Spatial heterogeneity and spatially varying determinants of childhood stunting in Northern Rwanda: A cross-sectional study to inform targeted interventions

by Clarisse Kagoyire, Albert Ndagijimana, Gilbert Nduwayezu, Jean Nepo Utumatwishima, Jean Pierre Mpatswenumugabo, Marie Anne Mukasafari, Diane Rinda, Vedaste Ndahindwa, Kristina Elfving, Gunilla Krantz, Torbjörn Lind, Ali Mansourian, Renée Båge, Ewa Wredle, Elias Nyandwi, Aline Umubyeyi, Jean Baptiste Ndahetuye, Petter Pilesjö

Despite national progress, stunting remains prevalent in specific regions of Rwanda, highlighting the limitations of coarse-resolution data for effective mapping and intervention planning. This study explored optimal spatial resolution and analytical approach to capture localised dynamics and the multifactorial nature of stunting. A cross-sectional, population-based study was conducted in the Northern Province of Rwanda, focusing on children aged 1–36 months. Data were collected using structured questionnaires covering socio-demographic, economic, health, childcare, livestock factors and anthropometric measurements. Environmental characteristics were obtained from national datasets, while household geographic coordinates were captured using a customized mobile geodata platform (emGeo). After data cleaning, predictors were analysed using univariable and multivariable logistic regression as well as geographically weighted logistic regression (GWLR) to account for spatial heterogeneity. Among 601 children, stunting prevalence was 27% (boys 33.8%; girls 20.9%). GWLR improved model fit, increasing adjusted deviance explained from 34% to 39%. Significant predictors included child age (adjusted OR = 2.46; 95% CI: 1.78–3.39), male sex (OR = 2.83; 95% CI: 1.65–4.86), birthweight (OR = 0.71; 95% CI: 0.54–0.94), maternal autonomy (ability to refuse sexual intercourse; OR = 0.48; 95% CI: 0.27–0.86), inconsistent maternal social support (OR = 2.30; 95% CI: 1.20–4.42), household electricity access (OR = 0.48; 95% CI: 0.27–0.84) and handwashing facilities (OR = 0.21; 95% CI: 0.07–0.67). GWLR revealed substantial spatial heterogeneity in these factors, delineating areas where each factor matters most. This household-level, spatially explicit analysis reveals localised risk patterns often masked by aggregated national data. Prioritising context-specific interventions (such as electrification, hygiene promotion, and enhanced maternal social support), can enhance effectiveness. The proposed analytical workflow provides a model for addressing persistent stunting in other resource-limited settings.

Stay or go? Exploring physician turnover in European Hospitals–Evidence from the METEOR survey

by Laura Maniscalco, Marco Enea, Peter de Winter, Neeltje de Vries, Anke Boone, Olivia Lavreysen, Kamil Baranski, Walter Mazzucco, Adriano Filadelfio Cracò, Malgorzata Kowalska, Szymon Szemik, Lode Godderis, Domenica Matranga

According to the World Health Organization (WHO), in 2022 there was a shortfall of approximately 1.2 million doctors, impacting healthcare system and patient care. Understanding turnover intentions is crucial for managing the healthcare workforce and ensuring continuous, and high-quality patient care. This study investigates the prevalence of physicians planning to leave their hospital or the profession, and risk factors such as job demand, resources, satisfaction, and burnout across four European countries. A cross-sectional multicenter study was conducted in eight hospitals across Belgium, the Netherlands, Poland and Italy, including both academic and non-academic institutions. Data from Poland were excluded due to a low response rate, to preserve respondent anonymity. Multivariable logistic regression analyses were performed, adjusted for country, demographics, and work context, using significant variables from the univariable analysis. The overall intention to leave the hospital was 16.5%, with the highest rates in Belgium (19.6%) and Italy (19%), and the lowest in the Netherlands (9.8%). The intention to leave the profession was 9.1%, with the highest rate in the Netherlands (16.1%), followed by Belgium (6.3%) and Italy (5.7%). Physicians at higher risk of leaving the hospital were younger (adjOR = 0.90, 95%CI = 0.86–0.93), lacked colleague support (adjOR = 3.18, 95%CI = 1.06–9.36), and were dissatisfied with job prospects (adjOR = 2.38, 95%CI = 1.02–5.54) and overall work (adjOR = 2.71, 95%CI = 1.09–6.69). Those more likely to leave the profession were from the Netherlands (adjOR = 4.14, 95%CI = 1.62–11.4), surgeons (adjOR = 2.90, 95%CI = 1.22–6.78), working in non-academic hospitals (adjOR = 2.43, 95%CI = 1.01–5.97), lacked development opportunities (adjOR = 5.97, 95%CI = 1.01–36.2), or were dissatisfied with career prospects (adjOR = 2.77, 95%CI = 1.04–7.27). Health system managers and relevant stakeholders involved in the planning, implementation, or evaluation of health policies and reforms aimed at improving healthcare job retention should take into account the key determinants of the intention to leave identified in this study.