ABSTRACT
Objective The primary aim of this study was to portray the level of spread and the dynamic of diffusion of mobile phone technology in sub-Saharan Africa during the last two decades. The secondary aim was to investigate factors related to the use of mobile phone technology in sub-Saharan Africa and to derive profiles of the most suitable areas to conduct mobile phone technology-based research. Methods The present work was based on the data collected by the World Bank database;a collection of public access data derived from yearly surveys conducted at country level. Two methods were applied to perform the selection of variables related to the diffusion of mobile phones in sub-Saharan Africa. Firstly, a Least Absolute Shrinkage and Selection Operator (LASSO) regression was applied. Afterwards, a system of simultaneous equation was applied to estimate the model coefficients and determine the joint statistical significance. Results The number of mobile phones subscriptions in relation to the population of sub-Saharan Africa has increased consistently during the period 2000 to 2010. The rate of mobile phones subscriptions in relation to the population ranged between less than 1% to more than 90%. Urban areas and having a lower number of people leaving in slums seems to be the most suitable places to conduct mobile phone-based interviews. This information is useful in identifying countries and macro areas to conduct mobile phone interviews;and this could be extended to smallest area within a country. Discussion More effort is required to better understand how to identify areas suitable for conducting research using mobile phones and other electronic-based tools. Such an effort should be based on individual level surveys to understand not only the material possibility but also the will to participate to research based on data capturing made by mobile phones and similar tools.
ABSTRACT
Background Separate studies suggest that the risks from smoking might vary between high-income (HICs), middle-income (MICs), and low-income (LICs) countries, but this has not yet been systematically examined within a single study using standardised approaches. We examined the variations in risks from smoking across different country income groups and some of their potential reasons. Methods We analysed data from 134 909 participants from 21 countries followed up for a median of 11.3 years in the Prospective Urban Rural Epidemiology (PURE) cohort study;9711 participants with myocardial infarction and 11 362 controls from 52 countries in the INTERHEART case-control study;and 11 580 participants with stroke and 11 331 controls from 32 countries in the INTERSTROKE case-control study. In PURE, all-cause mortality, major cardiovascular disease, cancers, respiratory diseases, and their composite were the primary outcomes for this analysis. Biochemical verification of urinary total nicotine equivalent was done in a substudy of 1000 participants in PURE. Findings In PURE, the adjusted hazard ratio (HR) for the composite outcome in current smokers (vs never smokers) was higher in HICs (HR 1.87, 95% CI 1.65-2.12) than in MICs (1.41, 1.34-1.49) and LICs (1.35, 1 .25-1.46;interaction p<0.0001). Similar patterns were observed for each component of the composite outcome in PURE, myocardial infarction in INTERHEART, and stroke in INTERSTROKE. The median levels of tar, nicotine, and carbon monoxide displayed on the cigarette packs from PURE HICs were higher than those on the packs from MICs. In PURE, the proportion of never smokers reporting high second-hand smoke exposure (>= 1 times/day) was 6.3% in HICs, 23.2% in MICs, and 14.0% in LICs. The adjusted geometric mean total nicotine equivalent was higher among current smokers in HICs (47.2 mu M) than in MICs (31. 1 mu M) and LICs (25.2 mu M;ANCOVA p<0.0001). By contrast, it was higher among never smokers in LICs (18.8 mu M) and MICs (11.3 mu M) than in HICs (5.0 mu M;ANCOVA p=0.0001). Interpretation The variations in risks from smoking between country income groups are probably related to the higher exposure of tobacco-derived toxicants among smokers in HICs and higher rates of high second-hand smoke exposure among never smokers in MICs and LICs. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd.