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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).
General and abdominal adiposity and hypertension in eight world regions: a pooled analysis of 837 population-based studies with 7·5 million participants
Zhou, Bin;Bennett, James E;Wickham, Aidan P;Singleton, Rosie K;Mishra, Anu;Carrillo-Larco, Rodrigo M;Ikeda, Nayu;Jain, Lakshya;Barradas-Pires, Ana;Heap, Rachel A;Lhoste, Victor PF;Sheffer, Kate E;Phelps, Nowell H;Rayner, Archie W;Gregg, Edward W;Woodward, Mark;Stevens, Gretchen A;Iurilli, Maria LC;Danaei, Goodarz;Di Cesare, Mariachiara;Aguilar-Salinas, Carlos A;Ahmad, Noor Ani;Bovet, Pascal;Chen, Zhengming;Damasceno, Albertino;Filippi, Sarah L;Janszky, Imre;Kengne, Andre P;Khang, Young-Ho;Khunti, Kamlesh;Laxmaiah, Avula;Lim, Lee-Ling;Lissner, Lauren;Margozzini, Paula;Mbanya, Jean Claude N;McGarvey, Stephen T;Shaw, Jonathan E;Söderberg, Stefan;Soto-Mota, Luis Adrián;Wang, Junyang;Zaccardi, Francesco;Abarca-Gómez, Leandra;Abbasi-Kangevari, Mohsen;Abdrakhmanova, Shynar;Abdul Ghaffar, Suhaila;Abdul Rahim, Hanan F;Abdurrahmonova, Zulfiya;Abu-Rmeileh, Niveen M;Acosta-Cazares, Benjamin;Adam, Ishag;Adamczyk, Marzena;Aekplakorn, Wichai;Agdeppa, Imelda A;Aghazadeh-Attari, Javad;Agyemang, Charles;Ahmad, Mohamad Hasnan;Ahmadi, Ali;Ahmadi, Naser;Ahmadi, Nastaran;Ahmed, Soheir H;Ahrens, Wolfgang;Aitmurzaeva, Gulmira;Ajlouni, Kamel;Al-Hazzaa, Hazzaa M;Al-Hinai, Halima;Al-Lawati, Jawad A;Al-Raddadi, Rajaa;Al Asfoor, Deena;Al Hourani, Huda M;Alarouj, Monira;AlBuhairan, Fadia;AlDhukair, Shahla;Ali, Mohamed M;Alieva, Anna V;Alkandari, Abdullah;Alkhatib, Buthaina M;Aly, Eman;Amarapurkar, Deepak N;Amiano Etxezarreta, Pilar;Amougou, Norbert;Andersen, Lars Bo;Anderssen, Sigmund A;Androutsos, Odysseas;Anjana, Ranjit Mohan;Ansari-Moghaddam, Alireza;Anufrieva, Elena;Aounallah-Skhiri, Hajer;Aris, Tahir;Arku, Raphael E;Arlappa, Nimmathota;Aryal, Krishna K;Assah, Felix K;Assembekov, Batyrbek;Assunção, Maria Cecília F;Auvinen, Juha;Avdičová, Mária;Azad, Kishwar;Azevedo, Ana;Azimi-Nezhad, Mohsen;Azizi, Fereidoun;Bacopoulou, Flora;Bahijri, Suhad;Bajramovic, Izet;Balakrishna, Nagalla;Bamoshmoosh, Mohamed;Banach, Maciej;Bandosz, Piotr;Banegas, José R;Baran, Rafał;Barbagallo, Carlo M;Barbosa 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Magdalena;Zejglicova, Kristyna;Zeljkovic Vrkic, Tajana;Zhang, Bing;Zhang, Zhen-Yu;Zhecheva, Yanitsa V;Zholdin, Bekbolat;Zimmet, Paul;Zins, Marie;Zuñiga Cisneros, Julio;Zuziak, Monika;Ezzati, Majid
2024
Abstract
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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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/509592
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simulazione ASN
Il report seguente simula gli indicatori relativi alla propria produzione scientifica in relazione alle soglie ASN 2023-2025 del proprio SC/SSD. Si ricorda che il superamento dei valori soglia (almeno 2 su 3) è requisito necessario ma non sufficiente al conseguimento dell'abilitazione. La simulazione si basa sui dati IRIS e sugli indicatori bibliometrici alla data indicata e non tiene conto di eventuali periodi di congedo obbligatorio, che in sede di domanda ASN danno diritto a incrementi percentuali dei valori. La simulazione può differire dall'esito di un’eventuale domanda ASN sia per errori di catalogazione e/o dati mancanti in IRIS, sia per la variabilità dei dati bibliometrici nel tempo. Si consideri che Anvur calcola i valori degli indicatori all'ultima data utile per la presentazione delle domande.
La presente simulazione è stata realizzata sulla base delle specifiche raccolte sul tavolo ER del Focus Group IRIS coordinato dall'Università di Modena e Reggio Emilia e delle regole riportate nel DM 589/2018 e allegata Tabella A. Cineca, l'Università di Modena e Reggio Emilia e il Focus Group IRIS non si assumono alcuna responsabilità in merito all’uso che il diretto interessato o terzi faranno della simulazione. Si specifica inoltre che la simulazione contiene calcoli effettuati con dati e algoritmi di pubblico dominio e deve quindi essere considerata come un mero ausilio al calcolo svolgibile manualmente o con strumenti equivalenti.