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1. Central obesity accelerates leukocyte telomere length (LTL) shortening in apparently healthy adults: A systematic review and meta-analysis.

Author

Zadeh FA, Bokov DO, Yasin G, Vahdat S, and Abbasalizad-Farhangi M

Subjects
Humans, Adult, Risk Factors, Body Mass Index, Leukocytes, Telomere, Obesity, Abdominal, Obesity
Abstract

Shorter telomere length is associated with numerous comorbidities; central obesity might trigger leukocyte telomere shortening; in the current meta-analysis we evaluated the association of central obesity with leukocyte telomere length among adults. A systematic search from Scopus, PubMed, Embase and Proquest electronic databases up to May 2021 was done. The final screening, provided five articles to be included in final meta-analysis. Those in the highest category of telomere length had 3.72 cm lower waist circumference (WC) compared with those in the lowest category (WMD=-3.718; CI=-7.180, -0.257 P = 0.035; I 2 = 95.4%). Also, those in the highest LTL category had 0.02 lower waist to hip ratio (WHR) compared with those in the lowest category, although this association was not significant (WMD: -0.02; CI=-0.04, 0.01; P = 0.19; I 2 = 90.7%). In quality assessment of included studies, all of the studies had moderate or high quality score and there was no study with poor quality. Higher leukocyte telomere length was accompanied with lower WC among adults. This association was not significant for difference in WHR. Because of the high heterogeneity values and also because of the observational design of included studies, the inference of causality of these associations needs further investigations.Supplemental data for this article is available online at https://doi.org/10.1080/10408398.2021.1971155 .

Published
2023
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2. Hypothalamic-pituitary hormones will be affected by the interaction between 5q13-14-rs2239670 (CARTPT) gene variants and diet in different obesity phenotypes.

Author

Mahmoudinezhad M, Abbasalizad-Farhangi M, and Kahroba H

Subjects
Cross-Sectional Studies, Female, Humans, Nerve Tissue Proteins, Phenotype, Pituitary Hormones, Diet, Obesity genetics
Abstract

Objective: Evidence show that cocaine and amphetamine regulated transcript-prepropeptide (CART-PT) gene variants may affect obesity related traits, but little is known about its end points. In the current study, we aimed to evaluate the interaction of CARTPT gene polymorphism with diet quality indices including dietary approaches to stop hypertension (DASH) and Mediterranean diet score (MDS) on cardio-metabolic risk factors. This cross sectional study recruited 288 apparently healthy obese individuals. Diet quality indices including DASH and MDS were evaluated using semi quantitative food frequency questionnaire (FFQ). Polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) was used for CARTPT genotypes., Results: No significant differences was reported for general characteristics and biochemical parameters across genotypes except for QUICKI among females (P = 0.01) and it was higher in heterozygous genotype. There was significant CARTPT-DASH interactions affecting serum fasting glucose level (P = 0.049). However, in relation to CERTPT-MDS interactions, the highest level of insulin (P = 0.003) and HOMA-IR (P = 0.003) values were shown among AA carriers in high adherence to MDS, while AA carriers in high compliance to MDS experienced decreased level of QUICKI (P = 0.001)., (© 2021. The Author(s).)

Published
2021
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3. Alpha-lipoic acid supplementation significantly reduces the risk of obesity in an updated systematic review and dose response meta-analysis of randomised placebo-controlled clinical trials.

Author

Vajdi M and Abbasalizad Farhangi M

Subjects
Body Mass Index, Body Weight drug effects, Female, Humans, Male, Obesity prevention & control, Waist Circumference drug effects, Waist-Hip Ratio, Weight Loss, Antioxidants therapeutic use, Dietary Supplements statistics & numerical data, Obesity drug therapy, Thioctic Acid therapeutic use
Abstract

Background: There are numerous trials reported the effect of alpha-lipoic acid (ALA) on obesity measurements; while no summarised dose-response meta-analysis is available to address the effects of dose and duration of ALA supplementation on obesity measurements. We aimed to summarise the results of studies evaluating the effects of ALA supplementation on obesity measurements in a systematic review and dose-response meta-analysis., Methods and Materials: In a systematic search from Scopus, PubMed, Embase, Proquest electronic databases up to January 2020 relevant studies were retrieved. Randomised, placebo-controlled trials investigating the effect of ALA supplementation on obesity measurements including weight, body mass index (BMI), waist circumference (WC), waist to hip ratio (WHR) and fat mass (FM) were included. Two class and dose-response meta-analysis were performed to data analysis., Results: Totally, 18, 21 and 8 studies were included for the meta-analysis of ALA-weight, ALA-BMI, ALA-WC, respectively. In the two-class meta-analysis, ALA treatment significantly reduced weight (WMD: -2.29 kg, 95% CI: -2.98, 1.60, P < .01) and BMI (WMD: -0.49 kg/m 2 , 95% CI:-0.83,-0.15, P = .005) but no effect on WC (WMD: -2.57 cm, 95% CI: -8.91, 3.76; P = .426). While the dose-response meta-analysis revealed that the duration of ALA treatment is a significant factor affecting WC reduction (P non-linearity  = .047). While no evidence of departure from linearity was observed for other variables; moreover, subgrouping also revealed that gender could be an important factor affecting the ALA impact on WC which was significant among women (WMD: -4.099; CI: -7.837, -0.361; P = .032)., Conclusion: According to our finding, ALA treatment significantly reduced BMI, weight in a two-class meta-analysis without evidence of departure from linearity in terms of dose or duration. While the association of ALA treatment on WC is dependent to the duration of the study. Although further trials evaluating the other obesity measurements specially central obesity will be helpful to infer a more reliable result., (© 2020 John Wiley & Sons Ltd.)

Published
2020
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4. Association of major dietary patterns and different metabolic phenotypes: a population-based study of northwestern Iran.

