BACKGROUND: Due to its economic burden and change of focus, there is no gainsaying of the potential impacts of the COVID-19 pandemic on the progress of several female genital mutilation (FGM) interventions across the various countries. However, the magnitude of the potential changes in likelihood and prevalence should be more accurately explored and quantified using a statistically robust comparative study. In this study, we examined the differences in the likelihood and prevalence of FGM among 15-49 years old women before and after the pandemic in Nigeria.
METHODS: We used advanced Bayesian hierarchical models to analyse post-COVID-19 datasets provided by the Multiple Indicator Cluster Surveys (MICS 2021) and pre-COVID-19 data from the Demographic and Health Surveys (DHS 2018).
RESULTS: Results indicated that although there was an overall decline in FGM prevalence nationally, heterogeneities exist at state level and at individual-/community-level characteristics. There was a 6.9% increase in prevalence among women who would like FGM to continue within the community. FGM prevalence increased by 18.9% in Nasarawa, while in Kaduna there was nearly 40% decrease.
CONCLUSIONS: Results show that FGM is still a social norm issue in Nigeria and that it may have been exacerbated by the COVID-19 pandemic. The methods, data and outputs from this study would serve to provide accurate statistical evidence required by policymakers for complete eradication of FGM.

Dementia is a major global public health concern that is increasingly leading to morbidity and mortality among older adults. While studies have focused on the risk factors and care provision, there is currently limited knowledge about the spatial risk pattern of the disease. In this study, we employ Bayesian spatial modelling with a stochastic partial differential equation (SPDE) approach to model the spatial risk using complete residential history data from the Danish population and health registers. The study cohort consisted of 1.6 million people aged 65 years and above from 2005 to 2018. The results of the spatial risk map indicate high-risk areas in Copenhagen, southern Jutland and Funen. Individual socioeconomic factors and population density reduce the intensity of high-risk patterns across Denmark. The findings of this study call for the critical examination of the contribution of place of residence in the susceptibility of the global ageing population to dementia.

The onset of COVID-19 across the world has elevated interest in geographic information systems (GIS) for pandemic management. In Germany, however, most spatial analyses remain at the relatively coarse level of counties. In this study, we explored the spatial distribution of COVID-19 hospitalizations in health insurance data of the AOK Nordost health insurance. Additionally, we explored sociodemographic and pre-existing medical conditions associated with hospitalizations for COVID-19. Our results clearly show strong spatial dynamics of COVID-19 hospitalizations. The main risk factors for hospitalization were male sex, being unemployed, foreign citizenship, and living in a nursing home. The main pre-existing diseases associated with hospitalization were certain infectious and parasitic diseases, diseases of the blood and blood-forming organs, endocrine, nutritional and metabolic diseases, diseases of the nervous system, diseases of the circulatory system, diseases of the respiratory system, diseases of the genitourinary and symptoms, and signs and findings not classified elsewhere.

The current study explores the spatial patterns of underweight and overweight among adult men and women in districts of India and identifies the micro-geographical locations where the risks of underweight and overweight are simultaneously prevalent, after accounting for demographic and socio-economic factors.
We relied on BMI (weight (kg)/height squared (m2)), a measure of nutritional status among adult individuals, from the 2015-2016 National Family and Health Survey. Underweight was defined as <18·5 kg/m2 and overweight as ≥25·0 kg/m2.
We adopted Bayesian structured additive quantile regression to model the underlying spatial structure in underweight and overweight burden.
Men aged 15-54 years (sample size: 108 092) and women aged 15-49 years (sample size: 642 002).
About 19·7 % of men and 22·9 % of women were underweight, and 19·6 % of men and 20·6 % of women were overweight. Results indicate that malnutrition burden in adults exhibits geographical divides across the country. Districts located in the central, western and eastern regions show higher risks of underweight. There is evidence of substantial spatial clustering of districts with higher risk of overweight in southern and northern India. While finding a little evidence on double burden of malnutrition among population groups, we identified a total of sixty-six double burden districts.
The current study demonstrates that the geographical burden of overweight in Indian adults is yet to surpass that of underweight, but the coexistence of double burden of underweight and overweight in selected regions presents a new challenge for improving nutritional status and necessitates specialised policy initiatives.

The aetiology of most childhood cancers is largely unknown. Spatially varying environmental factors such as traffic-related air pollution, background radiation and agricultural pesticides might contribute to the development of childhood cancer. This study is the first investigation of the spatial disease mapping of childhood cancers using exact geocodes of place of residence.
We included 5947 children diagnosed with cancer in Switzerland during 1985-2015 at 0-15 years of age from the Swiss Childhood Cancer Registry. We modelled cancer risk using log-Gaussian Cox processes and indirect standardisation to adjust for age and year of diagnosis. We examined whether the spatial variation of risk can be explained by modelled ambient air concentration of NO2, modelled exposure to background ionising radiation, area-based socio-economic position (SEP), linguistic region, duration in years of general cancer registration in the canton or degree of urbanisation.
For all childhood cancers combined, the posterior median relative risk (RR), compared to the national level, varied by location from 0.83 to 1.13 (min to max). Corresponding ranges were 0.96 to 1.09 for leukaemia, 0.90 to 1.13 for lymphoma, and 0.82 to 1.23 for central nervous system (CNS) tumours. The covariates considered explained 72% of the observed spatial variation for all cancers, 81% for leukaemia, 82% for lymphoma and 64% for CNS tumours. There was weak evidence of an association of CNS tumour incidence with modelled exposure to background ionising radiation (RR per SD difference 1.17; 0.98-1.40) and with SEP (1.6; 1.00-1.13).
Of the investigated diagnostic groups, childhood CNS tumours showed the largest spatial variation. The selected covariates only partially explained the observed variation of CNS tumours suggesting that other environmental factors also play a role.

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