Dataset Information

Investigating associations between rural-to-urban migration and cardiometabolic disease in Malawi: a population-level study.

ABSTRACT:

Background

The extent to which rural-to-urban migration affects risk for cardiometabolic diseases (CMD) in Africa is not well understood. We investigated prevalence and risk for obesity, diabetes, hypertension and precursor conditions by migration status.

Methods

In a cross-sectional survey in Malawi (February 2013-March 2017), 13?903 rural, 9929 rural-to-urban migrant and 6741 urban residents (?18?years old) participated. We interviewed participants, measured blood pressure and collected anthropometric data and fasting blood samples to estimate population prevalences and odds ratios, using negative binomial regression, for CMD, by migration status. In a sub-cohort of 131 rural-urban siblings-sets, migration-associated CMD risk was explored using conditional Poisson regression.

Results

In rural, rural-to-urban migrant and urban residents, prevalence estimates were; 8.9, 20.9 and 15.2% in men and 25.4, 43.9 and 39.3% in women for overweight/obesity; 1.4, 2.9 and 1.9% in men and 1.5, 2.8 and 1.7% in women for diabetes; and 13.4, 18.8 and 12.2% in men and 13.7, 15.8 and 10.2% in women for hypertension. Rural-to-urban migrants had the greatest risk for hypertension (adjusted relative risk for men 1.18; 95% confidence interval 1.04-1.34 and women 1.17: 95% confidence interval 1.05-1.29) and were the most screened, diagnosed and treated for CMD, compared with urban residents. Within sibling sets, rural-to-urban migrant siblings had a higher risk for overweight and pre-hypertension, with no evidence for differences by duration of stay.

Conclusions

Rural-to-urban migration is associated with increased CMD risk in Malawi. In a poor country experiencing rapid urbanization, interventions for the prevention and management of CMD, which reach migrant populations, are needed.

SUBMITTER: Chilunga FP

PROVIDER: S-EPMC6929524 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Investigating associations between rural-to-urban migration and cardiometabolic disease in Malawi: a population-level study.

Chilunga Felix P FP Musicha Crispin C Tafatatha Terence T Geis Steffen S Nyirenda Moffat J MJ Crampin Amelia C AC Price Alison J AJ

International journal of epidemiology 20191201 6

<h4>Background</h4>The extent to which rural-to-urban migration affects risk for cardiometabolic diseases (CMD) in Africa is not well understood. We investigated prevalence and risk for obesity, diabetes, hypertension and precursor conditions by migration status.<h4>Methods</h4>In a cross-sectional survey in Malawi (February 2013-March 2017), 13 903 rural, 9929 rural-to-urban migrant and 6741 urban residents (≥18 years old) participated. We interviewed participants, measured blood pressure and c ...[more]

