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51. Impact of the growing healthy mhealth program on maternal feeding practices, infant food preferences, and satiety responsiveness: Quasi-experimental study

Author

Russell, CG, Denney-Wilson, E, Laws, RA, Abbott, G, Zheng, M, Lymer, SJ, Taki, S, Litterbach, EKV, Ong, KL, Campbell, KJ, Russell, CG, Denney-Wilson, E, Laws, RA, Abbott, G, Zheng, M, Lymer, SJ, Taki, S, Litterbach, EKV, Ong, KL, and Campbell, KJ

Abstract

© Catherine Georgina Russell, Elizabeth Denney-Wilson, Rachel A Laws, Gavin Abbott, Miaobing Zheng, Sharyn J Lymer, Sarah Taki, Eloise-Kate V Litterbach, Kok-Leong Ong, Karen J Campbell. Background: Infancy is an important life stage for obesity prevention efforts. Parents’ infant feeding practices influence the development of infants’ food preferences and eating behaviors and subsequently diet and weight. Mobile health (mHealth) may provide a feasible medium through which to deliver programs to promote healthy infant feeding as it allows low cost and easy access to tailored content. Objective: The objective of this study was to describe the effects of an mHealth intervention on parental feeding practices, infant food preferences, and infant satiety responsiveness. Methods: A quasi-experimental study was conducted with an mHealth intervention group (Growing Healthy) and a nonrandomized comparison group (“Baby's First Food"). The intervention group received access to a free app with age-appropriate push notifications, a website, and an online forum that provided them with evidence-based advice on infant feeding for healthy growth from birth until 9 months of age. Behavior change techniques were selected using the Behaviour Change Wheel framework. Participants in both groups completed three Web-based surveys, first when their infants were less than 3 months old (baseline, T1), then at 6 months (time 2, T2), and 9 months of age (time 3, T3). Surveys included questions on infant feeding practices and beliefs (Infant Feeding Questionnaire, IFQ), satiety responsiveness (Baby Eating Behaviour Questionnaire), and infant’s food exposure and liking. Multivariate linear regression models, estimated using maximum likelihood with bootstrapped standard errors, were fitted to compare continuous outcomes between the intervention groups, with adjustment for relevant covariates. Multivariate logistic regression adjusting for the same covariates was performed for categorical outcomes.

Published
2018

52. The role of fibroblast growth factor 21 in atherosclerosis

Author

Kokkinos, J, Tang, S, Rye, KA, Ong, KL, Kokkinos, J, Tang, S, Rye, KA, and Ong, KL

Abstract

The metabolic properties of the endocrine fibroblast growth factor 21 (FGF21) have been extensively studied in the past decade. Previous studies have demonstrated the lipid-lowering, anti-inflammatory and anti-oxidant properties of FGF21. FGF21 is mainly secreted in the liver and adipose tissue in response to a range of physiological and pathological stimuli. In animal and in vitro studies, FGF21 has been shown to improve lipid profiles and inhibit key processes in the pathogenesis of atherosclerosis. It exerts its effects on the cardiovascular system via adiponectin dependent and independent mechanisms. However, the signalling pathways by which FGF21 exerts its effects on endothelial cells remains unknown and needs to be further investigated. The elevation of circulating FGF21 levels in cardiovascular disease has also raised questions as to whether FGF21 can be used as a biomarker to predict subclinical atherosclerosis and cardiovascular events. Recent findings from population studies must be validated in independent cohorts before FGF21 can be used as a biomarker in the clinical setting. The anti-atherosclerotic effects of FGF21 have been investigated in two recent clinical trials, where treatment with an FGF21 analog significantly improved the cardiometabolic profile in obese patients with type 2 diabetes. This review will evaluate recent advances that suggest there may be a role for FGF21 in atherosclerosis.

Published
2017

53. Baseline circulating FGF21 concentrations and increase after fenofibrate treatment predict more rapid glycemic progression in type 2 diabetes: Results from the FIELD study

Author

Ong, KL, O'Connell, R, Januszewski, AS, Jenkins, AJ, Xu, A, Sullivan, DR, Barter, PJ, Scott, RS, Taskinen, MR, Waldman, B, Colman, PG, Best, JD, Simes, JR, Rye, KA, Keech, AC, Ong, KL, O'Connell, R, Januszewski, AS, Jenkins, AJ, Xu, A, Sullivan, DR, Barter, PJ, Scott, RS, Taskinen, MR, Waldman, B, Colman, PG, Best, JD, Simes, JR, Rye, KA, and Keech, AC

Abstract

BACKGROUND: It is not known whether circulating fibroblast growth factor 21 (FGF21) concentrations are associated with glycemic progression in patients with established type 2 diabetes. This study reports this relationship in type 2 diabetes patients participating in the Fenofibrate Intervention and Event Lowering in Diabetes (FIELD) trial. METHODS: Plasma FGF21 was quantified in 9697 study participants. Among patients with lifestyle-only glucose control measures at baseline, glycemic progression was defined as the initiation of oral hypoglycemic agents or insulin therapy. We assessed the relationship of FGF21 concentrations with glycohemoglobin (Hb A1c), the homeostasis model assessment of ß-cell function (HOMA-B) and insulin resistance (HOMA-IR), and glycemic progression. RESULTS: Among 2584 patients with lifestyle-only glycemic therapy at baseline, plasma FGF21 concentrations were positively associated with HOMA-IR (5.1% increase per 100% increase in FGF21 concentrations). Patients with higher baseline plasma FGF21 concentrations had higher risk of glycemic progression over a 5-year period (P=0.02), but the association was not significant after further adjusting for alanine aminotransferase (ALT) enzyme activity. During the fenofibrate active run-in phase, higher tertiles of fenofibrate-induced increase in FGF21 concentrations were associated with higher risk of glycemic progression (adjusted hazards ratio =1.09 and 1.18 for tertiles 2 and 3, respectively, P for trend = 0.01), even after adjusting for ALT enzyme activity. This association was statistically significant in the fenofibrate group only (P = 0.01). CONCLUSIONS: Higher baseline and fenofibrate-induced increase in FGF21 concentrations predict more rapid glycemic progression in type 2 diabetes patients. This association may be partly explained by hepatic function.

Published
2017

54. A comparison of recruitment methods for an mHealth intervention targeting mothers: Lessons from the growing healthy program

Author

Laws, RA, Litterbach, EKV, Denney-Wilson, EA, Russell, CG, Taki, S, Ong, KL, Elliott, RM, Lymer, SJ, Campbell, KJ, Laws, RA, Litterbach, EKV, Denney-Wilson, EA, Russell, CG, Taki, S, Ong, KL, Elliott, RM, Lymer, SJ, and Campbell, KJ

Abstract

Background: Mobile health (mHealth) programs hold great promise for increasing the reach of public health interventions. However, mHealth is a relatively new field of research, presenting unique challenges for researchers. A key challenge is understanding the relative effectiveness and cost of various methods of recruitment to mHealth programs. Objective: The objectives of this study were to (1) compare the effectiveness of various methods of recruitment to an mHealth intervention targeting healthy infant feeding practices, and (2) explore factors influencing practitioner referral to the intervention. Methods: The Growing healthy study used a quasi-experimental design with an mHealth intervention group and a concurrent nonrandomized comparison group. Eligibility criteria included: expectant parents (>30 weeks of gestation) or parents with an infant <3 months old, ability to read and understand English, own a mobile phone, ≥18 years old, and living in Australia. Recruitment to the mHealth program consisted of: (1) practitioner-led recruitment through Maternal and Child Health nurses, midwives, and nurses in general practice; (2) face-to-face recruitment by researchers; and (3) online recruitment. Participants' baseline surveys provided information regarding how participants heard about the study, and their sociodemographic details. Costs per participant recruited were calculated by taking into account direct advertising costs and researcher time/travel costs. Practitioner feedback relating to the recruitment process was obtained through a follow-up survey and qualitative interviews. Results: A total of 300 participants were recruited to the mHealth intervention. The cost per participant recruited was lowest for online recruitment (AUD $14) and highest for practice nurse recruitment (AUD $586). Just over half of the intervention group (50.3%, 151/300) were recruited online over a 22-week period compared to practitioner recruitment (29.3%, 88/300 over 46 weeks) and fac

Published
2016

56. Relationship of pericardial fat with lipoprotein distribution: The Multi-Ethnic study of atherosclerosis

Author

Ong, KL, Ding, J, McClelland, RL, Cheung, BMY, Criqui, MH, Barter, PJ, Rye, KA, Allison, MA, Ong, KL, Ding, J, McClelland, RL, Cheung, BMY, Criqui, MH, Barter, PJ, Rye, KA, and Allison, MA

Abstract

Objective: Pericardial fat and lipoprotein abnormalities contribute to increased risk of cardiovascular disease (CVD). We investigated the relationship between pericardial fat volume and lipoprotein distribution, and whether the association of pericardial fat volume with subclinical atherosclerosis and incident CVD events differs according to lipoprotein distribution. Methods: We analyzed data from 5407 participants from the Multi-Ethnic Study of Atherosclerosis who had measurements of pericardial fat volume, lipoprotein distribution, carotid intima-media thickness (IMT), and coronary artery calcium (CAC). All participants were free of clinically apparent CVD at baseline. Incident CVD was defined as any adjudicated CVD event. Results: After adjusting for demographic factors, traditional risk factors, and biomarkers of inflammation and hemostasis, a larger pericardial fat volume was associated with higher large VLDL particle (VLDL-P) concentration and small HDL particle (HDL-P) concentration, and smaller HDL-P size (regression coefficients=0.585nmol/L, 0.366μmol/L, and-0.025nm per SD increase in pericardial fat volume respectively, all P<0.05). The association of pericardial fat volume with large VLDL-P concentration and HDL-P size, but not small HDL-P concentration, remained significant after further adjusting for each other as well as LDL cholesterol, HDL cholesterol, and triglycerides. The relationship of pericardial fat volume with incident CVD events, carotid IMT, and prevalence and severity of CAC did not differ by quartiles of large VLDL-P concentration, small HDL-P concentration, or HDL-P size (P for interaction>0.05). Conclusion: Pericardial fat is associated with atherogenic lipoprotein abnormalities. However, its relationship with subclinical atherosclerosis and incident CVD events does not differ according to lipoprotein distribution.

Published
2015

57. Relationship of fibroblast growth factor 21 with baseline and new on-study microvascular disease in the Fenofibrate Intervention and Event Lowering in Diabetes study

Author

Ong, KL, Januszewski, AS, O’Connell, R, Buizen, L, Jenkins, AJ, Xu, A, Sullivan, DR, Barter, PJ, Scott, RS, Taskinen, MR, Rye, KA, Keech, AC, Ong, KL, Januszewski, AS, O’Connell, R, Buizen, L, Jenkins, AJ, Xu, A, Sullivan, DR, Barter, PJ, Scott, RS, Taskinen, MR, Rye, KA, and Keech, AC

Abstract

Aims/hypothesis: Baseline circulating fibroblast growth factor 21 (FGF21) levels can predict total cardiovascular disease events in the Fenofibrate Intervention and Event Lowering in Diabetes (FIELD) study. This paper describes the relationship of baseline FGF21 levels and new on-study microvascular disease in patients with type 2 diabetes from the FIELD study. Methods: Baseline FGF21 levels were measured in plasma by enzyme-linked immunosorbent assay in 9697 study participants. Total microvascular disease was defined as the presence of any nephropathy, retinopathy, neuropathy and/or microvascular amputation. The relationship between FGF21 levels and microvascular disease was assessed by multivariable logistic regression. Results: Higher baseline FGF21 levels were found in patients with baseline total microvascular disease (p < 0.001). The association remained significant after adjusting for potential confounding factors (OR [95% CI] 1.13 [1.08, 1.19] per SD increase in loge-transformed FGF21 levels, p < 0.001). Of 6465 patients without baseline total microvascular disease, 1517 developed new on-study total microvascular disease over 5 years of follow-up. Higher baseline FGF21 levels were associated with a higher risk of new on-study total microvascular disease after adjusting for potential confounding factors (OR [95% CI] 1.09 [1.02, 1.16] per SD increase in loge-transformed FGF21 levels, p = 0.01). Addition of FGF21 levels in a model of new on-study total microvascular disease with established risk factors significantly, but modestly, increased the integrated discrimination improvement and the net reclassification improvement (both p < 0.01). Conclusions/interpretation: Higher baseline FGF21 levels are seen in patients with type 2 diabetes and established microvascular disease, and predict the future development of new microvascular disease.

