Dataset Information

Mortality in rural coastal Kenya measured using the Kilifi Health and Demographic Surveillance System: a 16-year descriptive analysis.

ABSTRACT: Background: The Kilifi Health and Demographic Surveillance System (KHDSS) was established in 2000 to define the incidence and prevalence of local diseases and evaluate the impact of community-based interventions. KHDSS morbidity data have been reported comprehensively but mortality has not been described. This analysis describes mortality in the KHDSS over 16 years. Methods: We calculated mortality rates from 2003-2018 in four intervals of equal duration and assessed differences in mortality across these intervals by age and sex. We calculated the period survival function and median survival using the Kaplan-Meier method and mean life expectancies using abridged life tables. We estimated trend and seasonality by decomposing a time series of monthly mortality rates. We used choropleth maps and random-effects Poisson regression to investigate geographical heterogeneity. Results: Mortality declined by 36% overall between 2003-2018 and by 59% in children aged <5 years. Most of the decline occurred between 2003 and 2006. Among adults, the greatest decline (49%) was observed in those aged 15-54 years. Life expectancy at birth increased by 12 years. Females outlived males by 6 years. Seasonality was only evident in the 1-4 year age group in the first four years. Geographical variation in mortality was ±10% of the median value and did not change over time. Conclusions: Between 2003 and 2018, mortality among children and young adults has improved substantially. The steep decline in 2003-2006 followed by a much slower reduction thereafter suggests improvements in health and wellbeing have plateaued in the last 12 years. However, there is substantial inequality in mortality experience by geographical location.

SUBMITTER: Otiende M

PROVIDER: S-EPMC10320326 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Mortality in rural coastal Kenya measured using the Kilifi Health and Demographic Surveillance System: a 16-year descriptive analysis.

Otiende Mark M Bauni Evasius E Nyaguara Amek A Amadi David D Nyundo Christopher C Tsory Emmanuel E Walumbe David D Kinuthia Michael M Kihuha Norbert N Kahindi Michael M Nyutu Gideon G Moisi Jennifer J Deribew Amare A Agweyu Ambrose A Marsh Kevin K Tsofa Benjamin B Bejon Philip P Bottomley Christian C Williams Thomas N TN Scott J Anthony G JAG

Wellcome open research 20210101

<b>Background:</b> The Kilifi Health and Demographic Surveillance System (KHDSS) was established in 2000 to define the incidence and prevalence of local diseases and evaluate the impact of community-based interventions. KHDSS morbidity data have been reported comprehensively but mortality has not been described. This analysis describes mortality in the KHDSS over 16 years. <b>Methods:</b> We calculated mortality rates from 2003-2018 in four intervals of equal duration and assessed differences in ...[more]

PMID: 37416502

Similar Datasets

Project description:Background: Endemic and seasonally recurring respiratory viruses are a major cause of disease and death globally. The burden is particularly severe in developing countries. Improved understanding of the source of infection, pathways of spread and persistence in communities would be of benefit in devising intervention strategies. Methods: We report epidemiological data obtained through surveillance of respiratory viruses at nine outpatient health facilities within the Kilifi Health and Demographic Surveillance System, Kilifi County, coastal Kenya, between January and December 2016. Nasopharyngeal swabs were collected from individuals of all ages presenting with acute respiratory infection (ARI) symptoms (up to 15 swabs per week per facility) and screened for 15 respiratory viruses using real-time PCR. Paediatric inpatient surveillance at Kilifi County Hospital for respiratory viruses provided comparative data. Results: Over the year, 5,647 participants were sampled, of which 3,029 (53.7%) were aged <5 years. At least one target respiratory virus was detected in 2,380 (42.2%) of the samples; the most common being rhinovirus 18.6% (1,050), influenza virus 6.9% (390), coronavirus 6.8% (387), parainfluenza virus 6.6% (371), respiratory syncytial virus (RSV) 3.9% (219) and adenovirus 2.7% (155). Virus detections were higher among <5-year-olds compared to older children and adults (50.3% vs 32.7%, respectively; χ 2(1) =177.3, P=0.0001). Frequency of viruses did not differ significantly by facility (χ 2(8) =13.38, P=0.072). However, prevalence was significantly higher among inpatients than outpatients in <5-year-olds for RSV (22.1% vs 6.0%; χ 2(1) = 159.4, P=0.0001), and adenovirus (12.4% vs 4.4%, χ 2(1) =56.6, P=0.0001). Conclusions: Respiratory virus infections are common amongst ARI outpatients in this coastal Kenya setting, particularly in young children. Rhinovirus predominance warrants further studies on the health and socio-economic implications. RSV and adenovirus were more commonly associated with severe disease. Further analysis will explore epidemiological transmission patterns with the addition of virus sequence data.

