Browsing by Author "Stevens G.A."

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    Diminishing benefits of urban living for children and adolescents’ growth and development
    (2023-03-30) Mishra A.; Zhou B.; Rodriguez-Martinez A.; Bixby H.; Singleton R.K.; Carrillo-Larco R.M.; Sheffer K.E.; Paciorek C.J.; Bennett J.E.; Lhoste V.; Iurilli M.L.C.; Di Cesare M.; Bentham J.; Phelps N.H.; Sophiea M.K.; Stevens G.A.; Danaei G.; Cowan M.J.; Savin S.; Riley L.M.; Gregg E.W.; Aekplakorn W.; Ahmad N.A.; Baker J.L.; Chirita-Emandi A.; Farzadfar F.; Fink G.; Heinen M.; Ikeda N.; Kengne A.P.; Khang Y.H.; Laatikainen T.; Laxmaiah A.; Ma J.; Monroy-Valle M.; Mridha M.K.; Padez C.P.; Reynolds A.; Sorić M.; Starc G.; Wirth J.P.; Abarca-Gómez L.; Abdeen Z.A.; Abdrakhmanova S.; Ghaffar S.A.; Abdul Rahim H.F.; Abdurrahmonova Z.; Abu-Rmeileh N.M.; Garba J.A.; Acosta-Cazares B.; Adam I.; Adamczyk M.; Adams R.J.; Adu-Afarwuah S.; Afsana K.; Afzal S.; Agbor V.N.; Agdeppa I.A.; Aghazadeh-Attari J.; Aguenaou H.; Aguilar-Salinas C.A.; Agyemang C.; Ahmad M.H.; Ahmadi A.; Ahmadi N.; Ahmadi N.; Ahmed I.; Ahmed S.H.; Ahrens W.; Aitmurzaeva G.; Ajlouni K.; Al-Hazzaa H.M.; Al-Lahou B.; Al-Raddadi R.; Al Hourani H.M.; Al Qaoud N.M.; Alarouj M.; AlBuhairan F.; AlDhukair S.; Aldwairji M.A.; Alexius S.; Ali M.M.; Alkandari A.; Alkerwi A.; Alkhatib B.M.; Allin K.; Alvarez-Pedrerol M.; Aly E.; Amarapurkar D.N.; Etxezarreta P.A.; Amoah J.; Amougou N.; Amouyel P.; Andersen L.B.; Anderssen S.A.; Androutsos O.; Ängquist L.; Anjana R.M.; Ansari-Moghaddam A.; Anufrieva E.; Mahidol University
    Optimal growth and development in childhood and adolescence is crucial for lifelong health and well-being1–6. Here we used data from 2,325 population-based studies, with measurements of height and weight from 71 million participants, to report the height and body-mass index (BMI) of children and adolescents aged 5–19 years on the basis of rural and urban place of residence in 200 countries and territories from 1990 to 2020. In 1990, children and adolescents residing in cities were taller than their rural counterparts in all but a few high-income countries. By 2020, the urban height advantage became smaller in most countries, and in many high-income western countries it reversed into a small urban-based disadvantage. The exception was for boys in most countries in sub-Saharan Africa and in some countries in Oceania, south Asia and the region of central Asia, Middle East and north Africa. In these countries, successive cohorts of boys from rural places either did not gain height or possibly became shorter, and hence fell further behind their urban peers. The difference between the age-standardized mean BMI of children in urban and rural areas was <1.1 kg m–2 in the vast majority of countries. Within this small range, BMI increased slightly more in cities than in rural areas, except in south Asia, sub-Saharan Africa and some countries in central and eastern Europe. Our results show that in much of the world, the growth and developmental advantages of living in cities have diminished in the twenty-first century, whereas in much of sub-Saharan Africa they have amplified.
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    General and abdominal adiposity and hypertension in eight world regions: a pooled analysis of 837 population-based studies with 7·5 million participants
    (2024-08-31) Zhou B.; Bennett J.E.; Wickham A.P.; Singleton R.K.; Mishra A.; Carrillo-Larco R.M.; Ikeda N.; Jain L.; Barradas-Pires A.; Heap R.A.; Lhoste V.P.F.; Sheffer K.E.; Phelps N.H.; Rayner A.W.; Gregg E.W.; Woodward M.; Stevens G.A.; Iurilli M.L.C.; Danaei G.; Cesare M.D.; Aguilar-Salinas C.A.; Ahmad N.A.; Bovet P.; Chen Z.; Damasceno A.; Filippi S.L.; Janszky I.; Kengne A.P.; Khang Y.H.; Khunti K.; Laxmaiah A.; Lim L.L.; Lissner L.; Margozzini P.; Mbanya J.C.; McGarvey S.; Shaw J.E.; Söderberg S.; Soto-Mota L.A.; Wang J.; Zaccardi F.; Ezzati M.; Abarca-Gómez L.; AbbasiKangevari M.; Abdrakhmanova S.; Abdul Ghaffar S.A.; Abdul Rahim H.F.; Abdurrahmonova Z.; Abu-Rmeileh N.M.; Acosta-Cazares B.; Adam I.; Adamczyk M.; Aekplakorn W.; Agdeppa I.A.; Aghazadeh-Attari J.; Agyemang C.; Ahmad M.H.; Ahmadi A.; Ahmadi N.; Ahmadi N.; Ahmed S.H.; Ahrens W.; Aitmurzaeva G.; Ajlouni K.; Al-Hazzaa H.M.; Al-Hinai H.; Al-Lawati J.A.; Al-Raddadi R.; Asfoor D.A.; Al Hourani H.M.; Alarouj M.; AlBuhairan F.; AlDhukair S.; Ali M.M.; Alieva A.V.; Alkandari A.; Alkhatib B.M.; Aly E.; Amarapurkar D.N.; Amiano Etxezarreta P.; Amougou N.; Andersen L.B.; Anderssen S.A.; Androutsos O.; Anjana R.M.; Ansari-Moghaddam A.; Anufrieva E.; Aounallah-Skhiri H.; Aris T.; Arku R.E.; Arlappa N.; Aryal K.K.; Assah F.K.; Assembekov B.; Assunção M.C.F.; Auvinen J.; Avdicová M.; Azad K.; Azevedo A.; Azimi-Nezhad M.; Zhou B.; Mahidol University
    Background: Adiposity can be measured using BMI (which is based on weight and height) as well as indices of abdominal adiposity. We examined the association between BMI and waist-to-height ratio (WHtR) within and across populations of different world regions and quantified how well these two metrics discriminate between people with and without hypertension. Methods: We used data from studies carried out from 1990 to 2023 on BMI, WHtR and hypertension in people aged 20–64 years in representative samples of the general population in eight world regions. We graphically compared the regional distributions of BMI and WHtR, and calculated Pearson's correlation coefficients between BMI and WHtR within each region. We used mixed-effects linear regression to estimate the extent to which WHtR varies across regions at the same BMI. We graphically examined the prevalence of hypertension and the distribution of people who have hypertension both in relation to BMI and WHtR, and we assessed how closely BMI and WHtR discriminate between participants with and without hypertension using C-statistic and net reclassification improvement (NRI). Findings: The correlation between BMI and WHtR ranged from 0·76 to 0·89 within different regions. After adjusting for age and BMI, mean WHtR was highest in south Asia for both sexes, followed by Latin America and the Caribbean and the region of central Asia, Middle East and north Africa. Mean WHtR was lowest in central and eastern Europe for both sexes, in the high-income western region for women, and in Oceania for men. Conversely, to achieve an equivalent WHtR, the BMI of the population of south Asia would need to be, on average, 2·79 kg/m2 (95% CI 2·31–3·28) lower for women and 1·28 kg/m2 (1·02–1·54) lower for men than in the high-income western region. In every region, hypertension prevalence increased with both BMI and WHtR. Models with either of these two adiposity metrics had virtually identical C-statistics and NRIs for every region and sex, with C-statistics ranging from 0·72 to 0·81 and NRIs ranging from 0·34 to 0·57 in different region and sex combinations. When both BMI and WHtR were used, performance improved only slightly compared with using either adiposity measure alone. Interpretation: BMI can distinguish young and middle-aged adults with higher versus lower amounts of abdominal adiposity with moderate-to-high accuracy, and both BMI and WHtR distinguish people with or without hypertension. However, at the same BMI level, people in south Asia, Latin America and the Caribbean, and the region of central Asia, Middle East and north Africa, have higher WHtR than in the other regions. Funding: UK Medical Research Council and UK Research and Innovation (Innovate UK).