Author

Nikniaz L, Abbasalizad Farhangi M, Tabrizi JS, and Nikniaz Z

Subjects
Adult, Animals, Cardiovascular Diseases epidemiology, Cross-Sectional Studies, Female, Humans, Iran epidemiology, Male, Meat, Middle Aged, Body Mass Index, Diet, Feeding Behavior, Metabolic Syndrome epidemiology, Obesity epidemiology, Phenotype
Abstract

Background: Finding the relationship between the major dietary patterns and cardiometabolic phenotypes could be used for planning prevention programs based on the cultural and dietary habits to prevent transient from a metabolically healthy state to an unhealthy state. So, we aimed to assess the association between dietary patterns and cardiometabolic phenotypes in the northwestern population of Iran., Method: In the present cross-sectional and population-based study, 504 adults sampled by cluster sampling in East-Azerbaijan, Iran. Factor analysis was used for determining the dietary pattern. Metabolic phenotypes were determined according to body mass index (BMI) cut-off point (25 kg/m 2 ), and the presence of the metabolic syndrome. The independent sample t-test, one-way ANOVA, chi-square, and multinomial regression were used for statistical analysis., Results: In both adjusted (OR: 2.24, 95% CI: 1.17, 4.31) and unadjusted models (OR: 3.14, 95% CI: 1.54, 5.42), the last tertile of the animal dietary pattern was associated with metabolically healthy obese (MHO) phenotypes. After adjusting, the last tertile of the animal dietary pattern was significantly associated with an increase of metabolically unhealthy obese (MUHO) phenotype (OR: 2.61, 95% CI: 1.18, 5.76)., Conclusion: In the present study, the animal dietary pattern was associated with MHO and MUHO phenotypes. It is suggested that some measures should be taken to strengthen nutrition education for the population and advocate a balanced diet to improve the condition.

Published
2019
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5. A structural equation modeling approach for the association of a healthy eating index with metabolic syndrome and cardio-metabolic risk factors among obese individuals.

Author

Khodarahmi M, Asghari-Jafarabadi M, and Abbasalizad Farhangi M

Subjects
Adult, Cardiovascular Diseases etiology, Cardiovascular Diseases prevention & control, Cross-Sectional Studies, Diet, Healthy standards, Feeding Behavior, Female, Humans, Latent Class Analysis, Male, Metabolic Syndrome etiology, Metabolic Syndrome prevention & control, Middle Aged, Nutrition Policy, Obesity complications, Obesity metabolism, Risk Assessment methods, Risk Factors, Socioeconomic Factors, Surveys and Questionnaires statistics & numerical data, Young Adult, Cardiovascular Diseases epidemiology, Diet, Healthy statistics & numerical data, Metabolic Syndrome epidemiology, Models, Biological, Obesity diet therapy, Patient Compliance statistics & numerical data
Abstract

Background: Numerous studies have evaluated the association between dietary factors and cardiovascular risk among patients with chronic disease. It is worthwhile to assess these associations in a combination model rather than in an isolated form. In the current study, we aimed to use structural equation modeling (SEM) to assess the association of adherence to a healthy eating index (HEI)-2015 with socio-demographic factors, psychological characteristics, metabolic syndrome (MetS) and other cardio-metabolic risk factors among obese individuals., Methods: This cross-sectional study was conducted among 188 healthy obese adults (96 males and 92 females) aged 20-50 years in Tabriz. A validated semi-quantitative food frequency questionnaire (FFQ) was used to record dietary intake and to estimate HEI-2015. Anthropometric parameters, blood pressure and biochemical measurements were evaluated according to standard protocols. Interrelationships among socio-demographic parameters and HEI with cardio-metabolic risk factors were analyzed using SEM., Results: The results of SEM analysis revealed that HEI mediated the association between age and several cardio-metabolic risk factors including fat mass (FM), fat free mass (FFM), systolic blood pressure (SBP) and high-density lipoprotein (HDL) (p < 0.05). Moreover, adherence to Dietary Guidelines for Americans (DGA) appears to mediate association between gender and waist circumference (B = -9.78), SBP (B = -4.83), triglyceride (B = -13.01) and HDL (B = 4.31). HEI also mediated indirect negative effects of socioeconomic status on FM (B = -0.56), FFM (B = -0.25), SBP (B = -0.55) and diastolic blood pressure (DBP) (B = -0.3). Additionally, depression and age had indirect unfavorable effects on some insulin resistance indices such as homeostasis model assessment of insulin resistance (B = 0.07; p<0.05, for age) and quantitative insulin sensitivity check index (p<0.05, for age and depression) via HEI. High adherence to HEI was found to be inversely associated with MetS risk (p<0.05)., Conclusion: Adherence to HEI-2015 seems to mediate the effect of socio-demographic parameters and mental health on cardio-metabolic risk factors as well as MetS risk. Further studies are needed to confirm these findings., Competing Interests: The authors have declared that no competing interests exist.

Published
2019
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6. Higher dietary acid load potentially increases serum triglyceride and obesity prevalence in adults: An updated systematic review and meta-analysis.

Author

Abbasalizad Farhangi M, Nikniaz L, and Nikniaz Z

Subjects
Adult, Humans, Obesity blood, Prognosis, Acids adverse effects, Diet adverse effects, Obesity etiology, Triglycerides blood
Abstract

Background: In the current meta-analysis, we aimed to systematically review and summarize the eligible studies evaluating the association between dietary acid load in terms of potential renal acid load (PRAL) and net-endogenous acid production (NEAP) with anthropometric parameters and serum lipids in adult population., Methods: In a systematic search from PubMed, Scopus, Web of Sciences and Cochrane electronic databases up to December 2018, relevant studies were included. Cross-sectional, case control or cohort studies evaluating the association between PRAL and NEAP with the mean values of body mass index (BMI), waist circumference (WC), low and high density lipoprotein cholesterol (LDL, HDL), triglyceride (TG), total cholesterol (TC) and the prevalence of obesity were included., Results: According to our results, having higher dietary acid load content in terms of high PRAL scores was associated with higher triglyceride concentrations (weighted mean difference (WMD): 3.468; confidence interval (CI): -0.231, 7.166, P = 0.04) and higher obesity prevalence (30% and 27% in highest versus lowest categories). Accordingly, being in the highest category of NEAP was associated with higher prevalence of obesity (25% and 22% in highest versus lowest category). In subgroup analysis, higher PRAL scores was associated with higher BMI in women (WMD: 0.122; CI: -0.001, 0.245; P = 0.049) and higher NEAP in men (WMD: 0.890; CI: 0.430, 1.350; P < 0.001). There was no association between dietary acid load and other studied parameters., Conclusions: In the current meta-analysis, high dietary acid load content was associated with higher serum triglyceride concentrations and higher obesity prevalence. Reducing dietary acid load content might be a useful preventive strategy against obesity and metabolic disorders., Competing Interests: The authors have declared that no competing interests exist.

Published
2019
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7. Oxidative stress-induced cognitive impairment in obesity can be reversed by vitamin D administration in rats.

Author

Hajiluian G, Abbasalizad Farhangi M, Nameni G, Shahabi P, and Megari-Abbasi M

Subjects
Animals, Biomarkers blood, Catalase metabolism, Cognitive Dysfunction blood, Diet, High-Fat adverse effects, Glutathione Peroxidase metabolism, Hippocampus drug effects, Hippocampus metabolism, Male, Malondialdehyde metabolism, NF-kappa B metabolism, Obesity blood, Rats, Rats, Wistar, Superoxide Dismutase metabolism, Thiobarbituric Acid Reactive Substances, Tumor Necrosis Factor-alpha metabolism, Vitamin D blood, Cognitive Dysfunction prevention & control, Obesity drug therapy, Oxidative Stress drug effects, Vitamin D pharmacology
Abstract

Background: There is evidence that obesity leads to cognitive impairments via several markers of oxidative stress including glutathione peroxidase (GPx), superoxide dismutase (SOD), catalase and malondialdehyde (MDA) in the hippocampus. Increased inflammatory markers in the brain have obesity triggering effects. In the current study we aimed to investigate the effects of vitamin D on cognitive function, nuclear factor (NF)-κB, tumor necrosis factor (TNF)-α concentration and markers of oxidative stress in the hippocampus of high-fat diet-induced obese rats., Methods and Materials: Forty male Wistar rats were divided into two groups: control diet (CD) and high-fat diet (HFD) for 16 weeks; then each group subdivided into two groups including: CD, CD + vitamin D, HFD and HFD + vitamin D. Vitamin D was administered at 500 IU/kg dosage for 5 weeks. Four weeks after supplementation, Morris water maze test was performed. NF-κB and TNF-α concentration in the hippocampus were determined using ELISA kits. Moreover, oxidative stress markers in the hippocampus including GPx, SOD, MDA and CAT concentrations were measured by spectrophotometry methods., Results: HFD significantly increased TNF-α (P = 0.04) and NF-κB (P = 0.01) concentrations in the hippocampus compared with CD. Vitamin D treatment led to a significant reduction in hippocampus NF-κB concentrations in HFD + vitamin D group (P = 0.001); however, vitamin D had no effect on TNF-α concentrations. Moreover, HFD significantly induced oxidative stress by reducing GPx, SOD and increasing MDA concentrations in the hippocampus. Vitamin D supplementation in HFD group also significantly increased GPx, SOD and reduced MDA concentrations., Conclusion: Vitamin D improved hippocampus oxidative stress and inflammatory markers in HFD-induced obese rats and improved cognitive performance. Further studies are needed to better clarify the underlying mechanisms.

Published
2018
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8. Vitamin D administration, cognitive function, BBB permeability and neuroinflammatory factors in high-fat diet-induced obese rats.

Author

Hajiluian G, Nameni G, Shahabi P, Mesgari-Abbasi M, Sadigh-Eteghad S, and Farhangi MA

Subjects
Animals, Energy Metabolism, Hippocampus drug effects, Hippocampus pathology, Male, NF-kappa B metabolism, Nerve Tissue Proteins metabolism, Obesity pathology, Permeability, Rats, Rats, Wistar, Vitamins pharmacology, Blood-Brain Barrier drug effects, Brain-Derived Neurotrophic Factor metabolism, Cognition drug effects, Diet, High-Fat, Hippocampus metabolism, Inflammation Mediators metabolism, Obesity metabolism, Vitamin D pharmacology
Abstract

Objectives: The purpose of this research was to investigate the effects of vitamin D administration on cognitive function, nuclear factor-κB (NF-κB), brain-derived neurotrophic factor (BDNF) concentration in the hippocampus and blood-brain barrier (BBB) permeability in high-fat diet (HFD)-induced obese rats., Methods: Male Wistar rats were fed either a control diet or HFD for 16 weeks (n=20); then, each group was randomized into two subgroups supplemented orally with 500 IU kg -1 vitamin D for 5 weeks. A Morris water maze (MWM) test was performed at the 21st week to examine cognitive function. BBB permeability was characterized by Evans blue dye in the hippocampus. BDNF and NF-κB concentrations in the hippocampus and serum vitamin D concentrations were also measured., Results: HFD led to a significant delay in escape latency time and reduced time of MWM probe test because of increased NF-κB and decreased BDNF concentrations in the hippocampus. Vitamin D supplementation in the HFD group significantly reduced body weight, NF-κB concentrations, BBB permeability and increased BDNF concentrations in the hippocampus., Conclusions: Vitamin D reversed HFD-induced cognitive impairments by reduction of the NF-κB and elevation of BDNF concentrations and modulation of the BBB permeability in rats' hippocampus.