Published
2015

58. The impact of LDLR function on fibroblast growth factor 21 levels

Author

Besseling, J, Ong, KL, Huijgen, R, Rye, KA, Hovingh, GK, Hutten, BA, Lambert, G, Besseling, J, Ong, KL, Huijgen, R, Rye, KA, Hovingh, GK, Hutten, BA, and Lambert, G

Abstract

Context: Fibroblast growth factor 21 (FGF21) has been described to have beneficial effects on glucose and lipid metabolism, and FGF21 analogs are currently evaluated in phase 1 trials. However, the complete spectrum of effects and regulators of FGF21 is yet partly elucidated. Recent studies have shown that FGF21 plays a role in transmembrane cholesterol transport. Objective: We set out to examine the association between FGF21 and LDLR mediated transmembrane cholesterol transport, by comparing FGF21 levels in patients with genetically impaired LDLR function and unaffected relatives. Secondly, we explored whether the severity of the LDLR mutation was associated with FGF21 levels. Methods: We performed a cross-sectional study in carriers of an LDLR mutation and their unaffected relatives. Subjects were eligible if they participated in the Dutch national screening program for familial hypercholesterolemia (FH), were 18-55 years old, and were carrier of a pathogenic LDLR mutation with an untreated LDL-C level below the 75th or above the 90th percentile of the general population, or did not carry an FH mutation. The outcome measure was the level of FGF21, which was assessed using ELISA. Results: We included 224 carriers of an LDLR mutation and 148 unaffected relatives. FGF21 levels were lower in LDLR mutation carriers compared to unaffected relatives (median [interquartile range]: 96.92 [60.80-174.05] versus 136.98 [77.34-219.47] pg/mL, respectively; p=0.08), but after adjusting for potential confounders, there was no association between LDLR mutations and FGF21 levels (p=0.70). Neither, did we find a relationship between the severity of LDLR mutations and FGF21 levels (p=0.51, after adjustment for potential confounders). Conclusions: We showed that levels of FGF21 are not different in patients with and without LDLR mutations, which suggests that decreased LDLR expression does not have a negative effect on FGF21 levels. Given the potential beneficial effects of FGF21 anal

Published
2015

59. Circulating microRNAs as biomarkers of alzheimer's disease: A systematic review

Author

Wu, HZY, Ong, KL, Seeher, K, Armstrong, NJ, Thalamuthu, A, Brodaty, H, Sachdev, P, Mather, K, Wu, HZY, Ong, KL, Seeher, K, Armstrong, NJ, Thalamuthu, A, Brodaty, H, Sachdev, P, and Mather, K

Abstract

Background: In recent years, microRNAs (miRNA), a class of non-coding RNA known to regulate protein expression posttranscriptionally, have been recognized as novel biomarkers of diseases. Objective: In this systematic review, we identify miRNAs that are differentially expressed in Alzheimer's disease (AD) and/or mild cognitive impairment (MCI) and evaluate their accuracy as potential blood biomarkers. Methods: Eligible studies of miRNAs in peripheral blood distinguishing patients with AD or MCI from cognitively normal controls were identified through standardized search strategies in Medline, PubMed, and Embase. MiRNAs that were differentially expressed were identified and where available their sensitivity and specificity for AD or MCI extracted from the retrieved studies. Results: Eighteen studies investigated the diagnostic value of miRNAs as peripheral biomarkers of AD/MCI. Twenty miRNAs were significantly upregulated and 32 miRNAs downregulated in AD compared to controls in ten AD studies. Nine miRNAs were consistently dysregulated in more than one study. Of the 8 MCI studies, only one miRNA, miR-132, was consistently upregulated in three independent studies. Of the studies that reported diagnostic accuracy data, the majority of miRNA panels and individual miRNAs had a sensitivity and specificity greater than 0.75. Conclusion: Individual studies suggest that miRNAs can differentiate patients with AD/MCI from cognitively normal controls with modest accuracy. However, the literature is constrained by methodological differences between studies, with few studies assessing the same miRNAs. To become potential biomarkers for AD, further studies with standardized study designs for replication and validation are required. Results from this review may help researchers select candidate miRNAs for further investigation.

Published
2015

60. The relationship of fibroblast growth factor 21 with cardiovascular outcome events in the Fenofibrate Intervention and Event Lowering in Diabetes study

Author

Ong, KL, Januszewski, AS, O’Connell, R, Jenkins, AJ, Xu, A, Sullivan, DR, Barter, PJ, Hung, WT, Scott, RS, Taskinen, MR, Keech, AC, Rye, KA, Ong, KL, Januszewski, AS, O’Connell, R, Jenkins, AJ, Xu, A, Sullivan, DR, Barter, PJ, Hung, WT, Scott, RS, Taskinen, MR, Keech, AC, and Rye, KA

Abstract

© 2014, Springer-Verlag Berlin Heidelberg. Aims/hypothesis: Circulating fibroblast growth factor 21 (FGF21) levels are often elevated in obesity, dyslipidaemia, insulin resistance and type 2 diabetes. This study investigated the relationship of plasma FGF21 levels with cardiovascular events in patients with type 2 diabetes.Methods: Plasma FGF21 levels were measured by ELISA at baseline in 9,697 individuals with type 2 diabetes participating in the Fenofibrate Intervention and Event Lowering in Diabetes (FIELD) study. We assessed the association of FGF21 levels with the incidence of different cardiovascular outcomes over 5 years. The primary outcome was total cardiovascular disease (CVD) events and the secondary outcomes were the four individual components: coronary heart disease events, total stroke, CVD mortality and coronary and carotid revascularisation. The tertiary outcome was hospitalisation for angina pectoris.Results: Higher baseline FGF21 levels were associated with higher risks of all cardiovascular outcome events after adjusting for the study treatment allocation (all p < 0.01). The associations remained significant for total CVD events and for coronary and carotid revascularisation after further adjusting for confounding factors, with the HR (95% CI) being 1.28 (1.10, 1.50) and 1.26 (1.01, 1.56), respectively, for the highest tertile compared with the lowest tertile (overall effect p = 0.002 and 0.007, respectively). The addition of FGF21 levels to a model including established CVD risk factors predicting total CVD events led to a non-significant increase in the C-statistic but there was a significant improvement in integrated discrimination and net reclassification.Conclusions/interpretation: Higher baseline plasma FGF21 levels were associated with higher risk of cardiovascular events in patients with type 2 diabetes.

Published
2015

61. Relationship of pericardial fat with biomarkers of inflammation and hemostasis, and cardiovascular disease: The Multi-Ethnic Study of Atherosclerosis

Author

Ong, KL, Ding, J, McClelland, RL, Cheung, BMY, Criqui, MH, Barter, PJ, Rye, KA, Allison, MA, Ong, KL, Ding, J, McClelland, RL, Cheung, BMY, Criqui, MH, Barter, PJ, Rye, KA, and Allison, MA

Abstract

Objective: Pericardial fat may increase the risk of cardiovascular disease (CVD) by increasing circulating levels of inflammation and hemostasis biomarkers. We investigated the associations of pericardial fat with inflammation and hemostasis biomarkers, as well as incident CVD events, and whether there are any ethnic differences in these associations. Methods: We analyzed results from 6415 participants from the Multi-Ethnic Study of Atherosclerosis who had measurements of pericardial fat volume and circulating levels of C-reactive protein (CRP), fibrinogen, interleukin (IL)-6, factor VIII, D-dimer and plasmin-antiplasmin complex (PAP), and had a mean follow-up period of 9.5 years. Incident CVD event was defined as any adjudicated CVD event. Results: After adjusting for confounding factors, pericardial fat volume was positively associated with natural log (ln) of IL-6 levels, but inversely associated with ln D-dimer and ln PAP levels (β=0.067,-0.032, and-0.105 respectively, all P<0.05). Although a larger pericardial fat volume was associated with a higher risk of incident CVD, the association was attenuated to borderline significance after adjusting for traditional cardiovascular risk factors (. P=0.050). There was a borderline significant ethnicity interaction (. P=0.080), whereby the association between pericardial fat volume and incident CVD was significant in Hispanic Americans, even after further adjusting for biomarkers of inflammation and hemostasis (hazard ratio=1.31 per SD increase, 95% confidence interval 1.09-1.57, P=0.004). Conclusion: Pericardial fat was associated with several inflammation and hemostasis biomarkers. The association of pericardial fat with incident CVD events was independent of these biomarkers only among Hispanic Americans.

Published
2015

62. Preventing obesity in infants: The Growing healthy feasibility trial protocol

Author

Denney-Wilson, E, Laws, R, Russell, CG, Ong, KL, Taki, S, Elliot, R, Azadi, L, Lymer, S, Taylor, R, Lynch, J, Crawford, D, Ball, K, Askew, D, Litterbach, EK, Campbell, KJ, Denney-Wilson, E, Laws, R, Russell, CG, Ong, KL, Taki, S, Elliot, R, Azadi, L, Lymer, S, Taylor, R, Lynch, J, Crawford, D, Ball, K, Askew, D, Litterbach, EK, and Campbell, KJ

Abstract

© 2015 BMJ Publishing Group. All rights reserved. Introduction: Early childhood is an important period for establishing behaviours that will affect weight gain and health across the life course. Early feeding choices, including breast and/or formula, timing of introduction of solids, physical activity and electronic media use among infants and young children are considered likely determinants of childhood obesity. Parents play a primary role in shaping these behaviours through parental modelling, feeding styles, and the food and physical activity environments provided. Children from low socioeconomic backgrounds have higher rates of obesity, making early intervention particularly important. However, such families are often more difficult to reach and may be less likely to participate in traditional programs that support healthy behaviours. Parents across all socio-demographic groups frequently access primary health care (PHC) services, including nurses in community health services and general medical practices, providing unparalleled opportunity for engagement to influence family behaviours. One emerging and promising area that might maximise engagement at a low cost is the provision of support for healthy parenting through electronic media such as the Internet or smart phones. The Growing healthy study explores the feasibility of delivering such support via primary health care services. Methods: This paper describes the Growing healthy study, a non-randomised quasi experimental study examining the feasibility of an intervention delivered via a smartphone app (or website) for parents living in socioeconomically disadvantaged areas, for promoting infant feeding and parenting behaviours that promote healthy rather than excessive weight gain. Participants will be recruited via their primary health care practitioner and followed until their infant is 9 months old. Data will be collected via web-based questionnaires and the data collected inherently by the app itself. Et

Published
2015

63. Adiponectin gene variants and the risk of coronary heart disease: A 16-year longitudinal study

Author

Cheung, CYY, Hui, EYL, Cheung, BMY, Woo, YC, Xu, A, Fong, CHY, Ong, KL, Yeung, CY, Janus, ED, Tse, HF, Sham, PC, Lam, KSL, Cheung, CYY, Hui, EYL, Cheung, BMY, Woo, YC, Xu, A, Fong, CHY, Ong, KL, Yeung, CY, Janus, ED, Tse, HF, Sham, PC, and Lam, KSL

Abstract

Objective: Circulating adiponectin levels have been shown to be associated with a risk of coronary heart disease (CHD). However, its primary role in protecting against the development of CHD remains controversial due to conflicting observations in prospective studies. To gain further insight into the primary role of adiponectin, our major objective was to investigate the relationship between single nucleotide polymorphisms (SNPs) of the adiponectin gene (ADIPOQ) and incident CHD in a population-based cohort with no CHD at baseline. Design and methods: We conducted a 16-year longitudinal study in 2196 subjects from the Hong Kong Cardiovascular Risk Factor Prevalence Study (CRISPS). During 33 862 person-years of follow-up, 184 subjects developed CHD (cumulative incidence rate=5.4 per 1000 person-years). Nine ADIPOQ SNPs with potential functional relevance or shown to be associated with adiponectin levels and/or CHD were genotyped. Results: Among the nine ADIPOQ SNPs, +276G>T (rs1501299) was independently associated with incident CHD in men but not in women, even after adjustments for traditional cardiovascular risk factors (Padjusted=5.5×10-3 to 0.023; hazard ratio=1.39-1.54). Furthermore, there was a significant association of the T allele of +276G>T with a lower adiponectin level (P=0.027; β (95% CI)=-0.05 (-0.10,-0.01). Conclusions: This study demonstrated that +276G>T may be an independent predictor of CHD development. Our findings suggest that low adiponectin levels, as may be influenced by+276G>T, confer a higher risk of CHD, in keeping with a role of hypoadiponectinaemia in the development of CHD in the general population. © 2014 European Society of Endocrinology Printed in Great Britain.

Published
2014

64. Cardiovascular drugs that increase the risk of new-onset diabetes

Author

Ong, KL, Barter, PJ, Waters, DD, Ong, KL, Barter, PJ, and Waters, DD

Abstract

The prevalence of type 2 diabetes is increasing worldwide, and diabetes is a strong adverse prognostic factor among patients with cardiovascular (CV) disease. Four classes of drugs that are commonly used for CV risk reduction, statins, niacin, thiazide diuretics, and ß-blockers, have been shown to increase the risk of new-onset diabetes (NOD) by 9% to 43% in meta-analyses or large-scale clinical trials. Clinical predictors for drug-related NOD appear to be similar to the predictors that have been described for NOD unrelated to drugs: fasting blood glucose >100 mg/dL and features of the metabolic syndrome such as body mass index >30 kg/m2, serum triglycerides >150 mg/dL, and elevated blood pressure, among others. The mechanisms whereby these drugs increase the risk of NOD are incompletely understood, although different hypotheses have been suggested. Lifestyle intervention consisting of diet and exercise has been shown in multiple studies to reduce the risk of NOD by approximately 50%, with persistent benefit during long-term follow-up. In patients at high risk for NOD, niacin should be avoided, and for hypertension, an angiotensin-converting enzyme inhibitor or even a ß1- selective blocker might be a better choice than a standard ß-blocker. For thiazide diuretics and particularly statins, benefit in terms of CV event reduction outweighs the risk of NOD. © 2014 Mosby, Inc.

Published
2014

65. Effect of change in body weight on incident diabetes mellitus in patients with stable coronary artery disease treated with atorvastatin (from the Treating to New Targets Study)

Author

Ong, KL, Waters, DD, Messig, M, Demicco, DA, Rye, KA, Barter, PJ, Ong, KL, Waters, DD, Messig, M, Demicco, DA, Rye, KA, and Barter, PJ

Abstract

Features of the metabolic syndrome are independent risk factors for new-onset diabetes mellitus (NODM) related to statin therapy. Obesity is the predominant underlying risk factor for the metabolic syndrome and diabetes mellitus. This study investigated whether change in body weight may predict NODM in statin-treated patients. A total of 7,595 patients without prevalent diabetes mellitus at baseline from the Treating to New Targets (TNT) study were included in this analysis. They were randomized to atorvastatin 10 or 80 mg/day and monitored for a median of 4.9 years. NODM developed in 659 patients (8.1% in the 10-mg group and 9.2% in the 80-mg group). There was a significant increase in body weight (0.9 kg, p <0.01 in both men and women) over 1 year after randomization. The increase in body weight was greater in patients with NODM than those without NODM (1.6 vs 0.9 kg, p <0.001). The association of change in body weight with NODM risk remained significant after adjusting for confounding factors (hazard ratios 1.33, 1.42, and 1.88 for quartiles 2, 3, and 4 compared with quartile 1, respectively). Similar results were obtained in patients with normal fasting glucose level. In conclusion, 1-year change in body weight is predictive of NODM in patients who underwent statin therapy from the TNT trial. Our study highlights the importance of weight control as a lifestyle measure to prevent statin-related NODM. © 2014 Elsevier Inc. All rights reserved.

Published
2014

66. The relationship between insulin resistance and vascular calcification in coronary arteries, and the thoracic and abdominal aorta: The multi-ethnic study of atherosclerosis

Author

Ong, KL, McClelland, RL, Rye, KA, Cheung, BMY, Post, WS, Vaidya, D, Criqui, MH, Cushman, M, Barter, PJ, Allison, MA, Ong, KL, McClelland, RL, Rye, KA, Cheung, BMY, Post, WS, Vaidya, D, Criqui, MH, Cushman, M, Barter, PJ, and Allison, MA

Abstract

Objective: Insulin resistance may be related to vascular calcification as both are associated with abdominal obesity. We investigated the association of insulin resistance with abdominal aortic calcium (AAC), coronary artery calcium (CAC) and thoracic aortic calcium (TAC), and whether it differs according to different levels of subcutaneous fat area (SFA) and visceral fat area (VFA) in a cross-sectional study design. Methods: We investigated 1632 participants without diabetes from the Multi-Ethnic Study of Atherosclerosis with valid data on homeostasis model assessment index (HOMA-IR), AAC, CAC, and TAC. Adipocytokines, SFA, and VFA were also determined. Results: HOMA-IR was associated with the presence of CAC, but not AAC and TAC, and the association remained significant after adjusting for traditional risk factors, adipocytokines, abdominal muscle mass, SFA, and VFA (prevalence ratio = 1.04 per one interquartile range [IQR] increase, P = 0.01). As the strength of the association of HOMA-IR with vascular calcification may differ by abdominal fat composition, subgroup analysis was performed among participants with different tertiles of SFA and VFA. Significant interactions between HOMA-IR with SFA and VFA separately were observed for the presence of TAC, but not AAC and CAC, even after adjusting for confounding factors. The association of HOMA-IR with TAC tended to be stronger in participants with more SFA and VFA. Conclusions: Atherosclerotic calcification, especially in the coronary arteries, is related to insulin resistance. Further studies are needed to delineate the mechanisms by which visceral obesity can lead to vascular calcification.

Published
2014

67. The relationship between total Bilirubin levels and total mortality in older adults: The United States national health and nutrition examination survey (NHANES) 1999-2004

Author

Ong, KL, Allison, MA, Cheung, BMY, Wu, BJ, Barter, PJ, Rye, KA, Ong, KL, Allison, MA, Cheung, BMY, Wu, BJ, Barter, PJ, and Rye, KA

Abstract

Objective: Due to its anti-oxidant and anti-inflammatory properties, bilirubin has been associated with reduced cardiovascular risk. A recent study demonstrated an L-shaped association of pre-treatment total bilirubin levels with total mortality in a statin-treated cohort. We therefore investigated the association of total bilirubin levels with total mortality in a nationally representative sample of older adults from the general population. Methods: A total of 4,303 participants aged ≥60 years from the United States National Health and Nutrition Examination Survey 1999-2004 with mortality data followed up through December 31, 2006 were included in this analysis, with a mean follow-up period of 4.5 years. Results: Participants with total bilirubin levels of 0.1-0.4 mg/dl had the highest mortality rate (19.8%). Compared with participants with total bilirubin levels of 0.5-0.7 mg/dl and in a multivariable regression model, a lower total bilirubin level of 0.1-0.4 mg/dl was associated with higher risk of total mortality (hazard ratios, 1.36; 95% confidence interval, 1.07-1.72; P = 0.012), while higher levels (≥0.8 mg/dl) also tended to be associated with higher risk of total mortality, but this did not reach statistical significance (hazard ratios, 1.24; 95% confidence interval, 0.98-1.56; P = 0.072). Conclusion: In this nationally representative sample of older adults, the association of total bilirubin levels with total mortality was the highest among those with a level between 0.1 and 0.4 mg/dl. Further studies are needed to investigate whether higher total bilirubin levels could be associated with a higher mortality risk, compared to a level of 0.5-0.7 mg/dl. © 2014 Ong et al.

Published
2014

68. Polymorphisms of the fibrinogen-beta gene are related to 2-hour glucose level after oral glucose tolerance test in Hong Kong Chinese

Author

Lam, TH, Cheung, BMY, Ong, KL, Leung, RYH, Wong, LYF, and Man, YB

Subjects
Male, Adult, Genotype, Fibrinogen, Impaired glucose tolerance, Middle Aged, Glucose Tolerance Test, Polymorphism, Single Nucleotide, Fibrinogen - genetics, Haplotype, Blood Glucose - analysis, Hong Kong, Humans, Regression Analysis, Female, Polymorphism
Abstract

Fibrinogen, an acute phase protein, is an important inflammatory marker that is associated with cardiovascular diseases. We studied the association of three common human fibrinogen-β gene (FGB) variants, -455G>A, -249C>T, and -148C>T with glycemic parameters in 265 non-diabetic Hong Kong Chinese subjects. Both FGB variants, -455G>A and -148C>T were in complete linkage disequilibrium and were associated with higher levels of plasma fibrinogen and 2-h glucose after a 75-g oral glucose load (p, link_to_OA_fulltext

Published
2008

69. Plasma Level of Adrenomedullin Is Influenced by a Single Nucleotide Polymorphism in the Adiponectin Gene

Author

Wong, HK, Ong, KL, Leung, RYH, Cheung, TT, Xu, A, Lam, TH, Lam, KSL, Cheung, BMY, Wong, HK, Ong, KL, Leung, RYH, Cheung, TT, Xu, A, Lam, TH, Lam, KSL, and Cheung, BMY

Abstract

Objective:Adrenomedullin (ADM) and adiponectin are both involved in inflammation and cardiovascular diseases. The plasma levels of these peptides are influenced by single nucleotide polymorphisms (SNPs) in the ADM and ADIPOQ genes respectively. There is some evidence that ADM may regulate adiponectin gene expression, but whether adiponectin can regulate ADM expression is unclear, and was therefore investigated.Methods:Plasma ADM level was measured in 476 subjects in the Hong Kong Cardiovascular Risk Factor Prevalence Study-2 (CRISPS2). We genotyped them for 2 ADIPOQ SNPs that are known to be associated with plasma adiponectin level.Results:The minor allele frequencies of ADIPOQ SNPs rs182052 and rs12495941 were 40.6% and 42.2% respectively. Plasma ADM level was significantly associated with rs182052 after adjusting for age and sex (β = 0.104, P = 0.023) but not with rs12495941 (β = 0.071, P = 0.120). In multivariate analysis, plasma ADM level increased with the number of minor alleles of rs182052 (P = 0.013). Compared to subjects with GG genotype, subjects with AA genotype had 17.7% higher plasma ADM level (95% CI: 3.6%-33.7%). Subgroup analysis revealed that the association was significant in diabetic patients (β = 0.344, P = 0.001) but not in non-diabetic subjects.Conclusion:Plasma ADM level is related to SNP rs182052 in the ADIPOQ gene. Our findings provide new evidence of the interplay between these two important peptides in cardiovascular disease and diabetes. Knowing the genotype may help to refine the interpretation of these biomarkers. © 2013 Wong et al.

Published
2013

70. Trends in C-reactive protein levels in US adults from 1999 to 2010

Author

Ong, KL, Allison, MA, Cheung, BMY, Wu, BJ, Barter, PJ, Rye, KA, Ong, KL, Allison, MA, Cheung, BMY, Wu, BJ, Barter, PJ, and Rye, KA

Abstract

C-reactive protein (CRP) is a well-known biomarker of systemic inflammation and cardiovascular disease. We investigated the trends in prevalence of elevated CRP levels (>3.0 mg/L) in a general population of US adults. Data from 27,214 subjects aged ≥20 years in the 1999-2010 National Health and Nutrition Examination Survey were analyzed. After adjustment for age, sex, race/ethnicity, body mass index (weight (kg)/height (m)2), and medications for lowering blood pressure, glucose, and lipids, the prevalence of elevated CRP decreased significantly from 36.7% in 1999-2002 to 32.0% in 2007-2010, corresponding to a decrease in mean CRP level from 1.92 to 1.66 mg/L (both P < 0.001). The trend remained significant after additional adjustment for several traditional cardiovascular risk factors and use of different medications, including statins. However, the decreasing trends were attenuated after additional adjustment for total bilirubin (P = 0.08 and 0.02), which increased from 0.62 to 0.73 mg/dL over 12 years (P < 0.001). The decreasing trend of CRP levels is encouraging and may be related to the increase in total bilirubin levels. Such trends may be explained in part by the increasing use of medications such as statins, which can increase bilirubin levels and decrease CRP levels. © 2013 The Author.

Published
2013

71. Arthritis: Its prevalence, Risk factors, And association with cardiovascular diseases in the United States, 1999 to 2008

Author

Ong, KL, Wu, BJ, Cheung, BMY, Barter, PJ, Rye, KA, Ong, KL, Wu, BJ, Cheung, BMY, Barter, PJ, and Rye, KA

Abstract

Objective: Arthritis is associated with cardiovascular diseases (CVDs). However, there are limited epidemiologic studies on arthritis in a national survey study. We therefore investigated the prevalence of self-reported arthritis and its association with CVDs. Methods: Data from 15,888 subjects aged 40 years or older in the United States National Health and Nutrition Examination Survey 1999 through 2008 were analyzed. CVD was defined as a self-reported history of heart attack, congestive heart failure, coronary heart disease, angina, or stroke. Results: The overall prevalence of self-reported arthritis in subjects aged 40 years or older increased from 33.5% in 1999 through 2000 to 37.0% in 2007 through 2008 (P for trend = 0.017). Among subjects with arthritis in 1999 through 2008, 35.3% had osteoarthritis (OA), 17.9% had rheumatoid arthritis (RA), and 10.2% had other types of arthritis, but 36.6% were unaware of their type of arthritis. Compared with subjects without OA, subjects with OA had higher odds for CVDs (odds ratio [OR], 1.53; P < .001), especially angina (OR, 2.18: P < .001). Compared with subjects without RA, subjects with RA had higher odds for CVDs (adjusted OR, 2.39; P < .001), especially congestive heart failure (OR, 3.59; P < .001). Conclusions: Both RA and OA are strongly associated with CVDs in the general population. Further studies are needed to investigate their causal relationship. © 2013 Elsevier Inc.

Published
2013

72. Long-term fenofibrate therapy increases fibroblast growth factor 21 and retinol-binding protein 4 in subjects with type 2 diabetes

Author

Ong, KL, Rye, KA, O'Connell, R, Jenkins, AJ, Brown, C, Xu, A, Sullivan, DR, Barter, PJ, Keech, AC, Ong, KL, Rye, KA, O'Connell, R, Jenkins, AJ, Brown, C, Xu, A, Sullivan, DR, Barter, PJ, and Keech, AC

Abstract

Context: Fenofibrate is a peroxisome proliferator-activated receptor (PPAR)-α agonist that showed beneficial effects on total cardiovascular risk in patients with type 2 diabetes in the Fenofibrate Intervention and Event Lowering in Diabetes (FIELD) study. Objective: This study aimed to investigate the long-term effect of fenofibrate therapy on three novel biomarkers of cardiovascular risk, namely adipocyte-fatty acid-binding protein (A-FABP), fibroblast growth factor 21 (FGF21), and retinol-binding protein 4 (RBP4), which are all down-stream targets of PPAR-α or PPAR-γ, in patients with type 2 diabetes. Design, Setting, and Patients: A total of 216 patients (108 in the fenofibrate group and 108 in the placebo group) were randomly selected from the FIELD study cohort. A-FABP, FGF21, and RBP4 levels were measured in serum samples at both baseline and the fifth year of the study. Results: Relative to the placebo group, the changes of serum FGF21 and RBP4 levels were 85% (P < 0.001) and 10% (P = 0.032) higher in the fenofibrate group, respectively, over 5 yr. Fenofibrate treatment had no detectable effect on serum A-FABP level (P > 0.05). The effect of fenofibrate treatment on serum FGF21, but not RBP4, remained significant after adjusting for fenofibrate-induced changes in glycosylated hemoglobin, total cholesterol, triglycerides, apolipoprotein A-II, fibrinogen, plasma creatinine, and homocysteine (P = 0.002). Conclusions: Long-term fenofibrate treatment could increase serum FGF21 levels over 5 yr in patients with type 2 diabetes. Additional studies are needed to investigate the potential role of FGF21 in the fenofibrate-mediated reduction of cardiovascular risk. Copyright © 2012 by The Endocrine Society.

Published
2012

73. Is human cytomegalovirus infection associated with hypertension? the united states national health and nutrition examination survey 1999-2002

Author

Li, C, Samaranayake, NR, Ong, KL, Wong, HK, Cheung, BMY, Li, C, Samaranayake, NR, Ong, KL, Wong, HK, and Cheung, BMY

Abstract

Purpose: Recent studies have implicated the human cytomegalovirus (HCMV) as a possible pathogen for causing hypertension. We aimed to study the association between HCMV infection and hypertension in the United States National Health and Nutrition Examination Survey (NHANES). Methods: We analyzed data on 2979 men and 3324 women in the NHANES 1999-2002. We included participants aged 16-49 years who had valid data on HCMV infection and hypertension. Results: Of the participants, 54.7% had serologic evidence of HCMV infection and 17.5% had hypertension. There were ethnic differences in the prevalence of HCMV infection (P<0.001) and hypertension (P<0.001). The prevalence of both increased with age (P<0.001). Before adjustment, HCMV seropositivity was significantly associated with hypertension in women (OR = 1.63, 95% CI = 1.25-2.13, P = 0.001) but not in men. After adjustment for race/ethnicity, the association between HCMV seropositivity and hypertension in women remained significant (OR = 1.55, 95% CI = 1.20-2.02, P = 0.002). Further adjustment for body mass index, diabetes status and hypercholesterolemia attenuated the association (OR = 1.44, 95% CI = 1.10-1.90, P = 0.010). However, after adjusting for age, the association was no longer significant (OR = 1.24, 95% CI = 0.91-1.67, P = 0.162). Conclusions: In this nationally representative population-based survey, HCMV seropositivity is associated with hypertension in women in the NHANES population. This association is largely explained by the association of hypertension with age and the increase in past exposure to HCMV with age. © 2012 Li et al.

Published
2012

74. Evaluation of the combined use of adiponectin and C-reactive protein levels as biomarkers for predicting the deterioration in glycaemia after a median of 5.4 years

Author

Ong, KL, Tso, AWK, Xu, A, Law, LSC, Li, M, Wat, NMS, Rye, KA, Lam, TH, Cheung, BMY, Lam, KSL, Ong, KL, Tso, AWK, Xu, A, Law, LSC, Li, M, Wat, NMS, Rye, KA, Lam, TH, Cheung, BMY, and Lam, KSL

Abstract

Aims/hypothesis: Hypoadiponectinaemia and raised C-reactive protein (CRP) level are obesity-related biomarkers associated with glucose dysregulation. We evaluated the combined use of these two biomarkers in predicting the deterioration of glycaemia in a prospective study after a median of 5.4 years. Methods: In total 1,288 non-diabetic participants from the Hong Kong Cardiovascular Risk Factor Prevalence Study-2, with high-sensitivity CRP (hsCRP) and total adiponectin levels measured were included. OGTT was performed in all participants. Two hundred and six participants had deterioration of glycaemia at follow-up, whereas 1,082 participants did not. Results: Baseline age, hsCRP and adiponectin levels were significant independent predictors of the deterioration of glycaemia in a Cox regression analysis after adjusting for baseline age, sex, BMI, hypertension, triacylglycerols, 2 h post-OGTT glucose and homeostasis model assessment of insulin resistance index (all p < 0.01). The introduction of hsCRP or adiponectin level to a regression model including the other biomarker improved the prediction of glycaemic progression significantly in all participants, especially in women (all p < 0.01). The combined inclusion of the two biomarkers resulted in a modest improvement in model discrimination, compared with the inclusion of either one alone. Among participants with impaired fasting glucose/impaired glucose tolerance (IFG/IGT) at baseline, hsCRP and adiponectin levels were not predictive of progression or improvement of glycaemic status. Conclusions/interpretation: Adiponectin and hsCRP levels are independent factors in predicting the deterioration of glycaemia, supporting the role of adiposity-related inflammation in the development of type 2 diabetes. Their combined use as predictive biomarkers is especially useful in women, but not in participants with IFG/IGT. © 2011 The Author(s).

Published
2011

75. The KCNJ11 E23K polymorphism and progression of glycaemia in Southern Chinese: A long-term prospective study

Author

Cheung, CYY, Tso, AWK, Cheung, BMY, Xu, A, Fong, CHY, Ong, KL, Law, LSC, Wat, NMS, Janus, ED, Sham, PC, Lam, KSL, Cheung, CYY, Tso, AWK, Cheung, BMY, Xu, A, Fong, CHY, Ong, KL, Law, LSC, Wat, NMS, Janus, ED, Sham, PC, and Lam, KSL

Abstract

Context: The KCNJ11 E23K variant is associated with type 2 diabetes mellitus (T2DM) in cross-sectional studies, but conflicting findings have been reported from prospective studies. Objective: This study aimed to evaluate whether the E23K variant could predict glycaemic progression in a Southern Chinese population. Methods/Principal Findings: We performed a long-term prospective study on 1912 subjects from the Hong Kong Cardiovascular Risk Factors Prevalence Study (CRISPS). The KCNJ11 E23K variant was associated with the progression to prediabetes after a median interval of 12 years on multinomial logistic regression analysis, even after adjustment for traditional risk factors (OR 1.29, P age, sex, BMI and fasting plasma glucose [FPG] adjusted = 0.02). Based on Cox proportional hazard regression analysis, the E23K variant also predicted incident prediabetes (HR 1.18, P age, sex, BMI and FPG adjusted = 0.021). However, E23K was not associated with the progression to T2DM in either multinomial or Cox regression analysis, and the association of E23K with glycaemic progression to either prediabetes or T2DM was significant only in unadjusted Cox regression analysis (P = 0.039). In a meta-analysis of eight prospective studies including our own, involving 15680 subjects, the E23K variant was associated with incident T2DM (fixed effect: OR 1.10, P = 4×10 -3; random effect: OR 1.11, P = 0.035). Conclusions: Our study has provided supporting evidence for the role of the E23K variant in glycaemic progression in Chinese, with its effect being more evident in the early stage of T2DM, as the subjects progressed from normal glucose tolerance to prediabetes. © 2011 Cheung et al.

Published
2011

76. The KCNJ11 E23K Polymorphism and Progression of Glycaemia in Southern Chinese: A Long-Term Prospective Study

Author

Sesti, G, Cheung, CYY, Tso, AWK, Cheung, BMY, Xu, A, Fong, CHY, Ong, KL, Law, LSC, Wat, NMS, Janus, ED, Sham, PC, Lam, KSL, Sesti, G, Cheung, CYY, Tso, AWK, Cheung, BMY, Xu, A, Fong, CHY, Ong, KL, Law, LSC, Wat, NMS, Janus, ED, Sham, PC, and Lam, KSL

Abstract

CONTEXT: The KCNJ11 E23K variant is associated with type 2 diabetes mellitus (T2DM) in cross-sectional studies, but conflicting findings have been reported from prospective studies. OBJECTIVE: This study aimed to evaluate whether the E23K variant could predict glycaemic progression in a Southern Chinese population. METHODS/PRINCIPAL FINDINGS: We performed a long-term prospective study on 1912 subjects from the Hong Kong Cardiovascular Risk Factors Prevalence Study (CRISPS). The KCNJ11 E23K variant was associated with the progression to prediabetes after a median interval of 12 years on multinomial logistic regression analysis, even after adjustment for traditional risk factors (OR 1.29, P(age, sex, BMI and fasting plasma glucose [FPG] adjusted) = 0.02). Based on Cox proportional hazard regression analysis, the E23K variant also predicted incident prediabetes (HR 1.18, P(age, sex, BMI and FPG adjusted)= 0.021). However, E23K was not associated with the progression to T2DM in either multinomial or Cox regression analysis, and the association of E23K with glycaemic progression to either prediabetes or T2DM was significant only in unadjusted Cox regression analysis (P = 0.039). In a meta-analysis of eight prospective studies including our own, involving 15680 subjects, the E23K variant was associated with incident T2DM (fixed effect: OR 1.10, P = 4×10(-3); random effect: OR 1.11, P = 0.035). CONCLUSIONS: Our study has provided supporting evidence for the role of the E23K variant in glycaemic progression in Chinese, with its effect being more evident in the early stage of T2DM, as the subjects progressed from normal glucose tolerance to prediabetes.

Published
2011

77. Polymorphisms of the fibrinogen-beta gene are related to 2-hour glucose level after oral glucose tolerance test in Hong Kong Chinese

Author

Wong, LYF, Ong, KL, Cheung, BMY, Leung, RYH, Man, YB, Lam, TH, Wong, LYF, Ong, KL, Cheung, BMY, Leung, RYH, Man, YB, and Lam, TH

Abstract

Fibrinogen, an acute phase protein, is an important inflammatory marker that is associated with cardiovascular diseases. We studied the association of three common human fibrinogen-β gene (FGB) variants, -455G>A, -249C>T, and -148C>T with glycemic parameters in 265 non-diabetic Hong Kong Chinese subjects. Both FGB variants, -455G>A and -148C>T were in complete linkage disequilibrium and were associated with higher levels of plasma fibrinogen and 2-h glucose after a 75-g oral glucose load (p<0.01). Carriers of FGB AC-haplotype, comprising the two nucleotide variants at positions -455 and -249, had higher fibrinogen level (2.64 ± 0.65 vs 2.42 ± 0.52 g/L, p=0.002) and 2-h glucose after a 75-g oral glucose load (5.87 ± 1.14 vs 5.47 ± 1.22 g/L, p=0.006). The associations were significant in men, but not women. In stepwise multiple regression analysis, AC-haplotype was independently associated with plasma fibrinogen level and 2-h glucose (p=0.002 and 0.010 respectively). This suggests that fibrinogen may play a role in the development of impaired glucose tolerance. © 2008 - IOS Press and the authors. All rights reserved.

Published
2008

78. An Approach to Argumentation Context Mining from Dialogue History in an E-Market Scenario

Author

Ong, KL, Li, W, Gao, J, Islam, KS, Ong, KL, Li, W, Gao, J, and Islam, KS

Abstract

Argumentation allows agents to exchange additional information to argue about their beliefs and other mental attitudes during the negotiation process. Utterances and subsequent observations may differ during argumentation due to the gap in internal and external information with other agent. Contextual information is one reason of deviation between utterance and subsequent observations. Historic dialogues are a key source for extracting contextual information regarding illocutions, ontological category or semantically similar category. How historical dialogues contribute to contextual information during argument generation, selection and evaluation process is crucial to modeling the commonsense that human being apply in managing dialogues. Identifying, managing and augmenting contextual information and use that information in agent dialogue requires attention to several dimensions, e.g., illocution, interaction protocol, ontology, context, contract etc. which is an important problem in electronic market research area. This paper presents an approach for extraction of argumentation context from historical dialogues between intelligent agents in e-market. We are developing an argumentation system to extract context from historical dialogue and exploit context for dialogue moves between agents. An agent architecture using context monitor, context network, context miner is presented for argumentation context mining

Published
2007

92. Management of Obesity in the National Health and Nutrition Examination Survey (NHANES), 2007-2008.

Author

Samaranayake NR, Ong KL, Leung RY, and Cheung BM

Abstract

PURPOSE: The prevalence of obesity has been increasing in the United States. We set out to investigate the use of pharmacologic and non-pharmacologic therapy for the treatment of obesity in recent years. METHODS: We included 2630 men and 2702 women who took part in the National Health and Nutrition Examination Survey from 2007 to 2008. We analyzed their demographic and anthropometric data and their weight and drug history. RESULTS: A total of 45.9% of men and 45.0% of women were candidates for treatment (body mass index >=30 kg/m(2), or >=27 kg/m(2) with risk factors). Among these participants, 85.1% considered themselves overweight, 90.1% would like to lose weight, 61.9% had dietary changes, 36.5% exercised, 3.7% took nonprescription drugs, and 2.2% took prescription drugs to control weight during the preceding year. During the preceding month, 0.5% and 0.1% of participants were taking phentermine and orlistat, respectively. There were no participants on sibutramine. CONCLUSIONS: Although obesity is highly prevalent, only a small percentage of obese Americans are on anti-obesity medication. The withdrawal of sibutramine would have minimal impact on the general population. There is a need for more lifestyle changes in the majority of obese individuals. [ABSTRACT FROM AUTHOR]

Published
2012

93. International survey of primary and revision total knee replacement.

Author

Kurtz SM, Ong KL, Lau E, Widmer M, Maravic M, Gómez-Barrena E, de Fátima de Pina M, Manno V, Torre M, Walter WL, de Steiger R, Geesink RG, Peltola M, Röder C, Kurtz, Steven M, Ong, Kevin L, Lau, Edmund, Widmer, Marcel, Maravic, Milka, and Gómez-Barrena, Enrique

Abstract

Purpose: Total knee arthroplasty (TKA) is currently the international standard of care for treating degenerative and rheumatologic knee joint disease, as well as certain knee joint fractures. We sought to answer the following three research questions: (1) What is the international variance in primary and revision TKA rates around the world? (2) How do patient demographics (e.g., age, gender) vary internationally? (3) How have the rates of TKA utilization changed over time?Methods: The survey included 18 countries with a total population of 755 million, and an estimated 1,324,000 annual primary and revision total knee procedures. Ten national inpatient databases were queried for this study from Canada, the United States, Finland, France, Germany, Italy, the Netherlands, Portugal, Spain, and Switzerland. Inpatient data were also compared with published registry data for eight countries with operating arthroplasty registers (Denmark, England & Wales, Norway, Romania, Scotland, Sweden, Australia, and New Zealand).Results: The average and median rate of primary and revision (combined) total knee replacement was 175 and 149 procedures/100,000 population, respectively, and ranged between 8.8 and 234 procedures/100,000 population. We observed that the procedure rate significantly increased over time for the countries in which historical data were available. The compound annual growth in the incidence of TKA ranged by country from 5.3% (France) to 17% (Portugal). We observed a nearly 27-fold range of TKA utilization rates between the 18 different countries included in the survey.Conclusion: It is apparent from the results of this study that the demand for TKA has risen substantially over the past decade in countries around the world. [ABSTRACT FROM AUTHOR]

Published
2011
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96. Prevalence, treatment, and control of diagnosed diabetes in the U.S. National Health and Nutrition Examination Survey 1999-2004.

Author

Ong KL, Cheung BMY, Wong LYF, Wat NMS, Tan KCB, and Lam KSL

Abstract

PURPOSE: This study aimed to examine the trends in prevalence, treatment, and control of diagnosed diabetes in United States adults 20 years of age or older. METHODS: Data from the National Health and Nutrition Examination Survey 1999-2004 were used. Glycemic, blood pressure, and total cholesterol target levels were defined as having glycosylated hemoglobin <7.0%, blood pressure <130/80 mm Hg, and total cholesterol <200 mg/dL, respectively. RESULTS: The prevalence of diagnosed diabetes was 7.8% in 2003-2004 and increased significantly in people aged 40-59 years, women, non-Hispanic whites, and obese people in the period 1999-2004. Although there was no significant change in the pattern of antidiabetic treatment, the age-adjusted percentage of people with diagnosed diabetes achieving glycemic and blood pressure target levels increased from 35.8% to 57.1% (p = 0.002) and from 35.7% to 48.3% (p = 0.04), respectively. However, there were only insignificant increases in percentages of those persons achieving total cholesterol target level (from 48.8% to 50.4%) and those achieving all 3 target levels (from 7.5% to 13.2%). CONCLUSIONS: In 1999-2004, the prevalence of diagnosed diabetes increased significantly in some subgroups of the population. However, the increases in percentages of people with diabetes achieving glycemic and blood pressure targets are encouraging, although there is room for improvement. [ABSTRACT FROM AUTHOR]

Published
2008
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97. High plasma level of fibroblast growth factor 21 is an Independent predictor of type 2 diabetes: a 5.4-year population-based prospective study in Chinese subjects.

