Household, community, sub-national and country-level predictors of primary cooking fuel switching in nine countries from the PURE study

Introduction. Switchingfrom polluting (e.g. wood, crop waste, coal)to clean (e.g. gas, electricity) cooking fuels can reduce household air pollution exposures and climate-forcing emissions.While studies have evaluated specific interventions and assessed fuel-switching in repeated cross-sectional surveys, the role of different multilevel factors in household fuel switching, outside of interventions and across diverse community settings, is not well understood. Methods.We examined longitudinal survey data from 24 172 households in 177 rural communities across nine countries within the Prospective Urban and Rural Epidemiology study.We assessed household-level primary cooking fuel switching during a median of 10 years offollow up (∼2005–2015).We used hierarchical logistic regression models to examine the relative importance of household, community, sub-national and national-level factors contributing to primary fuel switching. Results. One-half of study households(12 369)reported changing their primary cookingfuels between baseline andfollow up surveys. Of these, 61% (7582) switchedfrom polluting (wood, dung, agricultural waste, charcoal, coal, kerosene)to clean (gas, electricity)fuels, 26% (3109)switched between different polluting fuels, 10% (1164)switched from clean to polluting fuels and 3% (522)switched between different clean fuels

Nonlinear time series and principal component analyses: Potential diagnostic tools for COVID-19 auscultation

The development of novel digital auscultation techniques has become highly significant in the context of the outburst of the pandemic COVID 19. The present work reports the spectral, nonlinear time series, fractal, and complexity analysis of vesicular (VB) and bronchial (BB) breath signals. The analysis is carried out with 37 breath sound signals. The spectral analysis brings out the signatures of VB and BB through the power spectral density plot and wavelet scalogram. The dynamics of airflow through the respiratory tract during VB and BB are investigated using the nonlinear time series and complexity analyses in terms of the phase portrait, fractal dimension, Hurst exponent, and sample entropy. The higher degree of chaoticity in BB relative to VB is unwrapped through the maximal Lyapunov exponent. The principal component analysis helps in classifying VB and BB sound signals through the feature extraction from the power spectral density data. The method proposed in the present work is simple, cost-effective, and sensitive, with a far-reaching potential of addressing and diagnosing the current issue of COVID 19 through lung auscultation

Unravelling the potential of phase portrait in the auscultation of mitral valve dysfunction

The manuscript elucidates the potential of phase portrait, fast Fourier transform, wavelet, and time-series analyses of the heart murmur (HM) of normal (healthy) and mitral regurgitation (MR) in the diagnosis of valve-related cardiovascular diseases. The temporal evolution study of phase portrait and the entropy analyses of HM unveil the valve dysfunctioninduced haemodynamics. A tenfold increase in sample entropy in MR from that of normal indicates the valve dysfunction. The occurrence of a large number of frequency components between lub and dub in MR, compared to the normal, is substantiated through the spectral analyses. The machine learning techniques, K-nearest neighbour, support vector machine, and principal component analyses give 100% predictive accuracy. Thus, the study suggests a surrogate method of auscultation of HM that can be employed cost-effectively in rural health centres

Time series and fractal analyses of wheezing

Since the outbreak of the pandemic Coronavirus Disease 2019, the world is in search of novel non-invasive methods for safer and early detection of lung diseases. The pulmonary pathological symptoms refected through the lung sound opens a possibility of detection through auscultation and of employing spectral, fractal, nonlinear time series and principal component analyses. Thirty-fve signals of vesicular and expiratory wheezing breath sound, subjected to spectral analyses shows a clear distinction in terms of time duration, intensity, and the number of frequency components. An investigation of the dynamics of air molecules during respiration using phase portrait, Lyapunov exponent, sample entropy, fractal dimension, and Hurst exponent helps in understanding the degree of complexity arising due to the presence of mucus secretions and constrictions in the respiratory airways. The feature extraction of the power spectral density data and the application of principal component analysis helps in distinguishing vesicular and expiratory wheezing and thereby, giving a ray of hope in accomplishing an early detection of pulmonary diseases through sound signal analysis

Assessment of vaccine coverage and associated factors among children in urban agglomerations of Kochi, Kerala, India

Context: Urban population in India is growing exponentially. The public sector urban health delivery system has so far been limited in its reach and is far from adequate. Aims: This study aims to estimate routine immunization coverage and associated factors among children (12–23 months and 60–84 months) in the urban Kochi Metropolitan Area of Kerala. Settings and Design: A cross-sectional study was conducted in Kochi Metropolitan area. Materials and Methods: A cluster sampling technique was used to collect data on immunization status from 310 children aged between 12 and 23 months and 308 children aged between 60 and 84 months. Statistical Analysis: Crude coverage details for each vaccine were estimated using percentages and confidence intervals. Bivariate and multivariate analysis were conducted to identify factors associated with immunization coverage. Results: Among the children aged 12–23 months, 89% (95% CI 85.5%-92.5%) were fully immunized, 10% were partially immunized, and 1% unimmunized. Less than 10 years of schooling among mothers (OR 2.40, 95% CI 1.20–4.81) and living in a nuclear family (OR 1.72, 95% CI 1.06–3.14) were determinants associated with partial or unimmunization of children as per multivariate analysis. The coverage of individual vaccines was found to decrease after 18 months from 90% to 75% at 4–5 years for Diphtheria Pertussis Tetanus (DPT) booster. Bivariate analysis found lower birth order and belonging to the Muslim religion as significant factors for this decrease. Conclusion: Education of the mother and nuclear families emerged as areas of vulnerability in urban immunization coverage. Inadequate social support and competing priorities with regard to balancing work and home probably lead to delay or forgetfulness in vaccination. Therefore, a locally contextualized comprehensive strategy with strengthening of the primary health system is needed to improve the immunization coverage in urban areas