Published
2017
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9. SERUM CONCENTRATIONS OF CHOLECYSTOKININ, PEPTIDE YY, GHRELIN AND HIGH SENSITIVE C-REACTIVE PROTEIN IN ASSOCIATION WITH METABOLIC SYNDROME INGREDIENTS IN OBESE INDIVIDUALS.

Author

Abbasi, M. and Abbasalizad Farhangi, M.

Subjects
*GHRELIN, *C-reactive protein, *METABOLIC syndrome, *GASTROINTESTINAL hormones, *SYSTOLIC blood pressure, *TYPE 2 diabetes, *OBESITY, *PEPTIDE YY
Abstract

Objective. Metabolic syndrome (MetS) is a metabolic condition with high prevalence worldwide. This study aims to examine the relationship between serum concentrations of gastrointestinal hormones such as cholecystokinin (CCK), ghrelin, peptide YY (PYY), and high sensitive C-reactive protein (hs-CRP) and the ingredients of MetS in obese population. Subjects and Methods. This case-control study included 40 obese subjects (20 with MetS and 20 BMI and age-matched control individuals). The age range of the participants was 20-50 years and the participants' anthropometric characteristics were measured. Serum lipids and the concentrations of oxidized low density lipoprotein (Ox-LDL), insulin, hs-CRP, CCK, PYY, and ghrelin were assessed with commercial ELISA kits. Results. Serum levels of hs-CRP, total cholesterol (TC) and triglycerides (TG) in patients with MetS were significantly higher while CCK and insulin concentrations were higher in obese non- MetS group (P <0.05). PYY had a negative association with waist circumference (WC) and high density lipoprotein cholesterol (HDL-C) and ghrelin had a positive association with systolic blood pressure (SBP) and TC in obese control group (P < 0.05). In obese patients with MetS, hs-CRP had a strong positive association with TG. Conclusion. The current study revealed the possible role of hs-CRP and several GI- hormones in the pathogenesis of obesity-associated diseases and MetS. Additional works are needed to elucidate the possible underlying mechanisms and clarify several controversies in this issue. [ABSTRACT FROM AUTHOR]

Published
2020
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10. SERUM TRANSFORMING GROWTH FACTOR β (TGF-β) IS ASSOCIATED WITH BODY MASS INDEX IN HEALTHY WOMEN.

Author

Abbasalizad Farhangi, M., Saboor-Yaraghi, A. A., Eshraghian, M., Ostadrahimi, A., and Keshavarz, S. A.

Subjects
*SERUM, *GROWTH factors, *BODY mass index, *WOMEN'S health, *DIABETES
Abstract

Background. Elevated serum transforming growth factor-β (TGF-β) is associated with diabetes, cancers and several other diseases in numerous studies. However, there are a few studies reporting the possible relationship between serum TGF-β and obesity indices in apparently healthy individuals. In the present study we examined the possible relationship between body mass index (BMI), fasting serum glucose, lipid profile and liver enzymes in healthy women. Materials and methods. A total of 84 women (BMI 30.12 ± 5.74 kg/m²) were investigated. Anthropometric variables (weight, height, waist circumference and hip circumference) were measured in participants and BMI and waist to hip ratio (WHR) were calculated. Serum concentrations of TGF-β, fasting serum glucose (FSG), serum lipids and liver enzymes were assayed by commercial Enzyme-linked immunosorbent assay (ELISA) kits. Results. Among anthropometric variables, BMI and WC were potent positive predictors of serum TGF-β in stepwise multiple linear regression model (P<0.05). Serum ALT concentration was also positively correlated with serum TGF-β after adjustment for age and other biochemical variables (P = 0.031). In simple correlation analysis, serum TGF-β was positively associated with fat mass and negatively with fat free mass (P < 0.05). Conclusions. Our study confirms that serum TGF-β concentration is associated with indices of both general (BMI) and central obesity (WC), fat mass and liver enzyme in healthy Iranian women. Further studies are needed to possibly confirm these findings and to explore underlying mechanisms. [ABSTRACT FROM AUTHOR]

Published
2013
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11. Mapping local patterns of childhood overweight and wasting in low- and middle-income countries between 2000 and 2017

Author

Kinyoki, Damaris K., Ross, Jennifer M., Lazzar-Atwood, Alice, Munro, Sandra B., Schaeffer, Lauren E., Abbasalizad-Farhangi, Mahdieh, Abbasi, Masoumeh, Abbastabar, Hedayat, Abdelalim, Ahmed, Abdoli, Amir, Abdollahi, Mohammad, Abdollahpour, Ibrahim, Abdulkader, Rizwan Suliankatchi, Abebe, Nebiyu Dereje, Abebo, Teshome Abuka, Abegaz, Kedir Hussein, Abolhassani, Hassan, Abreu, Lucas Guimarães, Abrigo, Michael R. M., Abushouk, Abdelrahman I., Accrombessi, Manfred Mario Kokou, Acharya, Dilaram, Adabi, Maryam, Adebiyi, Akindele Olupelumi, Adedeji, Isaac Akinkunmi, Adekanmbi, Victor, Adeoye, Abiodun Moshood, Adetokunboh, Olatunji O., Adham, Davoud, Aduroja, Posi Emmanuel, Advani, Shailesh M., Afarideh, Mohsen, Aghaali, Mohammad, Agrawal, Anurag, Ahmad, Tauseef, Ahmadi, Keivan, Ahmadi, Sepideh, Ahmed, Muktar Beshir, Ahmed, Rushdia, Ajumobi, Olufemi, Akal, Chalachew Genet, Akalu, Temesgen Yihunie, Akinyemiju, Tomi, Akombi, Blessing, Al-Aly, Ziyad, Alam, Samiah, Alamene, Genet Melak, Alanzi, Turki M., Rabanal, Jacqueline Elizabeth Alcalde, Alema, Niguse Meles, Ali, Beriwan Abdulqadir, Ali, Muhammad, Alijanzadeh, Mehran, Alinia, Cyrus, Alipour, Vahid, Alizade, Hesam, Aljunid, Syed Mohamed, Almasi, Afshin, Almasi-Hashiani, Amir, Al-Mekhlafi, Hesham M., Al-Raddadi, Rajaa M., Altirkawi, Khalid, Alvis-Guzman, Nelson, Alvis-Zakzuk, Nelson J., Amare, Azmeraw T., Amegah, Adeladza Kofi, Amini, Saeed, Rarani, Mostafa Amini, Amiri, Fatemeh, Amit, Arianna Maever Loreche, Anber, Nahla Hamed, Andrei, Catalina Liliana, Ansari, Fereshteh, Ansari-Moghaddam, Alireza, Anteneh, Zelalem Alamrew, Antonio, Carl Abelardo T., Antriyandarti, Ernoiz, Anvari, Davood, Anwer, Razique, Appiah, Seth Christopher Yaw, Arabloo, Jalal, Arab-Zozani, Morteza, Araya, Ephrem Mebrahtu, Arefi, Zohreh, Aremu, Olatunde, Ärnlöv, Johan, Arzani, Afsaneh, Asadi-Aliabadi, Mehran, Asadi-Pooya, Ali A., Asgari, Samaneh, Asghari, Babak, Ashagre, Alebachew Fasil, Asrat, Anemaw A., Ataeinia, Bahar, Atalay, Hagos Tasew, Atnafu, Desta Debalkie, Atout, Maha Moh’d Wahbi, Ausloos, Marcel, Avokpaho, Euripide F. G. A., Awasthi, Ashish, Quintanilla, Beatriz Paulina Ayala, Ayanore, Martin Amogre, Aynalem, Yared A. Asmare, Azadmehr, Abbas, Azari, Samad, Azarian, Ghasem, Azene, Zelalem Nigussie, Babaee, Ebrahim, Badawi, Alaa, Badiye, Ashish D., Bahrami, Mohamad Amin, Baig, Atif Amin A., Bakhtiari, Ahad, Bakkannavar, Shankar M., Balakrishnan, Senthilkumar, Bali, Ayele Geleto, Banach, Maciej, Banik, Palash Chandra, Baradaran-Seyed, Zahra, Baraki, Adhanom Gebreegziabher, Barboza, Miguel A., Bärnighausen, Till Winfried, Barua, Lingkan, Basaleem, Huda, Basu, Sanjay, Bayati, Mohsen, Bayih, Mulat Tirfie, Baynes, Habtamu Wondifraw, Bedi, Neeraj, Behzadifar, Masoud, Behzadifar, Meysam, Bekele, Yibeltal Alemu, Bennett, Derrick A., Berbada, Dessalegn Ajema, Berhe, Kidanemaryam, Berhe, Abadi Kidanemariam, Berman, Adam E., Bernstein, Robert S., Bhageerathy, Reshmi, Bhandari, Dinesh, Bharadwaj, Pankaj, Bhattacharjee, Natalia V., Bhattacharyya, Krittika, Bijani, Ali, Bikbov, Boris, Bilano, Ver, Bililign, Nigus, Sayeed, Muhammad Shahdaat Bin, Birara, Setognal, Birhane, Minuye Biniam Biniam, Birhanu, Minyichil, Biswas, Raaj Kishore, Bitew, Zebenay Workneh, Bogale, Kassawmar Angaw, Bohlouli, Somayeh, Bolla, Srinivasa Rao, Boloor, Archith, Borzì, Antonio M., Borzouei, Shiva, Brady, Oliver J., Bragazzi, Nicola Luigi, Braithwaite, Dejana, Briko, Nikolay Ivanovich, Britton, Gabrielle, Budhathoki, Shyam S., Nagaraja, Sharath Burugina, Busse, Reinhard, Butt, Zahid A., Cahuana-Hurtado, Lucero, Cámera, Luis Alberto, Campos-Nonato, Ismael R., Cano, Jorge, Car, Josip, Cárdenas, Rosario, Carrero, Juan J., Carvalho, Félix, Castaldelli-Maia, João Mauricio, Castañeda-Orjuela, Carlos A., Castro, Franz, Cerin, Ester, Chansa, Collins, Charan, Jaykaran, Chatterjee, Pranab, Chattu, Vijay Kumar, Chauhan, Bal Govind, Chavshin, Ali Reza, Chehrazi, Mohammad, Chichiabellu, Tesfaye Yitna, Chin, Ken Lee, Christopher, Devasahayam J., Chu, Dinh-Toi, Cicuttini, Flavia M., Collison, Michael L., Cork, Michael A., Cormier, Natalie, Cortesi, Paolo Angelo, Costa, Vera M., Dadi, Abel Fekadu Fekadu, Dagnew, Baye, Dahlawi, Saad M. A., Damiani, Giovanni, Darwish, Amira Hamed, Daryani, Ahmad, Das, Jai K., Gupta, Rajat Das, Dávila-Cervantes, Claudio, Davis Weaver, Nicole, Leo, Diego De, Neve, Jan-Walter De, Demeke, Feleke Mekonnen, Demis, Asmamaw Bizuneh, Demissie, Dereje Bayissa, Demoz, Gebre Teklemariam, Denova-Gutiérrez, Edgar, Deribe, Kebede, Desai, Rupak, Desalegn, Beruk Berhanu, Desalew, Assefa, Deshpande, Aniruddha, Dey, Sagnik, Dharmaratne, Samath Dhamminda, Dhillon, Preeti, Dhimal, Meghnath, Dhungana, Govinda Prasad, Nasab, Mostafa Dianati, Diaz, Daniel, Forooshani, Zahra Sadat Dibaji, Dinsa, Girmaye Deye, Dipeolu, Isaac Oluwafemi, Djalalinia, Shirin, Do, Hoa Thi, Do, Huyen Phuc, Doku, Paul Narh, Dorostkar, Fariba, Doshmangir, Leila, Dubey, Manisha, Adema, Bereket Duko, Dunachie, Susanna J., Duncan, Bruce B., Cousin, Ewerton, Durães, Andre R., Earl, Lucas, Leylabadlo, Hamed Ebrahimzadeh, Eftekhari, Aziz, El Sayed, Iman, El Sayed Zaki, Maysaa, El Tantawi, Maha, Elbarazi, Iffat, Elemineh, Demelash Abewa, El-Jaafary, Shaimaa I., El-Khatib, Ziad, Elsharkawy, Aisha, El-Sherbiny, Yasser Mohamed, Elyazar, Iqbal R. F., Emamian, Mohammad Hassan, Enany, Shymaa, Endalew, Daniel Adane, Endalifer, Melese Linger, Eskandari, Khalil, Eskandarieh, Sharareh, Esmaeilnejad, Saman, Esteghamati, Alireza, Etemadi, Arash, Etisso, Atkilt Esaiyas, Fanzo, Jessica, Farahmand, Mohammad, Faraj, Anwar, Farashi, Sajjad, Fareed, Mohammad, Farioli, Andrea, Faro, Andre, Farzadfar, Farshad, Farzam, Hossein, Fatima, Syeda Sadia, Fattahi, Nazir, Fauk, Nelsensius Klau, Fazaeli, Ali Akbar, Fentahun, Netsanet, Ferede, Tomas Y., Fereshtehnejad, Seyed-Mohammad, Fernandes, Eduarda, Fernandes, João C., Feyissa, Garumma Tolu, Filip, Irina, Fischer, Florian, Flohr, Carsten, Foigt, Nataliya A., Folayan, Morenike Oluwatoyin, Fomenkov, Artem Alekseevich, Foroutan, Masoud, Förster, Jana, Francis, Joel Msafiri, Fukumoto, Takeshi, Gayesa, Reta Tsegaye, Geberemariyam, Biniyam Sahiledengle, Gebrehiwot, Tsegaye Tewelde, Gebremariam, Hadush, Gebremariam, Kidane Tadesse, Gebremedhin, Ketema Bizuwork Bizuwork, Gebremeskel, Gebreamlak Gebremedhn, Gebreslassie, Assefa Ayalew Ayalew, Gebretsadik, Gebretsadkan G. G., Gedefaw, Getnet Azeze, Geramo, Yilma Chisha Dea, Gesesew, Hailay Abrha, Geta, Birhanu, Getenet, Agegnehu Bante, Gezae, Kebede Embaye, Ghaffarifar, Fatemeh, Ghafourifard, Mansour, Ghajar, Alireza, Ghajarzadeh, Mahsa, Ghashghaee, Ahmad, Ghiasvand, Hesam, Gholamian, Asadollah, Gilani, Syed Amir, Gill, Tiffany K., Ginawi, Ibrahim Abdelmageed, Goli, Srinivas, Gomes, Nelson G. M., Gopalani, Sameer Vali, Goudarzi, Houman, Goulart, Alessandra C., Govindakarnavar, Arunkumar, Grada, Ayman, Grivna, Michal, Guimarães, Rafael Alves, Guled, Rashid Abdi, Guo, Yuming, Gupta, Rahul, Gupta, Rajeev, Hafezi-Nejad, Nima, Haile, Michael Tamene, Haj-Mirzaian, Arvin, Haj-Mirzaian, Arya, Hall, Brian J., Halvaei, Iman, Hamadeh, Randah R., Hamidi, Yadollah, Handiso, Demelash Woldeyohannes, Hankey, Graeme J., Haririan, Hamidreza, Hariyani, Ninuk, Hasaballah, Ahmed I., Hasan, Md. 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D., Iwu, Chinwe Juliana, Izadi, Neda, Jaafari, Jalil, Jaca, Anelisa, Jadidi-Niaragh, Farhad, Balalami, Nader Jafari, Jafarinia, Morteza, Jahani, Mohammad Ali, Jakovljevic, Mihajlo, Jalali, Amir, Jalilian, Farzad, Jayatilleke, Achala Upendra, Jeemon, Panniyammakal, Jehan, Fyezah, Jenabi, Ensiyeh, Jha, Ravi Prakash, Jha, Vivekanand, Ji, John S., Jia, Peng, John, Oommen, John-Akinola, Yetunde O., Johnson, Kimberly B., Jonas, Jost B., Joseph, Nitin, Joukar, Farahnaz, Jozwiak, Jacek Jerzy, Jungari, Suresh Banayya, Jürisson, Mikk, Kabir, Ali, Kabir, Zubair, Kahsay, Amaha, Kahssay, Molla, Kalani, Hamed, Kalankesh, Leila L., Kalhor, Rohollah, Kamiab, Zahra, Kanchan, Tanuj, Kapil, Umesh, Kapoor, Neeti, Karami, Manoochehr, Matin, Behzad Karami, Karch, André, Karim, Mohd A., Karki, Surendra, Kasaeian, Amir, Kasahun, Gebremicheal Gebreslassie, Kasaye, Habtamu Kebebe, Kassa, Tesfaye Dessale, Kassaye, Hagazi Gebremedhin, Kassebaum, Nicholas J., Karyani, Ali Kazemi, Kengne, Andre Pascal, Ketema, Daniel Bekele, Khader, Yousef Saleh, Khafaie, Morteza Abdullatif, Khaksarian, Mojtaba, Khalid, Nauman, Khalil, Ibrahim A., Khalilov, Rovshan, Khan, Asad, Khan, Ejaz Ahmad, Khan, Md Nuruzzaman, Khan, Mohammad Saud, Khan, Muhammad Shahzeb, Khatab, Khaled, Khater, Amir, Khater, Mona M., Khatib, Mahalqua Nazli, Khayamzadeh, Maryam, Khazaei-Pool, Maryam, Khazaei, Mohammad, Khazaei, Salman, Khodayari, Mohammad Taghi, Khosravi, Mohammad Hossein, Khundkar, Roba, Kiadaliri, Ali, Kianipour, Neda, Kiirithio, Daniel N., Kim, Yun Jin, Kimokoti, Ruth W., Kisa, Adnan, Kisa, Sezer, Kolola, Tufa, Komaki, Hamidreza, Kondlahalli, Shivakumar K. M., Koolivand, Ali, Koul, Parvaiz A., Koyanagi, Ai, Kraemer, Moritz U. G., Krishan, Kewal, Krohn, Kris J., Kugbey, Nuworza, Kumar, Manasi, Kumar, Pushpendra, Kumar, Vivek, Kurmi, Om P., Kuti, Oluwatosin, Vecchia, Carlo La, Lacey, Ben, Lad, Deepesh P., Lal, Aparna, Lal, Dharmesh Kumar, Lami, Faris Hasan, Lamichhane, Prabhat, Lang, Justin J., Lansingh, Van C., Lasrado, Savita, Lebedev, Georgy, Lee, Paul H., Lee, Shaun Wen Huey, Leili, Mostafa, Letourneau, Ian D., Lewycka, Sonia, Li, Shanshan, Lim, Lee-Ling, Linn, Shai, Liu, Shiwei, Liu, Simin, Lodha, Rakesh, Longbottom, Joshua, Lopez, Jaifred Christian F., Lorkowski, Stefan, Macarayan, Erlyn Rachelle King, Madadin, Mohammed, El Razek, Hassan Magdy Abd, El Razek, Muhammed Magdy Abd, Maghavani, Dhaval P., Mahasha, Phetole Walter, Mahotra, Narayan Bahadur, Maled, Venkatesh, Maleki, Afshin, Maleki, Shokofeh, Malta, Deborah Carvalho, Manafi, Ali, Manafi, Farzad, Manafi, Navid, Manohar, Narendar Dawanu, Mansour-Ghanaei, Fariborz, Mansouri, Borhan, Mansournia, Mohammad Ali, Mapoma, Chabila Christopher, Marami, Dadi, Marczak, Laurie B., Arnedo, Carlos Alberto Marrugo, Martins-Melo, Francisco Rogerlândio, Masaka, Anthony, Massenburg, Benjamin Ballard, Maulik, Pallab K., Mayala, Benjamin K., Mazidi, Mohsen, Mehndiratta, Man Mohan, Mehri, Freshteh, Mehta, Kala M., Meitei, Wahengbam Bigyananda, Mekonnen, Fantahun Ayenew, Mekonnen, Teferi, Meles, Gebrekiros Gebremichael, Meles, Hagazi Gebre, Melese, Addisu, Mendoza, Walter, Menezes, Ritesh G., Mengesha, Meresa Berwo, Mensah, George A., Meretoja, Tuomo J., Miazgowski, Tomasz, Kostova, Neda Milevska, Miller, Ted R., Mills, Edward J., Mini, G. 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L., Murthy, G. V. S., Musa, Kamarul Imran, Mustafa, Ghulam, Muthupandian, Saravanan, Nabavizadeh, Behnam, Naderi, Mehdi, Nadkarni, Girish N., Nagarajan, Ahamarshan Jayaraman, Naghavi, Mohsen, Naheed, Aliya, Naik, Gurudatta, Najafi, Farid, Nansseu, Jobert Richie, Narayan, K. M. Venkat, Nascimento, Bruno Ramos, Nayak, Vinod, Nazari, Javad, Ndwandwe, Duduzile Edith, Negoi, Ionut, Negoi, Ruxandra Irina, Ngunjiri, Josephine W., Nguyen, Cuong Tat, Nguyen, Huong Lan Thi, Nigatu, Dabere, Nigatu, Yeshambel T., Nikbakhsh, Rajan, Ningrum, Dina Nur Anggraini, Nnaji, Chukwudi A., Nong, Vuong Minh, Noubiap, Jean Jacques, Nowak, Christoph, Oancea, Bogdan, Ofori-Asenso, Richard, Oghenetega, Onome Bright, Oh, In-Hwan, Oladimeji, Olanrewaju, Oladnabi, Morteza, Olagunju, Andrew T., Olagunju, Tinuke O., Olusanya, Bolajoko Olubukunola, Olusanya, Jacob Olusegun, Oluwasanu, Mojisola Morenike, Omer, Muktar Omer, Onwujekwe, Obinna E., Asante, Kwaku Oppong, Oren, Eyal, Orisakwe, Orish Ebere, Ortiz, Alberto, Osarenotor, Osayomwanbo, Osgood-Zimmerman, Aaron E., Owolabi, Mayowa Ojo, P. A., Mahesh, Padubidri, Jagadish Rao, Pakshir, Keyvan, Pana, Adrian, Panda-Jonas, Songhomitra, Parsian, Hadi, Pashaei, Tahereh, Pasupula, Deepak Kumar, Patel, Sangram Kishor, Pathak, Ashish, Pathak, Mona, Pati, Sanghamitra, Patle, Ajay, Patton, George C., Paulos, Kebreab, Toroudi, Hamidreza Pazoki, Pepito, Veincent Christian Filipino, Perico, Norberto, Petri, William A., Pickering, Brandon V., Pigott, David M., Pirestani, Majid, Piroozi, Bakhtiar, Pirsaheb, Meghdad, Pokhrel, Khem Narayan, Postma, Maarten J., Pourjafar, Hadi, Pourmalek, Farshad, Kalhori, Reza Pourmirza, Pourshams, Akram, Poustchi, Hossein, Prada, Sergio I., Preotescu, Liliana, Pribadi, Dimas Ria Angga, Syed, Zahiruddin Quazi, Rabiee, Mohammad, Rabiee, Navid, Radfar, Amir, Rafiei, Alireza, Rahim, Fakher, Rahimi-Movaghar, Vafa, Rahman, Muhammad Aziz, Rahman, Sajjad ur, Rai, Rajesh Kumar, Rajabpour-Sanati, Ali, Rajati, Fatemeh, Ramezanzadeh, Kiana, Rana, Saleem Muhammad, Ranabhat, Chhabi Lal, Rao, Sowmya J., Rasella, Davide, Rashedi, Vahid, Rastogi, Prateek, Rathi, Priya, Rawaf, Salman, Rawaf, David Laith, Rawal, Lal, Ray, Sarah E., Remuzzi, Giuseppe, Renjith, Vishnu, Renzaho, Andre M. N., Resnikoff, Serge, Rezaei, Nima, Rezaeian, Shahab, Rezai, Mohammad Sadegh, Rezapour, Aziz, Riahi, Seyed Mohammad, Ribeiro, Ana Isabel, Rickard, Jennifer, Rodriguez, Alina, Roever, Leonardo, Roro, Elias Merdassa, Roshandel, Gholamreza, Rostami, Ali, Rubagotti, Enrico, Saad, Anas M., Saadatagah, Seyedmohammad, Sabde, Yogesh Damodar, Sabour, Siamak, Sadeghi, Ehsan, Sadeghi, Masoumeh, Safari, Saeed, Safari, Yahya, Safarpour, Hamid, Sagar, Rajesh, Sahebkar, Amirhossein, Sahraian, Mohammad Ali, Sajadi, S. Mohammad, Salahshoor, Mohammad Reza, Salam, Nasir, Salehi, Farkhonde, Zahabi, Saleh Salehi, Salem, Hosni, Salem, Marwa R. 