70 results found
Hassard F, Smith TR, Boehm AB, et al., 2022, Wastewater surveillance for rapid identification of infectious diseases in prisons., Lancet Microbe, Vol: 3, Pages: e556-e557
Castro-Gutierrez V, Hassard F, Vu M, et al., 2022, Monitoring occurrence of SARS-CoV-2 in school populations: A wastewater-based approach, PLOS ONE, Vol: 17, ISSN: 1932-6203
Grosso G, Di Cesare M, 2021, Dietary factors and non-communicable disease risk in Europe: evidence for European nutritional guidelines?, Publisher: OXFORD UNIV PRESS, ISSN: 1101-1262
Rahimzadeh S, Burczynska B, Ahmadvand A, et al., 2021, Geographical and socioeconomic inequalities in female breast cancer incidence and mortality in Iran: A Bayesian spatial analysis of registry data, PLOS ONE, Vol: 16, ISSN: 1932-6203
NCD Risk Factor Collaboration NCD-RisC, Iurilli N, 2021, Heterogeneous contributions of change in population distribution of body-mass index to change in obesity and underweight, eLife, Vol: 10, ISSN: 2050-084X
From 1985 to 2016, the prevalence of underweight decreased, and that of obesity and severe obesity increased, in most regions, with significant variation in the magnitude of these changes across regions. We investigated how much change in mean body mass index (BMI) explains changes in the prevalence of underweight, obesity, and severe obesity in different regions using data from 2896 population-based studies with 187 million participants. Changes in the prevalence of underweight and total obesity, and to a lesser extent severe obesity, are largely driven by shifts in the distribution of BMI, with smaller contributions from changes in the shape of the distribution. In East and Southeast Asia and sub-Saharan Africa, the underweight tail of the BMI distribution was left behind as the distribution shifted. There is a need for policies that address all forms of malnutrition by making healthy foods accessible and affordable, while restricting unhealthy foods through fiscal and regulatory restrictions.
Rezaei-Darzi E, Mehdipour P, Di Cesare M, et al., 2021, Evaluating equality in prescribing Novel Oral Anticoagulants (NOACs) in England: The protocol of a Bayesian small area analysis, PLOS ONE, Vol: 16, ISSN: 1932-6203
Kontis V, Bennett JE, Rashid T, et al., 2021, Magnitude, demographics and dynamics of the effect of the first wave of the COVID-19 pandemic on all-cause mortality in 21 industrialized countries (vol 26, pg 1919, 2020), NATURE MEDICINE, Vol: 27, Pages: 562-562, ISSN: 1078-8956
Hassard F, Lundy L, Singer AC, et al., 2021, Innovation in wastewater near-source tracking for rapid identification of COVID-19 in schools Comment, LANCET MICROBE, Vol: 2, Pages: E4-E5
Rodriguez-Martinez A, Zhou B, Sophiea MK, et al., 2020, Height and body-mass index trajectories of school-aged children and adolescents from 1985 to 2019 in 200 countries and territories: a pooled analysis of 2181 population-based studies with 65 million participants, The Lancet, Vol: 396, Pages: 1511-1524, ISSN: 0140-6736
SummaryBackgroundComparable global data on health and nutrition of school-aged children and adolescents are scarce. We aimed to estimate age trajectories and time trends in mean height and mean body-mass index (BMI), which measures weight gain beyond what is expected from height gain, for school-aged children and adolescents.MethodsFor this pooled analysis, we used a database of cardiometabolic risk factors collated by the Non-Communicable Disease Risk Factor Collaboration. We applied a Bayesian hierarchical model to estimate trends from 1985 to 2019 in mean height and mean BMI in 1-year age groups for ages 5–19 years. The model allowed for non-linear changes over time in mean height and mean BMI and for non-linear changes with age of children and adolescents, including periods of rapid growth during adolescence.FindingsWe pooled data from 2181 population-based studies, with measurements of height and weight in 65 million participants in 200 countries and territories. In 2019, we estimated a difference of 20 cm or higher in mean height of 19-year-old adolescents between countries with the tallest populations (the Netherlands, Montenegro, Estonia, and