Author

Chen C, Cheung BM, Tso AW, Wang Y, Law LS, Ong KL, Wat NM, Xu A, Lam KS, Chen, Cheng, Cheung, Bernard M Y, Tso, Annette W K, Wang, Yudong, Law, Lawrence S C, Ong, Kwok Leung, Wat, Nelson M S, Xu, Aimin, and Lam, Karen S L

Abstract

Objective: To investigate whether circulating levels of fibroblast growth factor 21 (FGF21), which previously has been shown to be elevated in obesity, could predict the development of type 2 diabetes in a 5.4-year, population-based, prospective study.Research Design and Methods: Baseline plasma FGF21 levels were measured using an enzyme-linked immunosorbent assay in 1,900 subjects from the Hong Kong Cardiovascular Risk Factor Prevalence Study (CRISPS). The prospective association of FGF21 with diabetes development over 5.4 years was analyzed using multiple logistic regression.Results: At baseline, plasma levels of FGF21 increased progressively with worsening dysglycemia from normal glucose tolerance, through prediabetes, to diabetes (global trend, P < 0.001). Of 1,292 subjects without diabetes at baseline, a high baseline FGF21 level was a strong independent predictor for diabetes development (odds ratio 1.792; P < 0.01), together with waist circumference and fasting plasma glucose levels.Conclusions: Plasma FGF21 levels were significantly increased in subjects with prediabetes and diabetes and predicted the development of diabetes in humans. [ABSTRACT FROM AUTHOR]

Published
2011
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99. Global age-sex-specific fertility, mortality, healthy life expectancy (HALE), and population estimates in 204 countries and territories, 1950–2019: a comprehensive demographic analysis for the Global Burden of Disease Study 2019

Author

Abbafati, C., Machado, D.B., Cislaghi, B., Salman, O.M., Karanikolos, M., McKee, M., Abbas, K.M., Brady, O.J., Larson, H.J., Trias-Llimós, S., Cummins, S., Langan, S.M., Sartorius, B., Hafiz, A., Jenabi, E., Mohammad Gholi Mezerji, N., Borzouei, S., Azarian, G., Khazaei, S., Abbasi, M., Asghari, B., Masoumi, S., Komaki, H., Taherkhani, A., Adabi, M., Abbasifard, M., Bazmandegan, G., Kamiab, Z., Vakilian, A., Anjomshoa, M., Mokari, A., Sabour, S., Shahbaz, M., Saeedi, R., Ahmadieh, H., Yousefinezhadi, T., Haj-Mirzaian, A., Nikbakhsh, R., Safi, S., Asgari, S., Irvani, S.N., Jahanmehr, N., Ramezanzadeh, K., Abbasi-Kangevari, M., Khayamzadeh, M., Abbastabar, H., Shirkoohi, R., Fazlzadeh, M., Janjani, H., Hosseini, M., Mansournia, M., Tohidinik, H., Bakhtiari, A., Fazaeli, A., Mousavi, S., Hasanzadeh, A., Nabavizadeh, B., Malekzadeh, R., Hashemian, M., Pourshams, A., Salimzadeh, H., Sepanlou, S.G., Afarideh, M., Esteghamati, A., Esteghamati, S., Ghajar, A., Heidari, B., Rezaei, N., Mohamadi, E., Rahimi-Movaghar, A., Rahim, F., Eskandarieh, S., Sahraian, M., Mohebi, F., Aminorroaya, A., Ebrahimi, H., Farzadfar, F., Mohajer, B., Pishgar, F., Saeedi Moghaddam, S., Shabani, M., Zarafshan, H., Abolhassani, H., Hafezi-Nejad, N., Heidari-Soureshjani, R., Abdollahi, M., Farahmand, M., Salamati, P., Mehrabi Nasab, E., Tajdini, M., Aghamir, S., Mirzaei, R., Dibaji Forooshani, Z., Khater, M.M., Abd-Allah, F., Abdelalim, A., Abualhasan, A., El-Jaafary, S.I., Hassan, A., Elsharkawy, A., Khater, A.M., Elhabashy, H.R., Salem, M.R.R., Salem, H., Sadeghi, M., Jafarinia, M., Amini-Rarani, M., Mohammadifard, N., Sarrafzadegan, N., Abdollahpour, I., Sarveazad, A., Tehrani-Banihashemi, A., Yoosefi Lebni, J., Manafi, N., Pazoki Toroudi, H., Dorostkar, F., Alipour, V., Sheikhtaheri, A., Arabloo, J., Azari, S., Ghashghaee, A., Rezapour, A., Naserbakht, M., Kabir, A., Mehri, F., Yousefifard, M., Asadi-Aliabadi, M., Babaee, E., Eshrati, B., Goharinezhad, S., Moradi-Lakeh, M., Abedi, P., Rashedi, V., Kumar, V., Elgendy, I.Y., Basu, S., Park, J., Pereira, A., Norheim, O.F., Eagan, A.W., Cahill, L.E., Sheikh, A., Abushouk, A.I., Kraemer, M.U.G., Thakur, B., Bärnighausen, T.W., Shrime, M.G., Abedi, A., Doshi, C.P., Abegaz, K.H., Geberemariyam, B.S., Aynalem, Y.A., Shiferaw, W.S., Abosetugn, A.E., Aboyans, V., Abrams, E.M., Gitimoghaddam, M., Kissoon, N., Stubbs, J.L., Brauer, M., Iyamu, I.O., Kopec, J.A., Pourmalek, F., Ribeiro, A.P., Malta, D.C., Gomez, R.S., Abreu, L.G., Abrigo, M.R.M., Almulhim, A.M., Dahlawi, S.M.A., Pottoo, F.H., Menezes, R.G., Alanzi, T.M., Alumran, A.K., Abu Haimed, A.K., Madadin, M., Alanezi, F.M., Abu-Gharbieh, E., Saddik, B., Abu-Raddad, L.J., Samy, A.M., El Nahas, N., Shalash, A.S., Nabhan, A.F., Kamath, A.M., Kassebaum, N.J., Aravkin, A.Y., Kochhar, S., Sorensen, R.J.D., Afshin, A., Burkart, K., Cromwell, E.A., Dandona, L., Dharmaratne, S.D., Gakidou, E., Hay, S.I., Kyu, H.H., Lopez, A.D., Lozano, R., Misganaw, A.T., Mokdad, A.H., Naghavi, M., 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Kissimova-Skarbek, Katarzyna, Kivimäki, Mika, Komaki, Hamidreza, Kopec, Jacek A, Kosen, Soewarta, Koul, Parvaiz A, Koyanagi, Ai, Kravchenko, Michael A, Krishan, Kewal, Krohn, Kris J, Kuate Defo, Barthelemy, Kumar, G Anil, Kumar, Manasi, Kumar, Pushpendra, Kumar, Vivek, Kusuma, Dian, Kyu, Hmwe Hmwe, La Vecchia, Carlo, Lacey, Ben, Lal, Dharmesh Kumar, Lalloo, Ratilal, Lami, Faris Hasan, Lansky, Sonia, Larson, Samantha Leigh, Larsson, Anders O, Lasrado, Savita, Lassi, Zohra S, Lazarus, Jeffrey V, Lee, Paul H, Lee, Shaun Wen Huey, Leever, Andrew T, Legrand, Kate E, Leonardi, Matilde, Li, Shanshan, Lim, Lee-Ling, Lim, Stephen S, Linn, Shai, Lodha, Rakesh, Logroscino, Giancarlo, Lopez, Alan D, Lopukhov, Platon D, Lotufo, Paulo A, Lozano, Rafael, Lu, Alton, Lunevicius, Raimunda, Madadin, Mohammed, Maddison, Emilie R, Magdy Abd El Razek, Hassan, Magdy Abd El Razek, Muhammed, Mahasha, Phetole Walter, Mahdavi, Mokhtar Mahdavi, Malekzadeh, Reza, Mamun, Abdullah A, Manafi, Navid, Mansour-Ghanaei, Fariborz, Mansouri, Borhan, Mansournia, Mohammad Ali, Mapoma, Chabila Christopher, Martini, Santi, Martins-Melo, Francisco Rogerlândio, Masaka, Anthony, Mastrogiacomo, Claudia I, Mathur, Manu Raj, May, Erin A, Mcalinden, Colm, Mcgrath, John J, Mckee, Martin, Mehndiratta, Man Mohan, Mehri, Fereshteh, Mehta, Kala M, Meitei, Wahengbam Bigyananda, Memiah, Peter T N, Mendoza, Walter, Menezes, Ritesh G, Mengesha, Endalkachew Worku, Mensah, George A, Meretoja, Atte, Meretoja, Tuomo J, Mestrovic, Tomislav, Michalek, Irmina Maria, Mihretie, Kebadnew Mulatu, Miller, Ted R, Mills, Edward J, Milne, George J, Mirrakhimov, Erkin M, Mirzaei, Hamed, Mirzaei, Maryam, Mirzaei-Alavijeh, Mehdi, Misganaw, Awoke Temesgen, Moazen, Babak, Moghadaszadeh, Masoud, Mohamadi, Efat, Mohammad, Dara K, Mohammad, Yousef, Mohammad Gholi Mezerji, Naser, Mohammadbeigi, Abolfazl, Mohammadian-Hafshejani, Abdollah, Mohammadpourhodki, Reza, Mohammed, Hussen, Mohammed, Shafiu, Mohebi, Farnam, Mohseni Bandpei, Mohammad A, Mokari, Amin, Mokdad, Ali H, Momen, Natalie C, Monasta, Lorenzo, Mooney, Meghan D, Moradi, Ghobad, Moradi, Masoud, Moradi-Joo, Mohammad, Moradi-Lakeh, Maziar, Moradzadeh, Rahmatollah, Moraga, Paula, Moreno Velásquez, Ilai, Morgado-da-Costa, Joana, Morrison, Shane Dougla, Mosser, Jonathan F, Mouodi, Simin, Mousavi, Seyyed Meysam, Mousavi Khaneghah, Amin, Mueller, Ulrich Otto, Musa, Kamarul Imran, Muthupandian, Saravanan, Nabavizadeh, Behnam, Naderi, Mehdi, Nagarajan, Ahamarshan Jayaraman, Naghavi, Mohsen, Naghshtabrizi, Behshad, Naik, Gurudatta, Najafi, Farid, Nangia, Vinay, Nansseu, Jobert Richie, Ndwandwe, Duduzile Edith, Negoi, Ionut, Negoi, Ruxandra Irina, Ngunjiri, Josephine W, Nguyen, Huong Lan Thi, Nguyen, Trang Huyen, Nigatu, Yeshambel T, Nikbakhsh, Rajan, Nikpoor, Amin Reza, Nixon, Molly R, Nnaji, Chukwudi A, Nomura, Shuhei, Noubiap, Jean Jacque, Nouraei Motlagh, Soraya, Nowak, Christoph, Oţoiu, Adrian, Odell, Christopher M, Oh, In-Hwan, Oladnabi, Morteza, Olagunju, Andrew T, Olusanya, Bolajoko Olubukunola, Olusanya, Jacob Olusegun, Omar Bali, Ahmed, Ong, Kanyin L, Onwujekwe, Obinna E, Ortiz, Alberto, Otstavnov, Nikita, Otstavnov, Stanislav S, Øverland, Simon, Owolabi, Mayowa O, P A, Mahesh, Padubidri, Jagadish Rao, Pakshir, Keyvan, Palladino, Raffaele, Pana, Adrian, Panda-Jonas, Songhomitra, Park, Jame, Pasupula, Deepak Kumar, Patel, Jenil R, Patel, Sangram Kishor, Patton, George C, Paulson, Katherine R, Pazoki Toroudi, Hamidreza, Pease, Spencer A, Peden, Amy E, Pepito, Veincent Christian Filipino, Peprah, Emmanuel K, Pereira, Alexandre, Pereira, David M, Perico, Norberto, Pigott, David M, Pilgrim, Thoma, Pilz, Tessa M, Piradov, Michael A, Pirsaheb, Meghdad, Pokhrel, Khem Narayan, Postma, Maarten J, Pourjafar, Hadi, Pourmalek, Farshad, Pourshams, Akram, Poznańska, Anna, Prada, Sergio I, Prakash, Sanjay, Preotescu, Liliana, Quazi Syed, Zahiruddin, Rabiee, Mohammad, Rabiee, Navid, Radfar, Amir, Rafiei, Alireza, Raggi, Alberto, Rahman, Muhammad Aziz, Rajabpour-Sanati, Ali, Ram, Pradhum, Ranabhat, Chhabi Lal, Rao, Sowmya J, Rasella, Davide, Rashedi, Vahid, Rastogi, Prateek, Rathi, Priya, Rawal, Lal, Remuzzi, Giuseppe, Renjith, Vishnu, Renzaho, Andre M N, Resnikoff, Serge, Rezaei, Nima, Rezai, Mohammad sadegh, Rezapour, Aziz, Rickard, Jennifer, Roever, Leonardo, Ronfani, Luca, Roshandel, Gholamreza, Rostamian, Morteza, Rubagotti, Enrico, Rwegerera, Godfrey M, Sabour, Siamak, Saddik, Basema, Sadeghi, Ehsan, Sadeghi, Masoumeh, Saeedi Moghaddam, Sahar, Safari, Yahya, Safi, Sare, Safiri, Saeid, Sagar, Rajesh, Sahebkar, Amirhossein, Sahraian, Mohammad Ali, Sajadi, S Mohammad, Salahshoor, Mohammad Reza, Salama, Joseph S, Salamati, Payman, Salem, Marwa R Rashad, Salimi, Yahya, Salomon, Joshua A, Salz, Inbal, Samad, Zainab, Samy, Abdallah M, Sanabria, Juan, Santric-Milicevic, Milena M, Saraswathy, Sivan Yegnanarayana Iyer, Sartorius, Benn, Sarveazad, Arash, Sathian, Brijesh, Sathish, Thirunavukkarasu, Sattin, Davide, Saylan, Mete, Schaeffer, Lauren E, Schiavolin, Silvia, Schwebel, David C, Schwendicke, Falk, Sekerija, Mario, Senbeta, Anbissa Muleta, Senthilkumaran, Subramanian, Sepanlou, Sadaf G, Serván-Mori, Edson, Shabani, Mahsima, Shahabi, Saeed, Shahbaz, Mohammad, Shaheen, Amira A, Shaikh, Masood Ali, Shalash, Ali S, Shams-Beyranvand, Mehran, Shamsi, Mohammadbagher, Shamsizadeh, Morteza, Shannawaz, Mohammed, Sharafi, Kiomar, Sharafi, Zeinab, Sharara, Fablina, Sharma, Rajesh, Shaw, David H, Sheikh, Aziz, Shin, Jae Il, Shiri, Rahman, Shrime, Mark G, Shuval, Kerem, Siabani, Soraya, Sigfusdottir, Inga Dora, Sigurvinsdottir, Rannveig, Silva, Diego Augusto Santo, Simonetti, Biagio, Simpson, Kyle E, Singh, Jasvinder A, Skiadaresi, Eirini, Skryabin, Valentin Yurievich, Soheili, Amin, Sokhan, Anton, Sorensen, Reed J D, Soriano, Joan B, Sorrie, Muluken Bekele, Soyiri, Ireneous N, Spurlock, Emma Elizabeth, Sreeramareddy, Chandrashekhar T, Stockfelt, Leo, Stokes, Mark A, Stubbs, Jacob L, Sudaryanto, Agu, Sufiyan, Mu'awiyyah Babale, Suliankatchi Abdulkader, Rizwan, Sykes, Bryan L, Tabarés-Seisdedos, Rafael, Tabb, Karen M, Tadakamadla, Santosh Kumar, Taherkhani, Amir, Tang, Muming, Taveira, Nuno, Taylor, Heather Jean, Teagle, Whitney L, Tehrani-Banihashemi, Arash, Teklehaimanot, Berhane Fseha, Tessema, Zemenu Tadesse, Thankappan, Kavumpurathu Raman, Thomas, Nihal, Thrift, Amanda G, Titova, Mariya Vladimirovna, Tohidinik, Hamid Reza, Tonelli, Marcello, Topor-Madry, Roman, Topouzis, Foti, Tovani-Palone, Marcos Roberto Roberto, Traini, Eugenio, Tran, Bach Xuan, Travillian, Ravensara, Trias-Llimós, Sergi, Truelsen, Thomas Clement, Tudor Car, Lorainne, Unnikrishnan, Bhaskaran, Upadhyay, Era, Vacante, Marco, Vakilian, Alireza, Valdez, Pascual R, Valli, Alessandro, Vardavas, Constantine, Vasankari, Tommi Juhani, Vasconcelos, Ana Maria Nogale, Vasseghian, Yasser, Veisani, Yousef, Venketasubramanian, Narayanaswamy, Vidale, Simone, Violante, Francesco S, Vlassov, Vasily, Vollset, Stein Emil, Vos, Theo, Vujcic, Isidora S, Vukovic, Ana, Vukovic, Rade, Waheed, Yasir, Wallin, Mitchell Taylor, Walters, Magdalene K, Wang, Hongbo, Wang, Yuan-Pang, Watson, Stefanie, Wei, Jingkai, Weiss, Jordan, Weldesamuel, Girmay Teklay, Werdecker, Andrea, Westerman, Ronny, Whiteford, Harvey A, Wiangkham, Taweewat, Wiens, Kirsten E, Wijeratne, Tissa, Wiysonge, Charles Shey, Wojtyniak, Bogdan, Wolfe, Charles D A, Wondmieneh, Adam Belay, Wool, Eve E, Wu, Ai-Min, Wu, Junjie, Xu, Gelin, Yamada, Tomohide, Yamagishi, Kazumasa, Yano, Yuichiro, Yaya, Sanni, Yazdi-Feyzabadi, Vahid, Yearwood, Jamal A, Yeheyis, Tomas Y, Yilgwan, Christopher Sabo, Yip, Paul, Yonemoto, Naohiro, Yoon, Seok-Jun, Yoosefi Lebni, Javad, York, Hunter W, Younis, Mustafa Z, Younker, Theodore Patrick, Yousefi, Zabihollah, Yousefinezhadi, Taraneh, Yousuf, Abdilahi Yousuf, Yusefzadeh, Hasan, Zahirian Moghadam, Telma, Zakzuk, Josefina, Zaman, Sojib Bin, Zamani, Mohammad, Zamanian, Maryam, Zandian, Hamed, Zhang, Zhi-Jiang, Zheng, Peng, Zhou, Maigeng, Ziapour, Arash, Murray, Christopher J L, Collaborators, GBD 2019 Demographics, GBD 2019 Demographics Collaborator, Violante FS, Value, Affordability and Sustainability (VALUE), Real World Studies in PharmacoEpidemiology, -Genetics, -Economics and -Therapy (PEGET), Microbes in Health and Disease (MHD), Department of Earth Systems Analysis, Biomechanical Engineering, TechMed Centre, Biomolecular Nanotechnology, Research Methodology, Measurement and Data Analysis, Materials Science and Technology of Polymers, Inorganic Materials Science, MESA+ Institute, Biomedical and Environmental Sensorsystems, Mesoscale Chemical Systems, Faculty of Engineering Technology, Nonlinear Solid Mechanics, Digital Society Institute, Pervasive Systems, Nanobiophysics, Faculty of Geo-Information Science and Earth Observation, Multi Scale Mechanics, Engineering Fluid Dynamics, Physics of Complex Fluids, Developmental BioEngineering, Physics of Fluids, Elastomer Technology and Engineering, Medical Cell Biophysics, European Membrane Institute, Department of Earth Observation Science, Biomaterials Science and Technology, Sustainable Process Technology, Department of Urban and Regional Planning and Geo-Information Management, Department of Natural Resources, XUV Optics, Databases (Former), Department of Water Resources, Psychology, Health & Technology, Membrane Science & Technology, Department of Public Health, Clinicum, HUS Neurocenter, HUS Comprehensive Cancer Center, and Environmental Sciences

Subjects
Male, very elderly, Demographic transition, HALE, 030204 cardiovascular system & hematology, preschool child, Global Burden of Disease, Carga Global de Enfermedades, 0302 clinical medicine, newborn, Risk Factors, Surveys and Questionnaires, and Risk Factors Study, 80 and over, 030212 general & internal medicine, Birth Rate, Child, Migration, 11 Medical and Health Sciences, Aged, 80 and over, education.field_of_study, Injuries, Geography, Mortality rate, 1. No poverty, DEATH, Censuses, General Medicine, SDG 10 - Reduced Inequalities, Middle Aged, Demographic analysis, 3142 Public health care science, environmental and occupational health, 3. Good health, demographic analysis, Estilo de Vida Saludable, risk factor, Child, Preschool, Demography/statistics & numerical data, Global Burden of Diseases, Injuries, Risk Factors, Fertility, Mortality, Migration, Population, epidemiology, Female, A990 Medicine and Dentistry not elsewhere classified, CHILD-MORTALITY, Live Birth, Global Health Metrics, TRANSITION, demographics, GBD, fertility, mortality, hale, Adult, Adolescent, Total fertility rate, Population, Global Burden of Diseases, Injuries, and Risk Factors Study, Birth rate, 03 medical and health sciences, Young Adult, Life Expectancy, SDG 3 - Good Health and Well-being, General & Internal Medicine, SYSTEMATIC ANALYSIS, Demografía, Humans, Global Burden of Disease Study, human, Mortality, education, Preschool, Aged, Demography, Spatial Analysis, questionnaire, Infant, Newborn, Klinisk medicin, HIV, Infant, Global Burden of Diseases, sex-specific fertility, Live Birth/epidemiology, purl.org/pe-repo/ocde/ford#3.02.00 [https], MODEL, Fertilidad, Fertility, Demographic change, Life expectancy, NA, global disease burden, Clinical Medicine, population research
Abstract

Background Accurate and up-to-date assessment of demographic metrics is crucial for understanding a wide range of social, economic, and public health issues that affect populations worldwide. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 produced updated and comprehensive demographic assessments of the key indicators of fertility, mortality, migration, and population for 204 countries and territories and selected subnational locations from 1950 to 2019. Methods 8078 country-years of vital registration and sample registration data, 938 surveys, 349 censuses, and 238 other sources were identified and used to estimate age-specific fertility. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate age-specific fertility rates for 5-year age groups between ages 15 and 49 years. With extensions to age groups 10-14 and 50-54 years, the total fertility rate (TFR) was then aggregated using the estimated age-specific fertility between ages 10 and 54 years. 7417 sources were used for under-5 mortality estimation and 7355 for adult mortality. ST-GPR was used to synthesise data sources after correction for known biases. Adult mortality was measured as the probability of death between ages 15 and 60 years based on vital registration, sample registration, and sibling histories, and was also estimated using ST-GPR. HIV-free life tables were then estimated using estimates of under-5 and adult mortality rates using a relational model life table system created for GBD, which closely tracks observed age-specific mortality rates from complete vital registration when available. Independent estimates of HIV-specific mortality generated by an epidemiological analysis of HIV prevalence surveys and antenatal clinic serosurveillance and other sources were incorporated into the estimates in countries with large epidemics. Annual and single-year age estimates of net migration and population for each country and territory were generated using a Bayesian hierarchical cohort component model that analysed estimated age-specific fertility and mortality rates along with 1250 censuses and 747 population registry years. We classified location-years into seven categories on the basis of the natural rate of increase in population (calculated by subtracting the crude death rate from the crude birth rate) and the net migration rate. We computed healthy life expectancy (HALE) using years lived with disability (YLDs) per capita, life tables, and standard demographic methods. Uncertainty was propagated throughout the demographic estimation process, including fertility, mortality, and population, with 1000 draw-level estimates produced for each metric. Findings The global TFR decreased from 2.72 (95% uncertainty interval [UI] 2.66-2.79) in 2000 to 2.31 (2.17-2.46) in 2019. Global annual livebirths increased from 134.5 million (131.5-137.8) in 2000 to a peak of 139.6 million (133.0-146.9) in 2016. Global livebirths then declined to 135.3 million (127.2-144.1) in 2019. Of the 204 countries and territories included in this study, in 2019, 102 had a TFR lower than 2.1, which is considered a good approximation of replacement-level fertility. All countries in sub-Saharan Africa had TFRs above replacement level in 2019 and accounted for 27.1% (95% UI 26.4-27.8) of global livebirths. Global life expectancy at birth increased from 67.2 years (95% UI 66.8-67.6) in 2000 to 73.5 years (72.8-74.3) in 2019. The total number of deaths increased from 50.7 million (49.5-51.9) in 2000 to 56.5 million (53.7-59.2) in 2019. Under-5 deaths declined from 9.6 million (9.1-10.3) in 2000 to 5.0 million (4.3-6.0) in 2019. Global population increased by 25.7%, from 6.2 billion (6.0-6.3) in 2000 to 7.7 billion (7.5-8.0) in 2019. In 2019, 34 countries had negative natural rates of increase; in 17 of these, the population declined because immigration was not sufficient to counteract the negative rate of decline. Globally, HALE increased from 58.6 years (56.1-60.8) in 2000 to 63.5 years (60.8-66.1) in 2019. HALE increased in 202 of 204 countries and territories between 2000 and 2019. Interpretation Over the past 20 years, fertility rates have been dropping steadily and life expectancy has been increasing, with few exceptions. Much of this change follows historical patterns linking social and economic determinants, such as those captured by the GBD Socio-demographic Index, with demographic outcomes. More recently, several countries have experienced a combination of low fertility and stagnating improvement in mortality rates, pushing more populations into the late stages of the demographic transition. Tracking demographic change and the emergence of new patterns will be essential for global health monitoring. Copyright (C) 2020 The Author(s). Published by Elsevier Ltd.

Published
2020

100. Measuring progress from 1990 to 2017 and projecting attainment to 2030 of the health-related Sustainable Development Goals for 195 countries and territories: a systematic analysis for the Global Burden of Disease Study 2017

Author

Lozano, Rafael, Fullman, Nancy, Abate, Degu, Abay, Solomon M, Abbafati, Cristiana, Abbasi, Nooshin, Abbastabar, Hedayat, Abd-Allah, Foad, Abdela, Jemal, Abdelalim, Ahmed, Abdel-Rahman, Omar, Abdi, Alireza, Abdollahpour, Ibrahim, Abdulkader, Rizwan Suliankatchi, Abebe, Nebiyu Dereje, Abebe, Zegeye, Abejie, Ayenew Negesse, Abera, Semaw F, Abil, Olifan Zewdie, Aboyans, Victor, Abraha, Haftom Niguse, Abrham, Aklilu Roba, Abu-Raddad, Laith Jamal, Abu-Rmeileh, Niveen Me, Abyu, Gebre Y, Accrombessi, Manfred Mario Kokou, Acharya, Dilaram, Acharya, Pawan, Adamu, Abdu A, Adebayo, Oladimeji M, Adedeji, Isaac Akinkunmi, Adedoyin, Rufus Adesoji, Adekanmbi, Victor, Adetokunboh, Olatunji O, Adhena, Beyene Meressa, Adhikari, Tara Ballav, Adib, Mina G, Adou, Arsène Kouablan, Adsuar, Jose C, Afarideh, Mohsen, Afshari, Mahdi, Afshin, Ashkan, Agarwal, Gina, Aghayan, Sargis Aghasi, Agius, Dominic, Agrawal, Anurag, Agrawal, Sutapa, Ahmadi, Alireza, Ahmadi, Mehdi, Ahmadieh, Hamid, Ahmed, Muktar Beshir, Ahmed, Sayem, Akalu, Temesgen Yihunie, Akanda, Ali S, Akbari, Mohammad Esmaeil, Akibu, Mohammed, Akinyemi, Rufus Olusola, Akinyemiju, Tomi, Akseer, Nadia, Alahdab, Fares, Al-Aly, Ziyad, Alam, Khurshid, Alam, Tahiya, Albujeer, Ammar, Alebel, Animut, Alene, Kefyalew Addis, Al-Eyadhy, Ayman, Alhabib, Samia, Ali, Raghib, Alijanzadeh, Mehran, Alizadeh-Navaei, Reza, Aljunid, Syed Mohamed, Alkerwi, Ala'a, Alla, François, Allebeck, Peter, Allen, Christine A, Almasi, Ali, Al-Maskari, Fatma, Al-Mekhlafi, Hesham M, Alonso, Jordi, Al-Raddadi, Rajaa M, Alsharif, Ubai, Altirkawi, Khalid, Alvis-Guzman, Nelson, Amare, Azmeraw T, Amenu, Kebede, Amini, Erfan, Ammar, Walid, Anber, Nahla Hamed, Anderson, Jason A, Andrei, Catalina Liliana, Androudi, Sofia, Animut, Megbaru Debalkie, Anjomshoa, Mina, Ansari, Hossein, Ansariadi, Ansariadi, Ansha, Mustafa Geleto, Antonio, Carl Abelardo T, Anwari, Palwasha, Appiah, Lambert Tetteh, Aremu, Olatunde, Areri, Habtamu Abera, Ärnlöv, Johan, Arora, Monika, Aryal, Krishna K, Asayesh, Hamid, Asfaw, Ephrem Tsegay, Asgedom, Solomon Weldegebreal, Asghar, Rana Jawad, Assadi, Reza, Ataro, Zerihun, Atique, Suleman, Atre, Sachin R, Atteraya, Madhu Sudhan, Ausloos, Marcel, Avila-Burgos, Leticia, Avokpaho, Euripide F G A, Awasthi, Ashish, Ayala Quintanilla, Beatriz Paulina, Ayele, Henok Tadesse, Ayele, Yohanes, Ayer, Rakesh, Azarpazhooh, Mahmoud Reza, Azzopardi, Peter S, Azzopardi-Muscat, Natasha, Babalola, Tesleem Kayode, Babazadeh, Arefeh, Badali, Hamid, Badawi, Alaa, Balakrishnan, Kalpana, Bali, Ayele Geleto, Banach, Maciej, Banerjee, Amitava, Banoub, Joseph Adel Mattar, Banstola, Amrit, Barac, Aleksandra, Barboza, Miguel A, Barker-Collo, Suzanne Lyn, Bärnighausen, Till Winfried, Barrero, Lope H, Barthelemy, Celine M, Bassat, Quique, Basu, Arindam, Basu, Sanjay, Battista, Robert J, Baune, Bernhard T, Baynes, Habtamu Wondifraw, Bazargan-Hejazi, Shahrzad, Bedi, Neeraj, Beghi, Ettore, Behzadifar, Masoud, Behzadifar, Meysam, Béjot, Yannick, Bekele, Bayu Begashaw, Belachew, Abate Bekele, Belay, Aregawi Gebreyesus, Belay, Saba Abraham, Belay, Yihalem Abebe, Bell, Michelle L, Bello, Aminu K, Bennett, Derrick A, Bensenor, Isabela M, Benzian, Habib, Berhane, Adugnaw, Berhe, Abadi Kidanemariam, Berman, Adam E, Bernabe, Eduardo, Bernstein, Robert S, Bertolacci, Gregory J, Beuran, Mircea, Beyranvand, Tina, Bhala, Neeraj, Bhalla, Ashish, Bhansali, Anil, Bhattarai, Suraj, Bhaumik, Soumyadeep, Bhutta, Zulfiqar A, Biadgo, Belete, Biehl, Molly H, Bijani, Ali, Bikbov, Boris, Bililign, Nigus, Bin Sayeed, Muhammad Shahdaat, Birlik, Sait Mentes, Birungi, Charles, Bisanzio, Donal, Biswas, Tuhin, Bitew, Helen, Bizuneh, Hailemichael, Bjertness, Espen, Bobasa, Eshetu Mulisa, Boufous, Soufiane, Bourne, Rupert, Bozorgmehr, Kayvan, Bragazzi, Nicola Luigi, Brainin, Michael, Brant, Luisa C, Brauer, Michael, Brazinova, Alexandra, Breitborde, Nicholas J K, Briant, Paul Svitil, Britton, Gabrielle, Brugha, Traolach, Bukhman, Gene, Busse, Reinhard, Butt, Zahid A, Cahuana-Hurtado, Lucero, Callender, Charlton SKH, Campos-Nonato, Ismael R, Campuzano Rincon, Julio Cesar, Cano, Jorge, Car, Josip, Car, Mate, Cárdenas, Rosario, Carrero, Juan J, Carter, Austin, Carvalho, Félix, Castañeda-Orjuela, Carlos A, Castillo Rivas, Jacqueline, Castro, Franz, Causey, Kate, Çavlin, Alanur, Cercy, Kelly M, Cerin, Ester, Chaiah, Yazan, Chalek, Julian, Chang, Hsing-Yi, Chang, Jung-Chen, Chattopadhyay, Aparajita, Chattu, Vijay Kumar, Chaturvedi, Pankaj, Chiang, Peggy Pei-Chia, Chin, Ken Lee, Chisumpa, Vesper Hichilombwe, Chitheer, Abdulaal, Choi, Jee-Young J, Chowdhury, Rajiv, Christensen, Hanne, Christopher, Devasahayam J, Chung, Sheng-Chia, Cicuttini, Flavia M, Ciobanu, Liliana G, Cirillo, Massimo, Claro, Rafael M, Claßen, Thomas Khaled Dwayne, Cohen, Aaron J, Collado-Mateo, Daniel, Cooper, Cyrus, Cooper, Leslie Trumbull, Cornaby, Leslie, Cortinovis, Monica, Costa, Megan, Cousin, Ewerton, Cromwell, Elizabeth A, Crowe, Christopher Stephen, Cunningham, Matthew, Daba, Alemneh Kabeta, Dadi, Abel Fekadu, Dandona, Lalit, Dandona, Rakhi, Dang, Anh Kim, Dargan, Paul I, Daryani, Ahmad, Das, Siddharth K, Das Gupta, Rajat, das Neves, José, Dasa, Tamirat Tesfaye, Dash, Aditya Prasad, Davis, Adrian C, Davitoiu, Dragos Virgil, Davletov, Kairat, Dayama, Anand, de Courten, Barbora, De Leo, Diego, De Neve, Jan-Walter, De Steur, Hans, Degefa, Meaza Girma, Degenhardt, Louisa, Degfie, Tizta Tilahun, Deiparine, Selina, Dellavalle, Robert P, Demoz, Gebre Teklemariam, Demtsu, Balem, Denova-Gutiérrez, Edgar, Deribe, Kebede, Dervenis, Nikolaos, Dessie, Getenet Ayalew, Dey, Subhojit, Dharmaratne, Samath D, Dhimal, Meghnath, Dicker, Daniel, Dinberu, Mesfin Tadese, Ding, Eric L, Djalalinia, Shirin, Do, Huyen Phuc, Dokova, Klara, Doku, David Teye, Douwes-Schultz, Dirk, Driscoll, Tim Robert, Duan, Leilei, Dubey, Manisha, Dubljanin, Eleonora, Duken, Eyasu Ejeta, Duncan, Bruce B, Duraes, Andre R, Ebrahimpour, Soheil, Edvardsson, David, El Bcheraoui, Charbel, Eldrenkamp, Erika, El-Khatib, Ziad, Elyazar, Iqbal RF, Enayati, Ahmadali, Endries, Aman Yesuf, Eshrati, Babak, Eskandarieh, Sharareh, Esteghamati, Alireza, Esteghamati, Sadaf, Estep, Kara, Fakhar, Mahdi, Fakhim, Hamed, Fanzo, Jessica, Faramarzi, Mahbobeh, Fareed, Mohammad, Farhadi, Farzaneh, Farid, Talha A, Farinha, Carla Sofia e Sá, Farioli, Andrea, Faro, Andre, Farvid, Maryam S, Farzadfar, Farshad, Farzaei, Mohammad Hosein, Farzam, Hossein, Fazaeli, Ali Akbar, Fazeli, Mir Sohail, Feigin, Valery L, Feigl, Andrea B, Fekadu, Wubalem, Feldman, Rachel, Fentahun, Netsanet, Fereshtehnejad, Seyed-Mohammad, Fernandes, Eduarda, Fernandes, Joao C, Feyissa, Garumma Tolu, Fijabi, Daniel Obadare, Filip, Irina, Finegold, Samuel, Finger, Jonas David, Fischer, Florian, Fitzmaurice, Christina, Flor, Luisa Sorio, Foigt, Nataliya A, Foreman, Kyle J, Frank, Tahvi D, Franklin, Richard Charles, Fukumoto, Takeshi, Fukutaki, Kai, Fuller, John E, Fürst, Thomas, Furtado, João M, Gakidou, Emmanuela, Gallus, Silvano, Gankpe, Fortune Gbetoho, Gansevoort, Ron T, Garcia, Ana Cristina, Garcia-Basteiro, Alberto L, Garcia-Gordillo, Miguel A, Gardner, William M, Gebre, Abadi Kahsu, Gebre, Teshome, Gebregergs, Gebremedhin Berhe, Gebrehiwot, Tsegaye Tewelde, Gebremedhin, Amanuel Tesfay, Gebremichael, Bereket, Gebremichael, Teklu Gebrehiwo, Gelano, Tilayie Feto, Geleijnse, Johanna M, Geramo, Yilma Chisha Dea, Getachew, Sefonias, Gething, Peter W, Gezae, Kebede Embaye, Ghadami, Mohammad Rasoul, Ghadimi, Reza, Ghadiri, Keyghobad, Ghasemi-Kasman, Maryam, Ghiasvand, Hesam, Ghimire, Mamata, Ghoshal, Aloke Gopal, Giampaoli, Simona, Gill, Paramjit Singh, Gill, Tiffany K, Giussani, Giorgia, Gnedovskaya, Elena V, Goldberg, Ellen M, Goli, Srinivas, Gona, Philimon N, Goodridge, Amador, Gopalani, Sameer Vali, Gorman, Taren M, Goto, Atsushi, Goulart, Alessandra C, Goulart, Bárbara Niegia Garcia, Grada, Ayman, Griswold, Max G, Grosso, Giuseppe, Gugnani, Harish Chander C, Guillemin, Francis, Guimaraes, Andre Luiz Sena, Guo, Yuming, Gupta, Prakash C, Gupta, Rahul, Gupta, Rajeev, Gupta, Tanush, Ha, Giang Hai, Haagsma, Juanita A, Hachinski, Vladimir, Hafezi-Nejad, Nima, Haghparast Bidgoli, Hassan, Hagos, Tekleberhan B, Haile, Michael Tamene, Hailegiyorgis, Tewodros Tesfa, Hailu, Gessessew Bugssa, Haj-Mirzaian, Arvin, Haj-Mirzaian, Arya, Hamadeh, Randah R, Hamidi, Samer, Hankey, Graeme J, Harb, Hilda L, Harikrishnan, Sivadasanpillai, Haririan, Hamidreza, Haro, Josep Maria, Hasan, Mehedi, Hassankhani, Hadi, Hassen, Hamid Yimam, Havmoeller, Rasmus, Hawley, Caitlin N, Hay, Simon I, He, Yihua, Hedayatizadeh-Omran, Akbar, Hegazy, Mohamed I, Heibati, Behzad, Heidari, Behnam, Heidari, Mohsen, Hendrie, Delia, Henok, Andualem, Heredia-Pi, Ileana, Herteliu, Claudiu, Heydarpour, Behzad, Heydarpour, Fatemeh, Heydarpour, Sousan, Hibstu, Desalegn T, Híjar, Martha, Hoek, Hans W, Hoffman, Daniel J, Hole, Michael K, Homaie Rad, Enayatollah, Hoogar, Praveen, Horita, Nobuyuki, Hosgood, H Dean, Hosseini, Seyed Mostafa, Hosseinzadeh, Mehdi, Hostiuc, Mihaela, Hostiuc, Sorin, Hotez, Peter J, Hoy, Damian G, Hsairi, Mohamed, Hsiao, Thomas, Hu, Guoqing, Huang, John J, Hughes, Caitlyn, Huynh, Chantal K, Igumbor, Ehimario U, Ikeda, Chad Thomas, Ilesanmi, Olayinka Stephen, Iqbal, Usman, Irvani, Seyed Sina Naghibi, Irvine, Caleb Mackay Salpeter, Islam, Sheikh Mohammed Shariful, Islami, Farhad, Ivers, Rebecca Q, Izadi, Neda, Jacobsen, Kathryn H, Jahangiry, Leila, Jahanmehr, Nader, Jain, Sudhir Kumar, Jakovljevic, Mihajlo, Jalu, Moti Tolera, Jamal, Amr A, James, Spencer L, Jassal, Simerjot K, Javanbakht, Mehdi, Jayatilleke, Achala Upendra, Jeemon, Panniyammakal, Jha, Ravi Prakash, Jha, Vivekanand, Ji, John S, Johnson, Catherine O, Johnson, Sarah C, Jonas, Jost B, Jonnagaddala, Jitendra, Jorjoran Shushtari, Zahra, Joshi, Ankur, Jozwiak, Jacek Jerzy, Jungari, Suresh Banayya, Jürisson, Mikk, K, Madhanraj, Kabir, Zubair, Kadel, Rajendra, Kahsay, Amaha, Kahssay, Molla, Kalani, Rizwan, Kapil, Umesh, Karami, Manoochehr, Karami Matin, Behzad, Karanikolos, Marina, Karimi, Narges, Karimi, Seyed M, Karimi-Sari, Hamidreza, Kasaeian, Amir, Kassa, Dessalegn H, Kassa, Getachew Mullu, Kassa, Tesfaye Dessale, Kassa, Zemenu Yohannes, Kassebaum, Nicholas J, Katikireddi, Srinivasa Vittal, Kaul, Anil, Kawakami, Norito, Kazemi, Zhila, Karyani, Ali Kazemi, Kazi, Dhruv Satish, KC, Prakash, Kebede, Seifu, Keiyoro, Peter Njenga, Kemmer, Laura, Kemp, Grant Rodgers, Kengne, Andre Pascal, Keren, Andre, Kesavachandran, Chandrasekharan Nair, Khader, Yousef Saleh, Khafaei, Behzad, Khafaie, Morteza Abdullatif, Khajavi, Alireza, Khalid, Nauman, Khalil, Ibrahim A, Khan, Ejaz Ahmad, Khan, Muhammad Shahzeb, Khan, Muhammad Ali, Khang, Young-Ho, Khanna, Tripti, Khater, Mona M, Khatony, Alireza, Khazaeipour, Zahra, Khazaie, Habibolah, Khoja, Abdullah T, Khosravi, Ardeshir, Khosravi, Mohammad Hossein, Khubchandani, Jagdish, Kiadaliri, Aliasghar A, Kiarie, Helen W, Kibret, Getiye D, Kiirithio, Daniel N, Kim, Daniel, Kim, Jun Y, Kim, Young-Eun, Kim, Yun Jin, Kimokoti, Ruth W, Kinfu, Yohannes, Kinra, Sanjay, Kisa, Adnan, Kissimova-Skarbek, Katarzyna, Kissoon, Niranjan, Kivimäki, Mika, Kocarnik, Jonathan M, Kochhar, Sonali, Kokubo, Yoshihiro, Kolola, Tufa, Kopec, Jacek A, Kosek, Margaret N, Kosen, Soewarta, Koul, Parvaiz A, Koyanagi, Ai, Kravchenko, Michael A, Krishan, Kewal, Krohn, Kristopher J, Kuate Defo, Barthelemy, Kucuk Bicer, Burcu, Kudom, Andreas A, Kulikoff, Xie Rachel, Kumar, G Anil, Kumar, Manasi, Kumar, Pushpendra, Kutz, Michael J, Kyu, Hmwe Hmwe, Lachat, Carl, Lad, Deepesh P, Lad, Sheetal D, Lafranconi, Alessandra, Lagat, Abraham K, Lal, Dharmesh Kumar, Lalloo, Ratilal, Lam, Hilton, Lami, Faris Hasan, Lamichhane, Prabhat, Lan, Qing, Lang, Justin J, Lansingh, Van C, Lansky, Sonia, Larson, Heidi J, Larsson, Anders O, Laryea, Dennis Odai, Lassi, Zohra S, Latifi, Arman, Lau, Kathryn Mei-Ming, Laxmaiah, Avula, Lazarus, Jeffrey V, Leasher, Janet L, Lebedev, Georgy, Ledesma, Jorge R, Lee, James B, Lee, Paul H, Leever, Andrew T, Leigh, James, Leinsalu, Mall, Leshargie, Cheru Tesema, Leung, Janni, Lewycka, Sonia, Li, Shanshan, Li, Xiaohong, Li, Yichong, Liang, Juan, Liang, Xiaofeng, Liben, Misgan Legesse, Lim, Lee-Ling, Limenih, Miteku Andualem, Linn, Shai, Liu, Shiwei, Liu, Yang, Lodha, Rakesh, Logroscino, Giancarlo, Lopez, Alan D, Lorkowski, Stefan, Lotufo, Paulo A, Lucchesi, Lydia R, Lyons, Ronan A, Macarayan, Erlyn Rachelle King, Mackay, Mark T, Maddison, Emilie R, Madotto, Fabiana, Maghavani, Dhaval P, Magis-Rodriguez, Carlos, Mahotra, Narayan Bahadur, Majdan, Marek, Majdzadeh, Reza, Majeed, Azeem, Malekzadeh, Reza, Malta, Deborah Carvalho, Mamun, Abdullah A, Manda, Ana-Laura, Mandarano-Filho, Luiz Garcia, Mangalam, Srikanth, Manguerra, Helena, Mansournia, Mohammad Ali, Mapoma, Chabila Christopher, Maravilla, Joemer C, Marcenes, Wagner, Marks, Ashley, Martin, Randall V, Martins, Sheila C O, Martins-Melo, Francisco Rogerlândio, Martopullo, Ira, Mashamba-Thompson, Tivani Phosa, Massenburg, Benjamin Ballard, Mathur, Manu Raj, Maulik, Pallab K, Mazidi, Mohsen, McAlinden, Colm, McGrath, John J, McKee, Martin, McMahon, Brian J, Mehata, Suresh, Mehndiratta, Man Mohan, Mehrotra, Ravi, Mehta, Kala M, Mehta, Varshil, Mejia-Rodriguez, Fabiola, Mekonen, Tesfa, Mekonnen, Tefera C Chane, Meles, Hagazi Gebre, Melese, Addisu, Melku, Mulugeta, Memiah, Peter T N, Memish, Ziad A, Mendoza, Walter, Mengistu, Desalegn Tadese, Mengistu, Getnet, Mensah, George A, Mensink, Gert B M, Mereta, Seid Tiku, Meretoja, Atte, Meretoja, Tuomo J, Mestrovic, Tomislav, Mezgebe, Haftay Berhane, Miazgowski, Bartosz, Miazgowski, Tomasz, Millear, Anoushka I, Miller, Ted R, Miller-Petrie, Molly Katherine, Milne, George J, Mini, G K, Minnig, Shawn P, Mirabi, Parvaneh, Mirarefin, Mojde, Mirrakhimov, Erkin M, Misganaw, Awoke Temesgen, Mitchell, Philip B, Moazen, Babak, Moghadamnia, Ali Akbar, Mohajer, Bahram, Mohammad, Karzan Abdulmuhsin, Mohammadi, Moslem, Mohammadifard, Noushin, Mohammadnia-Afrouzi, Mousa, Mohammed, Mohammed A, Mohammed, Shafiu, Mohan, Murali B V, Mohan, Viswanathan, Mohebi, Farnam, Moitra, Modhurima, Mokdad, Ali H, Molokhia, Mariam, Monasta, Lorenzo, Montañez, Julio Cesar, Moosazadeh, Mahmood, Moradi, Ghobad, Moradi, Mahmoudreza, Moradi-Lakeh, Maziar, Moradinazar, Mehdi, Moraga, Paula, Morawska, Lidia, Morgado-da-Costa, Joana, Morisaki, Naho, Morrison, Shane Douglas, Mosapour, Abbas, Moschos, Marilita M, Mountjoy-Venning, W Cliff, Mouodi, Simin, Mousavi, Seyyed Meysam, Muche, Achenef Asmamaw, Muchie, Kindie Fentahun, Mueller, Ulrich Otto, Muhammed, Oumer Sada S, Mukhopadhyay, Satinath, Mullany, Erin C, Muller, Kate, Mumford, John Everett, Murhekar, Manoj, Murthy, G V S, Murthy, Srinivas, Musa, Jonah, Musa, Kamarul Imran, Mustafa, Ghulam, Muthupandian, Saravanan, Nabhan, Ashraf F, Nachega, Jean B, Nagarajan, Ahamarshan Jayaraman, Nagel, Gabriele, Naghavi, Mohsen, Naheed, Aliya, Nahvijou, Azin, Naidoo, Kovin, Naik, Gurudatta, Naik, Nitish, Najafi, Farid, Naldi, Luigi, Nam, Hae Sung, Nangia, Vinay, Nansseu, Jobert Richie, Nascimento, Bruno Ramos, Nawaz, Haseeb, Neamati, Nahid, Negoi, Ionut, Negoi, Ruxandra Irina, Neupane, Subas, Newton, Charles Richard James, Ngalesoni, Frida N, Ngunjiri, Josephine W, Nguyen, Anh, Nguyen, Grant, Nguyen, Ha, Nguyen, Huong Lan Thi, Nguyen, Huong Thanh, Nguyen, Minh, Nichols, Emma, Nigatu, Solomon Gedlu, Ningrum, Dina Nur Anggraini, Nirayo, Yirga Legesse, Nisar, Muhammad Imran, Nixon, Molly R, Nolutshungu, Nomonde, Nomura, Marika, Norheim, Ole F, Noroozi, Mehdi, Norrving, Bo, Noubiap, Jean Jacques, Nouri, Hamid Reza, Nourollahpour Shiadeh, Malihe, Nowroozi, Mohammad Reza, Nyasulu, Peter S, Obermeyer, Carla Makhlouf, Ofori-Asenso, Richard, Ogah, Okechukwu Samuel, Ogbo, Felix Akpojene, Oh, In-Hwan, Okoro, Anselm, Oladimeji, Kelechi E, Oladimeji, Olanrewaju, Olagunju, Andrew T, Olagunju, Tinuke O, Olivares, Pedro R, Olsen, Helen Elizabeth, Olusanya, Bolajoko Olubukunola, Olusanya, Jacob Olusegun, Ong, Kanyin L, Ong, Sok King, Oommen, Anu Mary, Opio, John Nelson, Oren, Eyal, Oros, Andrei, Ortega-Altamirano, Doris D V, Ortiz, Alberto, Ortiz, Justin R, Ortiz-Panozo, Eduardo, Ota, Erika, Otstavnov, Stanislav S, Owolabi, Mayowa Ojo, P A, Mahesh, Pakhale, Smita, Pakhare, Abhijit P, Pan, Wen-Harn, Pana, Adrian, Panda, Basant Kumar, Panda-Jonas, Songhomitra, Pandian, Jeyaraj Durai, Papantoniou, Nikolaos, Park, Eun-Kee, Parry, Charles D H, Parsian, Hadi, Patel, Shanti, Pati, Sanghamitra, Patle, Ajay, Patton, George C, Paturi, Vishnupriya Rao, Paudel, Deepak, Paulson, Katherine R, Pearce, Neil, Peprah, Emmanuel K, Pereira, David M, Perico, Norberto, Pervaiz, Aslam, Pesudovs, Konrad, Petri, William A, Petzold, Max, Phillips, Michael R, Pigott, David M, Pillay, Julian David, Pirsaheb, Meghdad, Pletcher, Martin, Pond, Constance Dimity, Postma, Maarten J, Pourshams, Akram, Poustchi, Hossein, Prabhakaran, Dorairaj, Prakash, Swayam, Prasad, Narayan, Purcell, Caroline A, Pyakurel, Manita, Qorbani, Mostafa, Quansah, Reginald, Radfar, Amir, Rafay, Anwar, Rafiei, Alireza, Rahim, Fakher, Rahimi, Kazem, Rahimi-Movaghar, Afarin, Rahimi-Movaghar, Vafa, Rahman, Mahfuzar, Rahman, Md Shafiur, Rahman, Mohammad Hifz Ur, Rahman, Muhammad Aziz, Rahman, Sajjad ur, Rai, Rajesh Kumar, Rajati, Fatemeh, Rajsic, Sasa, Ram, Usha, Rana, Saleem M, Ranabhat, Chhabi Lal, Ranjan, Prabhat, Rasella, Davide, Rawaf, David Laith, Rawaf, Salman, Razo-García, Christian, Reddy, K Srinath, Reiner, Robert C, Reis, Cesar, Reitsma, Marissa B, Remuzzi, Giuseppe, Renzaho, Andre M N, Resnikoff, Serge, Reynales-Shigematsu, Luz Myriam, Rezaei, Satar, Rezaeian, Shahab, Rezai, Mohammad Sadegh, Riahi, Seyed Mohammad, Ribeiro, Antonio Luiz P, Rios-Blancas, Maria Jesus, Roba, Kedir Teji, Roberts, Nicholas L S, Roever, Leonardo, Ronfani, Luca, Roshandel, Gholamreza, Rostami, Ali, Roth, Gregory A, Roy, Ambuj, Rubagotti, Enrico, Ruhago, George Mugambage, Sabde, Yogesh Damodar, Sachdev, Perminder S, Saddik, Basema, Sadeghi, Ehsan, Safari, 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Subjects
GENDER-DIFFERENCES, SUICIDE, Medicine (all), Burden of Disease Study 2017, SDG, CONSUMPTION, 11 Medical And Health Sciences, GBD, Sustainable Development Goals, PREVENTION, ALCOHOL-USE, CARDIOVASCULAR-DISEASE, SMOKING PREVALENCE, General & Internal Medicine, factors risk, Medicine and Health Sciences, Human medicine, CESSATION, PERSPECTIVE, TRANSITION
Abstract

Background Efforts to establish the 2015 baseline and monitor early implementation of the UN Sustainable Development Goals (SDGs) highlight both great potential for and threats to improving health by 2030. To fully deliver on the SDG aim of "leaving no one behind", it is increasingly important to examine the health-related SDGs beyond national-level estimates. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017), we measured progress on 41 of 52 health -related SDG indicators and estimated the health-related SDG index for 195 countries and territories for the period 1990-2017, projected indicators to 2030, and analysed global attainment. Methods We measured progress on 41 health-related S DG indicators from 1990 to 2017, an increase of four indicators since GBD 2016 (new indicators were health worker density, sexual violence by non-intimate partners, population census status, and prevalence of physical and sexual violence [reported separately]). We also improved the measurement of several previously reported indicators. We constructed national-level estimates and, for a subset of health-related SDGs, examined indicator-level differences by sex and Socio-demographic Index (SDI) quintile. We also did subnational assessments of performance for selected countries. To construct the health related SDG index, we transformed the value for each indicator on a scale of 0-100, with 0 as the 2.5th percentile and 100 as the 97.5th percentile of 1000 draws calculated from 1990 to 2030, and took the geometric mean of the scaled indicators by target. To generate projections through 2030, we used a forecasting framework that drew estimates from the broader GBD study and used weighted averages of indicator-specific and country-specific annualised rates of change from 1990 to 2017 to inform future estimates. We assessed attainment of indicators with defined targets in two ways: first, using mean values projected for 2030, and then using the probability of attainment in 2030 calculated from 1000 draws. We also did a global attainment analysis of the feasibility of attaining SDG targets on the basis of past trends. Using 2015 global averages of indicators with defined SDG targets, we calculated the global annualised rates of change required from 2015 to 2030 to meet these targets, and then identified in what percentiles the required global annualised rates of change fell in the distribution of country-level rates of change from 1990 to 2015. We took the mean of these global percentile values across indicators and applied the past rate of change at this mean global percentile to all health-related SDG indicators, irrespective of target definition, to estimate the equivalent 2030 global average value and percentage change from 2015 to 2030 for each indicator. Findings The global median health-related SDG index in 2017 was 59.4 (IQR 35.4-67.3), ranging from a low of 11.6 (95% uncertainty interval 9.6-14.0) to a high of 84.9 (83.1-86.7). SDG index values in countries assessed at the subnational level varied substantially particularly in China and India, although scores in Japan and the UK were more homogeneous. Indicators also varied by SDI quintile and sex, with males having worse outcomes than females for non-communicable disease (NCD) mortality, alcohol use, and smoking, among others. Most countries were projected to have a higher health-related SDG index in 2030 than in 2017, while country-level probabilities of attainment by 2030 varied widely by indicator. Under-5 mortality, neonatal mortality, maternal mortality ratio, and malaria indicators had the most countries with at least 95% probability of target attainment. Other indicators, including NCD mortality and suicide mortality, had no countries projected to meet corresponding SDG targets on the basis of projected mean values for 2030 but showed some probability of attaimnent by 2030. For some indicators, including child malnutrition, several infectious diseases, and most violence measures, the annualised rates of change required to meet SDG targets far exceeded the pace of progress achieved by any country in the recent past. We found that applying the mean global annualised rate of change to indicators without defined targets would equate to about 19% and 22% reductions in global smoking and alcohol consumption, respectively; a 47% decline in adolescent birth rates; and a more than 85% increase in health worker density per 1000 population by 2030. Interpretation The GBD study offers a unique, robust platform for monitoring the health -related SDGs across demographic and geographic dimensions. Our findings underscore the importance of increased collection and analysis of disaggregated data and highlight where more deliberate design or targeting of interventions could accelerate progress in attaining the SDGs. Current projections show that many health -related SDG indicators, NCDs, NCD-related risks, and violence -related indicators will require a concerted shift away from what might have driven past gains curative interventions in the case of NCDs towards multisectoral, prevention -oriented policy action and investments to achieve SDG aims. Notably, several targets, if they are to be met by 2030, demand a pace of progress that no country has achieved in the recent past. The future is fundamentally uncertain, and no model can fully predict what breakthroughs or events might alter the course of the S DGs. What is clear is that our actions or inaction today will ultimately dictate how close the world, collectively, can get to leaving no one behind by 2030. Copyright (C) 2018 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.

Published
2018

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