Joachim Amoako , Matthan Fayia Saa , Emmanuel Bannerman-Williams , Anastasia Naa Koshie Bruce , Maame Boatemaa Ansong , Alexander Danquah , Abraham Ablorh , Wills Nii Adjetey Kwaw , Michael Adjei , Emmanuel K. Awuttey , Isabella D. Dakubo , Patience Akos Vormatu , Isaac Ekow Ennin , Charles Frederick Hayfron-Benjamin
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PAD was defined as ankle-brachial pressure index ≤0.90 and/or intermittent claudication. A multivariate logistic regression model was built to identify modifiable PAD risk factors, which were used to define the number of risk factors for each participant. The odds of PAD were determined based on the number of modifiable risk factors.</div></div><div><h3>Results</h3><div>The mean age, diabetes duration, and HbA<sub>1</sub>c concentrations were 59.81(±9.95) years, 13.66(±7.89) years, and 8.45(±1.94) %, respectively. PAD prevalence was 25.8 %. In a multivariable regression model, hypertension [odds ratio 2.00, 95 % confidence interval 1.33–3.01], chronic kidney disease [1.54(1.11–2.14)], central obesity [1.58(1.05–2.39)], and elevated LDL-cholesterol concentration [1.42(1.02–1.97)] were independently associated with PAD. After adjustment for age, sex, and diabetes duration, the odds of PAD increased with each additional risk factor from a 2.02-fold increase [OR 2.02, 95 %CI 0.69–5.97) in the presence of two risk factors, to 3.51-fold [3.51(1.20–10.24)] for three risk factors, and nearly five-fold [4.80 (1.57–14.67)] for four risk factors.</div></div><div><h3>Conclusion</h3><div>West Africans with diabetes are very sensitive to the cumulative effect of hypertension, chronic kidney disease, central obesity, and elevated LDL cholesterol concentration for PAD. These findings provide data to guide PAD screening/treatment strategies.</div></div>","PeriodicalId":29726,"journal":{"name":"International Journal of Cardiology Cardiovascular Risk and Prevention","volume":"26 ","pages":"Article 200469"},"PeriodicalIF":2.1000,"publicationDate":"2025-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Peripheral artery disease In West Africans with diabetes: a risk factor profile analysis\",\"authors\":\"Joachim Amoako , Matthan Fayia Saa , Emmanuel Bannerman-Williams , Anastasia Naa Koshie Bruce , Maame Boatemaa Ansong , Alexander Danquah , Abraham Ablorh , Wills Nii Adjetey Kwaw , Michael Adjei , Emmanuel K. Awuttey , Isabella D. Dakubo , Patience Akos Vormatu , Isaac Ekow Ennin , Charles Frederick Hayfron-Benjamin\",\"doi\":\"10.1016/j.ijcrp.2025.200469\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background</h3><div>Globally, peripheral artery disease (PAD) affects >200 million people, disproportionately affecting people with diabetes. Prior studies characterizing the risk profile of PAD in diabetes have excluded West Africans, whose vascular biology is relevantly different. This study characterized the aggregate effect of modifiable risk factors on PAD in West Africans with diabetes.</div></div><div><h3>Methods</h3><div>This was a cross-sectional study among 803 Ghanaian adults with diabetes. PAD was defined as ankle-brachial pressure index ≤0.90 and/or intermittent claudication. A multivariate logistic regression model was built to identify modifiable PAD risk factors, which were used to define the number of risk factors for each participant. The odds of PAD were determined based on the number of modifiable risk factors.</div></div><div><h3>Results</h3><div>The mean age, diabetes duration, and HbA<sub>1</sub>c concentrations were 59.81(±9.95) years, 13.66(±7.89) years, and 8.45(±1.94) %, respectively. PAD prevalence was 25.8 %. In a multivariable regression model, hypertension [odds ratio 2.00, 95 % confidence interval 1.33–3.01], chronic kidney disease [1.54(1.11–2.14)], central obesity [1.58(1.05–2.39)], and elevated LDL-cholesterol concentration [1.42(1.02–1.97)] were independently associated with PAD. After adjustment for age, sex, and diabetes duration, the odds of PAD increased with each additional risk factor from a 2.02-fold increase [OR 2.02, 95 %CI 0.69–5.97) in the presence of two risk factors, to 3.51-fold [3.51(1.20–10.24)] for three risk factors, and nearly five-fold [4.80 (1.57–14.67)] for four risk factors.</div></div><div><h3>Conclusion</h3><div>West Africans with diabetes are very sensitive to the cumulative effect of hypertension, chronic kidney disease, central obesity, and elevated LDL cholesterol concentration for PAD. 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引用次数: 0
摘要
在全球范围内,外周动脉疾病(PAD)影响了2亿人,其中糖尿病患者的影响尤为严重。先前关于糖尿病中PAD风险特征的研究排除了西非人,因为他们的血管生物学是不同的。本研究描述了西非糖尿病患者PAD可改变危险因素的总体影响。方法:对803名加纳成人糖尿病患者进行横断面研究。PAD定义为踝肱压力指数≤0.90和/或间歇性跛行。建立多变量logistic回归模型,确定可改变的PAD危险因素,用于定义每个参与者的危险因素数量。PAD的几率是根据可改变的危险因素的数量来确定的。结果患者平均年龄59.81(±9.95)岁,糖尿病病程13.66(±7.89)岁,HbA1c浓度8.45(±1.94)%。PAD患病率为25.8%。在多变量回归模型中,高血压[比值比2.00,95%可信区间1.33-3.01]、慢性肾病[1.54(1.11-2.14)]、中心性肥胖[1.58(1.05-2.39)]、ldl -胆固醇浓度升高[1.42(1.02-1.97)]与PAD独立相关。在调整了年龄、性别和糖尿病病程后,每增加一个危险因素,PAD的几率就会增加,从两个危险因素时的2.02倍[OR 2.02, 95% CI 0.69-5.97]增加到三个危险因素时的3.51倍[3.51(1.20-10.24)],四个危险因素时的近5倍[4.80(1.57-14.67)]。结论西非糖尿病患者对高血压、慢性肾病、中心性肥胖和LDL胆固醇浓度升高的累积效应非常敏感。这些发现为指导PAD筛查/治疗策略提供了数据。
Peripheral artery disease In West Africans with diabetes: a risk factor profile analysis
Background
Globally, peripheral artery disease (PAD) affects >200 million people, disproportionately affecting people with diabetes. Prior studies characterizing the risk profile of PAD in diabetes have excluded West Africans, whose vascular biology is relevantly different. This study characterized the aggregate effect of modifiable risk factors on PAD in West Africans with diabetes.
Methods
This was a cross-sectional study among 803 Ghanaian adults with diabetes. PAD was defined as ankle-brachial pressure index ≤0.90 and/or intermittent claudication. A multivariate logistic regression model was built to identify modifiable PAD risk factors, which were used to define the number of risk factors for each participant. The odds of PAD were determined based on the number of modifiable risk factors.
Results
The mean age, diabetes duration, and HbA1c concentrations were 59.81(±9.95) years, 13.66(±7.89) years, and 8.45(±1.94) %, respectively. PAD prevalence was 25.8 %. In a multivariable regression model, hypertension [odds ratio 2.00, 95 % confidence interval 1.33–3.01], chronic kidney disease [1.54(1.11–2.14)], central obesity [1.58(1.05–2.39)], and elevated LDL-cholesterol concentration [1.42(1.02–1.97)] were independently associated with PAD. After adjustment for age, sex, and diabetes duration, the odds of PAD increased with each additional risk factor from a 2.02-fold increase [OR 2.02, 95 %CI 0.69–5.97) in the presence of two risk factors, to 3.51-fold [3.51(1.20–10.24)] for three risk factors, and nearly five-fold [4.80 (1.57–14.67)] for four risk factors.
Conclusion
West Africans with diabetes are very sensitive to the cumulative effect of hypertension, chronic kidney disease, central obesity, and elevated LDL cholesterol concentration for PAD. These findings provide data to guide PAD screening/treatment strategies.