PMID: 31603469

Similar Datasets

Project description:Atmospheric particulate matter (PM) is a recognized risk factor for the global burden of disease in human populations. We are presenting here the application of toxicogenomics in the evaluation of the toxic effects of organic content of atmospheric particle matter (PM), from urban and rural environments (city of Barcelona and village of La Pobla, NE Spain), using the developing zebrafish embryo. The main goal is to identify the metabolic pathways involved in the adverse effects observed in zebrafish embryos exposed to PM organic content from urban and rural environments, also allowing the selection of genes of interest that are differentially expressed. The relevance of particle size to the PM toxicity is also addressed. Indeed, the zebrafish embryos were exposed to PM of aerodynamic diameter larger than 7.2 Î¼m and smaller than 0.5 Î¼m (PM10 and PM0.5, respectively). PM0.5 concentrated biological and toxic activities linked to organic substances. Transcriptomic analyses showed strong induction of the AhR signalling pathway (a.k.a. dioxin-like activity) for embryos exposed to both rural and urban extracts, correlating with the concentrations of PAHs. Urban extracts, with strong contribution of traffic emissions, specifically de-regulated oxidative stress-related genes, as well as pancreatic and eye-lens specific genes, two organs known to be affected by air pollution in humans. Exposure to rural extracts, with high contribution of wood burning emissions, affected genes implicated in basic cellular functions, in agreement with their strong embryotoxicity. Extracts from rural and urban samples elicited both common and specific transcriptome responses, suggesting different potentially adverse outcomes depending on PM source and composition. The authors thank the financial support of the Spanish Ministry (project TEA-PARTICLE, grant number CGL2011-29621) and the Portuguese Foundation for Science and Technology for the doctoral grant of Sofia R. Mesquita (SFRH/BD/80710/2011) funded by the Program POPH-QREN through the Portuguese Ministry of Education and Science and the European Social Fund, and support through project PEst-C/MAR/LA0015/2013. The PM filter samples used in the present study were PM10 and PM0.5 from the urban site - total of 4 samples from 2 sampling months; and PM0.5 from the rural site - total of 2 samples from 2 sampling months (PM10 samples from the rural site were not tested due to their very low concentration in organic compounds, and insignificant biological activity, previously measured). Sampling occurred during the cold periods of the year 2012/2013. The organic fraction of PM samples was extracted by sonication using a mixture of dichloromethane:methanol. Then, the extracts were filtered, evaporated and re-dissolved in Dimethyl sulfoxide (DMSO). Zebrafish fertilized eggs were exposed to PM organic extracts (0.2% DMSO) from the urban and rural sites from 24 to 120h post-fertilization. Total RNA was isolated from whole embryos (pools of 20 individuals), using Trizol reagent protocol (Invitrogen Life Technologies, Carlsberg, CA). The microarray study was performed using the Agilent Two-colour D. rerio Oligo Microarray v3 platform, following the Agilent Microarray â?? Based Gene Expression Analysis protocol. Three biological replicates were performed for each PM sample and controls. Biological replicates, a technical replicate and a self-to-self, were simultaneously amplified and labelled using Cyanine 3 (Cy3) and Cyanine 5 (Cy5) dye. After cRNA purification (RNeasy Kit, Quiagen GmbH, Hilden, Germany), the cRNA concentration and labelling were quantified in the NanoDrop spectrophotometer, obtaining incorporation rates in the range of 15-20pmol of cyanide dye/Âµl cRNA and yield values > 0.825ug, as recommended. cRNA was fragmented and hybridized in 4x44K arrays, for 17h at 65oC. After the hybridization the array slides were washed, and immediately scanned using Microarray Scanner Agilent G2505C system. Data was extracted using Agilent Feature Extraction Software v10.5.1.1, and the quality of microarray data was evaluated using the Quality Control report provided by Agilent Software. Based on the microarray data analysis, 22 primers were selected and designed using Primer Express 2.0 software (Applied Biosystems, Foster City, CA). Genes were quantified by real-time PCR to validate the microarray data, and a subset of 13 genes were further selected by their robust behaviour in the validation assays, allowing to differentiate the toxic potential of PM from urban and rural sources.

Project description:BackgroundWith the availability of multiple Coronavirus Disease 2019 (COVID-19) vaccines and the predicted shortages in supply for the near future, it is necessary to allocate vaccines in a manner that minimizes severe outcomes, particularly deaths. To date, vaccination strategies in the United States have focused on individual characteristics such as age and occupation. Here, we assess the utility of population-level health and socioeconomic indicators as additional criteria for geographical allocation of vaccines.Methods and findingsCounty-level estimates of 14 indicators associated with COVID-19 mortality were extracted from public data sources. Effect estimates of the individual indicators were calculated with univariate models. Presence of spatial autocorrelation was established using Moran's I statistic. Spatial simultaneous autoregressive (SAR) models that account for spatial autocorrelation in response and predictors were used to assess (i) the proportion of variance in county-level COVID-19 mortality that can explained by identified health/socioeconomic indicators (R2); and (ii) effect estimates of each predictor. Adjusting for case rates, the selected indicators individually explain 24%-29% of the variability in mortality. Prevalence of chronic kidney disease and proportion of population residing in nursing homes have the highest R2. Mortality is estimated to increase by 43 per thousand residents (95% CI: 37-49; p < 0.001) with a 1% increase in the prevalence of chronic kidney disease and by 39 deaths per thousand (95% CI: 34-44; p < 0.001) with 1% increase in population living in nursing homes. SAR models using multiple health/socioeconomic indicators explain 43% of the variability in COVID-19 mortality in US counties, adjusting for case rates. R2 was found to be not sensitive to the choice of SAR model form. Study limitations include the use of mortality rates that are not age standardized, a spatial adjacency matrix that does not capture human flows among counties, and insufficient accounting for interaction among predictors.ConclusionsSignificant spatial autocorrelation exists in COVID-19 mortality in the US, and population health/socioeconomic indicators account for a considerable variability in county-level mortality. In the context of vaccine rollout in the US and globally, national and subnational estimates of burden of disease could inform optimal geographical allocation of vaccines.

Dataset Information

Investigating associations between rural-to-urban migration and cardiometabolic disease in Malawi: a population-level study.

Background

Methods

Results

Conclusions

Publications

Investigating associations between rural-to-urban migration and cardiometabolic disease in Malawi: a population-level study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets