Classifying European cigarette consumption trajectories from 1970 to 2015.

OBJECTIVES: To systematically code and classify longitudinal cigarette consumption trajectories in European countries since 1970. DESIGN: Blinded duplicate qualitative coding of periods of year-over-year relative increase, plateau, and decrease of national per capita cigarette consumption and categorisation of historical cigarette consumption trajectories based on longitudinal patterns emerging from the data. SETTING: 41 countries or former countries in the European region for which data are available between 1970 and 2015. RESULTS: Regional trends in longitudinal consumption patterns identify stable or decreasing consumption throughout Northern, Western and Southern European countries, while Eastern and Southeastern European countries experienced much greater instability. The 11 emergent classes of historical cigarette consumption trajectories were also regionally clustered, including a distinctive inverted U or sine wave pattern repeatedly emerging from former Soviet and Southeastern European countries. CONCLUSIONS: The open-access data produced by this study can be used to conduct comparative international evaluations of tobacco control policies by separating impacts likely attributable to gradual long-term trends from those more likely attributable to acute short-term events. The complex, regionally clustered historical trajectories of cigarette consumption in Europe suggest that the enduring normative frame of a gently sloping downward curve in cigarette consumption can offer a false sense of security among policymakers and can distract from plausible causal mechanisms among researchers. These multilevel and multisectoral causal mechanisms point to the need for a greater understanding of the political economy of regional and global determinants of cigarette consumption.

Beyond MPOWER: a systematic review of population-level factors that affect European tobacco smoking rates.

BACKGROUND: Population-level factors within and beyond the scope of the World Health Organization's (WHO) MPOWER policy package have significant impacts on smoking rates. However, no synthesis of the existing evidence exists. This systematic review identifies population-level factors that influence cigarette smoking rates in European countries. METHODS: We searched the ProQuest database collection for original, peer-reviewed quantitative evaluations that investigated the effects of population-level exposures on smoking rates in European countries. Of the 3122 studies screened, 62 were ultimately included in the review. A standardized data extraction form was used to identify key characteristics of each study including publication year, years evaluated, countries studied, population characteristics, study design, data sources, analytic methods, exposure studied, relevant covariates and effects on tobacco smoking outcomes. RESULTS: One hundred and fifty-five population-level exposures were extracted from the 62 studies included in the review, 99 of which were related to WHO MPOWER measures. An additional 56 exposures fell into eight policy realms: economic crises, education policy, macro-economic factors, non-MPOWER tobacco regulations, population welfare, public policy, sales to minors and unemployment rates. About one-half of the MPOWER exposures affected smoking rates (55/99) and did so in an overwhelmingly positive way (55/55). Over three-quarters of the non-MPOWER exposures were associated with statistically significant changes in smoking outcomes (43/56), with about two-thirds of these exposures leading to a decrease in smoking (29/43). CONCLUSIONS: Population-level factors that fall outside of the WHO's MPOWER measures are an understudied research area. The impacts of these factors on tobacco control should be considered by policymakers.

Validating mental health assessment in Kenya using an innovative gold standard.

With the growing burden of mental health disorders worldwide, alongside efforts to expand availability of evidence-based interventions, strategies are needed to ensure accurate identification of individuals suffering from mental disorders. Efforts to locally validate mental health assessments are of particular value, yet gold-standard clinical validation is costly, time-intensive, and reliant on available professionals. This study aimed to validate assessment items for mental distress in Kenya, using an innovative gold standard and a combination of culturally adapted and locally developed items. The mixed-method study drew on surveys and semi-structured interviews, conducted by lay interviewers, with 48 caregivers. Interviews were used to designate mental health "cases" or "non-cases" based on emotional health problems, identified through a collaborative clinical rating process with local input. Individual mental health survey items were evaluated for their ability to discriminate between cases and non-cases. Discriminant survey items included 23 items adapted from existing mental health assessment tools, as well as 6 new items developed for the specific cultural context. When items were combined into a scale, results showed good psychometric properties. The use of clinically rated semi-structured interviews provides a promising alternative gold standard that can help address the challenges of conducting diagnostic clinical validation in low-resource settings.

Is Malaria an Important Cause of Death among Adults?

A long-held assumption has been that nearly all malaria deaths in high-transmission areas are of children younger than 5 years and pregnant women. Most global malaria mortality estimates incorporate this assumption in their calculations. In 2010, the Indian Million Death Study, which assigns cause of death by verbal autopsy (VA), challenged the reigning perception, producing a U-shaped mortality age curve, with rates rising after age 45 years in areas of India with substantial malaria transmission. Similar patterns are seen in Africa in the International Network for the Demographic Evaluation of Populations and Their Health (INDEPTH) network, also relying on VA. Whether these results are accurate or are misidentified deaths can be resolved by improving the evidence for assigning causes for adult acute infectious deaths in high malaria transmission areas. The options for doing so include improving the accuracy of VA and adding postmortem biological evidence, steps we believe should be initiated without delay.

Geospatial, racial, and educational variation in firearm mortality in the USA, Mexico, Brazil, and Colombia, 1990-2015: a comparative analysis of vital statistics data.

