Copula geoadditive modelling of anaemia and malaria in young children in Kenya, Malawi, Tanzania and Uganda

An analysis of the dual burden of childhood stunting and wasting in Myanmar: a copula geoadditive modelling approach

OBJECTIVE

To analyze the spatial variation and risk factors of the dual burden of childhood stunting and wasting in Myanmar.

DESIGN

Analysis was carried out on nationally representative data obtained from the Myan-mar Demographic and Health Survey conducted during 2015-2016. Childhood stunting and wasting are used as proxies of chronic and acute childhood undernutrition. A child with standardized height-for-age Z score (HAZ) below -2 is categorized as stunted while that with a weight-for-height Z score (WHZ) below -2 as wasted.

SETTING

A nationally representative sample of households from the 15 states and regions of Myanmar.

PARTICIPANTS

Children under the age of five (n 4162).

RESULTS

Overall marginal prevalence of childhood stunting and wasting were 28.9% (95% CI 27.5, 30.2) and 7.3% (95% CI 6.5, 8.0) while their concurrent prevalence was 1.6% (95% CI 1.2, 2.0). The study revealed mild positive association between stunting and wasting across Myanmar. Both stunting and wasting had significant spatial variation across the country with eastern regions having higher burden of stunting while southern regions having higher prevalence of wasting. Child age and maternal weight-for-height Z score had significant non- linear association with both stunting and wasting while child gender, ethnicity and household wealth quintile had significant association with stunting.

CONCLUSION

The study provides data-driven evidence about the association between stunting and wasting and their spatial variation across Myanmar. The resulting insights can aid in the formulation and implementation of targeted, region-specific interventions towards improving the state of childhood under-nutrition in Myanmar.

A Systematic Review of Joint Spatial and Spatiotemporal Models in Health Research

With the advancement of spatial analysis approaches, methodological research addressing the technical and statistical issues related to joint spatial and spatiotemporal models has increased. Despite the benefits of spatial modelling of several interrelated outcomes simultaneously, there has been no published systematic review on this topic, specifically when such models would be useful. This systematic review therefore aimed at reviewing health research published using joint spatial and spatiotemporal models. A systematic search of published studies that applied joint spatial and spatiotemporal models was performed using six electronic databases without geographic restriction. A search with the developed search terms yielded 4077 studies, from which 43 studies were included for the systematic review, including 15 studies focused on infectious diseases and 11 on cancer. Most of the studies (81.40%) were performed based on the Bayesian framework. Different joint spatial and spatiotemporal models were applied based on the nature of the data, population size, the incidence of outcomes, and assumptions. This review found that when the outcome is rare or the population is small, joint spatial and spatiotemporal models provide better performance by borrowing strength from related health outcomes which have a higher prevalence. A framework for the design, analysis, and reporting of such studies is also needed.

Copula Geo-Additive Modeling of Anaemia and Malnutrition among Children under Five Years in Angola, Senegal, and Malawi

Notwithstanding the interventions implemented to address child mortality, anaemia and malnutrition remain a concern for the future of developing countries. Anaemia and malnutrition contribute a high proportion of the causes of childhood morbidity in Africa. The objective of this study is to jointly model anaemia and malnutrition using a copula geo-additive model. This study is a secondary data analysis where a Demographic and Health Survey of 2016 data from Angola, Malawi, and Senegal was used. The descriptive analysis was conducted in SPSS and the copula geo-additive model analysis was performed in R 3.63. The results showed that female children are notably associated with anaemia and a malnourished status (female estimate = 0.144, p-value = 0.027 for anaemia; female estimate = −0.105, p-value = 000 for malnutrition). The probability of each result decreased with an improvement in the mother’s level of schooling. This indicates an urgent requirement for interventions to be implemented by policymakers in order to manage children’s mortality rates. These interventions can include the introduction of educational programs for older adults, children’s dietary programs, and income generation initiatives (starting a small business, etc.). It is hoped that this paper can foster the utilization of copula methodology in this field of science with the use of cross-sectional data.

Modeling Time to Blindness of Glaucoma Patients: A Case Study at Jimma University Medical Center

BACKGROUND

Glaucoma is a significant public health problem due to its substantial increase in the projected number of glaucoma cases. In Ethiopia, glaucoma accounts for 5.2% of irreversible blindness and is the fifth main cause of blindness. The main objective of this study was to modeling time to blindness of left and right eyes of glaucoma patients.

STUDY DESIGN

An institution-based retrospective cohort study.

METHODS

This study was conducted among 315 glaucoma patients admitted to the Ophthalmology Department of Jimma University Medical Center (JUMC), Southwest Ethiopia, from January 1, 2016, to August 30, 2020. Kaplan-Meier survival analysis and semiparametric and parametric copula models were applied to identify factors that affect time to the blindness in glaucoma patients and the dependence between time to the blindness of the left and right eyes, respectively. An Akaike information criterion (AIC) was used to select the best non-nested model.

RESULTS

In total, 211 (66.9%) out of 315 glaucoma patients were blind, whereas 104 (33.1%) patients were censored. The median time to the blindness of the left and right eyes was determined to be 12 months. The result suggested that the risk of the blindness in male patients was 1.005 (P = 0.01) times higher than that in female patients, and the risk of the blindness in patients who had early, moderate, and advanced glaucoma was estimated to be 0.582 (P = 0.002), 0.485 (P = 0.001) and 0.887 (P = 0.003) times less than that in the patients with absolute glaucoma, respectively.

CONCLUSIONS

Age, place of residence, gender, type of medication, diabetes disease, stage of glaucoma, duration of treatment, intraocular pressure (IOP), and cup-disk ratio were significantly associated with and affected by the time to the blindness of left and right eyes in glaucoma patients. Awareness should be given to the community to reduce the burden of glaucoma.

Joint modelling of malaria and anaemia in children less than five years of age in Malawi

BACKGROUND

Malaria and anaemia jointly remain a public health problem in developing countries of which Malawi is one. Although there is an improvement along with intervention strategies in fighting against malaria and anaemia in Malawi, the two diseases remain significant problems, especially in children 6-59 months of age. The main objective of this study was to examine the association between malaria and anaemia. Moreover, the study investigated whether socio-economic, geographic, and demographic factors had a significant impact on malaria and anaemia.

DATA AND METHODOLOGY

The present study used a secondary cross-sectional data set from the 2017 Malawi Malaria Indicator Survey (MMIS) with a total number of 2 724 children 6-9 months of age. The study utilized a multivariate joint model within the ambit of the generalized linear mixed model (GLMM) to analyse the data. The two response variables for this study were: the child has either malaria or anaemia.

RESULTS

The prevalence of malaria was 37.2% of the total number of children who were tested using an RDT, while 56.9% were anaemic. The results from the multivariate joint model under GLMM indicated a positive association between anaemia and malaria. Furthermore, the same results showed that mother's education level, child's age, the altitude of the place of residence, place of residence, toilet facility, access to electricity and children who slept under a mosquito bed net the night before the survey had a significant effect on malaria and anaemia.

CONCLUSION

The study indicated that there is a strong association between anaemia and malaria. This is interpreted to indicate that controlling for malaria can result in a reduction of anaemia. The socio-economic, geographical and demographic variables have a significant effect on improving malaria and anaemia. Thus, improving health care, toilet facilities, access to electricity, especially in rural areas, educating the mothers of children and increasing mosquito bed nets would contribute in the reduction of malaria and anaemia in Malawi.