Dataset Information

Childhood cause-specific mortality in rural Western Kenya: application of the InterVA-4 model.

ABSTRACT: Assessing the progress in achieving the United Nation's Millennium Development Goals in terms of population health requires consistent and reliable information on cause-specific mortality, which is often rare in resource-constrained countries. Health and demographic surveillance systems (HDSS) have largely used medical personnel to review and assign likely causes of death based on the information gathered from standardized verbal autopsy (VA) forms. However, this approach is expensive and time consuming, and it may lead to biased results based on the knowledge and experience of individual clinicians. We assessed the cause-specific mortality for children under 5 years old (under-5 deaths) in Siaya County, obtained from a computer-based probabilistic model (InterVA-4).Successfully completed VA interviews for under-5 deaths conducted between January 2003 and December 2010 in the Kenya Medical Research Institute/US Centers for Disease Control and Prevention HDSS were extracted from the VA database and processed using the InterVA-4 (version 4.02) model for interpretation. Cause-specific mortality fractions were then generated from the causes of death produced by the model.A total of 84.33% (6,621) childhood deaths had completed VA data during the study period. Children aged 1-4 years constituted 48.53% of all cases, and 42.50% were from infants. A single cause of death was assigned to 89.18% (5,940) of cases, 8.35% (556) of cases were assigned two causes, and 2.10% (140) were assigned 'indeterminate' as cause of death by the InterVA-4 model. Overall, malaria (28.20%) was the leading cause of death, followed by acute respiratory infection including pneumonia (25.10%), in under-5 children over the study period. But in the first 5 years of the study period, acute respiratory infection including pneumonia was the main cause of death, followed by malaria. Similar trends were also reported in infants (29 days-11 months) and children aged 1-4 years.Under-5 cause-specific mortality obtained using the InterVA-4 model is consistent with existing knowledge on the burden of childhood diseases in rural western Kenya.

SUBMITTER: Amek NO

PROVIDER: S-EPMC4221497 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Childhood cause-specific mortality in rural Western Kenya: application of the InterVA-4 model.

Amek Nyaguara O NO Odhiambo Frank O FO Khagayi Sammy S Moige Hellen H Orwa Gordon G Hamel Mary J MJ Van Eijk Annemieke A Vulule John J Slutsker Laurence L Laserson Kayla F KF

Global health action 20141029

<h4>Background</h4>Assessing the progress in achieving the United Nation's Millennium Development Goals in terms of population health requires consistent and reliable information on cause-specific mortality, which is often rare in resource-constrained countries. Health and demographic surveillance systems (HDSS) have largely used medical personnel to review and assign likely causes of death based on the information gathered from standardized verbal autopsy (VA) forms. However, this approach is e ...[more]

PMID: 25377340

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Project description:BACKGROUND:Elevated blood pressure is the leading risk for mortality in the world. Task redistribution has been shown to be efficacious for hypertension management in low- and middle-income countries. However, the workforce requirements for such a task redistribution strategy are largely unknown. Therefore, we developed a needs-based workforce estimation model for hypertension management in western Kenya, using need and capacity as inputs. METHODS:Key informant interviews, focus group discussions, a Delphi exercise, and time-motion studies were conducted among administrative leadership, clinicians, patients, community leaders, and experts in hypertension management. These results were triangulated to generate the best estimates for the inputs into the health workforce model. The local hypertension clinical protocol was used to derive a schedule of encounters with different levels of clinician and health facility staff. A Microsoft Excel-based spreadsheet was developed to enter the inputs and generate the full-time equivalent workforce requirement estimates over 3 years. RESULTS:Two different scenarios were modeled: (1) "ramp-up" (increasing growth of patients each year) and (2) "steady state" (constant rate of patient enrollment each month). The ramp-up scenario estimated cumulative enrollment of 7000 patients by year 3, and an average clinical encounter time of 8.9 min, yielding nurse full-time equivalent requirements of 4.8, 13.5, and 30.2 in years 1, 2, and 3, respectively. In contrast, the steady-state scenario assumed a constant monthly enrollment of 100 patients and yielded nurse full-time equivalent requirements of 5.8, 10.5, and 14.3 over the same time period. CONCLUSIONS:A needs-based workforce estimation model yielded health worker full-time equivalent estimates required for hypertension management in western Kenya. The model is able to provide workforce projections that are useful for program planning, human resource allocation, and policy formulation. This approach can serve as a benchmark for chronic disease management programs in low-resource settings worldwide.

Project description:BACKGROUND:Zinc treatment shortens diarrhea episodes and can prevent future episodes. In rural Africa, most children with diarrhea are not brought to health facilities. In a village-randomized trial in rural Kenya, we assessed if zinc treatment might have a community-level preventive effect on diarrhea incidence if available at home versus only at health facilities. METHODS:We randomized 16 Kenyan villages (1,903 eligible children) to receive a 10-day course of zinc and two oral rehydration solution (ORS) sachets every two months at home and 17 villages (2,241 eligible children) to receive ORS at home, but zinc at the health-facility only. Children's caretakers were educated in zinc/ORS use by village workers, both unblinded to intervention arm. We evaluated whether incidence of diarrhea and acute lower respiratory illness (ALRI) reported at biweekly home visits and presenting to clinic were lower in zinc villages, using poisson regression adjusting for baseline disease rates, distance to clinic, and children's age. RESULTS:There were no differences between village groups in diarrhea incidence either reported at the home or presenting to clinic. In zinc villages (1,440 children analyzed), 61.2% of diarrheal episodes were treated with zinc, compared to 5.4% in comparison villages (1,584 children analyzed, p<0.0001). There were no differences in ORS use between zinc (59.6%) and comparison villages (58.8%). Among children with fever or cough without diarrhea, zinc use was low (<0.5%). There was a lower incidence of reported ALRI in zinc villages (adjusted RR 0.68, 95% CI 0.46-0.99), but not presenting at clinic. CONCLUSIONS:In this study, home zinc use to treat diarrhea did not decrease disease rates in the community. However, with proper training, availability of zinc at home could lead to more episodes of pediatric diarrhea being treated with zinc in parts of rural Africa where healthcare utilization is low. TRIAL REGISTRATION:ClinicalTrials.gov NCT00530829.

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Project description:BackgroundThe proportion of pediatric and adolescent cancer patients surviving 5 years has increased during the past four decades. This growing population of survivors remains at risk for disease- and treatment-associated late mortality.MethodsA total of 20 483 five-year survivors of childhood and adolescent cancer diagnosed between January 1, 1970, and December 31, 1986, and enrolled in the Childhood Cancer Survivor Study (CCSS) were included in a National Death Index search for deaths occurring between January 1, 1979, and December 31, 2002. Treatment information was abstracted from primary medical records. Survival probabilities, standardized mortality ratios (SMRs), and absolute excess risks were calculated for overall and cause-specific deaths. Diagnosis- and sex-specific survival probabilities were estimated by the product-limit method. All statistical tests were two-sided.ResultsAmong the CCSS cohort, 2821 (13.8%) 5-year survivors had died by the end of the follow-up period. The cause of death was obtained for 2534 individuals, with 57.5% of deaths attributed to recurrent disease. Estimated probability of survival 30 years from diagnosis was 82%. When compared with the US population, the absolute excess risk of death from any cause was 7.36 deaths per 1000 person-years. The overall SMR was 8.4 (95% confidence interval [CI] = 8.0 to 8.7). Increases in cause-specific mortality were seen for deaths due to subsequent malignancy (SMR = 15.2, 95% CI = 13.9 to 16.6) and cardiac (SMR = 7.0, 95% CI = 5.9 to 8.2), pulmonary (SMR = 8.8, 95% CI = 6.8 to 11.2), and other medical (SMR = 2.6, 95% CI = 2.3 to 3.0) causes. At 20 years of follow-up (25 years after first cancer diagnosis), the death rate due to a subsequent malignancy exceeded that due to all other causes.ConclusionOur extended follow-up of 5-year survivors of pediatric and adolescent cancer indicates that excess mortality persists long after diagnosis. Continued observation is needed to further define lifetime risk and to determine the potential contribution of chronic health conditions and modifiable health behaviors.

Project description:Importance:In China, diabetes prevalence has increased substantially in recent decades, but there are no reliable estimates of the excess mortality currently associated with diabetes. Objectives:To assess the proportional excess mortality associated with diabetes and estimate the diabetes-related absolute excess mortality in rural and urban areas of China. Design, Setting, and Participants:A 7-year nationwide prospective study of 512?869 adults aged 30 to 79 years from 10 (5 rural and 5 urban) regions in China, who were recruited between June 2004 and July 2008 and were followed up until January 2014. Exposures:Diabetes (previously diagnosed or detected by screening) recorded at baseline. Main Outcomes and Measures:All-cause and cause-specific mortality, collected through established death registries. Cox regression was used to estimate adjusted mortality rate ratio (RR) comparing individuals with diabetes vs those without diabetes at baseline. Results:Among the 512?869 participants, the mean (SD) age was 51.5 (10.7) years, 59% (n?=?302?618) were women, and 5.9% (n?=?30?280) had diabetes (4.1% in rural areas, 8.1% in urban areas, 5.8% of men, 6.1% of women, 3.1% had been previously diagnosed, and 2.8% were detected by screening). During 3.64 million person-years of follow-up, there were 24?909 deaths, including 3384 among individuals with diabetes. Compared with adults without diabetes, individuals with diabetes had a significantly increased risk of all-cause mortality (1373 vs 646 deaths per 100?000; adjusted RR, 2.00 [95% CI, 1.93-2.08]), which was higher in rural areas than in urban areas (rural RR, 2.17 [95% CI, 2.07-2.29]; urban RR, 1.83 [95% CI, 1.73-1.94]). Presence of diabetes was associated with increased mortality from ischemic heart disease (3287 deaths; RR, 2.40 [95% CI, 2.19-2.63]), stroke (4444 deaths; RR, 1.98 [95% CI, 1.81-2.17]), chronic liver disease (481 deaths; RR, 2.32 [95% CI, 1.76-3.06]), infections (425 deaths; RR, 2.29 [95% CI, 1.76-2.99]), and cancer of the liver (1325 deaths; RR, 1.54 [95% CI, 1.28-1.86]), pancreas (357 deaths; RR, 1.84 [95% CI, 1.35-2.51]), female breast (217 deaths; RR, 1.84 [95% CI, 1.24-2.74]), and female reproductive system (210 deaths; RR, 1.81 [95% CI, 1.20-2.74]). For chronic kidney disease (365 deaths), the RR was higher in rural areas (18.69 [95% CI, 14.22-24.57]) than in urban areas (6.83 [95% CI, 4.73-9.88]). Among those with diabetes, 10% of all deaths (16% rural; 4% urban) were due to definite or probable diabetic ketoacidosis or coma (408 deaths). Conclusions and Relevance:Among adults in China, diabetes was associated with increased mortality from a range of cardiovascular and noncardiovascular diseases. Although diabetes was more common in urban areas, it was associated with greater excess mortality in rural areas.

Dataset Information

Childhood cause-specific mortality in rural Western Kenya: application of the InterVA-4 model.

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Childhood cause-specific mortality in rural Western Kenya: application of the InterVA-4 model.

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