hazard regression model, separately and pairwise to observe the independent and joint effect on all-cause death. RESULTS A total of 126 (1.2%) deaths were observed in the 1.7 years follow-up time. Borderline ABI has a higher predicted risk of death than normal ABI (HR = 1.87, 95%CI: 1.17-3.00) after adjusting for potential covariates. Compare with tHcy level < 15.02 μmo/L (low tHcy), those with tHcy ≥ 15.02 μmo/L (high tHcy) had higher risk to event outcome (HR = 1.99, 95% CI: 1.30-3.05). According to the cumulative hazard curve, group with borderline ABI and high tHcy level has significantly higher altitude and larger increasing rate over follow-up period compare to other groups. Among those with borderline ABI, participants with high tHcy had higher death risk than those with low tHcy, nevertheless, no significant different between borderline and normal ABI among those with low tHcy levels. CONCLUSIONS Borderline ABI and tHcy level both have independent predictive value on all-cause death. The combined group of borderline ABI and high tHcy has highest risk factor of outcomes, which suggested the mutual additive value of borderline ABI and tHcy. More attention should be given to the importance of borderline ABI in hypertensive population, especially with elevated tHcy level.
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Zhang J, Sun H, Yang X, Feng Y, Li Y, Han M, Qie R, Huang S, Yuan L, Li T, Hu H, Li X, Liu D, Wu X, Zhang Y, Wu Y, Hu F, Zhang M, Sun L, Zhao Y, Hu D. Dose-Response Association of Low and Normal Ankle Brachial Index With the Risk of Cardiovascular Disease Morbidity and Mortality. Angiology 2022:33197221114701. [PMID: 35830466 DOI: 10.1177/00033197221114701] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
We quantitatively evaluated the dose-response association of low and normal ankle brachial index (ABI) with the risk of morbidity and mortality from cardiovascular diseases (CVDs). PubMed, Embase, and Web of Science were systematically searched for cohort studies. Random effects or fixed effects models were used to estimate the pooled relative risks (RRs) and 95% confidence intervals (95% CIs). Generalized least squares regression was used to assess study-specific dose-response associations per 0.1 ABI decrease. Restricted cubic splines were used to evaluate linear or nonlinear trends. Twelve cohort studies (57 031 participants) were included in this meta-analysis. For low vs normal ABI levels, the pooled RRs were 2.03 (95% CI, 1.72-2.41; I2 = 52.9%; pheterogeneity=0.030) and 2.29 (95% CI, 1.98-2.64; I2 = 39.5%; pheterogeneity =0.158) for CVD morbidity and CVD mortality, respectively. For per 0.1 ABI decrease from 1.40 the risk for CVD morbidity and CVD mortality increased by 8% (1.08, 95% CI 1.04-1.11) and 11% (1.11, 95% CI 1.07-1.15), respectively. Restricted cubic splines showed inverse linear associations for CVD morbidity and CVD mortality. As a non-invasive index, lower ABI was significantly associated with the increased risk of morbidity and mortality from CVDs in an inverse linear manner.
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Affiliation(s)
- Jinli Zhang
- Department of Epidemiology and Biostatistics, College of Public Health, 12636Zhengzhou University, Zhengzhou, Henan, People's Republic of China
| | - Haohang Sun
- Cardiovascular Department, Zhengzhou Yihe Hospital, Zhengzhou, Henan, People's Republic of China
| | - Xingjin Yang
- Department of Epidemiology and Biostatistics, College of Public Health, 12636Zhengzhou University, Zhengzhou, Henan, People's Republic of China
| | - Yifei Feng
- Department of Epidemiology and Biostatistics, College of Public Health, 12636Zhengzhou University, Zhengzhou, Henan, People's Republic of China
| | - Yang Li
- Department of Biostatistics and Epidemiology, School of Public Health, 47890Shenzhen University, Shenzhen, Guangdong, People's Republic of China
| | - Minghui Han
- Department of Epidemiology and Biostatistics, College of Public Health, 12636Zhengzhou University, Zhengzhou, Henan, People's Republic of China
| | - Ranran Qie
- Department of Epidemiology and Biostatistics, College of Public Health, 12636Zhengzhou University, Zhengzhou, Henan, People's Republic of China
| | - Shengbing Huang
- Department of Epidemiology and Biostatistics, College of Public Health, 12636Zhengzhou University, Zhengzhou, Henan, People's Republic of China
| | - Lijun Yuan
- Department of Epidemiology and Biostatistics, College of Public Health, 12636Zhengzhou University, Zhengzhou, Henan, People's Republic of China
| | - Tianze Li
- Department of Epidemiology and Biostatistics, College of Public Health, 12636Zhengzhou University, Zhengzhou, Henan, People's Republic of China
| | - Huifang Hu
- Department of Epidemiology and Biostatistics, College of Public Health, 12636Zhengzhou University, Zhengzhou, Henan, People's Republic of China
| | - Xi Li
- Department of Epidemiology and Biostatistics, College of Public Health, 12636Zhengzhou University, Zhengzhou, Henan, People's Republic of China
| | - Dechen Liu
- Department of Epidemiology and Biostatistics, College of Public Health, 12636Zhengzhou University, Zhengzhou, Henan, People's Republic of China
| | - Xiaoyan Wu
- Department of Biostatistics and Epidemiology, School of Public Health, 47890Shenzhen University, Shenzhen, Guangdong, People's Republic of China
| | - Yanyan Zhang
- Department of Biostatistics and Epidemiology, School of Public Health, 47890Shenzhen University, Shenzhen, Guangdong, People's Republic of China
| | - Yuying Wu
- Department of Biostatistics and Epidemiology, School of Public Health, 47890Shenzhen University, Shenzhen, Guangdong, People's Republic of China
| | - Fulan Hu
- Department of Biostatistics and Epidemiology, School of Public Health, 47890Shenzhen University, Shenzhen, Guangdong, People's Republic of China
| | - Ming Zhang
- Department of Biostatistics and Epidemiology, School of Public Health, 47890Shenzhen University, Shenzhen, Guangdong, People's Republic of China
| | - Liang Sun
- Department of Social Medicine and Health Management, College of Public Health, 12636Zhengzhou University, Zhengzhou, Henan, People's Republic of China
| | - Yang Zhao
- Department of Epidemiology and Biostatistics, College of Public Health, 12636Zhengzhou University, Zhengzhou, Henan, People's Republic of China
| | - Dongsheng Hu
- Department of Epidemiology and Biostatistics, College of Public Health, 12636Zhengzhou University, Zhengzhou, Henan, People's Republic of China
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The Cardiovascular-Mortality-Based Estimate for Normal Range of the Ankle-Brachial Index (ABI). J Cardiovasc Dev Dis 2022; 9:jcdd9050147. [PMID: 35621858 PMCID: PMC9144270 DOI: 10.3390/jcdd9050147] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2022] [Revised: 05/02/2022] [Accepted: 05/03/2022] [Indexed: 11/16/2022] Open
Abstract
Background: The ankle−brachial index (ABI) is a first-line examination in cardiovascular risk evaluation. Since cut-off values for normal ABI vary, the aim of the present study was to identify the cardiovascular-mortality-based estimate for the normal range of the ABI. After determining the reference range for the ABI, the corresponding toe−brachial index (TBI) and toe pressure for normal ABI were analyzed. Methods: All consecutive non-invasive pressure measurements in the vascular laboratory of a large university hospital 2011−2013 inclusive were collected and combined with patient characteristics and official dates and causes of death. Patients with an ABI range of 0.8−1.4 on both lower limbs were included in this study. Results: From 2751 patients, 868 had bilateral ABI values within the inclusion. Both ABI category ranges 0.80−0.89 and 0.90−0.99 had poorer survival compared to ABI categories 1.00−1.29 (p < 0.05). The 1-, 3-, and 5-year cardiovascular-death-free survival for respective ABI categories 0.80−0.99 vs. 1.00−1.29 were 90% vs. 96%, 84% vs. 92%, and 60% vs. 87%. The 1-, 3-, and 5-year overall survival for ABI categories 0.80−0.99 vs. 1.00−1.29 were 85% vs. 92%, 75% vs. 83%, and 42% vs. 74%. Conclusions: Borderline ABI (0.90−0.99) associates with higher overall and cardiovascular mortality compared to ABI values 1.00−1.29.
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Disparate effects of ankle-brachial index on mortality in the 'very old' and 'younger old' populations-the PolSenior survey. Heart Vessels 2021; 37:665-672. [PMID: 34643792 PMCID: PMC8917102 DOI: 10.1007/s00380-021-01949-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/17/2021] [Accepted: 09/24/2021] [Indexed: 12/29/2022]
Abstract
To assess the relationship between ankle-brachial index (ABI) and up to 10-year mortality in older individuals below and above the age of 80 years. In a multicenter survey of health status in the community dwelling subjects aged 55-59 and 65 + years in Poland, we assessed baseline medical history including risk-factors. We measured ABI, and serum creatinine, cholesterol, NT-proBNP, and interleukin-6 (IL-6) concentrations. We assessed mortality based on public registry. Between 2009 and 2019, 27.3% of 561 participants < 80 years, and 79.4% of 291 participants ≥ 80 years, died (p < 0.001); 67.8, 41.5, and 40.3% in the ABI groups < 0.9, 0.9-1.4, and > 1.4, respectively (p < 0.01). In the unadjusted Cox models, ABI was associated with mortality in the entire group, and < 80 years. In the entire group, analysis adjusted for age and sex showed mortality risk increased by 11% per year, and 50% with male sex. Mortality decreased by 37% per 1 unit ABI increase. In the group of people ≥ 80 years, only age was significantly associated with mortality (p < 0.001). In stepwise regression ABI < 0.9, male sex, active smoking, and NT-proBNP level were associated with risk of death < 80 years. In the ≥ 80 years old, mortality risk was associated with older age, and higher levels of IL-6, but not ABI. The ABI < 0.9 is associated with higher mortality in older people, but not among the oldest-old. In the oldest age group, age is the strongest predictor of death. In this age group, inflammageing is of importance.
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Long-Term Morbidity and Mortality after First and Recurrent Cardiovascular Events in the ARTPER Cohort. J Clin Med 2020; 9:jcm9124064. [PMID: 33339366 PMCID: PMC7767029 DOI: 10.3390/jcm9124064] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2020] [Revised: 12/02/2020] [Accepted: 12/10/2020] [Indexed: 11/25/2022] Open
Abstract
Background: Cardiovascular events are a major cause of mortality and morbidity worldwide. The risk of recurrence after a first cardiovascular event has been documented in the international literature, although not as extensively in a Mediterranean population-based cohort with low cardiovascular risk. There is also ample, albeit contradictory, research on the recurrence of stroke and myocardial infarctions (MI) after a first event and the factors associated with such recurrence, including the role of pathological Ankle-Brachial Index (ABI). Methods: The Peripheral Arterial ARTPER study is aimed at deepening our knowledge of patient evolution after a first cardiovascular event in a Mediterranean population with low cardiovascular risk treated at a primary care centre. We study overall recurrence, cardiac and cerebral recurrence. We studied participants in the ARTPER prospective observational cohort, excluding patients without cardiovascular events or with unconfirmed events and patients who presented arterial calcification at baseline or who died. In total, we analyzed 520 people with at least one cardiovascular event, focusing on the presence and type of recurrence, the risk factors associated with recurrence and the behavior of the ankle-brachial index (ABI) as a predictor of risk. Results: Between 2006 and 2017, 46% of patients with a first cardiovascular event experienced a recurrence of some type; most recurrences fell within the same category as the first event. The risk of recurrence after an MI was greater than after a stroke. In our study, recurrence increased with age, the presence of peripheral arterial disease (PAD), diabetes and the use of antiplatelets. Diabetes mellitus was associated with all types of recurrence. Additionally, patients with an ABI < 0.9 presented more recurrences than those with an ABI ≥ 0.9. Conclusions: In short, following a cardiac event, recurrence usually takes the form of another cardiac event. However, after having a stroke, the chance of having another stroke or having a cardiac event is similar. Lastly, ABI < 0.9 may be considered a predictor of recurrence risk.
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