Bosnia and Herzegovina for boys; and the Netherlands, Montenegro, Denmark, and Iceland for girls) and those with the shortest populations (Timor-Leste, Laos, Solomon Islands, and Papua New Guinea for boys; and Guatemala, Bangladesh, Nepal, and Timor-Leste for girls). In the same year, the difference between the highest mean BMI (in Pacific island countries, Kuwait, Bahrain, The Bahamas, Chile, the USA, and New Zealand for both boys and girls and in South Africa for girls) and lowest mean BMI (in India, Bangladesh, Timor-Leste, Ethiopia, and Chad for boys and girls; and in Japan and Romania for girls) was approximately 9–10 kg/m2. In some countries, children aged 5 years started with healthier height or BMI than the global median and, in some cases, as healthy as the best performing countries, but they became
Kontis V, Bennett JE, Rashid T, et al., 2020, Magnitude, demographics and dynamics of the effect of the first wave of the COVID-19 pandemic on all-cause mortality in 21 industrialized countries, Nature Medicine, Vol: 26, Pages: 1919-1928, ISSN: 1078-8956
The Coronavirus Disease 2019 (COVID-19) pandemic has changed many social, economic, environmental and healthcare determinants of health. We applied an ensemble of 16 Bayesian models to vital statistics data to estimate the all-cause mortality effect of the pandemic for 21 industrialized countries. From mid-February through May 2020, 206,000 (95% credible interval, 178,100–231,000) more people died in these countries than would have had the pandemic not occurred. The number of excess deaths, excess deaths per 100,000 people and relative increase in deaths were similar between men and women in most countries. England and Wales and Spain experienced the largest effect: ~100 excess deaths per 100,000 people, equivalent to a 37% (30–44%) relative increase in England and Wales and 38% (31–45%) in Spain. Bulgaria, New Zealand, Slovakia, Australia, Czechia, Hungary, Poland, Norway, Denmark and Finland experienced mortality changes that ranged from possible small declines to increases of 5% or less in either sex. The heterogeneous mortality effects of the COVID-19 pandemic reflect differences in how well countries have managed the pandemic and the resilience and preparedness of the health and social care system.
Carrillo Larco R, Bennett JE, Di Cesare M, et al., 2020, The contribution of specific non-communicable diseases to the achievement of the Sustainable Development Goal 3.4 in Peru, PLoS One, Vol: 15, ISSN: 1932-6203
BackgroundNon-communicable diseases (NCDs) have received political attention and commitment, yet surveillance is needed to measure progress and set priorities. Building on global estimates suggesting that Peru is not on target to meet the Sustainable Development Goal 3.4, we estimated the contribution of various NCDs to the change in unconditional probability of dying from NCDs in 25 regions in Peru.MethodsUsing national death registries and census data, we estimated the unconditional probability of dying between ages 30 and 69 from any and from each of the following NCDs: cardiovascular, cancer, diabetes, chronic respiratory diseases and chronic kidney disease. We estimated the contribution of each NCD to the change in the unconditional probability of dying from any of these NCDs between 2006 and 2016.ResultsThe overall unconditional probability of dying improved for men (21.4%) and women (23.3%). Cancer accounted for 10.9% in men and 13.7% in women of the overall reduction; cardiovascular diseases also contributed substantially: 11.3% in men) and 9.8% in women. Consistently in men and women and across regions, diabetes moved in the opposite direction of the overall reduction in the unconditional probability of dying from any selected NCD. Diabetes contributed a rise in the unconditional probability of 3.6% in men and 2.1% in women.ConclusionsAlthough the unconditional probability of dying from any selected NCD has decreased, diabetes would prevent Peru from meeting international targets. Policies are needed to prevent diabetes and to strengthen healthcare to avoid diabetes-related complications and delay mortality.
Cohorts Consortium of Latin America and the Caribbean CC-LAC, Carrillo Larco R, Gregg EW, et al., 2020, Cohort profile: The Cohorts Consortium of Latin America and the Caribbean (CC-LAC), International Journal of Epidemiology, Vol: 49, Pages: 1437-1437g, ISSN: 0300-5771
Grosso G, Di Cesare M, 2020, Global trends of obesity, malnutrition and dietary risk factors, Publisher: OXFORD UNIV PRESS, Pages: V488-V488, ISSN: 1101-1262
NCD Risk Factor Collaboration NCD-RisC, 2020, Repositioning of the global epicentre of non-optimal cholesterol, Nature, Vol: 582, Pages: 73-77, ISSN: 0028-0836
High blood cholesterol is typically considered a feature of wealthy western countries1,2. However, dietary and behavioural determinants of blood cholesterol are changing rapidly throughout the world3 and countries are using lipid-lowering medications at varying rates. These changes can have distinct effects on the levels of high-density lipoprotein (HDL) cholesterol and non-HDL cholesterol, which have different effects on human health4,5. However, the trends of HDL and non-HDL cholesterol levels over time have not been previously reported in a global analysis. Here we pooled 1,127 population-based studies that measured blood lipids in 102.6 million individuals aged 18 years and older to estimate trends from 1980 to 2018 in mean total, non-HDL and HDL cholesterol levels for 200 countries. Globally, there was little change in total or non-HDL cholesterol from 1980 to 2018. This was a net effect of increases in low- and middle-income countries, especially in east and southeast Asia, and decreases in high-income western countries, especially those in northwestern Europe, and in central and eastern Europe. As a result, countries with the highest level of non-HDL cholesterol-which is a marker of cardiovascular risk-changed from those in western Europe such as Belgium, Finland, Greenland, Iceland, Norway, Sweden, Switzerland and Malta in 1980 to those in Asia and the Pacific, such as Tokelau, Malaysia, The Philippines and Thailand. In 2017, high non-HDL cholesterol was responsible for an estimated 3.9 million (95% credible interval 3.7 million-4.2 million) worldwide deaths, half of which occurred in east, southeast and south Asia. The global repositioning of lipid-related risk, with non-optimal cholesterol shifting from a distinct feature of high-income countries in northwestern Europe, north America and Australasia to one that affects countries in east and southeast Asia and Oceania should motivate the use of population-based policies and per
Taddei C, Jackson R, Zhou B, et al., 2020, National trends in total cholesterol obscure heterogeneous changes in HDL and non-HDL cholesterol and total-to-HDL cholesterol ratio: an analysis of trends in Asian and Western countries, International Journal of Epidemiology, Vol: 49, Pages: 173-192, ISSN: 1464-3685
Background: Although high-density lipoprotein (HDL) and non-HDL cholesterol have opposite associations with coronary heart disease (CHD), multi-country reports of lipid trends only use total cholesterol (TC). Our aim was to compare trends in total, HDL and non-HDL cholesterol and total-to-HDL cholesterol ratio in Asian and Western countries.Methods: We pooled 458 population-based studies with 82.1 million participants in 23 Asian and Western countries. We estimated changes in mean total, HDL and non-HDL cholesterol, and mean total-to-HDL cholesterol ratio by country, sex and age group.Results: Since ~1980, mean TC increased in Asian countries. In Japan and South Korea, TC rise was due to rising HDL cholesterol, which increased by up to 0.17 mmol/L per decade in Japanese women; in China, it was due to rising non-HDL cholesterol. TC declined in Western countries, except in Polish men. The decline was largest in Finland and Norway, ~0.4 mmol/Lper decade. The decline in TC in most Western countries was the net effect of an increase in HDL cholesterol and a decline in non-HDL cholesterol, with the HDL cholesterol increase largest in New Zealand and Switzerland. Mean total-to-HDL cholesterol ratio declined in Japan, South Korea and most Western countries, by as much as ~0.7 per decade in Swiss men (equivalent to ~26% decline in CHD risk per decade). The ratio increased in China. Conclusions: HDL cholesterol has risen and total-to-HDL cholesterol ratio has declined in many Western countries, Japan and South Korea, with only weak correlation to changes in TC or non-HDL cholesterol.
Bentham J, Singh GM, Danaei G, et al., 2020, Multidimensional characterization of global food supply from 1961 to 2013, Nature Food, Vol: 1, Pages: 70-75, ISSN: 2662-1355
Food systems are increasingly globalized and interdependent and diets around the world are changing. Characterising national food supplies and how they have changed can inform food policies that ensure national food security, support access to healthy diets and enhance environmental sustainability. Here, we analysed data for 171 countries on availability of 18 food groups from the United Nations Food and Agriculture Organization to identify and track 40 multi-dimensional food supply patterns from 1961 to 2013. Four predominant food group combinations were identified that explained almost 90% of cross-country variance in food supply: animal source and sugar; vegetable; starchy root and fruit; and seafood and oilcrops. South Korea, China and Taiwan experienced the largest changes in food supply over the past five decades, with animal source foods and sugar, vegetables, and seafood and oilcrops all becoming more abundant components of food supply. In contrast, in many Western countries, the supply of animal source foods and sugar declined. Meanwhile, there was remarkably little change in food supply in countries in the sub-Saharan Africa region. These changes have led to a partial global convergence in national supply of animal source foods and sugar, and a divergence in vegetables, and seafood and oilcrops. Our analysis has generated a novel characterisation of food supply that highlights the interdependence of multiple food types in national food systems. A better understanding of how these patterns have evolved and will continue to change is needed to support the delivery of healthy and sustainable food system policies.
Jaime Miranda J, Carrillo-Larco RM, Ferreccio C, et al., 2020, Trends in cardiometabolic risk factors in the Americas between 1980 and 2014: a pooled analysis of population-based surveys, The Lancet Global Health, Vol: 8, Pages: E123-E133, ISSN: 2214-109X
BackgroundDescribing the prevalence and trends of cardiometabolic risk factors that are associated with non-communicable diseases (NCDs) is crucial for monitoring progress, planning prevention, and providing evidence to support policy efforts. We aimed to analyse the transition in body-mass index (BMI), obesity, blood pressure, raised blood pressure, and diabetes in the Americas, between 1980 and 2014.MethodsWe did a pooled analysis of population-based studies with data on anthropometric measurements, biomarkers for diabetes, and blood pressure from adults aged 18 years or older. A Bayesian model was used to estimate trends in BMI, raised blood pressure (systolic blood pressure ≥140 mm Hg or diastolic blood pressure ≥90 mm Hg), and diabetes (fasting plasma glucose ≥7·0 mmol/L, history of diabetes, or diabetes treatment) from 1980 to 2014, in 37 countries and six subregions of the Americas.Findings389 population-based surveys from the Americas were available. Comparing prevalence estimates from 2014 with those of 1980, in the non-English speaking Caribbean subregion, the prevalence of obesity increased from 3·9% (95% CI 2·2–6·3) in 1980, to 18·6% (14·3–23·3) in 2014, in men; and from 12·2% (8·2–17·0) in 1980, to 30·5% (25·7–35·5) in 2014, in women. The English-speaking Caribbean subregion had the largest increase in the prevalence of diabetes, from 5·2% (2·1–10·4) in men and 6·4% (2·6–10·4) in women in 1980, to 11·1% (6·4–17·3) in men and 13·6% (8·2–21·0) in women in 2014). Conversely, the prevalence of raised blood pressure has decreased in all subregions; the largest decrease was found in North America from 27·6% (22·3–33·2) in men and 19·9% (15·8–24·4) in women in 1980, to 15·
Di Cesare M, Jarvis JD, Scarlatescu O, et al., 2020, NOACs Added to WHO's Essential Medicines List: Recommendations for Future Policy Actions, GLOBAL HEART, Vol: 15, ISSN: 2211-8160
Zaidel EJ, Leng X, Adeoye AM, et al., 2020, Inclusion in the World Health Organization Model List of Essential Medicines of Non-Vitamin K Anticoagulants for Treatment of Non-Valvular Atrial Fibrillation: A Step Towards Reducing the Burden of Cardiovascular Morbidity and Mortality, GLOBAL HEART, Vol: 15, ISSN: 2211-8160
