Sub national variation and inequalities in under-five mortality in Kenya since 1965

Macharia, Peter M.; Giorgi, Emanuele; Thuranira, Pamela N; Joseph, Noel K.; Sartorius, Benn; Snow, Robert W.; Okiro, Emelda A.

doi:10.1186/s12889-019-6474-1

Cited by 22 publications

(47 citation statements)

References 32 publications

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“…By 2017 ( Fig. 1d), neonatal mortality increased as a proportion of total deaths of children under 5 in 91% (90) of countries and for 83% (14,656) of units compared to 2000. In almost all places where U5MR decreased, the share of the mortality burden increased in the groups of children with younger ages.…”

Section: Article Researchmentioning

confidence: 99%

“…Country-level estimates facilitate international comparisons but mask important geographical heterogeneity. Previous assessments of mortality of children under 5 have noted significant within-country heterogeneity, particularly in sub-Saharan Africa 5,7,[10][11][12][13][14] , as well as in Brazil 15 , Iran 16 and China 17 . Understanding public health risks at more granular subpopulation levels is central to the emerging concept of precision public health 18 , which uses "the best available data to target more effectively and efficiently interventions…to those most in need" 18 .…”

Section: Precision Public Health and Child Mortalitymentioning

confidence: 99%

“…Over the 2000-2017 period, this number is 71.8 (68.5-74.9) million deaths, or 58% (55-61) of the total number of deaths of children under 5. Total deaths attributable to inequality in this scenario ranged from 13 (6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19)(20)(21)(22)(23)(24)…”

Section: Article Researchmentioning

confidence: 99%

“…Article reSeArcH roy Burstein 1,612 , Nathaniel J. Henry 1,612 , Michael l. collison 1 , laurie B. Marczak 1 , Amber Sligar 1 , Stefanie Watson 1 , Neal Marquez 1 , Mahdieh Abbasalizad-Farhangi 2 , Masoumeh Abbasi 3 , Foad Abd-Allah 4 , Amir Abdoli 5 , Mohammad Abdollahi 6 , ibrahim Abdollahpour 7,8 , rizwan Suliankatchi Abdulkader 9 , Michael r. M. Abrigo 10 , Dilaram Acharya 11,12 , Oladimeji M. Adebayo 13 , Victor Adekanmbi 14 , Davoud Adham 15 , Mahdi Afshari 16 , Mohammad Aghaali 17 , Keivan Ahmadi 18 , Mehdi Ahmadi 19 , ehsan Ahmadpour 20 , rushdia Ahmed 21,22 , chalachew Genet Akal 23 , Joshua O. Akinyemi 24 , Fares Alahdab 25 , Noore Alam 26 , Genet Melak Alamene 27 , Kefyalew Addis Alene 28,29 , Mehran Alijanzadeh 30 , cyrus Alinia 31 , Vahid Alipour 32,33 , Syed Mohamed Aljunid 34,35 , Mohammed J. Almalki 36,37 , Hesham M. Al-Mekhlafi 38,39 , Khalid Altirkawi 40 , Nelson Alvis-Guzman 41,42 , Adeladza Kofi Amegah 43 , Saeed Amini 44 , Arianna Maever loreche Amit 45,46 , Zohreh Anbari 44 , Sofia Androudi 47 , Mina Anjomshoa 48 , Fereshteh Ansari 49 , carl Abelardo t. Antonio 50,51 , Jalal Arabloo 33 , Zohreh Arefi 52 , Olatunde Aremu 53 , Bahram Armoon 54,55 , Amit Arora 56,57 , Al Artaman 58 , Anvar Asadi 59 , Mehran Asadi-Aliabadi 60 , Amir Ashraf-Ganjouei 7,61 , reza Assadi 62 , Bahar Ataeini...…”

mentioning

confidence: 99%

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Mapping 123 million neonatal, infant and child deaths between 2000 and 2017

Burstein¹,

Henry²,

Collison³

et al. 2019

Nature

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195

180

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Mapping 123 million neonatal, infant and child deaths between 2000 and 2017 Since 2000, many countries have achieved considerable success in improving child survival, but localized progress remains unclear. To inform efforts towards United Nations Sustainable Development Goal 3.2-to end preventable child deaths by 2030-we need consistently estimated data at the subnational level regarding child mortality rates and trends. Here we quantified, for the period 2000-2017, the subnational variation in mortality rates and number of deaths of neonates, infants and children under 5 years of age within 99 low-and middle-income countries using a geostatistical survival model. We estimated that 32% of children under 5 in these countries lived in districts that had attained rates of 25 or fewer child deaths per 1,000 live births by 2017, and that 58% of child deaths between 2000 and 2017 in these countries could have been averted in the absence of geographical inequality. This study enables the identification of high-mortality clusters, patterns of progress and geographical inequalities to inform appropriate investments and implementations that will help to improve the health of all populations. Gains in child survival have long served as an important proxy measure for improvements in overall population health and development 1,2. Global progress in reducing child deaths has been heralded as one of the greatest success stories of global health 3. The annual global number of deaths of children under 5 years of age (under 5) 4 has declined from 19.6 million in 1950 to 5.4 million in 2017. Nevertheless, these advances in child survival have been far from universally achieved, particularly in low-and middle-income countries (LMICs) 4. Previous subnational child mortality assessments at the first (that is, states or provinces) or second (that is, districts or counties) administrative level indicate that extensive geographical inequalities persist 5-7. Progress in child survival also diverges across age groups 4. Global reductions in mortality rates of children under 5-that is, the under-5 mortality rate (U5MR)-among post-neonatal age groups are greater than those for mortality of neonates (0-28 days) 4,8. It is relatively unclear how these age patterns are shifting at a more local scale, posing challenges to ensuring child survival. To pursue the ambitious Sustainable Development Goal (SDG) of the United Nations 9 to "end preventable deaths of newborns and children under 5" by 2030, it is vital for decision-makers at all levels to better understand where, and at what ages, child survival remains most tenuous.

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Section: Article Researchmentioning

confidence: 99%

Section: Precision Public Health and Child Mortalitymentioning

confidence: 99%

Section: Article Researchmentioning

confidence: 99%

mentioning

confidence: 99%

See 2 more Smart Citations

Mapping 123 million neonatal, infant and child deaths between 2000 and 2017

Burstein¹,

Henry²,

Collison³

et al. 2019

Nature

Self Cite

195

180

View full text Add to dashboard Cite

show abstract

“…Thus, the SAE models relied fully on the ANC4 empirical data for the generation of coverage maps. Similar model formulations have been applied elsewhere [12,14].…”

Section: Modelling Sub-county Coverage Using Small Area Estimationmentioning

confidence: 99%

Determinants of subnational disparities in antenatal care utilisation: a spatial analysis of demographic and health survey data in Kenya

Wairoto

Joseph

Macharia

et al. 2020

BMC Health Serv Res

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Background: The spatial variation in antenatal care (ANC) utilisation is likely associated with disparities observed in maternal and neonatal deaths. Most maternal deaths are preventable through services offered during ANC; however, estimates of ANC coverage at lower decision-making units (sub-county) is mostly lacking. In this study, we aimed to estimate the coverage of at least four ANC (ANC4) visits at the sub-county level using the 2014 Kenya Demographic and Health Survey (KDHS 2014) and identify factors associated with ANC utilisation in Kenya. Methods: Data from the KDHS 2014 was used to compute sub-county estimates of ANC4 using small area estimation (SAE) techniques which relied on spatial relatedness to yield precise and reliable estimates at each of the 295 sub-counties. Hierarchical mixed-effect logistic regression was used to identify factors influencing ANC4 utilisation. Sub-county estimates of factors significantly associated with ANC utilisation were produced using SAE techniques and mapped to visualise disparities. Results: The coverage of ANC4 across sub-counties was heterogeneous, ranging from a low of 17% in Mandera West sub-county to over 77% in Nakuru Town West and Ruiru sub-counties. Thirty-one per cent of the 295 subcounties had coverage of less than 50%. Maternal education, household wealth, place of delivery, marital status, age at first marriage, and birth order were all associated with ANC utilisation. The areas with low ANC4 utilisation rates corresponded to areas of low socioeconomic status, fewer educated women and a small number of health facility deliveries. Conclusion: Suboptimal coverage of ANC4 and its heterogeneity at sub-county level calls for urgent, focused and localised approaches to improve access to antenatal care services. Policy formulation and resources allocation should rely on data-driven strategies to guide national and county governments achieve equity in access and utilisation of health interventions.

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Space‐time modeling of child mortality at the Admin‐2 level in a low and middle income countries context

Godwin

Wakefield

2021

Statistics in Medicine

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The Sustainable Development Goals call for a total reduction of preventable child mortality before 2030. Further, the goals state the desirability to have subnational mortality estimates. Estimates at this level are required for health interventions at the subnational level. In a low and middle income countries context, the data on mortality typically consist of household surveys, which are carried out with a stratified, cluster design, and census microsamples. Most household surveys collect full birth history (FBH) data on birth and death dates of a mother's children, but censuses collect summary birth history (SBH) data which consist only of the number of children born and the number that died. In previous work, direct (survey-weighted) estimates with associated variances were derived from FBH data and smoothed in space and time. Unfortunately, the FBH data from household surveys are usually not sufficiently abundant to obtain yearly estimates at the Admin-2 level (at which interventions are often made). In this paper we describe four extensions to previous work: (i) combining SBH data with FBH data, (ii) modeling on a yearly scale, to combine data on a yearly scale with data at coarser time scales, (iii) adjusting direct estimates in Admin-2 areas where we do not observe any deaths due to small sample sizes, (iv) acknowledge differences in data sources by modeling potential bias arising from the various data sources. The methods are illustrated using household survey and census data from Kenya and Malawi, to produce mortality estimates from 1980 to the time of the most recent survey, and predictions to 2020.

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Sub national variation and inequalities in under-five mortality in Kenya since 1965

Cited by 22 publications

References 32 publications

Mapping 123 million neonatal, infant and child deaths between 2000 and 2017

Mapping 123 million neonatal, infant and child deaths between 2000 and 2017

Determinants of subnational disparities in antenatal care utilisation: a spatial analysis of demographic and health survey data in Kenya

Space‐time modeling of child mortality at the Admin‐2 level in a low and middle income countries context

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