Evidence map›Paper›PMID 39572746›Full record

ArticleScientific reports2024

Understanding demographic events and migration patterns in two urban slums of Nairobi City in Kenya.

Evans Omondi, Samuel Iddi, Sharon Chepkemoi, Bylhah Mugotitsa, Steve Cygu, Boscow Okumu, Abdhalah Ziraba, Damazo T Kadengye, Agnes Kiragga

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Performance of Road-Traffic-Based Exposure Proxies Against Personal PMmedRxiv : the preprint server for health sciences · 2026
    Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Evans OmondiAfrican Population and Health Research Center (APHRC), Nairobi, Kenya. evansotieno@aims.ac.za.
Samuel IddiAfrican Population and Health Research Center (APHRC), Nairobi, Kenya.
Sharon ChepkemoiAfrican Population and Health Research Center (APHRC), Nairobi, Kenya.
Bylhah MugotitsaAfrican Population and Health Research Center (APHRC), Nairobi, Kenya.
Steve CyguAfrican Population and Health Research Center (APHRC), Nairobi, Kenya.
Boscow OkumuAfrican Population and Health Research Center (APHRC), Nairobi, Kenya.
Abdhalah ZirabaAfrican Population and Health Research Center (APHRC), Nairobi, Kenya.
Damazo T KadengyeAfrican Population and Health Research Center (APHRC), Nairobi, Kenya.
Agnes KiraggaAfrican Population and Health Research Center (APHRC), Nairobi, Kenya.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding the dynamics of movements between different demographic events is essential for informing effective population management strategies. This study aims to characterize the trajectories of demographic and other vital events within the Nairobi Urban Health and Demographic Surveillance System (NUHDSS). Thus, it intends to unravel patterns and trends that can guide the development of targeted policies and interventions to address the population's evolving needs. Using a continuous-time homogeneous multi-state Markov model, longitudinal data from 223,350 individuals in Korogocho and Viwandani urban slums, we study the enumeration, births, deaths, and migrations among urban poor in Nairobi, shedding light on population dynamics and movements over time, disaggregated by gender. Findings indicate a positive net migration in population per thousand in 2002, dropping in 2004, with Viwandani consistently showing higher birth rates than Korogocho. Males generally have higher death rates than females. Females from Viwandani are 39.0% more likely to exit after enumeration compared to Korogocho, while males are 35.6% more likely to move from enumeration to exit compared to males from Korogocho. Both genders from Viwandani have a decreased likelihood of moving from birth to death compared to Korogocho. Our findings provide unique insights into migration in urban Kenya, the frequency and movement to different demographic events and any gender differences that warrant strategic policies for effective population and health planning in Africa. These findings can inform the design of effective health interventions that are often affected by migration and population growth.

Indexed as

Population DynamicsPoverty AreasUrban PopulationAdolescentAdultChildChild, PreschoolCitiesDemographyFemaleHumansInfantInfant, NewbornKenyaMaleMiddle AgedDemographyMigrationMulti-state modelPopulationSurveillanceUrban slums

Identifiers

PMID39572746
PMCPMC11582661

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.