OBJECTIVES: This study aimed to evaluate knowledge about the disease and assess ways of precautions to be taken during the pandemic.
METHODS: A questionnaire was developed and registered at Google Forms. The study population included dental practitioners, working in hospitals and clinics. A total of 495 dental practitioners from 14 different countries across the world responded. Most dentists were aware of the required modifications in the management of patients. The points allotted for each correct/best answer by participants for a group of questions regarding each component (Knowledge, Perceptions, and Practices) were added/summed to generate an overall score for each of the three components.
RESULTS: Both univariate and multivariate analysis employed for the evaluation of results. Moreover, the total practice score was significantly associated with gender and sector of practice. Multivariable analysis model using multiple linear regressions was formulated by including those variables which were significant at the univariate stage. Hence, the practice sector was the only variable found to be significantly associated with the total knowledge score (p-value
METHODS: In the Prospective Urban Rural Epidemiology (PURE) study, participants aged 35-70 years (n=156 625) were recruited from 110 803 households, in 604 communities and 22 countries; availability (presence of any dose of medication in the pharmacy on the day of audit) and medicine cost data were collected from pharmacies with the Environmental Profile of a Community's Health audit tool. Our primary analysis was to describe the availability and affordability of metformin and insulin and also commonly used and prescribed combinations of two medicines for diabetes management (two oral drugs, metformin plus a sulphonylurea [either glibenclamide (also known as glyburide) or gliclazide] and one oral drug plus insulin [metformin plus insulin]). Medicines were defined as affordable if the cost of medicines was less than 20% of capacity-to-pay (the household income minus food expenditure). Our analyses included data collected in pharmacies and data from representative samples of households. Data on availability were ascertained during the pharmacy audit, as were data on cost of medications. These cost data were used to estimate the cost of a month's supply of essential medicines for diabetes. We estimated affordability of medicines using income data from household surveys.
FINDINGS: Metformin was available in 113 (100%) of 113 pharmacies from high-income countries, 112 (88·2%) of 127 pharmacies in upper-middle-income countries, 179 (86·1%) of 208 pharmacies in lower-middle-income countries, 44 (64·7%) of 68 pharmacies in low-income countries (excluding India), and 88 (100%) of 88 pharmacies in India. Insulin was available in 106 (93·8%) pharmacies in high-income countries, 51 (40·2%) pharmacies in upper-middle-income countries, 61 (29·3%) pharmacies in lower-middle-income countries, seven (10·3%) pharmacies in lower-income countries, and 67 (76·1%) of 88 pharmacies in India. We estimated 0·7% of households in high-income countries and 26·9% of households in low-income countries could not afford metformin and 2·8% of households in high-income countries and 63·0% of households in low-income countries could not afford insulin. Among the 13 569 (8·6% of PURE participants) that reported a diagnosis of diabetes, 1222 (74·0%) participants reported diabetes medicine use in high-income countries compared with 143 (29·6%) participants in low-income countries. In multilevel models, availability and affordability were significantly associated with use of diabetes medicines.
INTERPRETATION: Availability and affordability of essential diabetes medicines are poor in low-income and middle-income countries. Awareness of these global differences might importantly drive change in access for patients with diabetes.
FUNDING: Full funding sources listed at the end of the paper (see Acknowledgments).
METHODS: In an international, community-based prospective study, we enrolled individuals from communities in 17 countries between Jan 1, 2005, and Dec 31, 2009 (except for in Karnataka, India, where enrolment began on Jan 1, 2003). Trained local staff obtained data from participants with interview-based questionnaires, measured weight and height, and recorded forced expiratory volume in 1 s (FEV₁) and forced vital capacity (FVC). We analysed data from participants 130-190 cm tall and aged 34-80 years who had a 5 pack-year smoking history or less, who were not affected by specified disorders and were not pregnant, and for whom we had at least two FEV₁ and FVC measurements that did not vary by more than 200 mL. We divided the countries into seven socioeconomic and geographical regions: south Asia (India, Bangladesh, and Pakistan), east Asia (China), southeast Asia (Malaysia), sub-Saharan Africa (South Africa and Zimbabwe), South America (Argentina, Brazil, Colombia, and Chile), the Middle East (Iran, United Arab Emirates, and Turkey), and North America or Europe (Canada, Sweden, and Poland). Data were analysed with non-linear regression to model height, age, sex, and region.
FINDINGS: 153,996 individuals were enrolled from 628 communities. Data from 38,517 asymptomatic, healthy non-smokers (25,614 women; 12,903 men) were analysed. For all regions, lung function increased with height non-linearly, decreased with age, and was proportionately higher in men than women. The quantitative effect of height, age, and sex on lung function differed by region. Compared with North America or Europe, FEV1 adjusted for height, age, and sex was 31·3% (95% CI 30·8-31·8%) lower in south Asia, 24·2% (23·5-24·9%) lower in southeast Asia, 12·8% (12·4-13·4%) lower in east Asia, 20·9% (19·9-22·0%) lower in sub-Saharan Africa, 5·7% (5·1-6·4%) lower in South America, and 11·2% (10·6-11·8%) lower in the Middle East. We recorded similar but larger differences in FVC. The differences were not accounted for by variation in weight, urban versus rural location, and education level between regions.
INTERPRETATION: Lung function differs substantially between regions of the world. These large differences are not explained by factors investigated in this study; the contribution of socioeconomic, genetic, and environmental factors and their interactions with lung function and lung health need further clarification.
FUNDING: Full funding sources listed at end of the paper (see Acknowledgments).
METHODS: In this international, community-based cohort study, we prospectively enrolled adults aged 35-70 years who had no intention of moving residences for 4 years from rural and urban communities across 17 countries. A portable spirometer was used to assess FEV1. FEV1 values were standardised within countries for height, age, and sex, and expressed as a percentage of the country-specific predicted FEV1 value (FEV1%). FEV1% was categorised as no impairment (FEV1% ≥0 SD from country-specific mean), mild impairment (FEV1% <0 SD to -1 SD), moderate impairment (FEV1%