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Sadeghi E, Khodadadiyan A, Hosseini SA, Hosseini SM, Aminorroaya A, Amini M, Javadi S. Novel anthropometric indices for predicting type 2 diabetes mellitus. BMC Public Health 2024; 24:1033. [PMID: 38615018 PMCID: PMC11016207 DOI: 10.1186/s12889-024-18541-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2023] [Accepted: 04/07/2024] [Indexed: 04/15/2024] Open
Abstract
BACKGROUND This study aimed to compare anthropometric indices to predict type 2 diabetes mellitus (T2DM) among first-degree relatives of diabetic patients in the Iranian community. METHODS In this study, information on 3483 first-degree relatives (FDRs) of diabetic patients was extracted from the database of the Endocrinology and Metabolism Research Center of Isfahan University of Medical Sciences. Overall, 2082 FDRs were included in the analyses. A logistic regression model was used to evaluate the association between anthropometric indices and the odds of having diabetes. Furthermore, a receiver operating characteristic (ROC) curve was applied to estimate the optimal cutoff point based on the sensitivity and specificity of each index. In addition, the indices were compared based on the area under the curve (AUC). RESULTS The overall prevalence of diabetes was 15.3%. The optimal cutoff points for anthropometric measures among men were 25.09 for body mass index (BMI) (AUC = 0.573), 0.52 for waist-to-height ratio (WHtR) (AUC = 0.648), 0.91 for waist-to-hip ratio (WHR) (AUC = 0.654), 0.08 for a body shape index (ABSI) (AUC = 0.599), 3.92 for body roundness index (BRI) (AUC = 0.648), 27.27 for body adiposity index (BAI) (AUC = 0.590), and 8 for visceral adiposity index (VAI) (AUC = 0.596). The optimal cutoff points for anthropometric indices were 28.75 for BMI (AUC = 0.610), 0.55 for the WHtR (AUC = 0.685), 0.80 for the WHR (AUC = 0.687), 0.07 for the ABSI (AUC = 0.669), 4.34 for the BRI (AUC = 0.685), 39.95 for the BAI (AUC = 0.583), and 6.15 for the VAI (AUC = 0.658). The WHR, WHTR, and BRI were revealed to have fair AUC values and were relatively greater than the other indices for both men and women. Furthermore, in women, the ABSI and VAI also had fair AUCs. However, BMI and the BAI had the lowest AUC values among the indices in both sexes. CONCLUSION The WHtR, BRI, VAI, and WHR outperformed other anthropometric indices in predicting T2DM in first-degree relatives (FDRs) of diabetic patients. However, further investigations in different populations may need to be implemented to justify their widespread adoption in clinical practice.
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Affiliation(s)
- Erfan Sadeghi
- Department of Biostatistics, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Alireza Khodadadiyan
- Department of Cardiovascular Research Centre, Shiraz University of Medical Sciences, Shiraz, Iran
| | | | - Sayed Mohsen Hosseini
- Department of Biostatistics & Epidemiology, School of Public Health, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Ashraf Aminorroaya
- Isfahan Endocrine and Metabolism Research Center, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Massoud Amini
- Isfahan Endocrine and Metabolism Research Center, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Sara Javadi
- Shiraz University of Medical Sciences, Shiraz, Iran.
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Mirza M, Brown-Hollie JP, Suarez-Balcazar Y, Parra-Medina D, Camillone S, Zeng W, Garcia-Gomez E, Heydarian N, Magaña S. Interventions for Health Promotion and Obesity Prevention for Children and Adolescents with Developmental Disabilities: a Systematic Review. REVIEW JOURNAL OF AUTISM AND DEVELOPMENTAL DISORDERS 2022:1-24. [PMID: 36032995 PMCID: PMC9395920 DOI: 10.1007/s40489-022-00335-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Accepted: 07/14/2022] [Indexed: 11/28/2022]
Abstract
This systematic review evaluated interventions and relevant outcomes for health promotion and obesity prevention among children and adolescents with developmental disabilities (DD). Twenty-one studies including randomized control trials (n= 9) and quasi-experimental studies (n=12) published between 2010 and 2021 met inclusion criteria related to participant characteristics, intervention type, and child obesity-related outcomes. Five types of intervention programs were identified: aerobic and strength training, sport-based physical activity, aquatic exercise, active video gaming, and diet and lifestyle. Whereas analysis of intervention outcomes, efficacy, and study rigor showed mixed results and weak evidence of effective interventions, this review identified gaps in the literature, promising strategies for addressing obesity in children with DD, and implications for practice and future research. Supplementary Information The online version contains supplementary material available at 10.1007/s40489-022-00335-5.