Project description:Background: Human rhinovirus (HRV) is the predominant cause of upper respiratory tract infections, resulting in a significant public health burden. The virus circulates as many different types (168), each generating strong homologous, but weak heterotypic, immunity. The influence of these features on transmission patterns of HRV in the community is understudied. Methods: Nasopharyngeal swabs were collected from patients with symptoms of acute respiratory infection (ARI) at nine out-patient facilities across a Health and Demographic Surveillance System between December 2015 and November 2016. HRV was diagnosed by real-time RT-PCR, and the VP4/VP2 genomic region of the positive samples sequenced. Phylogenetic analysis was used to determine the HRV types. Classification models and G-test statistic were used to investigate HRV type spatial distribution. Demographic characteristics and clinical features of ARI were also compared. Results: Of 5,744 NPS samples collected, HRV was detected in 1057 (18.4%), of which 817 (77.3%) were successfully sequenced. HRV species A, B and C were identified in 360 (44.1%), 67 (8.2%) and 390 (47.7%) samples, respectively. In total, 87 types were determined: 39, 10 and 38 occurred within species A, B and C, respectively. HRV types presented heterogeneous temporal patterns of persistence. Spatially, identical types occurred over a wide distance at similar times, but there was statistically significant evidence for clustering of types between health facilities in close proximity or linked by major road networks. Conclusion: This study records a high prevalence of HRV in out-patient presentations exhibiting high type diversity. Patterns of occurrence suggest frequent and independent community invasion of different types. Temporal differences of persistence between types may reflect variation in type-specific population immunity. Spatial patterns suggest either rapid spread or multiple invasions of the same type, but evidence of similar types amongst close health facilities, or along road systems, indicate type partitioning structured by local spread.

Project description:BackgroundEstimates 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.MethodsWe 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.FindingsThe 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).InterpretationAdults 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.FundingThe Wellcome Trust, GAVI Alliance.

Project description:PurposeDespite Kenya's encouraging progress in increasing access to modern contraception among youth, several barriers remain preventing large-scale efforts to reduce demand-side unmet need for family planning. Shifting social norms around the use and acceptability of modern contraception may represent a potent target for future interventions. However, the structure of normative influence on individual modern contraceptive use among youth needs to be determined. Therefore, our aim was to estimate the influence of individual and group-level normative influence on modern contraceptive use among adolescents from two villages in rural Kenya.MethodsTrained enumerators collected data from individuals aged 15-24 who provided oral informed consent, or parental informed consent, in two villages in rural Kilifi county. Participants completed a questionnaire related to modern contraceptive use and were asked to nominate one to five people (referents) with whom they spend free time. The enumerators photographed each individual who nominated at least one referent using Android phones and matched them with their nominated referents. Using this social network data, we estimated group-level normative influence by taking an average of referents' modern contraception use. We then explored associations between descriptive norms, injunctive norms, and network modern contraceptive use on individual modern contraceptive use, controlling for known confounders using logistic regression models. We also conducted sensitivity analyses to test a pattern of differential referent influence on individual modern contraceptive use.ResultsThere was a positive association between pro-modern contraception descriptive and injunctive norms and individual modern contraception use (adjusted Odds Ratio (aOR) = 1.29, 95% confidence interval (CI) = 1.05-1.6, and aOR = 1.31, CI = 1.06-1.62, respectively). Network modern contraceptive use was associated with individual use in the bivariate model (aOR = 2.57, CI = 1.6-4.12), but not in the multivariable model (aOR = 1.67, CI = 0.98-2.87). When stratified by sex and marital status, network modern contraceptive use was associated with individual modern contraceptive use among female participants (aOR = 2.9, CI = 1.31-6.42), and unmarried female participants (aOR = 5.26, CI = 1.34-20.69), but not among males. No interactive effects between norms variables were detected. Sensitivity analyses with a different estimate of network modern contraceptive use showed similar results.ConclusionsSocial norms are multilevel phenomena that influence youth modern contraceptive use, especially among young women in rural Kenya. Unmarried women with modern contraceptive users in their social network may feel less stigma to use contraception themselves. This may reflect gendered differences in norms and social influence effects for modern contraceptive use. Future research should investigate group-level normative influence in relation to family planning behaviors.

Dataset Information

Mortality in rural coastal Kenya measured using the Kilifi Health and Demographic Surveillance System: a 16-year descriptive analysis.

Publications

Mortality in rural coastal Kenya measured using the Kilifi Health and Demographic Surveillance System: a 16-year descriptive analysis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets