RESULTS: Important issues were identified during the data harmonisation process relating to data ownership, sharing methodologies and ethical concerns. Measures were assessed across eight domains; demographic; dietary; clinical and anthropometric; medical history; hypertension knowledge; physical activity; behavioural (smoking and alcohol); and biochemical domains. Identifying validated measures relevant across a variety of settings presented some difficulties. The resulting GACD hypertension data dictionary comprises 67 consensus measures. Of the 14 responding teams, only two teams were including more than 50 consensus variables, five teams were including between 25 and 50 consensus variables and four teams were including between 6 and 24 consensus variables, one team did not provide details of the variables collected and two teams did not include any of the consensus variables as the project had already commenced or the measures were not relevant to their study.
CONCLUSIONS: Deriving consensus measures across diverse research projects and contexts was challenging. The major barrier to their implementation was related to the time taken to develop and present these measures. Inclusion of consensus measures into future funding announcements would facilitate researchers integrating these measures within application protocols. We suggest that adoption of consensus measures developed here, across the field of hypertension, would help advance the science in this area, allowing for more comparable data sets and generalizable inferences.
METHODS: We developed the International Diet-Health Index (IDHI) to measure health impacts of dietary intake across 186 countries in 2010, using age-specific and sex-specific data on country-level dietary intake, effects of dietary factors on cardiometabolic diseases and country-specific cardiometabolic disease profiles. The index encompasses the impact of 11 foods/nutrients on 12 cardiometabolic diseases, the mediation of health effects of specific dietary intakes through blood pressure and body mass index and background disease prevalence in each country-age-sex group. We decomposed the index into IDHIbeneficial for risk-reducing factors, and IDHIadverse for risk-increasing factors. The flexible functional form of the IDHI allows inclusion of additional risk factors and diseases as data become available.
RESULTS: By sex, women experienced smaller detrimental cardiometabolic effects of diet than men: (females IDHIadverse range: -0.480 (5th percentile, 95th percentile: -0.932, -0.300) to -0.314 (-0.543, -0.213); males IDHIadverse range: (-0.617 (-1.054, -0.384) to -0.346 (-0.624, -0.222)). By age, middle-aged adults had highest IDHIbeneficial (females: 0.392 (0.235, 0.763); males: 0.415 (0.243, 0.949)) and younger adults had most extreme IDHIadverse (females: -0.480 (-0.932, -0.300); males: -0.617 (-1.054, -0.384)). Regionally, Central Latin America had the lowest IDHIoverall (-0.466 (-0.892, -0.159)), while Southeast Asia had the highest IDHIoverall (0.272 (-0.224, 0.903)). IDHIoverall was highest in low-income countries and lowest in upper middle-income countries (-0.039 (-0.317, 0.227) and -0.146 (-0.605, 0.303), respectively). Among 186 countries, Honduras had lowest IDHIoverall (-0.721 (-0.916, -0.207)), while Malaysia had highest IDHIoverall (0.904 (0.435, 1.190)).
CONCLUSION: IDHI encompasses dietary intakes, health effects and country disease profiles into a single index, allowing policymakers a useful means of assessing/comparing health impacts of diet quality between populations.
METHODS: This study used data from the Global COVID-19 Index provided by PEMANDU Associates. The sample, representing 161 countries, comprised the number of confirmed cases, deaths, stringency indices, population density and GNI per capita (USD). Correlation matrices were computed to reveal the association between the variables at three time points: day-30, day-60 and day-90. Three separate principal component analyses were computed for similar time points, and several standardized plots were produced.
RESULTS: Confirmed cases and deaths due to COVID-19 showed positive but weak correlation with stringency and GNI per capita. Through principal component analysis, the first two principal components captured close to 70% of the variance of the data. The first component can be viewed as the severity of the COVID-19 surge in countries, whereas the second component largely corresponded to population density, followed by GNI per capita of countries. Multivariate visualization of the two dominating principal components provided a standardized comparison of the situation in the161 countries, performed on day-30, day-60 and day-90 since the first confirmed cases in countries worldwide.
CONCLUSION: Visualization of the global spread of COVID-19 showed the unequal severity of the pandemic across continents and over time. Distinct patterns in clusters of countries, which separated many European countries from those in Africa, suggested a contrast in terms of stringency measures and wealth of a country. The African continent appeared to fare better in terms of the COVID-19 pandemic and the burden of mortality in the first 90 days. A noticeable worsening trend was observed in several countries in the same relative time frame of the disease's first 90 days, especially in the United States of America.
METHODS: We reviewed results for injuries from the GBD 2017 study. GBD 2017 measured injury-specific mortality and years of life lost (YLLs) using the Cause of Death Ensemble model. To measure non-fatal injuries, GBD 2017 modelled injury-specific incidence and converted this to prevalence and years lived with disability (YLDs). YLLs and YLDs were summed to calculate disability-adjusted life years (DALYs).
FINDINGS: In 1990, there were 4 260 493 (4 085 700 to 4 396 138) injury deaths, which increased to 4 484 722 (4 332 010 to 4 585 554) deaths in 2017, while age-standardised mortality decreased from 1079 (1073 to 1086) to 738 (730 to 745) per 100 000. In 1990, there were 354 064 302 (95% uncertainty interval: 338 174 876 to 371 610 802) new cases of injury globally, which increased to 520 710 288 (493 430 247 to 547 988 635) new cases in 2017. During this time, age-standardised incidence decreased non-significantly from 6824 (6534 to 7147) to 6763 (6412 to 7118) per 100 000. Between 1990 and 2017, age-standardised DALYs decreased from 4947 (4655 to 5233) per 100 000 to 3267 (3058 to 3505).
INTERPRETATION: Injuries are an important cause of health loss globally, though mortality has declined between 1990 and 2017. Future research in injury burden should focus on prevention in high-burden populations, improving data collection and ensuring access to medical care.