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    Global variation in diabetes diagnosis and prevalence based on fasting glucose and hemoglobin A1c
    (2023-01-01) Zhou B.; Sheffer K.E.; Bennett J.E.; Gregg E.W.; Danaei G.; Singleton R.K.; Shaw J.E.; Mishra A.; Lhoste V.P.F.; Carrillo-Larco R.M.; Kengne A.P.; Phelps N.H.; Heap R.A.; Rayner A.W.; Stevens G.A.; Paciorek C.J.; Riley L.M.; Cowan M.J.; Savin S.; Vander Hoorn S.; Lu Y.; Pavkov M.E.; Imperatore G.; Aguilar-Salinas C.A.; Ahmad N.A.; Anjana R.M.; Davletov K.; Farzadfar F.; González-Villalpando C.; Khang Y.H.; Kim H.C.; Laatikainen T.; Laxmaiah A.; Mbanya J.C.N.; Narayan K.M.V.; Ramachandran A.; Wade A.N.; Zdrojewski T.; Abbasi-Kangevari M.; Rahim H.F.A.; Abu-Rmeileh N.M.; Adambekov S.; Adams R.J.; Aekplakorn W.; Agdeppa I.A.; Aghazadeh-Attari J.; Agyemang C.; Ahmadi A.; Ahmadi N.; Ahmadi N.; Ahmed S.H.; Ajlouni K.; Al-Hinai H.; Al-Lahou B.; Al-Lawati J.A.; Asfoor D.A.; Al Qaoud N.M.; Alarouj M.; AlBuhairan F.; AlDhukair S.; Aldwairji M.A.; Ali M.M.; Alinezhad F.; Alkandari A.; Alomirah H.F.; Aly E.; Amarapurkar D.N.; Andersen L.B.; Anderssen S.A.; Andrade D.S.; Ansari-Moghaddam A.; Aounallah-Skhiri H.; Aris T.; Arlappa N.; Aryal K.K.; Assah F.K.; Assembekov B.; Auvinen J.; Avdičová M.; Azad K.; Azimi-Nezhad M.; Azizi F.; Bacopoulou F.; Balakrishna N.; Bamoshmoosh M.; Banach M.; Bandosz P.; Banegas J.R.; Barbagallo C.M.; Barceló A.; Baretić M.; Barrera L.; Basit A.; Batieha A.M.; Batista A.P.; Baur L.A.; Belavendra A.; Ben Romdhane H.; Benet M.; Berkinbayev S.; Mahidol University
    Fasting plasma glucose (FPG) and hemoglobin A1c (HbA1c) are both used to diagnose diabetes, but these measurements can identify different people as having diabetes. We used data from 117 population-based studies and quantified, in different world regions, the prevalence of diagnosed diabetes, and whether those who were previously undiagnosed and detected as having diabetes in survey screening, had elevated FPG, HbA1c or both. We developed prediction equations for estimating the probability that a person without previously diagnosed diabetes, and at a specific level of FPG, had elevated HbA1c, and vice versa. The age-standardized proportion of diabetes that was previously undiagnosed and detected in survey screening ranged from 30% in the high-income western region to 66% in south Asia. Among those with screen-detected diabetes with either test, the age-standardized proportion who had elevated levels of both FPG and HbA1c was 29–39% across regions; the remainder had discordant elevation of FPG or HbA1c. In most low- and middle-income regions, isolated elevated HbA1c was more common than isolated elevated FPG. In these regions, the use of FPG alone may delay diabetes diagnosis and underestimate diabetes prevalence. Our prediction equations help allocate finite resources for measuring HbA1c to reduce the global shortfall in diabetes diagnosis and surveillance.
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    National, regional, and global trends in insufficient physical activity among adults from 2000 to 2022: a pooled analysis of 507 population-based surveys with 5·7 million participants
    (2024-08-01) Strain T.; Flaxman S.; Guthold R.; Semenova E.; Cowan M.; Riley L.M.; Bull F.C.; Stevens G.A.; Raheem R.A.; Agoudavi K.; Anderssen S.A.; Alkhatib W.; Aly E.A.H.; Anjana R.M.; Bauman A.; Bovet P.; Moniz T.B.; Bulotait G.; Caixeta R.; Monteiro E.C.; Morales C.C.; Cortes C.C.; Crochemore-Silva I.; Cyr-Philbert S.; Damasceno A.; Davaakhuu N.; Ahmed M.A.E.; Farnberger C.; Farzadfar F.; Fernando D.; Froboese I.; Fromel K.; Gage R.; Garcia L.; Guwatudde D.; Hamřík Z.; Hansen B.H.; Irianto J.; Aloufi W.J.; Jeon J.; Jáuregui A.; Kagaruki G.B.; Katewongsa P.; Katulanda P.; Khang Y.H.; Malisoux L.; Massad S.; Mayige M.T.; Garcia C.M.; Mielke G.I.; Mendoza R.M.; Moosa S.; Msyamboza K.P.; Mutungi G.; Mwangi K.J.; Ndagijimana A.; Nyandwi A.; Obreja G.; Oh K.; Werneck A.O.; Ondarsuhu D.; Palam E.; Pereira E.; Phy M.; Pisaryk V.; Põlajev A.; Qureshi H.; Razak L.; Riaz B.K.; Richards J.; Rodriguez R.R.; Saamel M.; Savin S.; Schurink-Van Et Klooster T.; Mengue S.S.; Ganapathy S.S.; Shukurov S.; Sigmundova D.; Matos C.S.; Somatunga L.; Spiroski I.; Titze S.; Tjandrarini D.H.; Turley M.; Ugel E.; Uwinkindi F.; Viali S.; Wallmann-Sperlich B.; Wendel-Vos W.; Widyastari D.A.; Yuldashev R.; Zoma L.R.; Strain T.; Mahidol University
    Background: Insufficient physical activity increases the risk of non-communicable diseases, poor physical and cognitive function, weight gain, and mental ill-health. Global prevalence of adult insufficient physical activity was last published for 2016, with limited trend data. We aimed to estimate the prevalence of insufficient physical activity for 197 countries and territories, from 2000 to 2022. Methods: We collated physical activity reported by adults (aged ≥18 years) in population-based surveys. Insufficient physical activity was defined as not doing 150 minutes of moderate-intensity activity, 75 minutes of vigorous-intensity activity, or an equivalent combination per week. We used a Bayesian hierarchical model to compute estimates of insufficient physical activity by country or territory, year, age, and sex. We assessed whether countries or territories, regions, and the world would meet the global target of a 15% relative reduction of the prevalence of insufficient physical activity by 2030 if 2010–22 trends continue. Findings: We included 507 surveys across 163 countries and territories. The global age-standardised prevalence of insufficient physical activity was 31·3% (95% uncertainty interval 28·6–34·0) in 2022, an increase from 23·4% (21·1–26·0) in 2000 and 26·4% (24·8–27·9) in 2010. Prevalence was increasing in 103 (52%) of 197 countries and territories and six (67%) of nine regions, and was declining in the remainder. Prevalence was 5 percentage points higher among female (33·8% [29·9–37·7]) than male (28·7% [25·0–32·6]) individuals. Insufficient physical activity increased in people aged 60 years and older in all regions and both sexes, but age patterns differed for those younger than 60 years. If 2010–22 trends continue, the global target of a 15% relative reduction between 2010 and 2030 will not be met (posterior probability <0·01); however, two regions, Oceania and sub-Saharan Africa, were on track with considerable uncertainty (posterior probabilities 0·70–0·74). Interpretation: Concerted multi-sectoral efforts to reduce insufficient physical activity levels are needed to meet the 2030 target. Physical activity promotion should not exacerbate sex, age, or geographical inequalities. Funding: Ministry of Public Health, Qatar, and World Health Organization. Translations: For the Spanish and Portuguese translations of the abstract see Supplementary Materials section.