Di Cesare M, Soric M, Bovet P, et al., 2019, The epidemiological burden of obesity in childhood: a worldwide epidemic requiring urgent action, BMC MEDICINE, Vol: 17, ISSN: 1741-7015
Di Cesare M, 2019, Global trends of chronic non-communicable diseases risk factors, Publisher: OXFORD UNIV PRESS, Pages: 77-77, ISSN: 1101-1262
Sabates R, Di Cesare M, 2019, Can maternal education sustain or enhance the benefits of early life interventions? Evidence from the Young Lives Longitudinal Study, COMPARE-A JOURNAL OF COMPARATIVE AND INTERNATIONAL EDUCATION, Vol: 51, Pages: 651-669, ISSN: 0305-7925
Bixby H, Bentham J, Zhou B, et al., 2019, Rising rural body-mass index is the main driver of the global obesity epidemic, Nature, Vol: 569, Pages: 260-264, ISSN: 0028-0836
Body-mass index (BMI) has increased steadily in most countries in parallel with a rise in the proportion of the population who live in cities1,2. This has led to a widely reported view that urbanization is one of the most important drivers of the global rise in obesity3,4,5,6. 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.
Teplitski M, Irani T, Krediet CJ, et al., 2018, Student-Generated Pre-Exam Questions is an Effective Tool for Participatory Learning: A Case Study from Ecology of Waterborne Pathogens Course, JOURNAL OF FOOD SCIENCE EDUCATION, Vol: 17, Pages: 76-84, ISSN: 1541-4329
Ezzati M, Di Cesare M, Bentham J, 2018, Determining the worldwide prevalence of obesity reply, LANCET, Vol: 391, Pages: 1774-1774, ISSN: 0140-6736
NCD Risk Factor Collaboration NCD-RisC, 2017, Worldwide trends in body-mass index, underweight, overweight, and obesity from 1975 to 2016: a pooled analysis of 2416 population-based measurement studies in 128·9 million children, adolescents, and adults., Lancet, Vol: 390, Pages: 2627-2642, ISSN: 0140-6736
BACKGROUND: 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. METHODS: 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). FINDINGS: Regional change in age-standardised mean BMI in girls from 1975 to 2016 ranged from virtually no change (-0·01 kg/m(2) 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/m(2) per decade (0·69-1·35, PP>0·9999) in central Latin America and an increase of 0·95 kg/m(2) 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/m(2) per decade (-0·33 to 0·49, PP=0·6926) in eastern Europe to an increase of 0·77 kg/m(2) per decade (0·50-1·06, PP>0·9999) in Polynesia and Micronesia. Tre
Kenge AP, Bentham J, Zhou B, et al., 2017, Trends in obesity and diabetes across regions in Africa from 1980 to 2014: an analysis of pooled population-based studies., International Journal of Epidemiology, Vol: 46, Pages: 1421-1432, ISSN: 1464-3685
Background: The 2016 Dar Es Salaam Call to Action on Diabetes and other NCDs advocates national multi-sectoral NCD strategies and action plans based on available data and information from countries of sub-Saharan Africa and beyond. We estimated trends, from 1980 to 2014, in age-standardised mean body mass index (BMI) and diabetes prevalence in these countries in order to assess the co-progression and assist policy formulation.Methods: We pooled data from African and world-wide population-based studies which measured height, weight, and biomarkers to assess diabetes status in adults aged >18 years. A Bayesian hierarchical model was used to estimate trends, by sex, for 200 countries and territories including 53 countries across five African regions, (central, eastern, northern, southern and western) in mean BMI and diabetes prevalence (defined as either fasting plasma glucose of >7.0 mmol/L, history of diabetes diagnosis, or use of insulin or oral glucose control agents). ResultsAfrican data came from 245 population-based surveys (1.2 million participants) for BMI and 76 surveys (182 000 participants) for diabetes prevalence estimates. Countries with the highest number of data sources for BMI were South Africa (n=17), Nigeria (n=15) and Egypt (n=13); and for diabetes estimates, Tanzania (n=8), Tunisia (n=7), Cameroon, Egypt and South Africa (all n=6). The age-standardised mean BMI increased from 21.0 kg/m2 (95% credible interval: 20.3-21.7) to 23.0 kg/m2 (22.7-23.3) in men, and from 21.9 kg/m2 (21.3-22.5) to 24.9 kg/m2 (24.6-25.1) in women. The age-standardised prevalence of diabetes increased from 3.4% (1.5-6.3) to 8.5% (6.5-10.8) in men, and from 4.1% (2.0-7.5) to 8.9 % (6.9-11.2) in women. Estimates in northern and southern regions were mostly higher than the global average; those in central, eastern and western regions were lower than global averages. A positive association (correlation coefficient ≃0.9) was observed between mean BMI and diabetes prevalence
