Underweight, overweight, and obesity in childhood and adolescence are associated with adverse health consequences throughout the life-course. Our aim was to estimate worldwide trends in mean body-mass index (BMI) and a comprehensive set of BMI categories that cover underweight to obesity in children and adolescents, and to compare trends with those of adults. We pooled 2416 population-based studies with measurements of height and weight on 128·9 million participants aged 5 years and older, including 31·5 million aged 5-19 years. We used a Bayesian hierarchical model to estimate trends from 1975 to 2016 in 200 countries for mean BMI and for prevalence of BMI in the following categories for children and adolescents aged 5-19 years: more than 2 SD below the median of the WHO growth reference for children and adolescents (referred to as moderate and severe underweight hereafter), 2 SD to more than 1 SD below the median (mild underweight), 1 SD below the median to 1 SD above the median (healthy weight), more than 1 SD to 2 SD above the median (overweight but not obese), and more than 2 SD above the median (obesity). Regional change in age-standardised mean BMI in girls from 1975 to 2016 ranged from virtually no change (-0·01 kg/m2 per decade; 95% credible interval -0·42 to 0·39, posterior probability [PP] of the observed decrease being a true decrease=0·5098) in eastern Europe to an increase of 1·00 kg/m2 per decade (0·69-1·35, PP>0·9999) in central Latin America and an increase of 0·95 kg/m2 per decade (0·64-1·25, PP>0·9999) in Polynesia and Micronesia. The range for boys was from a non-significant increase of 0·09 kg/m2 per decade (-0·33 to 0·49, PP=0·6926) in eastern Europe to an increase of 0·77 kg/m2 per decade (0·50-1·06, PP>0·9999) in Polynesia and Micronesia. Trends in mean BMI have recently flattened in northwestern Europe and the high-income English-speaking and Asia-Pacific regions for both sexes, southwestern Europe for boys, and central and Andean Latin America for girls. By contrast, the rise in BMI has accelerated in east and south Asia for both sexes, and southeast Asia for boys. Global age-standardised prevalence of obesity increased from 0·7% (0·4-1·2) in 1975 to 5·6% (4·8-6·5) in 2016 in girls, and from 0·9% (0·5-1·3) in 1975 to 7·8% (6·7-9·1) in 2016 in boys; the prevalence of moderate and severe underweight decreased from 9·2% (6·0-12·9) in 1975 to 8·4% (6·8-10·1) in 2016 in girls and from 14·8% (10·4-19·5) in 1975 to 12·4% (10·3-14·5) in 2016 in boys. Prevalence of moderate and severe underweight was highest in India, at 22·7% (16·7-29·6) among girls and 30·7% (23·5-38·0) among boys. Prevalence of obesity was more than 30% in girls in Nauru, the Cook Islands, and Palau; and boys in the Cook Islands, Nauru, Palau, Niue, and American Samoa in 2016. Prevalence of obesity was about 20% or more in several countries in Polynesia and Micronesia, the Middle East and north Africa, the Caribbean, and the USA. In 2016, 75 (44-117) million girls and 117 (70-178) million boys worldwide were moderately or severely underweight. In the same year, 50 (24-89) million girls and 74 (39-125) million boys worldwide were obese. The rising trends in children's and adolescents' BMI have plateaued in many high-income countries, albeit at high levels, but have accelerated in parts of Asia, with trends no longer correlated with those of adults. Wellcome Trust, AstraZeneca Young Health Programme.

Body-mass index (BMI) has increased steadily in most countries in parallel with a rise in the proportion of the population who live in cities^1,2. This has led to a widely reported view that urbanization is one of the most important drivers of the global rise in obesity^3–6. Here we use 2,009 population-based studies, with measurements of height and weight in more than 112 million adults, to report national, regional and global trends in mean BMI segregated by place of residence (a rural or urban area) from 1985 to 2017. We show that, contrary to the dominant paradigm, more than 55% of the global rise in mean BMI from 1985 to 2017—and more than 80% in some low- and middle-income regions—was due to increases in BMI in rural areas. This large contribution stems from the fact that, with the exception of women in sub-Saharan Africa, BMI is increasing at the same rate or faster in rural areas than in cities in low- and middle-income regions. These trends have in turn resulted in a closing—and in some countries reversal—of the gap in BMI between urban and rural areas in low- and middle-income countries, especially for women. In high-income and industrialized countries, we noted a persistently higher rural BMI, especially for women. There is an urgent need for an integrated approach to rural nutrition that enhances financial and physical access to healthy foods, to avoid replacing the rural undernutrition disadvantage in poor countries with a more general malnutrition disadvantage that entails excessive consumption of low-quality calories.

Low-grade inflammation is associated with an increased risk of chronic degenerative disease, but its relationship with mortality is less well explored. We aimed at evaluating, at a large epidemiological level, the possible association of low-grade inflammation, as measured by a composite score, with overall mortality risk. We conducted a population-based prospective investigation on 20,337 adult subjects free from major hematological disease and acute inflammatory status, randomly recruited from the general population of the Moli-sani study. A low-grade inflammation score was obtained from the sum of 10-tiles of plasmatic (C-reactive protein) and cellular (leukocyte and platelet counts, granulocyte/lymphocyte ratio) biomarkers of low-grade inflammation; higher levels indicated increased low-grade inflammation. Hazard ratios were calculated using multivariable Cox proportional hazard models with 95% confidence intervals. At the end of follow-up (median 7.6 years), 837 all-cause deaths were recorded. As compared to subjects in the lowest quartile of the low-grade inflammation score, those in the highest category had a significantly increased risk in overall mortality (HR=1.44; 1.17–1.77), independently of possible confounders, including the presence of chronic diseases and a number of health-related behaviors. The magnitude of the association of low-grade inflammation with mortality was relatively higher in type 2 diabetic patients (HR=2.90; 1.74–4.84) and in individuals with a history of cardiovascular disease (HR=2.48; 1.50–4.11) as compared to their counterparts who were free from the disease. In conclusion, an elevated degree of low-grade inflammation, as measured by a composite score of inflammatory biomarkers, is an independent risk factor for total mortality in an apparently healthy adult general population.

The association of polyphenol content of human diet with low-grade inflammation is not yet fully understood. It was the objective of this study to evaluate the association of flavonoid and lignan intake with frequently used and easily applicable in clinical practice low-grade inflammation biomarkers, in a novel holistic approach. A total of 5,948 women and 5,965 men (aged ≥ 35years) were analysed from the Moli-sani cohort, randomly recruited from the general population. The EPIC-FFQ was used for dietary assessment. Flavonol, flavone, flavanone, flavanol, anthocyanin, isoflavone and lignan intakes were calculated using Eurofir eBASIS and the polyphenol antioxidant content (PAC)-score was constructed to assess the total content of diet in these nutrients. CRP levels, WBC and PLT count and granulocyte to lymphocyte ratio were conceived as low-grade inflammation biomarkers. INFLA-score was constructed summarizing synergistic effects of these biomarkers. The INFLA-score was negatively associated with PAC-score in different levels of adjustment, in both genders (for all β-coef< 0, P< 0.05). 10 units increase in PAC-score was associated with 5–8 % decrease in the likelihood of higher low-grade inflammation status (i. e. higher quartile of INFLA-score) in men and women (odds ratio [ORs] 0.92 to 0.95, p< 0.05). The total variation of INFLA-score that was explained by PAC-score was estimated to be 16.7 % in women and 9.1 % in men (%R²=16.7 and 9.1). In conclusion, polyphenol content of diet evaluated in a holistic approach was negatively associated with a score of low-grade inflammation biomarkers in a large population based study. For the first time low-grade inflammation was evaluated in a holistic way through INFLA-score and was associated with polyphenol content of diet. Supplementary Material to this article is available online at www.thrombosis-online.com.

The understanding of non-genetic regulation of platelet indices--platelet count, plateletcrit, mean platelet volume, and platelet distribution width--is limited. The association of these platelet indices with a number of biochemical, environmental and clinical variables was studied in a large cohort of the general population. Men and women (n=18,097, 52% women, 56±12 years) were randomly recruited from various villages in Molise (Italy) in the framework of the population-based cohort study "Moli-sani". Hemochromocytometric analyses were performed using an automatic analyzer (Beckman Coulter, IL, Milan, Italy). Associations of platelet indices with dependent variables were investigated by multivariable linear regression analysis. Full models including age, sex, body mass index, blood pressure, smoking, menopause, white and red blood cell counts, mean corpuscular volume, D-dimers, C-reactive protein, high-density lipoproteins, low-density lipoproteins, triglycerides, glucose, and drug use explained 16%, 21%, 1.9% and 4.7% of platelet count, plateletcrit, mean platelet volume and platelet distribution width variability, respectively; variables that appeared to be most strongly associated were white blood cell count, age, and sex. Platelet count, mean platelet volume and plateletcrit were positively associated with white blood cell count, while platelet distribution width was negatively associated with white blood cell count. Platelet count and plateletcrit were also positively associated with C-reactive protein and D-dimers (P<0.0001). Each of the other variables, although associated with platelet indices in a statistically significant manner, only explained less than 0.5% of their variability. Platelet indices varied across Molise villages, independently of any other platelet count determinant or characteristics of the villages. The association of platelet indices with white blood cell count, C-reactive protein and D-dimers in a general population underline the relation between platelets and inflammation.