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Departamento de Medicina, Instituto de Investigación Sanitaria Fundación Jiménez Díaz (IIS-FJD), Instituto de Investigación Sanitaria Hospital Universitario de La Princesa (IIS-IP), Veritati - Repositório Institucional da Universidade Católica Portuguesa, Biosciences, University of Helsinki, Clinicum, HUS Comprehensive Cancer Center, Institute for Molecular Medicine Finland, Department of Earth Observation Science, UT-I-ITC-ACQUAL, Faculty of Geo-Information Science and Earth Observation, Sálfræðideild (HR), Department of Psychology (RU), Samfélagssvið (HR), School of Social Sciences (RU), Háskólinn í Reykjavík, Reykjavik University, Instituto de Investigación Sanitaria Fundación Jiménez Díaz (ISS-FJD), Kinyoki, D, Ross, J, Lazzar-Atwood, A, Munro, S, Schaeffer, L, Abbasalizad-Farhangi, M, Abbasi, M, Abbastabar, H, Abdelalim, A, Abdoli, A, Abdollahi, M, Abdollahpour, I, Abdulkader, R, Abebe, N, Abebo, T, Abegaz, K, Abolhassani, H, Abreu, L, Abrigo, M, Abushouk, A, Accrombessi, M, 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Subjects
Male, Local patterns, Double burden, Börn, Research & Experimental Medicine, Sjúkdómseinkenni, DOUBLE BURDEN, Childhood overweight, Lífefnafræði, Læknisfræði, 0302 clinical medicine, Syndemic, Child, 11 Medical and Health Sciences, under 5 years of age, General Medicine, 3. Good health, Geography, Medicine, Research & Experimental, Child, Preschool, Income, GROWTH, AFRICA, medicine.medical_specialty, Biochemistry & Molecular Biology, RJ, Medicina, Immunology, education, MODELS, wa_395, General Biochemistry, Genetics and Molecular Biology, Article, 03 medical and health sciences, Humans, Author Correction, Developing Countries, Poverty, Biology, LBD Double Burden of Malnutrition Collaborators, Demography, Science & Technology, Wasting Syndrome, Public health, MORTALITY, Infant, Næringarskortur, medicine.disease, Obesity, TRENDS, signs and symptoms, Social Class, Risk factors, Sameindalíffræði, ITC-ISI-JOURNAL-ARTICLE, UNDERNUTRITION, Human medicine, Clinical Medicine, 030217 neurology & neurosurgery, Pediatric Obesity, obesity, Offita, Áhættuþættir, Geographic Mapping, Overweight, RA0421, Global health, risk factors, 030212 general & internal medicine, Signs and symptoms, Wasting, Malnutrition, Global Burden of Diseases, Global Nutrition, low- and middle-income countries, 2. Zero hunger, 1. No poverty, Public Health, Global Health, Social Medicine and Epidemiology, A900 Others in Medicine and Dentistry, Childhood wasting, PREVALENCE, Chemistry, Mapping, Female, Lýðheilsa, medicine.symptom, Life Sciences & Biomedicine, GROWTH FAILURE, Nutritional Status, malnutrition, ITC-HYBRID, ws_115, children, Environmental health, medicine, Erfðafræði, wd_200, Malnutrition, Infant, Newborn, Klinisk medicin, Cell Biology, Folkhälsovetenskap, global hälsa, socialmedicin och epidemiologi, 3121 General medicine, internal medicine and other clinical medicine, NA
Abstract

Artículo con numerosos autores, sólo se mencionan el primero, los de la UAM y grupo colectivo, A double burden of malnutrition occurs when individuals, household members or communities experience both undernutrition and overweight. Here, we show geospatial estimates of overweight and wasting prevalence among children under 5 years of age in 105 low- and middle-income countries (LMICs) from 2000 to 2017 and aggregate these to policy-relevant administrative units. Wasting decreased overall across LMICs between 2000 and 2017, from 8.4% (62.3 (55.1–70.8) million) to 6.4% (58.3 (47.6–70.7) million), but is predicted to remain above the World Health Organization’s Global Nutrition Target of, This work was primarily supported by grant OPP1132415 from the Bill & Melinda Gates Foundation awarded to S.I.H.

Published
2020

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