BACKGROUND: Firearm mortality is a leading, and largely avoidable, cause of death in the USA, Mexico, Brazil, and Colombia. We aimed to assess the changes over time and demographic determinants of firearm deaths in these four countries between 1990 and 2015. METHODS: In this comparative analysis of firearm mortality, we examined national vital statistics data from 1990-2015 from four publicly available data repositories in the USA, Mexico, Brazil, and Colombia. We extracted medically-certified deaths and underlying population denominators to calculate the age-specific and sex-specific firearm deaths and the risk of firearm mortality at the national and subnational level, by education for all four countries, and by race or ethnicity for the USA and Brazil. Analyses were stratified by intent (homicide, suicide, unintentional, or undetermined). We quantified avoidable mortality for each country using the lowest number of subnational age-specific and period-specific death rates. FINDINGS: Between 1990 and 2015, 106·3 million medically-certified deaths were recorded, including 2 472 000 firearm deaths, of which 851 000 occurred in the USA, 272 000 in Mexico, 855 000 in Brazil, and 494 000 in Colombia. Homicides accounted for most of the firearm deaths in Mexico (225 000 [82·7%]), Colombia (463 000 [93·8%]), and Brazil (766 000 [89·5%]). Suicide accounted for more than half of all firearm deaths in the USA (479 000 [56·3%]). In each country, firearm mortality was highest among men aged 15-34 years, accounting for up to half of the total risk of death in that age group. During the study period, firearm mortality risks increased in Mexico and Brazil but decreased in the USA and Colombia, with marked national and subnational geographical variation. Young men with low educational attainment were at increased risk of firearm homicide in all four countries, and in the USA and Brazil, black and brown men, respectively, were at the highest risk. The risk of firearm homicide was 14 times higher in black men in the USA aged 25-34 years with low educational attainment than comparably-educated white men (1·52% [99% CI 1·50-1·54] vs 0·11% [0·10-0·12]), and up to four times higher than in comparably-educated men in Brazil, Colombia, and Mexico. In the USA, the risk of firearm homicide was more than 30 times higher in black men with post-secondary education than comparably educated white men. If countries could achieve the same firearm mortality rates nationally as in their lowest-burden states, 1 777 800 firearm deaths at all ages and in both sexes could be avoided, including 1 028 000 deaths in men aged 15-34 years. INTERPRETATION: Firearm mortality in the USA, Mexico, Brazil, and Colombia is highest among young adult men, and is strongly associated with race and ethnicity, and low education levels. Reductions in firearm deaths would improve life expectancy, particularly for black men in the USA, and would reduce racial and educational disparities in mortality. FUNDING: Canadian Institutes of Health Research and the University of Toronto Connaught Global Challenge.

National Burden Estimates of healthy life lost in India, 2017: an analysis using direct mortality data and indirect disability data.

BACKGROUND: Many countries, including India, seek locally constructed disease burden estimates comprising mortality and loss of health to aid priority setting for the prevention and treatment of diseases. We created the National Burden Estimates (NBE) to provide transparent and understandable disease burdens at the national and subnational levels, and to identify gaps in knowledge. METHODS: To calculate the NBE for India, we combined 2017 UN death totals with national and subnational mortality rates for 2010-17 and causes of death from 211 166 verbal autopsy interviews in the Indian Million Death Study for 2010-14. We calculated years of life lost (YLLs) and years lived with disability (YLDs) for 2017 using published YLD-YLL ratios from WHO Global Health Estimates. We grouped causes of death into 45 groups, including ill-defined deaths, and summed YLLs and YLDs to calculate disability-adjusted life-years (DALYs) for these causes in eight age groups covering rural and urban areas and 21 major states of India. FINDINGS: In 2017, there were about 9·7 million deaths and 486 million DALYs in India. About three quarters of deaths and DALYs occurred in rural areas. More than a third of national DALYs arose from communicable, maternal, perinatal, and nutritional disorders. DALY rates in rural areas were at least twice those of urban areas for perinatal and nutritional conditions, chronic respiratory diseases, diarrhoea, and fever of unknown origin. DALY rates for ischaemic heart disease were greater in urban areas. Injuries caused 11·4% of DALYs nationally. The top 15 conditions that accounted for the most DALYs were mostly those causing mortality (ischaemic heart disease, perinatal conditions, chronic respiratory diseases, diarrhoea, respiratory infections, cancer, stroke, road traffic accidents, tuberculosis, and liver and alcohol-related conditions), with disability mostly due to a few conditions (nutritional deficiencies, neuropsychiatric conditions, vision and other sensory loss, musculoskeletal disorders, and genitourinary diseases). Every condition that was common in one part of India was uncommon elsewhere, suggesting state-specific priorities for disease control. INTERPRETATION: The NBE method quantifies disease burden using transparent, intuitive, and reproducible methods. It provides a simple, locally operable tool to aid policy makers in priority setting in India and other low-income and middle-income countries. The NBE underlines the need for many more countries to collect nationally representative cause of death data, paired with focused surveys of disability. FUNDING: Ministry of Health and Family Welfare, Government of India.