Ueda P, Woodward M, Lu Y, et al., 2017, Laboratory-based and office-based risk scores and charts to predict 10-year risk of cardiovascular disease in 182 countries: a pooled analysis of prospective cohorts and health surveys., Lancet Diabetes and Endocrinology, Vol: 5, Pages: 196-213, ISSN: 2213-8595
BACKGROUND: Worldwide implementation of risk-based cardiovascular disease (CVD) prevention requires risk prediction tools that are contemporarily recalibrated for the target country and can be used where laboratory measurements are unavailable. We present two cardiovascular risk scores, with and without laboratory-based measurements, and the corresponding risk charts for 182 countries to predict 10-year risk of fatal and non-fatal CVD in adults aged 40-74 years. METHODS: Based on our previous laboratory-based prediction model (Globorisk), we used data from eight prospective studies to estimate coefficients of the risk equations using proportional hazard regressions. The laboratory-based risk score included age, sex, smoking, blood pressure, diabetes, and total cholesterol; in the non-laboratory (office-based) risk score, we replaced diabetes and total cholesterol with BMI. We recalibrated risk scores for each sex and age group in each country using country-specific mean risk factor levels and CVD rates. We used recalibrated risk scores and data from national surveys (using data from adults aged 40-64 years) to estimate the proportion of the population at different levels of CVD risk for ten countries from different world regions as examples of the information the risk scores provide; we applied a risk threshold for high risk of at least 10% for high-income countries (HICs) and at least 20% for low-income and middle-income countries (LMICs) on the basis of national and international guidelines for CVD prevention. We estimated the proportion of men and women who were similarly categorised as high risk or low risk by the two risk scores. FINDINGS: Predicted risks for the same risk factor profile were generally lower in HICs than in LMICs, with the highest risks in countries in central and southeast Asia and eastern Europe, including China and Russia. In HICs, the proportion of people aged 40-64 years at high risk of CVD ranged from 1% for South Korean women to 42% for
Lauby-Secretan B, Scoccianti C, Loomis D, et al., 2016, Body Fatness and Cancer - Viewpoint of the IARC Working Group, NEW ENGLAND JOURNAL OF MEDICINE, Vol: 375, Pages: 794-798, ISSN: 0028-4793
Being taller is associated with enhanced longevity, and higher education and earnings. We reanalysed 1472 population-based studies, with measurement of height on more than 18.6 million participants to estimate mean height for people born between 1896 and 1996 in 200 countries. The largest gain in adult height over the past century has occurred in South Korean women and Iranian men, who became 20.2 cm (95% credible interval 17.5–22.7) and 16.5 cm (13.3–19.7) taller, respectively. In contrast, there was little change in adult height in some sub-Saharan African countries and in South Asia over the century of analysis. The tallest people over these 100 years are men born in the Netherlands in the last quarter of 20th century, whose average heights surpassed 182.5 cm, and the shortest were women born in Guatemala in 1896 (140.3 cm; 135.8–144.8). The height differential between the tallest and shortest populations was 19-20 cm a century ago, and has remained the same for women and increased for men a century later despite substantial changes in the ranking of countries.
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