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  1. Darbandi M, Pasdar Y, Moradi S, Mohamed HJJ, Hamzeh B, Salimi Y
    Prev Chronic Dis, 2020 10 22;17:E131.
    PMID: 33092686 DOI: 10.5888/pcd17.200112
    INTRODUCTION: Obesity is one of the main risk factors for cardiovascular disease (CVD) and cardiometabolic disease (CMD). Many studies have developed cutoff points of anthropometric indices for predicting these diseases. The aim of this systematic review was to differentiate the screening potential of body mass index (BMI), waist circumference (WC), and waist-to-hip ratio (WHR) for adult CVD risk.

    METHODS: We used relevant key words to search electronic databases to identify studies published up to 2019 that used receiver operating characteristic (ROC) curves for assessing the cut-off points of anthropometric indices. We used a random-effects model to pool study results and assessed between-study heterogeneity by using the I2 statistic and Cochran's Q test.

    RESULTS: This meta-analysis included 38 cross-sectional and 2 cohort studies with 105 to 137,256 participants aged 18 or older. The pooled area under the ROC curve (AUC) value for BMI was 0.66 (95% CI, 0.63-0.69) in both men and women. The pooled AUC values for WC were 0.69 (95% CI, 0.67-0.70) in men and 0.69 (95% CI, 0.64-0.74) in women, and the pooled AUC values for WHR were 0.69 (95% CI, 0.66-0.73) in men and 0.71 (95% CI, 0.68-0.73) in women.

    CONCLUSION: Our findings indicated a slight difference between AUC values of these anthropometric indices. However, indices of abdominal obesity, especially WHR, can better predict CVD occurrence.

  2. Haagsma JA, James SL, Castle CD, Dingels ZV, Fox JT, Hamilton EB, et al.
    Inj Prev, 2020 Oct;26(Supp 1):i12-i26.
    PMID: 31915273 DOI: 10.1136/injuryprev-2019-043296
    BACKGROUND: The epidemiological transition of non-communicable diseases replacing infectious diseases as the main contributors to disease burden has been well documented in global health literature. Less focus, however, has been given to the relationship between sociodemographic changes and injury. The aim of this study was to examine the association between disability-adjusted life years (DALYs) from injury for 195 countries and territories at different levels along the development spectrum between 1990 and 2017 based on the Global Burden of Disease (GBD) 2017 estimates.

    METHODS: Injury mortality was estimated using the GBD mortality database, corrections for garbage coding and CODEm-the cause of death ensemble modelling tool. Morbidity estimation was based on surveys and inpatient and outpatient data sets for 30 cause-of-injury with 47 nature-of-injury categories each. The Socio-demographic Index (SDI) is a composite indicator that includes lagged income per capita, average educational attainment over age 15 years and total fertility rate.

    RESULTS: For many causes of injury, age-standardised DALY rates declined with increasing SDI, although road injury, interpersonal violence and self-harm did not follow this pattern. Particularly for self-harm opposing patterns were observed in regions with similar SDI levels. For road injuries, this effect was less pronounced.

    CONCLUSIONS: The overall global pattern is that of declining injury burden with increasing SDI. However, not all injuries follow this pattern, which suggests multiple underlying mechanisms influencing injury DALYs. There is a need for a detailed understanding of these patterns to help to inform national and global efforts to address injury-related health outcomes across the development spectrum.

  3. Burstein R, Henry NJ, Collison ML, Marczak LB, Sligar A, Watson S, et al.
    Nature, 2019 Oct;574(7778):353-358.
    PMID: 31619795 DOI: 10.1038/s41586-019-1545-0
    Since 2000, many countries have achieved considerable success in improving child survival, but localized progress remains unclear. To inform efforts towards United Nations Sustainable Development Goal 3.2-to end preventable child deaths by 2030-we need consistently estimated data at the subnational level regarding child mortality rates and trends. Here we quantified, for the period 2000-2017, the subnational variation in mortality rates and number of deaths of neonates, infants and children under 5 years of age within 99 low- and middle-income countries using a geostatistical survival model. We estimated that 32% of children under 5 in these countries lived in districts that had attained rates of 25 or fewer child deaths per 1,000 live births by 2017, and that 58% of child deaths between 2000 and 2017 in these countries could have been averted in the absence of geographical inequality. This study enables the identification of high-mortality clusters, patterns of progress and geographical inequalities to inform appropriate investments and implementations that will help to improve the health of all populations.
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