7 research outputs found

    Clinical and Epidemiological Implications of 24-Hour Ambulatory Blood Pressure Monitoring for the Diagnosis of Hypertension in Kenyan Adults: A Population-Based Study.

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    BACKGROUND: The clinical and epidemiological implications of using ambulatory blood pressure monitoring (ABPM) for the diagnosis of hypertension have not been studied at a population level in sub-Saharan Africa. We examined the impact of ABPM use among Kenyan adults. METHODS AND RESULTS: We performed a nested case-control study of diagnostic accuracy. We selected an age-stratified random sample of 1248 adults from the list of residents of the Kilifi Health and Demographic Surveillance System in Kenya. All participants underwent a screening blood pressure (BP) measurement. All those with screening BP ≥140/90 mm Hg and a random subset of those with screening BP <140/90 mm Hg were invited to undergo ABPM. Based on the 2 tests, participants were categorized as sustained hypertensive, masked hypertensive, "white coat" hypertensive, or normotensive. Analyses were weighted by the probability of undergoing ABPM. Screening BP ≥140/90 mm Hg was present in 359 of 986 participants, translating to a crude population prevalence of 23.1% (95% CI 16.5-31.5%). Age standardized prevalence of screening BP ≥140/90 mm Hg was 26.5% (95% CI 19.3-35.6%). On ABPM, 186 of 415 participants were confirmed to be hypertensive, with crude prevalence of 15.6% (95% CI 9.4-23.1%) and age-standardized prevalence of 17.1% (95% CI 11.0-24.4%). Age-standardized prevalence of masked and white coat hypertension were 7.6% (95% CI 2.8-13.7%) and 3.8% (95% CI 1.7-6.1%), respectively. The sensitivity and specificity of screening BP measurements were 80% (95% CI 73-86%) and 84% (95% CI 79-88%), respectively. BP indices and validity measures showed strong age-related trends. CONCLUSIONS: Screening BP measurement significantly overestimated hypertension prevalence while failing to identify ≈50% of true hypertension diagnosed by ABPM. Our findings suggest significant clinical and epidemiological benefits of ABPM use for diagnosing hypertension in Kenyan adults

    Burden of disease in adults admitted to hospital in a rural region of coastal Kenya: an analysis of data from linked clinical and demographic surveillance systems

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    Background Estimates of the burden of disease in adults in sub-Saharan Africa largely rely on models of sparse data. We aimed to measure the burden of disease in adults living in a rural area of coastal Kenya with use of linked clinical and demographic surveillance data. Methods We used data from 18 712 adults admitted to Kilifi District Hospital (Kilifi , Kenya) between Jan 1, 2007, and Dec 31, 2012, linked to 790 635 person-years of observation within the Kilifi Health and Demographic Surveillance System, to establish the rates and major causes of admission to hospital. These data were also used to model diseasespecifi c disability-adjusted life-years lost in the population. We used geographical mapping software to calculate admission rates stratifi ed by distance from the hospital. Findings The main causes of admission to hospital in women living within 5 km of the hospital were infectious and parasitic diseases (303 per 100 000 person-years of observation), pregnancy-related disorders (239 per 100 000 personyears of observation), and circulatory illnesses (105 per 100 000 person-years of observation). Leading causes of hospital admission in men living within 5 km of the hospital were infectious and parasitic diseases (169 per 100 000 personyears of observation), injuries (135 per 100 000 person-years of observation), and digestive system disorders (112 per 100 000 person-years of observation). HIV-related diseases were the leading cause of disability-adjusted lifeyears lost (2050 per 100 000 person-years of observation), followed by non-communicable diseases (741 per 100 000 personyears of observation). For every 5 km increase in distance from the hospital, all-cause admission rates decreased by 11% (95% CI 7–14) in men and 20% (17–23) in women. The magnitude of this decline was highest for endocrine disorders in women (35%; 95% CI 22–46) and neoplasms in men (30%; 9–45). Interpretation Adults in rural Kenya face a combined burden of infectious diseases, pregnancy-related disorders, cardiovascular illnesses, and injuries. Disease burden estimates based on hospital data are aff ected by distance from the hospital, and the amount of underestimation of disease burden diff ers by both disease and sex

    Blood Pressure and Arterial Stiffness in Kenyan Adolescents With α+Thalassemia.

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    BACKGROUND: Recent studies have discovered that α-globin is expressed in blood vessel walls where it plays a role in regulating vascular tone. We tested the hypothesis that blood pressure (BP) might differ between normal individuals and those with α+thalassemia, in whom the production of α-globin is reduced. METHODS AND RESULTS: The study was conducted in Nairobi, Kenya, among 938 adolescents aged 11 to 17 years. Twenty-four-hour ambulatory BP monitoring and arterial stiffness measurements were performed using an arteriograph device. We genotyped for α+thalassemia by polymerase chain reaction. Complete data for analysis were available for 623 subjects; 223 (36%) were heterozygous (-α/αα) and 47 (8%) were homozygous (-α/-α) for α+thalassemia whereas the remaining 353 (55%) were normal (αα/αα). Mean 24-hour systolic BP ±SD was 118±12 mm Hg in αα/αα, 117±11 mm Hg in -α/αα, and 118±11 mm Hg in -α/-α subjects, respectively. Mean 24-hour diastolic BP ±SD in these groups was 64±8, 63±7, and 65±8 mm Hg, respectively. Mean pulse wave velocity (PWV)±SD was 7±0.8, 7±0.8, and 7±0.7 ms-1, respectively. No differences were observed in PWV and any of the 24-hour ambulatory BP monitoring-derived measures between those with and without α+thalassemia. CONCLUSIONS: These data suggest that the presence of α+thalassemia does not affect BP and/or arterial stiffness in Kenyan adolescents