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Affiliation(s)
- Mansha Mirza
- University of Illinois, 1919 W Taylor., IL 60612 Chicago, USA
| | | | | | - Deborah Parra-Medina
- Latino Research Institute, University of Texas at Austin, 210 W. 24th St., Austin, TX 78712 USA
| | - Sarah Camillone
- University of Illinois, 1919 W Taylor., IL 60612 Chicago, USA
| | - Weiwen Zeng
- University of Texas at Austin, 1925 San Jacinto Blvd, Austin, TX 78712 USA
| | | | - Nazanin Heydarian
- University of Texas Rio Grande Valley, 1201 W University Dr, Edinburg, TX 78539 USA
| | - Sandy Magaña
- University of Texas at Austin, 1925 San Jacinto Blvd, Austin, TX 78712 USA
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Trends in BMI Percentile and Body Fat Percentage in Children 12 to 17 Years of Age. CHILDREN (BASEL, SWITZERLAND) 2022; 9:children9050744. [PMID: 35626921 PMCID: PMC9140085 DOI: 10.3390/children9050744] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Revised: 04/28/2022] [Accepted: 05/16/2022] [Indexed: 12/15/2022]
Abstract
This study evaluates the cross-sectional trends in body fat percentage (BF%) and body mass index (BMI) percentile rank, and the relationship between the two in 332 (177 boys, 155 girls) 12- to 17-year-old children. Body mass index (BMI) was calculated using measured height and body mass, and sex-specific BMI for age percentile rank was determined using CDC growth charts. Body fat percentage (BF%) was measured with DEXA. Fat mass index (FMI) and fat-free mass index (FFMI) were calculated by normalizing the fat mass and fat-free mass for height. Compared to boys of the same age, girls had significantly higher BF% and FMI values and lower FFMI values. Compared to boys, at a given BMI percentile rank, females had a higher BF% and FMI, and a lower FFMI. In both boys and girls, there was an exponential increase in adiposity above the 70th percentile rank. BMI percentile rank is not an equivalent indicator of body fatness in boys and girls. Other measures of body composition can further inform the practitioner of a child’s adiposity.
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Mohamad MS, Mahadir Naidu B, Kaltiala R, Virtanen SM, Lehtinen-Jacks S. Thinness, overweight and obesity among 6- to 17-year-old Malaysians: secular trends and sociodemographic determinants from 2006 to 2015. Public Health Nutr 2021; 24:6309-6322. [PMID: 34348828 PMCID: PMC11148614 DOI: 10.1017/s1368980021003190] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
OBJECTIVE To examine secular trends and sociodemographic determinants of thinness, overweight and obesity among Malaysian children and adolescents from 2006 to 2015. DESIGN We used cross-sectional data from the National Health and Morbidity Surveys 2006, 2011 and 2015. Individuals were classified into pre- (6-9 years), early (10-13 years) and mid- (14-17 years) adolescence. BMI status was determined according to the International Obesity Task Force (IOTF) and WHO criteria, using measured height and weight. We analysed trends using log-binomial regression, by sex-age groups, stratified by sociodemographic factors (ethnicity, residential area, household size and household income), and accounting for the complex survey design. Associations between sociodemographic factors and prevalence of thinness and overweight (obesity included) in 2015 were assessed using log-Poisson regression. SETTING Nationwide population-based surveys, Malaysia. PARTICIPANTS Eligible 6-17-year-olds from urban and rural residential areas (n 28 094). RESULTS The prevalence of thinness decreased from 2006 to 2015 (IOTF: boys from 22 % to 18 %, girls from 23 % to 19 %; WHO: boys from 9 % to 7 %, girls from 8 % to 6 %), while the prevalence of overweight increased (IOTF: boys from 20 % to 26 %, girls from 19 % to 24 %; WHO: boys from 25 % to 31 %, girls from 22 % to 27 %). These changes were statistically significant in most sex-age groups. Thinness and overweight co-existed in all sociodemographic subgroups, with variation in the prevalence estimates, but similar secular changes in most subgroups. CONCLUSIONS Malaysia is facing a double burden of malnutrition at population level with a secular increase in overweight and obesity and a gradual decrease in thinness among 6-17-year-olds from varying sociodemographic backgrounds.
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Affiliation(s)
- Maria S Mohamad
- Unit of Health Sciences, Faculty of Social Sciences, Tampere University, Arvo Ylpön Katu 34, Tampere33520, Finland
| | - Balkish Mahadir Naidu
- Research and Methodology Unit, Department of Statistics Malaysia, Putrajaya, Malaysia
| | - Riittakerttu Kaltiala
- Department of Adolescent Psychiatry, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Suvi M Virtanen
- Unit of Health Sciences, Faculty of Social Sciences, Tampere University, Arvo Ylpön Katu 34, Tampere33520, Finland
- Health and Well-Being Promotion Unit, Finnish Institute for Health and Welfare, Helsinki, Finland
- Center for Child Health Research, Tampere University, Tampere University Hospital, Tampere, Finland
- The Science Center of Pirkanmaa Hospital District, Tampere, Finland
| | - Susanna Lehtinen-Jacks
- Unit of Health Sciences, Faculty of Social Sciences, Tampere University, Arvo Ylpön Katu 34, Tampere33520, Finland
- Division of Public Health Sciences, School of Health, Care and Social Welfare, Mälardalen University, Västerås, Sweden
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Physical growth of children and adolescents living at a moderate altitude: proposed percentiles based on age and sex. NUTR HOSP 2021; 38:1238-1247. [PMID: 34530621 DOI: 10.20960/nh.03722] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022] Open
Abstract
INTRODUCTION physical growth patterns and nutritional status of children and adolescents living at moderate altitude are not applicable for clinical assessment of growth for diverse populations around the world. OBJECTIVE a) to compare weight, height and body mass index (BMI) variables with CDC-2012 references; b) to verify if BMI and/or ponderal index (PI) are applicable to children living at moderate altitude; and c) to propose percentiles to assess physical growth by age and sex. METHODS a total of 5,377 students, ranging in age from 6.0 to 17.9 years, were evaluated. The students were from two geographic regions of moderate altitude in Peru (2,320 meters) and Colombia (2,640 meters). Weight and height were measured. BMI and PI were calculated. Weight, height and BMI were compared with CDC-2012 references. RESULTS males showed lower weight and height from age 11 to 17.9 years compared to CDC-2012. Females weighed less than the reference from 9.0 to 17.9 years. Female height was lower from 6.0 to 14.9 years; however, from 15.0 to 17.9 years, values were similar to the reference. As for BMI, there were differences in both sexes (in males, from 15.0 to 17.9 years, and in females, from 12.0 to 17.9 years). Age, weight and height explained BMI: between R2 = 17 and 83 % in males, and in females between R2 = 24 and 85 %. These same variables influenced PI in a lower percentage in both sexes: for males (R2 = 0.01 to 49 %) and for females (R2 = 0.01 to 18 %). CONCLUSIONS children and adolescents living at moderate altitude in Peru and Colombia diverge from the CDC-2012 physical growth patterns. In addition, PI is a new alternative for estimating weight in relation to BMI. The proposed curves for weight, height, and PI by age and sex could have greater implications in the control of child health programs and in clinical and epidemiological practices.