    Replication Data for: Effect of Previous Exposure to Malaria on Blood Pressure in Kilifi, Kenya: A Mendelian Randomization Study

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    This is a replication dataset for the research paper: "Effect of Previous Exposure to Malaria on Blood Pressure in Kilifi, Kenya: A Mendelian Randomization Study published in Journal of the American Heart Association

    Burden of disease in adults admitted to hospital in a rural region of coastal Kenya: an analysis of data from linked clinical and demographic surveillance systems

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    Background: Estimates of the burden of disease in adults in sub-Saharan Africa largely rely on models of sparse data. We aimed to measure the burden of disease in adults living in a rural area of coastal Kenya with use of linked clinical and demographic surveillance data. Methods: We used data from 18 712 adults admitted to Kilifi District Hospital (Kilifi, Kenya) between Jan 1, 2007, and Dec 31, 2012, linked to 790 635 person-years of observation within the Kilifi Health and Demographic Surveillance System, to establish the rates and major causes of admission to hospital. These data were also used to model disease-specific disability-adjusted life-years lost in the population. We used geographical mapping software to calculate admission rates stratified by distance from the hospital. Findings: The main causes of admission to hospital in women living within 5 km of the hospital were infectious and parasitic diseases (303 per 100 000 person-years of observation), pregnancy-related disorders (239 per 100 000 person-years of observation), and circulatory illnesses (105 per 100 000 person-years of observation). Leading causes of hospital admission in men living within 5 km of the hospital were infectious and parasitic diseases (169 per 100 000 person-years of observation), injuries (135 per 100 000 person-years of observation), and digestive system disorders (112 per 100 000 person-years of observation). HIV-related diseases were the leading cause of disability-adjusted life-years lost (2050 per 100 000 person-years of observation), followed by non-communicable diseases (741 per 100 000 person-years of observation). For every 5 km increase in distance from the hospital, all-cause admission rates decreased by 11% (95% CI 7–14) in men and 20% (17–23) in women. The magnitude of this decline was highest for endocrine disorders in women (35%; 95% CI 22–46) and neoplasms in men (30%; 9–45). Interpretation: Adults in rural Kenya face a combined burden of infectious diseases, pregnancy-related disorders, cardiovascular illnesses, and injuries. Disease burden estimates based on hospital data are affected by distance from the hospital, and the amount of underestimation of disease burden differs by both disease and sex. Funding: The Wellcome Trust, GAVI Alliance

    Verbal autopsy as a tool for identifying children dying of sickle cell disease : a validation study conducted in Kilifi district, Kenya

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    Background: Sickle cell disease (SCD) is common in many parts of sub-Saharan Africa (SSA), where it is associated with high early mortality. In the absence of newborn screening, most deaths among children with SCD go unrecognized and unrecorded. As a result, SCD does not receive the attention it deserves as a leading cause of death among children in SSA. In the current study, we explored the potential utility of verbal autopsy (VA) as a tool for attributing underlying cause of death (COD) in children to SCD. Methods: We used the 2007 WHO Sample Vital Registration with Verbal Autopsy (SAWY) VA tool to determine COD among child residents of the Kilifi Health and Demographic Surveillance System (KHDSS), Kenya, who died between January 2008 and April 2011. VAs were coded both by physician review (physician coded verbal autopsy, PCVA) using COD categories based on the WHO International Classification of Diseases 10(th) Edition (ICD-10) and by using the InterVA-4 probabilistic model after extracting data according to the 2012 WHO VA standard. Both of these methods were validated against one of two gold standards: hospital ICD-10 physician-assigned COD for children who died in Kilifi District Hospital (KDH) and, where available, laboratory confirmed SCD status for those who died in the community. Results: Overall, 6% and 5% of deaths were attributed to SCD on the basis of PCVA and the InterVA-4 model, respectively. Of the total deaths, 22% occurred in hospital, where the agreement coefficient (AC(1)) for SCD between PCVA and hospital physician diagnosis was 95.5%, and agreement between InterVA-4 and hospital physician diagnosis was 96.9%. Confirmatory laboratory evidence of SCD status was available for 15% of deaths, in which the AC(1) against PCVA was 87.5%. Conclusions: Other recent studies and provisional data from this study, outlining the importance of SCD as a cause of death in children in many parts of the developing world, contributed to the inclusion of specific SCD questions in the 2012 version of the WHO VA instruments, and a specific code for SCD has now been included in the WHO and InterVA-4 COD listings. With these modifications, VA may provide a useful approach to quantifying the contribution of SCD to childhood mortality in rural African communities. Further studies will be needed to evaluate the generalizability of our findings beyond our local context
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