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Liu L, Wang B, Liu X, Ren Y, Zhao Y, Liu D, Zhou J, Liu X, Zhang D, Chen X, Cheng C, Liu F, Zhou Q, Li J, Cao J, Chen J, Huang J, Zhang M, Hu D. Sex-Specific Association of Blood Pressure Categories With All-Cause Mortality: The Rural Chinese Cohort Study. Prev Chronic Dis 2020; 17:E09. [PMID: 31999540 PMCID: PMC6993785 DOI: 10.5888/pcd17.190131] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022] Open
Abstract
Introduction The relationship between blood pressure categories and all-cause mortality has not been fully addressed in cohort studies, especially in the general Chinese population. Our study aimed to assess the sex-specific association of systolic blood pressure (SBP), diastolic blood pressure (DBP), and 2017 United States hypertension guidelines with all-cause mortality in China. Methods We conducted a prospective study of 13,760 rural Chinese adults aged 18 or older (41.1% men). Mean age overall was 49.4, 51.0 for men, and 48.3 for women. We analyzed the blood pressure–mortality relationship by using restricted cubic splines and Cox proportional-hazards regression analysis, estimating hazard ratios (HRs) and 95% confidence intervals (CIs). Results During a mean follow-up of 5.95 years, 710 people died (60.3% men) from any cause. We found a U-shaped SBP–mortality or DBP–mortality relationship for both sexes. Mortality risk was increased for men with SBP 120–139 mm Hg (adjusted HR [aHR], 1.42; 95% CI, 1.10–1.82) or ≥140 mm Hg (aHR, 2.05; 95% CI, 1.54–2.72), and for DBP ≥90 mm Hg (aHR, 1.53; 95% CI, 1.10–2.13) as compared with SBP 100–119 mm Hg or DBP 70–79 mm Hg. Mortality risk also was increased for men with blood pressure status defined according to 2017 US hypertension guidelines as elevated, SBP 120–129 and DBP >80 mm Hg (aHR 1.48; 95% CI,1.11–1.98); stage 1 hypertension, SBP/DBP 130–139/80–89 mm Hg (aHR 1.53; CI, 1.19–1.97); and stage 2 hypertension, SBP/DBP ≥140/90 mm Hg (aHR 1.83; CI, 1.33–2.51). No significant relationship was observed for women. Conclusion Elevated blood pressure and stages 1 and 2 hypertension were positively associated with all-cause mortality for men but not women in rural China.
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Affiliation(s)
- Leilei Liu
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China
| | - Bingyuan Wang
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China.,Department of Preventive Medicine, Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China
| | - Xincan Liu
- Department of Cardiology, The First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou, Henan, People's Republic of China
| | - Yongcheng Ren
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China.,Department of Preventive Medicine, Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China
| | - Yang Zhao
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China.,Department of Preventive Medicine, Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China
| | - Dechen Liu
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China.,Department of Preventive Medicine, Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China
| | - Junmei Zhou
- Department of Preventive Medicine, Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China
| | - Xuejiao Liu
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China
| | - Dongdong Zhang
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China
| | - Xu Chen
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China
| | - Cheng Cheng
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China
| | - Feiyan Liu
- Department of Preventive Medicine, Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China
| | - Qionggui Zhou
- Department of Preventive Medicine, Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China
| | - Jianxin Li
- Study Team of Shenzhen's Sanming Project, The Affiliated Luohu Hospital of Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China.,Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People's Republic of China
| | - Jie Cao
- Study Team of Shenzhen's Sanming Project, The Affiliated Luohu Hospital of Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China.,Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People's Republic of China
| | - Jichun Chen
- Study Team of Shenzhen's Sanming Project, The Affiliated Luohu Hospital of Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China.,Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People's Republic of China
| | - Jianfeng Huang
- Study Team of Shenzhen's Sanming Project, The Affiliated Luohu Hospital of Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China.,Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People's Republic of China
| | - Ming Zhang
- Department of Preventive Medicine, Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China
| | - Dongsheng Hu
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China. E-mail:
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Fogel A, Blissett J. Associations between Otitis media, taste sensitivity and adiposity: Two studies across childhood. Physiol Behav 2019; 208:112570. [PMID: 31175890 DOI: 10.1016/j.physbeh.2019.112570] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2018] [Revised: 05/14/2019] [Accepted: 06/04/2019] [Indexed: 02/07/2023]
Abstract
BACKGROUND Otitis media (OM), or middle ear infections, are one of the most common diseases during early childhood. OM has been linked to changes in food preferences through potential effects on taste signalling, and thereby, to increased weight. OBJECTIVES We investigated the associations between OM, taste sensitivity and adiposity across two studies in early childhood and conducted exploratory post-hoc analyses of sex differences. METHODS Study I assessed 101 children between 2 and 3 years old (59.0% boys). Children were weighed and their height was measured to estimate BMI centiles. Waist measurements were taken to calculate Waist-to-Height Ratio (WHtR). Child's taste sensitivity was assessed using Short Sensory Profile questionnaire. Study II included 95 children between 5 and 9 years old (52.9% boys). Children were weighed and their height was measured to calculate their BMI. Children took part in a Sucrose Detection Threshold (SDT) assessment to establish their taste sensitivity. In both studies parents reported child's history of OM. RESULTS In Study I OM was associated with higher WHtR (p=0.047), though this was observed among girls (p=0.011), but not boys (p=0.53). OM was not linked to BMI centiles or taste sensitivity (all p>0.05). In Study II children with OM history had higher BMI centiles (p=0.010), and this effect was stronger in boys (p=0.037) than girls (p=0.17). Multiple OM exposure increased the odds of overweight by 6.2 times (95%CI [1.46, 26.50]). Boys with multiple OM exposure had higher SDT (p=0.022) compared to boys not exposed to OM, akin to lower taste sensitivity. This was not observed in girls (p=0.67). CONCLUSIONS OM history was associated with higher BMI among 5-9 year old children and this may be linked to taste impairments. This association was not observed in 2-3 year old children. Potential sex differences in these associations require further investigation.
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Affiliation(s)
- Anna Fogel
- Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research (A*STAR), Singapore.
| | - Jackie Blissett
- Department of Psychology, School of Life and Health Sciences, Aston University, Birmingham, UK
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Liu L, Chen X, Liu Y, Sun X, Yin Z, Li H, Zhang M, Wang B, Ren Y, Zhao Y, Liu D, Zhou J, Liu X, Zhang D, Cheng C, Liu F, Zhou Q, Xu Q, Xiong Y, Liu J, You Z, Hong S, Wang C, Hu D. The association between fasting plasma glucose and all-cause and cause-specific mortality by gender: The rural Chinese cohort study. Diabetes Metab Res Rev 2019; 35:e3129. [PMID: 30657630 DOI: 10.1002/dmrr.3129] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/26/2018] [Revised: 01/12/2019] [Accepted: 01/14/2019] [Indexed: 11/10/2022]
Abstract
BACKGROUND To evaluate the association between fasting plasma glucose (FPG) and mortality by gender. METHODS A total of 17 248 eligible participants from a rural Chinese prospective cohort population were included. The same questionnaire interview and anthropometric and laboratory measurements were performed at both baseline (2007-2008) and follow-up (2013-2014). Participants were classified according to baseline FPG and diabetic status by sex. Restricted cubic splines and Cox proportional-hazards regression models, estimating hazard ratio (HR) and 95% confidence interval (CI), were used to assess the FPG-mortality relation. RESULTS During the 6-year follow-up, 618 men and 489 women died. The FPG-mortality relation was J shaped for both sexes. For men, risk of all-cause and noncardiovascular disease (CVD)/noncancer mortality was greater with low fasting glucose (LFG) than with normal fasting glucose (adjusted HR [aHR] 1.60; 95% CI, 1.05-2.43; and aHR 2.16; 95% CI, 1.15-4.05). Men with diabetes mellitus (DM) showed increased risk of all-cause (aHR 2.04; 95% CI, 1.60-2.60), CVD (aHR 1.98; 95% CI, 1.36-2.89), and non-CVD/noncancer mortality (aHR 2.62; 95% CI, 1.76-3.91). Men with impaired fasting glucose (IFG) had borderline risk of CVD mortality (aHR 1.34; 95% CI, 1.00-1.79). Women with LFG had increased risk of non-CVD/noncancer mortality (aHR 2.27; 95% CI, 1.04-4.95), and women with DM had increased risk of all-cause (aHR 1.73; 95% CI, 1.35-2.23), CVD (aHR 1.76; 95% CI, 1.24-2.50), and non-CVD/noncancer mortality (aHR 1.97; 95% CI, 1.27-3.08). CONCLUSIONS LFG is positively associated with all-cause mortality risk in rural Chinese men but not in women.
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Affiliation(s)
- Leilei Liu
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Xu Chen
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Yu Liu
- The Affiliated Luohu Hospital of Shenzhen University Health Sciences Center, Shenzhen, China
| | - Xizhuo Sun
- The Affiliated Luohu Hospital of Shenzhen University Health Sciences Center, Shenzhen, China
| | - Zhaoxia Yin
- The Affiliated Luohu Hospital of Shenzhen University Health Sciences Center, Shenzhen, China
| | - Honghui Li
- The Affiliated Luohu Hospital of Shenzhen University Health Sciences Center, Shenzhen, China
| | - Ming Zhang
- Department of Preventive Medicine, Shenzhen University Health Sciences Center, Shenzhen, China
| | - Bingyuan Wang
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, China
- Department of Preventive Medicine, Shenzhen University Health Sciences Center, Shenzhen, China
| | - Yongcheng Ren
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, China
- Department of Preventive Medicine, Shenzhen University Health Sciences Center, Shenzhen, China
| | - Yang Zhao
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, China
- Department of Preventive Medicine, Shenzhen University Health Sciences Center, Shenzhen, China
| | - Dechen Liu
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, China
- Department of Preventive Medicine, Shenzhen University Health Sciences Center, Shenzhen, China
| | - Junmei Zhou
- Department of Preventive Medicine, Shenzhen University Health Sciences Center, Shenzhen, China
| | - Xuejiao Liu
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Dongdong Zhang
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Cheng Cheng
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Feiyan Liu
- Department of Preventive Medicine, Shenzhen University Health Sciences Center, Shenzhen, China
| | - Qionggui Zhou
- Department of Preventive Medicine, Shenzhen University Health Sciences Center, Shenzhen, China
| | - Qihuan Xu
- Department of Clinical Medicine, Shenzhen University, Shenzhen, China
| | - Yihan Xiong
- Department of Clinical Medicine, Shenzhen University, Shenzhen, China
| | - Jiali Liu
- Department of Clinical Medicine, Shenzhen University, Shenzhen, China
| | - Ziyang You
- Department of Clinical Medicine, Shenzhen University, Shenzhen, China
| | - Shihao Hong
- Department of Clinical Medicine, Shenzhen University, Shenzhen, China
| | - Chongjian Wang
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Dongsheng Hu
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, China
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Liu L, Liu Y, Sun X, Yin Z, Li H, Deng K, Chen X, Cheng C, Luo X, Zhang M, Li L, Zhang L, Wang B, Ren Y, Zhao Y, Liu D, Zhou J, Han C, Liu X, Zhang D, Liu F, Wang C, Hu D. Identification of an obesity index for predicting metabolic syndrome by gender: the rural Chinese cohort study. BMC Endocr Disord 2018; 18:54. [PMID: 30081888 PMCID: PMC6090693 DOI: 10.1186/s12902-018-0281-z] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/18/2017] [Accepted: 07/24/2018] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND To compare the accuracy of different obesity indexes, including waist circumference (WC), weight-to-height ratio (WHtR), body mass index (BMI), and lipid accumulation product (LAP), in predicting metabolic syndrome (MetS) and to estimate the optimal cutoffs of these indexes in a rural Chinese adult population. METHODS This prospective cohort involved 8468 participants who were followed up for 6 years. MetS was defined by the International Diabetes Federation, American Heart Association, and National Heart, Lung, and Blood Institute criteria. The power of the 4 indexes for predicting MetS was estimated by receiver operating characteristic (ROC) curve analysis and optimal cutoffs were determined by the maximum of Youden's index. RESULTS As compared with WHtR, BMI, and LAP, WC had the largest area under the ROC curve (AUC) for predicting MetS after adjusting for age, smoking, drinking, physical activity, and education level. The AUCs (95% CIs) for WC, WHtR, BMI, and LAP for men and women were 0.862 (0.851-0.873) and 0.806 (0.794-0.817), 0.832 (0.820-0.843) and 0.789 (0.777-0.801), 0.824 (0.812-0.835) and 0.790 (0.778-0.802), and 0.798 (0.785-0.810) and 0.771 (0.759-0.784), respectively. The optimal cutoffs of WC for men and women were 83.30 and 76.80 cm. Those of WHtR, BMI, and LAP were approximately 0.51 and 0.50, 23.90 and 23.00 kg/m2, and 19.23 and 20.48 cm.mmol/L, respectively. CONCLUSIONS WC as a preferred index over WHtR, BMI, and LAP for predicting MetS in rural Chinese adults of both genders; the optimal cutoffs for men and women were 83.30 and 76.80 cm.
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Affiliation(s)
- Leilei Liu
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan People’s Republic of China
| | - Yu Liu
- The Affiliated Luohu Hospital of Shenzhen University Health Sciences Center, Shenzhen, Guangdong People’s Republic of China
| | - Xizhuo Sun
- The Affiliated Luohu Hospital of Shenzhen University Health Sciences Center, Shenzhen, Guangdong People’s Republic of China
| | - Zhaoxia Yin
- The Affiliated Luohu Hospital of Shenzhen University Health Sciences Center, Shenzhen, Guangdong People’s Republic of China
| | - Honghui Li
- The Affiliated Luohu Hospital of Shenzhen University Health Sciences Center, Shenzhen, Guangdong People’s Republic of China
| | - Kunpeng Deng
- Yantian Entry-exit Inspection and Quarantine Bureau, Shenzhen, Guangdong People’s Republic of China
| | - Xu Chen
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan People’s Republic of China
| | - Cheng Cheng
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan People’s Republic of China
| | - Xinping Luo
- Department of Preventive Medicine, Shenzhen University Health Sciences Center, Shenzhen, Guangdong People’s Republic of China
| | - Ming Zhang
- Department of Preventive Medicine, Shenzhen University Health Sciences Center, Shenzhen, Guangdong People’s Republic of China
| | - Linlin Li
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan People’s Republic of China
| | - Lu Zhang
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan People’s Republic of China
| | - Bingyuan Wang
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan People’s Republic of China
- Department of Preventive Medicine, Shenzhen University Health Sciences Center, Shenzhen, Guangdong People’s Republic of China
| | - Yongcheng Ren
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan People’s Republic of China
- Department of Preventive Medicine, Shenzhen University Health Sciences Center, Shenzhen, Guangdong People’s Republic of China
| | - Yang Zhao
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan People’s Republic of China
- Department of Preventive Medicine, Shenzhen University Health Sciences Center, Shenzhen, Guangdong People’s Republic of China
| | - Dechen Liu
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan People’s Republic of China
- Department of Preventive Medicine, Shenzhen University Health Sciences Center, Shenzhen, Guangdong People’s Republic of China
| | - Junmei Zhou
- Department of Preventive Medicine, Shenzhen University Health Sciences Center, Shenzhen, Guangdong People’s Republic of China
| | - Chengyi Han
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan People’s Republic of China
| | - Xuejiao Liu
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan People’s Republic of China
| | - Dongdong Zhang
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan People’s Republic of China
| | - Feiyan Liu
- Department of Preventive Medicine, Shenzhen University Health Sciences Center, Shenzhen, Guangdong People’s Republic of China
| | - Chongjian Wang
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan People’s Republic of China
| | - Dongsheng Hu
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan People’s Republic of China
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10
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Chen LW, Tint MT, Fortier MV, Aris IM, Shek LPC, Tan KH, Chan SY, Gluckman PD, Chong YS, Godfrey KM, Rajadurai VS, Yap F, Kramer MS, Lee YS. Which anthropometric measures best reflect neonatal adiposity? Int J Obes (Lond) 2017; 42:501-506. [PMID: 28990589 DOI: 10.1038/ijo.2017.250] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/19/2017] [Revised: 09/05/2017] [Accepted: 09/27/2017] [Indexed: 11/09/2022]
Abstract
BACKGROUND Studying the determinants and the long-term consequences of fetal adipose accretion requires accurate assessment of neonatal body composition. In large epidemiological studies, in-depth body composition measurement methods are usually not feasible for cost and logistical reasons, and there is a need to identify anthropometric measures that adequately reflect neonatal adiposity. METHODS In a multiethnic Asian mother-offspring cohort in Singapore, anthropometric measures (weight, length, abdominal circumference, skinfold thicknesses) were measured using standardized protocols in newborn infants, and anthropometric indices (weight/length, weight/length2 (body mass index, BMI), weight/length3 (ponderal index, PI)) derived. Neonatal total adiposity was measured using air displacement plethysmography (ADP) and abdominal adiposity using magnetic resonance imaging (MRI). Correlations of the anthropometric measures with ADP- and MRI-based adiposity were assessed using Pearson's correlation coefficients (rp), including in subsamples stratified by sex and ethnicity. RESULTS Study neonates (n=251) had a mean (s.d.) age of 10.2 (2.5) days. Correlations between ADP-based fat mass (ADPFM) and anthropometric measures were moderate (rp range: 0.44-0.67), with the strongest being with weight/length, weight, BMI and sum of skinfolds (rp=0.67, 0.66, 0.62, 0.62, respectively, all P<0.01). All anthropometric measures except skinfold thicknesses correlated more strongly with ADP-based fat-free mass than ADPFM, indicating that skinfold measures may have more discriminative power in terms of neonatal total body adiposity. For MRI-based measures, weight and weight/length consistently showed strong positive correlations (rp⩾0.7) with abdominal adipose tissue compartments. These correlations were consistent in boys and girls, across different ethnic groups, and when conventional determinants of neonatal adiposity were adjusted for potential confounding. Abdominal circumference was not strongly associated with ADPFM or abdominal fat mass. CONCLUSIONS Simple anthropometric measures (weight and weight/length) correlated strongly with neonatal adiposity, with some evidence for greater discriminative power for skinfold measures. These simple measures could be of value in large epidemiological studies.
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Affiliation(s)
- L-W Chen
- Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - M-T Tint
- Department of Obstetrics & Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - M V Fortier
- Department of Diagnostic and Interventional Imaging, KK Women's and Children's Hospital, Singapore, Singapore
| | - I M Aris
- Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research, Singapore, Singapore
| | - L P-C Shek
- Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - K H Tan
- Department of Maternal Fetal Medicine, KK Women's and Children's Hospital, Singapore, Singapore.,Duke-National University of Singapore Graduate Medical School, Singapore, Singapore
| | - S-Y Chan
- Department of Obstetrics & Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.,Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research, Singapore, Singapore
| | - P D Gluckman
- Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research, Singapore, Singapore.,Liggins Institute, University of Auckland, Auckland, New Zealand
| | - Y-S Chong
- Department of Obstetrics & Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.,Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research, Singapore, Singapore
| | - K M Godfrey
- MRC Lifecourse Epidemiology Unit & NIHR Southampton Biomedical Research Centre, University of Southampton & University Hospital Southampton NHS Foundation Trust, Southampton, UK
| | - V S Rajadurai
- Department of Neonatology, KK Women's and Children's Hospital, Singapore, Singapore
| | - F Yap
- Duke-National University of Singapore Graduate Medical School, Singapore, Singapore.,Department of Pediatric Endocrinology, KK Women's and Children's Hospital, Singapore, Singapore
| | - M S Kramer
- Department of Obstetrics & Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.,Departments of Pediatrics and of Epidemiology, Biostatistics and Occupational Health, McGill University Faculty of Medicine, Montreal, Quebec, Canada
| | - Y S Lee
- Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.,Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research, Singapore, Singapore.,Khoo Teck Puat- National University Children's Medical Institute, National University Health System, Singapore, Singapore
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11
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Bates K, Gjonça A, Leone T. Double burden or double counting of child malnutrition? The methodological and theoretical implications of stuntingoverweight in low and middle income countries. J Epidemiol Community Health 2017; 71:779-785. [PMID: 28566281 PMCID: PMC5537509 DOI: 10.1136/jech-2017-209008] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2017] [Revised: 04/18/2017] [Accepted: 04/24/2017] [Indexed: 11/13/2022]
Abstract
BACKGROUND There is increasing concern at research and policy levels about the double burden of child malnutrition (DBCM)-with stunting and overweight found across different groups of children. Despite some case studies suggesting that stunting and overweight can occur concurrently in children, here known as 'stuntingoverweight', and major drives to reduce all forms of malnutrition in low and middle income countries (LMICs), stuntingoverweight is continually overlooked. This research evidences the prevalence of stuntingoverweight across LMICs, exploring the theoretical and methodological implications of failing to acknowledge this form of malnutrition. METHODS Prevalence estimates of stuntingoverweight are constructed from 79 LMICs with nationally representative anthropometric survey data. Stunting and overweight estimates are amended to exclude stuntedoverweight children. These estimates are compared with those published in the Joint Child Malnutrition Estimates (JMEs)-evidencing overestimation and double counting of stuntedoverweight children. RESULTS Children can be concurrently stunted and overweight. Stuntedoverweight children are found in all LMICs, from 0.3% to 11.7% of under-fives and are included in both stunting and overweight rates. Analysed together, this leads to double counting of stuntedoverweight children. This artificial inflation of stunting and overweight rates can give a false impression of a DBCM, obscuring the true diversity of malnutrition present. Over 10 million children are stuntedoverweight in the world. CONCLUSIONS Stuntingoverweight is a newly recognised, understudied phenomenon. Affected children are included in both stunting and overweight prevalence estimates, introducing unobserved heterogeneity to both individual-level and population-level research and double counting to population-level research. Overlooking stuntedoverweight children has great implications for methodology, theory, policies, programmes and the health of affected children.
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Affiliation(s)
- Katie Bates
- Department of Social Policy, London School of Economics and Political Science, London, UK
| | - Arjan Gjonça
- Department of Social Policy, London School of Economics and Political Science, London, UK
| | - Tiziana Leone
- Department of Social Policy, London School of Economics and Political Science, London, UK
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12
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Zhang M, Zhang H, Wang C, Ren Y, Wang B, Zhang L, Yang X, Zhao Y, Han C, Pang C, Yin L, Xue Y, Zhao J, Hu D. Development and Validation of a Risk-Score Model for Type 2 Diabetes: A Cohort Study of a Rural Adult Chinese Population. PLoS One 2016; 11:e0152054. [PMID: 27070555 PMCID: PMC4829145 DOI: 10.1371/journal.pone.0152054] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2015] [Accepted: 03/08/2016] [Indexed: 11/24/2022] Open
Abstract
Some global models to predict the risk of diabetes may not be applicable to local populations. We aimed to develop and validate a score to predict type 2 diabetes mellitus (T2DM) in a rural adult Chinese population. Data for a cohort of 12,849 participants were randomly divided into derivation (n = 11,564) and validation (n = 1285) datasets. A questionnaire interview and physical and blood biochemical examinations were performed at baseline (July to August 2007 and July to August 2008) and follow-up (July to August 2013 and July to October 2014). A Cox regression model was used to weigh each variable in the derivation dataset. For each significant variable, a score was calculated by multiplying β by 100 and rounding to the nearest integer. Age, body mass index, triglycerides and fasting plasma glucose (scores 3, 12, 24 and 76, respectively) were predictors of incident T2DM. The model accuracy was assessed by the area under the receiver operating characteristic curve (AUC), with optimal cut-off value 936. With the derivation dataset, sensitivity, specificity and AUC of the model were 66.7%, 74.0% and 0.768 (95% CI 0.760–0.776), respectively. With the validation dataset, the performance of the model was superior to the Chinese (simple), FINDRISC, Oman and IDRS models of T2DM risk but equivalent to the Framingham model, which is widely applicable in a variety of populations. Our model for predicting 6-year risk of T2DM could be used in a rural adult Chinese population.
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Affiliation(s)
- Ming Zhang
- Department of Preventive Medicine, Shenzhen University School of Medicine, Shenzhen, Guangdong, People’s Republic of China
| | - Hongyan Zhang
- Department of Preventive Medicine, Shenzhen University School of Medicine, Shenzhen, Guangdong, People’s Republic of China
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People’s Republic of China
| | - Chongjian Wang
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People’s Republic of China
| | - Yongcheng Ren
- Department of Preventive Medicine, Shenzhen University School of Medicine, Shenzhen, Guangdong, People’s Republic of China
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People’s Republic of China
| | - Bingyuan Wang
- Department of Preventive Medicine, Shenzhen University School of Medicine, Shenzhen, Guangdong, People’s Republic of China
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People’s Republic of China
| | - Lu Zhang
- Department of Preventive Medicine, Shenzhen University School of Medicine, Shenzhen, Guangdong, People’s Republic of China
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People’s Republic of China
| | - Xiangyu Yang
- Department of Preventive Medicine, Shenzhen University School of Medicine, Shenzhen, Guangdong, People’s Republic of China
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People’s Republic of China
| | - Yang Zhao
- Department of Preventive Medicine, Shenzhen University School of Medicine, Shenzhen, Guangdong, People’s Republic of China
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People’s Republic of China
| | - Chengyi Han
- Department of Preventive Medicine, Shenzhen University School of Medicine, Shenzhen, Guangdong, People’s Republic of China
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People’s Republic of China
| | - Chao Pang
- Department of Prevention and Health Care, Military Hospital of Henan Province, Zhengzhou, Henan, People’s Republic of China
| | - Lei Yin
- Department of Prevention and Health Care, Military Hospital of Henan Province, Zhengzhou, Henan, People’s Republic of China
| | - Yuan Xue
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People’s Republic of China
| | - Jingzhi Zhao
- Department of Prevention and Health Care, Military Hospital of Henan Province, Zhengzhou, Henan, People’s Republic of China
- * E-mail: (DH); (JZ)
| | - Dongsheng Hu
- Department of Preventive Medicine, Shenzhen University School of Medicine, Shenzhen, Guangdong, People’s Republic of China
- * E-mail: (DH); (JZ)
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13
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Abstract
The high prevalence of obesity is a major public health issue and contributes to the 'double burden' of disease in developing countries. Early exposure to poor nutrition may cause metabolic adaptations that, when accompanied by exposure to 'affluent' nutrition, may increase the risk for obesity and other metabolic disorders. The aim of this study was to determine differences in energy metabolism and nutritional status between normal-height and growth-retarded North Korean children living in South Korea. A total of 29 children were recruited and underwent measurements of resting energy expenditure (REE), respiratory quotient (RQ), anthropometrics and dietary intake. There was no difference in REE or any assessment of obesity between the growth-retarded and normal-height children. Children who were classified as growth retarded (HAZ<-1.0) or stunted (HAZ<-2.0) had a significantly higher RQ (β=0.036 or 0.060, respectively, P=0.018 or 0.016), independent of sex, age, fat-free mass, fat mass and food quotient, compared with children with normal height. The results from this study, the first from an Asian population, add to the growing body of literature suggesting that undernutrition early in life results in adaptations in energy metabolism that favor fat deposition, increasing the risk of stunted children becoming overweight or obese later in life. Continued research on this topic is warranted, given the continued rise in the prevalence of the double burden in transitional countries.
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14
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Román EM, Bejarano IF, Alfaro EL, Abdo G, Dipierri JE. Geographical altitude, size, mass and body surface area in children (1–4 years) in the Province of Jujuy (Argentina). Ann Hum Biol 2014; 42:431-8. [DOI: 10.3109/03014460.2014.959998] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
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15
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Bryant ES, James RS, Birch SL, Duncan M. Prediction of habitual physical activity level and weight status from fundamental movement skill level. J Sports Sci 2014; 32:1775-82. [PMID: 24839900 DOI: 10.1080/02640414.2014.918644] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
Abstract
Fundamental movement skills (FMS) have been assessed in children in order to investigate the issues of the low proportion of children who meet physical activity (PA) guidelines and rising levels of obesity. The aim of this research was to identify whether previous or current FMS level is a better predictor of PA levels and weight status in children. In January 2012 (year 1), 281 children were recruited from one primary school in the West Midlands, UK. Children performed eight FMS three times, which were videoed and assessed using a subjective checklist. Sprint speed and jump height were measured objectively. Height and mass were measured to calculate the body mass index to determine the weight status. Skinfold calliper readings were used to calculate body fat percentage. One year later, in January 2013, all these tests were repeated on the same children, with the additional collection of PA data via the use of pedometers. Following multiple linear regression, it was identified that prior mastery in FMS was a better predictor of current PA, whereas current FMS was a better predictor of current weight status. Overall, FMS mastery is needed in childhood to be able to participate in PA and maintain a healthy weight status.
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